• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 109 matches

• 2021
• 
  Yuan Zhao, Hong Liu, Kaizhou Gao:
  An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model. Appl. Intell. 51(1): 100-123 (2021)
• 2020
• 
  Yean Zhu, Weiyi Xu, Guoliang Luo, Haolun Wang, Jingjing Yang, Wei Lu:
  Random Forest enhancement using improved Artificial Fish Swarm for the medial knee contact force prediction. Artif. Intell. Medicine 103: 101811 (2020)
• 
  Pascal D. König, Georg Wenzelburger:
  Opportunity for renewal or disruptive force? How artificial intelligence alters democratic politics. Gov. Inf. Q. 37(3): 101489 (2020)
• 
  Marco Lippi, Giuseppe Contissa, Agnieszka Jablonowska, Francesca Lagioia, Hans-Wolfgang Micklitz, Przemyslaw Palka, Giovanni Sartor, Paolo Torroni:
  The Force Awakens: Artificial Intelligence for Consumer Law. J. Artif. Intell. Res. 67: 169-190 (2020)
• 
  Wolfgang Quapp, Josep Maria Bofill:
  Some Mathematical Reasoning on the Artificial Force Induced Reaction Method. J. Comput. Chem. 41(7): 629-634 (2020)
• 
  Qin Tu, Yanjie Wang, Donghai Yue, Frank Agyen Dwomoh:
  Analysis on the Impact Factors for the Pulling Force of the McKibben Pneumatic Artificial Muscle by a FEM Model. J. Robotics 2020: 4681796:1-4681796:11 (2020)
• 
  Sheikh Shanawaz Mostafa, Md. Abdul Awal, Mohiuddin Ahmad, Fernando Morgado Dias:
  Design of sEMG-based clench force estimator in FPGA using artificial neural networks. Neural Comput. Appl. 32(20): 15813-15823 (2020)
• 
  Alejandro E. Rodríguez-Sánchez:
  An Artificial Neural Networks approach to predict low-velocity impact forces in an elastomer material. Simul. 96(6) (2020)
• 
  Junghan Kwon, Sohee John Yoon, Yong-Lae Park:
  Flat Inflatable Artificial Muscles With Large Stroke and Adjustable Force- Length Relations. IEEE Trans. Robotics 36(3): 743-756 (2020)
• 
  Baki Karaböce:
  Force Sensitivity Determination of Artificial Mastoid used for Audiometric Bone-Conduction Measurements. MeMeA 2020: 1-5
• 
  Fumio Ito, Akihiro Kojima, Manabu Okui, Taro Nakamura:
  Proposal for 3D-printed pneumatic artificial muscles -Effect of leaf spring stiffness on contraction amount and contraction force-. SII 2020: 1163-1167
• 
  Pasquale Coscia, Lamberto Ballan, Francesco A. N. Palmieri, Alexandre Alahi, Silvio Savarese:
  Linear Artificial Forces for Human Dynamics in Complex Contexts. Neural Approaches to Dynamics of Signal Exchanges 2020: 21-33
• 2019
• 
  Dimitrios-Sokratis Komaris, Eduardo Pérez-Valero, Luke Jordan, John Barton, Liam Hennessy, Brendan O'Flynn, Salvatore Tedesco:
  Predicting Three-Dimensional Ground Reaction Forces in Running by Using Artificial Neural Networks and Lower Body Kinematics. IEEE Access 7: 156779-156786 (2019)
• 
  Naoki Saito, Toshiyuki Satoh, Norihiko Saga:
  Effects on knee joint force from a body weight load reduction system driven by rubber-less artificial muscle. Ind. Robot 46(5): 642-649 (2019)
• 
  Alessio D'Orazio, Archimede Forcellese, Michela Simoncini:
  Prediction of the vertical force during FSW of AZ31 magnesium alloy sheets using an artificial neural network-based model. Neural Comput. Appl. 31(11): 7211-7226 (2019)
• 
  Hossein Moayedi, Abbas Rezaei:
  An artificial neural network approach for under-reamed piles subjected to uplift forces in dry sand. Neural Comput. Appl. 31(2): 327-336 (2019)
• 
  Jinlong Piao, Eui-Sun Kim, Hongseok Choi, Chang-bae Moon, Eunpyo Choi, Jong-Oh Park, Chang-Sei Kim:
  Indirect Force Control of a Cable-Driven Parallel Robot: Tension Estimation using Artificial Neural Network trained by Force Sensor Measurements. Sensors 19(11): 2520 (2019)
• 
  Shafiqul Islam, Peter X. Liu, Abdulmotaleb El-Saddik, Reem Ashour, Jorge Dias, Lakmal D. Seneviratne:
  Artificial and Virtual Impedance Interaction Force Reflection-Based Bilateral Shared Control for Miniature Unmanned Aerial Vehicle. IEEE Trans. Ind. Electron. 66(1): 329-337 (2019)
• 
  Haitao Zhao, Jibo Wei, Shengchun Huang, Li Zhou, Qi Tang:
  Regular Topology Formation Based on Artificial Forces for Distributed Mobile Robotic Networks. IEEE Trans. Mob. Comput. 18(10): 2415-2429 (2019)
• 
  Jung-Tang Huang, Tsung Ying Kuo:
  An Artificial Skin for Detecting Pressure and Shear Forces simultaneously based on Capacitive Sensor and Magnetic Sensor. AIM 2019: 266-271
• 
  Tiziana Borg, Shelley Cardona Mills, Jeremy Scerri, Clive Seguna, Kris Scicluna:
  Integrated Position and Force Sensing for Optical Artificial Skin using Machine Learning Methods. IECON 2019: 5401-5406
• 
  Yuki Onozuka, Minoru Oba, Manabu Okui, Taro Nakamura:
  Rendering friction and viscosity using a wearable 4 degrees of freedom force feedback device with magnetorheological fluid clutches and pneumatic artificial muscles. IECON 2019: 705-710
• 2018
• 
  Vahab Khoshdel, Alireza Akbarzadeh:
  An optimized artificial neural network for human-force estimation: consequences for rehabilitation robotics. Ind. Robot 45(3): 416-423 (2018)
• 
  Satoshi Maeda, Yu Harabuchi, Makito Takagi, Kenichiro Saita, Kimichi Suzuki, Tomoya Ichino, Yosuke Sumiya, Kanami Sugiyama, Yuriko Ono:
  Implementation and performance of the artificial force induced reaction method in the GRRM17 program. J. Comput. Chem. 39(4): 233-251 (2018)
• 
  Alejandro Campos, Brandon Morgan:
  The effect of artificial bulk viscosity in simulations of forced compressible turbulence. J. Comput. Phys. 371: 111-121 (2018)
• 
  Swagata Das, Yusuke Kishishita, Toshio Tsuji, Cassie Lowell, Kazunori Ogawa, Yuichi Kurita:
  ForceHand Glove: A Wearable Force-Feedback Glove With Pneumatic Artificial Muscles (PAMs). IEEE Robotics Autom. Lett. 3(3): 2416-2423 (2018)
• 
  Lei Liu, Rui Guo, Junan Wu:
  A collision-free motion planning method by integrating complexity-reduction SLAM and learning-based artificial force design. Robotics Auton. Syst. 100: 132-149 (2018)
• 
  Ho Seon Choi, Chang Hee Lee, Myounghoon Shim, Jong In Han, Yoon Su Baek:
  Design of an Artificial Neural Network Algorithm for a Low-Cost Insole Sensor to Estimate the Ground Reaction Force (GRF) and Calibrate the Center of Pressure (CoP). Sensors 18(12): 4349 (2018)
• 
  S. Doctolero, E. Veenstra, C. J. B. Macnab, P. Goldsmith:
  Hybrid Force-Position Robot Control: An Artificial Neural Network Backstepping Approach. ICCI*CC 2018: 103-110
• 
  Yuki Onozuka, Ryo Suzuki, Yasuyuki Yamada, Taro Nakamura:
  An Exoskeleton Type 4-DOF Force Feedback Device Using Magnetorheological Fluid Clutches and Artificial Muscles. AIM 2018: 869-874

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