Miracle-dz/UniFAR-FTUs huggingface dataset:
Object-Based Multiple Foreground Video Co-Segmentation via Multi-State Selection Graph

We present a technique for multiple foreground video co-segmentation in a set of videos. This technique is based on category-independent object proposals. To identify the foreground objects in each frame, we examine the properties of the various regions that reflect the characteristics of foregrounds, considering the intra-video coherence of the foreground as well as the foreground consistency among the different videos in the set. Multiple foregrounds are handled via a multi-state selection graph in which a node representing a video frame can take multiple labels that correspond to different objects. In addition, our method incorporates an indicator matrix that for the first time allows accurate handling of cases with common foreground objects missing in some videos, thus preventing irrelevant regions from being misclassified as foreground objects. An iterative procedure is proposed to optimize our new objective function. As demonstrated through comprehensive experiments, this object-based multiple foreground video co-segmentation method compares well with related techniques that co-segment multiple foregrounds.
Automatic Key Frames Detection in Intravascular Ultrasound Sequences

We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events.
How to complete paraunitary filter banks and simultaneously preserve linear phase?

In this paper, the completion of linear-phase paraunitary filter banks (LPPUFBs) is presented. Given an M-band LPPUFB-admissible scaling filter H/sub 0/(z), the proposed method finds a complete parameterization such that the resulting M - 1 bandpass/highpass filters Hi(z) and the given filter Ho(z) form an LPPUFB. Results from completion of a general PUFB are used in combination with the LP-generating dyadic-based structure, so that the scaling filter H/sub 0/(z) of the resulting LPPUFB is as prescribed, and linear phase of the filter bank is guaranteed. The design procedure is demonstrated by an example.
GRADED POSETS ZETA MATRIX FORMULA

Summary The way to arrive at formula of zeta matrix for any graded posets with the finite set of minimal elements is delivered following [1]. This is being achieved via adjacency and zeta matrix description of bipartite digraphs chains – the representatives of graded posets. The bipartite digraphs elements of such chains amalgamate to form corresponding cover relation graded poset digraphs with corresponding adjacency matrices being amalgamated throughout natural join as special adequate database operation. The colligation of reachability and connectivity with the presented description is made explicit. The special posets encoded via KoDAGs directed acyclic graphs as cobeb posets Hasse diagrams are recognized as an example of differential posets subfamily. As on the 01.01. 2009 one reminisce 261-th anniversary of death of Johann Bernoulli the First this Sylvester Night article is to commemorate this date.
When the Buffer Breaks

Anxiety buffer disruption theory posits that a systemic breakdown of the psychological system that manages anxiety plays an important role in the etiology of posttraumatic stress disorder (PTSD). Traumatic life events undermine the capacity of one’s cultural worldview, self-esteem, and close relationships to manage anxiety, rendering people unable to cope with the distress produced by these events and thus leading to the hyperarousal, intrusive thoughts and emotions, negative alterations in cognitions or mood, and avoidance of trauma-related stimuli that are the defining features of PTSD. Evidence linking disrupted anxiety-buffer functioning to this disorder and implications for therapy are discussed.
How subtle differences in orthography influence conceptual interpretation

The present study investigates linguistic relativity. The units of writing investigated are e and en, which are used to represent units of language in Dutch, Frisian, and Afrikaans. Dutch has homographic forms in the plural suffix -en and the linking element of noun-noun compounds en. Frisian does not have homography of this kind, while Afrikaans has a different homography. This raises the question whether second language learners of Dutch consistently interpret the linking en in Dutch noun-noun compounds as plural in the way that native speakers do. Plurality ratings for Dutch modifiers obtained from native Dutch speakers are compared with ratings from Frisian-Dutch bilinguals and Afrikaaners learning Dutch as L2. Significant differences relating to orthography are observed. We therefore argue that differing orthographic conventions in one’s native language (L1) can lead to different interpretations for the same everyday words written in Dutch (L2). Orthography thus provides an example of linguistic relativity. Keywords:﻿﻿ linguistic relativity; second language learning; morphology; compounding; linking element; plurality; homography; Dutch; Frisian; Afrikaans
Non critical holographic models of the thermal phases of QCD

We analyze the thermal phases of a non critical holographic model of QCD. The model is based on a six dimensional background of Nc non extremal D4 branes wrapping a spacial circle of radius R and the compactified Euclidean time direction of radius β = 1/T. We place in this background stacks of Nf D4 and anti-D4 flavor probe branes with a separation distance L at large radial direction. The analysis of the DBI effective action yields the following phase diagram: At low temperature the system is in a confining phase with broken chiral symmetry. In the high temperature deconfining phase chiral symmetry can be either restored for L>Lc = 1.06R or broken for L<Lc. All of these phase transitions are of first order. We analyze the spectrum of the low-spin and high-spin mesons. High spin mesons above certain critical angular momentum ``melt''. We detect (no) drag for ( mesons) quarks moving in hot quark-gluon fluid. The results resemble the structure and properties of the thermal Sakai-Sugimoto model derived in hep-th/0604161.
Assessment of nano-scale Muller C-elements under variability based on a new fault model

Muller C-elements are considered as a main component of in asynchronous circuits. The traditional implementations of C-elements require an accurate transistor sizing as it is based on some specific current driving assumptions. Due to process variability at nano-scale technology node, such constraints cannot be guaranteed which may lead to malfunction of C-elements. In this paper, we carry out a thorough vulnerability analysis of Muller C-element under process variations at nano-scale technology nodes introducing a new fault model. We model the process variation impacts as a new fault model called driving fault. Considering this fault model, we perform MC simulations to find the driving fault tolerance of different C-element implantations. Experimental results show that two C-element implementations are completely tolerant against driving faults. It is notable to mention that tradeoffs between the overheads and driving fault tolerance of C-element implementations demonstrate that it is worthy to use driving fault tolerant C-element implementations in nano-scale technology nodes with extreme process variations.
Hydrometeor Detection Using Cloudsat—An Earth-Orbiting 94-GHz Cloud Radar

In late April 2006, NASA launched Cloudsat, an earth-observing satellite that uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. The first step in using Cloudsat measurements is to distinguish clouds and other hydrometeors from radar noise. In this article the operational Cloudsat hydrometeor detection algorithm is described, difficulties due to surface clutter are discussed, and several examples from the early mission are shown. A preliminary comparison of the Cloudsat hydrometeor detection algorithm with lidar-based results from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is also provided.
Findings Security Errors in Java Applications Using Lightweight Static Analysis

Application security is becoming increasingly important in Java. In this paper, we focus on security issues that frequently occur in enterprise Java components. We describe two commonly violated security patterns and show how such violations can be prevented with static analysis of the application source. We describe our techniques and experimentally evaluate them on a set of 10 large open-source Java applications totalling over 130,000 lines of code. Our current approach allows us to successfully find 22 real security errors. Finally, we outline limitations of the current approach as well future work that will allow us to increase our analysis coverage and detect more errors.
Neural consequences of bilingualism for cortical and subcortical function

Experience is a prime catalyst for change in the human brain and this capacity for change enables us to optimally engage with our environment. Just as continued practice swinging a tennis racket can lead to increased muscle strength in the racket-swinging hand (Lucki & Nicolay, 2007), the nervous system dynamically adapts tomeet task demands. Underlying this experience-dependent plasticity are structural and functional changes in brain regions engaged by these experiences. For example, learning to play golf results in plasticity of the sensorimotor cortex (Bezzola et al., 2011), learning to juggle induces plasticity in neural centers devoted to complex visual processing (Draganski et al., 2004), and practicing a musical instrument drives plasticity in auditory areas (Kraus & Chandrasekaran, 2010; Schlaug, 2001; Schlaug, Norton, Overy, & Winner, 2005). While active engagement in skill-based training reshapes training-related neural circuits, native language acquisition, a fundamental aspect of normal human development, plays a key role in shaping neural circuitry throughout the brain (reviewed in Huttenlocher, 2009). This pervasive wiring of cognitive and sensory circuits for language facilitates expertise in a given language and in doing so language exerts a stronghold on sensory abilities such that
Exploiting SWCNT structural variability towards the development of a photovoltaic device

In this paper we propose a conceptual Photovoltaic device that comprises a large number of vertically aligned Single-Walled Carbon Nanotubes (SWCNT) having distinct geometrical structure properties. Through employing analytical models of the CNT, we demonstrate how this structural variation can be exploited in absorbing a broadband of the solar spectra. The results show that given a group of CNTs with a low mean diameter dμ = 1 nm and high diameter spread (dσ), optimal band-gap variability can be achieved to maximize the potential of absorption within the proposed CNT-based Photovoltaic device.
Indirect Estimation of Long Memory Volatility Models

An indirect estimator is proposed for two long memory volatility models; the fractionally integrated generalised autoregressive conditional heteroskedasticity (FIGARCH) model and the long memory stochastic volatility (LMSV) model. The small sample properties of the indirect estimator are compared to the small sample properties of conventional maximum likelihood estimators. It is found that the indirect estimator has the potential to perform favourably with respect to maximum likelihood for higher order parameterised FIGARCH and LMSV models
Automatic and interactive parallelization

The goal of this dissertation is to give programmers the ability to achieve high performance by focusing on developing parallel algorithms, rather than on architecture-specific details. The advantages of this approach also include program portability and legibility. To achieve high performance, we provide automatic compilation techniques that tailor parallel algorithms to shared-memory multiprocessors with local caches and a common bus. In particular, the compiler maps complete applications onto the specifics of a machine, exploiting both parallelism and memory. To optimize complete applications, we develop novel, general algorithms to transform loops that contain arbitrary conditional control flow. In addition, we provide new interprocedural transformations which enable optimization across procedure boundaries. These techniques provide the basis for a robust automatic parallelizing algorithm that is applicable to complete programs. The algorithm for automatic parallel code generation takes into consideration the interaction of parallelism and data locality, as well as the overhead of parallelism. The algorithm is based on a simple cost model that accurately predicts cache line reuse from multiple accesses to the same memory location and from consecutive accesses. The optimizer uses this model to improve data locality. It also uses the model to discover and introduce effective parallelism that complements the benefits of data locality. The optimizer further improves the effectiveness of parallelism by seeking to increase its granularity. Parallelism is introduced only when granularity is sufficient to overcome its associated costs. The algorithm for parallel code generation is shown to be efficient and several of its component algorithms are proven optimal. The efficacy of the optimizer is illustrated with experimental results. In most cases, it is very effective and either achieves or improves the performance of hand-crafted parallel programs. When performance is not satisfactory, we provide an interactive parallel programming tool which combines compiler analysis and algorithms with human expertise.
Adaptive interaction in Web3D virtual worlds

In recent years a number of techniques have been studied for augmenting the ease of use of 3D worlds: methodologies for adapting both navigation and content allow a user to interact with a customized 3D world; adaptable navigation paradigms offer parallel modalities for different classes of users. In both cases the goal is to reduce the cognitive load needed for interaction.This work focuses on interaction adaptivity, trying to anticipate the user behaviors by monitoring their interaction patterns. Identification of recurring patterns of interaction is used for shortening users interaction when they approach objects belonging to the same class of those ones previously accessed.An agent based approach is used for monitoring the user activity and for proactively adapting interaction: a pair of agents, called numen (bound to the user) and genius loci (associated with the interaction areas called interaction loci) observe and mediate the users' interaction and adapt the 3D world in order to match their needs.The users are always made aware by the system about the changes in the 3D world and they are always in control. They can deactivate adaptiveness for a while, letting the system only to monitor their actions without applying automatically interaction shortcuts. An implementation architecture and a demonstration prototype are presented. A case study related to virtual fairs is examined, discussing a number of adaptive interaction examples.
Accumulation of Deficits as a Proxy Measure of Aging

This paper develops a method for appraising health status in elderly people. A frailty index was defined as the proportion of accumulated deficits (symptoms, signs, functional impairments, and laboratory abnormalities). It serves as an individual state variable, reflecting severity of illness and proximity to death. In a representative database of elderly Canadians we found that deficits accumulated at 3% per year, and show a gamma distribution, typical for systems with redundant components that can be used in case of failure of a given subsystem. Of note, the slope of the index is insensitive to the individual nature of the deficits, and serves as an important prognostic factor for life expectancy. The formula for estimating an individual's life span given the frailty index value is presented. For different patterns of cognitive impairments the average within-group index value increases with the severity of the cognitive impairment, and the relative variability of the index is significantly reduced. Finally, the statistical distribution of the frailty index sharply differs between well groups (gamma distribution) and morbid groups (normal distribution). This pattern reflects an increase in uncompensated deficits in impaired organisms, which would lead to illness of various etiologies, and ultimately to increased mortality. The accumulation of deficits is as an example of a macroscopic variable, i.e., one that reflects general properties of aging at the level of the whole organism rather than any given functional deficiency. In consequence, we propose that it may be used as a proxy measure of aging.
Trends in Direct Normal Solar Irradiance in Oregon from 1979-2003

To better understand the characteristics of the region’s solar resource, a preliminary study was undertaken of trends in direct normal irradiance from three sites around Oregon over a period of 25 years. An overall increase of about 1316% over the 25 years was found. Seasonal as well as yearly trends were studied. During the summer months an increase was observed while during the winter months a decrease was observed. Changes in clear noon values are also examined. This article analyzes direct normal data unlike other recent studies which find decreasing trends in global radiation data worldwide. The data analysis in this study is the first step in testing and refining regional climate models in the Pacific Northwest. A better understanding of the regional climate models can be achieved by utilizing longterm solar radiation data trends with changes in cloud cover, aerosol optical depth, and other meteorological changes.
A Flexible Recommendation System for Cable TV

Recommendation systems are being explored by Cable TV operators to improve user satisfaction with services, such as Live TV and Video on Demand (VOD) services. More recently, Catch-up TV has been introduced, allowing users to watch recent broadcast content whenever they want to. These services give users a large set of options from which they can choose from, creating an information overflow problem. Thus, recommendation systems arise as essential tools to solve this problem by helping users in their selection, which increases not only user satisfaction but also user engagement and content consumption. In this paper we present a learning to rank approach that uses contextual information and implicit feedback to improve recommendation systems for a Cable TV operator that provides Live and Catch-up TV services. We compare our approach with existing state-of-the-art algorithms and show that our approach is superior in accuracy, while maintaining high scores of diversity and serendipity.
Research on an energy-efficient and variation-sensitive clustering algorithm for wireless sensor network

Due to the characteristics of energy-limited, how to reduce the energy consumption of the wireless sensors network has become the crucial point. Research shows that it can reduce energy consumption to organize the nodes in the network into a hierarchical cluster structure. This paper synthetically analyzes several existing cluster algorithms, and then proposes an energy-efficient and variation-sensitive clustering algorithm. This algorithm makes some modification on the basis of some existing classical clustering algorithms. In order to reduce energy consumption, we adopt some special measures to form cluster, elect cluster head and change the way in which the sense data is constantly sent to cluster head by non-cluster head node.
On Estimating the Size and Confidence of a Statistical Audit

We consider the problem of statistical sampling for auditing elections, and we develop a remarkably simple and easily-calculated upper bound for the sample size necessary for determining with probability at least c if a given set of n objects contains fewer than b "bad" objects. While the size of the optimal sample drawn without replacement can be determined with a computer program, our goal is to derive a highly accurate and simple formula that can be used by election officials equipped with only a hand-held calculator. We actually develop several formulae, but the one we recommend for use in practice is: U3(n, b, c) = ⌈(n - (b - 1)/2) ċ (1 - (1 - c)1/b)⌉ = ⌈(n - (b - 1)/2) ċ (1 - exp(ln(1 - c)/b))⌉ As a practical matter, this formula is essentially exact: we prove that it is never too small, and empirical testing for many representative values of n ≤ 10,000, and b ≤ n/2, and c ≤ 0.99 never finds it more than one too large. Theoretically, we show that for all n and b this formula never exceeds the optimal sample size by more than 3 for c ≤ 0.9975, and by more than (-ln(1 - c))/2 for general c.
Bmc Infectious Diseases Seroepidemiology of Infection with Toxoplasma Gondii in Healthy Blood Donors of Durango, Mexico

Background: Toxoplasma gondii (T. gondii) infection in blood donors could represent a risk for transmission in blood recipients. There is scarce information about the epidemiology of T. gondii infection in blood donors in Mexico. Therefore, we sought to determine the prevalence of T. gondii infection and associated socio-demographic and behavioral characteristics in a population of healthy blood donors of Durango City, Mexico.
Moving Software from Expense to Asset

Reuse is recognized in Motorola, as a major cycle time and cost reduction enabler. The software vision is to assemble products from pre-fabricated parts, with a bill of material for software. This paper shares details on an asset based development strategy and approach. The key aspects of this asset based development strategy are: i) a top down, management-sponsored approach ii) driven through key changes to the software development process and iii) supported by an infrastructure/repository tool. New processes are being developed and integrated into the software development environment, to support asset based development. As part of this effort, a set of evaluation criteria has been developed for evaluating the submitted assets and to minimize potential barriers to reuse; these criteria are also discussed in this paper
A Multimodal Biometric Recognition of Touched Fingerprint and Finger-Vein

multimodal biometric systems have been widely used to overcome the limitation of unimodal biometric systems and to achieve high recognition accuracy. However, users feel inconvenience because most of the multimodal systems require several steps in order to acquire multimodal biometric data, which also requires the specific behaviors of users. In this research, we propose a new multimodal biometric recognition of touched fingerprint and finger-vein. This paper is novel in the following four ways. First, we can get a fingerprint and a finger-vein image at the same time by the proposed device, which acquires the fingerprint and finger-vein images from the first and second knuckles of finger, respectively. Second, the device's size is so small that we can adopt it on a mobile device, easily. Third, fingerprint recognition is done based on the minutia points of ridge area and finger-vein recognition is performed based on local binary pattern (LBP) with appearance information of finger area. Fourth, based on decision level fusion, we combined two results of fingerprint and finger-vein recognition. Experimental results confirmed the efficiency and usefulness of the proposed method.