Based on our long-term accumulated healthy brain image database, we used meta-analysismultivariate analytical algorithms to extract the cognitive biological characteristics of individual subjects. By using machine learning / artificial intelligence algorithms, these features were further calculated for capturing individual cognition according to related brain networks. This biological index could be a potential marker for evaluating individual brain health, cognitive functions,risk for neurodegenerative diseases.

The International Center for Wound RepairRegeneration of National Cheng Kung University transferredestablished Ducolege Biotechnology Co., Ltd., using Extre2Cold exclusive extraction technology to extract highly active marine collagen from Tilapia fish skin, which is type I collagen with a complete molecular structurehas a three-stranded helix structure. It is biologically activeperfectly presents the magical ability of fish skin to repair wounds. It can be widely used in biomedical materialsacademic research. It is currently first promoted in the development of high-level medical beauty repairmaintenance products, which is helpful for repairing damaged skin.

As for the proposed technology by combining the artificial bee colony algorithmthe semi-supervised extreme learning machine (ABC-SSELM), characteristic parameter normalization equations of I-V curves are tuned via low-cost data under normal operation of PV strings. The proposed ABC-SSELM method only needs 1-3 labeled data of the total dataset to save humantime cost. The accuracy of diagnosing various mixed faults can reach more than 99.84,the monitoring of dust accumulation can provide effective cleaning to increase the revenue of the solar PV power generation system.

Within 10 years, Taiwan will become a super senior society with the proportions in silver hairs of more than 20. Thus, a high-throughputsmart platform with bio-physiology-marker panels is developed for PD progression by combining the bio-medicalphysical sensors, SPRsmart circuit design, leading to a new UPDRS for a more accurateearly diagnosis of a physician.

This project aims to incorporate the state-of-the-art InformationCommunication Technologies (ICT), the Internet of Things (IoT), Big Data techniques in linking every aspect of community-based integrated long-term care (LTC), improving the efficiency of care servicesadministrative process,to realize the idea of Aging in Place emphasized in the Long-term Care Policy 2.0 in Taiwan.

The present technology provides a method for diagnosing Alzheimer＇s disease, including the following steps: detecting a blood sample taken from a human subject suspected of having Alzheimer＇s disease,the biomarker level is selected from G72 protein level, SLC7A11 mRNA expression level,a combination of the two,compared with a preset standard, wherein if the detected biomarker level in the blood sample is higher than the preset standard, the Individual humans are thought to have Alzheimer＇s disease.