检索结果-内蒙古大学图书馆

Proceedings of the 8th Annual Conference on the science of Dissemination and Implementation : Washington, DC, USA. 14-15 December 2015

引用

Implementation science : IS 2016年第2期11 Suppl 2卷 100页

作者： Chambers, David Simpson, Lisa Hill-Briggs, Felicia Neta, Gila Vinson, Cynthia Beidas, Rinad Marcus, Steven Aarons, Gregory Hoagwood, Kimberly Schoenwald, Sonja Evans, Arthur Hurford, Matthew Rubin, Ronnie Hadley, Trevor Barg, Frances Walsh, Lucia Adams, Danielle Mandell, David Martin, Lindsey Mignogna, Joseph Mott, Juliette Hundt, Natalie Kauth, Michael Kunik, Mark Naik, Aanand Cully, Jeffrey McGuire, Alan White, Dominique Bartholomew, Tom McGrew, John Luther, Lauren Rollins, Angie Salyers, Michelle Cooper, Brittany Funaiole, Angie Richards, Julie Lee, Amy Lapham, Gwen Caldeiro, Ryan Lozano, Paula Gildred, Tory Achtmeyer, Carol Ludman, Evette Addis, Megan Marx, Larry Bradley, Katharine VanDeinse, Tonya Wilson, Amy Blank Stacey, Burgin Powell, Byron Bunger, Alicia Cuddeback, Gary Barnett, Miya Stadnick, Nicole Brookman-Frazee, Lauren Lau, Anna Dorsey, Shannon Pullmann, Michael Mitchell, Shannon Schwartz, Robert Kirk, Arethusa Dusek, Kristi Oros, Marla Hosler, Colleen Gryczynski, Jan Barbosa, Carolina Dunlap, Laura Lounsbury, David O’Grady, Kevin Brown, Barry Damschroder, Laura Waltz, Thomas Ritchie, Mona Atkins, David Imel, Zac E. Xiao, Bo Can, Doğan Georgiou, Panayiotis Narayanan, Shrikanth Berkel, Cady Gallo, Carlos Sandler, Irwin Brown, C. Hendricks Wolchik, Sharlene Mauricio, Anne Marie Mehrotra, Sanjay Chandurkar, Dharmendra Bora, Siddhartha Das, Arup Tripathi, Anand Saggurti, Niranjan Raj, Anita Hughes, Eric Jacobs, Brian Kirkendall, Eric Loeb, Danielle Trinkley, Katy Yang, Michael Sprowell, Andrew Nease, Donald Lyon, Aaron Lewis, Cara Boyd, Meredith Melvin, Abigail Nicodimos, Semret Liu, Freda Jungbluth, Nathanial Flynn, Allen Landis-Lewis, Zach Sales, Anne Baloh, Jure Ward, Marcia Zhu, Xi Bennett, Ian Unutzer, Jurgen Mao, Johnny Proctor, Enola Vredevoogd, Mindy Chan, Ya-Fen Williams, Nathaniel Green, Phillip Bernstein, Steven Rosner, June-Marie DeWitt, Michelle Tetrault, Jeanette Dziura, James Hsiao, Allen Sussman, Scott O’Connor, Patrick Toll, Benjamin Jones, Michael Gassaway, Julie Tobin, Jonathan Zatzic Division of Cancer Control and Population Sciences National Cancer Institute National Institutes of Health Rockville USA AcademyHealth Washington USA Department of Medicine and Welch Center for Prevention Epidemiology and Clinical Research Johns Hopkins Medical Institutions Baltimore USA Psychiatry University of Pennsylvania Philadelphia USA Family Medicine and Community Health University of Pennsylvania Philadelphia USA School of Social Policy and Practice University of Pennsylvania Philadelphia USA Psychiatry UC San Diego La Jolla USA Child & Adolescent Psychiatry The Child Study Center at NYU Langone Medical Center New York NY New York USA Psychiatry and Behavioral Sciences MUSC Charleston USA DBHIDS City of Philadelphia Philadelphia USA CBH City of Philadelphia Philadelphia USA Psychiatry University of Pennsylvania Perelman School of Medicine Philadelphia USA Health Services Research & Development Department of Veterans Affairs & Baylor College of Medicine Houston USA Treatment Core Department of Veterans Affairs Waco USA National Center for PTSD Executive Division Department of Veterans Affairs White River Junction USA HSR&D HSR&D Center for Health Information and Communication Roudebush VA Medical Center Indianapolis USA Psychology Indiana University Purdue University Indianapolis Indianapolis USA Department of Psychiatric Rehabilitation and Counseling Rutgers University Newark USA Health Services Research & Development Richard L. Roudebush VAMC Indianapolis USA IUPUI Department of Psychology ACT Center of Indiana Indianapolis USA Human Development Washington State University Pullman USA Prevention Science Washington State University Pullman USA Group Health Research Institute Group Health Seattle USA Behavioral Health Services Group Health Seattle USA Preventive Care Group Health Seattle USA Health Services Research & Development Primary and Specialty Medical Care Service VA Puget Sound Seattle USA School of Social Work Un

A1 Introduction to the 8th Annual Conference on the science of Dissemination and Implementation: Optimizing Personal and Population Health David Chambers, Lisa Simpson D1 Discussion forum: Population health D&I research Felicia Hill-Briggs D2 Discussion forum: Global health D&I research Gila Neta, Cynthia Vinson D3 Discussion forum: Precision medicine and D&I research David Chambers S1 Predictors of community therapists’ use of therapy techniques in a large public mental health system Rinad Beidas, Steven Marcus, Gregory Aarons, Kimberly Hoagwood, Sonja Schoenwald, Arthur Evans, Matthew Hurford, Ronnie Rubin, Trevor Hadley, Frances Barg, Lucia Walsh, Danielle Adams, David Mandell S2 Implementing brief cognitive behavioral therapy (CBT) in primary care: Clinicians' experiences from the field Lindsey Martin, Joseph Mignogna, Juliette Mott, Natalie Hundt, Michael Kauth, Mark Kunik, Aanand Naik, Jeffrey Cully S3 Clinician competence: Natural variation, factors affecting, and effect on patient outcomes Alan McGuire, Dominique White, Tom Bartholomew, John McGrew, Lauren Luther, Angie Rollins, Michelle Salyers S4 Exploring the multifaceted nature of sustainability in community-based prevention: A mixed-method approach Brittany Cooper, Angie Funaiole S5 Theory informed behavioral health integration in primary care: Mixed methods evaluation of the implementation of routine depression and alcohol screening and assessment Julie Richards, Amy Lee, Gwen Lapham, Ryan Caldeiro, Paula Lozano, Tory Gildred, Carol Achtmeyer, Evette Ludman, Megan Addis, Larry Marx, Katharine Bradley S6 Enhancing the evidence for specialty mental health probation through a hybrid efficacy and implementation study Tonya VanDeinse, Amy Blank Wilson, Burgin Stacey, Byron Powell, Alicia Bunger, Gary Cuddeback S7 Personalizing evidence-based child mental health care within a fiscally mandated policy reform Miya Barnett, Nicole Stadnick, Lauren Brookman-Frazee, Anna Lau S8 Leveraging an existing

关键词： Veteran Affair Motivational Interview Qualitative Comparative Analysis Community That Care Supplemental Nutrition Assistance Program

来源：评论

学校读者我要写书评

暂无评论

Spatio-temporal prediction of collision candidates for static and dynamic objects in monocular image sequences

Spatio-temporal prediction of collision candidates for stati...

引用

IEEE Symposium on Intelligent Vehicle

作者： Alexander Schaub Darius Burschka Institute of System Dynamics and Control at the Robotics and Mechatronics Center German Aerospace Center Wessling Germany Department of Computer Science Technische Universität München Garching bei Munchen Germany

ISBN: (纸本)9781467327534

This paper presents a novel approach for reactive obstacle avoidance for static and dynamic objects using monocular image sequences. A sparse motion field is calculated by tracking point features using the Kanade-Lucas-Tomasi method. The rotational component of this sparse optical flow due to ego motion of the camera is compensated using motion parameters estimated directly from the images. A robust method for detection of static and dynamic objects in the scene is applied to identify collision candidates. The approach operates entirely in the image space of a monocular camera and does not require any extrinsic information about the configuration of the sensor or speed of the camera. The system prioritizes the detected collision candidates by their time to collision. Additionally, the spatial distribution of the candidates is calculated for non-degenerated conditions. We present the mathematical framework and the experimental validation of the suggested approach on simulated and real-world data.

关键词： Cameras Optical imaging Vectors Robot sensing systems Optical sensors Adaptive optics Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

引用

Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

来源：评论

学校读者我要写书评

暂无评论

An empirical analysis of social interaction on tobacco-oriented social networks

An empirical analysis of social interaction on tobacco-orien...

引用

2013 International Conference for Smart Health, ICSH 2013

作者： Liang, Yunji Zheng, Xiaolong Zeng, Daniel Dajun Zhou, Xingshe Leischow, Scott School of Computer Science Northwestern Polytechnical University Xi'an China Department of Management Information System University of Arizona Tucson AZ United States State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China Mayo Clinic in Arizona Phoenix AZ United States

ISBN: (纸本)9783642398438

Social media is widely utilized in the tobacco control campaigns. It is a great challenge to evaluate the efficiency of tobacco control policies on social network sites and find gaps among tobacco-oriented social networks. In this paper, we construct three tobacco-oriented social networks according to user interaction on Facebook tobacco-related fan pages. We further investigate the interaction patterns including temporal distribution and interaction patterns to reveal the differences of tobacco-oriented social networks. Our empirical analysis demonstrates that: 1) the user interaction on the pro-tobacco fan pages is more active. Fan pages for tobacco promotion are more successful in obtaining more user attention. 2) The gap between tobacco promotion and tobacco control is widening. These empirical results can provide us significant insights into understanding the evolutionary patterns of social interaction in tobacco-oriented social networks and further help the government departments of tobacco control to make reasonable decisions. © 2013 Springer-Verlag.

关键词： Tobacco

来源：评论

学校读者我要写书评

暂无评论

An improved parameterized approach for real time optimal motion planning of AUV moving in dynamic environment

An improved parameterized approach for real time optimal mot...

引用

IEEE Conference on Robotics, Automation and Mechatronics

作者： Wenhao Luo Jun Peng Jing Wang Department of Automation Key Laboratory of System Control And Information Processing Shanghai China School of Information Science and Engineering Hunan Engineering Laboratory Changsha China Computer Engineering Program Bethune-Cookman University Daytona Beach FL USA

In this paper, we present an improved analytic method to the optimal trajectory generation of an autonomous underwater vehicle (AUV) in a dynamic environment. The proposed approach explicitly incorporates both the AUV kinematic and the geometric constraints due to dynamic obstacles and the terrain while rendering the near-shortest path by a performance index related to the path length. In particular, the proposed design is based on a family of parameterized trajectories determined by three adjustable parameters, which provides a unified way to reformulate the geometric constraints and performance index into a set of parameterized constraint equations. To that end, such a constrained optimization problem boils down to optimize those adjustable parameters, which can be analytically solved in the parameter space. The proposed solution enhances the methodologies of real-time path planning for robots in 3D environment. Simulation results verify the effectiveness of the proposed method.

关键词： Trajectory Planning Vehicle dynamics Dynamics Collision avoidance Kinematics Optimization

来源：评论

学校读者我要写书评

暂无评论

Prediction of hard rock TBM penetration rate using least square support vector machine

引用

IFAC Proceedings Volumes 2013年第13期46卷 347-352页

作者： Yang Ge Jingcheng Wang Kang Li Department of Automation Shanghai Jiao Tong University Shanghai and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai 200240 China (Tel: 86-21-34205374 ) School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

The prediction of tunnel boring machine (TBM) penetration rate is helpful to plan construction time and to control cost. This paper studies on modeling the penetration rate and the rock mass parameters via least square support vector machine (LS-SVM). These rock properties include uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), peak slope index (PSI), distance between planes of weakness (DPW) and the alpha angle. The correlation between the rock parameters and the measured rate of penetration (ROP) is first investigated via LS-SVM. Then the necessity of normalizing the rock parameters is discussed. Finally, comparisons between the LS-SVM and other methods are presented to demonstrate the applicability of LS-SVM for predicting ROP.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On Variation of Infinite Horizon Performance of Model Predictive control with Varying Receding Horizon

引用

IFAC Proceedings Volumes 2013年第20期46卷 701-706页

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 P. R. China School of Electronics Electrical Engineering and Computer Science The Queen's University Belfast Belfast BT7 1NN UK

This paper investigates variation of infinite horizon (IH) performance of Model Predictive control (MPC) without constraints as the optimization horizon changes. By exploring properties of the Difference Riccati Equations (DRE), an upper bound and a lower bound of the ratio between variation of IH performance of MPC and finite horizon (FH) optimal cost are obtained. The result shows the dynamic behavior of IH performance of closed-loop MPC systems as the optimization horizon varies.

关键词： Model predictive control Infinite horizon performance Finite horizon optimal control Optimization horizon

来源：评论

学校读者我要写书评

暂无评论

A unified optimization method for real-time trajectory generation of mobile robots with kinodynamic constraints in dynamic environment

A unified optimization method for real-time trajectory gener...

引用

IEEE Conference on Robotics, Automation and Mechatronics

作者： Wenhao Luo Jun Peng Weirong Liu Jing Wang Wentao Yu Department of Automation Key Laboratory of System Control And Information Processing Shanghai China School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Controland Intelligent Automation Changsha China Computer Engineering Program Bethune-Cookman University Daytona Beach FL USA

This paper presents an efficient analytic method for a mobile robot to determine a collision-free trajectory with unified optimization. The robot kinodynamic constraints and the geometric constraints due to obstacles are addressed by considering a set of constrained inequalities from parameterized trajectories model. Two optimal performance matrices are employed to assess optimization problems. Particularly, both the constraints and performance functions are incorporated by similar forms in terms of trajectory parameters, which thereby can be considered in a uniform way. A parameter space of adjustable trajectory parameters is constructed to solve the unified optimization problem with constraints and results in more flexible and better optimal performance. The proposed approach is complete and enhances methods of deterministic real-time planning by overcoming typical drawbacks as intermediate configuration, curvature discontinuities, vertical singularities and incomplete optimization. Simulation results verify the validity and superiority of the proposed method.

关键词： Trajectory Robot kinematics Collision avoidance Mobile robots Acceleration Optimization

来源：评论

学校读者我要写书评

暂无评论

Multi-objective evolutionary algorithm for variable selection in calibration problems: A case study for protein concentration prediction

Multi-objective evolutionary algorithm for variable selectio...

引用

Congress on Evolutionary Computation

作者： Daniel Vitor de Lucena Telma Woerle de Lima Anderson da Silva Soares Alexandre C. B. Delbem Arlindo Rodrigues Galvão Filho Clarimar José Coelho Gustavo Teodoro Laureano Institute of Informatics Federal University of Goiás Goiania Brazil ICMC-USP University of São Paulo Sao Carlos Brazil Department of System and Control Technological Institute of Aeronautics Sao Jose dos Campos Brazil Computer Science Departament Pontifical University Catholic of Goías Goiania Brazil

ISBN: (纸本)9781479904532

This paper presents a multi-objective formulation for variable selection in calibration problems. The prediction of protein concentration on wheat is obtained by a linear regression model using variables obtained by a spectrophotometer device. This device measure hundreds of correlated variables related with physicochemical properties and that can be used to estimate the protein concentration. The problem is the selection of a subset informative and uncorrelated variables that help the minimization of prediction error. In this work we propose the use of two objectives in this problem: the prediction error and the number of variables in the model, both related to linear equations system stability. We proposed a multi-objective formulation using two multi-objective algorithms: the NSGA-II and the SPEA-II. Additionally we propose a final decision maker method to choice the final subset of variables from the Pareto front. For the case study is used wheat data obtained by NIR spectrometry where the objective is the determination of a variable subgroup with information about protein concentration. The results of traditional techniques of multivariate calibration as the Successive Projections Algorithm (SPA), Partial Least Square (PLS) and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 45%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares (PLS).

关键词： Mathematical model Genetic algorithms Predictive models Prediction algorithms Input variables Calibration Equations

来源：评论

学校读者我要写书评

暂无评论

New approach for e-learning evaluation

New approach for e-learning evaluation

引用

2012 7th International Forum on Strategic Technology, IFOST 2012

作者： Tudevdagva, Uranchimeg Hardt, Wolfram Evgeny, Tsoy Grif, Mikhail Power Engineering School Mongolian University of Science and Technology Ulaanbaatar Mongolia Department of Computer Science Chemnitz University of Technology Chemnitz Germany Department of Automated Control System Novosibirsk State Technical University Novosibirsk Russia

ISBN: (纸本)9781467317702

This paper deals with a new approach for evaluation of e-learning programs. Based on methods of general measure theory an evaluation model is developed which can be used for assessment of complex logical target structures in context of e-learning programs. Basic idea of presented method is the embedding of aims to be reached in an adapted logical structure which contains the key and sub targets of evaluation. For such structures a measure theoretical scoring model is developed. It is described how to given observation data, obtained with an adjusted assessment checklist, a score value for evaluation of an e-learning program can be computed. The presented model is very versatile. By the measure theoretical background the evaluation method becomes open, comprehensible and traceable. © 2012 IEEE.

关键词： E-learning

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：