Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving keyword search by query expansion in a probabilistic framework

Keyword search (KWS) in speech data has become an important area of research. Speech recognition error and out-ofvocabulary (OOV) problem are two major challenges in KWS. In this paper, a unified probabilistic framework is proposed for query expansion in KWS to counter both problems. The posterior scores of hits are re-estimated with this framework to re-rank hits and to determine decision thresholds. Experiments on Vietnamese conversational telephone speech show that the actual term-weighted value (ATWV) is significantly improved by expanding queries using this framework. Some deeper diagnostic analysis shows that this framework is insensitive to the parameter and is robust in large-scale expansion, where false alarm problem is very common.
Measuring Stages of Concern about the Innovation: A Manual for the Use of the SoC Questionnaire.

At a time when we are living in a unified and complex society that is evolving at an incredible speed, acquiring the language, culture, and literacy of natural science (chemistry) has become a need for people of all ages who interact with society. Nowadays, a new aspect of chemical literacy education focuses on contributions to the creation of chemistry, history, and science literacy, and it trends toward a change/reform based on public discussion and consensus in chemistry education policy. In order to make changes and reforms, it is necessary to define a policy to prepare future generations by learning from the past history, today's problems, problems and lessons. In this article, we aim to present the results of analyzing the past history and current state of the general chemistry education course
The Use of Exploratory Factor Analysis in Secondary Research: the Case of Motivation for Learning the Lithuanian Language by 8th Grade Students

The article deals with the use of exploratory factor analysis in quantitative secondary research. Exploratory factor analysis helps to find a theoretical background in the data of educational research. The way of proceeding the data in quantitative secondary research can be described as follows: data − exploratory factor analysis – theoretical background of research – interpretation of the data of secondary analysis. The article focuses on the phenomenon of motivation for learning the Lithuanian language by 8th grade students on the basis of the data of national research (2012). Exploratory factor analysis revealed the components of intrinsic motivation for learning the Lithuanian language. The questions Do you like Lithuanian language lessons; Are you interested in writing assignments at Lithuanian language lessons; Are you gifted in the Lithuanian language; Are you interested in reading texts in Lithuanian lessons are related with the factor of intrinsic motivation. The variables You are learning the Lithuanian language because you need to get a well-paid job; You are learning the Lithuanian language because it is important to obtain an interesting job; You are learning the Lithuanian language, because it is important to get entry to a higher school; the Lithuanian language is important to learn other subjects have high factor loadings on another factor, namely extrinsic motivation. Keywords: exploratory factor analysis, motivation for learning the Lithuanian language. DOI: http://dx.doi. org/10.15823/p.2017. 17
Effects of Inhibitory Synaptic Current Parameters on Thalamocortical Oscillations

6 We explore the role of specific GABAergic current conductance and decay 7 time in specific inhibitory synapses in driving macroscopic cortical 8 oscillations based on two computational neuron models. Simulations using a 9 previously established thalamocortical network model demonstrate that: 1) 10 oscillation frequency changes due to increased inhibitory conductance are 11 dependent on post-synaptic neuron type, 2) changes in inhibitory current 12 decay time have no effect on oscillation frequency, and 3) large changes in 13 inhibitory conductance can produce dynamic changes in the network 14 behavior that is uncaptured by peak oscillation frequency. These results 15 warrant careful treatment of different types of GABA recipients in 16 computational models, and motivate further investigat ion in the effects of 17 substances which promote GABAergic activity, such as propofol. 18
Preprocessing and Feature Selection for Improved Sensor Interoperability in Online Biometric Signature Verification

Due to the technological evolution and the increasing popularity of smartphones, people can access an application using authentication based on biometric approaches from many different devices. Device interoperability is a very challenging problem for biometrics, which needs to be further studied. In this paper, we focus on interoperability device compensation for online signature verification since this biometric trait is gaining a significant interest in banking and commercial sector in the last years. The proposed approach is based on two main stages. The first one is a preprocessing stage where data acquired from different devices are processed in order to normalize the signals in similar ranges. The second one is based on feature selection taking into account the device interoperability case, in order to select to select features which are robust in these conditions. This proposed approach has been successfully applied in a similar way to two common system approaches in online signature verification, i.e., a global features-based system and a time functions-based system. Experiments are carried out using Biosecure DS2 (Wacom device) and DS3 (Personal Digital Assistant mobile device) dynamic signature data sets which take into account multisession and two different scenarios emulating real operation conditions. The performance of the proposed global features-based and time functions-based systems applying the two main stages considered in this paper have provided an average relative improvement of performance of 60.3% and 26.5% Equal Error Rate (EER), respectively, for random forgeries cases, compared with baseline systems. Finally, a fusion of the proposed systems has achieved a further significant improvement for the device interoperability problem, especially for skilled forgeries. In this case, the proposed fusion system has achieved an average relative improvement of 27.7% EER compared with the best performance of time functions-based system. These results prove the robustness of the proposed approach and open the door for future works using devices as smartphones or tablets, commonly used nowadays.
Visualization and analysis of mass transfer phenomena in a three dimensional domain of a low temperature PEMFC

The proton exchange membrane fuel cell (PEMFC) is considered as a potential candidate of the hydrogen applications on the power sources in the future. This work depicts the steady-state single phase transport of reactants and water in a three dimensional computational domain of a low temperature Polymer Electrolyte Membrane Fuel Cell. The model computational domain includes anode and cathode flow channels, gas diffusion layers, membrane and catalyst layers. Both anode and cathode mass and momentum transport phenomena in the flow channels, gas diffusion layers (GDLs) and porous electrodes are included in this study. A Computational Fluid Dynamics code using the finite element method (FEM) is applied on the studied domain. Water analysis in the membrane will be discussed in further works. Mass transfer analysis focused on the air flow velocity parameter, a range of values is applied to observe its effect Simulation results show an important molar concentration of water in the cathode side compared to a low one in the anode side. A good oxygen concentration is obtained with an air flow velocity of 0.5 m/s, increasing this value may cause the membrane flooding phenomena.
Practical pluggable types for java

This paper introduces the Checker Framework, which supports adding pluggable type systems to the Java language in a backward-compatible way. A type system designer defines type qualifiers and their semantics, and a compiler plug-in enforces the semantics. Programmers can write the type qualifiers in their programs and use the plug-in to detect or prevent errors. The Checker Framework is useful both to programmers who wish to write error-free code, and to type system designers who wish to evaluate and deploy their type systems. The Checker Framework includes new Java syntax for expressing type qualifiers; declarative and procedural mechanisms for writing type-checking rules; and support for flow-sensitive local type qualifier inference and for polymorphism over types and qualifiers. The Checker Framework is well-integrated with the Java language and toolset. We have evaluated the Checker Framework by writing 5 checkers and running them on over 600K lines of existing code. The checkers found real errors, then confirmed the absence of further errors in the fixed code. The case studies also shed light on the type systems themselves.
Association between childhood obesity and use of regular medications in the UK: longitudinal cohort study of children aged 5–11 years

Objectives Increasing rates of childhood obesity have been suggested as a possible cause for the increasing prevalence of chronic conditions among adults and children. Few studies have examined whether obese children are more likely to use medications than normal weight children. We investigate this association in the UK. Design A panel study with repeated observations at ages 5, 7 and 11. Setting A general population sample drawn from the Millennium Cohort Study, a UK-based birth cohort. Participants A sample of 9667 children. Primary and secondary outcome measures Our primary outcomes were crude and adjusted probabilities of taking any regular medications and the number of medications among overweight and obese children compared with normal weight children. Our secondary outcome was the distribution of medication use by therapeutic classification across body mass index (BMI) groups. Results Obese children were more likely to use any medication (marginal effect (ME)=0.02, 95% CI 0.01 to 0.03) and to use more medications (ME=0.08, 95% CI 0.04 to 0.12) than normal weight children. Obese children used more medications for respiratory conditions than those of other BMI groups. Conclusions Obese children are more likely to use regular medications and have comorbid conditions, even at young ages. This suggests that the cost of prescriptions should be considered when evaluating the economic burden of childhood obesity and that preventative strategies to reduce childhood obesity could be cost-effective in the short as well as in the long term. While more research is needed, both clinicians and policymakers should be aware of these findings when planning prevention and treatment strategies.
A supervised ranking approach for detecting relationally similar word pairs

The similarity between the semantic relations that exist between two word pairs is defined as their relational similarity. For example, the semantic relation, is a large holds between the words in the word pair (lion, cat) and (ostrich, bird), because lion is a large cat, and ostrich is the largest living bird on earth. Consequently, the two word pairs, (lion, cat) and (ostrich, bird), are considered to be relationally similar. A high degree of relational similarity can be observed between analogous pairs of words. Measuring the relational similarity between word pairs is important in numerous natural language processing tasks such as solving word analogy questions, classifying noun-modifier relations and disambiguating word senses. We propose a supervised ranking-based method to detect relationally similar word pairs to a given word pair using information retrieved from a Web search engine. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a ranking Support Vector Machine is trained to recognize word pairs with similar semantic relations to a given word pair. To train and evaluate the proposed method, we use a benchmark dataset that contains 374 SAT multiple-choice word-analogy questions. To represent the relations that exist between two word pairs, we experiment with 11 different feature functions, including both symmetric and asymmetric feature functions. Our experimental results show that the proposed ranking-based approach outperforms several previously proposed relational similarity measures on this benchmark dataset, achieving an SAT score of 46.9.
KEPRAKTISAN MODEL ASSURANCE, RELEVANCE, INTEREST, ASSESSMENT, SATISFACTION (ARIAS) PADA PEMBELAJARAN MATEMATIKA

Mathematics is one of the basic subjects which is taught at every level of education, because it equips learners have the ability to think logically, analytically, systematicaly, critically and creatively, and the ability to solve problems and work together. In fact, many students do not have those abilities. One of the ways to improve their mathematical abilities is doing an effective learning with practical learning tools. In this study ARIAS learning model learning is as a tool of learning device. To achieve its practicality, learning devices are made to ease the teacher and student understanding. This study aimed to analyze the practicality of the learning device. This learning device is said to be practical if it has been tested in the experimental class and it gained positive response from students and teachers, and teacher has good interpretation when he manage his classroom activities. The result of this research is 79% of positive responses from teachers, and 87% positive responses from the students, and the average is 3.4 teachers manage the class well.
Prevalence and co-occurrence of addictive behaviors among former alternative high school youth

Background and Aims: Recent work has studied multiple addictions using a matrix measure, which taps multiple addictions through single responses for each type. Methods: The present study investigated use of a matrix measure approach among former alternative high school youth (average age = 19.8 years) at risk for addictions. Lifetime and last 30-day prevalence of one or more of 11 addictions reviewed in other work (Sussman, Lisha & Griffiths, 2011) was the primary focus (i.e., cigarettes, alcohol, other/hard drugs, eating, gambling, Internet, shopping, love, sex, exercise, and work). Also, the co-occurrence of two or more of these 11 addictive behaviors was investigated. Finally, the latent class structure of these addictions, and their associations with other measures, was examined. Results: We found that ever and last 30-day prevalence of one or more of these addictions was 79.2% and 61.5%, respectively. Ever and last 30-day co-occurrence of two or more of these addictions was 61.5% and 37.7%, respectively. Latent Class Analysis suggested two groups: a generally Non-addicted Group (67.2% of the sample) and a “Work Hard, Play Hard”-addicted Group that was particularly invested in addiction to love, sex, exercise, the Internet, and work. Supplementary analyses suggested that the single-response type self-reports may be measuring the addictions they intend to measure. Discussion and Conclusions: We suggest implications of these results for future studies and the development of prevention and treatment programs, though much more validation research is needed on the use of this type of measure.
Columbia University in the Novelty Track at TREC 2004

Our system for the Novelty Track at TREC 2004 looks be- yond sentence boundaries as well as within sentences to identify novel, nonduplicative passages. It tries to iden- tify text spans of two or more sentences that encompass mini-segments of new information. At the same time, we avoid any pairwise comparison of sentences, but rely on the presence of previously unseen terms to provide evidence of novelty. The system is guided by a number of parameters, both weights and thresholds, that are learned automatically with a randomized hill-climbing algorithm. During learning, we varied the target function to produce congurations that emphasize either precision or recall. We also implemented a straightforward vector-space model as a comparison and to test a combined approach. Both the retrieval and ltering tasks are quite dicult in themselves, and it is problematic to join them and force the ltering systems to use the experimental output of the re- trieval systems. The noisy input clouds what can be learned about determining novelty. We did only Task 2 of the Nov- elty Track this year, since it is most closely related to our on- going research into creating updates or bulletin summaries for an on-line news browsing system. Our submission for the Novelty Track, called SumSeg, is based on observations of the data we collected for the de- velopment of our update summarizer. We saw that new information sometimes appears in passages that are two or more sentences long, and sometimes only in clauses embed- ded in a sentence. (Task 4 is similar to Task 2, but it allows the systems to see the novel sentences from the rst v e documents. Time constraints prevented us from submitting runs for it that would have made use of additional input.) In order to recognize novelty in both cases { segments of two or more sentences, and embedded clauses that are only part of a sentence { we avoid direct sentence similarity mea- sures, and consider previously unseen words to be the main evidence of novelty. SumSeg has a number of thresholds for deciding how much novelty is necessary to trigger a novel classication. We implemented a randomized hill climb- ing algorithm to learn thresholds for how many new words would trigger a novel classication. We also sought to learn dieren t weights for dieren t types of nouns, for example,
A calibration simplified method for gaze interaction based on using experience

The step of calibration prevents the gaze interaction from interacting naturally, which usually needs five or more calibration points to obtain the user's calibration information. In this paper, a calibration simplified method is proposed, which is based on user experience and consists of the user experience accumulation stage and the calibration simplified stage. In the user experience accumulation stage, the calibration is still needed as usual before each gaze interaction and the calibration parameters and the position of the user are stored as the calibration experience, where the calibration parameters include the actual coordinates of the calibration points and their estimation errors. In the calibration simplified stage, the user needs to fixate on only one calibration point for calibration before the calibration information can be estimated according to the user experience stored in the first stage. Even the calibration information can be estimated according to only the position of the user and the stored calibration parameters, which means the user can interact with computer via gaze directly without calibration. The simulations show that the gaze estimation accuracy of the proposed calibration simplified method can be 1.4047° with one calibration point and 1.7489° without calibration point, which are much higher than that without the user experience.
Recommender System Based on Modularity

This paper presents a solution for the RecSys Challenge 2014 by performing a clustering in a bipartite graph whose vertices are of two types: user and item, having the edges as the engagement given to a tweet. The Modularity metric, which is well-known in the area of complex networks to quantify how good the groups of nodes are defined in the network, was used to form the groups that contain users and movies that are closely related. The resulting groups have members of both classes of vertices. From this clustering, a nearest neighbor technique was applied to rank the tweets by the engagement.
Formulation and Optimization of Sustained Release Stavudine Microspheres Using Response Surface Methodology

The aim of the current study was to formulate and optimize the formulation on the basis of in vitro performance of microsphere. A 32 full factorial design was employed to study the effect of independent variables, polymer-to-drug ratio (X 1) and stirring speed (X 2), on dependent variables, encapsulation efficiency, particle size, and time to 80% drug release. The best batch exhibited a high entrapment efficiency of 70% and mean particle size 290 μm. The drug release was also sustained for more than 12 hours. The study helped in finding the optimum formulation with excellent sustained drug release.
Combining Active and Passive Simulations for Secondary Motion

Describes how to generate secondary motion by coupling physically based simulations of passive objects to actively controlled characters. Our approach of using coupled simulations is general, can be applied to a wide range of phenomena and can add visual richness to an animated scene. While we simulated the secondary motion of many of the objects in the scene, a number of objects remain motionless. In some cases, modeling a few of the moving and flexible objects appears to emphasize the lack of motion in the others. Like the progression in models from wireframe to polygonal to subdivision surfaces, this increase in fidelity may also increase the viewer's expectations.
Modeling and Scheduling Asynchronous Incremental Workflows

We consider workflows that process very large incoming data feeds (e.g. web crawls or sky surveys) in an incremental fashion. Due to the large volume of data and relaxed application semantics, the workflow may not enforce strict temporal synchronization across the various input, intermediate and output data sets. In fact, asynchronous behavior is often programmed explicitly, to meet latency goals. Programming of asynchronous incremental workflows is mostly ad-hoc, and there is a lack of tools for reasoning about and scheduling such workflows. This paper analyzes the requirements of this class of data-intensive application, and introduces formal programming and scheduling models. Our programming model gives fine-grained control over the amount of temporal asynchrony in various parts of the workflow. Our scheduler dynamically switches between synchronous and asynchronous operator variants to achieve the desired temporal semantics, and also dynamically chooses among incremental and non-incremental variants based on the amount of data to be processed and operator costs.