gebhart/patrepeval huggingface dataset:
Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding (2018)

Learning to estimate 3D geometry in a single frame and optical flow from consecutive frames by watching unlabeled videos via deep convolutional network has made significant progress recently. Current state-of-the-art (SoTA) methods treat the two tasks independently. One typical assumption of the existing depth estimation methods is that the scenes contain no independent moving objects. while object moving could be easily modeled using optical flow. In this paper, we propose to address the two tasks as a whole, i.e. to jointly understand per-pixel 3D geometry and motion. This eliminates the need of static scene assumption and enforces the inherent geometrical consistency during the learning process, yielding significantly improved results for both tasks. We call our method as "Every Pixel Counts++" or "EPC++". Specifically, during training, given two consecutive frames from a video, we adopt three parallel networks to predict the camera motion (MotionNet), dense depth map (DepthNet), and per-pixel optical flow between two frames (OptFlowNet) respectively. The three types of information are fed into a holistic 3D motion parser (HMP), and per-pixel 3D motion of both rigid background and moving objects are disentangled and recovered. Comprehensive experiments were conducted on datasets with different scenes, including driving scenario (KITTI 2012 and KITTI 2015 datasets), mixed outdoor/indoor scenes (Make3D) and synthetic animation (MPI Sintel dataset). Performance on the five tasks of depth estimation, optical flow estimation, odometry, moving object segmentation and scene flow estimation shows that our approach outperforms other SoTA methods. Code will be available at: https://github.com/chenxuluo/EPC.
AuGEAS (2002)

When searching for content in in a large heterogeneous document collections like the World Wide Web it is not easy to know which documents provide reliable authoritative information about a subject. The problem is particularly pointed as it concerns content search for "high-value" informational needs such as retrieving medical information, where the cost of error may be high. In this paper, a method is described for estimating the authoritativeness of a document based on textual, non-topical cues. This method is complementary to estimates of authoritativeness based on link structure, such as the PageRank and HITS algorithms. This method is particularly suited to "high-value" content search where the user is interested in searching for information about a specific topic. A method for combining textual estimates of authoritativeness with link analysis is also presented. The types of textual cues to authoritativeness that are easily computed and utilized by our method are described, as well as the method used to select a subset of cues to increase the computation speed. Methods for applying authoritativeness estimates to re-ranking documents returned from search engines, combining textual authoritativeness with social authority, and use in query expansion are also presented. By combining textual authority with link analysis, a more complete and robust estimate can be made of a document's authoritativeness.
Context Memory Networks for Multi-Objective Semantic Parsing in Conversational Understanding (2016)

The end-to-end multi-domain and multi-task learning of the full semantic frame of user utterances (i.e., domain and intent classes and slots in utterances) have recently emerged as a new paradigm in spoken language understanding. An advantage of the joint optimization of these semantic frames is that the data and feature representations learnt by the model are shared across different tasks (e.g., domain/intent classification and slot filling tasks use the same feature sets). It’s important that the model should learn to pay attention to global and local aspects of the utterances while learning to map the entire utterance to an intent class and tag each word with a slot tag. We introduce the Context Memory Network (CMN), a neural network architecture which specifically focuses on learning better representations as attention vectors from past memory to be reasoned with for the end task of jointly learning the intent class and slot tags. The utterances trigger a dynamic memory network, which learns attention based representation for each word by allowing the model to condition on the list of related phrases in the form of memory networks. These representations are then provided to a new multi-objective long short term memory network (LSTM) to infer the intent class and slot tags. Our empirical investigations on CMN show impressive gains over the end-to-end LSTM baselines on ATIS dataset as well as two other humanto- machine conversational datasets.
Mobility label based network: Support for mobility using MPLS and Multi-Protocol BGP (2008)

To support mobility the network control plane is required to detect changes in the mobile node's location and distribute the new location information thus enabling the forwarding plane to deliver traffic in an optimal manner. This paper introduces a new mobility management protocol for mobile node registrations and movement handling based on the MPLS architecture and new elements in MP-BGP to achieve Mobility Label distribution at the network control plane and the optimal packet delivery by the network forwarding plane. This approach does not rely on Mobile IP and results in the elimination of triangular routing and the associated user facing performance penalties.
GENETIC ADDICTION RISK SCORE (GARS) ANALYSIS: EXPLORATORY DEVELOPMENT OF POLYMORPHIC RISK ALLELES IN POLY-DRUG ADDICTED MALES (2010)

There is a need to classify patients at genetic risk for drug seeking behavior prior to or upon entry to residential and or non-residential chemical dependency programs. We have determined based on a literature review, that there are seven risk alleles associated with six candidate genes that were studied in this patient population of recovering poly-drug abusers. To determine risk severity of these 26 patients we calculated the percentage of prevalence of the risk alleles and provided a severity score based on percentage of these alleles. Subjects carry the following risk alleles: DRD2=A1; SLC6A3 (DAT) =10R; DRD4=3R or 7R; 5HTTlRP = L or LA; MAO= 3R; and COMT=G. As depicted in table 2 low severity (LS) = 1-36%; Moderate Severity =37-50%, and High severity = 51100%. We studied two distinct ethnic populations group 1 consisted of 16 male Caucasian psycho stimulant addicts and group 2 consisted of 10 Chinese heroin addicted males. Based on this model the 16 subjects tested have at least one risk allele or 100%. Out of the 16 subjects we found 50% (8) HS; 31% (5) MS; and 19% LS (3 subjects). These scores are then converted to a fraction and then represented as a Genetic Addiction Risk Score (GARS) whereby we found the average GARS to be: 0.28 low severity, 0.44 moderate severity and 0.58 high severity respectively. Therefore, using this GARS we found that 81% of the patients were at moderate to high risk for addictive behavior. Of particular interest we found that 56% of the subjects carried the DRD2 A1 allele (9/16). Out of the 9 Chinese heroin addicts [one patient not genotyped] (group 2) we found 11% (1) HS; 56% (5) MS; and 33% LS (3 subjects). These scores are then converted to a fraction and then represented as GARS whereby we found the average GARS to be: 0.28 Low Severity; 0.43 moderate severity and 0.54 high severity respectively. Therefore, using GARS we found that 67% of the patients were at moderate to high risk for addictive behavior. Of particular interest we found that 56% of the subjects carried the DRD2 A1 allele (5/9) similar to group 1. Statistical analysis revealed that the groups did not differ in
SU‐FF‐T‐175: Dose Rate Optimization for Intensity‐Modulated Arc Therapy (2006)

Purpose: We use multiple dynamic arcs with different MLC shapes at different gantry angles for Intensity‐modulated arc therapy (IMAT). This study is to develop a fast and simple algorithm to optimize the dose rate as a function of gantry angle for IMAT for linear accelerators with dose rate variation capability for a dynamic arc. Method and Materials: The dose rate as a function of gantry angle for a dynamic arc is expressed by an analytical expression that favors beam directions with lower dose deposited to critical structures and higher dose deposited to the target volume. Three parameters are included in the analytical expression for further optimization of the dose rate base on an objective function. The optimized plan is transferred to a forward treatment planning system for final dose calculation. The method is applied to a phantom and a few clinical cases using 6 MV and 18 MV beams for a Varian linear accelerator. Results: The method has been demonstrated with a test phantom and a few clinical radiotherapy cases. We have showed that dose distributions and dose volume histograms have been improved with the dose rate optimization for IMAT. It gives more uniform dose to the target volume and lower dose to the critical structure. Conclusions: We have developed a fast and simple technique to optimize the dose rate as a function of gantry angle for intensity‐modulated arc therapy, while retaining its advantages of an intuitive treatment planning process and efficient radiation delivery.
Pleochroic dyes with high order parameters (1978)

The construction and performance of liquid crystal displays using the guest-host-interaction in conjunction with the cholesteric to nematic phase-change effect have been reported by White and Taylor (1974). Results are reported which extend this information and define new areas for investigation. Over 50 dichroic (pleochroic) azo-dyes have been prepared and their suitability for use in this type of display evaluated. Synthetic schemes for the preparation of these dyes are referred to briefly. Various aspects of the construction of this type of display have also been investigated with a view to optimising its appearance.
Enhanced polymeric lithography resists via sequential infiltration synthesis (2011)

Etch resistance of two commonly used lithography resists is increased significantly by sequential infiltration synthesis (SIS). Exposing films to trimethyl-aluminum and water with long dosage times infiltrates the bulk of the film with alumina, which renders them dramatically more resistant to plasma etching with no degradation to the patterns. Enhanced etch resistance eliminates the need for an intermediate hard mask and the concomitant costs and pattern fidelity losses. Moreover, by allowing for thinner resist films, this approach can improve the final pattern resolution.
Coxofemoral joint laxity from distraction radiography and its contemporaneous and prospective correlation with laxity, subjective score, and evidence of degenerative joint disease from conventional hip-extended radiography in dogs (1993)

A 3-year prospective study of large-breed dogs (4 months to 3 years of age) was conducted to evaluate the influence of radiographic positioning and age on coxofemoral joint (hip) laxity, subjective hip score, and development of degenerative joint disease (DJD). The dogs (n = 142) were breeder- or client-owned and represented 14 breeds. With dogs under heavy sedation, hips were radiographed in the standard hip-extended position and in the new compression/distraction position at 4, 6, 12, 24, and 36 months of age. The standard hip-extended radiographic view was evaluated by 3 methods: subjective evaluation by a board-certified veterinary radiologist (WHR), according to the standard 7-point Orthopedic Foundation for Animals (OFA) scoring scheme (OFA/WHR); joint laxity quantitation, using the Norberg angle (NA) method; and subjective scoring by a veterinary orthopedic surgeon for radiographic evidence of DJD. The hips in the distraction radiographic view were evaluated for passive hip laxity, as measured by use of a unitless distraction index (DI). Results of the study indicated that at a specific age (4, 6, 12, 24, or 36 months), all methods of hip evaluation correlated with each other at a moderate level (P < 0.05). The strength of contemporaneous correlation tended to increase with age of evaluation. Longitudinally, the between-method correlations were usually significant (P < 0.05), but not at a sufficiently high level to permit reliable between-method prediction. Prospective intraclass (within-method) statistical analysis of the various hip-scoring methods indicated that DI was superior to NA and OFA/WHR in comparability of score over time. The intraclass correlation coefficient ranged from 0.55 to 0.91 for DI in contrast to 0.40 to 0.78 for NA, and 0.06 to 0.39 for OFA/WHR over the age intervals of the study. For reference, the highest Kappa of 0.39 for the subjective OFA/WHR scoring reflected a maximal level of agreement between time intervals, only slightly better than chance. The associated large error questions the predictive use of the 7-point, subjective hip-scoring scheme, particularly prior to the age of 2 years.
A Multi-dimensional Progressive Perfect Hashing for High-Speed String Matching (2011)

Aho-Corasick (AC) automaton is widely used for multi-string matching in today's Network Intrusion Detection System (NIDS). With fast-growing rule sets, implementing AC automaton with a small memory without sacrificing its performance has remained challenging in NIDS design. In this paper, we propose a multi-dimensional progressive perfect hashing algorithm named P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -Hashing, which allows transitions of an AC automaton to be placed in a compact hash table without any collision. P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -Hashing is based on the observation that a hash key of each transition consists of two dimensions, namely a source state ID and an input character. When placing a transition in a hash table and causing a collision, we can change the value of a dimension of the hash key to rehash the transition to a new location of the hash table. For a given AC automaton, P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -Hashing first divides all the transitions into many small sets based on the two-dimensional values of the hash keys, and then places the sets of transitions progressively into the hash table until all are placed. Hash collisions that occurred during the insertion of a transition will only affect the transitions in the same set. The proposed P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -Hashing has many unique properties, including fast hash index generation and zero memory overhead, which are very suitable for the AC automaton operation. The feasibility and performance of P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -Hashing are investigated through simulations on the full Snort (6.4k rules) and Clam AV (54k rules) rule sets, each of which is first converted to a single AC automaton. Simulation results show that P <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -Hashing can successfully construct the perfect hash table even when the load factor of the hash table is as high as 0.91.
New bioactive, degradable composite microspheres as tissue engineering substrates (2000)

Novel bioactive, degradable polymer/glass/ceramic composite microspheres were developed using a solid-in-oil-in-water (s/o/w) emulsion solvent removal method. Modified bioactive glass (MBG) powders were encapsulated into the polylactic acid (PLA) matrix. Scanning electron microscopy and energy-dispersive X-ray analyses revealed that the MBG powders were mostly embedded in the polymer matrix, and submicron-size pores were present at the surface. Immersion in simulated physiological fluid (SPF) was used to evaluate the surface reactivity of the microspheres. The polymeric surface was fully transformed into carbonated calcium hydroxyapatite (c-HA) after 3 weeks of immersion. In contrast, PLA microspheres showed no evidence of any calcium phosphate deposition. Ion concentration analyses revealed a decrease in Ca and P concentrations and an increase in Si concentration in the SPF immersed with composite microspheres during the 3-week period. The Ca and P uptake rates decreased after 2 days of incubation. This coincided with the decrease of the Si release rate. These data lend support to the suggestion that the Si released from the MBG powders present in the polymer matrix is involved in the formation of the Ca-P layer. Our results support the concept that these new bioactive, degradable composite microspheres may serve as microcarriers for synthesis of bone and other tissues in vitro and in vivo.
METHOD FOR ULTRASONIC FLOW VECTOR MEASUREMENT (1993)

A new method (Ultrasonic Computed Velocimetry) to measure complete vector components of flow velocity is proposed. Using this method, it is possible to measure both of the flow velocity components along and transverse to the beam axis. This method is able to simultaneously measure the signs andmagnitude of the flow velocity components. Reflected ultrasound waves are used togetherwith fully linear signal processing procedures. The first step of the method is Fourier transformation of the received signals in the direction of the transducer array. The second step is also a Fourier transformation but in the polar axis directions. These two steps provide the two velocity compoments along and transverse to the beam axis. Detailed procedure and result of numerical simulation are presented.
A recursive algorithm for pruned bit-reversal permutations (2012)

A fast recursive algorithm for pruned bit-reversal permutations is proposed. The algorithm is based on a computationally efficient scheme for evaluating a novel permutation statistic called permutation inliers that counts inlier addresses under pruning. This statistic is computed by evaluating a recursion using integer shift and add operations in logarithmic time complexity. Moreover, a parallel pruned interleaving algorithm based on computing multiple inliers in parallel is proposed. The advantages of the proposed algorithm are reduced latency and reduced memory requirements, which are describe in many signal processing and communication applications.
A two-dimensional scalable crossbar matrix switch architecture (2004)

Rapid growth of Internet traffic causes a new challenge in the design of high-speed switches. One of main design issues for high-speed switches is a scalability problem. This paper proposes a scalable crossbar matrix (SCM) switch architecture, which consists of multiple crossbar switch units (XSU) with virtual output queues (VOQs) at the inputs and single-cell scheduling decomposition buffers (SDBs) at the outputs. We propose a distributed scheduling algorithm for the proposed scalable crossbar switch architecture, which consists of a credit based SLIP (C-SLIP) scheduling for crossbar switch units and backlog weighted round robin (BWRR) scheduling for switching fabric output ports. In this paper, we show that large-scale switch fabric can be built up by small-size crossbar switch units with improved delay performance and enough arbitration time margins. The simulation results show that the proposed switch architecture and distributed scheduling algorithm can provide 100% throughput under i.i.d. uniform traffic with a single iteration arbitration in a time slot.
Transcriptional changes associated with breast cancer occur as normal human mammary epithelial cells overcome senescence barriers and become immortalized (2007)

Gene expression profiles and cytological changes in related transcriptional regulators indicate that immortalized HMEC resemble non-invasive breast cancers, such as ductal and lobular carcinomas in situ, and are strikingly distinct from finite-lifespan HMEC, particularly with regard to genes involved in proliferation, cell cycle regulation, chromosome structure and the DNA damage response. The comparison of HMEC profiles with lines harboring oncogenic changes (e.g. overexpression of Her-2neu, loss of p53 expression) identifies genes involved in tissue remodeling as well as proinflamatory cytokines and S100 proteins. Studies on carcinogenesis using immortalized cell lines as starting points or "normal" controls need to account for the significant pre-existing genetic and epigenetic changes inherent in such lines before results can be broadly interpreted.
Efficient algorithms for computation of the loss curve of video sources (2003)

The loss curve of a video source characterizes the loss rate of the video stream generated by the source as a function of the allocated buffer size for a given transmission rate. The loss curve is useful in the optimal allocation of resources when the video stream is transmitted over a packet network, so that the desired tradeoff can be reached among the loss rate, bandwidth and the buffer space to be allocated in the network. We present an algorithm for computation of the entire loss curve of an elementary video stream. In contrast to earlier algorithms which employ statistical approaches, our algorithm is deterministic and computes the exact loss curve of the video stream. The algorithm exploits the piecewise linearity of the loss curve and computes only the points at which the slope of the loss curve changes. We also present an extension of the algorithm to MPEG-2 transport streams. The efficiency of the algorithm is demonstrated by results from several example video streams. For example, the algorithm was able to compute the entire loss curve of a 2-h elementary video stream in approximately 11 s on a Sun Ultra-2 workstation.
iSTAPLE: improved label fusion for segmentation by combining STAPLE with image intensity (2013)

Multi-atlas based methods have been a trend for robust and automated image segmentation. In general these methods first transfer prior manual segmentations, i.e., label maps, on a set of atlases to a given target image through image registration. These multiple label maps are then fused together to produce segmentations of the target image through voting strategy or statistical fusing, e.g., STAPLE. STAPLE simultaneously estimates the true segmentation and the label map performance level, but has been shown inaccurate for multi-atlas segmentation because it is determined completely on the propagated label maps without considering the target image intensity. We develop a new method, called iSTAPLE, that combines target image intensity into a similar maximum likelihood estimate (MLE) framework as in STAPLE to take advantage of both intensity-based segmentation and statistical label fusion based on atlas consensus and performance level. The MLE framework is then solved using a modified EM algorithm to simultaneously estimate the intensity profiles of structures of interest as well as the true segmentation and atlas performance level. Unlike other methods, iSTAPLE does not require the target image to have same image contrast and intensity range as the atlas images, which greatly extends the use of atlases. Experiments on whole brain segmentation showed that iSTAPLE performed consistently better than STAPLE.