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Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science : Seattle, WA, USA. 24-26 September 2015

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Implementation science : IS 2016年第1期11 Suppl 1卷 85页

作者： Cara Lewis Doyanne Darnell Suzanne Kerns Maria Monroe-DeVita Sara J. Landes Aaron R. Lyon Cameo Stanick Shannon Dorsey Jill Locke Brigid Marriott Ajeng Puspitasari Caitlin Dorsey Karin Hendricks Andria Pierson Phil Fizur Katherine A. Comtois Lawrence A. Palinkas Patricia Chamberlain Gregory A. Aarons Amy E. Green Mark. G. Ehrhart Elise M. Trott Cathleen E. Willging Maria E. Fernandez Nicholas H. Woolf Shuting Lily Liang Natalia I. Heredia Michelle Kegler Betsy Risendal Andrea Dwyer Vicki Young Dayna Campbell Michelle Carvalho Yvonne Kellar-Guenther Laura J. Damschroder Julie C. Lowery Sarah S. Ono Kathleen F. Carlson Erika K. Cottrell Maya E. O’Neil Travis L. Lovejoy Joanna J. Arch Jill L. Mitchell Cara C. Lewis Brigid R. Marriott Kelli Scott Jennifer Schurer Coldiron Eric J. Bruns Alyssa N. Hook Benjamin C. Graham Katelin Jordan Rochelle F. Hanson Angela Moreland Benjamin E. Saunders Heidi S. Resnick Shannon Wiltsey Stirman Cassidy A. Gutner Jennifer Gamarra Dawne Vogt Michael Suvak Jennifer Schuster Wachen Katherine Dondanville Jeffrey S. Yarvis Jim Mintz Alan L. Peterson Elisa V. Borah Brett T. Litz Alma Molino Stacey Young McCaughan Patricia A. Resick Nancy Pandhi Nora Jacobson Neftali Serrano Armando Hernandez Elizabeth Zeidler- Schreiter Natalie Wietfeldt Zaher Karp Michael D. Pullmann Barbara Lucenko Bridget Pavelle Jacqueline A. Uomoto Andrea Negrete Molly Cevasco Suzanne E. U. Kerns Robert P. Franks Christopher Bory Edward J. Miech Teresa M. Damush Jason Satterfield Derek Satre Maria Wamsley Patrick Yuan Patricia O’Sullivan Helen Best Susan Velasquez Miya Barnett Lauren Brookman-Frazee Jennifer Regan Nicole Stadnick Alison Hamilton Anna Lau Scott Roesch Byron J. Powell Thomas J. Waltz Matthew J. Chinman Laura Damschroder Jeffrey L. Smith Monica M. Matthieu Enola K. Proctor JoAnn E. Kirchner Monica J. Matthieu Craig S. Rosen Sarah C. Walker Asia S. Bishop Mariko Lockhart Allison L. Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal Daniel M. Blonigen Anne M. Mauricio Thomas D. Dishion Jenna Rudo-Stern Department of Psychological and Brain Sciences Indiana University Bloomington USA Department of Psychiatry & Behavioral Sciences University of Washington Seattle USA Psychology Department University of Montana Missoula USA Department of Psychology La Salle University Philadelphia USA Division of Public Behavioral Health and Justice Policy University of Washington Seattle USA National Center for PTSD VA Palo Alto Health Care System Menlo Park USA Department of Psychiatry University of Arkansas for Medical Sciences Little Rock USA Department of Psychology University of Washington Seattle USA Department of Speech and Hearing Sciences University of Washington Seattle USA Department of Psychological Sciences University of Missouri Columbia USA Department of Children Youth and Families School of Social Work University of Southern California Los Angeles USA Oregon Social Learning Center Eugene USA Department of Psychiatry University of California San Diego La Jolla USA Child and Adolescent Services Research Center (CASRC) San Diego USA Department of Psychology San Diego State University San Diego USA Pacific Institute for Research and Evaluation Behavioral Health Research Center of the Southwest Albuquerque USA School of Public Health University of Texas Health Science Center at Houston Houston USA Woolf Consulting Santa Barbara USA Rollins School of Public Health Emory University Atlanta USA University of Colorado Cancer Center at Denver Aurora USA South Carolina Primary Health Care Association Columbia USA Veterans Affairs (VA) Ann Arbor Center for Clinical Management Research Ann Arbor USA Personalizing Options through Veteran Engagement (PROVE) Quality Enhancement Research Initiative (QUERI) Program Ann Arbor USA Center to Improve Veteran Involvement in Care (CIVIC) Veterns Affairs (VA) Portland Health Care System (VAPORHCS) Portland USA Department of Family Medicine Oregon Health & Science University Portland USA Division of General Internal Medi

Introduction to the 3rd Biennial Conference of the Society for Implementation Research Collaboration: advancing efficient methodologies through team science and community partnerships Cara Lewis, Doyanne Darnell, Suzanne Kerns, Maria Monroe-DeVita, Sara J. Landes, Aaron R. Lyon, Cameo Stanick, Shannon Dorsey, Jill Locke, Brigid Marriott, Ajeng Puspitasari, Caitlin Dorsey, Karin Hendricks, Andria Pierson, Phil Fizur, Katherine A. Comtois A1: A behavioral economic perspective on adoption, implementation, and sustainment of evidence-based interventions Lawrence A. Palinkas A2: Towards making scale up of evidence-based practices in child welfare systems more efficient and affordable Patricia Chamberlain A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A5: Efficient synthesis: Using qualitative comparative analysis and the Consolidated Framework for Implementation Research across diverse studies Laura J. Damschroder, Julie C. Lowery A6: Establishing a veterans engagement group to empower patients and inform Veterans Affairs (VA) health services research Sara

关键词： Veteran Affair Motivational Interview Veteran Health Administration Dialectical Behavior Therapy Qualitative Comparative Analysis

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Application of SVM in Citation Information Extraction

Application of SVM in Citation Information Extraction

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International Workshop on Complexity and data Mining (IWCDM)

作者： Jiguang Liang Robert Layton Wei Wang Web Data Mining Laboratory Department of Education Technology Educational Science College Nanjing Normal University Nanjing Jiangsu China Internet Commerce Security Laboratory University of Ballarat Ballarat Australia Machine Learning and Cognition Laboratory Department of Education Technology Educational Science College Nanjing Normal University Nanjing Jiangsu China

Support Vector Machines are an effective form of binary-class classification algorithm. To enhance the utilization of text structural features for information extraction, which are greatly restricted by the Hidden Markov Model (HMM), this paper proposes a support vector machine multi-class classification based on Markov properties to extract the information from a citation database. The proposed model extracts symbol characteristics as features and composes a binary tree of the transition probabilities. Experiments show that the proposed method outperforms HMM and basic SVM methods.

关键词： Hidden Markov models Support vector machines Feature extraction Binary trees data mining Markov processes Probability

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Using ERPs for assessing the (sub) conscious perception of noise

Using ERPs for assessing the (sub) conscious perception of n...

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

作者： Anne K. Porbadnigk Jan-N. Antons Benjamin Blankertz Matthias S. Treder Robert Schleicher Sebastian Möller Gabriel Curio Machine Learning Laboratory Berlin Institute of Technology Berlin Germany Quality and Usability Lab Telekom Laboratories Berlin Germany Intelligent Data Analysis Group Fraunhofer FIRST Berlin Germany Department of Neurology and Clinical Neurophysiology Charite Berlin Germany Department of Neurology Clinical Neurophysiology Charite Berlin Germany

In this paper, we investigate the use of event-related potentials (ERPs) as a quantitative measure for quality assessment of disturbed audio signals. For this purpose, we ran an EEG study (N=11) using an oddball paradigm, during which subjects were presented with the phoneme /a/, superimposed with varying degrees of signal-correlated noise. Based on this data set, we address the question to which degree the degradation of the auditory stimuli is reflected on a neural level, even if the disturbance is below the threshold of conscious perception. For those stimuli that are consciously recognized as being disturbed, we suggest the use of the amplitude and latency of the P300 component for assessing the level of disturbance. For disturbed stimuli for which the noise is not perceived consciously, we show for two subjects that a classifier based on shrinkage LDA can be applied successfully to single out stimuli, for which the noise was presumably processed subconsciously.

关键词： Noise Presses Electroencephalography Training Degradation Noise measurement Pattern recognition

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Abstracts for the 6th Congress of Asian Sleep Research Society

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Sleep and Biological Rhythms 2009年第4期7卷 A1-A49页

作者： Seog Ju Kim In Kyoon Lyoo Yu-Jin Lee Do-Un Jeong Hirohiko Kanai Masanori Ookubo Atsushi Yoshimura Masako Okawa Noto Yamada Takeshi Munezawa Yoshitaka Kaneita Yoneatsu Osaki Hideyuki Kanda Tadahiro Ohtsu Masumi Minowa Kenji Suzuki Susumu Hijuchi Hiroyuki Suzuki Takashi Ohida Takashi Abe Yoko Komada Shoichi Asaoka Yuichi Inoue Jin-Seong Lee Sang-Yong Cho Deependra Kumar Hruda N. Mallick Velayudhan M. Kumar Mahesh K. Kaushik Akihiro Karashima Noiihiro Katayama Mitsuyuki Nakao Ravindra P. Nagendra Sathiamma Sulekha Sathyaprabha T. Narasappa Pradhan Nityanadan Bindu M. Kutty M. Nirmala P. N. Ravindra Basavaraj Ramappa Tubaki T. N. Sathyaprabha D. Sudhakar G. S. Lavekar C. R. Chandrashekar Kazuyoshi Kitaoka Mika Shimizu Sachiko Chikahisa Kazuo Yoshizaki Hiroyoshi Sei Jong-Won Kim Misa Takegami Shin Yamazaki Yasuaki Hayashino Rei Ono Koji Otani Miho Sekiguchi Shinichi Konno Shunichi Fukuhara Antonia J. Jakobson Paul Fitzgerald Russell Conduit Xin Shirley Li Siu Ping Joyce Lam Wai Man Mandy Yu Yun Kwok Wing Kazue Okamoto-Mizuno Koh Mizuno Mituaki Yamamoto Shuichiro Shirakawa Hirokazu Doi Mikako Kato Kazuyuki Shinohara Masako Tamaki Shiori Matsuda Katsuo Yamazaki Tadao Hori Keiko Ogawa Kazumi Takahashi Kunio Kitahama Katuo Yamazaki Yoshimasa Koyama Kohei Shioda Yugo Ueda Yukiko Nakamura Clara Inoue Kazushige Goto Sunao Uchida Yuko Morita Yoshiko Honda Tohru Kodama Mari Hagihara Toru Nakajima Masato Saito Yoshihiko Koga Shinichiro Tanaka Hiroshi Yamadera Madoka Takahara Sachiko Suwa Minoru Onozuka Sadao Sato Fumiharu Togo Taiki Komatsu Takeshi Mitani Jongbae Choi Bin Zhang Taeko Sasai Hiromi Mitsubayashi Mitsuhiro Ohtsu Isao Hasegawa Tatsuya Ishii Akira Komori Asami Suzuki Yue Nakahara Mitsuyasu Hiroki Mariko Nakauma Nobuo Someya Tomomasa Ochiai Shouhei Komori Rayleigh Ping-Ying Chiang Zai-Ting Yeh Seong T. Kim Seung H. Yoon Jeong S. Kwon Jong H. Choi Hyung J. Ahn Youngsoo Kim Bolortuya Yunren Lichao Chen Radhika Basheer Robert W. Mccarley Robert E. Strecker Makoto Honda Tetsuaki Arai Miyuki Fukazawa Yutaka Honda Kuniaki T Department of Psychiatry Gachon University of Medicine and Science Incheon Republic of Korea Department of Psychiatry Seoul National University Seoul Republic of Korea Department of Neuropsychiatry and Center for Sleep and Chronobiology Seoul National University Hospital Seoul Republic of Korea Department of Neuropsychiatry Seoul National University Hospital Seoul Republic of Korea Seoul National University Hospital Seoul Republic of Korea Department of Psychiatry Shiga University of Medical Science Otsu Japan Division of Public Health Department of Social Medicine Nihon University School of Medicine Tokyo Japan Department of Public Health Nihon University School of Medicine Tokyo Japan Division of Environmental and Preventive Medicine Department of Social Medicine Faculty of Medicine Tottori University Yonago Japan Department of Hygiene and Preventive Medicine Fukushima Medical University Fukushima Japan Department of Public Health Showa University School of Medicine Tokyo Japan Faculty of Humanities Seitoku University Matsudo Japan Section on Behavioral Science Division of Clinical Research National Hospital Organization Kurihama Alcoholism Center Yokosuka Japan Department of Otolaryngology Second Hospital Fujita Health University Nagoya Japan National Hospital Organization Kurihama Alcoholism Center Kanagawa Japan Metropolitan Police Department Criminal Investigation Laboratory Tokyo Japan Japan Somnology Center Neuropsychiatrie Research Institute Tokyo Japan Department of Somnology Tokyo Medical University Tokyo Japan Japan Somnology Center Neuropsychiatric Research Institute Tokyo Japan Department of Somnology Tokyo Medical and Dental University Tokyo Japan Center for Sleep and Chronobiology Department of Psychiatry and Behavioral Science Seoul National University College of Medicine Seoul Republic of Korea Department of Psychiatry and Behavioral Science Center for Sleep and Chronobiology Seoul Republic of Korea Department of Physiology Al

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CONTROL SYSTEM DESIGN CONSIDERING A TRADEOFF BETWEEN EVALUATED UNCERTAINTY RANGES AND CONTROL PERFORMANCE

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Asian Journal of Control 2008年第1期1卷

作者： Y. Wakasa Y. Yamamoto Dept. of Applied Analysis and Complex Dynamical Systems Graduate School of Informatics Kyoto University Kyoto Japan. Yuji Wakasa was born in Okayama Japan in 1968. He received the B.S. and M.S. degrees in engineering from Kyoto university Japan in 1992 and 1994 respectively. From 1994 to 1998 he was a Research Associate in the Department of Information Technology Okayama University. Since April 1998 he has been a Research Associate in the Graduate School of Informatics Kyoto University. His current research interests include robust control and control system design via mathematical programming. Yutaka Yamamoto received his B.S. and M.S. degrees in engineering from Kyoto University Kyoto Japan in 1972 and 1974 respectively and the M.S. and Ph.D. degree in mathematics from the University of Florida in 1976 and 1978 respectively. From 1978 to 1987 he was with Department of Applied Mathematics and Physics Kyoto University and from 1987 to 1997 with Department of Applied System Science. Since 1998 he is a professor at the current position. His current research interests include realization and robust control of distributed parameter systems learning control sampled-data systems and digital signal processing. Dr. Yamamoto is a receipient of the Sawaragi memorial paper award (1985) the Outstanding Paper Award of SICE (1987) Best Author Award of SICE (1990) the George Axelby Outstanding Paper Award of IEEE CSS in 1996 Takeda Paper Prize of SICE in 1997. He is a Fellow of IEEE. He was an associate editor of Automatica. He is currently an associate editor of IEEE Transactions on Automatic Control Systems and Control Letters and Mathematics of Control Signals and Systems. He is a member of the IEEE the Society of Instrument and Control Engineers (SICE) and the Institute of Systems Control and Information Engineers.

This paper presents a design method of control systems such that a designer can flexibly take account of tradeoffs between evaluated uncertainty ranges and the level of control performance. The problem is reduced to a BMI problem and approximately solved by LMIs. The convergence of the proposed approximation is proved in a modified sense. A numerical example shows the effectiveness of the proposed method in comparison with the standard robust control.

关键词： Control system design LMI BMI tradeoff curves

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Can we determine the top unresolved problems of visualization?

Can we determine the top unresolved problems of visualizatio...

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IEEE Visualization 2004 - Proceedings, VIS 2004

作者： Rhyne, Theresa-Marie Hibbard, Bill Johnson, Chris Chen, Chaomei Eick, Steve North Carolina State University University of Wisconsin Madison University of Utah Drexel University SSS-Research Inc. University of Illinois Chicago Learning Technology Service North Carolina State University Sci. Computing and Imaging Institute University of Utah Department of Computer Science Depts. of Phys. and Bioengineering Coll. of Info. Sci. and Technology Drexel University UIC's Natl. Center for Data Mining

ISBN: (纸本)0780387880

The top unresolved problems in visualization were investigated by panelists from both the information and scientific visualization domains. One of the key unresolved challenges in visualization is collaboration in its broadest sense. Visualization 'scientists' need to spend more time understanding the underlying science applications in order to create effective visual representations. In order to 'evolve' visualization into a more scientific enquiry, visualization scientists need to understand and use the scientific method such as formulation of an hypothesis to explain the phenomena. Effective human computer interaction continues to be one of the top research and development goals for both visualization and computer graphics.

关键词： Visualization

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CLEER - AN AI-SYSTEM DEVELOPED TO ASSIST EQUIPMENT ARRANGEMENTS ON WARSHIPS

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NAVAL ENGINEERS JOURNAL 1989年第3期101卷 127-137页

作者： ZHOU, HH SILVERMAN, BG SIMKOL, J Dr. H. Harry Zhou:is a research professor at the Institute for Artificial Intelligence of The George Washington University. Dr. Zhou received his master's degree and Ph.D. in computer science from Vanderbilt University in 1984 and 1987 respectively. He did his dissertation in the fields of artificial intelligence analogical reasoning and machine learning. His research interests include: classifier systems genetic algorithms learning by analogy inductive learning adaptive expert systems automated knowledge acquisition and adaption. He is also interested in data base design programming languages mental modeling and software engineering. Dr. Barry G. Silverman:is director of the Institute for Artificial Intelligence and a professor at the Engineering Administration Department of The George Washington University. He is also president of IntelliTek Inc. an AI consulting firm. Dr. Silverman received the B.S.E. M.S.E. and Ph.D. degrees from the University of Pennsylvania. He has been a principal developer of four generic AI products as well as eight AI applications. Since 1979 he has written over 100 papers and reports on these AI efforts. Joel Simkol:is a research scientist currently engaged in designing expert system architectures to support electronic warfare vulnerability analyses threat assessments shipboard topside antenna arrangements and C3countermeasures employment. Mr. Simkol's work in applying expert systems technology to electromagnetic interference and to spectrum management has generated increased interest and participation from all branches of government agencies.

This paper describes a modularized AI system being built to help improve electromagnetic compatibility (EMC) among shipboard topside equipment and their associated systems. CLEER is intended to act as an easy to use integrator of existing expert knowledge and pre-existing data bases and large scale analytical models. Due to these interfaces; to the need for portability of the software; and to artificial intelligence related design requirements (such as the need for spatial reasoning, expert data base management, model base management, track-based reasoning, and analogical (similar ship) reasoning) it was realized that traditional expert system shells would be inappropriate, although relatively off-the-shelf AI technology could be incorporated. In the same vein, the rapid prototyping approach to expert system design and knowledge engineering was not pursued in favor of a rigorous systems engineering methodology. The critical design decisions affecting CLEER's development are summarized in this paper along with lessons learned to date all in terms of “how,” “why,” and “when” specific features are being developed.

关键词： Artificial Intelligence

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