A special created to explore the enormously popular Chilean television series, Los 80, which tells the story of the Herrera family living their lives under the military regime. Features a video interview with Boris Quercia (of "Sexo con Amor" and "El rey de los huevones"), a text interview with screenwriter, Rodrigo Cuevas, a gallery of behind the scenes moments, and a interactive time line which shows how the Herrera family interacts with Chilean history.

Editor’s note: The Gazette sports staff has compiled lists of its top 15 favorite sports movies. Each day, a different staffer will share some insight into one of their favorites. Some of them...

DES MOINES — The Iowa Supreme Court has asked a group of criminal and civil lawyers, judges and court staff from judicial districts across the state to make recommendations on how criminal and...

En Australie, les paysages photographiés sont toujours un régal pour les yeux. Le photographe allemand Tom Hegen nous offre des clichés aériens à couper le souffle. Il nous emmène en Australie occidentale à la découverte des lacs salés. Ses plans d’eaux suivent en réalité les traces des anciens systèmes fluviaux. La région a été façonnée par le climat […]

Cette période inédite de confinement a inspiré de nombreux artistes, dont fait partie l’illustrateur Mariano Pascual. L’artiste argentin établi à Barcelone a traduit en images les sentiments flous, désordonnés et un brin anxiogènes induits par la pandémie. Stocks de papier toilette, télétravail et laisser-aller derrière les portes closes de son domicile… À travers une série de visuels […]

DES MOINES — The Iowa Supreme Court has asked a group of criminal and civil lawyers, judges and court staff from judicial districts across the state to make recommendations on how criminal and civil jury trials will resume with coronavirus health restrictions.

The court is asking the 17-member Jumpstart Jury Trials Task Force to develop temporary policies and procedures for jury trials that will ensure the “fundamental rights of a defendant” to a jury trial, while at the same time “protecting the health and safety” of the jurors, attorneys, judges and the public, said Des Moines lawyer Guy Cook, co-chairman of the task force.

The court, Cook said Thursday, has put together a “good cross-section” of professionals who have experience with civil and criminal trials.

Task force members are:

• Associate Supreme Court Justice Mark McDermott, chairman

• Guy Cook, Des Moines criminal and civil attorney, co-chairman

• 4th Judicial District Judge Michael Hooper

• 5th Judicial District Judge David Porter

• Angela Campbell, Des Moines criminal defense attorney

• Jim Craig, Cedar Rapids civil attorney, president of Iowa Defense Counsel Association

• Janietta Criswell, clerk and jury manager, 8th Judicial District, Ottumwa

• Kathy Gaylord, district court administrator, 7th Judicial District, Davenport

• Patrick Jennings, Woodbury county attorney, Sioux City

• Julie Kneip, clerk of court, 2nd Judicial District, Fort Dodge

• Bill Miller, Des Moines civil attorney, chairman of Iowa State Bar Association litigation

• Todd Nuccio, Iowa state court administrator

• Jerry Schnurr, Fort Dodge civil attorney and president-elect of Iowa State Bar Association

• Jennifer Solberg, Woodbury County chief public defender

• Chad Swanson, Waterloo civil attorney, president of Iowa Association of Justice

• Brian Williams, Black Hawk county attorney

• Mark Headlee, information technology director of Iowa Judicial Branch

The committee will review the current schedule to resume jury trials that the court has established in consultation with public health officials and other health care providers, and recommend whether the schedule should be altered, according to the court’s order.

Jury criminal trials can resume July 13 and civil trials Aug. 3, according to the order.

The task force also will make recommendations for how those trials should proceed, according to the court’s order.

Members should develop policies and procedures aimed at protecting the health and safety of jurors, court staff, attorneys, judges and visitors throughout the trial process, particularly during the identification of potential jurors, summons of potential jurors, jury selection, trials, jury instructions and jury deliberations.

Cook said members will have to consider the challenges for each type of trial. More jurors, for example, are needed in a criminal case, so space and logistics will have to be considered with social distancing requirements.

That will be more difficult in the rural courthouses that have less space.

A pool of 80 to 100 potential jurors are sometimes summoned for felony trials in larger counties, but that, too, may be a challenge with social distancing.

Another possibility would be requiring masks, but how will a mask affect the credibility of a witness if it hides the person’s facial expressions, Cook said.

These are all issues the members may encounter.

Steve Davis, Iowa Judicial Branch spokesman, said the goal is one uniform statewide plan, but it’s possible that each district may have some discretion, as in the previous orders issued during this pandemic, because of the differences in each county.

Davis said the task force members were chosen based on gender, background and geographic area.

The recommendations should be submitted to the court the first week in June.

Davis said he didn’t yet know when the task force would start meeting by phone or video conference or how often.

Comments: (319) 398-8318; trish.mehaffey@thegazette.com

In today’s Adobe Photoshop tutorial I’m going to show you how to turn anything into gold using this simple combination of Photoshop filters and tools. The effect smooths out the details of a regular image and adds an array of shiny reflections to mimic the appearance of a polished metal statue. A gradient overlay gives […]

The post Video Tutorial: How to Turn Anything into Gold in Photoshop appeared first on Spoon Graphics.

In today’s Adobe Illustrator tutorial I’m going to take you through the process of creating a colourful embroidered patch, based on the kinds of designs associated with National Parks. The artwork will incorporate a landscape scene at sunset, which helps to keep the design simple with a silhouette graphic and a warm colour palette. Stick […]

The post Video Tutorial: How to Create an Embroidered Patch Design in Illustrator appeared first on Spoon Graphics.

In today’s Adobe Photoshop video tutorial I’m going to take you through my process of creating a vintage style advertisement poster with letterpress print effects. We’ll start by laying out the design with a selection of fonts inspired by the era of wood type, along with some hand-drawn graphic elements using a limited 3-colour palette. […]

The post Video Tutorial: Vintage Letterpress Poster Design in Photoshop appeared first on Spoon Graphics.

Summer is in full swing here in the states! It’s a perfect time to grab your skateboard and go cruising. Today we’re going to learn how to design flat skateboards and colorful vector longboards in Adobe Illustrator! We’ll be working with Clipping Masks, Stroke, and Pathfinder panel. Let’s get started! Tutorial Details Program: Adobe Illustrator CC Difficulty: […]

The post 10 Step Tutorial: How to Design Flat Skateboards Using Adobe Illustrator appeared first on Vectips.

There is no better time than the end of the year for some fresh inspiration! One of the most popular trends this year, features splitscreen layouts, lots of white space, clean typography and subtle effects. With this playful trend in mind, I’ve created a two-part tutorial to show you how to use flexbox, 3D transforms […]

The post Tutorial: Trendy Splitscreen Layout With CSS3 Animations (Pt. 1) appeared first on Web Designer Wall.

Last week I demonstrated how to build a split-screen website layout using CSS flexbox and viewport units that offers an alternative way to present a brand’s featured content. Clicking on one side or the other navigates further into the site without a page load, using CSS transitions and 3d transforms. This week, I’ll show you […]

The post Tutorial: Duo Layout With CSS3 Animations & Transitions (Pt. 2) appeared first on Web Designer Wall.

Have you got yourself a Sony Xperia Z1 Compact but not sure how to do something on it? Don’t worry, we’ve come up with a comprehensive guide for all the things your handset is capable of. Navigate the various sections using the links below. If you can’t find what you’re looking for just leave a … Continue reading Sony Xperia Z1 Compact Complete Guide →

I wish I had found Alix Kates Shulman’s memoir "To Love What Is: A Marriage Transformed" in the first month of my husband’s severe TBI, and yet I may not have absorbed it the way I did reading it fifteen years post-injury.

Welcome back to another Adobe Illustrator based tutorial, in which we're going to take a close look behind the process of creating a simple iPhone icon, using nothing more than some basic geometric shapes that we're going to adjust here and there. 1. Set Up a New Project File As with any new project, we’re […]

The post Illustrator Tutorial: How to Create an iPhone Icon appeared first on Bittbox.

In today’s tutorial, we're going to take a close look behind the process of creating a simple computer icon, and see how easy it is to build one of our one using nothing more than some basic geometric shapes. 1. Set Up a New Project File As with any new project, we’re going to kick […]

The post Illustrator Tutorial: How to Create a Simple Computer Icon appeared first on Bittbox.

In today’s tutorial, we’re going to take an in-depth look behind the process of creating a folder icon, and see how easy it is to build one from scratch using nothing more than a couple of basic geometric shapes, which we’re going to adjust here and there. So, assuming you already have Illustrator up and […]

The post Illustrator Tutorial: How to Create a Folder Icon appeared first on Bittbox.

Welcome back to another Illustrator based tutorial, in which we’re going to learn how to create a simple watch icon, using nothing more than a couple of basic geometric shapes and tools. So, assuming you already have the software running in the background, bring it up and let’s jump straight into it! 1. Set Up […]

The post Illustrator Tutorial: How to Create a Watch Icon appeared first on Bittbox.

Welcome back to another Illustrator based tutorial, in which we’re going to take a close look behind the process of creating an incognito icon, using nothing more than a couple of simple shapes and tools. So, assuming you already have the software running in the background, bring it up and let’s jump straight into it! […]

The post Illustrator Tutorial: How to Create an Icognito Icon appeared first on Bittbox.

In today’s tutorial, we’re going to take a quick look at the process of creating an Ice Cream icon, and learn how easy it is to build one from scratch using nothing more than a couple of basic geometric shapes that we’re going to adjust here and there. So, assuming you already have the software […]

The post Illustrator Tutorial: How to Create an Ice Cream icon appeared first on Bittbox.

n today’s tutorial, we’re going to take a quick look behind the process of creating a notification bell icon, and see how easy it is to do so using nothing more than a couple of basic geometric shapes and tools. So, assuming you already have the software up and running, let’s jump straight into it! […]

The post Illustrator Tutorial: How to Create a Notification Bell Icon appeared first on Bittbox.

Welcome back to another Illustrator based tutorial, in which we’re going to learn how to create a recycle bin notification icon, using nothing more than a couple of basic geometric shapes that we’re going to adjust here and there. So, assuming you already have the software running in the background, bring it up and let’s […]

The post Illustrator Tutorial: How to Create a Recycle Bin Notification Icon appeared first on Bittbox.

We're so excited to have a huge guest on the show – big time comedian and noted metalhead, Brian Posehn,...

The post METAL INJECTION LIVECAST #551 - Where Nickelback Shines with special guest Comedian Brian Posehn appeared first on Metal Injection.

In this article, we characterize nearly invariant subspaces of finite defect for the backward shift operator acting on the vector-valued Hardy space which is a vectorial generalization of a result of Chalendar-Gallardo-Partington (C-G-P). Using this characterization of nearly invariant subspace under the backward shift we completely describe the almost invariant subspaces for the shift and its adjoint acting on the vector valued Hardy space.

In this note, we unify and extend various concepts in the area of $G$-complete reducibility, where $G$ is a reductive algebraic group. By results of Serre and Bate--Martin--R"{o}hrle, the usual notion of $G$-complete reducibility can be re-framed as a property of an action of a group on the spherical building of the identity component of $G$. We show that other variations of this notion, such as relative complete reducibility and $sigma$-complete reducibility, can also be viewed as special cases of this building-theoretic definition, and hence a number of results from these areas are special cases of more general properties.

Given graphs $T$ and $H$, the generalized Tur'an number ex$(n,T,H)$ is the maximum number of copies of $T$ in an $n$-vertex graph with no copies of $H$. Alon and Shikhelman, using a result of ErdH os, determined the asymptotics of ex$(n,K_3,H)$ when the chromatic number of $H$ is greater than 3 and proved several results when $H$ is bipartite. We consider this problem when $H$ has chromatic number 3. Even this special case for the following relatively simple 3-chromatic graphs appears to be challenging.

The suspension $widehat H$ of a graph $H$ is the graph obtained from $H$ by adding a new vertex adjacent to all vertices of $H$. We give new upper and lower bounds on ex$(n,K_3,widehat{H})$ when $H$ is a path, even cycle, or complete bipartite graph. One of the main tools we use is the triangle removal lemma, but it is unclear if much stronger statements can be proved without using the removal lemma.

Let $chi_{Delta}(mathbb{R}^{n})$ denote the minimum number of colors needed to color $mathbb{R}^{n}$ so that there will not be a monochromatic equilateral triangle with side length $1$. Using the slice rank method, we reprove a result of Frankl and Rodl, and show that $chi_{Delta}left(mathbb{R}^{n} ight)$ grows exponentially with $n$. This technique substantially improves upon the best known quantitative lower bounds for $chi_{Delta}left(mathbb{R}^{n} ight)$, and we obtain [ chi_{Delta}left(mathbb{R}^{n} ight)>(1.01446+o(1))^{n}. ]

We study an equivariant extension of the Batalin-Vilkovisky formalism for quantizing gauge theories. Namely, we introduce a general framework to encompass failures of the quantum master equation, and we apply it to the natural equivariant extension of AKSZ solutions of the classical master equation (CME). As examples of the construction, we recover the equivariant extension of supersymmetric Yang-Mills in 2d and of Donaldson-Witten theory.

A natural problem in the context of the coupon collector's problem is the behavior of the maximum of independent geometrically distributed random variables (with distinct parameters). This question has been addressed by Brennan et al. (British J. of Math. & CS. 8 (2015), 330-336). Here we provide explicit asymptotic expressions for the moments of that maximum, as well as of the maximum of exponential random variables with corresponding parameters. We also deal with the probability of each of the variables being the maximal one.

The calculations lead to expressions involving Hurwitz's zeta function at certain special points. We find here explicitly the values of the function at these points. Also, the distribution function of the maximum we deal with is closely related to the generating function of the partition function. Thus, our results (and proofs) rely on classical results pertaining to the partition function.

The characterization of phase dynamics in coupled oscillators offers insights into fundamental phenomena in complex systems. To describe the collective dynamics in the oscillatory system, order parameters are often used but are insufficient for identifying more specific behaviors. We therefore propose a topological approach that constructs quantitative features describing the phase evolution of oscillators. Here, the phase data are mapped into a high-dimensional space at each time point, and topological features describing the shape of the data are subsequently extracted from the mapped points. We extend these features to time-variant topological features by considering the evolution time, which serves as an additional dimension in the topological-feature space. The resulting time-variant features provide crucial insights into the time evolution of phase dynamics. We combine these features with the machine learning kernel method to characterize the multicluster synchronized dynamics at a very early stage of the evolution. Furthermore, we demonstrate the usefulness of our method for qualitatively explaining chimera states, which are states of stably coexisting coherent and incoherent groups in systems of identical phase oscillators. The experimental results show that our method is generally better than those using order parameters, especially if only data on the early-stage dynamics are available.

We introduce a Gaussian measure formally preserved by the 2-dimensional Primitive Equations driven by additive Gaussian noise. Under such measure the stochastic equations under consideration are singular: we propose a solution theory based on the techniques developed by Gubinelli and Jara in cite{GuJa13} for a hyperviscous version of the equations.

In this paper we construct an equivariant embedding of the affine space $mathbb{A}^n$ with the translation group action into a complete non-projective algebraic variety $X$ for all $n geq 3$. The theory of toric varieties is used as the main tool for this construction. In the case of $n = 3$ we describe the orbit structure on the variety $X$.

We prove that all non-degenerate relative equilibria of the planar Newtonian $n$--body problem can be continued to spaces of constant curvature $kappa$, positive or negative, for small enough values of this parameter. We also compute the extension of some classical relative equilibria to curved spaces using numerical continuation. In particular, we extend Lagrange's triangle configuration with different masses to both positive and negative curvature spaces.

In this paper we study manifolds $M_{Sigma}$ with fibered singularities, more specifically, a relevant space $Riem^{psc}(X_{Sigma})$ of Riemannian metrics with positive scalar curvature. Our main goal is to prove that the space $Riem^{psc}(X_{Sigma})$ is homotopy invariant under certain surgeries on $M_{Sigma}$.

Input transformation based defense strategies fall short in defending against strong adversarial attacks. Some successful defenses adopt approaches that either increase the randomness within the applied transformations, or make the defense computationally intensive, making it substantially more challenging for the attacker. However, it limits the applicability of such defenses as a pre-processing step, similar to computationally heavy approaches that use retraining and network modifications to achieve robustness to perturbations. In this work, we propose a defense strategy that applies random image corruptions to the input image alone, constructs a self-correlation based subspace followed by a projection operation to suppress the adversarial perturbation. Due to its simplicity, the proposed defense is computationally efficient as compared to the state-of-the-art, and yet can withstand huge perturbations. Further, we develop proximity relationships between the projection operator of a clean image and of its adversarially perturbed version, via bounds relating geodesic distance on the Grassmannian to matrix Frobenius norms. We empirically show that our strategy is complementary to other weak defenses like JPEG compression and can be seamlessly integrated with them to create a stronger defense. We present extensive experiments on the ImageNet dataset across four different models namely InceptionV3, ResNet50, VGG16 and MobileNet models with perturbation magnitude set to {epsilon} = 16. Unlike state-of-the-art approaches, even without any retraining, the proposed strategy achieves an absolute improvement of ~ 4.5% in defense accuracy on ImageNet.

With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash-like scenario or post incident forensics analysis. The cause of crash could be either a fault in the sensor/actuator system, a physical damage/attack, or a cyber attack on the drone's software. In this paper, we propose novel architectures based on deep Convolutional and Long Short-Term Memory Neural Networks (CNNs and LSTMs) to detect (via Autoencoder) and classify drone mis-operations based on sensor data. The proposed architectures are able to learn high-level features automatically from the raw sensor data and learn the spatial and temporal dynamics in the sensor data. We validate the proposed deep-learning architectures via simulations and experiments on a real drone. Empirical results show that our solution is able to detect with over 90% accuracy and classify various types of drone mis-operations (with about 99% accuracy (simulation data) and upto 88% accuracy (experimental data)).

Image analysis in the field of digital pathology has recently gained increased popularity. The use of high-quality whole slide scanners enables the fast acquisition of large amounts of image data, showing extensive context and microscopic detail at the same time. Simultaneously, novel machine learning algorithms have boosted the performance of image analysis approaches. In this paper, we focus on a particularly powerful class of architectures, called Generative Adversarial Networks (GANs), applied to histological image data. Besides improving performance, GANs also enable application scenarios in this field, which were previously intractable. However, GANs could exhibit a potential for introducing bias. Hereby, we summarize the recent state-of-the-art developments in a generalizing notation, present the main applications of GANs and give an outlook of some chosen promising approaches and their possible future applications. In addition, we identify currently unavailable methods with potential for future applications.

In this paper, we work on intra-variable handwriting, where the writing samples of an individual can vary significantly. Such within-writer variation throws a challenge for automatic writer inspection, where the state-of-the-art methods do not perform well. To deal with intra-variability, we analyze the idiosyncrasy in individual handwriting. We identify/verify the writer from highly idiosyncratic text-patches. Such patches are detected using a deep recurrent reinforcement learning-based architecture. An idiosyncratic score is assigned to every patch, which is predicted by employing deep regression analysis. For writer identification, we propose a deep neural architecture, which makes the final decision by the idiosyncratic score-induced weighted average of patch-based decisions. For writer verification, we propose two algorithms for patch-fed deep feature aggregation, which assist in authentication using a triplet network. The experiments were performed on two databases, where we obtained encouraging results.

In learning-to-rank for information retrieval, a ranking model is automatically learned from the data and then utilized to rank the sets of retrieved documents. Therefore, an ideal ranking model would be a mapping from a document set to a permutation on the set, and should satisfy two critical requirements: (1)~it should have the ability to model cross-document interactions so as to capture local context information in a query; (2)~it should be permutation-invariant, which means that any permutation of the inputted documents would not change the output ranking. Previous studies on learning-to-rank either design uni-variate scoring functions that score each document separately, and thus failed to model the cross-document interactions; or construct multivariate scoring functions that score documents sequentially, which inevitably sacrifice the permutation invariance requirement. In this paper, we propose a neural learning-to-rank model called SetRank which directly learns a permutation-invariant ranking model defined on document sets of any size. SetRank employs a stack of (induced) multi-head self attention blocks as its key component for learning the embeddings for all of the retrieved documents jointly. The self-attention mechanism not only helps SetRank to capture the local context information from cross-document interactions, but also to learn permutation-equivariant representations for the inputted documents, which therefore achieving a permutation-invariant ranking model. Experimental results on three large scale benchmarks showed that the SetRank significantly outperformed the baselines include the traditional learning-to-rank models and state-of-the-art Neural IR models.

A classical problem in appointment scheduling, with applications in health care, concerns the determination of the patients' arrival times that minimize a cost function that is a weighted sum of mean waiting times and mean idle times. One aspect of this problem is the sequencing problem, which focuses on ordering the patients. We assess the performance of the smallest-variance-first (SVF) rule, which sequences patients in order of increasing variance of their service durations. While it was known that SVF is not always optimal, it has been widely observed that it performs well in practice and simulation. We provide a theoretical justification for this observation by proving, in various settings, quantitative worst-case bounds on the ratio between the cost incurred by the SVF rule and the minimum attainable cost. We also show that, in great generality, SVF is asymptotically optimal, i.e., the ratio approaches 1 as the number of patients grows large. While evaluating policies by considering an approximation ratio is a standard approach in many algorithmic settings, our results appear to be the first of this type in the appointment scheduling literature.

In the era of Internet of Things (IoT), Malware has been proliferating exponentially over the past decade. Traditional anti-virus software are ineffective against modern complex Malware. In order to address this challenge, researchers have proposed Hardware-assisted Malware Detection (HMD) using Hardware Performance Counters (HPCs). The HPCs are used to train a set of Machine learning (ML) classifiers, which in turn, are used to distinguish benign programs from Malware. Recently, adversarial attacks have been designed by introducing perturbations in the HPC traces using an adversarial sample predictor to misclassify a program for specific HPCs. These attacks are designed with the basic assumption that the attacker is aware of the HPCs being used to detect Malware. Since modern processors consist of hundreds of HPCs, restricting to only a few of them for Malware detection aids the attacker. In this paper, we propose a Moving target defense (MTD) for this adversarial attack by designing multiple ML classifiers trained on different sets of HPCs. The MTD randomly selects a classifier; thus, confusing the attacker about the HPCs or the number of classifiers applied. We have developed an analytical model which proves that the probability of an attacker to guess the perfect HPC-classifier combination for MTD is extremely low (in the range of $10^{-1864}$ for a system with 20 HPCs). Our experimental results prove that the proposed defense is able to improve the classification accuracy of HPC traces that have been modified through an adversarial sample generator by up to 31.5%, for a near perfect (99.4%) restoration of the original accuracy.

Multimodal Sentiment Analysis is an active area of research that leverages multimodal signals for affective understanding of user-generated videos. The predominant approach, addressing this task, has been to develop sophisticated fusion techniques. However, the heterogeneous nature of the signals creates distributional modality gaps that pose significant challenges. In this paper, we aim to learn effective modality representations to aid the process of fusion. We propose a novel framework, MISA, which projects each modality to two distinct subspaces. The first subspace is modality invariant, where the representations across modalities learn their commonalities and reduce the modality gap. The second subspace is modality-specific, which is private to each modality and captures their characteristic features. These representations provide a holistic view of the multimodal data, which is used for fusion that leads to task predictions. Our experiments on popular sentiment analysis benchmarks, MOSI and MOSEI, demonstrate significant gains over state-of-the-art models. We also consider the task of Multimodal Humor Detection and experiment on the recently proposed UR_FUNNY dataset. Here too, our model fares better than strong baselines, establishing MISA as a useful multimodal framework.

We show that the traveling salesman problem (TSP) and its many variants may be modeled as functional optimization problems over a graph. In this formulation, all vertices and arcs of the graph are functionals; i.e., a mapping from a space of measurable functions to the field of real numbers. Many variants of the TSP, such as those with neighborhoods, with forbidden neighborhoods, with time-windows and with profits, can all be framed under this construct. In sharp contrast to their discrete-optimization counterparts, the modeling constructs presented in this paper represent a fundamentally new domain of analysis and computation for TSPs and their variants. Beyond its apparent mathematical unification of a class of problems in graph theory, the main advantage of the new approach is that it facilitates the modeling of certain application-specific problems in their home space of measurable functions. Consequently, certain elements of economic system theory such as dynamical models and continuous-time cost/profit functionals can be directly incorporated in the new optimization problem formulation. Furthermore, subtour elimination constraints, prevalent in discrete optimization formulations, are naturally enforced through continuity requirements. The price for the new modeling framework is nonsmooth functionals. Although a number of theoretical issues remain open in the proposed mathematical framework, we demonstrate the computational viability of the new modeling constructs over a sample set of problems to illustrate the rapid production of end-to-end TSP solutions to extensively-constrained practical problems.

Linkage Tree Genetic Algorithm (LTGA) is an effective Evolutionary Algorithm (EA) to solve complex problems using the linkage information between problem variables. LTGA performs well in various kinds of single-task optimization and yields promising results in comparison with the canonical genetic algorithm. However, LTGA is an unsuitable method for dealing with multi-task optimization problems. On the other hand, Multifactorial Optimization (MFO) can simultaneously solve independent optimization problems, which are encoded in a unified representation to take advantage of the process of knowledge transfer. In this paper, we introduce Multifactorial Linkage Tree Genetic Algorithm (MF-LTGA) by combining the main features of both LTGA and MFO. MF-LTGA is able to tackle multiple optimization tasks at the same time, each task learns the dependency between problem variables from the shared representation. This knowledge serves to determine the high-quality partial solutions for supporting other tasks in exploring the search space. Moreover, MF-LTGA speeds up convergence because of knowledge transfer of relevant problems. We demonstrate the effectiveness of the proposed algorithm on two benchmark problems: Clustered Shortest-Path Tree Problem and Deceptive Trap Function. In comparison to LTGA and existing methods, MF-LTGA outperforms in quality of the solution or in computation time.

Recently, the Edge Computing paradigm has gained significant popularity both in industry and academia. Researchers now increasingly target to improve performance and reduce energy consumption of such devices. Some recent efforts focus on using emerging RRAM technologies for improving energy efficiency, thanks to their no leakage property and high integration density. As the complexity and dynamism of applications supported by such devices escalate, it has become difficult to maintain ideal performance by static RRAM controllers. Machine Learning provides a promising solution for this, and hence, this work focuses on extending such controllers to allow dynamic parameter updates. In this work we propose an Adaptive RRAM Variability-Aware Controller, AVAC, which periodically updates Wait Buffer and batch sizes using on-the-fly learning models and gradient ascent. AVAC allows Edge devices to adapt to different applications and their stages, to improve computation performance and reduce energy consumption. Simulations demonstrate that the proposed model can provide up to 29% increase in performance and 19% decrease in energy, compared to static controllers, using traces of real-life healthcare applications on a Raspberry-Pi based Edge deployment.

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

For a long time after her injury, soccer great Briana Scurry "hid her hell." Now, she knows that that was not the right thing to do and she wants to teach others to become more open and understanding about concussion.

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.

"The penalty kicks, the final goals in the Olympics, playing in front of the president, in front of 90,000 people ... that is what I was born to do ... and my brain is what I used to get myself there."