fukushima


Coronavirus Is Proving We Need More Resilient Supply Chains

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As governments and health care agencies work to stop the spread of Covid-19 and to treat those who are infected, manufacturers in more than a dozen industries are struggling to manage the epidemic's growing impact on their supply chains. Unfortunately, many are facing a supply crisis that stems from weaknesses in their sourcing strategies that could have been corrected years ago. Just how extensive the crisis is can be seen in data released by Resilinc, a supply-chain-mapping and risk-monitoring company, which shows the number of sites of industries located in the quarantined areas of China, South Korea, and Italy, and the number of items sourced from the quarantined regions of China. After the March 2011 earthquake and tsunami in Fukushima, Japan, many multinationals learned painful lessons about the hidden weaknesses in their supply chains -- weaknesses that resulted in loss of revenue, and in some cases, market cap. While most companies could quickly assess the impacts that Fukushima had on their direct suppliers, they were blindsided by the impacts on second- and third-tier suppliers in the affected region.


What Is Computer Vision?

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When you look at the following image, you see people, objects, and buildings. It brings up memories of past experiences, similar situations you've encountered. The crowd is facing the same direction and holding up phones, which tells you that this is some kind of event. The person standing near the camera is wearing a T-shirt that hints at what the event might be. As you look at other small details, you can infer much more information from the picture.


Delayed probe of Fukushima No. 1 reactor to push back fuel debris removal

The Japan Times

A plan to remove fuel debris from the primary containment vessel of a reactor at the Fukushima No. 1 nuclear power plant is expected to be further pushed back after it became apparent that Tokyo Electric Power Company Holdings Ltd. will not be able to conduct an internal probe -- a key step to start removing the fuel debris -- by the end of March as planned. The internal probe would involve using remote-controlled robots to collect fuel debris inside the No. 1 reactor so Tepco can examine its composition and form. Tepco's plan is to open three holes in both the outer and inner doors of the primary containment vessel using pressurized water mixed with a polishing agent. After it succeeded in opening three holes in the outer door, Tepco started drilling a hole in the inner door in June 2019. But that procedure caused the concentration of radioactive dust to increase temporarily, prompting staff to suspend work.


A Brief History of Computer Vision (and Convolutional Neural Networks)

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Although Computer Vision (CV) has only exploded recently (the breakthrough moment happened in 2012 when AlexNet won ImageNet), it certainly isn't a new scientific field. Computer scientists around the world have been trying to find ways to make machines extract meaning from visual data for about 60 years now, and the history of Computer Vision, which most people don't know much about, is deeply fascinating. In this article, I'll try to shed some light on how modern CV systems, powered primarily by convolutional neural networks, came to be. I'll start with a work that came out in the late 1950s and has nothing to do with software engineering or software testing. One of the most influential papers in Computer Vision was published by two neurophysiologists -- David Hubel and Torsten Wiesel -- in 1959.


Japanese team developing AI-based system to forecast chance of tsunami and scale of damage

The Japan Times

Drawing lessons from one of the worst disasters in the nation's history, a team of Japanese researchers is developing an artificial intelligence-based tsunami-forecasting system set for release in fiscal 2020 that could help limit loss of life and property in future calamities. In March 2011, massive tsunami 30 meters high triggered by a 9.1 magnitude earthquake destroyed a large swath of the Tohoku coastline, taking not only residents but also entire communities and businesses by surprise. The researchers hope the new system will help municipalities and companies nationwide better prepare for any future calamities and prevent related disasters, such as the triple core meltdown at the Fukushima No. 1 power plant that resulted from the tsunami. The team, made up of researchers from risk management consultancy Tokio Marine & Nichido Risk Consulting Co. and the National Research Institute for Earth Science and Disaster Resilience are working on the nation's first system for predicting the likelihood of tsunami based on location, as well as the scope of damage in areas expected to be hit. "The existing forecasting system only estimates the maximum height of a tsunami but not its likelihood … and sometimes there are no available measures to prepare for the worst-case scenario," a spokesman for Tokio Marine & Nichido Risk Consulting said by phone.


Japan offers U.S. its robotics tech for use in denuclearizing North Korea

The Japan Times

Japan has told the United States it is ready to provide its robot technology for use in dismantling nuclear and uranium enrichment facilities in North Korea as Washington and Pyongyang pursue further denuclearization talks, government sources said Friday. As Japan turns to the remotely controlled robots it has developed to decommission reactors crippled by the triple core meltdown in 2011 at the Fukushima No. 1 power plant, it believes the same technology can be used in North Korea, according to the sources. The offer is part of Japan's efforts to make its own contribution to the denuclearization talks amid concern that Tokyo could be left out of the loop as the United States and North Korea step up diplomacy. Tokyo has already told Washington it would shoulder part of the costs of any International Atomic Energy Agency inspections of North Korean facilities and dispatch its own nuclear experts to help. The scrapping of nuclear facilities, such as the Yongbyon complex, which has a graphite-moderated reactor, will come into focus in forthcoming working-level talks between Washington and Pyongyang.


NTT to launch trial of farming support service with drones and AI tech in Fukushima

The Japan Times

Nippon Telegraph and Telephone Corp. (NTT) said Thursday it will launch a trial for a farming support service using drones and artificial intelligence technology, with a goal of commercializing the service in Japan and other Asian countries. The new system, which connects drones with GPS satellites, is anticipated to help the farm industry in the nation amid a serious labor shortage. NTT aims to raise crop output by up to 30 percent through the new service. The telecommunications giant will conduct the trial service on 8 hectares of a rice field in Fukushima Prefecture from later this month to March 2021. It aims to launch the service on a commercial basis in Japan in two years.


Removal of fuel at Fukushima's melted nuclear reactor begins

Los Angeles Times

The operator of the tsunami-wrecked Fukushima nuclear plant began removing fuel Monday from a cooling pool at one of three reactors that melted down in the 2011 disaster, a milestone in what will be a decades-long process to decommission the facility. Tokyo Electric Power Co. said workers started removing the first of 566 used and unused fuel units stored in the pool at Unit 3. The fuel units in the pool located high up in reactor buildings are intact despite the disaster, but the pools are not enclosed, so removing the units to safer ground is crucial to avoid disaster in case of another major earthquake similar to the one that caused the 2011 tsunami. TEPCO says the removal at Unit 3 will take two years, followed by the two other reactors, where about 1,000 fuel units remain in the storage pools. Removing fuel units from the cooling pools comes ahead of the real challenge of removing melted fuel from inside the reactors, but details of how that might be done are still largely unknown. Removing the fuel in the cooling pools was delayed more than four years by mishaps, high radiation and radioactive debris from an explosion that occurred at the time of the reactor meltdowns, underscoring the difficulties that remain.


Removal of fuel at Fukushima's melted reactor begins

Al Jazeera

The operator of the tsunami-wrecked Fukushima nuclear plant has begun removing fuel from a cooling pool at one of three reactors that melted down in the 2011 disaster, a milestone in the decades-long process to decommission the plant. Tokyo Electric Power Co (Tepco) said on Monday that workers started removing the first of 566 used and unused fuel units stored in the pool at Unit 3. The fuel units in the pool located high up in reactor buildings are intact despite the disaster, but the pools are not enclosed so removing the units to safer ground is crucial to avoid disaster in case of another major quake. Tepco said the removal at Unit 3 would take two years, followed by the two other reactors. The step comes ahead of the real challenge of removing melted fuel from inside the reactors, but details of how that might be done are still largely unknown. Removing the fuel in the cooling pools was delayed five years by mishaps, high radiation and radioactive debris from an explosion that occurred at the time of the reactor meltdown, underscoring the difficulties that remain.


A Brief History of Computer Vision (and Convolutional Neural Networks)

#artificialintelligence

Although Computer Vision (CV) has only exploded recently (the breakthrough moment happened in 2012 when AlexNet won ImageNet), it certainly isn't a new scientific field. Computer scientists around the world have been trying to find ways to make machines extract meaning from visual data for about 60 years now, and the history of Computer Vision, which most people don't know much about, is deeply fascinating. In this article, I'll try to shed some light on how modern CV systems, powered primarily by convolutional neural networks, came to be. I'll start with a work that came out in the late 1950s and has nothing to do with software engineering. One of the most influential papers in Computer Vision was published by two neurophysiologists -- David Hubel and Torsten Wiesel -- in 1959.