This creative platform is about an interactive music platform. The main purpose is to enable users to integrate musicinteract to achieve the effect of a music theory that combines the basic rhythm of training with the basics of learning.

The system consists of a racket sensor, a smartphone App, and the IoT shuttlecock serving machines. Data of the 3-axis inertial sensor will be sent to the smartphone via Bluetooth for analysis. The App can recognize 7 stroke activities, including clear, cut, drive, lob, rush, net play, and smash using machine learning algorithms, while the speed, force, and stroke times are recorded at the same time. The App also enables the user to set parameters of the serving machines for assigning shot placements and serving schedules.

The interpretation of next generation sequencing is a big challenge. In order to improve the molecular diagnosis of the patient, we developed the AI_Variant prioritizer, a machine learning based variant prioterization system that can help to prioritize candidate variants for human disease. This module highlighted the possible disease causing variants to help clinician to increase the disease diagnostic yield and decrease the load of manpower.

The main purpose of this invention is to provide a training system with the surrounding photographing unit, the display unit,a force platform. The system can immediately capture the motion of the user from various angles,measure the force of the user from both legs, in order to provide the useful biofeedback information to coachesathletes.

The smart glove was made by soft force sensor with the multi-walled carbon nanotube cast in the mesh structurecombined with an interdigitated electrode together, then used AC/DC conversionspace calculation to establish the interactive virtual reality(VR) somatosensory system under the wireless. The recipient can achieve the same feedback as the demonstrator＇s behaviorskills in VR.

　　This pressure-detection smart baseball obtains applied force, dynamicinertial features of pitcher during pitching. Through the connection between wireless moduleterminal, data will be transferredprovides vibration as a pitching signal. Also, precise adjustment is achievable through back-end analysiscustomized training formulation, which enhances pitching ability, optimizes training,improves pitcher＇s condition assessment.

To train neurosurgery internsincrease their confidencesurgical skills, we employed 3D printing, mold design,casting technology to develop medical simulators. The simulators allow students to adjust the angle of the head based on the location of the angioma (brain tumor), perform a craniotomy, move the soft tissue of the brain aside using forceps, locate the angioma (brain tumor),clip the angioma (remove the brain tumor) using medical instruments,complete the entire training while artificial blood is flowing through the simulator.

Assisted by in-house AI deep compression toolchain (ezLabel, ezModel, ezQUANT, ezHybrid-M), the proposed technology supports automatic AI model designoptimization with the integrated performance of 120x model size reduction70x power reduction in 2D CNN model,develops a world-first 1/2/4/8-bit CNN model realized by the developed high efficiency Hybrid fixed point CNN NPU (Hybrid-NPU), which has been verified in Xilinx ZCU102 FPGAachieves the performance up to 2.5 TOPS(8-b)/ 20TOPS(1-b)@28nm technology running at 550MHz4TOPS/W energy efficiency.