Information Ecosystem Reengineering (IER) -- the technological reconditioning of information sources, services, and systems within a complex information ecosystem -- is a foundational challenge in the digital transformation of public sector services and smart governance platforms. From a semantic knowledge management perspective, IER becomes especially entangled due to the potentially infinite number of possibilities in its conceptualization, namely, as a result of manifoldness in the multi-level mix of perception, language and conceptual interlinkage implicit in all agents involved in such an effort. This paper proposes a novel approach -- Representation Disentanglement -- to disentangle these multiple layers of knowledge representation complexity hindering effective reengineering decision making. The approach is based on the theoretically grounded and implementationally robust ontology-driven conceptual modeling paradigm which has been widely adopted in systems analysis and (re)engineering. We argue that such a framework is essential to achieve explainability, traceability and semantic transparency in public sector knowledge representation and to support auditable decision workflows in governance ecosystems increasingly driven by Artificial Intelligence (AI) and data-centric architectures.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service. An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

We present a framework for achieving end-to-end management objectives for multiple services that concurrently execute on a service mesh. We apply reinforcement learning (RL) techniques to train an agent that periodically performs control actions to reallocate resources. We develop and evaluate the framework using a laboratory testbed where we run information and computing services on a service mesh, supported by the Istio and Kubernetes platforms. We investigate different management objectives that include end-to-end delay bounds on service requests, throughput objectives, cost-related objectives, and service differentiation. We compute the control policies on a simulator rather than on the testbed, which speeds up the training time by orders of magnitude for the scenarios we study. Our proposed framework is novel in that it advocates a top-down approach whereby the management objectives are defined first and then mapped onto the available control actions. It allows us to execute several types of control actions simultaneously. By first learning the system model and the operating region from testbed traces, we can train the agent for different management objectives in parallel.

Recently has seen the growth in the use of mobile health (mHealth) information services, which have rich guides on improving physical activity. These rich guides evolved from the consideration of various personal behavioural factors, which often deviate from the user's health conditions. The behavioural factors include changing fitness preferences, adherence issues, and uncertainty about future fitness outcomes, which may all lead to a decline in the quality of the mHealth information services. Many of these mHealth information services provide limited fitness guidance owing to the dynamics of the user's health conditions. This paper seeks an adaptive method using deep reinforcement learning to make personalised physical activity recommendations, which is learnt from retrospective physical activity data and can simulate realistic behaviour trajectories. We construct a real-time interaction model for the mHealth information service system based on scientific knowledge about physical activity to evaluate its exercise performance. The physical activity performance evaluation model is used to find the optimal exercise intensity considering the fitness and fatigue effects to avoid the lack of exercise or overload. The short-term activity plans are made using deep reinforcement learning and personal health conditions that change over time. Using this method, we can dynamically update the physical activity recommendation policy in accordance with the real implementation behaviour. Our DRL-based recommender policy was validated by comparison to other benchmark policies. Experimental results show that this adaptive learning algorithm can improve recommendation performance over 4.13 percent.

Karlsruhe, August 29, 2019 – At the SEMANTiCS conference in Karlsruhe from 9 to 12 September, representatives from industry and science will discuss the use of semantic technologies and artificial intelligence. FIZ Karlsruhe is a co-organizer, and with good reason: the digital change has reached and affected research data, methods and processes. Efficient information infrastructures have a key role to play in mastering the new challenges. FIZ Karlsruhe will present its spectrum as a Leibniz Institute for Information Infrastructure in various roundtable discussions, presentations and with its own stand. SEMANTiCS is one of the leading conferences in the field of semantic technologies and artificial intelligence. FIZ Karlsruhe, together with the Karlsruhe Institute of Technology (KIT), has succeeded in bringing this renowned international event to Karlsruhe for its 15th anniversary.

On Thursday, Geisinger Health announced its CEO Dr. David Feinberg was leaving to fill a newly created leadership role at Google, a sure sign the tech giant wants to cash in on the $3.5 trillion healthcare industry. Google is not the only one. Five the world's 10 largest companies have announced major health initiatives over the past year, including: Amazon, Apple, Berkshire-Hathaway, JPMorgan Chase and, now, Alphabet, Inc. (Google). Sources close to the Google announcement said Feinberg will report to AI head Jeff Dean, who we're told led a months-long search for the right candidate. According to CNBC's Christina Farr, who first reported on the details of the transition, "Feinberg's job will be figuring out how to organize Google's fragmented health initiatives, which overlap among many different business."

Opponents of the Federal Communications Commission have outlined their chief arguments on net neutrality to a federal appeals court in Washington, in hopes of undoing the FCC's move last year to repeal its own rules for Internet service providers. The legal briefs reflect a widening front in the multipronged campaign by consumer groups and tech companies to rescue the ISP regulations, which originally barred providers from blocking websites or slowing them. With the FCC's changes, Internet providers may legally manipulate Internet traffic as it travels over their infrastructure, as long as they disclose their practices to consumers. The FCC's decision last year to repeal the rules was "arbitrary and capricious," said officials from the state of New York, the California Public Utilities Commission and others in court documents Monday -- asking the U.S. Court of Appeals for the District of Columbia Circuit to overrule the agency. The FCC was too credulous in accepting industry promises "to refrain from harmful practices," the officials said, "notwithstanding substantial record evidence showing that [Internet] providers have abused and will abuse their gatekeeper roles in ways that harm consumers and threaten public safety."

Your.MD, an AI-driven health information service delivered via a bot, has raised $10 million in new funding. The round was led by Orkla Ventures, the venture arm of Orkla, a leading supplier of branded consumer goods to the health, pharmacy, and grocery sectors in the Nordics, Baltics and parts of Central Europe. Existing investor Smedvig Capital and other unnamed existing shareholders also participated. Billed as a AI-based "pre-primary care service," Your.MD is available for web, iOS, Android, Facebook Messenger, Skype, Slack and Telegram. It is part chatbot, helping users figure out what might be wrong with them via a conversational interface that drills down into your symptoms, and part next-generation search engine to surface detailed and verified information on various medical conditions.

When it comes to our cars, driver expectations have shifted into high gear. Now, of course we still want a vehicle that looks good, provides comfort and optimal safety, but our feature wish list has grown and it includes a dash of the Internet of Things (IoT). Today, more and more drivers expect their cars to connect them with their surroundings -- whether it's traffic conditions, approaching weather or other cars that can share information, which helps us avoid anything from gridlock to erratic drivers who may be lurking just around the bend. As we have seen in recent months, new in-car innovations are gaining momentum with the latest coming from IBM and BMW Group. Today we announced a new collaboration focused on exploring how Watson cognitive computing can personalize and enhance the driving experience. And when I say collaboration, I mean a true side-by-side effort.

When it comes to our cars, drivers are asking for new features powered by the Internet of Things (IoT) and companies like IBM and BMW Group are answering their call. In fact, today we announced a new collaboration focused on exploring how Watson cognitive computing can personalize and enhance the driving experience. And when I say collaboration, I mean a true side-by-side effort–BMW Group, is collocating a team of researchers at IBM's new global headquarters for its Watson Internet of Things business (IoT) in Munich, Germany. Together, every day, we will marry the power IoT and connected cars, a combination that will forever change the driving experience. A fascinating aspect of this collaboration is something that's on the mind of every driver, weather.