We establish versions of Conley's (i) fundamental theorem and (ii) decomposition theorem for a broad class of hybrid dynamical systems. The hybrid version of (i) asserts that a globally-defined "hybrid complete Lyapunov function" exists for every hybrid system in this class. Motivated by mechanics and control settings where physical or engineered events cause abrupt changes in a system's governing dynamics, our results apply to a large class of Lagrangian hybrid systems (with impacts) studied extensively in the robotics literature. Viewed formally, these results generalize those of Conley and Franks for continuous-time and discrete-time dynamical systems, respectively, on metric spaces. However, we furnish specific examples illustrating how our statement of sufficient conditions represents merely an early step in the longer project of establishing what formal assumptions can and cannot endow hybrid systems models with the topologically well characterized partitions of limit behavior that make Conley's theory so valuable in those classical settings.

Assistive robots enable people with disabilities to conduct everyday tasks on their own. However, these tasks can be complex, containing both coarse reaching motions and fine-grained manipulation. For example, when eating, not only does one need to move to the correct food item, but they must also precisely manipulate the food in different ways (e.g., cutting, stabbing, scooping). Shared autonomy methods make robot teleoperation safer and more precise by arbitrating user inputs with robot controls. However, these works have focused mainly on the high-level task of reaching a goal from a discrete set, while largely ignoring manipulation of objects at that goal. Meanwhile, dimensionality reduction techniques for teleoperation map useful high-dimensional robot actions into an intuitive low-dimensional controller, but it is unclear if these methods can achieve the requisite precision for tasks like eating. Our insight is that---by combining intuitive embeddings from learned latent actions with robotic assistance from shared autonomy---we can enable precise assistive manipulation. In this work, we adopt learned latent actions for shared autonomy by proposing a new model structure that changes the meaning of the human's input based on the robot's confidence of the goal. We show convergence bounds on the robot's distance to the most likely goal, and develop a training procedure to learn a controller that is able to move between goals even in the presence of shared autonomy. We evaluate our method in simulations and an eating user study.

By using dissipativity approach, we establish the stability condition for the feedback connection of a deterministic dynamical system $Sigma$ and a stochastic memoryless map $Psi$. After that, we extend the result to the class of large scale systems in which: $Sigma$ consists of many sub-systems; and $Psi$ consists of many "stochastic actuators" and "probability controllers" that control the actuator's output events. We will demonstrate the proposed approach by showing the design procedures to globally stabilize the manufacturing systems while locally balance the stock levels in any production process.

We analyze the computational complexity of motion planning through local "input/output" gadgets with separate entrances and exits, and a subset of allowed traversals from entrances to exits, each of which changes the state of the gadget and thereby the allowed traversals. We study such gadgets in the 0-, 1-, and 2-player settings, in particular extending past motion-planning-through-gadgets work to 0-player games for the first time, by considering "branchless" connections between gadgets that route every gadget's exit to a unique gadget's entrance. Our complexity results include containment in L, NL, P, NP, and PSPACE; as well as hardness for NL, P, NP, and PSPACE. We apply these results to show PSPACE-completeness for certain mechanics in Factorio, [the Sequence], and a restricted version of Trainyard, improving prior results. This work strengthens prior results on switching graphs and reachability switching games.

Public key encryption with equality test (PKEET) allows testing whether two ciphertexts are generated by the same message or not. PKEET is a potential candidate for many practical applications like efficient data management on encrypted databases. Potential applicability of PKEET leads to intensive research from its first instantiation by Yang et al. (CT-RSA 2010). Most of the followup constructions are secure in the random oracle model. Moreover, the security of all the concrete constructions is based on number-theoretic hardness assumptions which are vulnerable in the post-quantum era. Recently, Lee et al. (ePrint 2016) proposed a generic construction of PKEET schemes in the standard model and hence it is possible to yield the first instantiation of PKEET schemes based on lattices. Their method is to use a $2$-level hierarchical identity-based encryption (HIBE) scheme together with a one-time signature scheme. In this paper, we propose, for the first time, a direct construction of a PKEET scheme based on the hardness assumption of lattices in the standard model. More specifically, the security of the proposed scheme is reduces to the hardness of the Learning With Errors problem.

In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in $SE(3)$. The robots have no explicit communication network among them, and they do no know the mass or friction properties of the object, or where they are attached to the object. However, we assume they share data from a common IMU placed arbitrarily on the object. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller's behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller's performance using numerical simulations of a manipulation task in 3D, and with hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodelled effects, such as discretization errors and complex frictional interactions.

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.

We introduce a variant of PCPs, that we refer to as rectangular PCPs, wherein proofs are thought of as square matrices, and the random coins used by the verifier can be partitioned into two disjoint sets, one determining the row of each query and the other determining the *column*.

We construct PCPs that are efficient, short, smooth and (almost-)rectangular. As a key application, we show that proofs for hard languages in NTIME$(2^n)$, when viewed as matrices, are rigid infinitely often. This strengthens and considerably simplifies a recent result of Alman and Chen [FOCS, 2019] constructing explicit rigid matrices in FNP. Namely, we prove the following theorem: - There is a constant $delta in (0,1)$ such that there is an FNP-machine that, for infinitely many $N$, on input $1^N$ outputs $N imes N$ matrices with entries in $mathbb{F}_2$ that are $delta N^2$-far (in Hamming distance) from matrices of rank at most $2^{log N/Omega(log log N)}$.

Our construction of rectangular PCPs starts with an analysis of how randomness yields queries in the Reed--Muller-based outer PCP of Ben-Sasson, Goldreich, Harsha, Sudan and Vadhan [SICOMP, 2006; CCC, 2005]. We then show how to preserve rectangularity under PCP composition and a smoothness-inducing transformation. This warrants refined and stronger notions of rectangularity, which we prove for the outer PCP and its transforms.

Unsupervised machine translation (MT) has recently achieved impressive results with monolingual corpora only. However, it is still challenging to associate source-target sentences in the latent space. As people speak different languages biologically share similar visual systems, the potential of achieving better alignment through visual content is promising yet under-explored in unsupervised multimodal MT (MMT). In this paper, we investigate how to utilize visual content for disambiguation and promoting latent space alignment in unsupervised MMT. Our model employs multimodal back-translation and features pseudo visual pivoting in which we learn a shared multilingual visual-semantic embedding space and incorporate visually-pivoted captioning as additional weak supervision. The experimental results on the widely used Multi30K dataset show that the proposed model significantly improves over the state-of-the-art methods and generalizes well when the images are not available at the testing time.

An optimal base station (BS) location depends on the traffic (user) distribution, propagation pathloss and many system parameters, which renders its analytical study difficult so that numerical algorithms are widely used instead. In this paper, the problem is studied analytically. First, it is formulated as a convex optimization problem to minimize the total BS transmit power subject to quality-of-service (QoS) constraints, which also account for fairness among users. Due to its convex nature, Karush-Kuhn-Tucker (KKT) conditions are used to characterize a globally-optimum location as a convex combination of user locations, where convex weights depend on user parameters, pathloss exponent and overall geometry of the problem. Based on this characterization, a number of closed-form solutions are obtained. In particular, the optimum BS location is the mean of user locations in the case of free-space propagation and identical user parameters. If the user set is symmetric (as defined in the paper), the optimal BS location is independent of pathloss exponent, which is not the case in general. The analytical results show the impact of propagation conditions as well as system and user parameters on optimal BS location and can be used to develop design guidelines.

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.

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

Behavioral research can provide important insights for SE practices. But in performing it, many studies of SE are committing a normative fallacy - they misappropriate normative and prescriptive theories for descriptive purposes. The evidence from reviews of empirical studies of decision making in SE suggests that the normative fallacy may is common. This article draws on cognitive psychology and behavioral economics to explains this fallacy. Because data collection is framed by narrow and empirically invalid theories, flawed assumptions baked into those theories lead to misleading interpretations of observed behaviors and ultimately, to invalid conclusions and flawed recommendations. Researchers should be careful not to rely solely on engineering methods to explain what people do when they do engineering. Instead, insist that descriptive research be based on validated descriptive theories, listen carefully to skilled practitioners, and only rely on validated findings to prescribe what they should do.

In this paper, we present a novel method for line artefacts quantification in lung ultrasound (LUS) images of COVID-19 patients. We formulate this as a non-convex regularisation problem involving a sparsity-enforcing, Cauchy-based penalty function, and the inverse Radon transform. We employ a simple local maxima detection technique in the Radon transform domain, associated with known clinical definitions of line artefacts. Despite being non-convex, the proposed method has guaranteed convergence via a proximal splitting algorithm and accurately identifies both horizontal and vertical line artefacts in LUS images. In order to reduce the number of false and missed detection, our method includes a two-stage validation mechanism, which is performed in both Radon and image domains. We evaluate the performance of the proposed method in comparison to the current state-of-the-art B-line identification method and show a considerable performance gain with 87% correctly detected B-lines in LUS images of nine COVID-19 patients. In addition, owing to its fast convergence, which takes around 12 seconds for a given frame, our proposed method is readily applicable for processing LUS image sequences.

We develop a categorical compositional distributional semantics for Lambek Calculus with a Relevant Modality !L*, which has a limited edition of the contraction and permutation rules. The categorical part of the semantics is a monoidal biclosed category with a coalgebra modality, very similar to the structure of a Differential Category. We instantiate this category to finite dimensional vector spaces and linear maps via "quantisation" functors and work with three concrete interpretations of the coalgebra modality. We apply the model to construct categorical and concrete semantic interpretations for the motivating example of !L*: the derivation of a phrase with a parasitic gap. The effectiveness of the concrete interpretations are evaluated via a disambiguation task, on an extension of a sentence disambiguation dataset to parasitic gap phrase one, using BERT, Word2Vec, and FastText vectors and Relational tensors.

An approach is given for solving large linear systems that combines Krylov methods with use of two different grid levels. Eigenvectors are computed on the coarse grid and used to deflate eigenvalues on the fine grid. GMRES-type methods are first used on both the coarse and fine grids. Then another approach is given that has a restarted BiCGStab (or IDR) method on the fine grid. While BiCGStab is generally considered to be a non-restarted method, it works well in this context with deflating and restarting. Tests show this new approach can be very efficient for difficult linear equations problems.

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.

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.

Soccer great Briana Scurry started playing soccer at 12 on an all boys team and in the goal — the "safest" position for a girl ...

Soccer great Briana Scurry writes an open letter to young athletes about her love for soccer and the importance of taking concussions seriously.

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 […]

The post How Personalized Landing Pages Can Make Your Site More Profitable appeared first on WebFX Blog.

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, […]

The post Top 6 Company Website Design Templates appeared first on WebFX Blog.

By Sci Dev Net Advances in printed solar cell technology promise clean renewable energy, opening possibilities for 1.3 billion people still without electric power in developing countries. The technology, which only requires the use of existing industrial-size printers, can produce … Continue reading →

By Timothy Schoechle Courtesy of Solar Today A Colorado community is developing a community-based clean energy economy. Boulder, Colorado, sits at the foot of the Rocky Mountains a half-hour drive northwest of Denver. It is a city, but still small … Continue reading →

By Andrea Germanos Common Dreams On the heels of clean fuel milestones in Germany and Portugal , a new report finds that the renewable energy industry employed over 8.1 million people worldwide in 2015. According to the International Renewable Energy … Continue reading →

By Lauren McCauley Common Dreams In landmark agreement, California’s last remaining nuclear plant will be replaced by greenhouse-gas-free energy sources A plan to shutter the last remaining nuclear power plant in California and replace it with renewable energy is being … Continue reading →

Welcome to the Design Patterns Demystified (DPD) series, in this edition we are going to discuss Template Design Pattern. So let us understand the why, how, what, and where of Template Design Pattern.

The Why

Let us understand first, why we need this pattern with the help of an example. Let's you are building a reusable library which is orchestrating the operation of buying an item on an e-commerce platform. Now, irrespective of what you are buying, you will follow the same sequence of steps like building your cart, adding an address, filling in payment details, and then finishing the payment. The details in these steps will vary based on what you are buying, how much you are buying, the delivery address, and the preferred mode of payment, but the complete orchestration of steps remains the same.

Welcome back! In the first part of this series, we looked at a very "low-level" way to interact with a relational database by sending it raw SQL strings and retrieving the results. We created a very simple Express application that we can use as an example and deployed it on Heroku with a Postgres database.

In this part, we're going to examine a few libraries which build on top of that foundation, adding layers of abstraction that let you read and manipulate database data in a more "JavaScript-like" way.

Introduction

Ngx-Bootstrap has released a package of open-source tools which are native Angular directives for Bootstrap 3 and 4. It contains all core components powered by Angular. In this article, we will learn about the Typehead component which is a cool feature of Ngx-bootstrap.

What Is Typeahead?

Typeahead — Also known as autocomplete or autosuggest is a language prediction tool that many search interfaces use to provide suggestions for users as they type in a textbox. This is a method for searching and filtering through text. It is also sometimes known as autocomplete, incremental search, search-as-you-type, and inline search.

Handling user input with forms is the cornerstone of many common applications.

Applications use forms to enable users to log in, to update a profile, to enter sensitive information, and to perform many other data-entry tasks

Lambda functions are quite an intuitive concept of Modern C++ introduced in C++11, so there are already tons of articles on lambda function tutorials over the internet. But still, there are some untold things (like IIFE, types of lambda, etc.) left, which nobody talks about. Therefore, here I am to not only show you lambda function in C++, but we'll also cover how it works internally and other aspects of Lambda.

The title of this article is a bit misleading. Because lambda doesn't always synthesize to function pointer. It's an expression (precisely unique closure). But I have kept it that way for simplicity. So from now on, I will use lambda function and expression interchangeably.

PRINCE Raoden of Arelon awoke early that morning, completely unaware that he had been damned for all eternity. What a way to start a novel. As a reader, I don’t think about the first words of a book when…

The Cannabis Issue It's been almost a month since the COVID-19 pandemic forced folks inside and made "social distancing" part of our daily lexicons.…

The Cannabis Issue So many of us are stuck inside right now, and that lack of socializing means we're all probably going a little bit stir crazy.…

[IMAGE-1]After having their school year totally disrupted by the coronavirus pandemic, a return to some semblance of normalcy come summer is all many school-age kids and their families are looking forward to. For many, this anticipation includes annual summer camp traditions, from sleep-away adventures on the lake to fun-filled day camps for arts, learning or team sports.…

Summer Camps 2020 "Regional Summer Camps Hope the Pandemic Doesn't Put Activities on Pause, But Have Backup Plans Ready if it Does" …

We at the Inlander are committed to keeping people informed and connected throughout the coronavirus outbreak. We'll continue to update this page with the latest headlines.…

There’s a cliche that always follows a big tragedy — something we say after natural disasters, economic collapses, school shootings, acts of terrorisms.…

UPDATE: The Department of Veterans Affairs announced after this article was first published that Spokane Veterans Home residents with COVID-19 would be moved to the Mann-Grandstaff VA Medical Center.…

Monty Spears didn't know it at the time, but the last time he'd see his father would be through the window at the Life Care Center of Lewiston.…

We could blame the enormous — and justifiable — success of the Lego flicks for the existence of Playmobil: The Movie, but that would be unfair to all the shameless knockoffs and cinematic coattail riders.…

Sam Mendes' 1917, which took Best Picture and Best Director awards at the Golden Globes earlier this week, looks like a standard period piece.…

[IMAGE-1] First of all: No. Why would a suddenly single dad to traumatized young children leave said shocked and distressed kids with his new fiancée, who is also the sole survivor of her own massive childhood trauma?…

[IMAGE-1] Before smartphones and Instagram, there were influencers, and they could be as shallow, overconfident and pejorative as they are today. This new adaptation of Jane Austen's Emma — the feature debuts of photographer and music-video director Autumn de Wilde and Man Booker Prize-winning novelist turned screenwriter Eleanor Catton — brings that sort of modern frisson to its retelling of the tale of a very rich young woman who amuses herself by interfering in the romantic lives of those around her.…

What am I supposed to say here?…

We at the Inlander remain committed to keeping people informed and connected during the coronavirus outbreak, supporting our readers and local businesses in the ways we always have. We have experienced some disruption in where we distribute papers, but we're stocking and restocking thousands of copies at local Rosauers, Super 1, URM Cash & Carry, Yoke's, Albertson's and Safeway stores, plus Papa Murphy's locations, My Fresh Basket and more.…

Jenny Don't and the Spurs were right in the middle of recording their third full-length album when a vocal polyp put a halt to the process.…

Celebrities: They're just like us! Along with everyone else, famous people are self-isolating at home, and some of them have taken to social media to alleviate the stress of the outside world. We don't need to tell you that events everywhere are canceled, so a few big-time musicians are putting on personal concerts for their fans and followers, and a lot of them — save for that cringe-inducing, star-studded cover of "Imagine" that was going around yesterday — are actually pretty good.…

Welcome to the quarantine.…

Calling all fearless freaks! Mark your calendars: The Flaming Lips have rescheduled their now-canceled April gig at the Fox Theater for March 19, 2021.…