Miracle-dz/UniFAR-FTUs huggingface dataset:
Translation model based weighting for phrase extraction

Domain adaptation for statistical machine translation is the task of altering general models to improve performance on the test domain. In this work, we suggest several novel weighting schemes based on translation models for adapted phrase extraction. To calculate the weights, we first phrase align the general bilingual training data, then, using domain specific translation models, the aligned data is scored and weights are defined over these scores. Experiments are performed on two translation tasks, German-to-English and Arabic-toEnglish translation with lectures as the target domain. Different weighting schemes based on translation models are compared, and significant improvements over automatic translation quality are reported. In addition, we compare our work to previous methods for adaptation and show significant gains.
Particle swarm optimization for linear support vector machines based classifier selection

Particle swarm optimization is a metaheuristic technique widely applied to solve various optimization problems as well as parameter selection problems for various classification techniques. This paper presents an approach for linear support vector machines classifier optimization combining its selection from a family of similar classifiers with parameter optimization. Experimental results indicate that proposed heuristics can help obtain competitive or even better results compared to similar techniques and approaches and can be used as a solver for various classification tasks.
Question bias and biased question words in Mandarin, German and Bangla

OF THE DISSERTATION Question bias and biased question words in Mandarin, German and Bangla by Beibei Xu Dissertation Director: Veneeta Dayal Bias is a linguistic phenomenon that is primarily found in questions. Various kinds of biased questions have been studied extensively in the literature, e.g. Negative Polar Questions, Questions with Minimizers, Questions with Verum focus (Büring & Gunlogson 2000, Guerzoni 2003, Ladd 1981, Romero & Han 2004, a.o.). Aside from those biased questions, there are questions with dedicated words that can express bias (i.e. biased question words). Those words are nandao in Mandarin, etwa in German, and naki in Bangla. The current dissertation takes a modal approach to bias, distinct from earlier accounts of bias. In order to find out the nature of bias, e.g. how it is introduced, at which level it is interpreted, and why it is primarily found in questions, I study the three biased question words at the interface of syntax, semantics and pragmatics. Based on the analyses of the three words, I claim that bias is a not-at-issue content that is revealed via the speaker’s public belief domain (i.e. Discourse commitment). Considering the phenomenon in general, I isolate three conditions for introducing bias: a preference ranking of alternatives, selection of a particular alternative as privileged, and the requirement to update the Question Under Discussion with the alternatives. Biased question words lexically satisfy all three conditions and give rise to the obligatorily biased reading of questions containing them. With these three conditions, I provide a definition for bias and explain the opening statement that “bias is a linguistic phenomenon that is primarily found in questions”.
Ecological processes dominate the 13C land disequilibrium in a Rocky Mountain subalpine forest

Fossil fuel combustion has increased atmospheric CO2 by ≈ 115 µmol mol−1 since 1750 and decreased its carbon isotope composition (δ13C) by 1.7–2‰ (the 13C Suess effect). Because carbon is stored in the terrestrial biosphere for decades and longer, the δ13C of CO2 released by terrestrial ecosystems is expected to differ from the δ13C of CO2 assimilated by land plants during photosynthesis. This isotopic difference between land‐atmosphere respiration (δR) and photosynthetic assimilation (δA) fluxes gives rise to the 13C land disequilibrium (D). Contemporary understanding suggests that over annual and longer time scales, D is determined primarily by the Suess effect, and thus, D is generally positive (δR > δA). A 7 year record of biosphere‐atmosphere carbon exchange was used to evaluate the seasonality of δA and δR, and the 13C land disequilibrium, in a subalpine conifer forest. A novel isotopic mixing model was employed to determine the δ13C of net land‐atmosphere exchange during day and night and combined with tower‐based flux observations to assess δA and δR. The disequilibrium varied seasonally and when flux‐weighted was opposite in sign than expected from the Suess effect (D = −0.75 ± 0.21‰ or −0.88 ± 0.10‰ depending on method). Seasonality in D appeared to be driven by photosynthetic discrimination (Δcanopy) responding to environmental factors. Possible explanations for negative D include (1) changes in Δcanopy over decades as CO2 and temperature have risen, and/or (2) post‐photosynthetic fractionation processes leading to sequestration of isotopically enriched carbon in long‐lived pools like wood and soil.
On the Traceability of the Accountable Anonymous Channel

Anonymous channels guaranteeing anonymity of senders such as Tor are effective for whistle-blowing and other privacy sensitive scenarios. However, there is a risk of being abused for illegal activities. As a countermeasure to illegal activities using an anonymous channel, it is natural to construct an accountable anonymous channel which can revoke anonymity of senders when an unlawful message was sent out from them. In this paper, we point out that an accountable anonymous channel THEMIS does not provide anonymity in a perfect way and there is a possibility that attackers can identify senders even if messages are not malicious. Feasibility of tracing senders is analyzed by using simulation. Moreover, we give a simple remedy of the flaw in THEMIS.
Towards architectural information in implementation: NIER track

Agile development methods favor speed and feature producing iterations. Software architecture, on the other hand, is ripe with techniques that are slow and not oriented directly towards implementation of costumers' needs. Thus, there is a major challenge in retaining architectural information in a fast-faced agile project. We propose to embed as much architectural information as possible in the central artefact of the agile universe, the code. We argue that thereby valuable architectural information is retained for (automatic) documentation, validation, and further analysis, based on a relatively small investment of effort. We outline some preliminary examples of architectural annotations in Java and Python and their applicability in practice.
Effect of speech rate variation on acoustic phone stability in Afrikaans speech recognition

We analyse the effect of speech rate variation on Afrikaans phone stability from an acoustic perspective. Specifically we introduce two techniques for the acoustic analysis of speech rate variation, apply these techniques to an Afrikaans speech recognition corpus containing extensive speech variation, and demonstrate how these techniques can be used to better understand the performance of a speech recognition system trained on such data.
VitisCyc: a metabolic pathway knowledgebase for grapevine (Vitis vinifera)

We have developed VitisCyc, a grapevine-specific metabolic pathway database that allows researchers to (i) search and browse the database for its various components such as metabolic pathways, reactions, compounds, genes and proteins, (ii) compare grapevine metabolic networks with other publicly available plant metabolic networks, and (iii) upload, visualize and analyze high-throughput data such as transcriptomes, proteomes, metabolomes etc. using OMICs-Viewer tool. VitisCyc is based on the genome sequence of the nearly homozygous genotype PN40024 of Vitis vinifera “Pinot Noir” cultivar with 12X v1 annotations and was built on BioCyc platform using Pathway Tools software and MetaCyc reference database. Furthermore, VitisCyc was enriched for plant-specific pathways and grape-specific metabolites, reactions and pathways. Currently VitisCyc harbors 68 super pathways, 362 biosynthesis pathways, 118 catabolic pathways, 5 detoxification pathways, 36 energy related pathways and 6 transport pathways, 10,908 enzymes, 2912 enzymatic reactions, 31 transport reactions and 2024 compounds. VitisCyc, as a community resource, can aid in the discovery of candidate genes and pathways that are regulated during plant growth and development, and in response to biotic and abiotic stress signals generated from a plant's immediate environment. VitisCyc version 3.18 is available online at http://pathways.cgrb. oregonstate.edu.
Training system of bicycle pedaling using auditory feedback

Recently, bicycling as a sport has attracted a great deal of attention. Previous research on bicycles suggests that pedaling at high frequency at a constant speed is most effective. However, it is hard for beginners to acquire such pedaling skills since expert cyclists develop the skills through long-term training. We propose a bicycle pedaling training system using auditory feedback. The system generates feedback sound every time a pedal crank turns a quarter rotation. Users can keep the pedaling speed constant by synchronizing pedaling with the feedback sound with background music whose tempo is constant. We conducted an experiment with eleven subjects for four weeks and confirmed that the variances of pedaling speed for the subjects trained with the proposed system decreased significantly compared with those of the conventional method.
Acute Hemorrhagic Apoplectic Pituitary Adenoma: Endoscopic Management, Surgical Outcomes, and Complications

Objective: To assess safety and effectiveness of endoscopic transsphenoidal surgery (ETS) for acute hemorrhagic apoplectic pituitary adenoma. Methods: Eighty nine patients with hemorrhagic apoplectic pituitary tumor undergoing endoscopic transsphenoidal surgery were included into a retrospective chart of this study. Charts were reviewed for patient age, sex, presentation, lesion size, surgical procedure, extent of resection, clinical outcome, and surgical complications. Results: Seventy eight (87.7%) patients achieved total resection, 9 (10.1%) had subtotal resection, and 2 (2.2%) patients had partial resection; no patient experienced insufficient resection. After surgery, 65 (90.3%) of 72 patients who had visual acuity deterioration preoperatively normalized and improved significantly; the rate for remission of visual field was 87.7%. All other acute symptoms, such as severe headache, nausea, vomiting, alteration of mental status, and loss of consciousness, vanished postoperatively. Twenty eight (90.4%) of 31 patients with active secreting adenoma had hormonal remission based on endocrinological evaluation. Three (3.4%) patients incurred CSF leakage which was managed with lumbar drainage. Nine (10.1%) patients incurred transient DI postoperatively, and 2 (2.2%) of them developed permanent DI. Seven (7.9%) patients developed hypopituitarism which was treated with replacement therapy of hormone. One (1.1%) experienced craniotomy for intracranial hemorrhage and died from severe surgical complications postoperatively. There were no patients of meningitis or carotid artery injury. Conclusion: Early detection and emergent endoscopic transsphenoidal surgery provided a safe and effective surgical option for hemorrhagic apoplectic pituitary tumor with a low morbidity and mortality.
Throughput optimization in multi-cell CDMA networks

In this paper, we investigate the performance of a multi-cell CDMA network by determining the maximum throughput that the network can achieve for a given grade-of-service requirement, quality-of-service requirement, network topology and call arrival rate profile. Our analysis is restricted to the reverse link and accounts for mobility of users between cells. A constrained nonlinear optimization problem is formulated that maximizes the network throughput subject to upper bounds on the blocking probabilities and a lower bound on the bit energy to interference ratio. The goal is to optimize the usage of network resources, provide consistent grade-of-service for all the cells in the network, and maintain a pre-specified quality-of-service. The solution to the optimization problem yields the maximum network throughput as well as the maximum number of calls that should be admitted in each cell for a given topology and call arrival rate profile. Our optimization algorithm yields significantly higher throughput compared with traditional call admission schemes.
"Please Don't Call on Me": Correlates of Small Group Participation

This study explored the relationship between self-esteem, communication apprehension, extraversion, and small group participation. Fifty female undergraduate General Psychology students participated in groups of 5 to provide feedback regarding 2 children’s videos. They viewed two 5-min clips and responded to questions regarding the education and entertainment values for preschool-aged children (ages 5–7). The experimenter recorded the number and length of times each person spoke. Following the video, the participants completed a self-esteem scale, a communication apprehension scale, and an extraversion scale. Hierarchical regression determined that self-esteem was not a significant predictor of small group participation; however, communication apprehension was. JESSICA PHILLIPS
Mapping attenuation beneath North America using waveform cross‐correlation and cluster analysis

We measure seismic attenuation beneath North America using waveform cross‐correlation and cluster analysis, and obtain images of the laterally varying anelastic structure of the upper mantle. Cluster analysis improves attenuation measurements by systematically comparing only highly similar waveforms, which reduces bias from scattering, directional differences in source functions, and source‐side structure. While lacking station coverage in many areas, the P‐ and S‐wave results are correlated (R2 ≥ 0.5) in both travel time and attenuation. Much weaker correlations are observed between travel‐time and attenuation measurements. Similarities and differences between attenuation and travel times may be used to infer the source of the observed anomalies. The observed anelastic structure has a long‐wavelength pattern crudely similar to that of seismic velocity, which likely indicates higher temperatures beneath western North America than in the east. Shorter‐wavelength structure suggests complex variations requiring alternate explanations such as variable water content.
On the use of Bhattacharyya based GMM distance and neural net features for identification of cognitive load levels

This paper presents a method for detecting cognitive load levels from speech. When speech is modulated by different levels of cognitive load, acoustic characteristics of speech change. In this paper, we measure acoustic distance of a stressed utterance from the baseline stress free speech using GMM-SVM kernel with Bhattacharyya based GMM distance. In addition, it is believed that airflow structure of speech production is nonlinear. This motivates us to investigate better techniques to capture nonlinear characteristic of stress information in acoustic features. Inspired by the recent success of neural networks for representation learning, we employ a single hidden layer feed forward network with non-linear activation to extract the feature vectors. Furthermore, people have different reactions to a particular task load. This inter-speaker difference in stress responses presents a major challenge for stress level detection. We use a bootstrapped training process to learn the stress response of a particular speaker. We perform experiments using data sets from Cognitive Load with Speech and EGG (CLSE) provided for the Cognitive Load Sub-Challenge of the INTERSPEECH 2014 Computational Paralinguistics Challenge. The results show that the system with our proposed strategies performs well on validation and test sets. Index Terms: cognitive load, GMM-supervector, neural net features
Extracting vocal melody from karaoke music audio

Extracting the melody from polyphonic musical audio is a nontrivial research problem. This paper presents an approach for vocal melody extraction from dual channel Karaoke music audio. The extracted melody corresponds to the singing voice in the original performance channel, which can then be used for melody-based music retrieval. In the proposed technique, audio signals from both the accompaniment channel and the original performance channel are analyzed. The note partials are firstly extracted from the signal, which is represented in constant-Q transform frequency domain. Then the volume balance between the two channels is estimated based on signal approximation in the sub-bands. Finally, the pitch corresponding to the singing voice is identified based on the note partial differences between the two channels. The extracted melody is represented as a sequence of pitch values. This technique assumes that the two channels have similar accompaniment instrument performance except for the singing voices. Experimental result on 40 Karaoke music audios has shown the performance of the proposed technique. The pitch extraction rate is above 70% and melody retrieval accuracy in an 800-tune-database is 90%.
T-tail Flutter: Potential-Flow Modelling and Experimental Validation

This paper focuses on the benchmarking of three dfferent methodologies based on potential-flow aerodynamics for T-tail flutter prediction, validating them against wind-tunnel measurements and investigating scenarios where lesser T-tail ffects drive the stability behaviour. In order to overcome the inability of the standard doublet lattice method to predict T-tail flutter, three alternatives are considered: (i) incorporation of supplementary T-tail effects as additional terms in the flutter equations; (ii) a generalisation of the boundary conditions and air loads calculation on the double lattice; and (iii) a linearisation of the unsteady vortex lattice method with arbitrary kinematics. Comparison with experimental results evidences that all three models are consistent and accurate for the subsonic aeroelasticity of realistic T-tail cofigurations. The models are then exercised for an empennage with unconventional characteristics, in which the fin natural frequency in torsion is smaller than in bending. It will be shown that in this case ffects that are generally second-order play a major role, and lead to drastically distinct quantitative and even qualitative flutter curves. The paper concludes with flight test results of the Airbus A400M, which complements the scarce literature on T-tail aircraft in flight.
On the Contribution of PWM Methods to the Common Mode (Leakage) Current in Conventional Three-Phase Two-Level Inverters as Applied to AC Motor Drives

This paper experimentally investigates the common mode voltage (CMV) and common mode current (CMC, leakage current) characteristics of various PWM methods for the classical two-level three-phase voltage source inverter (VSI) as applied to induction motors. The classical SVPWM and DPWM methods which have high CMV/CMC, and the recently proposed reduced CMV (RCMV) PWM methods, such as NSPWM and AZSPWM1 are considered. The effect of including the low cost industry solution of the common mode inductor (CMI) for CMC reduction is investigated. Furthermore, the dependency of the CMC on the inverter topology is investigated by the experimental evaluation of a commercial three-level neutral-point-clamped (NPC) VSI. Based on the experimental results, it is shown that it is beneficial to employ high performance RCMV-PWM methods for the purpose of CMV/CMC reduction. It is shown that including a small CMI further enhances the CMC performance of a drive. Such a configuration provides comparable CMC performance to that of a three-level NPC-VSI and it is more favorable as it is more economical and efficient. The experiments involve a 4-kW, 4-pole induction motor driven by a two-level VSI and a three-level NPC-VSI with diode rectifier front-ends supplied from the three-phase 400 V, 50 Hz power line.
Reconfiguration of electric distribution systems

A methodology to reconfigure an electric power distribution network under normal operating conditions to reduce the active losses of the network or to balance the load of the system's feeders is presented. An heuristic solution algorithm is used. It is based on the method of branch exchange, where different radial configurations are generated, improving the objective function and originating a sequence of maneuvers to be performed on the network. In order to guide the search for configurations, the Power Summation Method is used for load flow calculations, in iterative and direct simplified versions. Significant reductions in CPU time are achieved with the simplified version. Turbo Pascal programming facilitates the dynamic handling of the network structore.
An O(log k) Approximate Min-Cut Max-Flow Theorem and Approximation Algorithm

It is shown that the minimum cut ratio is within a factor of O(log k) of the maximum concurrent flow for k-commodity flow instances with arbitrary capacities and demands. This improves upon the previously best-known bound of O(log2 k) and is existentially tight, up to a constant factor. An algorithm for finding a cut with ratio within a factor of O(log k) of the maximum concurrent flow, and thus of the optimal min-cut ratio, is presented.
Verification modulo versions: towards usable verification

We introduce Verification Modulo Versions (VMV), a new static analysis technique for reducing the number of alarms reported by static verifiers while providing sound semantic guarantees. First, VMV extracts semantic environment conditions from a base program P. Environmental conditions can either be sufficient conditions (implying the safety of P) or necessary conditions (implied by the safety of P). Then, VMV instruments a new version of the program, P', with the inferred conditions. We prove that we can use (i) sufficient conditions to identify abstract regressions of P' w.r. t. P; and (ii) necessary conditions to prove the relative correctness of P' w.r. t. P. We show that the extraction of environmental conditions can be performed at a hierarchy of abstraction levels (history, state, or call conditions) with each subsequent level requiring a less sophisticated matching of the syntactic changes between P' and P. Call conditions are particularly useful because they only require the syntactic matching of entry points and callee names across program versions. We have implemented VMV in a widely used static analysis and verification tool. We report our experience on two large code bases and demonstrate a substantial reduction in alarms while additionally providing relative correctness guarantees.
A Model for Accomplishing and Managing Dynamic Cloud Federations

Cloud computing is not just a promising approach to the service provisioning: nowadays it represents the reference model in such field. Several cloud service providers have emerged as de facto standards and an increasing number of companies are choosing to migrate their business in the Cloud "ecosystem". Nevertheless, each provider adopts a particular interface to manage its services and uses a proprietary technology. In this paper we present a cloud federation model which is able to provide scalability and flexibility to small clouds. The idea is to benefit of renting seamless resources according to federation agreements among operators. The challenge here is to overcome all the problems raising trying to merge small clouds with heterogeneous administrative domains.