Miracle-dz/UniFAR-FTUs huggingface dataset:
Two Samples are Enough: Opportunistic Flow-level Latency Estimation using NetFlow

The inherent support in routers (SNMP counters or NetFlow) is not sufficient to diagnose performance problems in IP networks, especially for flow-specific problems and hence, the aggregate behavior within a router appears normal. To address this problem, in this paper, we propose a Consistent NetFlow (CNF) architecture for measuring per-flow performance measurements within routers. CNF utilizes NetFlow architecture that already reports the first and last timestamps per-flow, and hash-based sampling for ensuring that two routers record same flows. We devise a novel Multiflow estimator that approximates the intermediate delay samples from other background flows to improve the per-flow latency estimates significantly compared to the naive estimator that only uses actual flow samples. In our experiments using real backbone traces and realistic delay models, we show that Multiflow estimator is accurate with a median relative error of less than 20% for flows of size greater than 100 packets. We also show that prior approach based on trajectory sampling performs about 2-3x worse.
Synthesis of Regular Logic Bricks for Robust IC Design

With scaling of CMOS technologies to 65nm and below, IC designs are suffering from decreasing yield, increasing variations, and escalating design and manufacturing costs. Regularity in IC design has been recognized as an effective means to combat variability in nanoscale technologies [1]. One methodology to enforce design regularity that produces RET(Resolution Enhancement Technique)-friendly designs is to implement ICs using a small library of regular logic bricks [2]. A regular logic brick is a physical implementation of logic function(s) created from a small set of logic primitives that are mapped onto a regular layout fabric. In this project, we propose a methodology for the design and synthesis of such logic bricks. Since logic bricks are comprised of a limited set of logic primitives for manufacturability reasons, we propose a primitive-based direct mapping approach for generating optimized bricks that, in contrast to classical synthesis approaches, can provide direct control of implementation structures at abstract functional level based on the detection of natural decompositions that exist in the function.
The Broken “Ring of Fire”: A New Radiological Sign as Predictor of Syndesmosis Injury?

Background: Subcircumferential periosteal edema above the ankle joint is frequently present on magnetic resonance imaging (MRI) with syndesmosis injuries but has not been previously reported. Fluid height within the interosseous membrane also has not previously been shown to be associated with syndesmosis injury severity. Purpose: To investigate whether a new sign on MRI and measurement of the length of fluid within the interosseous membrane above the ankle may be used to enable identification of a syndesmosis injury and allow differentiation from lateral ligament injury. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: Three groups of patients (those with an isolated syndesmosis injury [SI group], isolated lateral ligament injury [LLI group], and no injury [NI group]) who had an ankle MRI for another reason were identified from a patient notes database and the MRI scans retrieved. The scans were anonymized and independently assessed by 8 clinicians (surgeons and radiologists) who were blinded to the diagnosis. The maximum length of fluid above the ankle within the intraosseous membrane was measured for each patient. The presence or absence of distal anterior, lateral, and posterior tibial periosteal edema was recorded (broken “ring of fire”). Results: Measurement of the length of fluid above the ankle had excellent intraobserver reliability (intraclass correlation coefficient, 0.97; 95% CI, 0.93-0.99) but poor interobserver reliability. Fluid extended higher in both the LLI group (P = .0043) and SI group (P = .0058) than the NI group, but there was no significant difference between the LLI and SI groups (P = .3735), indicating that this measurement cannot differentiate between the injuries. The presence of the broken “ring of fire” around the distal tibia was significantly more frequent in the SI group when compared with both LLI and NI groups (P < .00001). The sensitivity of this sign is 49%, but when present, this sign has a 98% specificity for syndesmosis injury. Conclusion: The presence of tibial subcircumferential periosteal edema 4 to 6 cm above the ankle joint (the “ring of fire”) is highly suggestive of a syndesmosis injury. This new radiological sign can assist with early identification of such injuries. The measurement of height of fluid above the ankle within the interosseous membrane is variable and cannot differentiate severe ankle sprains from high ankle sprains involving the syndesmosis.
DSpot: Test Amplification for Automatic Assessment of Computational Diversity

In this work, we characterize a new form of software diver- sity: the existence of a set of variants that (i) all share the same API, (ii) all behave the same according to an input- output based specification and (iii) exhibit observable dif- ferences when they run outside the specified input space. We quantify computational diversity as the dissimilarity be- tween execution traces on inputs that are outside the speci- fied domain. Our technique relies on test amplification. We propose source code transformations on test cases to explore the input domain and systematically sense the observation domain. We run our experiments on 472 variants of 7 classes from open-source, large and thoroughly tested Java classes. Our test amplification multiplies by ten the number of input points in the test suite and is effective at detecting software diversity.
The Impact of AlN Spacer on Forward Gate Current and Stress-Induced Leakage Current (SILC) of GaN HEMT

A typical GaN HEMT forward gate current can be described by a simplified model, i.e., a Schottky diode with a parasitic resistance. This model, though, fails to fit certain GaN HEMT devices, noticeably those with AlN spacer. The Tsu-Esaki tunneling model with transfer matrix approach was used to investigate this phenomenon. The result shows that the forward gate current at low Vg is limited by Schottky interface as expected. At higher Vg, the AlN/GaN interface barrier gradually becomes dominant in deciding the gate current. This observation also reveals a discrepancy between measured and calculated gate current with an AlN spacer. Stress-induced leakage current (SILC) of this device type is investigated and the leakage current can be assigned to failure of the Schottky diode and/or the AlN/GaN interface using the back-to-back diode model. This model helps circuit designers to simulate RF performance under gate leakage condition.
The Big Picture The State of Music at LabROSA

Nonnegative matrix factorization (NMF) has been widely used for discovering physically meaningful latent components in audio signals to facilitate source separation. Most of the existing NMF algorithms require that the number of latent components is provided a priori, which is not always possible. In this paper, we leverage developments from the Bayesian nonparametrics and compressive sensing literature to propose a probabilistic Beta Process Sparse NMF (BP-NMF) model, which can automatically infer the proper number of latent components based on the data. Unlike previous models, BP-NMF explicitly assumes that these latent components are often completely silent. We derive a novel mean-field variational inference algorithm for this nonconjugate model and evaluate it on both synthetic data and real recordings on various tasks.
Two Dynamic Discrete Choice Estimation Problems and Simulation Method Solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.
Deriving functional dependencies from the entity-relationship model

FROM THE ENTITV-RELATIONSNIP MODEL he process of database design can be divided into several sta,ges. This four-stage process comprises: l Rquiwments mllpction: In this stage, users are interviewed to obtain descriptions of their information needs. This results in a preliminary specification of needs of all user groups in an organization. l CCVVZ$I~U~~ d&n: A conceptual model of the application is developed using the data collected in the first stage. This model is independent of the databaw management system to be employed. l Lo~@cal &s&n: The conceptual model is translated into a specific model such as the relational, network or hierarchical model. For example, if a relational database management system (DBMS) is to be used, the relations to be implemented are specified. l Physiral d+n: The logical schema from the logical design step is mapped into a storage representation for a DBMS. The appropriate storage structures, indexes, and physical parameters to optimize performance are selected.
Goal Oriented Symbolic Propagation in Bayesian Networks

The paper presents an efficient goal oriented algorithm for symbolic propagation in Bayesian networks. The proposed algorithm performs symbolic propagation using numerical methods. It first takes advantage of the independence relationships among the variables and produce a reduced graph which contains only the relevant nodes and parameters required to compute the desired propagation. Then, the symbolic expression of the solution is obtained by performing numerical propagations associated with specific values of the symbolic parameters. These specific values are called the canonical components. Substantial savings are obtained with this new algorithm. Furthermore, the canonical components allow us to obtain lower and upper bounds for the symbolic expressions resulting from the propagation. An example is used to illustrate the proposed methodology.
Nigma: an Image Retrieval System

The paper presents the functionality of a system which retrieves images on the basis of automatically generated indexes (i.e. semantic image representations, obtained by automatic image analysis, indicating the content of the images). The system consists of two parts: an oo-line indexing part and an on-line image retrieval part. The indexing component is used to automatically generate semantic representations of images so that the image retrieval component can use this information to enable image retrieval. The man-machine communication of the image retrieval component is based on an iconical graphical query language to accomplish geographical query speciication for image access. Experiments have been carried out on three diierent sets of images from the following domains: MRI images of the chest, electronic schemas and topographic maps. The experiments show encouraging results especially for domains which have a high degree of formality in their pictorial expression, such as electronic schemas and topographic maps, and to a less extent for domains having a weak degree of formality such as MRI images of the chest.
Real-time both hands tracking using CAMshift with motion mask and probability reduction by motion prediction

Hand gesture interfaces are more intuitive and convenient than traditional interfaces. They are the most important parts in the relationship between users and devices. Hand tracking for hand gesture interfaces is an active area of research in image processing. However, previous works have limits such as requiring the use of multiple camera or sensor, working only with single color background, etc. This paper proposes a real-time both hands tracking algorithm based on “CAMshift (Continuous Adaptive Mean Shift Algorithm)” using only a single camera in multi-color backgrounds. In order to track hands robustly, the proposed algorithm uses “motion mask” to combine color and movement probability distributions and “probability reduction” for multi-hand tracking in non-limiting environments. Experimental results demonstrate that this algorithm can precisely track both hands of an operator in multi-color backgrounds and process the VGA size input sequences from a web camera in real time (about 25 fps).
MERITS OF A SUBHARMONIC APPROACH TO A SINGLE-PASS , 1 : 5-Å FEL

SLAC/SSRL and collaborators elsewhere are studying the physics of a single-pass, FEL amplifier operating in the 1 2 Å wavelength region based on electron beams from the SLAC linac at 15GeV energy. Hoping to reduce the total wiggler length needed to reach saturation when starting from shot noise, we have examined the benefits of making the first part of the wiggler resonant at a sub-harmonic wavelength ( e.g. 4:5 Å) at which the gain length can be significantly shorter. This leads to bunching of the electron beam at both the subharmonic and fundamental wavelengths, thus providing a strong coherent “seed” for exponential growth of radiation at the fundamental in the second part of the wiggler. Using both multi-harmonic and multi-frequency 2D FEL simulation codes, we have examined the predicted performance of such devices and the sensitivity to electron beam parameters such as current, emittance, and instantaneous energy spread.
Commercially Available Data Mining Tools used in the Economic Environment

This paper presents some of the most common commercially available data mining tools, with their most important features, side by side, and some considerations regarding the evaluation of data mining tools by companies that want to acquire such a system. Among some of the most important factors that a company has to take into account are the amounts of data available, how it is stored and the data mining tasks that must be performed, but there are also others. Not the last it should be mentioned that the cost of a data mining system is important for a company, having a limiting effect on the expansion of the data mining products market towards small companies.
Supply Chain Performance under Market Valuation: An Operational Approach to Restore Efficiency

Based on a supply chain framework, we study the stocking decision of a downstream buyer who receives private demand information and has the incentive to influence her capital market valuation. We first characterize a market equilibrium under a general, single buyback contract. We show that the buyer's stocking decision can be distorted in equilibrium. Such a downstream stocking distortion hurts the buyer firm's own performance, and it also influences the performances of the supplier and the supply chain. We further reveal scenarios where full supply chain efficiency cannot be reached under any single buyback contract. Then, focusing on contract design, we characterize conditions under which a menu of buyback contracts can prevent downstream stocking distortion and restore full efficiency in the supply chain. Our study demonstrates that in a supply chain context, a firm's incentive to undertake real economic activities to influence capital market valuation can potentially be resolved through operational means. This paper was accepted by Yossi Aviv, operations management.
ANALYSIS OF ERROR-RESILIENT VIDEO TRANSMISSION BASED ON SYSTEMATIC SOURCE-CHANNEL CODING

This paper discusses the modeling and analysis of a systematic lossy source channel coding system for errorresilient video transmission. The systematic portion of the transmission consists of a video bitstream transmitted without channel coding over an error-prone channel. Error-resilience is achieved by transmitting a supplementary bitstream generated by Wyner-Ziv encoding of the video signal. The scheme is attractive because it provides gracefully decreasing video quality over a range of symbol error rates, when compared with conventional FEC. We propose a model for the endto-end video distortion delivered by this system. The model considers the encoder’s rate-distortion trade-off, quantization mismatch from Wyner-Ziv coding, previous frame error concealment and error propagation. The model predictions agree closely with experimental results and thereby suggest an optimization algorithm to find the best rate-distortion tradeoff for systematic lossy forward error protection of video waveforms.
Wafer-Scale Millimeter-Wave Phased-Array RFICs

Presents a summary of the millimeter-wave wafer-scale phased array work at UCSD. This concept can drastically reduce the cost of millimeter-wave phased arrays by combining the RFIC blocks, antennas, power distribution and summing, digital control and up and down converters all on the same wafer (or large piece of silicon), and eliminates all RF transitions in and out of the chip, therefore resulting in more efficient systems and lower cost systems. Examples at 90-100 GHz, 108-114 GHz and 400 GHz will be presented in this paper, together with their measured antenna patterns.
Preparation of Bimetallic Pd-Co Nanoparticles on Graphene Support for Use as Methanol Tolerant Oxygen Reduction Electrocatalysts

Graphene-supported (40-x) wt% Pd x wt% Co (0≤x≤13.33) alloys/composites have been prepared by a microwave-assisted polyol reduction method and been investigated for their structural and electrocatalytic properties for the oxygen reduction reaction (ORR) in 0.5 M H2SO4 at 298 K. The study demonstrated that the bimetallic Pd-Co composite nanoparticles are, in fact, alloy nanoparticles with fcc crystalline structure. Partial substitution of Pd by Co (from 3.64 to 13.33 wt%) in 40 wt% Pd/graphene decreases the lattice parameter as well as the crystallite size and increases the apparent catalytic activity, the latter, however, being the greatest with 8 wt% Co. The ORR activity of the active 32 wt% Pd 8wt% Co is found to be considerably low when it was deposited on the support multiwall carbon nanotubes under similar conditions. The rotating disk electrode study indicated that the ORR on 32 wt% Pd 8 wt% Co/GNS in 0.5 M H2SO4 follows approximately the four-electron pathway.
Information Extraction with Character-level Neural Networks and Noisy Supervision

We present an architecture for information extraction from text that augments an existing parser with a character-level neural network. The network is trained using a measure of consistency of extracted data with existing databases as a form of noisy supervision. Our architecture combines the ability of constraint-based information extraction systems to easily incorporate domain knowledge and constraints with the ability of deep neural networks to leverage large amounts of data to learn complex features. Boosting the existing parser's precision, the system led to large improvements over a mature and highly tuned constraint-based production information extraction system used at Bloomberg for financial language text.
A new sharing secret algorithm in stego images with authentication

In the paper, a new sharing secret algorithm in stego images with authentication is presented. The proposed approach employs a novel secret image sharing scheme based on set partitioning in hierarchical trees (SPIHT) algorithm, uses two stego blocks instead of a single block for authentication, and designs the check bits by effectively combining existing authentication ideas with Hamming codes. As a result, it enhances the authentication ability, improves visual quality of the stego images and incorporates an error correction capability of the leading method in the field. Experimental results demonstrate these promising characteristics of this method.
Sequential Monte Carlo samplers for marginal likelihood computation in multiplicative exponential noise models

Model scoring in latent factor models is essential for a broad spectrum of applications such as clustering, change point detection or model order estimation. In a Bayesian setting, model selection is achieved via computation of the marginal likelihood. However, this is a typically challenging task as it involves calculation of a multidimensional integral over all the latent variables. In this paper, we consider approximate computation of the conditional marginal likelihood in a multiplicative exponential noise model, which is the generative model for latent factor models with the Itakura-Saito divergence such as the Nonnegative Matrix Factorization (NMF). We show that standard approaches are not accurate and propose two new methods in the sequential Monte Carlo (SMC) samplers framework. We explore the performances of these estimators on two problems.
THE X-RAY HALO OF CEN X-3

Using two Chandra observations, we have derived estimates of the dust distribution and distance to the eclipsing high-mass X-ray binary Cen X-3 using the energy-resolved dust-scattered X-ray halo. By comparing the observed X-ray halos in 200 eV bands from 2–5 keV to the halo profiles predicted by the Weingartner & Draine interstellar grain model, we find that the vast majority (≈ 70%) of the dust along the line of sight to the system is located within about 300 pc of the Sun, although the halo measurements are insensitive to dust very close to the source. One of the Chandra observations occurred during an egress from eclipse as the pulsar emerged from behind the mass-donating primary. By comparing model halo light curves during this transition to the halo measurements, a source distance of 5.7 ± 1.5 kpc (68% confidence level) is estimated, although we find this result depends on the distribution of dust on very small scales. Nevertheless, this value is marginally inconsistent with the commonly accepted distance to Cen X-3 of 8 kpc. We also find that the energy scaling of the scattering optical depth predicted by the Weingartner & Draine interstellar grain model does not accurately represent the results determined by X-ray halo studies of Cen X-3. Relative to the model, there appears to be less scattering at low energies or more scattering at high energies in Cen X-3.
Omni font OCR error correction with effect on retrieval

Recent library digitization projects attempt to provide large collections of printed material from varying sources in a searchable format. The scanned documents are typically processed using Optical Character Recognition (OCR), which typically introduces errors in the text. This paper proposes a technique for correction of OCR degraded text that is independent of character-level OCR errors, and hence independent of scanned document source. It is based on language modeling in conjunction with a uniform character model that uses edit distance only. The technique compares well to state-of-the-art correction techniques that are based on language modeling and source-specific character error models. Although the proposed technique yielded lower correction effectiveness, its impact on retrieval effectiveness is statistically significant and at par with state-of-the-art correction techniques. The main requirement of the proposed technique is the training of a “good” language model matching genre, style, and temporal coverage. The advantage of being independent of character level errors is clear in applications were printed documents vary in source, font, and degradation level.
Fuzzy Compensation Support Vector Classification for Direction of Arrival Estimation

This paper presents a new direction of arrival (DOA) estimation method based on a multi-class implementation of fuzzy compensation support vector machine (SVM). The proposed method can achieve higher accurate estimates for DOA while avoiding the all-direction peak value searching technique used in other traditional DOA estimation methods. Meanwhile, compared with other SVM-based DOA estimation, like LS-SVM algorithm, this approach reduces the training and testing time and performs better with larger data, so is easier to implement in real-time applications. Computer simulation results show the effectiveness of the proposed method.