Robot intelligence technology and applications : 6th International Conference, RiTA 2018, Kuala Lumpur, Malaysia, December 16-18, 2018 : revised selected papers

This book constitutes revised selected papers from the 6th International Conference on Robot Intelligence Technology and Applications, RiTA 2018, held in Putrajaya, Malaysia, in December 2018. The 20 full papers presented in this volume were carefully reviewed and selected from 80 submissions. The papers present studies on machine learning; optimization; modelling and simulation; path planning; neural networks; landmark recognition; and reinforcement learning. -- Provided by publisher Front Matter ....Pages i-xiii Data-Driven Neuroendocrine-PID Tuning Based on Safe Experimentation Dynamics for Control of TITO Coupled Tank System with Stochastic Input Delay (Mohd Riduwan Ghazali, Mohd Ashraf Ahmad, Raja Mohd Taufika Raja Ismail)....Pages 1-12 Neuro-Fuzzy Sampling: Safe and Fast Multi-query Randomized Path Planning for Mobile Robots (Weria Khaksar, Md Zia Uddin, Jim Torresen)....Pages 13-27 Hierarchical Attention Networks for Different Types of Documents with Smaller Size of Datasets (Hon-Sang Cheong, Wun-She Yap, Yee-Kai Tee, Wai-Kong Lee)....Pages 28-41 Social Robot Intelligence and Network Consensus (João Silva Sequeira)....Pages 42-54 UDLR Convolutional Network for Adaptive Image Denoiser (Sungmin Cha, Taesup Moon)....Pages 55-61 Robust Feedback Controller Design Using Cuckoo Search Optimization to Maximize Stability Radius (Mahmud Iwan Solihin, Rini Akmeliawati)....Pages 62-75 Chaos-Based Reinforcement Learning When Introducing Refractoriness in Each Neuron (Katsuki Sato, Yuki Goto, Katsunari Shibata)....Pages 76-84 Integration of Semantic and Episodic Memories for Task Intelligence (Ue-Hwan Kim, Jong-Hwan Kim)....Pages 85-100 Human Robot Social Interaction Framework Based on Emotional Episodic Memory (Won-Hyong Lee, Sahng-Min Yoo, Jae-Woo Choi, Ue-Hwan Kim, Jong-Hwan Kim)....Pages 101-116 Convolutional Neural Network-Based Collaborative Filtering for Recommendation Systems (Yat Hong Low, Wun-She Yap, Yee Kai Tee)....Pages 117-131 A Pedestrian Dead Reckoning System with Error Correction by Landmark Recognition (Khanh Nguyen-Huu, Seon-Woo Lee)....Pages 132-143 Effective Indoor Robot Localization by Stacked Bidirectional LSTM Using Beacon-Based Range Measurements (Hyungtae Lim, Hyun Myung)....Pages 144-151 Track Management for Distributed Multi-target Tracking in Sensor Network (Woo-Cheol Lee, Han-Lim Choi)....Pages 152-163 Deregulating the Electricity Market for the Peninsula Malaysian Grid Using a System Dynamics Approach (Darren Teck Liang Lee, Andrew Huey Ping Tan, Eng Hwa Yap, Kim-Yeow Tshai)....Pages 164-188 ArUcoRSV: Robot Localisation Using Artificial Marker (Izwan Azmi, Mohamad Syazwan Shafei, Mohammad Faidzul Nasrudin, Nor Samsiah Sani, Abdul Hadi Abd Rahman)....Pages 189-198 Spike Encoding Modules Using Neuron Model in Neural Networks (Yeeun Kim, Seunghee Lee, Wonho Song, Hyun Myung)....Pages 199-206 The Classification of EEG Signal Using Different Machine Learning Techniques for BCI Application (Mamunur Rashid, Norizam Sulaiman, Mahfuzah Mustafa, Sabira Khatun, Bifta Sama Bari)....Pages 207-221 The Identification of Oreochromis niloticus Feeding Behaviour Through the Integration of Photoelectric Sensor and Logistic Regression Classifier (Mohamad Radzi Mohd Sojak, Mohd Azraai Mohd Razman, Anwar P. P. Abdul Majeed, Rabiu Muazu Musa, Ahmad Shahrizan Abdul Ghani, Ismed Iskandar)....Pages 222-228 Motion Planning to Reduce the Thrust of Underwater Robot Using Null-Space Compliance (Junbo Chae, Youngeon Lee, Yeongjun Lee, Hyun-Taek Choi, Tae-Kyeong Yeu)....Pages 229-235 Match Outcomes Prediction of Six Top English Premier League Clubs via Machine Learning Technique (Rabiu Muazu Musa, Anwar P. P. Abdul Majeed, Mohd Azraai Mohd Razman, Mohd Ali Hanafiah Shaharudin)....Pages 236-244 Back Matter ....Pages 245-245 This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.