检索结果-内蒙古大学图书馆

The Development of Solar-Powered Gas Metering Units Equipped with Radio or 3G Based Telemetry Systems

IOP Conference Series: Materials science and Engineering 2020年第1期791卷

作者： M A Velichko Yu P Gladkikh I B Kostina Department of Computer Science Natural Sciences and Teaching Methods Belgorod State National Research University Pobeda St. Belgorod 85 308015 Russia

In this article we have described the development of solar-powered gas metering units including modern ultrasonic and vortex flowmeters for volume and mass measurement of natural gas, associated petroleum gases, inert gases, oxygen, hydrogen, air, nitrogen, carbon dioxide and any other single and multicomponent gases that are not aggressive to the flowmeter materials. We have shown implementation of such units in the existing gas producing stations in the desert of Kara-Kum. Confirmed was the ability of our gas metering units to operate more than a year without network power supply and staff intervention. Also pictured was creation of telemetry system for collecting and transmitting metrological information, including gas flow rate, temperature, pressure, humidity to the central terminal. Different physical layers have been used to transfer data from the metering units, including radio channels at 433 MHz frequency between units and central station. This telemetry system implemented selfmaintenance and self-monitoring features, facilitating remote control of metering unit, so important in rigid conditions of solar-rich deserts and semi-deserts.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A survey on studying the social networks of students

arXiv

引用

arXiv 2019年

作者： Saxena, Akrati Saxena, Pratishtha Reddy, Harita Gera, Ralucca Department of Computer Science School of Computing National University of Singapore Singapore Singapore Department of Computer Science and Engineering Center for Advanced Studies Lucknow India Department of Computer Science and Engineering National Institute of Technology Karnataka India Department of Applied Mathematics Associate Provost for Graduate Education Teaching and Learning Commons Naval Postgraduate School MontereyCA United States

Do studies show that physical and online students’ social networks support education? Analyzing interactions between students in schools and universities can provide a wealth of information. Studies on students’ social networks can help us understand their behavioral dynamics, the correlation between their friendships and academic performance, community and group formation, information diffusion, and so on. Educational goals and holistic development of students with various academic abilities and backgrounds can be achieved by incorporating the findings attained by the studies in terms of knowledge propagation in classroom and spread of delinquent behaviors. Moreover, we use Social Network Analysis (SNA) to identify isolated students, ascertain the group study culture, analyze the spreading of various habits like smoking, drinking, and so on. In this paper, we present a review of the research showing how analysis of students’ social networks can help us identify how improved educational methods can be used to make learning more inclusive at both school and university levels and achieve holistic development of students through expansion of their social networks, as well as control the spread of delinquent behaviors. Copyright © 2019, The Authors. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Learning to match jobs with resumes from sparse interaction data using multi-view co-teaching network

arXiv

引用

arXiv 2020年

作者： Bian, Shuqing Chen, Xu Zhao, Wayne Xin Zhou, Kun Hou, Yupeng Song, Yang Zhang, Tao Wen, Ji-Rong School of Information Renmin University of China China Gaoling School of Artificial Intelligence Renmin University of China China Beijing Key Laboratory of Big Data Management and Analysis Methods China Department of Computer Science University College London United Kingdom BOSS Zhipin NLP Center China

With the ever-increasing growth of online recruitment data, job-resume matching has become an important task to automatically match jobs with suitable resumes. This task is typically casted as a supervised text matching problem. Supervised learning is powerful when the labeled data is sufficient. However, on online recruitment platforms, job-resume interaction data is sparse and noisy, which affects the performance of job-resume match algorithms. To alleviate these problems, in this paper, we propose a novel multi-view co-teaching network from sparse interaction data for job-resume matching. Our network consists of two major components, namely text-based matching model and relation-based matching model. The two parts capture semantic compatibility in two different views, and complement each other. In order to address the challenges from sparse and noisy data, we design two specific strategies to combine the two components. First, two components share the learned parameters or representations, so that the original representations of each component can be enhanced. More importantly, we adopt a co-teaching mechanism to reduce the influence of noise in training data. The core idea is to let the two components help each other by selecting more reliable training instances. The two strategies focus on representation enhancement and data enhancement, respectively. Compared with pure text-based matching models, the proposed approach is able to learn better data representations from limited or even sparse interaction data, which is more resistible to noise in training data. Experiment results have demonstrated that our model is able to outperform state-of-the-art methods for job-resume matching. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Region-tree Based Sorted List Indexing for Real-time Entity Resolution in n-Dimensional Data Space 2

Region-tree Based Sorted List Indexing for Real-time Entity ...

引用

2018 2nd Annual International Conference on Cloud Technology and Communication Engineering, CTCE 2018

作者： Zhu, Liang Lu, Weipeng Ma, Qin Meng, Weiyi School of Cyber Security and Computer Science Hebei University China Department of Foreign Language Teaching and Research Hebei University China Department of Computer Science State University of New York at Binghamton United States

Entity resolution (ER) is the process of identifying which tuples/records in a dataset refer to the same real-world entity. In this paper, we primarily focus on the deduplication task for n-dimensional datasets that contain real vectors with the dimensionality 2 ≤ n ≤ 784. By presenting an algorithm with complete and disjoint space partitioning, the ER-Index with a region-tree and sorted lists will be created by a sample set of a (dirty) dataset. We utilize primary horizontal fragmentation to partition a dataset into a set of fragments, and then resolve the fragments one by one applying the ER-Index and algorithms. Extensive experiments are conducted to demonstrate the performances of our proposed approaches. © Published under licence by IOP Publishing Ltd.

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Argumentative Link Prediction using Residual Networks and Multi-Objective Learning 5

Argumentative Link Prediction using Residual Networks and Mu...

引用

5th Workshop on Argument Mining, co-located with EMNLP 2018

作者： Galassi, Andrea Lippi, Marco Torroni, Paolo Department of Computer Science and Engineering DISI University of Bologna Italy Department of Sciences and Methods for Engineering University of Modena Reggio Emilia Italy

ISBN: (纸本)9781948087698

We explore the use of residual networks for argumentation mining, with an emphasis on link prediction. The method we propose makes no assumptions on document or argument structure. We evaluate it on a challenging dataset consisting of user-generated comments collected from an online platform. Results show that our model outperforms an equivalent deep network and offers results comparable with state-of-the-art methods that rely on domain knowledge. © 2018 Association for Computational Linguistics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Supplemental educational program to heighten the impact of research - an opportunity for OA imaging

引用

Osteoarthritis imaging 2023年第2期3卷 100155页

作者： Deborah Burstein Rudolph Mitchell Emery Brown Martha L Gray Associate Professor Department of Radiology Beth Israel Deaconess Medical Center Harvard Medical School 330 Brookline Avenue Boston MA USA. Associate Director for Research and Evaluation in the Teaching + Learning Lab Massachusetts Institute of Technology Cambridge MA USA. Edward Hood Taplin Professor of Computational Neuroscience and Health Sciences and Technology Department of Brain and Cognitive Sciences and Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge MA USA. J.W. Kieckefer Professor of Medical and Electrical Engineering Department of Electrical Engineering and Computer Science and Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge MA USA.

Objective:To develop and evaluate a supplementary educational program ("IMPACT") centered on enabling participants to consider specifically and articulate explicitly the best path for and potential impact of their research. Design:Participants (trainees) and faculty mentors were from all areas of biomedical research. The group worked longitudinally in small, rotating groups, through a process of developing a written statement ("Impact Statement"), an overview ("Impact Storyline") and an oral presentation ("Impact Case") of their work. Results:One hundred and eighty-seven Fellows enrolled in the program. Of the 179 (96%) Fellows who completed the program, 159 (89%) responded to a post-program survey; 94% indicated that IMPACT was a significant learning experience, 89% indicated that they were more able to identify the long-term potential of their research, 95% felt more able to talk about their work to diverse audiences. Conclusion:This voluntary educational program was appreciated by the participants and led to increased confidence in their ability to drive their science towards a clear impact and communicating that potential to others. This type of program may aid in redirecting some of the efforts and resources of imaging in OA from the large focus on technical developments to more direct biological and clinical questions which might be resolved with current technology.

关键词： Communication Diversity Impact Research

来源：评论

学校读者我要写书评

暂无评论

Findings from the Tushirikiane-4-MH (Supporting Each Other for Mental Health) Mobile Health-Supported Virtual Reality Randomized Controlled Trial Among Urban Refugee Youth in Kampala, Uganda

引用

Global Mental Health 2025年 12卷 e12-e12页

作者： Logie, Carmen H. Okumu, Moses Admassu, Zerihun MacKenzie, Frannie Gittings, Lesley Kortenaar, Jean-Luc Khan, Naimul Hakiza, Robert Musoke, Daniel Kibuuka Nakitende, Aidah Katisi, Brenda Kyambadde, Peter Lester, Richard Mbuagbaw, Lawrence Factor-Inwentash Faculty of Social Work University of Toronto Toronto ON Canada Women's College Research Institute Women's College Hospital Toronto ON Canada United Nations University Institute for Water Environment & Health Hamilton ON Canada Centre for Gender and Sexuality Health Equity Vancouver BC Canada School of Social Work University of Illinois Urbana-Champaign United States Uganda Christian University Mukono Uganda School of Health Studies Western University London ON Canada Centre for Social Science Research University of Cape Town South Africa Dalla Lana School of Public Health University of Toronto Toronto ON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada Young African Refugees for Integral Development (YARID) Kampala Uganda International Research Consortium Kampala Uganda National AIDS and STI Control Programme Ministry of Health Kampala Uganda Most At Risk Population Initiative Mulago Hospital Kampala Uganda Department of Medicine University of British Columbia Vancouver BC Canada Department of Health Research Methods Evidence and Impact McMaster University Hamilton ON Canada Department of Anesthesia McMaster University Hamilton ON Canada

Background: Virtual reality (VR) for mental health promotion remains understudied in low income humanitarian settings. We examined the effectiveness of VR in reducing depression with urban refugee youth in Kampala, Uganda. methods: This randomized controlled trial assessed VR alone (Arm 1), VR followed by group problem management plus (GPM+) (Arm 2), and a control group (Arm 3), with a peer-driven and convenience sample of refugee youth aged 16-25 in Kampala. The primary outcome, depression, was measured with the Patient Health Questionnaire-9. Secondary outcomes included: mental health literacy, mental health stigma, self-compassion, mental wellbeing, and adaptive coping. Analyses were conducted at three timepoints (baseline, 8-weeks, 16-weeks) using generalized estimating equations (GEE). Results: Among participants (n=335, mean age: 20.77, standard deviation: 3.01;cisgender women: n=158, cisgender men: n=173, transgender women: n=4) we found no depression reductions for Arms 1 or 2 at 16-weeks compared with Arm 3. At 16-weeks, mental health literacy was significantly higher for Arm 2 compared with Arm 3, and self compassion was significantly higher in Arms 1 and Arm 2 compared with Arm 3. Discussion: VR alongside GPM+ may benefit self-compassion and MHL among urban refugee youth in Kampala, but these interventions were not effective in reducing depression. © The Author(s), 2025. Published by Cambridge University Press.

关键词： depression refugees self-compassion Uganda virtual reality youth

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence in the NHS: Moving from ideation to implementation

引用

Future healthcare journal 2024年第3期11卷 100183页

作者： Anmol Arora Tom Lawton School of Clinical Medicine University of Cambridge Cambridge CB2 0SP UK. Department of Oncology University College London London WC1E 6DD UK. Department of Computer Science University of York York YO10 5GH UK. Improvement Academy Bradford Teaching Hospitals NHS Foundation Trust Bradford BD9 6RJ UK.

来源：评论

学校读者我要写书评

暂无评论

Identification of the football teams assessment model using the COMET method

引用

Procedia computer science 2019年 159卷 2491-2501页

作者： Krzysztof Palczewski Wojciech Sałabun Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

Many people, organizations and managers try to assess the performance of the football teams and seek new improved approaches. Rankings are an unavoidable part of the football world, where high competitiveness and efficiency is a natural factor. One of the techniques to deal with such problems is the use of multi-criteria decision-analysis methods (MCDA), offering an effective approach to not only ranking but also assessing, selecting and sorting given alternatives. In this paper, the Characteristic Objects METhod (COMET) is used in order to create a performance ranking of the top-tier football clubs. The assessment model is identified and compared with the existing benchmark ranking by the Spearman’s rank correlation coefficient.

关键词： COMET Characteristic Objects Method football ranking MCDA multi-criteria decision-analysis

来源：评论

学校读者我要写书评

暂无评论

Ccdh: Complexity Based Causal Discovery of Hidden Common Cause (and Other Beasts) in Time Series

SSRN

引用

SSRN 2022年

作者： Varga, Bálint Stippinger, Marcell Benkő, Zsigmond Fabó, Dániel Halász, Péter Erőss, Loránd Somogyvári, Zoltán Telcs, András Department of Computational Sciences Wigner Research Centre for Physics BudapestH-1121 Hungary János Szentágothai Doctoral School of Neurosciences Semmelweis University BudapestH-1085 Hungary Epilepsy Center Juhász Pál National Institute of Clinical Neurosciences BudapestH-1145 Hungary EPI-HELP BudapestH-1012 Hungary Department of Functional Neurosurgery National Institute of Clinical Neurosciences BudapestH-1145 Hungary Faculty of Information Technology and Bionics Péter Pázmány Catholic University BudapestH-1083 Hungary Neuromicrosystems ltd. BudapestH-1113 Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics BudapestH-1111 Hungary Department of Quantitative Methods University of Pannonia Faculty of Business and Economics VeszprémH-8200 Hungary

Non-interventional causal discovery is a challenging task. This is particularly true for causal relations of dynamic systems with chaotic attractors. The known solutions are data-intensive and cannot detect a hidden common driver (common cause or confounder). We propose a new method which eliminates both *** method is based on Takens' embedding theorem and complexity of the rank order patterns of the embedded series measured by the compressibility usingnon-sequential recursive pair substitution. The method works on shortsamples and is capable of detecting all kinds of causal connection (including hidden common cause). The newmethod is validated on synthetic data sets and applied to two types of humanelectrophysiological data from epileptic patients. In bothcases, the method revealed self-consistent, contradiction-free and biologically relevant causal connections between the investigatedareas. Thus the method may provide additional indication for the location ofintervention for the decision making medical panel. Given the method advantages and simplicity it might be applied in many other scientific and practical areas with success. © 2022, The Authors. All rights reserved.

关键词： Time series

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：