This paper presents DIALOG (Digital Investigation Ontology); a framework for the management, reuse, and analysis of Digital Investigation knowledge. DIALOG provides a general, application independent vocabulary that can be used to describe an investigation at different levels of detail. DIALOG is defined to encapsulate all concepts of the digital forensics field and the relationships between them. In particular, we concentrate on the Windows Registry, where registry keys are modeled in terms of both their structure and function. Registry analysis software tools are modeled in a similar manner and we illustrate how the interpretation of their results can be done using the reasoning capabilities of ontology

Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General Movement Assessment (GMA) can be used to classify infant movements using a Gestalt approach, identifying infants at high risk of developing PS. Training and maintenance of assessment skills are essential and expensive for the correct use of GMA, yet many practitioners lack these skills, preventing larger-scale screening and leading to significant risks of missing opportunities for early detection and intervention for affected infants. We present an automated approach to GMA, based on body-worn accelerometers and a novel sensor data analysis method-Discriminative Pattern Discovery (DPD)-that is designed to cope with scenarios where only coarse annotations of data are available for model training. We demonstrate the effectiveness of our approach in a study with 34 newborns (21 typically developing infants and 13 PS infants with abnormal movements). Our method is able to correctly recognise the trials with abnormal movements with at least the accuracy that is required by newly trained human annotators (75%), which is encouraging towards our ultimate goal of an automated PS screening system that can be used population-wide.

Our research is focused on understanding and applying biological memory transfers to new AI systems that can fundamentally improve their performance, throughout their fielded lifetime experience. We leverage current understanding of biological memory transfer to arrive at AI algorithms for memory consolidation and replay. In this paper, we propose the use of generative memory that can be recalled in batch samples to train a multi-task agent in a pseudo-rehearsal manner. We show results motivating the need for task-agnostic separation of latent space for the generative memory to address issues of catastrophic forgetting in lifelong learning.

The U.S. Federal Aviation Administration is still working to figure out the best way of making sure that people fly their drones safely and legally. It's very much a work in progress, and has been for years. At this point, anyone who wants to fly a drone weighing more than 250 grams (even just for fun in the backyard) must register that drone and follow some generally common sense rules and regulations. The FAA, to their credit, has been keeping track of how this has all been going, and late last week they announced a few important updates. The new change that will affect everyone is that all drones are now required to display registration information externally.

China steps up plans for using artificial intelligence to strengthen its military; Bill Hemmer reports. The President and the Pentagon are signaling that artificial intelligence (AI) is now a major priority for U.S. national security, and competition from China and Russia may be a key motivator. President Trump issued an executive order on Feb. 11 titled "Maintaining American Leadership in Artificial Intelligence." It's a directive that he says "will affect the missions of nearly all executive departments and agencies," and he didn't mince words on the significance of this quest. "Continued American leadership in AI is of paramount importance to maintaining the economic and national security of the United States," the executive order reads.

A scientific coalition is urging a ban on the development of weapons governed by artificial intelligence. A scientific coalition is urging a ban on the development of weapons governed by artificial intelligence (AI), warning they may malfunction unpredictably and kill innocent people. The coalition has established the Campaign to Stop Killer Robots to lobby for an international accord. Said Human Rights Watch's Mary Wareham, autonomous weapons "are beginning to creep in. Drones are the obvious example, but there are also military aircraft that take off, fly, and land on their own; robotic sentries that can identify movement."

On Feb. 11, the White House released an executive order on "Maintaining American Leadership in Artificial Intelligence" (AI)--the latest attempt to develop a national strategy for AI. The order envisions the United States taking significant steps to increase research and development efforts while reforming its executive agencies to better compete with the Chinese government's investments in AI development through its Made in China 2025 plan. Although the order is full of promising language and constructive suggestions for executive agencies, it is unlikely to have much of a long-term effect without further support from Congress. The executive order has three basic prongs. First, it charges executive agencies to "prioritize AI" across several dimensions.

There is no question the United States is on a mission to preserve its role as a global leader in AI (artificial intelligence) adoption and innovation. Perhaps even more noteworthy is what this latest initiative has in common with past data-related initiatives? If you watched the 2019 State of the Union address a couple of weeks ago, you heard President Trump say he's eager to work with Congress to invest in "cutting edge industries of the future." He referred to this investment in cutting-edge industries as a necessity, not an option. Candidly, I was eagerly awaiting more commentary and was hoping he would elaborate.

Environments like nuclear, offshore, space and deep mining can be challenging for people to work in, with potentially extreme temperatures, pressure and high levels of radiation. Up to £2 million is available to fund feasibility studies and collaborative R&D projects that develop electronics, sensors and photonics that can cope with these conditions. This competition is part of the Industrial Strategy Challenge Fund to develop safer and more productive technologies for working in extreme environments. Funding is provided by UK Research and Innovation and delivered by Innovate UK. Through the robots for a safer world challenge, government is investing £93 million in advanced robotics that remove people from potentially harmful operations, improve productivity, and open up new, cross-disciplinary opportunities.

With competitive pressure increasing drastically and the digital economy progressing considerably, enterprises need to figure out new ways to plan, develop, and add value. Therefore, to adapt to digital transformation efficiently, DevOps has become a necessity to eliminate technical and cultural constraints for offering value rapidly. Unfortunately, the conservative nature of IT enterprises has led to slower adoption of DevOps. Additionally, many organizations still need to adopt them for efficient processes. The adoption would enhance the efficiency of operational processes and reduce downtime in the development life cycle of software.