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2015 International Conference on Circuits and Systems(CAS 2015)

作者： Edson Mota Daniela Costa Paulo Caetano da Silva Masters program in Systems and Computer Science Salvador University (UNIFACS)

The practice of disclosure of information on corporate sustainability represents a breakthrough in relations between business and society. The initiative of the Global Reporting Initiative(GRI) in the adoption of XBRL in the process of dissemination of sustainability reporting contributes to the increase of their quality;however, the great heterogeneity of enterprise information systems still pose an obstacle to their use in the corporative scenario. This article presents a conceptual model for the adoption of a serviceoriented architecture for issuing reports based on XBRL taxonomy proposed by GRI in supporting the processes of disclosure of sustainability information.

关键词： disclosure sustainability global reporting initiative SOA XBRL

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Generating Activity Streams from Events occurring in company-internal IT infrastructures

Generating Activity Streams from Events occurring in company...

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2011 IEEE 13th International Conference on Communication Technology(ICCT 2011)

作者： Eng.S.M.Khaled Reza S.M.Mohsin Reza Masters Program in Computational Engineering (Distributed Systems Engineering) Faculty of Computer Science Dresden University of Technology Dresden Germany Masters Program in Information Technology (Embedded Systems Engineering) Faculty of Computer Science Electrical Engineering and Information Technology University of Stuttgart Germany

In the current era of technology,the Internet and web technologies become the center source of *** to the huge amount of contents,one of the main challenges of modern information technology is aimed at how to reduce and manage information in a structured way with mobilizing users to the similar kind of relevant ***,any intelligent system should be able to understand people's interest about a particular type of information and automatically mobilize him to the similar kind of available information *** idea of high level Activity Streams along with its standardized format can play a vital role to solve this problem in the broader *** paper introduces a novel system called CoASGen (Consolidation and Activity Streams Generator) which is able to automatically generate high level Activity Streams after aggregating and consolidating from different independent systems (*** a software company context:version management system,wikis,bug trackers etc.).It retrieves life time information as heterogeneous web feed by sensing user activities from those independent systems and then it transforms several similar types of atomic activities into high level Activity Streams using semantic technologies along with its specific standardized ***,it shows these high level Activity Streams to the user interface which is able to automatically motivate users to find relevant information easily without either missing any data or losing valuable *** system solves the problem "data silos" by reducing and managing information in a structured way.

关键词： Activity Streams,Atomic Activity,High Level Activity Stream,CoASGen System

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A handle electrode system for measuring heart rate while riding a bicycle

A handle electrode system for measuring heart rate while rid...

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

作者： Masutaka Watanabe Sosuke Tsukamoto Hiroshi Hoshino Masters Program in Electronic and Computer Engineering Graduate School of Science and Engineering Tokyo Denki University Hiki Saitama Japan School of Science and Engineering Tokyo Denki University Hiki Saitama Japan

In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle. Three electrodes made from conductive cloth were adhered to the handle. A method detecting heart-rate from the obtained electrocardiogram was also proposed. To assess the applicability of the proposed system, a simple experiment was performed. The experiment was performed in four conditions of road surfaces; lawn, asphalt, a tiled, and an uneven road. Experimental result suggests that the proposed system can be useful for obtaining R waves while riding a bicycle.

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Two-dimensional location and direction estimating method

Two-dimensional location and direction estimating method

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

作者： Teruhiro Haga Sosuke Tsukamoto Hiroshi Hoshino Masters Program in Electronic and Computer Engineering Graduate School of Science and Engineering Tokyo Denki University Hiki Saitama Japan School of Science and Engineering Tokyo Denki University Hiki Saitama Japan

In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna. As a prototype system, a measurement stage (a circle 240mm in diameter) with 36 antennas that placed in each 10 degrees was developed. Two transmitter antennas are settled in a right angle on the stage as the target object, and the position and the rotation angle is estimated by measuring efficiency of the radio communication of each 36 antennas. The experimental result revealed that even when the estimated location is not so accurate (about a 30 mm error), the rotation angle is accurately estimated (about 2.33 degree error on average). The result suggests that the proposed method will be useful for estimating the location and the direction of an object.

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Localization of mobile robot by matching three-dimensional data of SOKUIKI sensor and aerial imagery

Localization of mobile robot by matching three-dimensional d...

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IEEE/SICE International Symposium on System Integration

作者： Kohei Ito Keisuke Yokota Akihisa Ohya Department of Mechanical Engineering Kanazawa Technical College Ishikawa Japan Masters Program in Computer Science University of Tsukuba Ibaraki Japan Division of Information Engineering University of Tsukuba Ibaraki Japan

In recent years, the demand for autonomous mobile robots in outdoors environments has been increasing. In order to guide the robot, it is essential to get the current position. In this study, we propose a method to correct the self-position of the robot, which is estimated by odometry, aerial imagery, and the SOKUIKI sensor. First, we explore how to superimpose the reflection point cloud on top of the aerial imagery. Next, matching the edge data of aerial imagery and the upper edge of the building from the inclined reflection point cloud corrects the self-correction of the robot, by which the robot is able to run on the straight road for about 60m autonomously.

关键词： Robot sensing systems Image edge detection Mobile robots Buildings Educational institutions Equations

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From market baskets to mole rats: Using data mining techniques to analyze RFID data describing mole rat behavior 11

From market baskets to mole rats: Using data mining techniqu...

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17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2011

作者： McCloskey, Dan P. Kress, Michael E. Imberman, Susan P. Kushnir, Igor Briffa-Mirabella, Susan Dept. Psychology College of Staten Island 2800 Victory Blvd Staten Island NY 10314 United States CSI/IBR Center for Developmental Neuroscience College of Staten Island 2800 Victory Blvd Staten Island NY 10314 United States College of Staten Island Department of Technology Systems 2800 Victory Blvd Staten Island NY 10314 United States College of Staten Island Dept. Computer Science 2800 Victory Blvd Staten Island NY 10314 United States College of Staten Island Masters Program In Neuroscience 2800 Victory Blvd Staten Island NY 10314 United States Program in Neuroscience Department of Biology Graduate Center at CUNY 2800 Victory Blvd Staten Island NY 10314 United States Program Computer Science Graduate Center at CUNY College of Staten Island 2800 Victory Blvd Staten Island NY 10314 United States

ISBN: (纸本)9781450308137

The use of new technologies, such as RFID sensors, provides scientists with novel ways of doing experimental research. As scientists become more technologically savvy and use these techniques, the traditional approaches to data analysis fail given the huge amounts of data produced by these methods. In this paper we describe an experiment in which colonies of naked mole rats were tagged with RFID transponders. RFID sensors were strategically placed in the mole rat caging system. The goal of this experiment was to document and analyze the interactions between animals. The huge amount of data produced by the sensors was not analyzable using the traditional methods employed by behavioral neuroscience researchers. Computational methods used by data miners, such as cluster analysis, association rule mining, and graphical models, were able to scale to the data and produce knowledge and insight that was previously unknown. This paper describes in detail the experimental setup and the computational methods used. Copyright 2011 ACM.

关键词： Cluster analysis

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Human API as a research source in health care

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Ethnographic Praxis in Industry Conference Proceedings 2014年第1期2013卷 266-281页

作者： KNOWL BAEK KYLE DUKE ROY LUO MONICA LEE ANIJO MATHEW is enrolled in the masters program at IIT Institute of Design where she merges ethnographic research design thinking and business strategy to solve complex real world problems. is a graduate of the IIT Institute of Design where he leveraged a combination of ethnographic research and business strategy to assist clients such as Hyatt Hotels Corporation Godrej & Boyce and the Bill & Melinda Gates Foundation in their efforts to develop new innovative offerings. has a background in computer science and is enrolled in the masters program at IIT Institute of Design. is a graduate of the IIT Institute of Design where she focused her studies on user experience design strategy and interaction design. is an Assistant Professor at IIT Institute of Design.

This paper illustrates how the concept of “Human API” can help cancer post-treatment cancer patients with challenges they face once they are released from the hospital. The results and implications of this semester long graduate project will help illuminate how the Human API through its various data collection methods could potentially play a larger role in extended cancer care. The research will also attempt to determine if hyper-connected networks of individual patients could become effective sources of information for health institutions to engage and connect with patients after treatment or surgery.

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Machine learning to detect self-reporting of symptoms, testing access, and recovery associated with COVID-19 on Twitter: retrospective big data infoveillance study

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JMIR Public Health and Surveillance 2020年第2期6卷 e19509页

作者： Mackey, Tim Purushothaman, Vidya Li, Jiawei Shah, Neal Nali, Matthew Bardier, Cortni Liang, Bryan Cai, Mingxiang Cuomo, Raphael Department of Anesthesiology and Division of Global Public Health and Infectious Diseases School of Medicine University of California San Diego San diego CA United States Global Health Policy Institute San Diego CA United States S-3 Research LLC San Diego CA United States Department of Healthcare Research and Policy University of California San Diego San Diego CA United States Department of Family Medicine and Public Health School of Medicine University of California San Diego San diego CA United States Masters Program in Global Health Department of Anthropology University of California San Diego San diego CA United States Masters Program in Computer Science Jacobs School of Engineering University of California San Diego San diego CA United States

Background: The coronavirus disease (COVID-19) pandemic is a global health emergency with over 6 million cases worldwide as of the beginning of June 2020. The pandemic is historic in scope and precedent given its emergence in an increasingly digital era. Importantly, there have been concerns about the accuracy of COVID-19 case counts due to issues such as lack of access to testing and difficulty in measuring recoveries. Objective: The aims of this study were to detect and characterize user-generated conversations that could be associated with COVID-19-related symptoms, experiences with access to testing, and mentions of disease recovery using an unsupervised machine learning approach. Methods: Tweets were collected from the Twitter public streaming application programming interface from March 3-20, 2020, filtered for general COVID-19-related keywords and then further filtered for terms that could be related to COVID-19 symptoms as self-reported by users. Tweets were analyzed using an unsupervised machine learning approach called the biterm topic model (BTM), where groups of tweets containing the same word-related themes were separated into topic clusters that included conversations about symptoms, testing, and recovery. Tweets in these clusters were then extracted and manually annotated for content analysis and assessed for their statistical and geographic characteristics. Results: A total of 4,492,954 tweets were collected that contained terms that could be related to COVID-19 symptoms. After using BTM to identify relevant topic clusters and removing duplicate tweets, we identified a total of 3465 (<1%) tweets that included user-generated conversations about experiences that users associated with possible COVID-19 symptoms and other disease experiences. These tweets were grouped into five main categories including first- and secondhand reports of symptoms, symptom reporting concurrent with lack of testing, discussion of recovery, confirmation of negative COVID-19 d

关键词： COVID-19 Infoveillance Machine learning Surveillance Twitter

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Applying fuzzy functions and sequential coordination to optimization of machinery arrangement and pipe routing

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NAVAL ENGINEERS JOURNAL 1998年第6期110卷 43-54页

作者： Wu, BC Young, GS Schmidt, W Choppella, K Dr. Bi-Chu Wu:received a PhD in Mechanical Engineering from the University of Maryland College Park in 1991. She has worked on projects involving naval architecture design optimization solid mechanics and database development. Presently a senwr engineer with Angle Incorporated Dr Wu's research interests are in design optimization and fuzzy logic applications. Dr. Gin-Shu Young: a senior engineer with Angle Incorporated holds a PhD in Mechanical Engineering from the University of Maryland College Park. As a guest researcher with National Institute of Standards and Technologies from 1990 to 1993 he worked on vision-based navigation for autonomous vehicles. His experience also includes applications of optimization fuzzy logic neural network and genetic algorithm methods to engineering system design Mr. William Schmidt:co-founded Angle Incorporated in 1990 and has served as Vice PresidentlChiefScientist during this tame. He holds a B.Sc. in Applied Science from the Naval Acadt?my and an M.Sc. in Physics from the Naval Post Graduate School. He has cner 20 years experience in technical leadership material and personnel management. He has led the application of computer aided design (CAD) and Product Model Information Exchange to the shipbuilding industry. His experience also includes leading the amlication of model based operational analysis to support the Live Fire Test Program for DDG 51 Class Destroyers. Mr. Krishna M. Choppella:is a Sofware Engineer at Eidea Laboratories Incotporated where he works on componentbased distributed enterpvise frameworks. He has been involved in creating data analysis tools for the US Nay by integrating CAD modeis databases and graphical front ends. His work in the Masters degree program in Mechanical Engineering at the University of Texas at Austin was in di0ddase.r spectroscopy of combustion products in porous-matri burners. He received his Bachelors degree in Electrical Engineering in India. He was a Research Associate at the Centre for Laser Technology and Project Engi

Ship design is often multidisciplinary involving several design elements with various types of objectives and constraints (O/C) some easily described as mathematical formulas, others better modeled as descriptive assertions. This paper describes a method based on fuzzy functions and an integrated performance index to model O/C using descriptive assertions to be used with mathematical formulas in optimization. Another issue addressed in this paper concerns the coordination of design elements when sequentially coupled, that is, when one leads the other and the performance of the follower depends greatly on the design of the leader. Based on neuro-fuzzy techniques, the method described here coordinates and optimizes sequentially coupled elements. The two methods are applied to machinery arrangement (MA) and pipe routing (PR). Preliminary models for optimization of MA and PR are described considering convenience, producibility: engine room size, interference and location as factors in the O/C set. Some test results from MA/PR applications are presented and discussed. The methods are generic and can be extended to other elements in ship design. They are mutually independent and may be used separately Two advantages of their use are an improvement in overall performance and a reduction in the need for redesign of elements.

关键词： Optimization

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Characterizing weibo social media posts from wuhan, china during the early stages of the COVID-19 pandemic: Qualitative content analysis

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JMIR Public Health and Surveillance 2020年第4期6卷 e24125页

作者： Xu, Qing Shen, Ziyi Shah, Neal Cuomo, Raphael Cai, Mingxiang Brown, Matthew Li, Jiawei Mackey, Tim Department of Healthcare Research and Policy University of California San Diego - Extension San Diego CA United States Global Health Policy and Data Institute San Diego CA United States S-3 Research LLC San Diego CA United States Masters Program in Computer Science Jacobs School of Engineering University of California San Diego San Diego CA United States Department of Anesthesiology School of Medicine University of California San Diego San Diego CA United States US Embassy National Cancer Institute National Institutes of Health Beijing China Department of Anesthesiology Division of Infectious Diseases and Global Public Health School of Medicine University of California San Diego San Diego CA United States

Background: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conversations related to information exposure and self-reported user experiences. Objective: This study aims to characterize the knowledge, attitudes, and behaviors of social media users located at the initial epicenter of the outbreak by analyzing data from the Sina Weibo platform in Chinese. Methods: We used web scraping to collect public Weibo posts from December 31, 2019, to January 20, 2020, from users located in Wuhan City that contained COVID-19–related keywords. We then manually annotated all posts using an inductive content coding approach to identify specific information sources and key themes including news and knowledge about the outbreak, public sentiment, and public reaction to control and response measures. Results: We identified 10,159 COVID-19 posts from 8703 unique Weibo users. Among our three parent classification areas, 67.22% (n=6829) included news and knowledge posts, 69.72% (n=7083) included public sentiment, and 47.87% (n=4863) included public reaction and self-reported behavior. Many of these themes were expressed concurrently in the same Weibo post. Subtopics for news and knowledge posts followed four distinct timelines and evidenced an escalation of the outbreak’s seriousness as more information became available. Public sentiment primarily focused on expressions of anxiety, though some expressions of anger and even positive sentiment were also detected. Public reaction included both protective and elevated health risk behavior. Conclusions: Between the announcement of pneumonia and respiratory illness of unknown origin in late December 2019 and the discovery of human-to-human transmission on January 20, 2020, we observed a high volume of public anxie

关键词： Attitude Behavior China Content analysis COVID-19 Data mining Infodemic Infodemiology Infoveillance Knowledge Social media Weibo

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