Japanese authorities are introducing a variety of measures to prevent the wrongful use of drones, which has been increasing due to many people being unfamiliar with regulations, especially tourists from abroad. Under the civil aeronautics law, a drone of 200 grams or more cannot be operated in airspace around airports or residential areas without permission from the government. In addition, the law regulating the use of drones bans flights in airspace near designated important places such as the Prime Minister's Office, the Imperial Palace and nuclear power plants. Foreign tourists and others unfamiliar with the laws continue to violate them. In 2019, 14 foreign nationals had their cases sent to prosecutors, as of Nov. 20.
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.
The drone attack claimed by Yemeni rebels on key Saudi Arabian oil refineries that took place on September 14, 2019 has brought the powerful technology back into the news. Unfortunately, the strikes that disrupted roughly 5% of the world's oil supply has also contributed more ammunition to the overarching negative connotations the word "drone" conjures. "Drone" is a very broad term. Colloquially, drones are usually thought of as remote-piloted flying devices used by militaries for surveillance and offensive tactics or by civilians for recreational or business purposes. Merriam-Webster defines it as "an unmanned aircraft or ship guided by remote control or onboard computers."
Wildlife is flourishing in the exclusion zone around the disabled Fukushima Daichii nuclear reactor in Japan, images from remotely-operated cameras have revealed. Researchers spotted more than 20 species in areas around the reactor, including wild boar, macaques and fox-like raccoon dogs. The findings help reveal how wildlife populations respond in the wake of catastrophic nuclear disaster like those that occurred at Fukushima and Chernobyl. Humans were evacuated from certain zones around the the Fukushima reactor following radiation leaks caused by the Tōhoku earthquake and tsunami of 2011. Wildlife ecologist James Beasley of the University of Georgia, in the US, and colleagues used a network of 106 remote cameras to capture images of the wildlife in the area around the Fukushima Daiichi power plant over a four-month period.
It had already been an eventful day in Iran: The country had just launched missiles at United States forces based in Iraq and an airliner carrying at least 176 people crashed shortly after takeoff from Tehran on Wednesday, killing everyone on board. Then just before dawn, a 4.5-magnitude earthquake struck southern Iran at a depth of about six miles, the United States Geological Survey reported, in the same region as the troubled Bushehr nuclear power plant. It struck just as Iranian leaders were trumpeting their strike on two Iraqi bases housing United States forces, in retaliation for last week's American drone strike that killed Maj. No casualties were immediately reported, but rescue teams were working at the site, Jahangir Dehqani, managing director of the Bushehr crisis management agency, told the state-run IRNA news agency. The quake was reported about 30 miles from the Russian-built Bushehr nuclear plant.
Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a data-driven approach, Feature Similarity Measurement FFSM), to establish a technical basis to overcome these difficulties by exploring local patterns using machine learning. The underlying local patterns in multiscale data are represented by a set of physical features that embody the information from a physical system of interest, empirical correlations, and the effect of mesh size. After performing a limited number of high-fidelity numerical simulations and a sufficient amount of fast-running coarse-mesh simulations, an error database is built, and deep learning is applied to construct and explore the relationship between the local physical features and simulation errors. Case studies based on mixed convection have been designed for demonstrating the capability of data-driven models in bridging global scale gaps.
IDAHO FALLS, Idaho, Dec. 5, 2019 – A powerful new supercomputer arrived this week at Idaho National Laboratory's Collaborative Computing Center. The machine has the power to run complex modeling and simulation applications, which are essential to developing next-generation nuclear technologies. Named after a central Idaho mountain range, Sawtooth arrives in December and will be available to users early next year. That is the highest ranking reached by an INL supercomputer. Of 102 new systems added to the list in the past six months, only three were faster than Sawtooth.
Man-made brainpower (AI) will soon be at the core of each major technological framework on the planet to manage and get to your strategic information. Only a couple of uses are cyber and homeland security, anti-money laundering, payments, financial markets, biotech, healthcare, marketing, natural language processing (NLP), computer vision, electrical grids, nuclear power plants, air traffic control, and Internet of Things (IoT). Artificial Intelligence is turning into a significant staple of innovation, scarcely any individuals comprehend the advantages and weaknesses of AI and Machine Learning innovations. While machine intelligence is sure to assume a key role in the making of cutting edge frameworks in a wide assortment of industry areas sooner rather than later, it is especially applicable in quickly developing businesses, for example, ICT, manufacturing and transportation. Over the globe, mobile operators are preparing to deploy the fifth era of 3GPP mobile wireless networks (5G).
Many real-world multi-agent reinforcement learning applications require agents to communicate, assisted by a communication protocol. These applications face a common and critical issue of communication's limited bandwidth that constrains agents' ability to cooperate successfully. In this paper, rather than proposing a fixed communication protocol, we develop an Informative Multi-Agent Communication (IMAC) method to learn efficient communication protocols. Our contributions are threefold. First, we notice a fact that a limited bandwidth translates into a constraint on the communicated message entropy, thus paving the way of controlling the bandwidth. Second, we introduce a customized batch-norm layer, which controls the messages' entropy to simulate the limited bandwidth constraint. Third, we apply the information bottleneck method to discover the optimal communication protocol, which can satisfy a bandwidth constraint via training with the prior distribution in the method. To demonstrate the efficacy of our method, we conduct extensive experiments in various cooperative and competitive multi-agent tasks across two dimensions: the number of agents and different bandwidths. We show that IMAC converges fast, and leads to efficient communication among agents under the limited-bandwidth constraint as compared to many baseline methods.