Titlebook: RITA 2018; Proceedings of the 6 Anwar P. P. Abdul Majeed,Jessnor Arif Mat-Jizat,Ju Conference proceedings 2020 Springer Nature Singapore Pt

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MEAN

The Influence of Coolant on Tool Deterioration of Uncoated Carbide Tools in End Milling Hardened In hardened state of Inconel 718Plus nickel-based superalloy with uncoated carbide tools in dry and wet conditions. Experimental results showed that on average, both dry and wet conditions allowed for four passes (.) before the end of tool life.

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MELD

,Learning Time Constant of?Continuous-Time Neurons with Gradient Descent,eproducing task in which a learning network is trained to generate the same oscillatory outputs from the teacher network. The training result shows that our proposed method can successfully update the time constants and suggests that leaning of time constants expands the freedom in learning and improve the learning performance.

聾子

Study on Airless Variable Rigid Wheel to Travel Rigid and Loose Surface for UGV,lexible wheel is better to traverse loose soil. If the rigid wheel traverse loose soil, the slip behavior is easy to occur. From these knowledges, we develop the variable rigid wheel to adapt two different condition. Moreover, we report the experiments using the proposed wheel.

CRAB

MPC in Space State for the Control of a Furuta Pendulum,anipulated variables and the controlled variables. The results show a great robustness of the control strategy implemented since it is able to keep the system stable, even when there are modeling errors, non-measurable perturbations and restrictions on the process variables.

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2195-4356 nto various aspects of the building blocks of Industry 4.0.GThis book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018). Reflecting the conference’s main theme, “Robotics and Machine Intelligence: Building Blocks for Industry 4.

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A Design and Training Application for Deep Convolutional Neural Networks and Support Vector Machines, in which compressed features obtained from the DCNNs are used as inputs for the SVMs. The usability and operability of the developed design and training application for DCNNs and SVMs are demonstrated and evaluated through training and classification experiments.

AER