Suzuki Motor Corp. Chairman Osamu Suzuki will retire after leading the Japanese automaker for more than 40 years and making it into a global player with an overwhelming dominance in the Indian car market, the firm said Wednesday. The 91-year-old chairman will leave the post at a shareholders meeting slated for June and become an adviser, it said. Suzuki has served as either president, chairman or CEO of the company, known for its minivehicles and motorcycles, since 1978. "I decided to give way to successors to promote a midterm business plan," which the Hamamatsu, Shizuoka Prefecture-based company released the same day, Suzuki said during an online news conference. He added that the company's 100-year anniversary last year also prompted his decision to step down from the chairman's post.
NAGOYA – Toyota Motor Corp. on Tuesday began construction of a smart city at the foot of Mount Fuji in central Japan as a testing ground for new technologies including robotics and artificial intelligence. About 360 people including Toyota employees will initially move to the so-called Woven City to be built at the 70.8-hectare former Toyota factory site in Susono, Shizuoka Prefecture. It will be powered by electricity from fuel cells, which derive power from a hydrogen-oxygen reaction, in addition to solar panels. Toyota describes the city -- run with partner companies such as telecommunications giant Nippon Telegraph and Telephone Corp. -- as a "living laboratory" where it will test autonomous vehicles, robots and artificial intelligence in a real-world environment. The automaker has commissioned Danish architect Bjarke Ingels, who designed the 2 World Trade Center in New York City and Google's headquarters in California, to plan the layout of the city.
In March, Japan's largest auto parts maker, Denso Corp., was facing the urgent task of how to secure enough face masks for its workers given the mass shortage that was occurring amid the spread of COVID-19 infections. While the company, located in Kariya, Aichi Prefecture, had sufficient stocks of masks back then, executives were getting worried that if the company ran short, its production might be affected, since each factory worker needs five masks a day. At an executive meeting March 2, all eyes turned to Yasuhiko Yamazaki, 56, senior executive officer in charge of production, when he said, "How about making them ourselves?" After returning home, Yamazaki cut a mask he had with a pair of scissors, looked at its three-layered structure with nonwoven material used as a middle layer, and felt certain it could be made by Denso. The following day, he gathered seven to eight employees who were well-versed in auto parts production technology and were engaged in the designing and manufacturing of machinery and equipment.
At a factory south of Toyota City, Aichi Prefecture, robots have started sharing the work of quality-control inspectors, as the coronavirus pandemic accelerates a shift from Toyota's vaunted "go and see" system which helped revolutionize mass production in the 20th century. Inside the auto-parts plant of Musashi Seimitsu Industry Co. Ltd., a robotic arm picks up and spins a bevel gear, scanning its teeth against a light in search of surface flaws. The inspection takes about two seconds -- similar to that of highly trained employees who check around 1,000 units per shift. "Inspecting 1,000 of the exact same thing day-in day-out requires a lot of skill and expertise, but it's not very creative," Chief Executive Hiroshi Otsuka said. "We'd like to release workers from those tasks."
Nagoya – Komehyo Co., a Japanese recycle store operator, said Tuesday it will introduce an artificial intelligence-based system to appraise used brand goods. The system can tell whether an item is fake and identify the model number of a genuine item using pictures taken with a microscope and other means, according to the company. The introduction of the system will reduce the time needed for appraisal when buying used items from customers, Komehyo said. The company will start using the system at its main outlet in Nagoya, Aichi Prefecture, on Aug. 25. It plans to introduce the system at other outlets in and outside the country in stages.
This paper discusses the prediction of hierarchical time series, where each upper-level time series is calculated by summing appropriate lower-level time series. Forecasts for such hierarchical time series should be coherent, meaning that the forecast for an upper-level time series equals the sum of forecasts for corresponding lower-level time series. Previous methods for making coherent forecasts consist of two phases: first computing base (incoherent) forecasts and then reconciling those forecasts based on their inherent hierarchical structure. With the aim of improving time series predictions, we propose a structured regularization method for completing both phases simultaneously. The proposed method is based on a prediction model for bottom-level time series and uses a structured regularization term to incorporate upper-level forecasts into the prediction model. We also develop a backpropagation algorithm specialized for application of our method to artificial neural networks for time series prediction. Experimental results using synthetic and real-world datasets demonstrate the superiority of our method in terms of prediction accuracy and computational efficiency.
NAGANO – Seiko Epson Corp., a major Japanese maker of printers and industrial robots, said Thursday it will make use of its paper recycling technology to start producing face masks from late May. Production will take place at two of its domestic plants and will eliminate the need to outsource masks for its employees. It has also decided to donate 5,600 face shields, planned to be used by its employees in Japan and abroad, to the prefectural government to help ease medical supply shortages. The company has not yet decided whether it will sell any of the masks it produces to general consumers. Seiko Epson's PaperLab recycling machine for offices produces paper from used paper without the need of any water.
WASHINGTON--A type of artificial intelligence called machine learning can help predict which patients will develop diabetes, according to an ENDO 2020 abstract that will be published in a special supplemental section of the Journal of the Endocrine Society. Diabetes is linked to increased risks of severe health problems, including heart disease and cancer. Preventing diabetes is essential to reduce the risk of illness and death. "Currently we do not have sufficient methods for predicting which generally healthy individuals will develop diabetes," said lead author Akihiro Nomura, M.D., Ph.D., of the Kanazawa University Graduate School of Medical Sciences in Kanazawa, Japan. The researchers investigated the use of a type of artificial intelligence called machine learning in diagnosing diabetes.
In 1997, Hiroaki Kitano, a research scientist at Sony, helped organize the first Robocup, a robot soccer tournament that attracted teams of robotics and artificial intelligence researchers to compete in the picturesque city of Nagoya, Japan. At the start of the first day, two teams of robots took to the pitch. As the machines twitched and surveyed their surroundings, a reporter asked Kitano when the match would begin. "I told him it started five minutes ago!" he says with a laugh. Such was the state of AI and robotics at the time.
Japanese railway companies are turning to artificial intelligence to help tackle potential problems for their shinkansen bullet trains caused by accumulations of snow. West Japan Railway Co. is developing an AI system to gauge the amount of snow attached to Hokuriku Shinkansen trains that cut through Niigata, Toyama and Ishikawa prefectures adjacent to the Sea of Japan. The railway operator currently decides how many personnel to deploy for snow clearance a day beforehand, based on information from meteorological data providers and past experience, but it is often not very accurate. AI will gather data from images of trains that have accumulated snow while traveling, study weather conditions and predict the number of personnel necessary for clearance work. Test operations have proved positive so far and the system is set for full introduction next winter.