We present several completely general diversity metrics to quantify the problem-solving capacity of any public policy decision making process. This is performed by modelling the policy process using a declarative process paradigm in conjunction with constraints modelled by expressions in linear temporal logic. We introduce a class of traces, called first-passage traces, to represent the different executions of the declarative processes. Heuristics of what properties a diversity measure of such processes ought to satisfy are used to derive two different metrics for these processes in terms of the set of first-passage traces. These metrics turn out to have formulations in terms of the entropies of two different random variables on the set of traces of the processes. In addition, we introduce a measure of `goodness' whereby a trace is termed {\it good} if it satisfies some prescribed linear temporal logic expression. This allows for comparisons of policy processes with respect to the prescribed notion of `goodness'.

Intelligent signal processing for wireless communications is a vital task in modern wireless systems, but it faces new challenges because of network heterogeneity, diverse service requirements, a massive number of connections, and various radio characteristics. Owing to recent advancements in big data and computing technologies, artificial intelligence (AI) has become a useful tool for radio signal processing and has enabled the realization of intelligent radio signal processing. This survey covers four intelligent signal processing topics for the wireless physical layer, including modulation classification, signal detection, beamforming, and channel estimation. In particular, each theme is presented in a dedicated section, starting with the most fundamental principles, followed by a review of up-to-date studies and a summary. To provide the necessary background, we first present a brief overview of AI techniques such as machine learning, deep learning, and federated learning. Finally, we highlight a number of research challenges and future directions in the area of intelligent radio signal processing. We expect this survey to be a good source of information for anyone interested in intelligent radio signal processing, and the perspectives we provide therein will stimulate many more novel ideas and contributions in the future.

Network-oriented research has been increasingly popular in many scientific areas. In neuroscience research, imaging-based network connectivity measures have become the key for understanding brain organizations, potentially serving as individual neural fingerprints. There are major challenges in analyzing connectivity matrices including the high dimensionality of brain networks, unknown latent sources underlying the observed connectivity, and the large number of brain connections leading to spurious findings. In this paper, we propose a novel blind source separation method with low-rank structure and uniform sparsity (LOCUS) as a fully data-driven decomposition method for network measures. Compared with the existing method that vectorizes connectivity matrices ignoring brain network topology, LOCUS achieves more efficient and accurate source separation for connectivity matrices using low-rank structure. We propose a novel angle-based uniform sparsity regularization that demonstrates better performance than the existing sparsity controls for low-rank tensor methods. We propose a highly efficient iterative Node-Rotation algorithm that exploits the block multi-convexity of the objective function to solve the non-convex optimization problem for learning LOCUS. We illustrate the advantage of LOCUS through extensive simulation studies. Application of LOCUS to Philadelphia Neurodevelopmental Cohort neuroimaging study reveals biologically insightful connectivity traits which are not found using the existing method.

In conducting non-linear dimensionality reduction and feature learning, it is common to suppose that the data lie near a lower-dimensional manifold. A class of model-based approaches for such problems includes latent variables in an unknown non-linear regression function; this includes Gaussian process latent variable models and variational auto-encoders (VAEs) as special cases. VAEs are artificial neural networks (ANNs) that employ approximations to make computation tractable; however, current implementations lack adequate uncertainty quantification in estimating the parameters, predictive densities, and lower-dimensional subspace, and can be unstable and lack interpretability in practice. We attempt to solve these problems by deploying Markov chain Monte Carlo sampling algorithms (MCMC) for Bayesian inference in ANN models with latent variables. We address issues of identifiability by imposing constraints on the ANN parameters as well as by using anchor points. This is demonstrated on simulated and real data examples. We find that current MCMC sampling schemes face fundamental challenges in neural networks involving latent variables, motivating new research directions.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. What if an unmanned fighter or advanced drone, operated with various levels of advanced AI-informed algorithms, engaged in fast air-to-air combat maneuvers in a direct dogfight or close-in engagement with a manned enemy fighter? These questions, which raise substantial tactical, strategic and command and control questions, are fast becoming a near-term reality. NEW AIR FORCE STEALTH BOMBER ARRIVES IN JUST '2 YEARS' "Autonomous systems going up against a manned system in some kind of air-to-air engagement ... is a bold idea," Lt. Gen. "Jack" Shanahan, Director, Joint Artificial Intelligence Center, told The Mitchell Institute for Aerospace Studies in a special video interview series.

The Department of Energy's (DoE) Artificial Intelligence and Technology Office (AITO) has developed the First Five Consortium, which was formed in response to the White House Executive Forum focused on Humanitarian Assistance and Disaster Response, the department reported on Tuesday. "AITO is proud to lead on getting near real-time information into the hands of our First Responders," said Cheryl Ingstad, director of AITO. "This will allow them to save more lives and protect assets and our nation's resources." DoE's First Five Consortium has been co-chaired with Microsoft Corporation, to unify industry, government, non-profit and academia to develop solutions that will improve the impact mitigation of natural disasters within the nation. Microsoft recently established a critical infrastructure team to help advance systems, services, and functions essential to the operation of society and the economy.

The United States Postal Service today suspended measures that caused mail-delivery delays across the country in recent weeks, including an initiative designed to remove hundreds of mail-sorting machines from active rotation. There are no public plans to reinstate machines that have already been taken offline, but starting today, no additional units will be removed from service until after the US presidential election in November. Vice reported last week that the USPS had begun retiring mail-sorting machines across the country "without any official explanation or reason given," significantly slowing employees' ability to organize and send mail. A total of 671 machines, or 10 percent of the postal service's stock, were scheduled to be taken offline, according to The Washington Post. This was part of a larger initiative to "strengthen the Postal Service" by Postmaster General Louis DeJoy, who joined the USPS in June after 35 years as an executive at a large supply-chain logistics company.

Motorists could be allowed to let their cars drive themselves on motorways, using automated technology, as early as next year, under proposals being considered by the government. Manufacturers are expected to roll out the next generation of collision-avoidance and lane-keeping technology in new car models in 2021. They will progress from providing alerts and driver assistance to taking control – and potentially responsibility – for speed and steering once under way. While the technology has been envisaged to help navigate traffic jams at low speed, the government is considering legalising it for use at speeds of up to 70mph in the slow lane of motorways, with the cars automatically staying in lane and slowing down for vehicles in front. A crucial question in the government consultation, launched on Tuesday, is whether the driver will be held legally responsible for the car or whether the car will be defined as automated vehicles.

Postmaster General DeJoy to testify before Senate; American Postal Workers Union president Mark Dimondstein weighs in. "The new Postmaster General has instituted a number of policies that are truly slowing down mail," Mark Dimondstein, president of the American Postal Workers Union, told "America's Newsroom" on Tuesday. Dimondstein made the comment in anticipation of Postmaster General Louis DeJoy testifying on Friday about the U.S. Postal Service amid the battle over mail-in ballots before the Senate Homeland Security and Governmental Affairs Committee. The hearing comes after congressional Democrats over the weekend demanded DeJoy and the chairman of the U.S. Postal Service Board of Governors Robert Duncan testify over recent "sweeping and dangerous operational changes" at the agency that they claim are "slowing" the mail and "jeopardizing the integrity of the 2020 election. A source familiar with the plans told Fox News that DeJoy has agreed to appear on Monday. Host Trace Gallagher asked Dimondstein on Tuesday if he believes, as Democrats contest, that DeJoy "is trying to sabotage the election by making cuts that slow down the flow of mail?" "I can't really judge the motivation," he said in response. "We just have to look at the deeds and the deeds thus far is the new Postmaster General has instituted a number of policies that are truly slowing down mail.

Cybersecurity is a constant concern for businesses of all sizes. There are countless threats to organizational data by a growing host of bad actors, and the risks of a cyberattack on your business are only growing. A recent study found that 76 percent of U.S. businesses had experienced a cyberattack last year alone. Given the large number of remote workers logging into company files from unsecured networks with no IT supervision, it's not a question of "if" but "when" your company will become infiltrated. For most businesses, well-known hacks like ransomware or phishing are top of mind.