Seika, a town located in the southern part of the Kyoto Prefecture, has a mascot anime girl character named Seika Kyomachi. The mascot is notable for employing various technological innovations in her mission to spread information about the town; she became a Voiceroid character in 2016, her 3D data is open source, and in July she became a Virtual YouTuber. Her latest foray is into artificial intelligence, which would allow her to respond to queries in real time. The "Narikiri AI" (Impersonation AI) project is a collaboration between the city of Seikai and NTT Communication Science Laboratories. The AI will be developed by taking feedback from a small group of users who are knowledgeable about the town and the mascot; they provide sample questions and answers, as well as vote on responses that sound the most in-character for the mascot.
SEIKA, Kyoto Prefecture--Fans of the adorable Seika Kyomachi, the town of Seika's popular mascot, will soon be able to carry on a conversation with the digital character. The small town, located between Kyoto and Nara, is collaborating with NTT Communication Science Laboratories to develop artificial intelligence capabilities for the mascot. The plan would allow Seika Kyomachi to answer questions from visitors and locals about tourism and municipal administration. Seika officials announced the project in July, and aim to put the AI-driven character into practical use in November. The town introduced Seika Kyomachi as its official mascot in 2013 and has long pioneered new ways to use the cute character.
Imagine a computer-based system visualizing your thoughts and secret thoughts; yes, it's possible now by artificial intelligence assistance. Recent advancements in hardware innovation have re-energized technology. It becomes more accurate, authentic, can produce better sound, accurate visualization, and understanding of the location. Outstanding computer processors support computer to make a decision, plan outputs and don't repeat the mistake as they learn from it. The four scientists in Kyoto at Kyoto University did an exceptional experiment that exceeds the global expectations about such a dreamy truth. They have done their experiment in ATR Computational Neuroscience Laboratories. The artificial intelligence system becomes so smart and real to duplicate human minds and show what they're thinking in their minds.
Health researchers have put artificial intelligence to work in crunching big data, allowing them to develop technology that can predict the future onset of around 20 diseases so people can make preventative lifestyle changes. The model developed at Hirosaki University and Kyoto University calculates one's probability of developing a disease within three years based on data obtained from voluntary health checkups on about 20,000 people in Japan. If a patient agrees to disclose data on some 20 categories collected during checkups, the model can project the potential development of arteriosclerosis, hypertension, chronic kidney disease, osteoporosis, coronary heart disease and obesity, among other conditions. The team set up two groups of people for each disease -- those whose data suggested they could develop the ailment in the future and a control group -- and crunched their health data to predict whether would will actually develop the disease. "We made correct predictions on whether individuals will develop the diseases within three years with high accuracy," said Yasushi Okuno, professor at Kyoto University's Graduate School of Medicine.
Kyoto – Japan's Nintendo Co. has suspended domestic shipments of its popular Nintendo Switch video game console due to a production delay caused by the coronavirus outbreak, company officials said Wednesday. Nintendo has yet to decide when to resume shipments. The company will continue Nintendo Switch shipments for customers who had placed orders and European and U.S. markets, where sufficient inventories are available. It has also halted domestic shipments of the Switch Lite portable game machine. Nintendo outsources production of the game consoles to plants in China and Vietnam.
KYOTO – A proof by mathematician Shinichi Mochizuki of a major conundrum in number theory that went unresolved for over 30 years has finally been validated, Kyoto University said Friday following a controversy over his method, which was often labeled too novel or complicated to understand. Accepted for publication by the university's Research Institute for Mathematical Sciences was Mochizuki's 600-page proof of the abc conjecture, which provides immediate proofs for many other famous mathematical problems, including Fermat's last theorem, which took almost 350 years to be demonstrated. The abc conjecture, proposed by European mathematicians in 1985, is an equation of three integers a, b, and c composed of different prime numbers, where a b c, and describing the relationship between the product of the prime numbers and c. "There are a number of new notions and it was hard to understand them," Masaki Kashiwara, head of the team that examined the professor's theory, said at a news conference. He proved the abc conjecture with a "totally new, innovative theory," said fellow professor Akio Tamagawa. "His achievement creates a huge impact in the field of number theory."
Kyocera Corp. has started developing a device to check human health and immunity from the odor of one's stool, aiming to put it into practical use in three years. In collaboration with AuB Inc., a Tokyo-based startup, Kyocera will analyze data from the device, which will be installed in toilet seats. The Kyoto-based electronics giant will create a system that infers the intestinal environment of the user with the aid of artificial intelligence technology and data collected by AuB, according to Kyocera officials. Kyocera will deliver the results to clients through a smartphone application and propose measures to improve diet and other elements of their lives to improve health, the officials said. As part of the development process, AuB will gather stool samples from 29 players of a youth team belonging to Kyoto Sanga F.C., a professional soccer team.
Read the paper to learn more about Kaokore dataset, our motivations in making them, as well as creative usage of it! KaoKore is a novel dataset of face images from Japanese illustrations along with multiple labels for each face, derived from the Collection of Facial Expressions. KaoKore dataset is build based on the Collection of Facial Expressions, which results from an effort by the ROIS-DS Center for Open Data in the Humanities (CODH) that has been publicly available since 2018. It provides a dataset of cropped face images extracted from Japanese artworks publicly available from National Institute of Japanese Literature, Kyoto University Rare Materials Digital Archive and Keio University Media Center from the Late Muromachi Period (16th century) to the Early Edo Period (17th century) to facilitate research into art history, especially the study of artistic style. It also provides corresponding metadata annotated by researchers with domain expertise.
Technology is global, but ideas are local. The same IoT technology is being deployed all over the world, but a small Japanese startup might be who helps us make sense of it all. There is amazing work being done in user experience design, but most designers are operating with the contract of keeping users engaged. This is a fundamental shift from the traditional user-centered and functional design approaches. Today we sit down with Kaz Oki, founder of Mui Lab, and we talk about user design can actually improve our lives and help us disengage. We also talk about the challenges of getting VCs to invest in hardware startups, why Kyoto might be Japan's next innovation hub, and what it takes for a startup to successfully spin out of a Japanese company It's a great discussion, and I think you will really enjoy it. Welcome to Disrupting Japan, straight talk from Japan's most successful entrepreneurs. If you're a fan of Disrupting Japan, you know that I have a strong dislike for attempts to make Japan sound too exotic and this goes in both directions. On one side, we have consultants who claim that Japanese business practices are so unique, arcane, and confusing that the only way westerners can possibly understand them is by paying large sums of money to consultants such as themselves. And on the other side, of course, we have people insisting that foreigners can't really understand Japanese anime without a thorough and nuanced knowledge of Japanese language and history. I mean, there are differences, of course, and those differences should be acknowledged and respected, but whether an idea is coming from Japan or America, or Germany, one true measure of the value of that idea is its universality. The most important achievements might emerge out of cultural biases or sensitivities but they address something universally true, something deeply human. Today, we sit down with Kaz Oki of Mui Lab and we're going to talk about Mui's radical rethinking of how we should interact with computers and the different contexts for that interaction. The Mui itself is a tactile and visual user interface that literally fades into the furniture when you're not using it.
--The reduction of metal artifacts in computed tomography (CT) images, specifically for strong artifacts generated from multiple metal objects, is a challenging issue in medical imaging research. Although there have been some studies on supervised metal artifact reduction through the learning of synthesized artifacts, it is difficult for simulated artifacts to cover the complexity of the real physical phenomena that may be observed in X-ray propagation. In this paper, we introduce metal artifact reduction methods based on an unsupervised volume-to-volume translation learned from clinical CT images. We construct three-dimensional adversarial nets with a regularized loss function designed for metal artifacts from multiple dental fillings. The results of experiments using 915 CT volumes from real patients demonstrate that the proposed framework has an outstanding capacity to reduce strong artifacts and to recover underlying missing voxels, while preserving the anatomical features of soft tissues and tooth structures from the original images. EDICAL procedures such as diagnosis, surgical planning, and radiotherapy can be seriously degraded by the presence of metal artifacts in computed tomography (CT) imaging. Metal objects such as dental fillings, fixation devices, and other electric instruments implanted in patients' bodies inhibit X-ray propagation , preventing accurate calculation of the CT values during image reconstruction and yielding dark bands or streak artifacts in the CT images . To correct the images, missing CT values for the underlying anatomical features must be compensated at the same time as the artifacts are removed. Although doctors make clinical efforts to manually collect such artifacts, this is a labor-intensive and time-consuming task. M. Nakao and T. Matsuda are with the Graduate School of Informatics, Kyoto University, Y oshida-Honmachi, Sakyo, Kyoto 606-8501, JAP AN; email: firstname.lastname@example.org.