This paper investigates a class of optimal control problems associated with Markov processes with local state information. The decision-maker has only local access to a subset of a state vector information as often encountered in decentralized control problems in multi-agent systems. Under this information structure, part of the state vector cannot be observed. We leverage ab initio principles and find a new form of Bellman equations to characterize the optimal policies of the control problem under local information structures. The dynamic programming solutions feature a mixture of dynamics associated unobservable state components and the local state-feedback policy based on the observable local information. We further characterize the optimal local-state feedback policy using linear programming methods. To reduce the computational complexity of the optimal policy, we propose an approximate algorithm based on virtual beliefs to find a sub-optimal policy. We show the performance bounds on the sub-optimal solution and corroborate the results with numerical case studies.

We investigate learnability of possibilistic theories from entailments in light of Angluin's exact learning model. We consider cases in which only membership, only equivalence, and both kinds of queries can be posed by the learner. We then show that, for a large class of problems, polynomial time learnability results for classical logic can be transferred to the respective possibilistic extension. In particular, it follows from our results that the possibilistic extension of propositional Horn theories is exactly learnable in polynomial time. As polynomial time learnability in the exact model is transferable to the classical probably approximately correct model extended with membership queries, our work also establishes such results in this model.

We propose an augmented Lagrangian preconditioner for a three-field stress-velocity-pressure discretization of stationary non-Newtonian incompressible flow with an implicit constitutive relation of power-law type. The discretization employed makes use of the divergence-free Scott-Vogelius pair for the velocity and pressure. The preconditioner builds on the work [P. E. Farrell, L. Mitchell, and F. Wechsung, SIAM J. Sci. Comput., 41 (2019), pp. A3073-A3096], where a Reynolds-robust preconditioner for the three-dimensional Newtonian system was introduced. The preconditioner employs a specialized multigrid method for the stress-velocity block that involves a divergence-capturing space decomposition and a custom prolongation operator. The solver exhibits excellent robustness with respect to the parameters arising in the constitutive relation, allowing for the simulation of a wide range of materials.

Monitoring users on large computing platforms such as high performance computing (HPC) and cloud computing systems is non-trivial. Utilities such as process viewers provide limited insight into what users are running, due to granularity limitation, and other sources of data, such as system call tracing, can impose significant operational overhead. However, despite technical and procedural measures, instances of users abusing valuable HPC resources for personal gains have been documented in the past cite{hpcbitmine}, and systems that are open to large numbers of loosely-verified users from around the world are at risk of abuse. In this paper, we show how electrical power consumption data from an HPC platform can be used to identify what programs are executed. The intuition is that during execution, programs exhibit various patterns of CPU and memory activity. These patterns are reflected in the power consumption of the system and can be used to identify programs running. We test our approach on an HPC rack at Lawrence Berkeley National Laboratory using a variety of scientific benchmarks. Among other interesting observations, our results show that by monitoring the power consumption of an HPC rack, it is possible to identify if particular programs are running with precision up to and recall of 95\% even in noisy scenarios.

Neural networks have opened up many new opportunities to utilize remotely sensed images in meteorology. Common applications include image classification, e.g., to determine whether an image contains a tropical cyclone, and image translation, e.g., to emulate radar imagery for satellites that only have passive channels. However, there are yet many open questions regarding the use of neural networks in meteorology, such as best practices for evaluation, tuning and interpretation. This article highlights several strategies and practical considerations for neural network development that have not yet received much attention in the meteorological community, such as the concept of effective receptive fields, underutilized meteorological performance measures, and methods for NN interpretation, such as synthetic experiments and layer-wise relevance propagation. We also consider the process of neural network interpretation as a whole, recognizing it as an iterative scientist-driven discovery process, and breaking it down into individual steps that researchers can take. Finally, while most work on neural network interpretation in meteorology has so far focused on networks for image classification tasks, we expand the focus to also include networks for image translation.

We consider generic optimal Bayesian inference, namely, models of signal reconstruction where the posterior distribution and all hyperparameters are known. Under a standard assumption on the concentration of the free energy, we show how replica symmetry in the strong sense of concentration of all multioverlaps can be established as a consequence of the Franz-de Sanctis identities; the identities themselves in the current setting are obtained via a novel perturbation of the prior distribution of the signal. Concentration of multioverlaps means that asymptotically the posterior distribution has a particularly simple structure encoded by a random probability measure (or, in the case of binary signal, a non-random probability measure). We believe that such strong control of the model should be key in the study of inference problems with underlying sparse graphical structure (error correcting codes, block models, etc) and, in particular, in the derivation of replica symmetric formulas for the free energy and mutual information in this context.

In this paper, we analyze the symbol error rate (SER) performance of the simultaneous wireless information and power transfer (SWIPT) enabled three-node differential decode-and-forward (DDF) relay networks, which adopt the power splitting (PS) protocol at the relay. The use of non-coherent differential modulation eliminates the need for sending training symbols to estimate the instantaneous channel state informations (CSIs) at all network nodes, and therefore improves the power efficiency, as compared with the coherent modulation. However, performance analysis results are not yet available for the state-of-the-art detectors such as the approximate maximum-likelihood detector. Existing works rely on Monte-Carlo simulation to show that there exists an optimal PS ratio that minimizes the overall SER. In this work, we propose a near-optimal detector with linear complexity with respect to the modulation size. We derive an accurate approximate SER expression, based on which the optimal PS ratio can be accurately estimated without requiring any Monte-Carlo simulation.

The interoperability of proof assistants and the integration of their libraries is a highly valued but elusive goal in the field of theorem proving. As a preparatory step, in previous work, we translated the libraries of multiple proof assistants, specifically the ones of Coq, HOL Light, IMPS, Isabelle, Mizar, and PVS into a universal format: OMDoc/MMT.

Each translation presented tremendous theoretical, technical, and social challenges, some universal and some system-specific, some solvable and some still open. In this paper, we survey these challenges and compare and evaluate the solutions we chose.

We believe similar library translations will be an essential part of any future system interoperability solution and our experiences will prove valuable to others undertaking such efforts.

Vision-and-Language Navigation (VLN) requires an agent to follow natural-language instructions, explore the given environments, and reach the desired target locations. These step-by-step navigational instructions are crucial when the agent is navigating new environments about which it has no prior knowledge. Most recent works that study VLN observe a significant performance drop when tested on unseen environments (i.e., environments not used in training), indicating that the neural agent models are highly biased towards training environments. Although this issue is considered as one of the major challenges in VLN research, it is still under-studied and needs a clearer explanation. In this work, we design novel diagnosis experiments via environment re-splitting and feature replacement, looking into possible reasons for this environment bias. We observe that neither the language nor the underlying navigational graph, but the low-level visual appearance conveyed by ResNet features directly affects the agent model and contributes to this environment bias in results. According to this observation, we explore several kinds of semantic representations that contain less low-level visual information, hence the agent learned with these features could be better generalized to unseen testing environments. Without modifying the baseline agent model and its training method, our explored semantic features significantly decrease the performance gaps between seen and unseen on multiple datasets (i.e. R2R, R4R, and CVDN) and achieve competitive unseen results to previous state-of-the-art models. Our code and features are available at: https://github.com/zhangybzbo/EnvBiasVLN

This paper illustrates five different techniques to assess the distinctiveness of topics, key terms and features, speed of information dissemination, and network behaviors for Covid19 tweets. First, we use pattern matching and second, topic modeling through Latent Dirichlet Allocation (LDA) to generate twenty different topics that discuss case spread, healthcare workers, and personal protective equipment (PPE). One topic specific to U.S. cases would start to uptick immediately after live White House Coronavirus Task Force briefings, implying that many Twitter users are paying attention to government announcements. We contribute machine learning methods not previously reported in the Covid19 Twitter literature. This includes our third method, Uniform Manifold Approximation and Projection (UMAP), that identifies unique clustering-behavior of distinct topics to improve our understanding of important themes in the corpus and help assess the quality of generated topics. Fourth, we calculated retweeting times to understand how fast information about Covid19 propagates on Twitter. Our analysis indicates that the median retweeting time of Covid19 for a sample corpus in March 2020 was 2.87 hours, approximately 50 minutes faster than repostings from Chinese social media about H7N9 in March 2013. Lastly, we sought to understand retweet cascades, by visualizing the connections of users over time from fast to slow retweeting. As the time to retweet increases, the density of connections also increase where in our sample, we found distinct users dominating the attention of Covid19 retweeters. One of the simplest highlights of this analysis is that early-stage descriptive methods like regular expressions can successfully identify high-level themes which were consistently verified as important through every subsequent analysis.

The increasing ubiquity of low-cost wireless sensors in smart homes and buildings has enabled users to easily deploy systems to remotely monitor and control their environments. However, this raises privacy concerns for third-party occupants, such as a hotel room guest who may be unaware of deployed clandestine sensors. Previous methods focused on specific modalities such as detecting cameras but do not provide a generalizable and comprehensive method to capture arbitrary sensors which may be "spying" on a user. In this work, we seek to determine whether one can walk in a room and detect any wireless sensor monitoring an individual. As such, we propose SnoopDog, a framework to not only detect wireless sensors that are actively monitoring a user, but also classify and localize each device. SnoopDog works by establishing causality between patterns in observable wireless traffic and a trusted sensor in the same space, e.g., an inertial measurement unit (IMU) that captures a user's movement. Once causality is established, SnoopDog performs packet inspection to inform the user about the monitoring device. Finally, SnoopDog localizes the clandestine device in a 2D plane using a novel trial-based localization technique. We evaluated SnoopDog across several devices and various modalities and were able to detect causality 96.6% percent of the time, classify suspicious devices with 100% accuracy, and localize devices to a sufficiently reduced sub-space.

Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method, however, its accuracy in detection is only ~70-75%. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80-98%, but similar accuracy of 70%. To enhance the accuracy of CT imaging detection, we developed an open-source set of algorithms called CovidCTNet that successfully differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 90% compared to radiologists (70%). The model is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. In order to facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and parametric details in an open-source format. Open-source sharing of our CovidCTNet enables developers to rapidly improve and optimize services, while preserving user privacy and data ownership.

An interesting and frequent type of multi-word expression (MWE) is the headless MWE, for which there are no true internal syntactic dominance relations; examples include many named entities ("Wells Fargo") and dates ("July 5, 2020") as well as certain productive constructions ("blow for blow", "day after day"). Despite their special status and prevalence, current dependency-annotation schemes require treating such flat structures as if they had internal syntactic heads, and most current parsers handle them in the same fashion as headed constructions. Meanwhile, outside the context of parsing, taggers are typically used for identifying MWEs, but taggers might benefit from structural information. We empirically compare these two common strategies--parsing and tagging--for predicting flat MWEs. Additionally, we propose an efficient joint decoding algorithm that combines scores from both strategies. Experimental results on the MWE-Aware English Dependency Corpus and on six non-English dependency treebanks with frequent flat structures show that: (1) tagging is more accurate than parsing for identifying flat-structure MWEs, (2) our joint decoder reconciles the two different views and, for non-BERT features, leads to higher accuracies, and (3) most of the gains result from feature sharing between the parsers and taggers.

Motivated by the current demand of clinical governance, surgical simulation is now a well-established modality for basic skills training and assessment. The practical deployment of the technique is a multi-disciplinary venture encompassing areas in engineering, medicine and psychology. This paper provides an overview of the key topics involved in surgical simulation and associated technical challenges. The paper discusses the clinical motivation for surgical simulation, the use of virtual environments for surgical training, model acquisition and simplification, deformable models, collision detection, tissue property measurement, haptic rendering and image synthesis. Additional topics include surgical skill training and assessment metrics as well as challenges facing the incorporation of surgical simulation into medical education curricula.

Different state-of-the-art methods of the detection of schizophrenia symptoms based on the estimation of text coherence have been analyzed. The analysis of a text at the level of phrases has been suggested. The method based on the graph of the consistency of phrases has been proposed to evaluate the semantic coherence and the cohesion of a text. The semantic coherence, cohesion, and other linguistic features (lexical diversity, lexical density) have been taken into account to form feature vectors for the training of a model-classifier. The training of the classifier has been performed on the set of English-language interviews. According to the retrieved results, the impact of each feature on the output of the model has been analyzed. The results obtained can indicate that the proposed method based on the graph of the consistency of phrases may be used in the different tasks of the detection of mental illness.

In this paper, we present a novel MaxSAT-based technique to compute Maximum Probability Minimal Cut Sets (MPMCSs) in fault trees. We model the MPMCS problem as a Weighted Partial MaxSAT problem and solve it using a parallel SAT-solving architecture. The results obtained with our open source tool indicate that the approach is effective and efficient.

Despite the improvements in helmet technology, helmets may prevent skull fractures, but they do not prevent concussions.

After she was hit, retired soccer star Briana Scurry felt off balance, sensitive to light and sound,and felt intense pain in her head and neck.

Retired soccer star Briana Scurry talks about how frustrating and complicated it is trying to explain what it feels like to have symptoms from a concussion and why bouncing back is not always an option.

If you don't feel right after a concussion, talk to your parents, your coach, your doctor ... get a second, third, fourth opinion ... Do not accept that you will not get better.

One out of two girls will sustain a concussion playing soccer, but most will recover and return to play with ease. Nevertheless, awareness and education are key to keeping players safe.

Was her depression physiological from the hit to her head or because her professional soccer career was over?

As someone who had a phenomenal career in professional soccer and that had a career-ending head injury, Briana Scurry knows she can help other female — and male — athletes.

Bob Duncan talks about what happened to his son when he returned to college and to his midterm exams only 24 hours after his concussion.

Are sports organizations like FIFA taking concussions in sports seriously enough?

What happens when the drive to play outweighs the potential risk of injury? Some high school athletes are finding ways around the precautions coaching and medical staff take to ensure their safety.

Graphic design is everywhere — it’s used in traditional marketing efforts like billboards and fliers, and more importantly, it’s used in nearly every single digital marketing initiative from web design to social media marketing. If you’re a business that’s working with a digital marketing agency for any number of marketing campaigns (especially web design), it’s […]

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Personalization is one of the most effective marketing techniques to connect with customers online. While the exact methods are different for every business, adding personalized elements to landing pages is a proven method of driving conversions on your site. But why is it so successful? The simple answer is that personalization shows customers that you […]

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Traffic isn’t great, online sales are even worse, and let’s not talk about the lack of phone calls. Everyone, including you, is wondering the same thing — is your website a failure? Not yet, and not if you have anything to say about it. While a failing website can seem like a problem without a […]

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Does your website feature design straight out of the ’90s and functionality from the stone age? If so, it’s time for an upgrade — and WebFX can help. When it comes to website redesign checklists, we’re at the top of our game, and we know how to get things done. But where do you start […]

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If you’re not already thinking about 2020 web design, the time is now. Already, web design trends for 2020 have started to emerge, and if you want to stay on-trend and engage site visitors, it’s crucial to pay attention. But what is the future of web design in 2020? Will everything change? Well — not […]

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In this article, we'll explore 10 quick and easy ways to improve your site's accessibility.

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WordPress powers 35% of all websites, which makes WordPress sites a go-to target for hackers. If you’re like most WordPress site owners, you’re probably asking the same question: Is my WordPress site secure? While you can’t guarantee site security, you can take several steps to improve and maximize your WordPress security. Keep reading to learn […]

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Are you looking to generate more leads and revenue with your website? If so, it’s time to consider web design for lead generation to help you create a website that caters to your audience and encourages them to become leads for your business.  On this page, we’ll provide you with five lead generation website design […]

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Did you know that breaking the Americans with Disabilities Act (ADA) can result in a six-figure fine? For every violation, companies can receive a $150,000 fine — and if you have a WordPress site, you could be liable. While WordPress aims to ensure website accessibility, it cannot guarantee it since every site owner customizes the […]

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Subscribe to our YouTube channel for the latest in digital marketing! we know you’ll love this additional resource! (how to host a website)   Transcript: What is website hosting?  This is to make a point, I promise.  When you go to a party, there’s always a host. The host is usually the one who sets […]

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Dozens of people find your business when looking for a type of product but aren’t sure which product fits their needs best. With a well-designed and organized category page, you’ll help people browse products easier and find what they want. To help you get inspired, let’s take a look at some excellent category page design […]

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Are you looking for a content management system (CMS) that will help you create the digital content you need? With so many options on the market, it’s challenging to know which one is the best CMS software for your business. On this page, we’ll take a look at the six best CMS’s for website development […]

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Subscribe to our YouTube channel for the latest in digital marketing! Transcript: Your website isn’t set in stone, so you shouldn’t treat it like it is.  Technology and the internet change quickly, and often. You should update your website regularly to keep up with the times. Having an up-to-date and optimized site creates a great […]

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If you’re looking to grow your business online, it’s time to start setting up different types of website conversions to help your company succeed. Whether you’re looking to earn more email subscribers or sell more products, you can set conversion goals that grow your business. On this page, we’ll discuss what a conversion goal is, […]

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The nail biting. The endless coffee. The sleepless nights. You can’t keep it up, but you need to know: Is my site hacked? Good news, you don’t have to stay up all night, grind down your nails, or consume all the coffee in the building to find out if your website has been hacked. You […]

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Web design is responsible for nearly 95% of a visitor’s first impression of your business. That’s why it’s more important than ever to incorporate modern web design into your marketing strategy. But what modern web design trends are on the horizon for 2020 — and how can you use them to freshen up your site? […]

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Did you know that 75% of opinions on website credibility comes from design? If you want people to look at your services and find you credible, you must invest in web design for services pages to provide your audience with a positive experience. By looking at some web design examples for service pages, you’ll get […]

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What do Amazon, Hershey’s, and The Wall Street Journal have in common? They’ve all gotten named in lawsuits related to website accessibility and the Americans with Disabilities Act (ADA). They aren’t alone, either. In 2018, more than 2000 website accessibility lawsuits (a 177% increase from 2017) got filed, emphasizing the increased importance and focus on […]

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As a small or midsize business (SMB), your company website is often the first touchpoint for potential clients — and you want it to make a great first impression. The secret to hitting home with your audience is to have a sophisticated and lively website design that’s aesthetically pleasing and provides great user experience (UX). […]

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When you’re trying to grow your business online, you must monitor vital metrics to ensure your business is growing. One important metric is your website’s conversions. Conversions help you determine if you’re driving success with your digital marketing campaigns. So, what is website conversion? How can you improve your website conversion rate? Keep reading to […]

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Are you looking to build a new site for your business? If so, company website design templates can help you create the website you want. With so many templates available, how do you determine which one is best for your business? On this page, we’ll provide you with the top six company website design templates, […]

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Are you looking to start 2020 with a fresh web design for your business? If so, you must know what you need to do in 2020 to have a website that drives success for your business. With website statistics for 2020, you can see what to do and what to avoid, which will help you […]

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Did you know that over 70% of people will research a company on the web before deciding to buy or visit, yet 46% of small businesses in the U.S. don’t have a website? If you don’t have a site, people can’t research your company and determine if you’re a good fit for their needs. If […]

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Your website is your virtual business card and it often provides the first impression of your business to future customers — making it one of the most important aspects of your company. But if your website still has cobwebs from the 2000s, it’s time to put together a website redesign process. A website redesign process […]

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