In the advent of the novel coronavirus epidemic since December 2019, governments and authorities have been struggling to make critical decisions under high uncertainty at their best efforts. Composite Monte-Carlo (CMC) simulation is a forecasting method which extrapolates available data which are broken down from multiple correlated/casual micro-data sources into many possible future outcomes by drawing random samples from some probability distributions. For instance, the overall trend and propagation of the infested cases in China are influenced by the temporal-spatial data of the nearby cities around the Wuhan city (where the virus is originated from), in terms of the population density, travel mobility, medical resources such as hospital beds and the timeliness of quarantine control in each city etc. Hence a CMC is reliable only up to the closeness of the underlying statistical distribution of a CMC, that is supposed to represent the behaviour of the future events, and the correctness of the composite data relationships. In this paper, a case study of using CMC that is enhanced by deep learning network and fuzzy rule induction for gaining better stochastic insights about the epidemic development is experimented. Instead of applying simplistic and uniform assumptions for a MC which is a common practice, a deep learning-based CMC is used in conjunction of fuzzy rule induction techniques. As a result, decision makers are benefited from a better fitted MC outputs complemented by min-max rules that foretell about the extreme ranges of future possibilities with respect to the epidemic.

The coronavirus pandemic is having a peculiarly American side effect: Gun sales are surging. The stocks of publicly traded guns and ammo companies American Outdoor Brands Corp., Vista Corp., and Sturm Ruger & Co. are up. Sales leaped by more than 19% in January and 17% in February, compared with the same months in 2019, according to Small Arms Analytics & Forecasting. Gun buyers in the United States bought an estimated 1.24 million guns in, January up from 1.04 million the year before, and 1.36 million in February, up from 1.26 million the year before, according to Small Arms Analytics, which bases estimates on background check data. Those millions of new guns are in addition to the approximately 400 million guns American already own.

Dr. Alex Antic is a trusted and experienced Data Science leader, with a proven record of delivering innovative, successful and sustainable projects in government, industry and startups (including Sports Analytics), that leverage data and Machine Learning/Deep Learning capabilities to deliver actionable insights. Dr. Antic is currently serving as an Academic at ANU, whilst also being a Principal Data Scientist for Federal Agency. Before his current role at ANU, Alex was a quantitative analyst at hedge fund and investment bank. He has also worked with the actuarial teams in the marketing analytics. Because of this unique career path with the commercial experience, he understands the business needs well as well as able to be pragmatics with the commercial perspective whilst working at different environment.

Gernot Heiser is chief research scientist at CSIRO Data61 and Scientia Professor and John Lions Chair at UNSW Sydney, Australia. Gerwin Klein is chief research scientist at CSIRO Data61 and a conjoint professor at UNSW Sydney, Australia. June Andronick is chief research scientist at CSIRO Data61 and a conjoint associate professor at UNSW Sydney, Australia.

In March 2011, the catastrophic accident known as "The Fukushima Daiichi nuclear disaster" took place, initiated by the Tohoku earthquake and tsunami in Japan. The only nuclear accident to receive a Level-7 classification on the International Nuclear Event Scale since the Chernobyl nuclear power plant disaster in 1986, the Fukushima event triggered global concerns and rumors regarding radiation leaks. Among the false rumors was an image, which had been described as a map of radioactive discharge emanating into the Pacific Ocean, as illustrated in the accompanying figure. In fact, this figure, depicting the wave height of the tsunami that followed, still to this date circulates on social media with the inaccurate description. Social media is ideal for spreading rumors, because it lacks censorship.

Chris Bain is a professor of Digital Health in the Faculty of IT at Monash University, Melbourne, Australia. Abraham Oshni Alvandi is a research assistant in Digital Health in the Faculty of IT at Monash University, Melbourne, Australia.

NTU SPIRIT Smart Nation Research Centre, together with the Singapore Judiciary, has successfully developed an Intelligent Case Retrieval System (ICRS) using AI capabilities. ICRS enables efficient retrieval of relevant precedent cases through the use of continuously adaptive AI/data analytics approaches. The use of such tools can help the legal profession to understand case details and perform legal research by trawling through the case repositories at a faster and more accurate rate to obtain the most relevant case precedents and identify possible outcomes in different areas of law. The value of ICRS is to better enable all parties to evaluate the strengths or weaknesses of their cases. With better quality legal submissions, judges too are assisted in their decision-making processes, thus elevating the quality of judgments delivered.

A successful digital economy requires cybersecurity to be a vital enabler, protecting the interests of individuals and businesses and enabling the resilience of businesses and services. Since 2013, Singapore's medium- to long-term directions for cybersecurity is to develop R&D expertise and capabilities to improve the trustworthiness of cyber infrastructures and systems with an emphasis on security, reliability, resilience, and usability among government agencies, academia, and industry. Various initiatives to support research, innovation, and enterprise have been implemented under the Whole-of-Government National Cybersecurity R&D (NCR) Programme.8 The program supports a synergistic range of initiatives to advance technological state-of-the-art in thematic National Satellites of Excellence in universities, grants for local research projects, international research collaborations, and joint technology developments with industry. Innovation is fostered through cross-sector R&D discussions and partnerships and fast-tracked by national testbeds for safe and repeatable cybersecurity experiments.

To capture cultural heritage is to capture the experience of people who are directly involved in creating, witnessing, and maintaining cultural heritage objects. Ideally, the people accessing digital representations of cultural heritage objects are able to understand the significance underlying the objects. The question is how to capture (the experience of) cultural objects in digital form. Various modalities exist for representing cultural heritage: unstructured textual data, possibly including images or videos, as well as structured data. Capisco has been shown to provide quality semantic search results for English-language texts, with promising early results for other languages.

Japan's National Institute of Informatics (NII) launched its inaugural NII Shonan Meeting in February 2011. It was the first international conference of informatics in Asia, following in the style of the Dagstuhl seminars in Germany, designed to bring together the world's leading researchers and engineers to discuss open problems and challenges. More than 140 meetings have been held since then, and the number of participants totaled approximately 3,500 by November 2019. NII supports all the administrative arrangements for organizers and covers approximately half the fee for every academic participant (including room, board, and meeting fees). Sometimes, we also have summer/winter schools.