nils-herrmann/clean_scirepeval huggingface dataset:
Detection of slide transition for topic indexing

This paper presents an automatic and novel approach in detecting the transitions of slides for video sequences of technical lectures. Our approach adopts a foreground vs background segmentation algorithm to separate a presenter from the projected electronic slides. Once a background template is generated, text captions are detected and analyzed. The segmented caption regions as well as background templates together provide salient visual cues to decide whether a slide is flipped and replaced. The partitioning of videos according to slide changes not only structure the content of video according to topics, but also facilitate the synchronization of video, audio and electronic slides for effective indexing, browsing and retrieval.
Accelerating the Nonequispaced Fast Fourier Transform on Commodity Graphics Hardware

We present a fast parallel algorithm to compute the nonequispaced fast Fourier transform on commodity graphics hardware (the GPU). We focus particularly on a novel implementation of the convolution step in the transform as it was previously its most time consuming part. We describe the performance for two common sample distributions in medical imaging (radial and spiral trajectories), and for different convolution kernels as these parameters all influence the speed of the algorithm. The GPU-accelerated convolution is up to 85 times faster as our reference, the open source NFFT library on a state-of-the-art 64 bit CPU. The accuracy of the proposed GPU implementation was quantitatively evaluated at the various settings. To illustrate the applicability of the transform in medical imaging, in which it is also known as gridding, we look specifically at non-Cartesian magnetic resonance imaging and reconstruct both a numerical phantom and an in vivo cardiac image.
Destabilization of backward waves by space charge in gyrotron beams

The beam tunnels of high power gyrotrons can become unstable to the excitation of gyro-backward waves, degrading beam quality and lowering the efficiency of the desired, operating mode. Efforts are usually made to suppress this instability by disrupting or damping the backward propagating electromagnetic mode. We study here the effect on start oscillation currents of the coupling of the backward wave to the forward propagating electrostatic cyclotron maser instability [1, 2]. Normally, in the analysis of the gyro-bwo an absolutely unstable mode is formed due to coupling of the backward propagating structure mode and the forward propagating beam perturbation. When space charge is included the forward propagating signal also acquires gain due to the negative mass effect, and this results in a lowering of the start current threshold for the gyro-bwo instability. The start current is minimal when the cyclotron resonance condition is maintained over the beam tunnel. This may take place when an axial wavenumber of unstable perturbations on the beam corresponds to the tapering of the magnetic field. This implies the modes will be sensitive to the magnetic field tapering and to the spread in electron axial velocity.
Biomechanical assessment of passive joint control in children with cerebral palsy-instrumentation

In this study a measurement system is described which is used to quantitatively evaluate joint dynamics at the elbow, knee and ankle during active and passive motion. The test instrument consists of a computer controlled DC servo motor; torque, displacement and other sensors; signal conditioning electronics; and a data acquisition and analysis system. The system is being used in conjunction with clinical tests to evaluate a group of children with cerebral palsy undergoing dorsal segmental rhizotomy surgery to reduce spasticity and improve ambulatory capacity.<<ETX>>
Decision networks for integrating the behaviors of virtual agents and avatars

We examine the use of decision networks in animating virtual agents. We have developed a system that allows the realization of multiple, parallel behaviors for an agent. The networks we utilize, called PaT-Nets, are used both to represent individual behaviors and also to encode rules of engagement between agents. The multiple networks simultaneously attached to an individual agent are used to control locomotion, planning, visual attention and decision-making strategy. We discuss how human players may be substituted for autonomous players and still operate under the represented behaviors in the PaT-Nets.
Analysis of spectral changes and filter design in tagged cardiac MRI

Tagged cardiac magnetic resonance images are often pre-filtered before tag lines are tracked to reduce noise, emphasize tag lines, and, in grid tagged images, suppress tag lines in one of the two directions. Cardiac deformation causes changes in the spectrum at each time frame, and an effective pre-filter should cover as much of the deformed spectrum as possible around the peaks from a given tag line direction while minimizing the leakage from peaks in the other tag line direction. In this paper, we propose a model for spectral changes due to cardiac deformation, and use this model to motivate the design of a composite Gabor (C-Gabor) pre-filter. The performance of this filter was compared to standard Gabor and HARP filters in ten human imaging studies. Experimental results demonstrated that the C-Gabor filter was superior to the other two filters because it achieved better performance over the largest range of parameters
Audio-Visual Affect Recognition

The ability of a computer to detect and appropriately respond to changes in a user's affective state has significant implications to human-computer interaction (HCI). In this paper, we present our efforts toward audio-visual affect recognition on 11 affective states customized for HCI application (four cognitive/motivational and seven basic affective states) of 20 nonactor subjects. A smoothing method is proposed to reduce the detrimental influence of speech on facial expression recognition. The feature selection analysis shows that subjects are prone to use brow movement in face, pitch and energy in prosody to express their affects while speaking. For person-dependent recognition, we apply the voting method to combine the frame-based classification results from both audio and visual channels. The result shows 7.5% improvement over the best unimodal performance. For person-independent test, we apply multistream HMM to combine the information from multiple component streams. This test shows 6.1% improvement over the best component performance
3C-SiC on Si: A bio- and hemo-compatible material for advanced nano-bio devices

Silicon carbide (SiC) has long been known as a robust semiconductor with superior properties to silicon for electronic applications. The cubic form of SiC, known as 3C-SiC, has been researched for non-electronic applications, such as MEMS and biosensors. In particular, our group has demonstrated that 3C-SiC is one of the few semiconductor materials that possesses both bio- and hemacompatibility, thus opening up a plethora of applications for this material. We have pioneered several biomedical devices using 3C-SiC grown on Si substrates, and recently have been investigating the use of this novel material for both biosensor and neural prosthetic applications. Research to develop suitable biosensors, mainly via surface functionalization of 3C-SiC surfaces, has shown that 3C-SiC can be functionalized in much the same was as Si. We review nearly a decade of activity in 3C-SiC on Si biotechnology, with particular emphasis on the most promising applications: surface functionalization, in-vivo glucose sensing and biomedical implants for connecting the human nervous system to advanced prosthetics.
Characterization of the directional mobile radio channel in industrial scenarios, based on wideband propagation measurements

The object of this paper is to provide data from wideband directional channel measurements carried out at 5.2 GHz in two different industrial scenarios. The channel is characterized by the temporal, azimuthal and Doppler characteristics under LOS and non-LOS situations. The results give insight into the propagation behavior for this type of environment and reveal that the installation of wireless LANs in industrial scenarios imposes important requirements on the system design.
Design of a linear C-band helix TWT for digital communications experiments using the CHRISTINE suite of large-signal codes

A set of optimization goal functions designed to improve the efficiency and linearity performance of helix traveling-wave tubes (TWT) is described. These goal functions were implemented in the CHRISTINE suite of large-signal helix TWT codes along with a steepest-descent optimization algorithm to automate the process of circuit parameter variation and to facilitate the rapid exploration of alternative TWT designs. We compare the predicted power, efficiency, and linearity of four different helix TWT circuits, each developed according to a different set of optimization criteria. Out of these designs, a single design was selected to be further developed for use in C-band high-data-rate communications experiments. The detailed design of this linearized TWT with a predicted 1-dB small-signal bandwidth of 1.2 GHz, small-signal centerband gain of 35.7 dB (f/sub c/=5.5 GHz), and centerband saturated output power of 52 dBm (158.5 W) is presented.
Envelope model of beam radius variations in steady state beam-circuit interaction codes

The beam envelope equation  provides a simple model of the steady state dependence of the radius of an electron beam on axial location. Since the forces acting on a beam in any linear beam VE device depend on the beam radius, it is useful to have a model of the axial variation of the beam size in a beam-circuit interaction code. We describe an implementation of the envelope model in the CHRISTINE-CC large signal code for coupled-cavity TWTs [2], which ordinarily uses disks of fixed radius to represent the beam. Using this “add-in” envelope model, we illustrate some effects of beam expansion and contraction in a coupled-cavity TWT.
Computed tomography super-resolution using convolutional neural networks

The practical application of Computed Tomography (CT) faces the dilemma between higher image resolution and less X-ray exposure for patients, motivating the research on CT super-resolution (SR). In this paper, we apply state-of-the-art SR techniques to reconstruct CT images using two proposed advanced CT SR models based on Convolutional Neural Networks (CNNs) and residual learning: a single-slice CT SR network (S-CTSRN), and a multi-slice CT SR network (M-CTSRN). S-CTSRN improves the high-frequency feature extraction by incorporating the residual learning strategy, while M-CTSRN further utilizes the coherence between neighboring CT slices for better SR reconstruction. We evaluate both models on a large-scale CT dataset1, and obtain competitive results both quantitatively and qualitatively.
Electrical characterization of VLSI packages

The authors define, verify, and demonstrate measurement instruments and test fixtures required to successfully characterize IC packages electrically for low-frequency applications (<50 MHz). Three fundamentally different measurement techniques were evaluated. One uses the HP 4191A RF Impedance Analyzer instrument, which measures the frequency-domain reflection coefficient and phase angle of any load and calculates its impedance. Another measurement technique uses the HP 4194A Impedance/Gain Phase Analyzer, which measures the frequency-domain voltage across the test load generated by the current through its magnitude and phase shift. The other measurement technique is called ramp-derivative; its measurement principle is based on the time domain transient response and the fundamental definition of resistance, inductance, and capacitance to determine their respective values.<<ETX>>
Context classification during blood pressure self-measurement using the sensor seat and the audio classification device

Blood pressure self-measurement (BPSM) requires the patient to follow a range of recommendations. Patients must remain silent during measurements, be seated correctly with back support and legs uncrossed, and must have rested at least 5 minutes prior to taking the measurement. Current blood pressure (BP) devices cannot verify whether the patient has followed these recommendations or not. As a result, the data quality of BP measurements could be biased. We present a proof-of-concept demonstration prototype that uses audio context classification for detecting speech during the measurement process, as well as a sensor seat for measuring patient posture and activity before and during the BPSM process.
Efficient Nonparametric Belief Propagation with Application to Articulated Body Tracking

An efficient Nonparametric Belief Propagation (NBP) algorithm is developed in this paper. While the recently proposed nonparametric belief propagation algorithm has wide applications such as articulated tracking [22, 19], superresolution [6], stereo vision and sensor calibration , the hardcore of the algorithm requires repeatedly sampling from products of mixture of Gaussians, which makes the algorithm computationally very expensive. To avoid the slow sampling process, we applied mixture Gaussian density approximation by mode propagation and kernel fitting [2, 7]. The products of mixture of Gaussians are approximated accurately by just a few mode propagation and kernel fitting steps, while the sampling method (e.g. Gibbs sampler) needs many samples to achieve similar approximation results. The proposed algorithm is then applied to articulated body tracking for several scenarios. The experimental results show the robustness and the efficiency of the proposed algorithm. The proposed efficient NBP algorithm also has potentials in other applications mentioned above.
A comprehensive study of surface modified graphene based polymer nanocomposites for multifunctional electronic applications

Graphene is a new emerging nanocarbon material, with exciting unique properties including superb thermal and electrical conductivity, strong mechanical and anti-corrosive property, extremely high surface area etc. It can be considered as new generation reinforcement material for polymer composites due to its cheap production cost comparison with carbon nanotube, ease of functionalization and dramatic improvements in properties at very low filler content, high specific surface area, good compatibility, low mass density, elegant flexibility. This review presents an overview of surface functionalised graphene/polymer nanocomposites discussing different strategies for functionalization of graphene, a series of effective processing routes for producing high quality polymer nanocomposites and recent developments in the electrical properties of functionalised grapheme polymer nanocomposites. Finally, this review provides an overview of potential applications of the graphene based polymer nanocomposites in various areas, such as sensors, electrodes, energy storage, EMI and ESD materials.
A breakthrough in power electronics reliability — New die attach and wire bonding materials

Power Electronics on DCB are used for high power devices. There is a wide field of applications for such power electronic devices like converters or inverters for wind mills, solar parks or for electric and hybrid vehicles. High efficiency, long life time and increased power density are the major technical requirements for those devices. Especially the life time, but also the power density are limited by die attach and wire bond materials. New material solutions to overcome these limitations in life time will be discussed in this paper. Results of an active power cycling test of DCB devices supported by the failure analysis and material data will be used to demonstrate and explain the novel materials advantages versus conventional solutions.
A scalable distributed RRT for motion planning

Rapidly-exploring Random Tree (RRT), like other sampling-based motion planning methods, has been very successful in solving motion planning problems. Even so, sampling-based planners cannot solve all problems of interest efficiently, so attention is increasingly turning to parallelizing them. However, one challenge in parallelizing RRT is the global computation and communication overhead of nearest neighbor search, a key operation in RRTs. This is a critical issue as it limits the scalability of previous algorithms. We present two parallel algorithms to address this problem. The first algorithm extends existing work by introducing a parameter that adjusts how much local computation is done before a global update. The second algorithm radially subdivides the configuration space into regions, constructs a portion of the tree in each region in parallel, and connects the subtrees,i removing cycles if they exist. By subdividing the space, we increase computation locality enabling a scalable result. We show that our approaches are scalable. We present results demonstrating almost linear scaling to hundreds of processors on a Linux cluster and a Cray XE6 machine.
A new consistent image registration formulation with a B-spline deformation model

A consistent image registration formulation with B-spline deformation model is proposed. This formulation avoids the computation of the inverse of a deformation in the iterative optimization and allows the analytical computation of both gradient and Hessian of the cost function. Because of the formulation, the algorithm is computationally efficient and could potentially produce more accurate registration results. Experiments show that the proposed algorithm produces promising results while keeping the estimated deformations consistent.
110+ GHz Transimpedance Amplifier in InP-HBT Technology for 100 Gbit Ethernet

A 50 dB-Ω transimpedance amplifier (TIA) with a bandwidth greater than 110 GHz has been demonstrated using InP HBT technology. The wide-band amplifier with a cutoff frequency > 110 GHz was designed and fabricated in HRL Laboratories' G4 0.25 μm InP HBT IC technology. The amplifier operates at -4.0 V with a current draw of 76 mA for a power consumption of 304 mW. The basic Cherry-Hooper gain cell is used with a single-ended input and a differential output buffer stage.
Amplitude/Timing Jitter and Peak-to-Peak Variation Optimal Rate Multipliers

We present the design and performance validation of jitter and peak-to-peak variation optimal rate multipliers based on finite-impulse-response optical interferometers. To this end, we show that uniform impulse response interferometers yield minimum jitter and peak-to-peak variation for most practical cases. We also discuss the realization of optimal interferometers with sampled fiber Bragg gratings (FBGs), and show by means of numerical simulations that the jitter and peak-to-peak variation performance of the designed FBGs is in close agreement with the theory.
Cod-ConfDB: a codon - conformation database

A relational database of codons, corresponding amino acid sequence and the protein conformation in terms of dihedral angles, "Cod-ConfDB" has been developed considering well- resolved representative proteins of the protein data bank (PDB). In other words, the database provides information at three levels viz. the nucleotide level (codons), the protein primary structure level (amino acid sequence) and the three-dimensional structure level (conformation of the protein). The database is Web accessible and can be queried through the Web interface. The database would have numerous applications including the optimization of protein expression, serve as a knowledge base for proteinfolding algorithms and hence find application in protein three-dimensional structure prediction and further answering numerous questions such as the role of synonymous codons in fold determination etc.
Determining 3-D motion and structure of a rigid body using straight line correspondences

This paper describes the main results obtained for the determination of 3-D motion and structure of a rigid body containing straight line segments, given a sequence of (2-D) perspective views . The analysis is based on the representation of the central projection of a 3-D line on the unit sphere. Methods over 2 and 3 frames are shown for the cases of pure rotation, pure translation, and general motion.
Dynamic Simulation of Coal Mine Electrical Power Systems

A flexible method for modeling mine electrical power systems is presented. Utilizing this simulation procedure, detailed analyses of bus voltages, transmission line power flows, and machine behavior are possible under conditions of steady-state or dynamic operation. Mining machine operation changes, as well as motor starting sequences, may be simulated. The model operates interactively, and the power system is configured as a user responds to program generated questions and requests. The theory behind the programming, as well as explanations of the models, are provided. An example is also given to demonstrate simulation capabilities.
Dynamical analysis of chaos anti-synchronisation in bidirectionally coupled SMIB power system

Controlled operation of electrical power system is challenging, especially when they unveil chaotic behavior under the privation of reactive power and various disturbances. There are exchanges of power among different parts of power systems involved in its operation. Hence, we investigate the effect of bidirectional coupling between two Single Machine Infinite Bus (SMIB) power systems to study its dynamic behavior. The dynamics of these coupled systems is strongly influenced by variation in coupling strength. The uncoupled systems which are initially in chaotic state can be anti synchronised between each other by suitable choice of coupling form and optimum coupling strength. It is observed that stronger coupling can drive chaotic systems back to periodic state.
Clustering of MIMO Channel Parameters - Performance Comparison

Novel channel models as from COST 273 and IST- WINNER projects are models to evaluate the performance of multi-antenna concepts under link-level and system-level. For consistent performance evaluation the channel models needed to be parameterized by multipath parameters based on measurements. It seems these parameters can be grouped into geometrically co-located paths, so called clusters. The reliability and reproducibility of the estimated parameter groups, depend inter alia on the decision criterions, initialization and the chosen cluster algorithm itself. In this paper the focus is to analyse the performance of different clustering algorithms and initialization stages. Furthermore an improved initialization approach is presented. Index Terms—Multipath clustering, spatial channel modelling, high resolution multipath parameter estimation, geometry-based stochastic channel model, generic multi-path cluster MIMO channel
An analysis of finite precision effects for the autocorrelation method and Burg's method of linear prediction

New analytical results are derived for quantifying the performance degradation induced by finite precision arithmetic upon the autocorrelation method and Burg's algorithm for linear prediction. Analysis shows that reflection coefficients computed by the FP autocorrelation method have more severe degradation than those computed by the FP Burg algorithm. Finally, experimental results are presented which show very close agreement between the analytical derivations and experimental results.