gebhart/patrepeval huggingface dataset:
Where to Place: A Real-Time Visual Saliency Based Label Placement for Augmented Reality Applications (2018)

Textual overlays/labels add contextual information in Augmented Reality (AR) applications. The spatial placement of labels is a challenging task due to constraints that labels (i) are not occluding the object/scene of interest, and, (ii) are optimally placed for better interpretation of scene. To this end, we present a novel method for optimal placement of labels for AR. We formulate this method by an objective function that minimizes both occlusion with visually salient regions in scenes of interest, and the temporal jitter for facilitating coherence in real-time AR applications. The main focus of proposed algorithm is real-time label placement on low-end android phones/tablets. The sophisticated state-of-the-art algorithms for optimal positioning of textual label work only on the images and are often inefficient for real-time performance on those devices. We demonstrate the efficiency of our method by porting the algorithm on a smart-phone/tablet. Further, we capture objective and subjective metrics to determine the efficacy of the method; objective metrics include computation time taken for determining the label location and Label Occlusion over Saliency (LOS) score over salient regions in the scene. Subjective metrics include position, temporal coherence in the overlay, color and responsiveness.
Clothing-based person clustering in family photos (2010)

This paper presents methods to explore and fuse various clothing features for person clustering in family photos. Our approach automatically detects the clothing regions, extracts the global and localized features based on color and texture, and then computes multiple partitions of people based on different features, which are combined into the final consolidated person clustering with a cluster ensemble technique. The clothing clusters can be used for complementing face clusters and for other photo organization applications. The effectiveness of our approach is tested on real-world family photo datasets.
Design of Powered Ankle-Foot Prosthesis With Nonlinear Parallel Spring Mechanism (2018)

In this paper, a powered ankle-foot prosthesis with nonlinear parallel spring mechanism is developed. The parallel spring mechanism is used for reducing the energy consumption and power requirement of the motor, at the same time simplifying control of the prosthesis. To achieve that goal, the parallel spring mechanism is implemented as a compact cam-spring mechanism that is designed to imitate human ankle dorsiflexion stiffness. The parallel spring mechanism can store the negative mechanical energy in controlled dorsiflexion (CD) phase and release it to assist the motor in propelling a human body forward in a push-off phase (PP). Consequently, the energy consumption and power requirements of the motor are both decreased. To obtain this desired behavior, a new design method is proposed for generating the cam profile. Unlike the existing design methods, the friction force is considered here. The cam profile is decomposed into several segments, and each segment is fitted by a quadratic Bezier curve. Experimental results show that the cam-spring mechanism can mimic the desired torque characteristics in the CD phase (a loading process) more precisely. Finally, the developed prosthesis is tested on a unilateral below-knee amputee. Results indicate that, with the assistance of the parallel spring mechanism, the motor is powered off and control is not needed in the CD phase. In addition, the peak power and energy consumption of the motor are decreased by approximately 37.5% and 34.6%, respectively.
Large-Scale Deduplication with Constraints Using Dedupalog (2009)

We present a declarative framework for collective deduplication of entity references in the presence of constraints. Constraints occur naturally in many data cleaning domains and can improve the quality of deduplication. An example of a constraint is "each paper has a unique publication venue''; if two paper references are duplicates, then their associated conference references must be duplicates as well. Our framework supports collective deduplication, meaning that we can dedupe both paper references and conference references collectively in the example above. Our framework is based on a simple declarative Datalog-style language with precise semantics. Most previous work on deduplication either ignoreconstraints or use them in an ad-hoc domain-specific manner. We also present efficient algorithms to support the framework. Our algorithms have precise theoretical guarantees for a large subclass of our framework. We show, using a prototype implementation, that our algorithms scale to very large datasets. We provide thoroughexperimental results over real-world data demonstrating the utility of our framework for high-quality and scalable deduplication.
LWD-DATC: Logging-While-Drilling Dipole Shear Anisotropy estimation from Two-Component waveform rotation (2017)

Sonic dipole shear anisotropy orientation in subsurface formations is key information for a complete characterization of rock mechanical models for well planning. In Wireline logging, it is estimated with the well-known Alford rotation on four-component inline and crossline waveforms from two orthogonal dipole firings. In contrast, shear orientation estimation is more challenging in Logging-While-Drilling (LWD) operations because of the following reasons:—No exactly orthogonal cross-dipole firings in LWD tools due to tool rotation while drilling;—Coupling between the formation flexural mode and the strong collar flexural mode propagating through the stiff drill collar;—Unavoidable tool eccentering;—Strong drilling noise from vibration, shock, and the turbulent mud flow around the tool; To overcome the aforementioned challenges, this paper describes a new technique to estimate the LWD dipole shear orientation with two-component waveforms obtained from a single dipole firing. It is accomplished by maximizing the projected energy of the two-component waveforms into a subspace defined by two eigenfunctions (the Bessel functions of the first- and second-kinds) accounting for the propagation of the two coupled flexural modes over multiple frequency points. By resorting to the subspace estimation, the new technique has been successfully validated on synthetic data and tested on field data sets.
Optical Interconnect for High-End Computer Systems (2010)

Advances in silicon photonic technology have made possible the use of optical communication in large-scale chip arrays. This article shows how such a structure utilizes the high bandwidth of the optical links through optical proximity communication that enables significant levels of device integration.
Iso-charts (2004)

We describe a fully automatic method, called iso-charts, to create texture atlases on arbitrary meshes. It is the first to consider stretch not only when parameterizing charts, but also when forming charts. The output atlas bounds stretch by a user-specified constant, allowing the user to balance the number of charts against their stretch. Our approach combines two seemingly incompatible techniques: stretch-minimizing parameterization, based on the surface integral of the trace of the local metric tensor, and the "isomap" or MDS (multi-dimensional scaling) parameterization, based on an eigen-analysis of the matrix of squared geodesic distances between pairs of mesh vertices. We show that only a few iterations of nonlinear stretch optimization need be applied to the MDS parameterization to obtain low-stretch atlases. The close relationship we discover between these two parameterizations also allows us to apply spectral clustering based on MDS to partition the mesh into charts having low stretch. We also novelly apply the graph cut algorithm in optimizing chart boundaries to further minimize stretch, follow sharp features, and avoid meandering. Overall, our algorithm creates texture atlases quickly, with fewer charts and lower stretch than previous methods, providing improvement in applications like geometric remeshing. We also describe an extension, signal-specialized atlas creation, to efficiently sample surface signals, and show for the first time that considering signal stretch in chart formation produces better texture maps.
Parametric Graph-Based Separable Transforms For Video Coding (2020)

In many video coding systems, separable transforms (such as two-dimensional DCT-2) have been used to code block residual signals obtained after prediction. This paper proposes a parametric approach to build graph-based separable transforms (GBSTs) for video coding. Specifically, a GBST is derived from a pair of line graphs, whose weights are determined based on two non-negative parameters. As certain choices of those parameters correspond to the discrete sine and cosine transform types used in recent video coding standards (including DCT-2, DST-7 and DCT-8), this paper further optimizes these graph parameters to better capture residual block statistics and improve video coding efficiency. The proposed GBSTs are tested on the Versatile Video Coding (VVC) reference software, and the experimental results show that about 0.4% average coding gain is achieved over the existing set of separable transforms constructed based on DCT-2, DST-7 and DCT-8 in VVC.
EspA, a protein secreted by enteropathogenic <i>Escherichia coli</i>, is required to induce signals in epithelial cells (1996)

Enteropathogenic Escherichia coli (EPEC) is a leading cause of infant diarrhoea. EPEC mediates several effects on host epithelial cells, including activation of signal-transduction pathways, cytoskeletal rearrangement along with pedestal and attaching/effacing lesion formation. It has been previously shown that the EPEC eaeB (espB) gene encodes a secreted protein required for signal transduction and adherence, while eaeA encodes intimin, an EPEC membrane protein that mediates intimate adherence and contributes to focusing of cytoskeletal proteins beneath bacteria. DNA-sequence analysis of a region between eaeA and eaeB identified a predicted open reading frame (espA) that matched the amino-terminal sequence of a 25 kDa EPEC secreted protein. A mutant with a non-polar insertion in espA does not secrete this protein, activate epithelial cell signal transduction or cause cytoskeletal rearrangement. These phenotypes were complemented by a cloned espA gene. The espA mutant is also defective for invasion. It is concluded that espA encodes an EPEC secreted protein that is necessary for activating epithelial signal transduction, intimate contact, and formation of attaching and effacing lesions, processes which are central to pathogenesis.
Heat‐Induced Fragmentation of the Maize Waxy Protein During Protein Extraction from Starch Granules (1998)

ABSTRACT The starch granule of maize contains a characteristic set of tightly bound polypeptides. Granule‐associated polypeptides are typically extracted from starch granules by heating starch granule suspensions at 90–100°C in a detergent such as SDS. Solubilized proteins are recovered by centrifugation and analyzed by gel electrophoresis. Previously identified tightly bound granule intrinsic proteins consist of the 85‐kDa starch‐branching enzyme IIb, the 76‐kDa starch synthase I, and the 60‐kD waxy (Wx) protein, also known as granule‐bound starch synthase I. However, SDS extracts from starch granules of maize also contain a cluster of proteins ranging in mass between 47 and 32 kDa In this study, we analyzed this group of granule‐associated proteins and found that each was recognized by the Wx antibody. A 15 amino acid N‐terminal sequence from the 47‐kDa polypeptide was identical to the predicted N‐terminus of the Wx protein. Further analysis revealed that each immunoreactive polypeptide between 47 and 32 kDa was a heat‐induced fragmentation product of the Wx protein. Conditions for the extraction of granule proteins were evaluated. Our results demonstrate that granule proteins are effectively released by mild extraction (10‐min incubation at 72°C). Relative to the Wx protein, starch synthase I and starch branching enzyme IIb were less susceptible to thermal fragmentation. These results demonstrate that the 85‐, 76‐, and 60‐kDa polypeptides are authentic granule‐intrinsic proteins, and that the majority of polypeptides between 47 and 32 kDa are artifacts of high‐temperature granule extraction procedures.
A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame (2020)

Simultaneous localization and mapping is an indispensable yet challenging direction for mobile robots. Attracted by 3D LiDAR with accurate depth information and robustness to illumination variations, many 3D LiDAR SLAM methods based on scan-to-map matching have been developed. However, there is a critical issue of existing approaches, where a large and dense map is generally required to achieve satisfactory localization accuracy, leading to low efficiency of scan-to-map matching. To solve this problem, in this letter, we propose a novel 3D LiDAR SLAM based on directed geometry point (DGP) and sparse frame. The former is used to provide a sparse distribution of points in the spatial dimension and the latter gives rise to a sparse distribution of frames in the temporal sequence. The sparsity of points and frames impove the efficiency of 3D LiDAR SLAM, and the strict data association based on directed geometric points also brings in good accuracy of pose estimation. To compensate the accuracy loss of the localization and mapping caused by frame sparsity, point propagation is proposed to improve the quality of directed geometric points in the map and the accuracy of scan-to-map matching. Also, loop detection and pose graph optimization are conducted for global consistency. The experimental results demonstrate the effectiveness of the proposed method in terms of accuracy and efficiency.
Low-temperature grown graphene films by using molecular beam epitaxy (2012)

Complete graphene film is prepared by depositing carbon atoms directly on Cu foils in a molecular beam epitaxy chamber at 300 °C. The Raman spectrum of the film has indicated that high-quality few-layer graphene is obtained. With back-gated transistor architecture, the characteristic current modulation of graphene transistors is observed. Following the similar growth procedure, graphitization is observed at room temperature, which is consistent with the molecular dynamics simulations of graphene growth.
textTOvec: Deep Contextualized Neural Autoregressive Topic Models of\n Language with Distributed Compositional Prior (2018)

We address two challenges of probabilistic topic modelling in order to better\nestimate the probability of a word in a given context, i.e., P(word|context):\n(1) No Language Structure in Context: Probabilistic topic models ignore word\norder by summarizing a given context as a "bag-of-word" and consequently the\nsemantics of words in the context is lost. The LSTM-LM learns a vector-space\nrepresentation of each word by accounting for word order in local collocation\npatterns and models complex characteristics of language (e.g., syntax and\nsemantics), while the TM simultaneously learns a latent representation from the\nentire document and discovers the underlying thematic structure. We unite two\ncomplementary paradigms of learning the meaning of word occurrences by\ncombining a TM (e.g., DocNADE) and a LM in a unified probabilistic framework,\nnamed as ctx-DocNADE. (2) Limited Context and/or Smaller training corpus of\ndocuments: In settings with a small number of word occurrences (i.e., lack of\ncontext) in short text or data sparsity in a corpus of few documents, the\napplication of TMs is challenging. We address this challenge by incorporating\nexternal knowledge into neural autoregressive topic models via a language\nmodelling approach: we use word embeddings as input of a LSTM-LM with the aim\nto improve the word-topic mapping on a smaller and/or short-text corpus. The\nproposed DocNADE extension is named as ctx-DocNADEe.\n We present novel neural autoregressive topic model variants coupled with\nneural LMs and embeddings priors that consistently outperform state-of-the-art\ngenerative TMs in terms of generalization (perplexity), interpretability (topic\ncoherence) and applicability (retrieval and classification) over 6 long-text\nand 8 short-text datasets from diverse domains.\n
Closed-form quality measures for compressed medical images: compression noise statistics of transform coding (2004)

This paper provides a theoretical foundation for the closed-form expression of model observers on compressed images. In medical applications, model observers, especially the channelized Hotelling observer, have been successfully used to predict human observer performance and to evaluate image quality for detection tasks in various backgrounds. To use model observers, however, requires knowledge of noise statistics. This paper first identifies quantization noise as the sole distortion source in transform coding, one of the most commonly used methods for image compression. Then, it represents transform coding as a 1-D block-based matrix expression, it further derives first and second moments, and the probability density function (pdf) of the compression noise at pixel, block and image levels. The compression noise statistics depend on the transform matrix and the quantization matrix in the transform coding algorithm. Compression noise is jointly normally distributed when the dimension of the transform (the block size) is typical and the contents of image sets vary randomly. Moreover, this paper uses JPEG as a test example to verify the derived statistics. The test simulation results show that the closed-form expression of JPEG quantization and compression noise statistics correctly predicts the estimated ones from actual images.
A high frequency, low volume, point-of-load power supply for distributed power systems (1987)

A resonant version of the dc-dc forward converter is presented in this paper. It is a topology capable of operation in the 10 MHz range, and it can be used for very low volume, point-of-load conversion in distributed power systems. In comparison to other resonant topologies, this converter takes advantage of a very low transformer leakage inductance to achieve zero-voltage switching of all its power semiconductor devices. Its resonant ring is also independent of load current. A 50 watt prototype operating at 3.6 MHz and a discussion of the component work necessary to reach 10 MHz are presented.
Fast image retrieval based on K-means clustering and multiresolution data structure for large image databases (2000)

This paper presents a fast search algorithm based on multi- resolution data structure for efficient image retrieval in large image databases. The proposed algorithm consists of two stages: a database-building stage and a searching stage. In the database-building stage, we partition the image data set into a pre-defined number of clusters by using the MacQueen K-means clustering algorithm. The searching stage has the two steps to choose proper clusters and to find the best match among all the images included in the chosen clusters. In order to reduce the heavy computational cost in the searching stage, we proposed two kinds of fast exhaustive searching algorithms based on the multi- resolution feature space, which guarantee a perfect retrieval accuracy of 100%. By applying these two algorithms to the searching stage, we can find the best match with very high search speed and accuracy. In addition, we consider a retrieval scheme producing multiple output images including the best match. Intensive simulation results show that the proposed schemes provide a prospective search performance.
Terahertz quantum cascade laser based on LO-phonon-scattering assisted depopulation (2003)

We report the development of a quantum cascade laser at the longest wavelength to date, /spl lambda/=87.2 m (3.44 THz), that uses longitudinal-optical phonon scattering for electron depopulation. Operating in pulsed mode, lasing is obtained up to sixty-four Kelvin.
Sensitivity map computation in adaptive electrical capacitance volume tomography with multielectrode excitations (2015)

Electrical capacitance tomography (ECT) is a low‐cost, high‐speed imaging technique useful in many industrial settings. ECT is predicated on the knowledge of sensitivity maps between capacitance electrodes that blanket the imaging domain. The simultaneous activation of multiple electrodes can be advantageous to manipulate the resulting field distributions and capture additional spatial information for imaging purposes. However, conventional methods for sensitivity map computation in ECT are not adequate in the presence of multielectrode activation because the mutual coupling between electrodes is not properly accounted for. This coupling becomes especially critical in adaptive electrical capacitance volume tomography (AECVT) sensors, where signals from many small electrode segments are combined into synthetic electrodes. A more general approach is presented for sensitivity map computation in AECVT based on the actual posteriori (induced) charge distributions rather than the conventional approach based on boundary conditions with no account for electrode interactions.
Batch polymerization of methyl methacrylate in mini/macroemulsions (1993)

Abstract The kinetics of the isothermal batch macroemulsion and miniemulsion polymerizations of methyl methacrylate (MMA) at 50°C have been studied. Hexadecane was used as the cosurfactant or swelling agent. The nucleation mechanisms were observed to be different between macroemulsions and miniemulsions. The effect of surfactant, cosurfactant, initiator, shear, and hold time on droplet nucleation was studied. The miniemulsion particles were found to contain more radicals on average than the macroemulsion particles using certain recipes. This resulted in higher polymerization rates for the miniemulsions at identical particle numbers. The latex‐particle‐size distributions were similar even though the mini‐emulsion droplets start out with a high polydispersity of around 1.5. Miniemulsion latexes were found to be more stable under shear. Conductance of emulsions during polymerization was found to be a valuable on‐line tool for investigating particle nucleation and growth. © 1993 John Wiley & Sons, Inc.