Universidad Católica Santo Domingo

Recent progress on saliency detection is substantial, benefiting mostly from the explosive development of Convolutional Neural Networks (CNNs). Semantic segmentation and saliency detection algorithms developed lately have been mostly based on Fully Convolutional Neural Networks (FCNs). There is still a large room for improvement over the generic FCN models that do not explicitly deal with the scale-space problem. Holisitcally-Nested Edge Detector (HED) provides a skip-layer structure with deep supervision for edge and boundary detection, but the performance gain of HED on saliency detection is not obvious. In this paper, we propose a new saliency method by introducing short connections to the skip-layer structures within the HED architecture. Our framework provides rich multi-scale feature maps at each layer, a property that is critically needed to perform segment detection. Our method produces state-of-the-art results on 5 widely tested salient object detection benchmarks, with advantages in terms of efficiency (0.08 seconds per image), effectiveness, and simplicity over the existing algorithms.

OBJECTIVE: There is growing public health interest in understanding and promoting successful aging. While there has been some exciting empirical work on objective measures of physical health, relatively little published research combines physical, cognitive, and psychological assessments in large, randomly selected, community-based samples to assess self-rated successful aging. METHOD: In the Successful AGing Evaluation (SAGE) study, the authors used a structured multicohort design to assess successful aging in 1,006 community-dwelling adults in San Diego County, ages 50-99 years, with oversampling of people over 80. A modified version of random-digit dialing was used to recruit subjects. Evaluations included a 25-minute telephone interview followed by a comprehensive mail-in survey of physical, cognitive, and psychological domains, including positive psychological traits and self-rated successful aging, scaled from 1 (lowest) to 10 (highest). RESULTS: The mean age of the respondents was 77.3 years. Their mean self-rating of successful aging was 8.2, and older age was associated with a higher rating, despite worsening physical and cognitive functioning. The best multiple regression model achieved, using all the potential correlates, accounted for 30% of the variance in the score for self-rated successful aging and included resilience, depression, physical functioning, and age (entering the regression model in that order). CONCLUSIONS: Resilience and depression had significant associations with self-rated successful aging, with effects comparable in size to that for physical health. While no causality can be inferred from cross-sectional data, increasing resilience and reducing depression might have effects on successful aging as strong as that of reducing physical disability, suggesting an important role for psychiatry in promoting successful aging.

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In situations where a sequence of forecasts is observed, a common strategy is to examine&#13;\n“rationality” conditional on a given loss function. We examine this from a different perspective—&#13;\nsupposing that we have a family of loss functions indexed by unknown shape parameters, then given&#13;\nthe forecasts can we back out the loss function parameters consistent with the forecasts being rational&#13;\neven when we do not observe the underlying forecasting model? We establish identification of the&#13;\nparameters of a general class of loss functions that nest popular loss functions as special cases and&#13;\nprovide estimation methods and asymptotic distributional results for these parameters. This allows us&#13;\nto construct new tests of forecast rationality that allow for asymmetric loss. The methods are applied&#13;\nin an empirical analysis of IMF and OECD forecasts of budget deficits for the G7 countries. We find&#13;\nthat allowing for asymmetric loss can significantly change the outcome of empirical tests of forecast&#13;\nrationality.

On Friday, 19 March 2004, at approximately 8:45 p.m. Pacific Standard Time (PST), an Internet worm began to spread, targeting a buffer overflow vulnerability in several Internet Security Systems (ISS) products, including its RealSecure Network, RealSecure Server Sensor, RealSecure Desktop, and BlackICE. The worm took advantage of a security flaw in these firewall applications that eEye Digital Security discovered earlier in March. Once the Witty worm - so called because its payload contained the phrase, "(^,^)insert witty message here (^,^)" - infects a computer, it deletes a randomly chosen section of the hard drive, which, over time, renders the machine unusable. We share a global view of the worm's spread, with particular attention to its features.

To meet the computational demands required of deep learning, cloud operators are turning toward specialized hardware for improved efficiency and performance. Project Brainwave, Microsofts principal infrastructure for AI serving in real time, accelerates deep neural network (DNN) inferencing in major services such as Bings intelligent search features and Azure. Exploiting distributed model parallelism and pinning over low-latency hardware microservices, Project Brainwave serves state-of-the-art, pre-trained DNN models with high efficiencies at low batch sizes. A high-performance, precision-adaptable FPGA soft processor is at the heart of the system, achieving up to 39.5 teraflops (Tflops) of effective performance at Batch 1 on a state-of-the-art Intel Stratix 10 FPGA.

DDSCAT 7.2 is a freely available open-source Fortran-90 software package applying the discrete dipole approximation (DDA) to calculate scattering and absorption of electromagnetic waves by targets with arbitrary geometries and complex refractive index. The targets may be isolated entities (e.g., dust particles), but may also be 1-d or 2-d periodic arrays of "target unit cells", which can be used to study absorption, scattering, and electric fields around arrays of nanostructures. The DDA approximates the target by an array of polarizable points. The theory of the DDA and its implementation in DDSCAT is presented in Draine (1988) and Draine &amp; Flatau (1994), and its extension to periodic structures in Draine &amp; Flatau (2008). Efficient near-field calculations are enabled following Flatau &amp; Draine (2012). DDSCAT 7.2 allows accurate calculations of electromagnetic scattering from targets with size parameters 2*pi*aeff/lambda &lt; 25 provided the refractive index m is not large compared to unity (|m-1| &lt; 2). DDSCAT 7.2 includes support for MPI, OpenMP, and the Intel Math Kernel Library (MKL). DDSCAT 7.2 supports calculations for a variety of target geometries (e.g., ellipsoids, regular tetrahedra, rectangular solids, finite cylinders, hexagonal prisms, etc.). Target materials may be both inhomogeneous and anisotropic. It is straightforward for the user to import new target geometries into the code. DDSCAT 7.2 calculates total cross sections for absorption and scattering and selected elements of the Mueller scattering intensity matrix for specified orientation of the target relative to the incident wave, and for specified scattering directions. DDSCAT 7.2 calculates E throughout a user-specified rectangular volume containing the target. A Fortran-90 code READNF to read E and P from files created by DDSCAT 7.2 is included in the distribution.

We calculate an extensive set of characteristics for Internet AS topologies extracted from the three data sources most frequently used by the research community: traceroutes, BGP, and WHOIS. We discover that traceroute and BGP topologies are similar to one another but differ substantially from the WHOIS topology. Among the widely considered metrics, we find that the joint degree distribution appears to fundamentally characterize Internet AS topologies as well as narrowly define values for other important metrics. We discuss the interplay between the specifics of the three data collection mechanisms and the resulting topology views. In particular, we show how the data collection peculiarities explain differences in the resulting joint degree distributions of the respective topologies. Finally, we release to the community the input topology datasets, along with the scripts and output of our calculations. This supplement should enable researchers to validate their models against real data and to make more informed selection of topology data sources for their specific needs.

We have measured 3D face geometry, skin reflectance, and subsurface scattering using custom-built devices for 149 subjects of varying age, gender, and race. We developed a novel skin reflectance model whose parameters can be estimated from measurements. The model decomposes the large amount of measured skin data into a spatially-varying analytic BRDF, a diffuse albedo map, and diffuse subsurface scattering. Our model is intuitive, physically plausible, and -- since we do not use the original measured data -- easy to edit as well. High-quality renderings come close to reproducing real photographs. The analysis of the model parameters for our sample population reveals variations according to subject age, gender, skin type, and external factors (e.g., sweat, cold, or makeup). Using our statistics, a user can edit the overall appearance of a face (e.g., changing skin type and age) or change small-scale features using texture synthesis (e.g., adding moles and freckles). We are making the collected statistics publicly available to the research community for applications in face synthesis and analysis.

DDSCAT.5a is a freely available software package which applies the "discrete dipole approximation" (DDA) to calculate scattering and absorption of electromagnetic waves by targets with arbitrary geometries and complex refractive index. The DDA approximates the target by an array of polarizable points. DDSCAT.5a requires that these polarizable points be located on a cubic lattice. DDSCAT.5a10 allows accurate calculations of electromagnetic scattering from targets with "size parameters" 2 pi a/lambda &lt; 15 provided the refractive index m is not large compared to unity (|m-1| &lt; 1). The DDSCAT package is written in Fortran and is highly portable. The program supports calculations for a variety of target geometries (e.g., ellipsoids, regular tetrahedra, rectangular solids, finite cylinders, hexagonal prisms, etc.). Target materials may be both inhomogeneous and anisotropic. It is straightforward for the user to import arbitrary target geometries into the code, and relatively straightforward to add new target generation capability to the package. DDSCAT automatically calculates total cross sections for absorption and scattering and selected elements of the Mueller scattering intensity matrix for specified orientation of the target relative to the incident wave, and for specified scattering directions. This User Guide explains how to use DDSCAT.5a10 to carry out EM scattering calculations. CPU and memory requirements are described.

Even with the significant focus on IP address lookup in the published literature as well as focus on this market by commercial semiconductor vendors, there is still a challenge for router architects to find solutions that simultaneously meet 3 criteria: scaling in terms of lookup speeds as well as table sizes, the ability to perform high speed updates, and the ability to fit into the overall memory architecture of an Level 3 forwarding engine or packet processor with low systems cost overhead. In this paper, we describe a scheme that meets all three criteria. By contrast, published and commercial semiconductor solutions meet some but not all of these three criteria.For example, many approaches that provide dense tables have poor update times; others require large amounts of expensive high speed memory dedicated to this application. Many IP address lookup approaches do not take into account the flexibility of ASICs or the structure of modern high speed memory technologies such as RLDRAM[1] and FCRAM[2]. In this paper, we present a family of IP lookup schemes using a data structure that compactly encodes large prefix tables in order to address the criteria listed above. We also present a series of optimizations to the core algorithm that allows the memory access width of the algorithm to be reduced at the cost of memory references or allocated memory. Such flexibility in performance versus density is an important feature for the lookup engine of routers that may be deployed in different networks with varying requirements on address lookup length and table density (e.g. global IPv4 networks, global v6, VPN based v4 networks, MPLS, and IP tunneling encapsulation points).

Finite element solvers are a basic component of simulation applications; they are common in computer graphics, engineering, and medical simulations. Although adaptive solvers can be of great value in reducing the often high computational cost of simulations they are not employed broadly. Indeed, building adaptive solvers can be a daunting task especially for 3D finite elements. In this paper we are introducing a new approach to produce conforming, hierarchical, adaptive refinement methods (CHARMS). The basic principle of our approach is to refine basis functions, not elements. This removes a number of implementation headaches associated with other approaches and is a general technique independent of domain dimension (here 2D and 3D), element type (e.g., triangle, quad, tetrahedron, hexahedron), and basis function order (piece-wise linear, higher order B-splines, Loop subdivision, etc.). The (un-)refinement algorithms are simple and require little in terms of data structure support. We demonstrate the versatility of our new approach through 2D and 3D examples, including medical applications and thin-shell animations.

We calculate an extensive set of characteristics for Internet AS topologies extracted from the three data sources most frequently used by the research community: traceroutes, BGP, and WHOIS. We discover that traceroute and BGP topologies are similar to one another but differ substantially from the WHOIS topology. Among the widely considered metrics, we find that the joint degree distribution appears to fundamentally characterize Internet AS topologies as well as narrowly define values for other important metrics. We discuss the interplay between the specifics of the three data collection mechanisms and the resulting topology views. In particular, we how how the data collection peculiarities explain differences in the resulting joint degree distributions of the respective topologies. Finally, we release to the community the input topology datasets, along with the scripts and output of our calculations. This supplement hould enable researchers to validate their models against real data and to make more informed election of topology data sources for their specific needs

This tutorial describes challenges and possible avenues for the implementation of the components of a solid-state system, which emulates a biological brain. The tutorial is devoted mostly to a charge-based (i.e. electric controlled) implementation using transition metal oxide materials, which exhibit unique properties that emulate key functionalities needed for this application. In Sec. I, we compare the main differences between a conventional computational machine, based on the Turing-von Neumann paradigm, and a neuromorphic machine, which tries to emulate important functionalities of a biological brain. We also describe the main electrical properties of biological systems, which would be useful to implement in a charge-based system. In Sec. II, we describe the main components of a possible solid-state implementation. In Sec. III, we describe a variety of Resistive Switching phenomena, which may serve as the functional basis for the implementation of key devices for neuromorphic computing. In Sec. IV, we describe why transition metal oxides are promising materials for future neuromorphic machines. Theoretical models describing different resistive switching mechanisms are discussed in Sec. V, while existing implementations are described in Sec. VI. Section VII presents applications to practical problems. We list in Sec. VIII important basic research challenges and open issues. We discuss issues related to specific implementations, novel materials, devices, and phenomena. The development of reliable, fault tolerant, energy efficient devices, their scaling, and integration into a neuromorphic computer may bring us closer to the development of a machine that rivals the brain.

We introduce the design and implementation of FreeRider, the first system that enables backscatter communication with multiple commodity radios, such as 802.11g/n WiFi, ZigBee, and Bluetooth, while these radios are simultaneously used for productive data communication. Furthermore, we are, to our knowledge, the first to implement and evaluate a multi-tag system. The key technique used by FreeRider is codeword translation, where a tag can transform a codeword present in the original excitation signal into another valid codeword from the same codebook during backscattering. In other words, the backscattered signal is still a valid WiFi, ZigBee, or Bluetooth signal. Therefore, commodity radios decode the backscattered signal and extract the tag's embedded information. More importantly, FreeRider does codeword translation regardless of the data transmitted by these radios. Therefore, these radios can still do productive data communication. FreeRider accomplishes codeword translation by modifying one or more of the three dimensions of a wireless signal --- amplitude, phase and frequency. A tag ensures that the modified signal is still comprised of valid codewords that come the same codebook as the original excitation signal. We built a hardware prototype of FreeRider, and our empirical evaluations show a data rate of ~60kbps in single tag mode, 15kbps in multi-tag mode, and a backscatter communication distance up to 42m when operating on 802.11g/n WiFi.

Contrasts between implicit and explicit knowledge in the serial reaction time (SJRT) paradigm have been challenged because they have depended on a single dissociation; intact implicit knowledge in the absence of corresponding explicit knowledge. In the SRT task, subjects respond with a corresponding keypress to a cue that appears in one of four locations. The cue follows a repeating sequence of locations, and subjects can exhibit knowledge of the repeating sequence through increasingly rapid performance (an implicit test) or by being able to recognize the sequence (an explicit test). In our study, amnesic patients were given extensive SRT training. Their implicit and explicit test performance was compared to the performance of control subjects who memorized the training sequence. Compared with control subjects, amnesic patients exhibited superior performance on the implicit task and impaired performance on the explicit task. This crossover interaction suggests that implicit and explicit knowledge of the embedded sequence are separate and encapsulated and that they presumably depend on different brain systems.

Despite increasing efforts on universal representations for visual recognition, few have addressed object detection. In this paper, we develop an effective and efficient universal object detection system that is capable of working on various image domains, from human faces and traffic signs to medical CT images. Unlike multi-domain models, this universal model does not require prior knowledge of the domain of interest. This is achieved by the introduction of a new family of adaptation layers, based on the principles of squeeze and excitation, and a new domain-attention mechanism. In the proposed universal detector, all parameters and computations are shared across domains, and a single network processes all domains all the time. Experiments, on a newly established universal object detection benchmark of 11 diverse datasets, show that the proposed detector outperforms a bank of individual detectors, a multi-domain detector, and a baseline universal detector, with a 1.3x parameter increase over a single-domain baseline detector. The code and benchmark are available at http://www.svcl.ucsd.edu/projects/universal-detection/.

In many enterprises today, middleboxes called WAN optimizers are being deployed across WAN access links in order to eliminate redundancy in network traffic and reduce WAN access costs. In this paper, we present the design and implementation of EndRE, an alternate approach where redundancy elimination is provided as an end system service. Unlike middleboxes, such an approach benefits both end-to-end encrypted traffic as well as traffic on last-hop wireless links to mobile devices. EndRE needs to be fast, adaptive and parsimonious in memory usage in order to opportunistically leverage resources on end hosts. Thus, we design a new fingerprinting scheme called SampleByte that is much faster than Rabin fingerprinting while delivering similar compression gains. Unlike Rabin, SampleByte can also adapt its CPU usage depending on server load. Further, we introduce optimizations to reduce server memory footprint by 33-75 % compared to prior approaches. Using several terabytes of network traffic traces from 11 enterprise sites, testbed experiments and a pilot deployment, we show that EndRE delivers 26 % bandwidth savings on average, processes payloads at speeds of 1.5-4Gbps, reduces end-to-end latencies by up to 30%, and translates bandwidth savings into equivalent energy savings on mobile smartphone. 1

Studies on HIV virology and pathogenesis address the complex mechanisms that result in the HIV infection of the cell and destruction of the immune system. These studies are focused on both the structure and the replication characteristics of HIV and on the interaction of the virus with the host. Continuous updating of knowledge on structure, variability and replication of HIV, as well as the characteristics of the host immune response, are essential to refine virological and immunological mechanisms associated with the viral infection and allow us to identify key molecules in the virus life cycle that can be important for the design of new diagnostic assays and specific antiviral drugs and vaccines. In this article we review the characteristics of molecular structure, replication and pathogenesis of HIV, with a particular focus on those aspects that are important for the design of diagnostic assays.

A great deal of attention in evidence‐based policy and practice is directed to statistical studies–especially randomized controlled trials–that support causal conclusions, which this chapter dubs ‘It‐works‐somewhere claims’. What's needed for policy and practice, however, are conclusions that the policy will work for us, as when and how we would implement it. Despite widespread recognition of the problem of external validity, it is all too easy to suppose that conclusions of the first sort provide strong evidence for those of the second sort. This chapter argues that this is not the case. Further, ‘external validity’ is the wrong way to characterize the problem. Usually the only reliable way to use an it‐works‐somewhere result as evidence for ‘It will work for us’ is via what J.S. Mill calls a ‘tendency’ claim (and the chapter calls a ‘capacity’ claim). This however points out how weak ‘It works somewhere’ is in support of ‘It will work for us’, for two reasons. (1) It takes a great deal of theory, observation and experiment, far beyond the statistical study itself, to establish a tendency/capacity claim; (2) Reliable prediction requires in addition a great deal of local knowledge supplied by neither the statistical study nor the capacity claim.