未來科技館

Artificial Intelligence Automatic Sputum Microscopy System AIASMS: AIASMS can automatically shoot images from sputum smear samples and identify Mycobacterium tuberculosis(MTB). AIASMS can find the most suitable depth for shooting images and then automatically shoot images under the microscope through auto-focusing. These images will be stored in the cloud database. Meanwhile, AIASMS detect whether the sputum smear contains MTB. AIASMS can accurately label the location of the TB. The sensitivity and specificity can reach 90% and 99% respectively. We also cooperate with three hospitals in the northern, central, and southern regions of Taiwan to conduct blind testing, and the sensitivity can be more than 90%. AIASMS can also distinguish between MTB and Non-tuberculous mycobacteria (NTM). Finally, n the expansion of technology, we have extended the identification of the acid-resistant staining to the identification of gram staining, so that our system can widely identify a variety of bacteria.

div style="text-align: justify"Taiwan was once the shrimp capital of the world. Though just a small island, the technology, abundance,reputation was globally known. Over time, the changes in water qualitythe environment led to lessless shrimp. AI may be the innovative solution needed to revive the industry./div

As artificial intelligence rapidly develops and enhances human’s quality of life, another cause for concern is the dangers and possible threats to humanity. “Moral judgement” will be a big issue that needs to be addressed as these intelligent machines become more and more prevalent in society. As with any new technologies, the topic of applied ethics often arises. So, the extension of that is AI ethics issues.

Taiwan was formerly the Shrimp Capital of the World. With the changing of the timesincreasingly updated technology, AI smart farming is the new milestone for Taiwan’s agriculturefisheries.

As artificial intelligence rapidly developsenhances human’s quality of life, another cause for concern is the dangerspossible threats to humanity. “Moral judgement” will be a big issue that needs to be addressed as these intelligent machines become moremore prevalent in society. As with any new technologies, the topic of applied ethics often arises. So, the extension of that is AI ethics issues.

High entropy materials were proposeddeveloped by Professor Jien-Wei Yeh in 1995. He named, defined,elucidated “High-Entropy Alloys,” as well as established High-Entropy Materials Center to develop critical materials for smart machine, green technology, biomedical technology,national defense. Alloys with high strength, corrosion resistance,anti-bacterial capability are also developed for manufacturing knives, door handles, handrails, etc. to prevent infection during the post-epidemic era.

This project collaborates with the international team to collect a very large-scale Chinese emotional corpus. In terms of technology, the fairness of speech emotion recognition is also discussed to solve social issues that may be encountered regarding the usability of emotion recognition. Among them, it is found that the database annotations are all labeled with the unfair perspective of men and women, which leads to biases in the trained model. In order to solve this problem, there have been preliminary achievements in the technological development of fairness, and will be submitted in the near future.

The world is moving towards a more aged society, with Asia being at the most rapid pace. Since 2018, Taiwan has also officially
become an Aged Society. It is estimated that by 2026 it will become a Super-Aged Society. As aging is inevitable, it is important to pay attention to health maintenance and upkeep.

Epidermolysis bullosa (EB) is an inherited blistering skin diseaseis also one of the most "urgent, severe, difficultrare" diseases. Since there are at least 21 disease-causing genes involved in EB with markedly variable manifestations, it is particularly difficult for accurate diagnosis. In recent years, next generation sequencing (NGS) has been widely applied in the genetic diagnosis of rare hereditary disorders. The EB team in NCKU established the protocol of EB diagnosis by combining NGSvarious tools of pathologymolecular studies. Till now, we have completed the genetic diagnosis for more than 50 Taiwanese EB patients.

This integrated research project follows the Taiwan's 2030 Science & Technology Vision and takes LOHAS community and inclusive technology as the major research direction. We aim to develop trustable AI technologies, and introduce them to future smart services. That will realize the development of human-centric smart technology, and strengthen the governance and application of emerging technologies. The integrated project consists of 7 sub-projects led by PIs from National Taiwan University, National Tsing-Hua Universiy and Academia Sinica and composed of top AI technological teams. These sub-projects are divided into 3 clusters, including machine learning (sub-projects 1 and 2), computer vision (sub-projects 3 and 4), and human-centric computing (sub-projects 5, 6 and 7). We will deal with the issues of bias, fairness, transparency, explainability, traceability, and so on, from the aspects of data collection, technology, and application landing. Each sub-project will implement specific smart services to reflect the benefits and practical applications of the developed technologies. The NTU Joint Research Center for AI Technology and All Vista Healthcare, an AI Innovation Research Center supported by MOST, is responsible for management, planning, and execution of the integrated research project. We will propose a plan that can be generalized and applied to the intelligent service industry.

Did you know that Tuberculosis is still a highly infectious disease affecting Taiwan and is one of the top 10 causes of death worldwide? TB is an airborne illness that can be contracted by breathing in germs. Early TB detection greatly reduces the risk of spreading the illness.

Quote:br / “It is worth giving up some things because of dream pursuing” Professor SHOU-DE, LIN  at the department of computer scienceInformation Engineering in National Taiwan University, Chief Machine Learning Scientist in Appier, said “An escape from comfort zone to seek new challenges makes my life become more colorful.”br /  br / Content:br /  br / Given qualified for being as the freshman of National Taiwan University College of Medicine, Professor Lin chose the department of electrical engineering in NTU as the first priority in Joint College Entrance Examination (JCEE). Though the undergraduate education  did not cultivate him the passion on the field of electrical engineering, Professor Lin said, however, he was still recommended for further study at the graduate institute of electronics engineering in NTU due to his talentsoutstanding academic performance.

By using the machine learning algorithms, this study developed a risk stratification model for predicting the occurrence of in-hospital cardiac arrest (IHCA) events in patients admitted from the emergency department with COVID-19 and pneumonia. The results showed that the model's performance is better than by using the National Early Warning Score (NEWS).

This project goes on developing embedded AI deep learning technology focus on the ADAS/Self-driving applications. We develop the technology from five aspects, including automatic object labeling toollabeled datasets, deep learning softwarehardware technology development, various ADAS/Self-driving object detectionbehavior prediction technology, self-driving control technology as well as virtual simulation environment establishment for ADAS/Self-driving applications.

The core concept of the decision support system is to establish machine learning-based predictive models and enable their interpretability to support physicians making clinical decisions in practice.

The NeRF-based technique describes a super-fast convergence approach to reconstructing the per-scene radiance field from a set of images that capture the scene with known poses.

This project goes on developing embedded AI deep learning technology focus on the ADAS/Self-driving applications. We develop the technology from five aspects, including automatic object labeling toollabeled datasets, deep learning softwarehardware technology development, various ADAS/Self-driving object detectionbehavior prediction technology, self-driving control technology as well as virtual simulation environment establishment for ADAS/Self-driving applications.

(1) Ｇel-type solid electrolytesAll solid-state electrolytes for Lithium Ion Battery (LIBs)(2) Fabrication of dye-sensitized solar cells by printing processits applications on Internet-of-Things (IoT) - MOST 2019 Award(3) Silicon-carbon coating anode materials for LIBs: SiLican startup company growthglobal business layout(4) Power enhanced Intermediate Temperature Solid State Fuel Cell (SOFC)(5) Worldwide highest conversion efficiency (19.4) perovskite solar cells(6) Industrial linkingProduct design : LevioPoleSmart motorcycle suitcase

Recently, Deep Reinforcement Learning (DRL) has been applied to many AI applications. One of the successful achievements is the AlphaZero, called the Zero method in this project, was presented to learn without human knowledgesurprisingly surpass all the human playersall the AI programs.

With the development of science and technology, more and more kinds of electronic products come out, and the demand for charging is becoming more and more important. The compound annual growth rate of wireless charging exceeds 40％. For the demand for wireless charging equipment, the nitride developed by our team Gallium power transistors can achieve high-efficiency wireless charging through power levels ranging from 25 watts to 2500 watts and meet fast charging. It is one of the best applications for exhibiting the characteristics of gallium nitride transistors.

The "Viral Vaccine Cell Production Technology Platform" of this exhibition is based on 1. Host cellvirus matchcolonization technology 2. Cell-expressed virus receptor technology 3. Blocking antiviral mechanism of host cell 4. Immortalization technology of host cell 5. Serum-free suspension cell culture technology to produce high-immunity virus vaccine strains containing intact virus antigens.

1. Identification of host factor, which is required for virus replication, by “EditCell Virology Platform”.2. The host factor will be as a target to develop antivirals.3. The antiviral effects of the candidates can be validated in vitroin vivo.4. Two FDA-approved drugs are repurposed for COVID-19 treatment.

A virus NT was performed in a biosafety level 3 laboratory to determine the titers. A SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) was designed to detect neutralizing antibodies in the serum, based on the binding affinity of SARS-CoV-2 viral protein 1 and viral protein 2 to antibodies. ELISA results viral protein 1 and 2, generated comparable neutralizing antibody titers. The results analyzed by spline regression and two-variable generalized additive model precisely reflected the real NT value. Our method can serve as a surrogate to quantify neutralizing antibody titer.

Reliability of Cu-to-Cu direct bonging: In order to realize the reliability of Cu-to-Cu direct bonding interconnects, we adopted nanotwinned Cu (nt-Cu) electroplating process to fabricate nt-Cu microbump for Cu-to-Cu direct bonding. Figure (a) is the photo of chip after bonding. Underfill (UF) dispensing was used to protect Cu microbumps. The cross-section SEM image of Cu microbump is shown in figure (b). Some chips underwent the reliability tests, including temperature cycling test (TCT) and electromigration (EM) test. To further study the failure mechanism, finite element analysis (FEA) was done to know the stress and current distribution during reliability test. This research could provide fundamental understanding for Cu-Cu joints with organic dielectric hybrid bonding.

This technology aims to automatically extract and define features from a data-driven framework of data engineering, machine learning, and ensemble learning algorithms to analyzing the big data collected from equipment sensors and quality characteristic measurement results. This technology provides prediction results of unmeasured products quality characteristics and its confident score base on the extracted feature for advanced process control.

The technology combines specific visual recognition and electrochemical quantitative detection in a single portable device, providing instant and convenient copper ion detection. The sensing sensitivity has reached the standards of Taiwan and the United States for heavy metal detection for food, human body, and environments. In use, this portable and user-friendly interface device not only makes it simple to report back to the EPA database for water quality analysis, but also it can be utilized for real-time detection from youngsters to the elderly.

div style="text-align: justify"Constructing a functional connectomeits computational model is a crucial step toward understanding the mechanisms of brain functions. To achieve this goal, we developed two correlated technologies: (1) An all- optical physiology (AOP) that is capable of millisecond volumetric imagingaccurate stimulation in living animal brains. This system allows us to establish functional connectomeneural coding with a single-cell resolution. (2) A cellular-level spiking neural circuit simulation system that is capable of tuning itself based on the input data from the AOP system. We have demonstrated our technologies in the Drosophila late visual systemwill apply them in the brains of larger species such as mice. We expect that our technologies will be able to greatly enhance our knowledge of the brain operation principles. Our 3D all-optical physiology (AOP) platform incorporates single-photon point stimulationtwo-photon high-speed volumetric recordings (Optics Letters 2019, "Editors pick"). We have demonstrated its effectiveness in studying the anterior visual pathway of fruit flies (iScience2019). In comparison, contemporary high-speed AOP platforms are limited to single-depthdiscrete multi-plane recordings that are not suitable for studying functional connections. Our high-resolution computational model is constructed based on the combination of static connectomeAOP data,is much more realistic than the existing models. Our work aids establishing in-vivo 3D functional connectomescomputational models of the brains, thus provides insight into the mechanisms of brain functions./div

The technology optimizes the antigen protein expression system, so that the structural protein Erns of classical swine fever virus (CSFV) converts insoluble proteins into soluble proteins during the production process. The breakthrough of this technology allows the antigen protein to be applied to the development of an immune attachment screening platform, as a specialized differential diagnostic reagents can distinguish between virus-infected and vaccinated pigs, which can be applied to the monitoring system of virus transmission range and vaccination

1. Demonstrate Virtual Manufacturing/AR/VR technology, integrate product designprocess planning processes (simultaneous engineering).2. 3D printing design system: Utillized Rhinos built-in calculation editor Grasshopperinfinite element method to generate complex lattice microstructures. The lattices model could directly transfer to all types additive manufacturing machine to fabricate the designs, allowing for rapid prototypinglattices shapes iteration.

The project will develop accuratepower-saving positioningtechniques. We then combine crowd/edge profiles with geographical knowledge to predict spatial-temporal trajectories of individualsgroups.