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The thumb is the first digit of the hand. (Wikipedia.org)






Conferences related to Thumb

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2014 IEEE International Conference on Robotics and Automation (ICRA)

Robotics and Automation


2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014)

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  • 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013)

    Papers are solicited in all related areas in robotics and intelligent systems. Proposals for tutorials and workshops, as well as organized/special sessions are also welcome to address the emerging areas and innovative applications of new technologies.

  • 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012)

    The 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012) will be held in Vilamoura-Algarve, Portugal, during October 7-11, 2012. The theme of the conference will be Robotics for Quality of Life and Sustainable Development. Papers are solicited in all related areas in robotics and intelligent systems. Proposals for tutorials and workshops, as well as organized/special sessions are also welcome to address the emerging areas and innovative applications of new technologies.

  • 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011)

    The 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011) will be held in San Francisco, California, USA, during September 25-30, 2011. The theme of the conference will be Human- Centered Robotics, and its format will feature innovations in the form of interactive multimedia presentations and special-topic symposia celebrating 50 years of robotics.

  • 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)

    Papers are solicited in all related areas in robotics and intelligent systems. Proposals and tutorials and workshops, as well as organized/special sessions are also welcome to address the emerging areas and innovative applications of new technologies.

  • 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009)

    Papers are solicited in all related areas in robotics and intelligent systems. Proposals for tutorials and workshops, as well as organized/special sessions are also welcome to address the emerging areas and innovative applications of new technologies.

  • 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2008)

    IROS 2008 serves as an international forum for robotics researchers to discuss and exchange their ideas on technical problems and their solutions. Conference includes technical presentations, tutorials and workshops, exhibits, posters, competitions, plenary session, and panel discussions.

  • 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2007)

  • 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2006)

  • 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005)


2013 46th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)

Forum for presenting and discussing innovative microarchitecture ideas and techniques foradvanced computing and communication systems, providing a close interaction between academic researchers andindustrial designers and bringing together researchers in fields related to microarchitecture, compilers, chips, andsystems for technical exchange on traditional microarchitecture topics and emerging research areas.

  • 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)

    Forum for presenting and discussing innovative microarchitecture ideas and techniques for advanced computing and communication systems, providing a close interaction between academic researchers and industrial designers and bringing together researchers in fields related to microarchitecture, compilers, chips, and systems for technical exchange on traditional microarchitecture topics and emerging research areas.

  • 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)

    MICRO-43 is the premier forum for presenting, discussing and debating new and innovative microarchitecture ideas and techniques for advanced computing and communication systems. The goal of this symposium is to bring together researchers in fields related to processor architecture, compilers, and systems, for technical exchange on traditional MICRO topics as well as new emerging research areas.

  • 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)

    MICRO is the premier forum for presenting, discussing and debating new and innovative microarchitecture ideas and techniques for advanced computing and communication systems. The goal of this symposium is to bring together researchers in fields related to processor architecture, compilers, and systems, for technical exchange on traditional MICRO topics as well as new emerging research areas.

  • 2008 41st IEEE/ACM International Symposium on Microarchitecture (MICRO)

    The 41st International Symposium on Microarchitecture is the premier forum for presenting, discussing, and debating new and innovative microarchitecture ideas and techniques for advanced computing and communication systems. This symposium brings together researchers in fields related to microarchitecture, compilers, and systems for technical exchange on traditional microarchitectural topics and emerging research areas.

  • 2007 40th IEEE/ACM International Symposium on Microarchitecture (MICRO)

    MICRO is the premier forum for presenting, discussing and debating new and innovative microarchitecture ideas and techniques for advanced computing and communication systems. The goal of this symposium is to bring together researchers in fields related to processor architecture, compilers, and systems, for technical exchange on traditional MICRO topics as well as new emerging research areas.

  • 2006 39th IEEE/ACM International Symposium on Microarchitecture (MICRO)

  • 2005 38th IEEE/ACM International Symposium on Microarchitecture (MICRO)


2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR 2013)

The conference presents the latest results from world leading research labs and clinics in the field of rehabilitation robotics. A special focus is on clinical evaluation and promotion of interaction between engineers, clinicians and therapists.


2012 IEEE 19th International Conference on Industrial Engineering and Engineering Management (IE&EM 2012)

The conference's objective is to gather the wisdom of industrial engineering to promote the innovation and development of manufacturing industry while it's themes are desired to stay close to China's economic construction and cutting edge breakthroughs in IE & EM, with a view of seizing the opportunities of economic development in China and the world.

  • 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management (IE&EM 2011)

    Advanced Decision Analysis and Methods ,Knowledge Management,Engineering Economy and Cost Analysis,Global celebaration and Communication,Global Information System Integration and Interaction,Global Manufacturing and Management,Information and Product Lifecycle Management,Intelligent Systems,Manufacturing Systems,Operations Research,Production Planning and Control,Quality Control and Management,Reliability and Maintenance Engineering,Safety, Security and Risk Management,Service Management,Systems Modeli

  • 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management (IE&EM 2010)

    Advanced Decision Analysis and Methods ,Knowledge Management,Engineering Economy and Cost Analysis,Global celebaration and Communication,Global Information System Integration and Interaction,Global Manufacturing and Management,Information and Product Lifecycle Management,Intelligent Systems,Manufacturing Systems,Operations Research,Production Planning and Control,Quality Control and Management,Reliability and Maintenance Engineering,Safety, Security and Risk Management,Service Management,Systems Modeling/S

  • 2009 IEEE 16th International Conference on Industrial Engineering and Engineering Management (IE&EM 2009)

    The 16th conference of IE&EM will promote development of methods and applications in all fields of industrial engineering and engineering management, and provide an excellent opportunity for researchers to discuss modern approaches and techniques for IE systems and their applications, as an academic platform of the experience and outcome exchange.


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Hand kinematics estimation to control prosthetic devices: a nonlinear approach for simultaneous and proportional estimation of 15 DoFs

Parviz Ghaderi; Saeed Karimimehr; Mehran Emadi Andani; Hamid Reza Marateb 2015 22nd Iranian Conference on Biomedical Engineering (ICBME), 2015

The new generation of prosthetic devices are based on simultaneous and proportional estimation of kinematics from recorded surface electromyographic (sEMG) signals of the desire limb. In this paper we applied Generalized Regression Neural Network (GRNN), a non-linear system identification approach, to estimate fingers kinematics (15 Degrees of Freedom) from sEMG signals. The parameters were optimized based on training data of ...


Hand pose recognition by using masked Zernike moments

JungSoo Park; Hyo-Rim Choi; JunYoung Kim; TaeYong Kim 2014 International Conference on Computer Vision Theory and Applications (VISAPP), 2014

In this paper we present a novel way of applying Zernike moments for image matching. Zernike moments are obtained from projecting image information under a circumscribed circle to Zernike basis function. However, the problem is that the power of discrimination may be reduced because hand images include lots of overlapped information due to their shape characteristic. On the other hand, ...


High performance anthropomorphic robot hand with grasp force magnification mechanism

Takeshi Takaki; Toru Omata 2009 IEEE International Conference on Robotics and Automation, 2009

This paper presents a lightweight 328 g anthropomorphic robot hand that can exert a large grasp force. We propose a combination mechanism of a flexion- drive and a force-magnification-drive for a cable driven multifingered robot hand. The flexion-drive consisting of a feed screw enables quick motion of its fingers and the force-magnification-drive consisting of an eccentric cam, a bearing and ...


A study of factors influencing media choice in Norwegian organizations

L. Chidambaram; C. E. Moe; D. H. Olsen Proceedings of the Thirty-First Hawaii International Conference on System Sciences, 1998

This paper presents the results of a survey used to collect data about media choice from 228 respondents in Norwegian organizations. In this study, we focus on the role of three factors in influencing media choice: (a) task type, (b) experience with different media and (c) users perceptions of media. Results indicate that traditional media (such as face-to-face meetings and ...


Pulse oximetry of body cavities and organs

P. A. Kyriacou; M. Hickey; J. P. Phillips 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013

The focus of this paper will be in the development and in vivo applications of new custom made photoplethysmographic (PPG) and pulse oximetry optical and fiber optic sensors and instrumentation in an effort to investigate their suitability in the estimation of blood oxygen saturation and their contribution in the assessment of organ/tissue perfusion and viability. The paper describes the development ...


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eLearning

Hand kinematics estimation to control prosthetic devices: a nonlinear approach for simultaneous and proportional estimation of 15 DoFs

Parviz Ghaderi; Saeed Karimimehr; Mehran Emadi Andani; Hamid Reza Marateb 2015 22nd Iranian Conference on Biomedical Engineering (ICBME), 2015

The new generation of prosthetic devices are based on simultaneous and proportional estimation of kinematics from recorded surface electromyographic (sEMG) signals of the desire limb. In this paper we applied Generalized Regression Neural Network (GRNN), a non-linear system identification approach, to estimate fingers kinematics (15 Degrees of Freedom) from sEMG signals. The parameters were optimized based on training data of ...


Hand pose recognition by using masked Zernike moments

JungSoo Park; Hyo-Rim Choi; JunYoung Kim; TaeYong Kim 2014 International Conference on Computer Vision Theory and Applications (VISAPP), 2014

In this paper we present a novel way of applying Zernike moments for image matching. Zernike moments are obtained from projecting image information under a circumscribed circle to Zernike basis function. However, the problem is that the power of discrimination may be reduced because hand images include lots of overlapped information due to their shape characteristic. On the other hand, ...


High performance anthropomorphic robot hand with grasp force magnification mechanism

Takeshi Takaki; Toru Omata 2009 IEEE International Conference on Robotics and Automation, 2009

This paper presents a lightweight 328 g anthropomorphic robot hand that can exert a large grasp force. We propose a combination mechanism of a flexion- drive and a force-magnification-drive for a cable driven multifingered robot hand. The flexion-drive consisting of a feed screw enables quick motion of its fingers and the force-magnification-drive consisting of an eccentric cam, a bearing and ...


A study of factors influencing media choice in Norwegian organizations

L. Chidambaram; C. E. Moe; D. H. Olsen Proceedings of the Thirty-First Hawaii International Conference on System Sciences, 1998

This paper presents the results of a survey used to collect data about media choice from 228 respondents in Norwegian organizations. In this study, we focus on the role of three factors in influencing media choice: (a) task type, (b) experience with different media and (c) users perceptions of media. Results indicate that traditional media (such as face-to-face meetings and ...


Pulse oximetry of body cavities and organs

P. A. Kyriacou; M. Hickey; J. P. Phillips 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013

The focus of this paper will be in the development and in vivo applications of new custom made photoplethysmographic (PPG) and pulse oximetry optical and fiber optic sensors and instrumentation in an effort to investigate their suitability in the estimation of blood oxygen saturation and their contribution in the assessment of organ/tissue perfusion and viability. The paper describes the development ...


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IEEE-USA E-Books

  • Backmatter

    Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

  • Introduction

    This chapter contains sections titled: Advantages and Disadvantages of Modeling and Simulation Comparison of Homebrew Models and Simulation Tools Common Pitfalls of Modeling and Simulation and Rules of Thumb An Overview of Common M&S Tools An Overview of the Rest of This Book

  • Optimal Strategies and Heuristics for Ecological Search Problems

    All animals, including humans, search for a variety of different things in their natural environment, from food to mates to a suitable place to live. Most types of search can be represented as stopping problems of varying complexity, in which the animal has to decide when to stop searching and accept the current option. All forms of search take time, and in solving a stopping problem the animal has to trade off this time cost against the expected benefits of continuing to search. This chapter discusses two main approaches to predicting search behavior: the optimality approach and the heuristics approach. The optimality approach identifies the best possible solution to a search problem and thereby sets an upper bound to what natural selection can achieve. The heuristics approach considers simple decision algorithms, or "rules of thumb," which animals may use to implement efficient search behavior. Although few studies have tried to integrate these functional and mechanistic perspectives, they are likely to provide complementary insights. Often, the form of an optimal strategy suggests which kinds of heuristics might be expected to evolve. Stopping problems may be simple, repeated, or embedded in other stopping problems. For example, if searchers assess the value of each encountered option by examining a series of cues, the assessment process can be considered as another stopping problem. When the searcher is uncertain about the environment it is in, its previous experiences during search can strongly influence the optimal behavior. Where a limited number of items can be accepted, as in mate search, a key constraint is whether the searcher can return to previously encountered items. Some search problems are complicated by the fact that the encountered items are themselves searching. The chapter concludes with a discussion of some open questions for future research.

  • No title

    In teaching an introduction to the finite element method at the undergraduate level, a prudent mix of theory and applications is often sought. In many cases, analysts use the finite element method to perform parametric studies on potential designs to size parts, weed out less desirable design scenarios, and predict system behavior under load. In this book, we discuss common pitfalls encountered by many finite element analysts, in particular, students encountering the method for the first time. We present a variety of simple problems in axial, bending, torsion, and shear loading that combine the students' knowledge of theoretical mechanics, numerical methods, and approximations particular to the finite element method itself. We also present case studies in which analyses are coupled with experiments to emphasize validation, illustrate where interpretations of numerical results can be misleading, and what can be done to allay such tendencies. Challenges in presenting the necessary mix f theory and applications in a typical undergraduate course are discussed. We also discuss a list of tips and rules of thumb for applying the method in practice. Table of Contents: Preface / Acknowledgments / Guilty Until Proven Innocent / Let's Get Started / Where We Begin to Go Wrong / It's Only a Model / Wisdom Is Doing It / Summary / Afterword / Bibliography / Authors' Biographies

  • Design Tools

    This chapter contains sections titled: Conceptual Tools, Sun Charts, Rules of Thumb, Advanced Daylighting Design Tools, Tools for Estimating Thermal Performance, Tools for Estimating Thermal Comfort, Comprehensive Tools, Future Directions, References

  • Index of Algorithms, Figures, and Tables

    Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

  • No title

    This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data. One reason for that is data sparsity, i.e., the limited amounts of data we have available in NLP. However, in most real- world NLP applications our labeled data is also heavily biased. This book introduces extensions of supervised learning algorithms to cope with data sparsity and different kinds of sampling bias. This book is intended to be both readable by first-year students and interesting to the expert audience. My intention was to introduce what is necessary to appreciate the major challenges we face in contemporary NLP related to data sparsity and sampling bias, without wasting too much time on details about supervised learning algorithms or particular NLP applications. I use text classification, part-of- speech tagging, and depen ency parsing as running examples, and limit myself to a small set of cardinal learning algorithms. I have worried less about theoretical guarantees ("this algorithm never does too badly") than about useful rules of thumb ("in this case this algorithm may perform really well"). In NLP, data is so noisy, biased, and non-stationary that few theoretical guarantees can be established and we are typically left with our gut feelings and a catalogue of crazy ideas. I hope this book will provide its readers with both. Throughout the book we include snippets of Python code and empirical evaluations, when relevant.

  • Algorithmic Extensions

    Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

  • Power and speed

    This chapter contains sections titled: Introduction, Air resistance, Conclusions on air resistance, Slope and rolling resistance, Steady-speed power equation, Rules of thumb, Acceleration, Measurement of on-road power, Discussion of insights regarding power and drag, Bicycles versus other vehicles, Human versus animal muscle power, Bicycling versus other human- powered locomotion, Notes, References

  • Quantized FIR Filter Design Using Compensating Zeros

    This chapter contains sections titled: Quantized Filter Design Figures of Merit Filter Structures Example 1: A Windowed FIR Filter Simple Quantization Compensating Zeros Quantization Example 2: A Biorthogonal FIR Filter Design Rules-of-Thumb Conclusions References



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