gebhart/patrepeval huggingface dataset:
Efficient processing of compressed video (2002)

Compressed digital video is becoming prevalent for video storage and communication. It is often desirable to perform various video processing tasks on compressed video streams, however, operations once considered simple, such as splicing and reverse play, are much more complex in the context of compressed video. The conceptually-simple approach of completely decoding the video into the pixel domain, performing the processing, and re-encoding the entire video sequence is often inefficient and impractical. This paper investigates the problem of transcoding compressed video data from one standards-compliant data stream to another. The goal is to develop video transcoding algorithms that achieve high performance with computational efficiency. In particular, this paper presents efficient algorithms for splicing and reverse play of compressed video streams.
Undergate-type Triode Carbon Nanotube Field Emission Display with a Microchannel Plate (2001)

The characteristics of a field emission display (FED), which is based on an undergate-type triode carbon nanotube (CNT), have been examined by incorporating an electron-multiplying microchannel plate (MCP) between the anode and cathode plates of a FED. The MCP was fabricated by electroless plating and the sol–gel process on punched alumina. By applying appropriate voltages between the two faces of an MCP within a FED, the current at the anode plate of a FED was found to be enhanced more than three to five times, leading to higher brightness. The focusing of field emitted electrons was also improved by adjusting the bottom voltage of the MCP, which resulted in a clear image. Therefore, the incorporation of the MCP improved the performance of an undergate-type CNT FED, which can now be considered as one of the key candidates for flat panel displays.
<title>Gated frequency-resolved optical imaging with an optical parametric amplifier for medical applications</title> (1996)

Implementation of optical imagery in a diffuse inhomogeneous medium such as biological tissue requires an understanding of photon migration and multiple scattering processes which act to randomize pathlength and degrade image quality. The nature of transmitted light from soft tissue ranges from the quasi-coherent properties of the minimally scattered component to the random incoherent light of the diffuse component. Recent experimental approaches have emphasized dynamic path-sensitive imaging measurements with either ultrashort laser pulses (ballistic photons) or amplitude modulated laser light launched into tissue (photon density waves) to increase image resolution and transmissive penetration depth. Ballistic imaging seeks to compensate for these 'fog-like' effects by temporally isolating the weak early-arriving image-bearing component from the diffusely scattered background using a subpicosecond optical gate superimposed on the transmitted photon time-of-flight distribution. The authors have developed a broadly wavelength tunable (470 nm - 2.4 micrometer), ultrashort amplifying optical gate for transillumination spectral imaging based on optical parametric amplification in a nonlinear crystal. The time-gated image amplification process exhibits low noise and high sensitivity, with gains greater than 10<SUP>4</SUP> achievable for low light levels. We report preliminary benchmark experiments in which this system was used to reconstruct, spectrally upcovert, and enhance near-infrared two-dimensional images with feature sizes of 65 micrometer/mm<SUP>2</SUP> in background optical attenuations exceeding 10<SUP>12</SUP>. Phase images of test objects exhibiting both absorptive contrast and diffuse scatter were acquired using a self-referencing Shack-Hartmann wavefront sensor in combination with short-pulse quasi-ballistic gating. The sensor employed a lenslet array based on binary optics technology and was sensitive to optical path distortions approaching lambda/100.
LAHVA: Linked Animal-Human Health Visual Analytics (2007)

Coordinated animal-human health monitoring can provide an early warning system with fewer false alarms for naturally occurring disease outbreaks, as well as biological, chemical and environmental incidents. This monitoring requires the integration and analysis of multi-field, multi-scale and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. To facilitate these investigations, we have created an application to provide a visual analytics framework for analyzing both human emergency room data and veterinary hospital data. Our integrated visual analytic tool links temporally varying geospatial visualization of animal and human patient health information with advanced statistical analysis of these multi-source data. Various statistical analysis techniques have been applied in conjunction with a spatio-temporal viewing window. Such an application provides researchers with the ability to visually search the data for clusters in both a statistical model view and a spatio-temporal view. Our interface provides a factor specification/filtering component to allow exploration of causal factors and spread patterns. In this paper, we will discuss the application of our linked animal-human visual analytics (LAHVA) tool to two specific case studies. The first case study is the effect of seasonal influenza and its correlation with different companion animals (e.g., cats, dogs) syndromes. Here we use data from the Indiana Network for Patient Care (INPC) and Banfield Pet Hospitals in an attempt to determine if there are correlations between respiratory syndromes representing the onset of seasonal influenza in humans and general respiratory syndromes in cats and dogs. Our second case study examines the effect of the release of industrial wastewater in a community through companion animal surveillance.
Low-current Spin Transfer Torque MRAM (2017)

To achieve low write current in high density Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM) arrays, it is important to understand and co-optimize the different kinds of device switching currents, governed by different materials parameters. We demonstrate that double magnetic tunnel junctions (DMTJs) lower the switching current threshold I <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c0</inf> by a factor of two when compared to conventional single MTJs. In single MTJs, the overdrive required to reach a write-error rate (WER) of 1E-6 was reduced by materials optimization from 53% to 29% a write-error rate (WER) of 1E-6 by materials optimization. Ultra-low switching current of 8 µA at WER = 1E-9 was achieved in an 11 nm MTJ with 10 ns write pulses.
Open set face recognition using transduction (2005)

This paper motivates and describes a novel realization of transductive inference that can address the Open Set face recognition task. Open Set operates under the assumption that not all the test probes have mates in the gallery. It either detects the presence of some biometric signature within the gallery and finds its identity or rejects it, i.e., it provides for the "none of the above" answer. The main contribution of the paper is Open Set TCM-kNN (Transduction Confidence Machine-k Nearest Neighbors), which is suitable for multiclass authentication operational scenarios that have to include a rejection option for classes never enrolled in the gallery. Open Set TCM-kNN, driven by the relation between transduction and Kolmogorov complexity, provides a local estimation of the likelihood ratio needed for detection tasks. We provide extensive experimental data to show the feasibility, robustness, and comparative advantages of Open Set TCM-kNN on Open Set identification and watch list (surveillance) tasks using challenging FERET data. Last, we analyze the error structure driven by the fact that most of the errors in identification are due to a relatively small number of face patterns. Open Set TCM-kNN is shown to be suitable for PSEI (pattern specific error inhomogeneities) error analysis in order to identify difficult to recognize faces. PSEI analysis improves biometric performance by removing a small number of those difficult to recognize faces responsible for much of the original error in performance and/or by using data fusion.
A Switchable Self-Doped Polyaniline:  Interconversion between Self-Doped and Non-Self-Doped Forms (2003)

A novel strategy for the synthesis of a substituted polyaniline that can be switched between a self-doped and non-self-doped state is presented. The approach uses the complexation between boronic acid-substituted aniline, a diol (d-fructose), and fluoride to generate an anionic monomer. Under these conditions, chemical polymerization results in a self-doped, water-soluble, conducting polyaniline under neutral aqueous conditions. The self-doped polymer can be simply and reversibly converted to an insoluble non-self-doped form by reducing the concentration of fluoride. Characteristics of the polymerization reaction and the resulting polymer are discussed.
Electrodeposition of Redox Polymers and Co-Electrodeposition of Enzymes by Coordinative Crosslinking This research was supported by the Welch Foundation and by the US Army Research Laboratory. (2002)

When four conditions are met redox polymers can be electrodeposited by ligand exchange: the film must be electron- or hole-conducting; the redox centers of the deposited polymer that are based on transition metal complexes must contain a labile ligand in their inner coordination sphere; the redox polymer must contain a strongly coordinating but yet uncoordinated ligand; and the surface density of the adsorbed redox polymer must be high. By taking care of these points, the authors also succeeded in co-depositing enzymes and electroreducing/oxidizing their substrates with the electrodes obtained.
Explaining Data-Driven Document Classifications (2013)

Many document classification applications require human understanding of the reasons for data-driven classification decisions by managers, client-facing employees, and the technical team. Predictive models treat documents as data to be classified, and document data are characterized by very high dimensionality, often with tens of thousands to millions of variables (words). Unfortunately, due to the high dimensionality, understanding the decisions made by document classifiers is very difficult. This paper begins by extending the most relevant prior theoretical model of explanations for intelligent systems to account for some missing elements. The main theoretical contribution is the definition of a new sort of explanation as a minimal set of words (terms, generally), such that removing all words within this set from the document changes the predicted class from the class of interest. We present an algorithm to find such explanations, as well as a framework to assess such an algorithmâs performance. We demonstrate the value of the new approach with a case study from a real-world document classification task: classifying web pages as containing objectionable content, with the goal of allowing advertisers to choose not to have their ads appear on those pages. A second empirical demonstration on news-story topic classification shows the explanations to be concise and document-specific, and to be capable of providing understanding of the exact reasons for the classification decisions, of the workings of the classification models, and of the business application itself. We also illustrate how explaining the classifications of documents can help to improve data quality and model performance.
Network Traffic Prediction Using Recurrent Neural Networks (2018)

The network traffic prediction problem involves predicting characteristics of future network traffic from observations of past traffic. Network traffic prediction has a variety of applications including network monitoring, resource management, and threat detection. In this paper, we propose several Recurrent Neural Network (RNN) architectures (the standard RNN, Long Short Term Memory (LSTM) networks, and Gated Recurrent Units (GRU)) to solve the network traffic prediction problem. We analyze the performance of these models on three important problems in network traffic prediction: volume prediction, packet protocol prediction, and packet distribution prediction. We achieve state of the art results on the volume prediction problem on public datasets such as the GEANT and Abilene networks. We also believe this is the first work in the domain of protocol prediction and packet distribution prediction using RNN architectures. In this paper, we show that RNN architectures demonstrate promising results in all three of these domains in network traffic prediction, outperforming standard statistical forecasting models significantly.
On the Concept of the Multi-Source Inverter for Hybrid Electric Vehicle Powertrains (2017)

This paper presents an inverter topology named the multi-source inverter that aims to connect several independent DC sources to the same AC output using a single stage of conversion. This power converter has been developed for applications, such as electrified powertrains. Compared to the conventional hybrid powertrains that use a DC/DC converter to provide an adaptable voltage to the load, the multi-source inverter can drive a traction motor from variable DC voltages without the use of an additional power converter. Hence, the high power DC/DC converter can be dissociated from the traction mode and its use will be restricted to the engine's start-up and regenerative braking, allowing a significant reduction of its power rating from tens of kWatts to a few kWatts. The overall efficiency of the electrified traction drive can also be improved due to the single conversion stage between the battery and the motor. In this paper, the multi-source inverter topology is introduced and its different operating modes are determined through the study of the inverter circuit. Closed-loop control simulations and experiments with a scaled-down prototype and an induction motor were performed to validate the effectiveness of the proposed topology and concept.
Implementation of Spread Spectrum Image Steganography (2001)

Abstract : Steganographic techniques are useful to convey hidden information by using various types of typically-transmitted multimedia data as cover for concealed communication. Spread Spectrum Image Steganography (SSIS) is a data-hiding/hidden-communication method that uses digital imagery as a cover signal. This report describes an SSIS prototype system for embedding messages in images and extracting messages from stegoimages. The components, which were written in the Java and C programming languages, were kept modular to provide a workbench for further experimentation. We discuss experiments that were performed with the system, along with possible avenues of future research to improve the SSIS process.
Synthetic modulators of the complement system. 1. Synthesis and biological activity of 5,5',5"-[1,3,6-naphthalenetriyltris(sulfonylimino)]tris[1,3-benzenedisulfonate] hexasodium salt (1980)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTSynthetic modulators of the complement system. 1. Synthesis and biological activity of 5,5',5"-[1,3,6-naphthalenetriyltris(sulfonylimino)]tris[1,3-benzenedisulfonate] hexasodium saltR. B. Conrow, N. Bauman, J. A. Brockman, and S. BernsteinCite this: J. Med. Chem. 1980, 23, 3, 240–242Publication Date (Print):March 1, 1980Publication History Published online1 May 2002Published inissue 1 March 1980https://pubs.acs.org/doi/10.1021/jm00177a006https://doi.org/10.1021/jm00177a006research-articleACS PublicationsRequest reuse permissionsArticle Views95Altmetric-Citations6LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
10-Gbit/s transoceanic soliton transmission using mostly normal dispersion fiber (2002)

Soliton transmission using periodic dispersion compensation has recently become an attractive method to reduce amplitude and timing errors by means of soliton power enhancement in low path-averaged dispersion transmission lines. We report here the results of error-free soliton transmission exceeding 10 Mm in a dispersion-mapped system consisting of mostly normal dispersion fiber, but in which a low path-averaged anomalous dispersion is obtained. A consequence of low dispersion in soliton transmission systems using frequency-sliding techniques is a stronger impact from the frequency-sliding filters on the pulse dynamics.
Automatic portion estimation and visual refinement in mobile dietary assessment (2009)

As concern for obesity grows, the need for automated and accurate methods to monitor nutrient intake becomes essential as dietary intake provides a valuable basis for managing dietary imbalance. Moreover, as mobile devices with built-in cameras have become ubiquitous, one potential means of monitoring dietary intake is photographing meals using mobile devices and having an automatic estimate of the nutrient contents returned. One of the challenging problems of the image-based dietary assessment is the accurate estimation of food portion size from a photograph taken with a mobile digital camera. In this work, we describe a method to automatically calculate portion size of a variety of foods through volume estimation using an image. These "portion volumes" utilize camera parameter estimation and model reconstruction to determine the volume of food items, from which nutritional content is then extrapolated. In this paper, we describe our initial results of accuracy evaluation using real and simulated meal images and demonstrate the potential of our approach.
Porous silicon photodetector (1993)

The porous silicon photodetector shows high band and high sensitivity properties. The porous silicon layer being the top layer of porous silicon photodetector, and the pore size distribution of porous silicon result in high band detectivity. Various porosities corresponding to various silicon wires would respond to various wavelengths of incident light.The high sensitivity is attributed to the textured surface, the direct band of porous silicon and the porous silicon layer thickness controllability of absorption region of metal-PS-silicon photodetector. The textured surface of porous silicon would reduce the reflection of incident light which would enhance the sensitivity of porous silicon photodetector.
Location of a Neutralizing Epitope for the Haemagglutinin-Neuraminidase Glycoprotein of Newcastle Disease Virus (1988)

The binding site of a monoclonal antibody to the haemagglutinin-neuraminidase (HN) polypeptide of Newcastle disease virus (NDV) has been located. Complementary DNA or synthetic oligonucleotides corresponding to portions of the HN gene were cloned into the Escherichia coli vector pUC19 and fragments of the HN protein were thereby fused to the alpha-peptide of beta-galactosidase. Western blot analysis of E. coli lysates containing expressed fragments of the HN cDNA or synthetic oligonucleotides identified an antibody-binding peptide (Asp-Glu-Gln-Asp-Tyr-Gln-Ile-Arg; amino acid residues 346 to 353). Nucleotide sequence analysis of an antibody-resistant mutant of NDV revealed a Glu (wild-type) to Lys (mutant) substitution within the above sequence. The methods described could be useful for the location of continuous epitopes of other polypeptides.
Electrochromism And Electrochromic Devices (2019)

This chapter reviews the basic materials background and the state of the art for electrochromic devices. Electrochromism is well known in numerous inorganic and organic substances; the chapter is devoted to the former class. The electrochromic oxide films must be permeable to ions and must show some electrical conductivity. Transmitting electrochromic devices can incorporate a thin film that serves as an ion storage. Inorganic ion conductors have been studied in several different prototype electrochromic devices. Reflectance changes have been reported in devices with bulk-type ion conductors, and transmittance as well as reflectance changes have been reported in devices with thin-film ion conductors. Electrochromic materials undergo reversible and persistent changes of their optical properties under the action of voltage pulses. Electrochromic devices can be of several different types, categorized according to the type of electrolyte or ion conductor forming the central part of the construction.
Laser Induced Breakdown Spectroscopy for Rapid Delineation of Metals in Soils (1995)

The development of a metal sensor that can be deployed with a cone penetrometer for in-situ subsurface measurements is described. The sensor utilized Laser Induced Breakdown Spectroscopy (LIBS) to analyze the atomic emission of metals on contaminated soil samples. The novel approach taken in this work is that the measurements are done remotely with both laser excitation and signal collection transmitted through fiber optic cables.
An Ingestible Capsule for the Photodynamic Therapy of <italic>Helicobacter Pylori</italic> Infection (2016)

Helicobacter pylori (H. pylori) is a Gram-negative pathogen bacterium affecting the mucosa of the stomach and causing severe gastric diseases. H. pylori-related infections are currently treated with pharmacological therapies, which are associated with increasing antibiotic resistance and consequent reduction of the efficacy down to 70%-85%. Moreover, drugs have generally side effects that further affect the healthcare system in terms of additional financial and medical efforts. The aim of this study is to present an innovative device for the treatment of H. pylori infection, consisting of an ingestible lighting capsule performing photodynamic therapy by means of light at specific wavelengths. The proposed treatment is minimally invasive and the described system can be considered the first photodynamic swallowable device ever proposed. Preliminary experiments demonstrated that the capsule integrated with LED sources can provide the required lighting power to kill the bacterium with an efficiency up to about 96%.