nils-herrmann/clean_scirepeval huggingface dataset:
Local estimation of collision probabilities in 802.11 WLANs: An experimental study

Current 802.11 networks do not typically achieve the maximum potential throughput despite link adaptation and cross-layer optimization techniques designed to alleviate many causes of packet loss. A primary contributing factor is the difficulty in distinguishing between various causes of packet loss, including collisions caused by high network use, co-channel interference from neighboring networks, and errors due to poor channel conditions. In previous work, we used NS-2 simulations to show that estimating various components of loss probability such as direct collisions, staggered collisions, and physical layer errors, can be used to improve the throughput of 802.11 networks via link adaptation, carrier sense threshold adaptation, and MAC layer packet length adaptation. We have also proposed a method to estimate the various components of loss probability by comparing channel occupancy at a station with that of its access point. In this paper, we use Ath5k open source wireless card driver in an experimental testbed in order to experimentally verify the accuracy of our previously proposed approach to estimating collision probability. We show that our proposed methodology accurately estimates overall collision probability to within 5%. This experimental verification demonstrates the feasibility of our collision probability estimation approach and the resulting throughput gains in practice.
Large Area Cell Based Image Localization

We present a memory scalable image localization system that uses distributed kd-trees created on overlapping geographic cells using a database of 10 million Google Street View images for an area of approximately 10,000 square kilometers in Taiwan. Given a collection of images over a region of interest (ROI), we generate a database by dynamically creating geographic cells that are optimized so that each cell contains roughly the same number of images. We then create kd-trees for each cell from SIFT features extracted from the images in that cell. When querying the system, we run traditional feature matching on each cell and pool the results for each cell to rerank with a geometric constraint. The key idea is the subdivisions of the ROI into overlapping geographic cells, allowing our system to scale to 10 million images and to efficiently utilize prior query location information when available. We evaluate our system on a test set of 29 geo-tagged images, not from Google Street View, taken throughout Taiwan with various resolutions, aspect ratios, and qualities. We also evaluate our system on a set of 97 images without geo-tag data.
Inverse and approximation problem for two-dimensional fractal sets

The geometry of fractals is rich enough that they have extensively been used to model natural phenomena and images. Iterated function systems (IFS) theory provides a convenient way to describe and classify deterministic fractals in the form of a recursive definition. As a result, it is conceivable to develop image representation schemes based on the IFS parameters that correspond to a given fractal image. In this paper, we consider two distinct problems: an inverse problem and an approximation problem. The inverse problem involves finding the IFS parameters of a signal that is exactly generated via an IFS. We make use of the wavelet transform and of the image moments to solve the inverse problem. The approximation problem involves finding a fractal IFS-generated image whose moments match, either exactly or in a mean squared error sense, a range of moments of the original image. The approximating measures are generated by an IFS model of a special form and provide a general basis for the approximation of arbitrary images. Experimental results verifying our approach will be presented.
Data processing algorithms for generating textured 3D building facade meshes from laser scans an camera images

In this paper, we develop a set of data processing algorithms for generating textured facade meshes of cities from a series of vertical 2D surface scans and camera images, obtained by a laser scanner and digital camera while driving on public roads under normal traffic conditions. These processing steps are needed to cope with imperfections and non-idealities inherent in laser scanning systems such as occlusions and reflections from glass surfaces. The data is divided into easy-to-handle quasi-linear segments corresponding to approximately straight driving direction and sequential topological order of vertical laser scans; each segment is then transformed into a depth image. Dominant building structures are detected in the depth images, and points are classified into foreground and background layers. Large holes in the background layer, caused by occlusion from foreground layer objects, are filled in by planar or horizontal interpolation. The depth image is further processed by removing isolated points and filling remaining small holes. The foreground objects also leave holes in the texture of building facades, which are filled by horizontal and vertical interpolation in low frequency regions, or by a copy-paste method otherwise. We apply the above steps to a large set of data of downtown Berkeley with several million 3D points, in order to obtain texture-mapped 3D models.
Video similarity detection with video signature clustering

The proliferation of video content on the Web makes similarity detection an indispensable tool in Web data management, searching, and navigation. We have previously proposed a compact representation of video clips, called video signature, for retrieving similar video clips in large databases. In this paper, we propose a new signature clustering algorithm to further improve retrieval performance. The algorithm treats all the signatures as an abstract threshold graph, where the threshold is determined based on local data statistics. Similar clusters are identified as highly connected regions in the graph. This algorithm outperforms simple thresholding and hierarchical clustering techniques in identifying a set of manually-determined similar clusters from a dataset of 46,356 Web video clips. At 95% precision, our algorithm attains 85% recall while simple thresholding and complete-link hierarchical scheme attain 67% and 75% recall respectively. Applying our algorithm to the entire dataset, 6,900 similar clusters are identified, with an average cluster size of 2.81 video clips. The distribution of cluster sizes follows a power-law distribution, which has been shown to describe many Web phenomena.
Motion indexing of video

A system has been developed to analyze and index surveillance videos based on the motions of objects in the scene. A segmentation and tracking system extracts trajectories from compressed video, which are represented in a multiresolution manner and stored in a database. Hand-drawn queries can be submitted to the system for imprecise searches. The system was tested on real video footage with numerous moving objects; the success rates for tracking and recall in most cases exceeded 70 percent, a promising result.
Spectral characteristics of the double loop /spl Sigma//spl Delta/ modulator

An important factor affecting the performance of /spl Sigma//spl Delta/ modulators is their tone behavior. A recent approach to alleviate the tone problem consists of moving the open loop poles outside the unit circle. In this paper, we determine the frequency location of two dominant tones as a function of pole location and obtain a partial characterization of the spectral shape. Audio testing along with a series of simulations are then performed to compare the efficacy of pole placement with that of the more traditional tone removal technique of dithering.
Binary and phase shifting mask design for optical lithography

The authors propose a number of pre-distorted mask design techniques for binary and phase-shifting masks. Their approach is based on modeling the imaging mechanism of a stepper by the Hopkins equations and taking advantage of the contrast-enhancement characteristics of photoresist. Optimization techniques such as the branch and bound algorithm and simulated annealing algorithm are used to systematically design pre-distorted masks under incoherent and partially coherent illumination. Computer simulations are used to show that the intensity contour shapes and developed resist shapes of their designed mask patterns are sharper than those of conventional masks. The designed phase-shifting masks are shown to result in higher contrast as well as sharper contours than binary masks. An example of phase conflicting masks designed with the algorithm is shown to outperform a simple intuitive design. This example indicates that a fairly general design procedure consisting of alternating phase shifts and their optimized phase-shift masks is a viable candidate for future phase-shifting mask design.
A multi-start algorithm for signal adaptive subband systems (image coding)

A method for optimizing the filter coefficients of signal adaptive subband systems, in which the polyphase transfer matrix is paraunitary, using a mean-squared-error criterion is proposed. An efficient algorithm was developed for locating numerous local optima in the coefficient space, permitting a degree of confidence in the location of globally optimal or near-optimal solutions. Both separable systems and a particular class of nonseparable filter systems are studied. The application of the algorithm to a number of images is described.<<ETX>>
2D tree detection in large urban landscapes using aerial LiDAR data

We present a scalable approach to tree detection in large urban landscapes using aerial LiDAR data. Similar to our previous work in 2006, our current method consists of segmentation followed by classification. However, unlike our previous work, the current approach does not use color information or aerial imagery, and hence is more generally applicable. Also, our current approach has been successfully tested on two very large datasets, which are many orders of magnitude larger than the dataset used in 2006. Specifically, we use a North American dataset, containing 125 million LiDAR returns over 3 km2, and a European dataset, containing 200 million LiDAR returns over 7 km2. For both datasets, we report precision and recall rates of over 95%.
Rate control for streaming video over wireless

Rate control is an important issue in video streaming applications for both wired and wireless networks. A widely accepted rate control method in wired networks is TCP-friendly rate control (TFRC) (Floyd, 2000). It is equation-based rate control in which the TCP-friendly rate is determined as a function of packet loss rate, round-trip time, and packet size. TFRC assumes that packet loss in wired networks is primarily due to congestion, and as such is not applicable to wireless networks in which the main cause of packet loss is at the physical layer. In this article we review existing approaches to solve this problem. Then we propose multiple TFRC connections as an end-to-end rate control solution for wireless video streaming. We show that this approach not only avoids modifications to the network infrastructure or network protocol, but also results in full utilization of the wireless channel. NS-2 simulations, actual experiments over a 1/spl times/RTT CDMA wireless data network, and video streaming simulations using traces from the actual experiments are carried out to characterize the performance and show the efficiency of our proposed approach.
Two-dimensional polynomial interpolation from nonuniform samples

The authors derive a number of results on sufficient conditions under which the 2-D polynomial interpolation problem has a unique or nonunique solution. It is found that, if the sum of the degrees of the irreducible curves on which the interpolation points are chosen is small compared to the degree of the interpolating polynomial, then the problem becomes singular. Similarly, if there are too many points on any of the irreducible curves on which the interpolation points are chosen, then the interpolation problem runs into singularity. Examples of geometric distribution of interpolation points satisfying these conditions are shown. The examples include polynomial interpolation of polar samples, and samples on straight lines. The authors propose a recursive algorithm for computing 2-D polynomial coefficients for the nonsingular case where all the interpolation points are chosen on lines passing through the origin. The result is applied to the problem of nonuniform frequency sampling design for 2-D FIR filter design, and a few examples of such design are shown.
Receiver-driven bandwidth sharing for TCP and its application to video streaming

Applications using Transmission Control Protocol (TCP), such as web-browsers, ftp, and various peer-to-peer (P2P) programs, dominate most of the Internet traffic today. In many cases, users have bandwidth-limited last mile connections to the Internet which act as network bottlenecks. Users generally run multiple concurrent networking applications that compete for the scarce bandwidth resource. Standard TCP shares bottleneck link capacity according to connection round-trip time (RTT), and consequently may result in a bandwidth partition which does not necessarily coincide with the user's desires. In this work, we present a receiver-based bandwidth sharing system (BWSS) for allocating the capacity of last-hop access links according to user preferences. Our system does not require modifications to the TCP protocol, network infrastructure or sending hosts, making it easy to deploy. By breaking fairness between flows on the access link, the BWSS can limit the throughput fluctuations of high-priority applications. We utilize the BWSS to perform efficient video streaming over TCP to receivers with bandwidth-limited last mile connections. We demonstrate the effectiveness of our proposed system through Internet experiments.
Stability of reconstruction of real and complex multidimensional signals from Fourier transform magnitude

The lower bound on the condition number of the problem of reconstruction for two classes of signals is derived. The lower bound for N*N images in which the norm of the Fourier transform magnitude (FTM) vector is dominated by DC and low-frequency components is shown to grow with N. The lower bound for images in which the elements of the FTM vector contribute more or less equally to its norm is 1. The problem of reconstruction from FTM and known phase in space domain is discussed. Since the introduction of sufficiently random space-domain phase results in flattened FTM distribution, the lower bound on the condition number of the reconstruction problem with respect to the FTM vector again becomes one. This is in agreement with experimental results, indicating that randomizing the phase in space domain improves the convergence rate of the Grechberg-Saxton algorithm.<<ETX>>
Watertight Planar Surface Meshing of Indoor Point-Clouds with Voxel Carving

3D modeling of building architecture from point-cloud scans is a rapidly advancing field. These models are used in augmented reality, navigation, and energy simulation applications. State-of-the-art scanning produces accurate point-clouds of building interiors containing hundreds of millions of points. Current surface reconstruction techniques either do not preserve sharp features common in a man-made structures, do not guarantee water tightness, or are not constructed in a scalable manner. This paper presents an approach that generates watertight triangulated surfaces from input point-clouds, preserving the sharp features common in buildings. The input point-cloud is converted into a voxelized representation, utilizing a memory-efficient data structure. The triangulation is produced by analyzing planar regions within the model. These regions are represented with an efficient number of elements, while still preserving triangle quality. This approach can be applied to data of arbitrary size to result in detailed models. We apply this technique to several data sets of building interiors and analyze the accuracy of the resulting surfaces with respect to the input point-clouds.
Multiple TFRC Connections Based Rate Control for Wireless Networks

Rate control is an important issue in video streaming applications for both wired and wireless networks. A widely accepted rate control method in wired networks is equation based rate control , in which the TCP friendly rate is determined as a function of packet loss rate, round trip time and packet size. This approach, also known as TCP friendly rate control (TFRC), assumes that packet loss in wired networks is primarily due to congestion, and as such is not applicable to wireless networks in which the bulk of packet loss is due to error at the physical layer. In this paper, we propose multiple TFRC connections as an end-to-end rate control solution for wireless video streaming. We show that this approach not only avoids modifications to the network infrastructure or network protocol, but also results in full utilization of the wireless channel. NS-2 simulations, actual experiments over 1 times RTT CDMA wireless data network, and and video streaming simulations using traces from the actual experiments, are carried out to validate, and characterize the performance of our proposed approach
Deconvolution of electrograms to detect infarcted myocardium

Ablation to prevent cardiac arrhythmias requires interpretation of electrograms to locate the arrhythmogenic tissue. This study examined a novel signal processing technique employing deconvolution to calculate electrograms which best fit observed electrograms. We hypothesize that the power of difference between the calculated and the observed electrogram detects changes in morphology resulting from myocardial infarction. 380 electrograms were recorded from 10 dogs. Scintigraphic studies with Thallium-201 identified recording sites as normal or infarcted tissue. The power of the difference increased 65 percent for infarcted tissue as compared to normal tissue (p<0.0001). Receiver operating curves were plotted, and deconvolution detected 80% of the infarcted sites with a 20% false positive rate. Deconvolution's performance for detection of infarcted tissue was superior to previous metrics and shows promise for improving clinical electrogram interpretation.
Optimal binary image design based on the branch and bound algorithm

Mathematical programming techniques for systematic determination of optimal binary masks for precompensation in incoherent optical systems are developed. The feasibility of applying combinatorial optimization techniques to binary mask design for optical lithography is demonstrated. The mask is optimized in such a way as to precompensate the distortions due to optical diffraction of the system. The problem is formulated as a binary linear programming problem and solved with the branch and bound algorithm. Two different formulations corresponding to two optimization criteria are proposed and evaluated. Variation of the optimal mask as a function of the optical system bandwidth is discussed. One- and two-dimensional examples involving bars and a corner are presented.<<ETX>>
Optimal sampling and reconstruction of NMR signals with time-varying gradients

An optimal sampling and reconstruction scheme has been derived for free induction decay (FID) signals resulting from sinusoidal gradients that occur in nuclear magnetic resonance (NMR) imaging. The problem has been formulated as a linear parameter estimation problem by writing the observed signal, r(t), as the sum of the noise-free FID signal and a zero mean, white, Gaussian random process with intensity sigma /sup 2/. The noise-free FID signal is modeled to be a linear combination of the uniform samples of the object distribution, f(n/sub 1/,n/sub 2/). The optimal maximum-likelihood (ML) estimate of f(n/sub 1/,n/sub 2/) is derived for the constant-gradient case and then generalized to arbitrary time varying gradients.<<ETX>>
Multipath unicast and multicast video communication over wireless ad hoc networks

In this paper, we address the problem of real-time video communication over wireless ad hoc networks. For the unicast case, we propose a robust, multipath source routing protocol for both interactive and video on-demand applications. Simulations show that our proposed scheme enhances the quality of video applications as compared to the existing protocols. For the multicast case, we propose multiple tree multicast streaming as a way to provide robustness for video multicast applications. Specifically, we propose a distributed double disjoint tree multicast routing protocol called serial MDTMR, and characterize its performance via simulations. We show that serial MDTMR achieves reasonable tree connectivity while maintaining disjointness of two trees, and that it outperforms single tree multicast communication.
Automatic identification of window regions on indoor point clouds using LiDAR and cameras

In this paper, we propose an algorithm to automatically identify window regions on exterior facing facades of buildings using interior 3D point cloud resulting from an ambulatory backpack sensor system, outfitted with multiple LiDAR sensors and cameras. We develop a set of discriminative features for the task, namely visual brightness, infrared opaqueness, and an occlusion indicator, within a Markov Random Field (MRF) framework to provide structured prediction for window or glass regions. A preprocessing classifier is trained on the features to produce node potentials, and large margin parameter training is used to boost performance. Our algorithm has been trained on data taken at the 3rd floor of Cory Hall at UC Berkeley, with a total façade area of 269.1 m2, and has been tested on walls taken on the 2nd floor of Cory Hall, a Walgreens, and an office building in San Francisco, with a total exterior façade area of 454.6 m2. Window regions are successfully identified with 85.5% F1-score and 94.2% accuracy.
Deconvolution and propagation metrics of cardiac electrograms

Available metrics of cardiac electrograms are not considered to be adequate for activation time determination. The authors hypothesize that a deconvolution, which fits a modeled electrogram to an observed electrogram, is possible and would provide useful metrics of observed electrograms. They developed an algorithm which fits a uniform wave with constant velocity passing under the electrode. Activation time estimates were robust for fractionated electrograms, indicating potential clinical utility.<<ETX>>
Scene Text Localization and Recognition with Oriented Stroke Detection

An unconstrained end-to-end text localization and recognition method is presented. The method introduces a novel approach for character detection and recognition which combines the advantages of sliding-window and connected component methods. Characters are detected and recognized as image regions which contain strokes of specific orientations in a specific relative position, where the strokes are efficiently detected by convolving the image gradient field with a set of oriented bar filters. Additionally, a novel character representation efficiently calculated from the values obtained in the stroke detection phase is introduced. The representation is robust to shift at the stroke level, which makes it less sensitive to intra-class variations and the noise induced by normalizing character size and positioning. The effectiveness of the representation is demonstrated by the results achieved in the classification of real-world characters using an euclidian nearest-neighbor classifier trained on synthetic data in a plain form. The method was evaluated on a standard dataset, where it achieves state-of-the-art results in both text localization and recognition.