Titlebook: Computational Science and Technology; 5th ICCST 2018, Kota Rayner Alfred,Yuto Lim,Patricia Anthony Conference proceedings 2019 Springer Nat

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Agent based integer programming framework for solving real-life curriculum-based university course i Malaysia Sabah, Labuan International Campus (UMSLIC). Similar to other timetabling problems, CB-UCT in UMSLIC has its own distinctive constraints and features. The proposed framework deal with the problem using a distributed Multi-Agent System (MAS) environment in which a central agent coordinates

单片眼镜

3D Face Recognition using Kernel-based PCA Approach,ar shapes due to appearance deformations, and face variations presented by facial expressions. Recognizing faces reliably across changes in facial expression has proved to be a more difficult problem leading to low recognition rates in many face recognition experiments. This is mainly due to the ten

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Mobile-Augmented Reality Framework For Students Self-Centred Learning In Higher Education Institutioutcome. Objectives: To find if visualization plays a vital role mobile learning through comparison between three groups that were analysed using SmartPLS 3 using Measurement and Structural Model, Traditional, Mobile and mobile-Augmented Reality (mAR) Groups. The analysed data were collected at five

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Computational Optimization Analysis of Feedforward plus Feedback Control Scheme for Boiler System,0. This paper proposes computational optimization analysis for designing the widely used industrial control systems - feedforward and feedback control schemes. Although several different optimal tunings for servo and regulatory control problems exist, their applications often present some challenges

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Limpid

Daily Activities Classification on Human Motion Primitives Detection Dataset,rmal person. The dataset is obtained from Human Motion Primitives Detection [1]. There is a total of 839 trials from 14 activities performed by 16 volunteers (11 males and 5 females) ages between 19 to 91 years. A wrist worn tri-axial accelerometer was used to accrue the acceleration data of X, Y an

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GROWL

Autonomous Road Potholes Detection on Video,onitoring and maintenance. Video data of roads was collected using a GoPro camera mounted on a car. Region-based Fully Convolutional Networks (RFCN) was employed to produce the model to detect potholes from images, and validated on the collected videos. The R-FCN model is able to achieve a Mean Aver

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