"The primary goal of this project is to establish a complete hospital-based liver cancer database, profiles for data feature extraction,develop different cancer, prediction models. A Medical AI program to predict the poster treatment (including operationradiofrequency ablation) recurrence of liver cancer will be established. The program system will assist doctors in the medical decision, identify high-risk patients,adjust clinical follow-up programs."

This proposed technique aims for solving the key challenge in the chemical, pharmaceutical,biomedical raw material industries: how to develop effectiveeconomically feasible downstream processing. We presented an integrated continuous extractionphase separation reactor, which consist of a unique helix wire to precisely control the liquid-liquid interface. It provides R&Dindustry with a complete solution at production sites to quickly screen downstream processing with different permutationscombinationsgreatly reduces time costsexpensive materials used.

Our IoT of food allergen detection system has high sensitivityspecificity by magnetic nano-beads with advanced material coating. This advanced material successful inhibit biofouling in biosensor system. Other than this, Our system combine nanotechnology, biotechnology, IoTAI model. Device is small any easily carry to anywhere.

During the pandemic, it is necessary to reduce contactwear masks, but identification is still required. The original technology includes the development of inertial measurement units beneath the walking surface, real-time detection of gait,accurate predictions of gait parameters with machine learning models. Most importantly, our technology can use a small number of samples (only one footstep data) for identifications. Non-contact, non-monitoring,rapid identification are going to be the future applications in smart buildings/homes.

The system, “Occluded Resistant Face DetectionRecognition System”, contains different scale detectors for calculating face locations. Additive angular margin loss is added into the training phase for achieving high efficiencyaccuracy. The system can achieves 80 accuracy under the 50 face occluded.

Two indoor positioning techniques are presented. The first one is a monocular vision based landmark matching scheme for identifying absolute indoor locations. The scheme requires just one photo shotmatches it with a landmark database to obtain the location. The landmark data base can be easily adapted to different fields. The proposed scheme is highly computing efficient. The correct landmark identification rate is up to 90the positioning accuracy is 1.5m. The second one is a relative positioning scheme based on ultra-wide band (UWB) technology. It can be employed on an automatic guided vehicle (AGV) to implement the trailing function. The accuracy of positioning is 80cm.

We constructed a model to differentiate different neurodegenerative diseases by using blood-based biomarkers. Linear Discriminant Analysis (LDA) was used to reduce dimensionsMICE (Multivariate Imputation by Chained Equations) was used for missing value treatmentchoose CART model to predict missing value imputation. This machine learning model would be used for early dectection of neurodegenerative diseases.