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未來科技館 Search Result 86
    • DeepFIND

      DeepFIND

      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.
    • Out of the Lab, a Scientist Dig out the Merit of AI.

      Out of the Lab, a Scientist Dig out the Merit of AI.

      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.
    • EditCell Virology Platform

      EditCell Virology Platform

      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.
    • New insight into the brain: Optical imaging/stimulationspiking neural circuit models

      New insight into the brain: Optical imaging/stimulationspiking neural circuit models

      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
    • A green production of waste carbon to graphite(graphene) nanopowders

      A green production of waste carbon to graphite(graphene) nanopowders

      The invention belongs to the field of low-temperature electrochemical graphitization and is improved by the FFC-Cambridge Process. In comparison to the traditional process, the invention can be at a low temperature of 850oC and shorter process time. This strategy can convert carbon blacks into high-value graphite (graphene). The method is simple, low temperature, without adding catalyzer, and low-cost. The products have a wide range of applications such as energy storage, catalysis, absorption, separation, processing metal cutter, precision die, aeronautics, and astronautics.
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