Miracle-dz/UniFAR-FTUs huggingface dataset:
Series active filter based resonance damping of high power three-phase, LCL filtered, grid connected voltage source inverters

A series active filter (SAF) based method for the damping of resonant harmonics created by the LCL-filter of the grid connected PWM-VSI is proposed. Oscillations in multi-megawatt rated high power inverters with LCL-filters are damped with resistors which create undesired power losses typically up to 1% of the rated power of the system. The method stated in this paper overcomes the stability/oscillation problem while providing a solution to the resistive power loss. The proposed SAF compensated system performs satisfactorily under rated load conditions and the transition from passive damping to SAF is flawless. Adaptability of the proposed method to dynamic loads is also advantageous as opposed to passive damping methods. Simplified circuit diagrams and schematics are provided through the paper. Mathematical model of the passively damped filter is compared and contrasted with the SAF compensated system. The validity of the proposed method is proven via simulations.
The importance of hippocampal dynamic connectivity in explaining memory function in multiple sclerosis

Brain dynamics (i.e., variable strength of communication between areas), even at the scale of seconds, are thought to underlie complex human behavior, such as learning and memory. In multiple sclerosis (MS), memory problems occur often and have so far only been related to “stationary” brain measures (e.g., atrophy, lesions, activation and stationary (s) functional connectivity (FC) over an entire functional scanning session). However, dynamics in FC (dFC) between the hippocampus and the (neo)cortex may be another important neurobiological substrate of memory impairment in MS that has not yet been explored. Therefore, we investigated hippocampal dFC during a functional (f) magnetic resonance imaging (MRI) episodic memory task and its relationship with verbal and visuospatial memory performance outside the MR scanner.
Word Embedding Evaluation Datasets and Wikipedia Title Embedding for Chinese

Distributed word representations are widely used in many NLP tasks, and there are lots of benchmarks to evaluate word embeddings in English. However there are barely evaluation sets with large enough amount of data for Chinese word embeddings. Therefore, in this paper, we create several evaluation sets for Chinese word embedding on both word similarity task and analogical task via translating some existing popular evaluation sets from English to Chinese. To assess the quality of translated datasets, we obtain human rating from both experts and Amazon Mechanical Turk workers. While translating the datasets, we ﬁnd out that around 30 percents of word pairs in the benchmarks are Wikipedia titles. This motivate us to evaluate the performance of Wikipedia title embeddings on our new benchmarks. Thus, in this paper, not only the new benchmarks are tested but some new improved approaches of Wikipedia title embeddings are proposed. We perform training of embeddings of Wikipedia titles using not only their Wikipedia context but also their Wikipedia categories, most of categories are noun phrases, and we identify the head words of the noun phrases by a parser for further emphasizing their roles on the training of title embeddings. Experimental results and the comprehensive error analysis demonstrate that the benchmarks can precisely reﬂect the approaches’ quality, and the effectiveness of our improved approaches on Wikipedia title embeddings are also veriﬁed and analyzed in detail.
Value of hedge and expected returns

ABSTRACT We demonstrate how it is possible to generate value for an investor with a hedge attached to the buy-and-hold strategy of an S&P 500 index fund. We study the S&P 500 index portfolio (not including dividends) and the value-weighted S&P 500 index portfolio (including dividends) of the Center for Research in Securities Prices for 1967:01–2011:12, using the capacity utilization and the unemployment rates in real time to determine if a hedge position should be initiated or closed. A hedge is initiated if the capacity utilization, the unemployment rate or a combination of the two signals a contraction in the real economy. The hedge position is closed if it signals otherwise an expansion. We use utility gains (Campbell and Thompson 2008), the manipulation-proof performance measure (MPPM) statistics (Ingersoll et al. 2007) and the P-Sharpe ratio (Bailey and López de Prado 2012) to evaluate the performance of a particular hedge strategy. The empirical results show that there are infinitely many hedges that can generate positive utility gains, higher MPPM statistics and higher P-Sharpe ratios.
Plenoptic Image Coding Using Macropixel-Based Intra Prediction

The plenoptic image in a super high resolution is composed of a number of macropixels recording both spatial and angular light radiance. Based on the analysis of spatial correlations of macropixel structure, this paper proposes a macropixel-based intra prediction method for plenoptic image coding. After applying an invertible image reshaping method to the plenoptic image, the macropixel structures are aligned with the coding unit grids of a block-based video coding standard. The reshaped and regularized image is compressed by the video encoder comprising the proposed macropixel-based intra prediction, which includes three modes: multi-block weighted prediction mode (MWP); co-located single-block prediction mode; and boundary matching-based prediction mode (BMP). In the MWP mode and BMP mode, the predictions are generated by minimizing spatial Euclidean distance and boundary error among the reference samples, respectively, which can fully exploit spatial correlations among the pixels beneath the neighboring microlens. The proposed approach outperforms high-efficiency video coding standard by an average of 47.0% bitrate reduction. Compared with other state-of-the-art methods, such as pseudo-video based on tiling and arrangement method, intra block copy mode, and locally linear embedding-based prediction, it can also achieve 45.0%, 27.7%, and 22.7% bitrate savings on average, respectively.
European Language Resource Coordination: Collecting Language Resources for Public Sector Multilingual Information Management

In order to help improve the quality, coverage and performance of automated translation solutions for current and future Connecting Europe Facility (CEF) digital services, the European Language Resource Coordination (ELRC) consortium was set up through a service contract operating under the European Commission’s CEF SMART 2014/1074 programme to initiate a number of actions to support the collection of Language Resources (LRs) within the public sector in EU member and CEF-affiliated countries. The first action focused on raising awareness in the public sector through the organisation of dedicated events: 2 international conferences and 29 country-specific workshops to engage national as well as regional/municipal governmental organisations, language competence centres, relevant European institutions and other potential holders of LRs from public service administrations and NGOs. In order to gather resources shared by the contributors, the ELRC-SHARE Repository was set up together with services supporting the sharing of LRs, such as the ELRC Helpdesk and Intellectual Property Rights (IPR) clearance support. All collected LRs pass a validation process developed by ELRC. The collected LRs cover all official EU languages, plus Icelandic and Norwegian.
Monocular Vehicle Self-localization method based on Compact Semantic Map*

High precision localization is a crucial requirement for the autonomous driving system. Traditional positioning methods have some limitations in providing stable and accurate vehicle poses, especially in an urban environment. Herein, we propose a novel self-localizing method using a monocular camera and a 3D compact semantic map. Pre-collected information of the road landmarks is stored in a self-defined map with a minimal amount of data. We recognize landmarks using a deep neural network, followed with a geometric feature extraction process which promotes the measurement accuracy. The vehicle location and posture are estimated by minimizing a self-defined re-projection residual error to evaluate the map-to-image registration, together with a robust association method. We validate the effectiveness of our approach by applying this method to localize a vehicle in an open dataset, achieving the RMS accuracy of 0.345 meter with reduced sensor setup and map storage compared to the state of art approaches. We also evaluate some key steps and discuss the contribution of the subsystems.
The effect of computed tomographical gantry angle on the measurement of the canine intercondylar notch

Summary This study was conducted to evaluate the clinical application of computed tomography of the canine femoral intercondylar notch. The canine femoral intercondylar notch is angled 12 degrees from the dorsal plane and obliqued 7 degrees proximolateral to distomedial in the sagittal plane. Measurements of the notch were performed with eight, 12, and 16 degrees of gantry tilt. With the exception of proximal opening notch angle, significant differences were not detected in measurements referenced to 12 degrees of gantry tilt. Evidence from this study indicated that a ± 4 degree variation in gantry tilt angle from a desired angle of 12 degrees did not significantly affect clinical interpretations of intercondylar notch measurements or notch width index ratios.
Future of human mitochondrial DNA editing technologies

Abstract ATP and other metabolites, which are necessary for the development, maintenance, and functioning of bodily cells are all synthesized in the mitochondria. Multiple copies of the genome, present within the mitochondria, together with its maternal inheritance, determine the clinical manifestation and spreading of mutations in mitochondrial DNA (mtDNA). The main obstacle in the way of thorough understanding of mitochondrial biology and the development of gene therapy methods for mitochondrial diseases is the absence of systems that allow to directly change mtDNA sequence. Here, we discuss existing methods of manipulating the level of mtDNA heteroplasmy, as well as the latest systems, that could be used in the future as tools for human mitochondrial genome editing.
Speech enhancement for nonstationary noise environments

In this paper, we propose a robust speech enhancement algorithm for nonstationary noise environments, which comprises a multiband spectral subtraction (MBSS) speech estimator and a minima controlled recursive averaging (MCRA) noise estimation. A multiband approach is obtained by dividing the whole spectrum into multiple subbands and applying spectral subtraction independently in each band. The noise estimate exploit the observation that the noise signal typically has a nonuniform effect on the spectrum of speech and is given by averaging the past spectrum power value and using a time and frequency dependent smoothing factor that is calculated based on the speech presence probability in subbands. We test the performance of proposed algorithm in various nonstationary noise environments. The experiment results confirm the superiority of the MBSS and MCRA estimator. Outstanding speech enhancement is achieved, while avoiding the residual musical noise phenomena.
Detection and Virulence Gene Characterization of Salmonella Isolates from Fish by Conventional and Molecular Methods

Salmonella isolates (n=9) used in this study were isolated from 216 fish samples collected from retail market of Anand city, Gujarat, India. Salmonella serovars from fish were isolated and identified as per BAM USFDA method and serotyped at National Salmonella and Escherichia Centre (NSEC), Kasauli (Himachal Pradesh, India). Virulence factors of Salmonella serovars have been characterized with invA, spvR, spvC and stn genes using the polymerase chain reaction (PCR). All Salmonella serovars possessed 284 bp invA gene and 260 bp enterotoxin (stn) gene but lacks spvR or spvC gene. This showed that all Salmonella serovars isolated from fish were capable of producing gastroenteric illness to humans but were unable to produce systemic infection. The invA and stn genes might be the specific targets for Salmonella identification.
Employing Polygraph Assessment

ALTHOUGH the exact number is not known, it is a safe bet that tens of thousands of polygraph tests are administered in the United States every year. Most of these tests are administered by federal agencies as part of the government’s national security screening program, and some are given by law enforcement to screen the integrity of potential new recruits. A substantial fraction are forensic polygraphs administered by law enforcement as an investigative tool to assist the resolution of criminal cases. Some come from criminal defendants who hire examiners in private practice with the hope of obtaining exculpatory outcomes. Others arise from civil cases involving parental custody/fitness, sex offender commitment, and employee rights. In any case, it is unlikely that a forensic psychologist has administered a polygraph. Instead, polygraphs are administered by polygraphers who work in a profession that is largely disconnected from psychology and informed little by psychological science. Our aim in this chapter is to bridge this gap between applied polygraphy and forensic psychology by providing the information needed to critically evaluate polygraph practice. In addition to examining the current state of polygraph testing, we also review future possible applications of deception detection techniques.
Deposited in DRO : 07 May 2008 Version of attached le : Other Peer-review status of attached

Supersymmetry breaking in a metastable vacuum is re-examined in a cosmological context. It is shown that thermal effects generically drive the Universe to the metastable minimum even if it begins in the supersymmetry-preserving one. This is a generic feature of the ISS models of metastable supersymmetry breaking due to the fact that SUSY preserving vacua contain fewer light degrees of freedom than the metastable ground state at the origin. These models of metastable SUSY breaking are thus placed on an equal footing with the more usual dynamical SUSY breaking scenarios.
Overcoming the Long Tail Problem: A Case Study on CO2-Footprint Estimation of Recipes using Information Retrieval

We propose approaches that use information retrieval methods for the automatic calculation of CO2-footprints of cooking recipes. A particular challenge is the “long tail problem” that arises with the large diversity of possible ingredients. The proposed approaches are generalizable to other use cases in which a numerical value for semi-structured items has to be calculated, for example, the calculation of the insurance value of a property based on a real estate listing. Our ﬁrst approach, ingredient matching, calculates the CO2-footprint based on the ingredient descriptions that are matched to food products in a language resource and therefore suffers from the long tail problem. On the other hand, our second approach directly uses the recipe to estimate the CO2-value based on its closest neighbor using an adapted version of the BM25 weighting scheme. Furthermore, we combine these two approaches in order to achieve a more reliable estimate. Our experiments show that the automatically calculated CO2-value estimates lie within an acceptable range compared to the manually calculated values. Therefore, the costs of the calculation of the CO2-footprints can be reduced dramatically by using the automatic approaches. This helps to make the information available to a large audience in order to increase the awareness and transparency of the environmental impact of food consumption.
Echo-Doppler measurements of portal vein and hepatic artery in asymptomatic patients with hepatitis B virus and healthy adults.

BACKGROUND AND AIM The aim of this prospective study was to determine the range of various hemodynamic parameters of portal vein and hepatic artery with echo-Doppler imaging in asymptomatic carriers of hepatitis B virus (HBV) and healthy adults. METHODS One hundred and twenty two healthy adults and fifty-three asymptomatic patients with chronic HBV formed two groups. All participants underwent color Doppler imaging of the portal vein and hepatic artery. A single operator performed all echo-Doppler measurements. The examination protocol included measurements of portal vein and hepatic artery diameter (d), blood flow (BF), time averaged velocity (TAV) and calculation of Doppler Perfusion Index (DPI) of liver. RESULTS Asymptomatic HBV carriers showed a statistically significant decrease in portal vein TAV (12.8 ± 6.1 vs 17.5 ± 8.8), an increase in portal vein BF (411.38 ± 211.31 vs 327.55 ± 188.77) and decrease in DPI (0.18 ± 0.14 vs 0.28 ± 0.15). CONCLUSIONS Echo-Doppler measurements of portal vein and hepatic artery can detect significant hemodynamic changes in asymptomatic HBV carriers.
Annotating Educational Questions for Student Response Analysis

Questions play an important role in the educational domain, representing the main form of interaction between instructors and students. In this paper, we introduce the ﬁrst taxonomy and annotated educational corpus of questions that aims to help with the analysis of student responses. The dataset can be employed in approaches that classify questions based on the expected answer types. This can be an important component in applications that require prior knowledge about the desired answer to a given question, such as educational and question answering systems. To demonstrate the applicability and the effectiveness of the data within approaches to classify questions based on expected answer types, we performed extensive experiments on our dataset using a neural network with word embeddings as features. The approach achieved a weighted F 1 -score of 0.511, overcoming the baseline by 12%. This demonstrates that our corpus can be effectively integrated in simple approaches that classify questions based on the response type.
A new surrogate for tensor multirank and applications in image and video completion

How to define and relax the tensor rank is a challenging and meaningful topic. The CP-rank, n-rank, and tensor multirank are three of the most popular definitions. Among them n-rank and tensor multirank are widely studied in the low-rank tensor completion problem, and their relaxations are sum of nuclear norm (SNN) and tensor nuclear norm (TNN), respectively. Both the two kinds of nuclear norm treat the singular values equally, while the different singular values for the practical images represent different physical meanings and should be treated differently. In this paper, we propose a tensor logDet function as the relaxation for tensor multirank rather than TNN. To demonstrate the effectiveness of the proposed function, we introduce the function into the low-rank tensor completion problem and develop an alternating direction method of multipliers (ADMM)-based method. Extensive experiments have shown that the proposed method outperforms the SNN and TNN based methods.
Parameterized Model Checking Modulo Explicit Weak Memory Models

We present a modular framework for model checking parameterized array-based transition systems with explicit access operations on weak memory. Our approach extends the MCMT (Model Checking Modulo Theories) framework of Ghilardi and Ranise with explicit weak memory models. We have implemented this new framework in Cubicle-W, an extension of the Cubicle model checker. The modular architecture of our tool allows us to change the underlying memory model seamlessly (TSO, PSO.). Our first experiments with a TSO-like memory model look promising.
Linking, Searching, and Visualizing Entities in Wikipedia

In this paper, we describe a new system to extract, index, search, and visualize entities in Wikipedia. To carry out the entity extraction, we designed a high-performance, multilingual, entity linker and we used a document model to store the resulting linguistic annotations. The entity linker, HEDWIG, extracts the mentions from text usinga string matching Engine and links them toentities with a combination of statistical rules and PageRank. The document model, Docforia (Klang and Nugues, 2017), consists of layers, where each layer is a sequence of ranges describing a speciﬁc annotation, here the entities. We evaluated HEDWIG with the TAC 2016 data and protocol (Ji and Nothman, 2016) and we reached the CEAFm scores of 70.0 on English, on 64.4 on Chinese, and 66.5 on Spanish. We applied the entity linker to the whole collection of English and Swedish articles of Wikipedia and we used Lucene to index the layers and a search module to interactively retrieve all the concordances of an entity in Wikipedia. The user can select and visualize the concordances in the articles or paragraphs. Contrary to classic text indexing, this system does not use strings to identify the entities but unique identiﬁers from Wikidata (Less)
Lean six sigma project management – a stakeholder management perspective

Purpose – The purpose of this paper is to understand the success of Lean Six Sigma (LSS) in banking and financial services industry and to develop a structured stakeholders management model for successful LSS project management. Design/methodology/approach – A two-phase methodology is used. Phase 1 establishes the literature to understand two key process improvement methodologies – Lean and Six Sigma and to derive synergies by their combination leading to success in banking and financial services. The literature also helps to recognize the importance of stakeholder management in LSS projects and to understand how it helps in accelerating change in organizations. Phase 2 of the methodology is based on the interviews conducted by 56 global LSS project managers. This is to understand the practical challenges faced by the LSS project managers in banking and financial services tying back to the existing literature. Findings – The paper identifies the possible opportunities for structured stakeholder management.
Energy Efficiency Optimization for MIMO Distributed Antenna Systems With Pilot Contamination

In this paper, we study the energy-efficiency (EE) maximization problem for a multiple-input multiple-output distributed antenna system (DAS) with pilot contamination. With per-user quality of service constraints and per remote antenna unit (RAU) power requirements, we formulate the EE maximization problem as a joint optimization of sparse transmit beamforming, RAU selection, and RAU clustering. The considered problem is a non-convex multivariate optimization problem. To solve the problem, we transform it to an equivalent parametric programming problem (PPP) with a given EE parameter and design a two-layer optimization scheme to solve the original problem. The outer layer involves two kinds of algorithms to iteratively update the EE parameter based on Dinkelbach’s algorithm and bi-section search, respectively. The more challenging issue lies in the inner loop, where a non-convex multivariate PPP needs to be tackled. A series of techniques, including the reweighted $\ell_\mathbf {1}$ -norm, D.C. function, and semidefinite relaxation (SDR), is adopted to approximate the non-convex multivariate PPP with a convex SDR problem. Furthermore, a heuristic algorithm is proposed to reduce the complexity of a two-layer scheme. Simulation results show that the proposed algorithms significantly improve the EE and demonstrate that RAU selection and RAU clustering contribute to a higher EE.