It is indisputable that physical activity is vital for an individual's health and wellness. However, a global prevalence of physical inactivity has induced significant personal and socioeconomic implications. In recent years, a significant amount of work has showcased the capabilities of self-tracking technology to create positive health behavior change. This work is motivated by the potential of personalized and adaptive goal-setting techniques in encouraging physical activity via self-tracking. To this end, we propose UBIWEAR, an end-to-end framework for intelligent physical activity prediction, with the ultimate goal to empower data-driven goal-setting interventions. To achieve this, we experiment with numerous machine learning and deep learning paradigms as a robust benchmark for physical activity prediction tasks. To train our models, we utilize, "MyHeart Counts", an open, large-scale dataset collected in-the-wild from thousands of users. We also propose a prescriptive framework for self-tracking aggregated data preprocessing, to facilitate data wrangling of real-world, noisy data. Our best model achieves a MAE of 1087 steps, 65% lower than the state of the art in terms of absolute error, proving the feasibility of the physical activity prediction task, and paving the way for future research.

Digital engineering transformation is a crucial process for the engineering paradigm shifts in the fourth industrial revolution (4IR), and artificial intelligence (AI) is a critical enabling technology in digital engineering transformation. This article discusses the following research questions: What are the fundamental changes in the 4IR? More specifically, what are the fundamental changes in engineering? What is digital engineering? What are the main uncertainties there? What is trustworthy AI? Why is it important today? What are emerging engineering paradigm shifts in the 4IR? What is the relationship between the data-intensive paradigm and digital engineering transformation? What should we do for digitalization? From investigating the pattern of industrial revolutions, this article argues that ubiquitous machine intelligence (uMI) is the defining power brought by the 4IR. Digitalization is a condition to leverage ubiquitous machine intelligence. Digital engineering transformation towards Industry 4.0 has three essential building blocks: digitalization of engineering, leveraging ubiquitous machine intelligence, and building digital trust and security. The engineering design community at large is facing an excellent opportunity to bring the new capabilities of ubiquitous machine intelligence and trustworthy AI principles, as well as digital trust, together in various engineering systems design to ensure the trustworthiness of systems in Industry 4.0.

Supervised Question Answering systems (QA systems) rely on domain-specific human-labeled data for training. Unsupervised QA systems generate their own question-answer training pairs, typically using secondary knowledge sources to achieve this outcome. Our approach (called PIE-QG) uses Open Information Extraction (OpenIE) to generate synthetic training questions from paraphrased passages and uses the question-answer pairs as training data for a language model for a state-of-the-art QA system based on BERT. Triples in the form of are extracted from each passage, and questions are formed with subjects (or objects) and predicates while objects (or subjects) are considered as answers. Experimenting on five extractive QA datasets demonstrates that our technique achieves on-par performance with existing state-of-the-art QA systems with the benefit of being trained on an order of magnitude fewer documents and without any recourse to external reference data sources.

Abstract: Deep learning-based 3D object detectors have made significant progress in recent years and have been deployed in a wide range of applications. It is crucial to understand the robustness of detectors against adversarial attacks when employing detectors in security-critical applications. In this paper, we make the first attempt to conduct a thorough evaluation and analysis of the robustness of 3D detectors under adversarial attacks. Specifically, we first extend three kinds of adversarial attacks to the 3D object detection task to benchmark the robustness of state-of-the-art 3D object detectors against attacks on KITTI and Waymo datasets, subsequently followed by the analysis of the relationship between robustness and properties of detectors. Then, we explore the transferability of cross-model, cross-task, and cross-data attacks.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Russia continued its assault on Ukraine's infrastructure in Kyiv with a swarm of explosive drones throughout Monday morning. Russia's attacks on Kyiv have been relentless since New Year's Eve. Russia followed up its holiday missile attack with drones that flew into the city just after midnight on Monday morning.

Dr. Marty Trevino is the Chief Scientist for the Insight Cyber Group, former NSA Senior Technical Director, and a frequent speaker at NDU. Artificial intelligence (AI) has become a central component within industrial-grade embedded devices being deployed throughout industrial technology (IT), operations technology (OT) and building automation (BA). What is evolving is a seamless blending of our cyber and physical worlds. Our blended technological and physical world has produced a new category of complex, intelligent, nested systems that are pervasive. We call these dynamic and often intelligent systems cyber-physical systems (CPS). Originating in 2006 at the National Science Foundation, CPS is not AI but utilizes machine learning (ML) for specific functions, including reconfiguring without human assistance.

We worked with the NHS to explore how artificial intelligence (AI) could help radiologists quickly compare and assess computerised tomography (CT) scans to enable quicker diagnoses and improve patient outcomes. Radiologists at George Eliot Hospital NHS Trust, which serves more than 300,000 people across Warwickshire, Leicestershire and Coventry, perform around 60 scans each day. Many of these are related to cancer, and in most cases a comparison with a previous scan is necessary to assess lesion growth or shape changes. This manual alignment and comparison is labour intensive, but no suitable automation tools exist. Automating this process and improving alignment and overlay of scans would enable slight changes in volume or new lesions to be picked up more quickly. This includes a report guiding radiologists to review or further evaluate particular regions.

Several waves of Russian drones targeted critical infrastructure in Ukraine's capital and surrounding areas, officials said, as Moscow extended its constant bombardment into a second day in 2023. An explosion hit Kyiv's Desnianskiy district and drone debris hit a road in the district, in the capital's northeast, damaging a building next to it, Ukrainian officials reported early on Monday. As a result of overnight strikes on Kyiv, energy infrastructure facilities were damaged, causing power and heating outages, Mayor Vitali Klitschko said. Ukraine's air defence systems destroyed 20 aerial objects above Kyiv early on Monday, its military said, after air raid sirens wailed for more than four hours. Earlier, one person was wounded by debris from a drone destroyed over the city.

Troops battle through burning streets. Missiles take down fighter jets. The dramatic visuals have the trappings of real-life combat, but they are clips from video games fueling misinformation. Footage from the war-themed Arma 3 video game, often marked "live" or "breaking news" to make it appear genuine, has been used repeatedly in recent months in fake videos about the Russian offensive in Ukraine. The frequency and ease with which gaming footage is mistaken as real, even by some media broadcasters, and shared as authentic news on social media highlights what researchers call its serious potential to spread misinformation.

We have the vision of a world where each day is safer and more secure than the one before. These aren't easy goals to accomplish – but we're not here for easy. We are a company built on the foundation of challenging and disrupting the way things are done, and we're looking for innovators who are as committed to shaping the future of cybersecurity as we are. Palo Alto Networks is evolving to meet the needs of our employees now and in the future through FLEXWORK, our approach to how we work. And because it FLEXes around each individual employee based on their individual choices, employees are empowered to push boundaries and help us all evolve, together.