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2014 IEEE 40th Photovoltaic Specialist Conference (PVSC)

作者： Craig H. Swartz Odille C. Noriega Pathiraja A. R. D. Jayathilaka Madhavie Edirisooriya Xin-Hao Zhao Michael J. DiNezza Shi Liu Yong-Hang Zhang Thomas H. Myers Materials Science Engineering & Commercialization Program Texas State University San Marcos TX USA Center for Photonics Innovation Tempe AZ USA School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ USA

ISBN: (纸本)9781479943975

Confocal photoluminescence is shown to be a powerful tool for analyzing defect structure in epitaxial CdTe appropriate for photovoltaic applications. Non-radiative defects such as dislocations are easily mapped and quantified. Photoluminescence intensity measurements are shown to be a valuable tool for quantifying interface state density. Very low dislocation density and twin content can be achieved for epitaxial CdTe, and low interface state densities result from using CdMgTe barriers.

关键词： Epitaxial growth Radiative recombination DH-HEMTs Indexes Gallium arsenide Lenses

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Verification of relationship between heart rate and body movement for fatigue estimation

Verification of relationship between heart rate and body mov...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Jinhua She Hitoshi Nakamura Junya Imani Yasuhiro Ohyama Hiroshi Hashimoto Min Wu School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Control and Intelligent Automation Changsha China School of Computer Science Tokyo University of Technology Hachioji Japan Graduate School of Bionics Tokyo University of Technology Hachioji Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology Japan

It is an urgent need to find an objective way to estimate the degree of fatigue of employees. In this study, we designed a monitoring and estimation system for the degree of fatigue. This paper explains a long-term pedaling experiment that we use it to explore the possibility to use only the time sequence data of head movement during pedaling to estimate the fatigue. While we show the possibility for this through experimental data, it is clear that we need to collect more data to establish an estimation method.

关键词： Fatigue Heart rate Estimation Educational institutions Monitoring Correlation Electronic mail

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Wind Energy Projection for the Philippines based on Climate Change Modeling

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Energy Procedia 2014年 52卷 26-37页

作者： Angeli Silang Sherdon Niño Uy Julie Mae Dado Faye Abigail Cruz Gemma Narisma Nathaniel Libatique Gregory Tangonan Ateneo Innovation Center Ateneo de Manila University Quezon City 1108 Philippines Electronics Computer and Communications Engineering Department Ateneo de Manila University Quezon City 1108Philippines Manila Observatory Quezon City 1108 Philippines Atmospheric Science Program Department of Physics Ateneo de Manila University Quezon City 1108Philippines

To complement the existing method of wind energy assessment, this study presents wind energy projection by downscaling a regional climate model, RegCM3, which is also used in predicting rainfall and temperature changes, and using a conversion method using the Weibull distribution. A couple of papers which used long-term predicting models focused on two regions, China and the US High Plains, show a decrease of about 14% and 7%-17% respectively in wind power density due to global warming over the next century. This paper focuses on a smaller grid size of 10 km x 10 km to concentrate on a specific wind farm in Pililla, Rizal, Philippines which is considered as a commercially feasible site by wind developers. Wind energy projection that considers the effects of climate change for the expected period of operation of 25 years is used because this gives wind developers an outlook on the power production during the wind farm's lifetime and would contribute in determining the wind farm's potential for financial returns. Percentage difference of wind power density between the baseline period of 2008-2012 and five-year projection periods from 2013-2037 are presented. Contrary to the results of studies in China and western US, the results of this research show that there is an average five-year period increase of 6% in wind power density in Pililla, Rizal over the next 25 years.

关键词： wind energy assessment climate change wind projection

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Twitter sentiment predicts affordable care act marketplace enrollment

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Journal of Medical Internet Research 2015年第2期17卷 e51页

作者： Wong, Charlene A. Sap, Maarten Schwartz, Andrew Town, Robert Baker, Tom Ungar, Lyle Merchant, Raina M. Robert Wood Johnson Foundation Clinical Scholars Program University of Pennsylvania 1303 Blockley Hall 423 Guardian Dr. Philadelphia 19104 PA United States Penn. Medicine Social Media and Health Innovation Lab. University of Pennsylvania Philadelphia PA United States Leonard Davis Institute of Health Economics University of Pennsylvania Philadelphia PA United States Computer and Information Science Department Positive Psychology Center University of Pennsylvania Philadelphia PA United States Wharton School University of Pennsylvania Philadelphia PA United States National Bureau of Economic Research Cambridge MA United States Penn. Law School University of Pennsylvania Philadelphia PA United States Department of Emergency Medicine University of Pennsylvania Philadelphia PA United States

Background: Traditional metrics of the impact of the Affordable Care Act (ACA) and health insurance marketplaces in the United States include public opinion polls and marketplace enrollment, which are published with a lag of weeks to months. In this rapidly changing environment, a real-time barometer of public opinion with a mechanism to identify emerging issues would be valuable. Objective: We sought to evaluate Twitter's role as a real-time barometer of public sentiment on the ACA and to determine if Twitter sentiment (the positivity or negativity of tweets) could be predictive of state-level marketplace enrollment. Methods: We retrospectively collected 977,303 ACA-related tweets in March 2014 and then tested a correlation of Twitter sentiment with marketplace enrollment by state. Results: A 0.10 increase in the sentiment score was associated with an 8.7% increase in enrollment at the state level (95% CI 1.32-16.13;P=.02), a correlation that remained significant when adjusting for state Medicaid expansion (P=.02) or use of a state-based marketplace (P=.03). Conclusions: This correlation indicates Twitter's potential as a real-time monitoring strategy for future marketplace enrollment periods;marketplaces could systematically track Twitter sentiment to more rapidly identify enrollment changes and potentially emerging issues. As a repository of free and accessible consumer-generated opinions, this study reveals a novel role for Twitter in the health policy landscape. ©Charlene A Wong, Maarten Sap, Andrew Schwartz, Robert Town, Tom Baker, Lyle Ungar, Raina M Merchant.

关键词： Affordable care act Health insurance marketplace Social media

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Q&A

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Design Management Review 2016年第1期27卷

作者： Hillary Hartley Garren Givens Jennifer Pahlka The deputy executive director of 18F the US government's in‐house digital services consultancy based inside the General Services Administration. (18F got its name from its address. The GSA is located at the intersection of 18th Street and F Street in Washington DC.) Hartley co‐founded 18F to be a laboratory of sorts—staffed by developers and designers hailing from both inside and outside government working together to build digital services that could be used across agencies. The executive director of the Presidential Innovation Fellows (PIF) program which was established by the White House's Office of Science and Technology Policy in 2012 to pair talented diverse technologists and innovators with top civil servants and change‐makers working at the highest levels of the federal government. In August 2015 President Obama signed an Executive Order making the Presidential Innovation Fellows program a permanent part of the federal government going forward housed within the General Services Administration (GSA). He is also the deputy director of 18F (see Q&A page 13). Jennifer Pahlka is the founder and executive director of Code for America a San Francisco‐based nonprofit organization that according to the Washington Post “is the technology world's equivalent of the Peace Corps or Teach for America.” Known for her TED talk “Coding a Better Government” Pahlka came to the job after several years and various roles in the computer game industry. She was also one of the founders of the US Digital Service (see page 35).

She was a founder of 18F, the US government's in‐house digital services consultancy, and now she sees her workplace as a laboratory of sorts, staffed by designers as well as developers. As the executive director of the Presidential innovation Fellows program, he looks to recruit the best and the brightest in technical, design, and entrepreneurial talent. Known for her TED talk, “Coding a Better Government,” Jennifer Pahlka helps design and technology professionals live the idea of government by the people, for the people .

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Using emotional context from article for contextual music recommendation 13

Using emotional context from article for contextual music re...

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21st ACM International Conference on Multimedia, MM 2013

作者： Chen, Chih-Ming Tsai, Ming-Feng Liu, Jen-Yu Yang, Yi-Hsuan Department of Computer Science Program in Digital Content and Technology National Chengchi University Taipei 11605 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei 11564 Taiwan

ISBN: (纸本)9781450324045

This paper proposes a context-aware approach that recommends music to a user based on the user's emotional state predicted from the article the user writes. We analyze the association between user-generated text and music by using a real-world dataset with tripartite information collected from the social blogging website LiveJournal. The audio information represents various perceptual dimensions of music listening, including danceability, loudness, mode, and tempo;the emotional text information consists of bag-of-words and three dimensional affective states within an article: valence, arousal and dominance. To combine these factors for music recommendation, a factorization machine- based approach is taken. Our evaluation shows that the emotional context information mined from user-generated articles does improve the quality of recommendation, com- paring to either the collaborative filtering approach or the content-based approach. Copyright © 2013 ACM.

关键词： Collaborative filtering

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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Constant false alarm rate anomaly-based approach for network intrusion detection

Constant false alarm rate anomaly-based approach for network...

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10th International Conference on High Capacity Optical Networks and Emerging/Enabling Technologies, HONET-CNS 2013

作者： Alshaalan, Rayan Assadhan, Basil Al-Muhtadi, Jalal Bin-Abbas, Hesham El-Samie, Fathi Abd Alshebeili, Saleh Deptartment of Electrical Engineering King Saud University Riyadh Saudi Arabia Deptarpment of Computer Science King Saud University Riyadh Saudi Arabia National Technology Innovation Centers Program Riyadh Saudi Arabia King Saud University Riyadh Saudi Arabia

ISBN: (纸本)9781479925698

With the rapid growth of communication technologies, the widespread use of the Internet, and the recent introduction of e-services, the number of computer network security threats is dramatically increasing. This paper presents an efficient method for anomaly detection in network traffic. In this method, network traffic is decomposed into control and data planes. As the data traffic generation is based on control traffic, the behavior of the two planes is expected to be similar during normal behavior. Therefore, detecting dissimilarity (via cross-correlation) between the traffic of the two planes can indicate an abnormal behavior. Constant and adaptive thresholding techniques have been developed in this paper for the design of a false alarm rate intrusion detection processors. Simulation experiments have been carried out on a real traffic obtained at King Saud University at the end of 2012. © 2013 IEEE.

关键词： Intrusion detection

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Music Recommendation Based on Multiple Contextual Similarity Information

Music Recommendation Based on Multiple Contextual Similarity...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Chih-Ming Chen Ming-Feng Tsai Jen-Yu Liu Yi-Hsuan Yang Department of Computer Science & Program in Digital Content and Technology National Chengchi University Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan

This paper proposes a music recommendation approach based on various similarity information via Factorization Machines (FM). We introduce the idea of similarity, which has been widely studied in the filed of information retrieval, and incorporate multiple feature similarities into the FM framework, including content-based and context-based similarities. The similarity information not only captures the similar patterns from the referred objects, but enhances the convergence speed and accuracy of FM. In addition, in order to avoid the noise within large similarity of features, we also adopt the grouping FM as an extended method to model the problem. In our experiments, a music-recommendation dataset is used to assess the performance of the proposed approach. The datasets is collected from an online blogging Web site, which includes user listening history, user profiles, social information, and music information. Our experimental results show that, with various types of feature similarities the performance of music recommendation can be enhanced significantly. Furthermore, via the grouping technique, the performance can be improved significantly in terms of Mean Average Precision, compared to the traditional collaborative filtering approach.

关键词： Feature extraction Frequency modulation Vectors Recommender systems History Music Data mining

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Human Touch Behavior Classification to Therapy Robot using SOM

Human Touch Behavior Classification to Therapy Robot using S...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Koji Makino Wasantha Samarathunga Hubais Abdelrahman Jin-Hua She Yasuhiro Ohyama Hiroshi Hashimoto Graduate school of medicine and Engineering University of Yamanashi School of Computer Science Tokyo University of Technology Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology

ISBN: (纸本)9781479902255

In this research, a classification method for human touching behaviors to haptic therapy robot is proposed. It is difficult to apply explicit discrete representation for human touch behaviors such as "slap", "pat" due to the existence of intermediate touch behavioral patterns. Therefore a new classification approach for human touch behaviors using Self Organizing Map (SOM) is proposed, using its ability to classify the nearby data in to a group. Further in this research the axis of out put maps are defined to be meaningful by specifying the initial placement of the input data during the training process.

关键词： Touch self-organising feature maps GRHL3 gene Classification Methods incoming data Robot Axis Human maps Medicine

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