nils-herrmann/clean_scirepeval huggingface dataset:
A study of image retrieval by anchoring

Anchoring is a technique for representing objects by their distances to a few well chosen anchors, or vantage points. It can be used in content-based image retrieval for computing image similarity as a function of distances to a fixed set of representative images. Since the number of anchors is usually small, this leads to a reduced dimensionality for similarity searching, enables efficient indexing, and avoids potentially expensive similarity computations in the original feature domain, while guaranteeing lack of false dismissals. Anchoring is therefore surprisingly simple, yet effective, and flavors of it have seen application in speech recognition, audio classification, protein homology detection, and shape matching. In this paper, we describe the anchoring technique in some detail and study its properties, both from an empirical and an analytical standpoint. In particular, we investigate issues in baseline distance selection, anchor selection, and number of anchors. We compare different approaches and evaluate performance of different parameter settings. We also propose two new anchor selection heuristics which may overcome some of the drawbacks of the currently used greedy selection methods.
Electron Dynamics of the Rod-Pinch Diode in the Cygnus Experiment at Los Alamos

In this work, two-dimensional particle-in-cell simulations are used to examine the electron physics in the rod-pinch diode, a device that can be used to produce a relatively low-energy (a few MeV) radiographic electron source. It is found that with diode parameters for which the electrons’ dominant dynamics are approximated well as a magnetized fluid, the diode produces an electron source with a desired small spot size as the electrons drift to and impinge on the anode tip. However, for a large cathode-to-anode radius ratio, a population of electrons that consists predominantly of electrons emitted from the downstream surface of the cathode is found to propagate in the upstream direction and the diode may perform anomalously as a consequence. A method is proposed for improving the quality of the electron source by suppressing electron emission from the downstream cathode surface to reduce the presence of unmagnetized electrons.
Accurate coverage summarization of UAV videos

A predominant fraction of UAV videos are never watched or analyzed and there is growing interest in having a summary view of the UAV videos for obtaining a better overall perspective of the visual content. Real time summarization of the UAV video events is also important from tactical perspective. Our research focuses on developing resilient algorithms for summarizing videos that can be efficiently processed either onboard or offline. Our previous work  on the video summarization has focused on the event summarization. More recently, we have investigated the challenges in providing the coverage summarization of the video content from UAV videos. Different from the traditional coverage summarization taking SfM approach (e.g., ) on SIFT-based [14] feature points, there are several additional challenges including jitter, low resolution, contrast, lack of salient features in UAV videos. We propose a novel correspondence algorithm that exploits the 3D context that can potentially alleviate the correspondence ambiguity. Our results on VIRAT dataset shows that our algorithm can find many correct correspondences in low resolution imagery while avoiding many false positives from the traditional algorithms.
Diagnostics for the DIII-D radiative divertor

This paper reviews the design of new diagnostics and the modifications to existing diagnostics needed to carry out radiative divertor experiments in DIII-D following installation in late 1996 of a set of baffle structures that will restrict the backflow to the core plasma of neutral deuterium atoms and impurity gases. The divertor slots formed by the new baffle structures will inhibit the easy view of the divertor legs and target plates that the open divertor geometry in DIII-D currently affords. We review a basic set of diagnostics that are needed to demonstrate the reduction of divertor heat loading and radiative dissipation of energy within the divertor. This will include IR cameras, bolometry, foil bolometers, and Langmiur probes. Within the limits of available funding, we will implement a supplemental set of instruments which provide a more detailed understanding of the underlying physical processes. Many existing diagnostics require only re-aiming to provide proper coverage of the initial 23 cm long divertor plasma configuration (X-point to floor distance). Other diagnostics need extensive reconfiguration using in-vessel fiber-optic bundles or high power laser mirrors. The new divertor baffle panels provide a protective shelf for diagnostic hardware mounted underneath them, but the water cooling channels in the panels limit the permissible size of through holes and, thereby, restrict the available views of under-the-baffle diagnostics. The successful resolution of the design and implementation of these diagnostic modifications is dependent on a strong coordination between GA and its many diagnostic collaborators.
Magnet Power Supply Control, of the NSLS VUV and X-Ray Storage Rings, Transfer Lines

The transfer lines for NSLS VUV and X-ray storage rings have been split. New power supplies have been incorporated with existing ones. The existing microprocessor system has been upgraded in order to control the additional functions. This system expands the input/output port of the microprocessor to an addressable serial/parallel link to each magnet power supply. The implementation of this system will be discussed.
Information Discovery in Ecological Systems by Artificial Neural Networks: Algal Blooms at Gippsland Lakes

This paper aims to discuss two aspects of working with large ecological data sets; analysis and modelling of ecological data sets, and subdivision of data into smaller subsets for the purpose of analysis and modelling. Different approaches to the information discovery in ecological systems based on Artificial Neural Networks (ANNs) are considered ANNs are powerful modelling tools. Their strength is derived from their ability to model complex, non-linear relationships. However, a drawback of ANNs is that they cannot distinguish between noise and actual data in a system. Ecological systems are prone to greater noise than many other systems. The solution therefore lies in applying ANNs to ecological problems more creatively. In algal blooms and similar ecological problems the use of ANNs has been primarily limited to the predictive modelling and sensitivity analysis. This paper proposes a multi-stage analysis comprising of predictive function modelling, sensitivity analysis, principal component analysis (PCA) and non-linear principal component analysis (NLPCA). The most common method of data subdivision for training, validating and testing is a method of random or redundant subsets. This method of data subdivision is not always appropriate because ecological systems represent open sets with complex relationships. Ecological data are often incomplete and contaminated by noise. This paper proposes a systematic approach to subdivision of data into training, validating and testing datasets.
History data collection, retrieving and display in the NSLS control system

This paper presents the history data collection, retrieve and presentation subsystem of our control system. We made every effort to to make the software friendly, convenient and robust. It is widely used and has become a very valuable diagnostic tool. Anyone may start and stop his own history at any data rate up to 20 Hz. The data can be periodically written to disk files or stored in a cyclic ring buffer and dumped to a disk file upon request. All the history data files use the self-contained and self-explanatory standard format. One graphical display program displays all the history data files because of their standard format. In addition to the standard features of a plot program, this display program can display up to 16 devices on both axis, take differences with a reference point, browse the data file by pages or a scroll bar, zoom-in and zoom-out any portion of the plot, do many types of analyses, etc.
MPEG-7 multimedia description schemes

MPEG-7 multimedia description schemes (MDSs) are metadata structures for describing and annotating audio-visual (AV) content. The description schemes (DSs) provide a standardized way of describing in XML the important concepts related to AV content description and content management in order to facilitate searching, indexing, filtering, and access. The DSs are defined using the MPEG-7 description definition language, which is based on the XML Schema language, and are instantiated as documents or streams. The resulting descriptions can be expressed in a textual form (i.e., human readable XML for editing, searching, filtering) or compressed binary form (i.e., for storage or transmission). In this paper, we provide an overview of the MPEG-7 MDSs and describe their targeted functionality and use in multimedia applications.
Spatial and feature normalization for content-based retrieval

We explore methods for spatial and feature normalization of visual descriptors for content-based retrieval (CBR). A great many descriptors have been developed for characterizing features such as color, texture, edges, and so forth. In addition, numerous methods have also been proposed for extracting descriptors from whole images or regions. Furthermore, different options are possible for normalizing descriptor values for matching. We study different spatial and feature normalization strategies that include extracting descriptors from different spatial partitionings and normalizing descriptor values based on metric-space considerations or statistics of image collections. We empirically evaluate the relative efficacy in an image retrieval testbed.
Nitrogen-14 quadrupole resonance detection of RDX and HMX based explosives

Concerns the use of 14N signals in RDX and HMX. The principle is to subject the quadrupole nuclei to bursts of RF radiation and monitor the signals generated in the quiescent periods between pulses. These signals may be divided into two types: free induction decays (FID) and echoes. The first is the decaying signal observed immediately following the pulse; it is generated by the interaction of the oscillating magnetic field B of the applied RF with the magnetic moment of the quadrupolar nucleus. Often, this B field is generated by surrounding the sample with a small induction coil; the pulse may be imagined to tip the nuclear quadrupole moments away from their equilibrium orientation in the electric field gradient of their surroundings by a so-called "flip" angle α; they then precess at one of their allowed frequencies inducing a voltage in the same RF coil used to excite the transition. This voltage is observed to decay with a time constant, the FID or spin phase memory decay time. In many solids there are variations in the quadrupole frequencies due, for example, to defects or impurities in the material which alter the electric field gradient in their vicinity. The result is to produce a de-phasing of the NQR precession frequencies and a decay of the RF signal. Practical equipment is developed.
Enriching an informal engineering education program with social relevance and history for middle school girls

Two educators collaborated to design and test a one-week summer course for middle school girls on sound, engineering, and invention as an exemplar integrated STEM program that draws upon rich historical and social contexts with the goal of attracting and retaining students in STEM. An engineering design project and an invention project formed the core of the course. Music and related technologies served as the unifying theme intended to tap into the interests of youth. Historical primary sources and writing about invention and innovation provided additional entry points into engineering as a human and creative endeavor. Exposure to female inventors, scientists and engineers was also planned as a way for the girls to become acquainted with positive role models. Included in this paper is a discussion of the underlying philosophies that influenced the design of the learning experiences for youth underrepresented in STEM.
Mission and overview of a Fusion Development Facility

The mission of the proposed Fusion Development Facility (FDF) is to fill the gaps between ITER and current experiments and a fusion demonstration power plant (DEMO). FDF should carry forward Advanced Tokamak (AT) physics and enable development of fusion's energy applications. Near term advanced tokamak physics and non-superconducting magnet technology will be used to achieve steady-state with burn, producing 100–250 MW fusion power with modest energy gain (Q≪5) in a modest sized device (between DIII-D and JET). FDF will further develop all elements of AT physics for an advanced performance DEMO. With neutron flux at the outboard midplane of 1–2 MW/m2, continuous operation for periods up to two weeks, and a goal of a duty factor of 0.3 per year, FDF can produce fluences of 3–6 MW-yr/m2 in ten years of operation, for fusion nuclear component research and development. The development of blankets suitable for tritium, electricity, and hydrogen production will be done first in port modules. Then, the most promising candidates will be deployed as full blankets in FDF. Two to three full blankets and about a dozen port blanket types could be tested. A goal of FDF is to demonstrate closure of the fusion fuel cycle, producing its own tritium. FDF, ITER, IFMIF, and other AT devices will provide the basis for a fusion DEMO power plant of the ARIES-AT type.
Cygnus diverter switch analysis

The Cygnus Dual Beam Radiographic Facility consists of two 2.25-MV, 60-kA, 50-ns x-ray sources fielded in an underground laboratory at the Nevada Test Site. The tests performed in this laboratory involve study of the dynamic properties of plutonium and are called subcritical experiments. From end-to-end, the Cygnus machines utilize the following components: Marx generator, water-filled pulse-forming line (PFL), water-filled coaxial transmission line (WTL), 3-cell inductive voltage adder (IVA), and rod-pinch diode. The upstream WTL interface to the PFL is via a radial insulator with coaxial geometry. The downstream WTL terminates in a manifold where the center conductor splits into three lines which individually connect to each of the IVA cell inputs. There is an impedance mismatch at this juncture. It is a concern that a reflected pulse due to anomalous behavior in the IVA or diode might initiate breakdown upon arrival at the upstream PFL/WTL insulator. Therefore near the beginning of the WTL a radial diverter switch is installed to protect the insulator from over voltage and breakdown. The diverter has adjustable gap spacing, and an in-line aqueous-solution (sodium thiosulfate) resistor array for energy dissipation. There are capacitive voltage probes at both ends of the WTL and on the diverter switch. These voltage signals will be analyzed to determine diverter performance. Using this analysis the usefulness of the diverter switch will be evaluated.
Cygnus PFL switch jitter

The Cygnus Dual Beam Radiographic Facility consists of two identical radiographic sources: Cygnus 1 and Cygnus 2. Each source has the following X-ray output: 1-mm diameter spot size, 4 rads at 1 m, 50-ns full-width-half-maximum. The diode pulse has the following electrical specifications: 2.25 MV, 60 kA, 60 ns. This Radiographic Facility is located in an underground tunnel test area at the Nevada Test Site (NTS). The sources were developed to produce high-resolution images on subcritical tests performed at NTS. Subcritical tests are single-shot, high-value events. For this application, it is desirable to maintain a high level of reproducibility in source output. The major components of the Cygnus machines are Marx generator, water-filled pulse forming line (PFL), water-filled coaxial transmission line, three-cell inductive voltage adder, and rod-pinch diode. A primary source of fluctuation in Cygnus shot-to-shot performance may be jitter in breakdown of the main PFL switch, which is a “self-break” switch. The PFL switch breakdown time determines the peak PFL charging voltage, which ultimately affects the source X-ray spectrum and dose. Therefore, PFL switch jitter may contribute to shot-to-shot variation in these parameters, which are crucial to radiographic quality. In this paper we will present PFL switch jitter analysis for both Cygnus machines and present the correlation with dose. For this analysis, the PFL switch on each machine was maintained at a single gap setting, which has been used for the majority of shots at NTS. In addition the PFL switch performance for one larger switch gap setting will be examined.
Detection of Stochastic Nuclear Quadrupole Resonance Signals

Nuclear quadrupole resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique, allowing the detection of compounds containing quadrupolar nuclei, a requirement fulfilled by many high explosives and narcotics. The practical use of NQR is restricted by the inherently low signal- to-noise ratio of the observed signals, indicating a need for more effective techniques. The current literature focuses on the use of conventional, multiple-pulsed NQR (cNQR) to obtain signals. Here, we investigate an alternative method called stochastic NQR, having many advantages over cNQR, also proposing several detection strategies for the method. The presented detectors are evaluated on both simulated and measured trinitrotoluene (TNT) data.
Analysis of antenna interactions using the INSTANT software

INSTANT (short for INSTalled ANTenna performance) is a ray-tracing software suite that accurately predicts antenna behaviour, including antenna-antenna interactions, in the presence of conducting bodies, such as aircraft, ships and land vehicles. Special features of INSTANT are its direct use of a NURBS (non-uniform rational B-spline) representation to model surfaces and its employment of computer graphics techniques to treat the consequent ray intersections with bodies in a reliable, accurate and efficient manner.
Content adaptation framework: bringing the Internet to information appliances

The deployment of information appliances is predicted to exceed that of personal computers in the next few years. However, due to the wide range of communication, processing, storage and display capabilities of information appliances, the multimedia content on the Internet needs to be adapted before it can be efficiently delivered to these devices. We present content adaptation framework (CAF), a general framework for customizing Internet content for diverse client devices. The system first analyzes the content to be customized. Next, a variety of transcoders generate multi-resolution, multimodal versions of the content. The transcoded versions of the multimedia content are represented in a novel multi-modal, multi-resolution representation hierarchy called the InfoPyramid. Finally, a selection module uses an extended rate-distortion framework to pick the best content versions from the InfoPyramid while meeting the client device characteristics and resources. The content adaptation system can be deployed at various nodes in the Internet topology, such as at the server, at the client device or at an intermediate proxy. We present examples of proxy and server content adaptation systems based on CAF. Based on the content adaptation framework, we present a description scheme for multimedia and Internet content. This description scheme enables universal access to content. It has been proposed to various standards bodies.
Towards large scale land-cover recognition of satellite images

The entire Earth surface has been documented with satellite imagery. The amount of data continues to grow as higher resolutions and temporal information become available. With this increasing amount of surface and temporal data, recognition, segmentation, and event detection in satellite images with a highly scalable system becomes more and more desirable. In this paper, a semantic taxonomy is constructed for the land-cover classification of satellite images. Both the training and running of the classifiers are implemented in a distributed Hadoop computing platform. Publicly available high resolution datasets were collected and divided into tiles of fixed dimensions as training data. The training data was manually indexed into the semantic taxonomy categories, such as ”Vegetation”, ”Building”, and ”Pavement”. A scalable modeling system implemented in the Hadoop MapReduce framework is used for training the classifiers and performing subsequent image classification. A separate larger test dataset of the San Diego region, acquired from Microsoft BING Maps, was used to demonstrate the efficacy of our system at large scale. The presented methodology of land-cover recognition provides a scalable solution for automatic satellite imagery analysis, especially when GIS data is not readily available, or surface change may occur due to catastrophic events such as flooding, hurricane, and snow storm, etc.
Exploring semantic dependencies for scalable concept detection

Semantic concept detection from multimedia features enables high-level access to multimedia content. While constructing robust detectors is feasible for concepts with sufficient training samples, concepts with fewer training samples are hard to train efficiently. Comparable performance may be possible if the dependence of these concepts on the ones that can be robustly modeled is exploited. In this paper we show this phenomenon using the TREC Video 2002 Corpus as a test bed. Using a basic set of 12 semantic concepts modeled with support vector machines, we predict presence of 4 other concepts. We then compare the performance of these predictors with direct SVM models for these 4 concepts and observe improvements of up to 150% in average precision.
Towards Understanding the Effectiveness of Election Related Images in Social Media

In recent years, political campaigns have paid increasing attention to social media. During the election period, numerous election related images are posted. However, not all the images have the same effectiveness, and researchers have not investigated the intrinsic relationship between the effectiveness and the high-level visual features of social images. In this paper, we present a new study to analyze the effectiveness of election related images in social media. We first compute three semantic visual attributes for election related images: 1) face attribute, which indicates the presence of a political candidate, 2) text attribute, which describes the area of text information, 3) logo attribute, which denotes whether an image contains a campaign logo. Next, we consider the effectiveness in terms of the number of views and comments, and employ analysis of variance and association analysis to understand the importance of visual attributes in affecting the effectiveness of election related images. In addition, visual attributes distribution analysis reveals Obama campaign's deliberate effort targeting social media. The experiments on the 2012 US presidential election related images provide interesting insight that can be exploited in similar scenarios.