Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonnative and second-language speech perception : commonalities and complementarities

Language experience systematically constrains perception of speech contrasts that deviate phonologically and/or phonetically from those of the listener’s native language. These effects are most dramatic in adults, but begin to emerge in infancy and undergo further development through at least early childhood. The central question addressed here is: How do nonnative speech perception findings bear on phonological and phonetic aspects of second language (L2) perceptual learning? A frequent assumption has been that nonnative speech perception can also account for the relative difficulties that late learners have with specific L2 segments and contrasts. However, evaluation of this assumption must take into account the fact that models of nonnative speech perception such as the Perceptual Assimilation Model (PAM) have focused primarily on naïve listeners, whereas models of L2 speech acquisition such as the Speech Learning Model (SLM) have focused on experienced listeners. This chapter probes the assumption that L2 perceptual learning is determined by nonnative speech perception principles, by considering the commonalities and complementarities between inexperienced listeners and those learning an L2, as viewed from PAM and SLM. Among the issues examined are how language learning may affect perception of phonetic vs. phonological information, how monolingual vs. multiple language experience may impact perception, and what these may imply for attunement of speech perception to changes in the listener’s language environment. Commonalities and complementarities 3
SCIENTIFIC COMMITTEE THIRD REGULAR SESSION 13-24 August 2007 Honolulu, United States of America RECORDING SEABIRD BYCATCH IN LONGLINE OBSERVER PROGRAMS WCPFC-SC3-EB SWG/WP-6

This paper discusses best practice for collecting seabird bycatch data in pelagic longline observer programs. The paper recognizes that key challenges for WCPFC include: • The levels of observer coverage needed for recording and monitoring bycatch of non-target species such as seabirds, which typically have high variability in CPUE • The need to divide observer time between a range of tasks • The standardization of data collection across existing programs, and establishing a protocol with a sufficient level of detail to ensure consistency • The importance of high quality observer training in relation to recording bycatch data Recommendations are: • Effective monitoring of bycatch rates of non-target species will require high observer coverage. These levels may have to be achieved progressively. Coefficients of variation of seabird CPUE should be regularly reviewed to assess the effectiveness of observer coverage in monitoring bycatch rates. • Specific time should be allocated for observers to spend observing hooks as they are hauled aboard. Sampling protocols should be made explicit. • Seabird bycatch rates must be reported based on hooks observed from the hauling deck itself • The protocol for recording seabird bycatch data should be specified in as much detail as possible, to ensure consistency. Crucial data to record are time/date of setting, a description of the configuration/ characteristics of gear, a detailed description of mitigation measures and their level of adoption, seabird identification, number of seabirds caught and status • It is highly desirable to collect seabird carcasses and return to port for identification. If this is not feasible then photographs of the upper and lower body and bill may be sufficient. • Currently, few seabird bycatch data are reported standardized by seabird abundance, but this would make comparisons between bycatch rates more meaningful. • The experience of BirdLife International is that high quality observer training, including the provision of targeted materials is crucial in order to obtain reliable bycatch data Introduction At-sea observer programs are accepted as the only reliable and accurate source of many of the data needed for fisheries management, including verification of fishing effort and CPUE data, and collection of data on discards and on interactions with non-target species.
4. Chapter 4 – Extracting Translation Examples 30 4.1 Preparing the Corpus 30 4.2 Parallel Text Alignment 31 4.2.1 Finding Parallel Text Anchors 32 4.2.2 Dk-vec Matching 34 4.2.3 Extracting Anchors 38 4.2.4 Extracting Corresponding Paragraphs 38

We describe an implementation of an Example-Based Machine Translation system that translates short sentences from Arabic to English. The system uses a large parallel corpus, aligned at the paragraph level, and built using many parallel Arabic-English documents from the United-Nations database. This is a non-structural system, so examples are stored in their surface forms, with some additional morphological and part-of-speech information. Each new input sentence is matched to example patterns by using various levels of morphological data. Matched fragments are transferred to English using a rough word-level alignment algorithm, which makes use a bilingual dictionary, along with WordNet. There is no syntactical parser involved in the matching and/or transfer processes, although we do use a shallow English parser to help with specific situations. Currently, the system first fragments any newly introduced input sentence and then translates each segment separately; recombining those translations into a final coherent form is left for future work. We encountered several problems in the matching and the transfer steps, some of which were solved, partially or totally, sometimes by using linguistic tools for both languages. We discuss those problems and our proposed solutions. The system has been implemented and automatically evaluated. Results are encouraging.
Reactive Power Capability Model of Wind Power Plant Using Aggregated Wind Power Collection System

This article presents the development of a reactive power capability model for a wind power plant (WPP) based on an aggregated wind power collection system. The voltage and active power dependent reactive power capability are thus calculated by using aggregated WPP collection system parameters and considering losses in the WPP collection system. The strength of this proposed reactive power capability model is that it not only requires less parameters and substantially less computational time compared to typical detailed models of WPPs, but it also provides an accurate estimation of the available reactive power. The proposed model is based on a set of analytical equations which represent converter voltage and current limitations. Aggregated impedance and susceptance of the WPP collection system are also included in the analytical equations, thereby incorporating losses in the collection system in the WPP reactive power capability calculation. The proposed WPP reactive power capability model is compared to available methodologies from literature and for different WPP topologies, namely, Horns Rev 2 WPP and Burbo Bank WPP. Performance of the proposed model is assessed and discussed by means of simulations of various case studies demonstrating that the error between the calculated reactive power using the proposed model and the detailed model is below 4% as compared to an 11% error in the available method from literature. The efficacy of the proposed method is further exemplified through an application of the proposed method in power system integration studies. The article provides new insights and better understanding of the WPPs’ limits to deliver reactive power support that can be used for power system stability assessment, particularly long-term voltage stability.
Outward rotations: a tool for rounding solutions of semidefinite programming relaxations, with applications to MAX CUT and other problems

We present a tool, outward rotations, for enhancing the performance of several semide(cid:12)nite programming based approximation algorithms. Using outward rotations, we obtain an approximation algorithm for MAX CUT that, in many interesting cases, performs better than the algorithm of Goemans and Williamson. We also obtain an improved approximation algorithm for MAX NAE-f3g-SAT. Finally, we provide some evidence that outward rotations can also be used to obtain improved approximation algorithms for MAX NAE-SAT and MAX SAT.
Adaptive Suppression of Interfering Signals in Communication Systems

The growth in the number of wireless devices and applications underscores the need for characterizing and mitigating interference induced problems such as distortion and blocking. A typical interference scenario involves the detection of a small amplitude signal of interest (SOI) in the presence of a large amplitude interfering signal; it is desirable to attenuate the interfering signal while preserving the integrity of SOI and an appropriate dynamic range. If the frequency of the interfering signal varies or is unknown, an adaptive notch function must be applied in order to maintain adequate attenuation. This work explores the performance space of a phase cancellation technique used in implementing the desired notch function for communication systems in the 1-3 GHz frequency range. A system level model constructed with MATLAB and related simulation results assist in building the theoretical foundation for setting performance bounds on the implemented solution and deriving hardware specifications for the RF notch subsystem devices. Simulations and measurements are presented for a Low Noise Amplifier (LNA), voltage variable attenuators, bandpass filters and phase shifters. Ultimately, full system tests provide a measure of merit for this work as well as invaluable lessons learned. The emphasis of this project is the on-wafer LNA measurements, dependence of IC system performance on mismatches and overall system performance tests. Where possible, predictions are plotted alongside measured data. The reasonable match between the two validates system and component models and more than compensates for the painstaking modeling efforts. Most importantly, using the signal to interferer ratio (SIR) as a figure of merit, experimental results demonstrate up to 58 dB of SIR improvement. This number represents a remarkable advancement in interference rejection at RF or microwave frequencies.
DCU's Experiments for the NTCIR-8 IR4QA Task

We describe DCU’s participation in the NTCIR-8 IR4QA task [16]. This task is a cross-language information retrieval (CLIR) task from English to Simplified Chinese which seeks to provide relevant documents for later cross language question answering (CLQA) tasks. For the IR4QA task, we submitted 5 official runs including two monolingual runs and three CLIR runs. For the monolingual retrieval we tested two information retrieval models. The results show that the KL-Divergence language model method performs better than the Okapi BM25 model for the Simplified Chinese retrieval task. This agrees with our previous CLIR experimental results at NTCIR-5. For the CLIR task, we compare query translation and document translation methods. In the query translation based runs, we tested a method for query expansion from external resource (QEE) before query translation. Our result for this run is slightly lower than the run without QEE. Our results show that the document translation method achieves 68.24% MAP performance compared to our best query translation run. For the document translation method, we found that the main issue is the lack of named entity translation in the documents since we do not have a suitable parallel corpus for training data for the statistical machine translation system. Our best CLIR run comes from the combination of query translation using Google translate and the KL-Divergence language model retrieval method. It achieves 79.94% MAP relative to our best monolingual run.
CRISPR-Based Methods for Caenorhabditis elegans Genome Engineering

The advent of genome editing techniques based on the clustered regularly interspersed short palindromic repeats (CRISPR)–Cas9 system has revolutionized research in the biological sciences. CRISPR is quickly becoming an indispensible experimental tool for researchers using genetic model organisms, including the nematode Caenorhabditis elegans. Here, we provide an overview of CRISPR-based strategies for genome editing in C. elegans. We focus on practical considerations for successful genome editing, including a discussion of which strategies are best suited to producing different kinds of targeted genome modifications.
Comparison of classification methods to detect the Parkinson disease

Parkinson's disease is a chronic neurological degenerative disease affecting the central nervous system responsible for essentially progressive evolution movement disorders. The detection of this disease is made using a clinical diagnosis made by an expert. To save time and for more comfort in the Diagnostic and also to increase the efficiency of treatment through preventive detection, classification has found its place in the detection of this disease. For this purpose, many classification algorithms were used to achieve the best results, but the problem is which classifiers may be the most efficient for this detection, because each classification algorithms was applied to a local database, what influences the results. In this paper we have tried to apply three types of classifiers, k-near neighbor "k-NN", the Naive Bayes "NB" and support vector machines "SVM", on the same database to compare and to know which of the three classifiers will be the most efficient.
Towards a Cross-Cultural Conceptual Framework for Researching Social and Emotional Education

The central aim of this study was to investigate how different countries practice social and emotional education (SEE) using a comparative research design to create a cross-cultural conceptual framework. The study used a sequential quantitative-qualitative analysis with a comparative design that included 750 teachers. Cross-cultural differences were found in the research sample regarding teachers’ self-perceived role in socialising emotion: specifically, the teachers’ openness to emotional expression in the classroom, and what social and emotional aptitudes were more likely to be included as part of SEE provision. More variation was found in these variables internationally compared to intranationally. A conceptual framework using two dimensions was created in order to aid future cross-cultural research regarding SEE provision and the study of emotional rules in the teaching profession: the Ideal Affect (likelihood of suppressing rather than expressing emotion) and the Ideal Self (likelihood of developing skills for independence versus interdependence).
Parallel implementation of 3D object reconstruction in a Robotic navigational environment

Stereo vision systems in a Robotic navigation environment determine the depth in the form of a depth map image from two or more images which are taken at the same time, but from slightly different viewpoints. Ground suppression from depth map is essential for object reconstruction in 3D environment as the ground surface is considered as traveling medium than as an object. Ground separated depth map needs to be segmented to identify the objects of interest. Objects identified below the threshold size need to be removed from the scene. In this paper we propose a Fuzzy-based parallel object clustering algorithm to reconstruct the objects of interest in 3D environment from the ground suppressed depth map. The depth map is divided into Fuzzy layers in X-Z plane and these Fuzzy layers are processed in parallel to reconstruct the objects of interest in 3D environment using region growing method on a cluster computing setup. Experimental results show that Fuzzy logic effectively handles the uncertainty in object reconstruction process. The parallel implementation of the algorithm drastically reduces the time required for object reconstruction process in congested navigational environments.
The Evolution of COP9 Signalosome in Unicellular and Multicellular Organisms

The COP9 signalosome (CSN) is a highly conserved protein complex, recently being crystallized for human. In mammals and plants the COP9 complex consists of nine subunits, CSN 1–8 and CSNAP. The CSN regulates the activity of culling ring E3 ubiquitin and plays central roles in pleiotropy, cell cycle, and defense of pathogens. Despite the interesting and essential functions, a thorough analysis of the CSN subunits in evolutionary comparative perspective is missing. Here we compared 61 eukaryotic genomes including plants, animals, and yeasts genomes and show that the most conserved subunits of eukaryotes among the nine subunits are CSN2 and CSN5. This may indicate a strong evolutionary selection for these two subunits. Despite the strong conservation of the protein sequence, the genomic structures of the intron/exon boundaries indicate no conservation at genomic level. This suggests that the gene structure is exposed to a much less selection compared with the protein sequence. We also show the conservation of important active domains, such as PCI (proteasome lid-CSN-initiation factor) and MPN (MPR1/PAD1 amino-terminal). We identified novel exons and alternative splicing variants for all CSN subunits. This indicates another level of complexity of the CSN. Notably, most COP9-subunits were identified in all multicellular and unicellular eukaryotic organisms analyzed, but not in prokaryotes or archaeas. Thus, genes encoding CSN subunits present in all analyzed eukaryotes indicate the invention of the signalosome at the root of eukaryotes. The identification of alternative splice variants indicates possible “mini-complexes” or COP9 complexes with independent subunits containing potentially novel and not yet identified functions.
A hybrid filtering approach for question answering

We describe a question answering system that took part in the bilingual CLEFQA task (German-English) where German is the source language and English the target language.We used the BableFish online translation system to translate the German questions into English. The system is targeted at Factoid and Denition questions. Our focus in designing the current system is on testing our online methods which are based on information extraction and linguistic ltering methods. Our system does not make use of precompiled tables or Gazetteers but uses Web snippets to rerank candidate answers extracted from the document collections. WordNet is also used as a lexical resource in the system. Our question answering system consists of the following core components: Question Anal- ysis, Passage Retrieval, Sentence Analysis and Answer Selection. These components employ various Natural Language Processing (NLP) and Machine Learning (ML) tools, a set of heuristics and dierent lexical resources. Seamless integration of the various components is one of the major challenges of QA system development. In order to facilitate our develop- ment process, we used the Unstructured Information Management Architecture (UIMA) as our underlying framework.
CADICA: Diagnosis of Coronary Artery Disease Using the Imperialist Competitive Algorithm

Coronary artery disease (CAD) is currently a prevalent disease from which many people suffer. Early detection and treatment could reduce the risk of heart attack. Currently, the golden standard for the diagnosis of CAD is angiography, which is an invasive procedure. In this article, we propose an algorithm that uses data mining techniques, a fuzzy expert system, and the imperialist competitive algorithm (ICA), to make CAD diagnosis by a non-invasive procedure. The ICA is used to adjust the fuzzy membership functions. The proposed method has been evaluated with the Cleveland and Hungarian datasets. The advantage of this method, compared with others, is the interpretability. The accuracy of the proposed method is 94.92% by 11 rules, and the average length of 4. To compare the colonial competitive algorithm with other metaheuristic algorithms, the proposed method has been implemented with the particle swarm optimization (PSO) algorithm. The results indicate that the colonial competition algorithm is more efficient than the PSO algorithm.
Financial well-being among Malaysian manufacturing employees

Employees and financial well-being are two aspects that are closely related to each other, and have been deeply studied by researchers. Not only can financial well-being directly affect an individual, but it can also indirectly affect his/her organization as well as employer. Any level of financial employees’ well-being, either low or high, will change their job performance. Thus, the purpose of this study is to determine the level of financial well-being among manufacturing employees in Batu Pahat, as well as to test the relationships between determinants and financial well-being among manufacturing employees in Batu Pahat. In this study, seven research hypotheses were developed to examine seven determinants, including age, income, gender, education, current job position, income, and marital status which influence employees‘ financial well-being. In this study, 220 employees at the production level were selected randomly from a manufacturing company in Batu Pahat, Johor, Malaysia. Then, a questionnaire was distributed to the employees. The data obtained were analyzed quantitatively using SPSS version 22.0. The results of this study revealed that the level of financial well-being was moderate and all of the determinants were positively related to financial well-being among the manufacturing employees. This quantitative study is important to the manufacturing industry in Malaysia in order to gain insight on the correlation between financial well-being and its determinants.
CellSs: a Programming Model for the Cell BE Architecture

In this work we present Cell superscalar (CellSs) which addresses the automatic exploitation of the functional parallelism of a sequential program through the different processing elements of the Cell BE architecture. The focus in on the simplicity and flexibility of the programming model. Based on a simple annotation of the source code, a source to source compiler generates the necessary code and a runtime library exploits the existing parallelism by building at runtime a task dependency graph. The runtime takes care of the task scheduling and data handling between the different processors of this heterogeneous architecture. Besides, a locality-aware task scheduling has been implemented to reduce the overhead of data transfers. The approach has been implemented and tested with a set of examples and the results obtained since now are promising
Circulação e apropriação da pedagogia personalizada e comunitária no Brasil (1959-1969)

Este artigo se propoe a compreender a circulacao e a apropriacao da pedagogia personalizada e comunitaria no Brasil de 1959 ao final dos anos de 1960. Inicialmente, faz uma sintese dessa proposta educacional concebida por Pierre Faure, padre jesuita frances que amalgamou o movimento da Escola Nova e a tradicao pedagogica catolica. O foco e colocado sobre as operacoes de circulacao e de apropriacao da pedagogia personalizada e comunitaria, procurando verificar seu circuito catolico e franco-brasileiro por meio de diferentes estrategias e constatar seu uso em colegios catolicos por meio de recursos didaticos que personalizavam e incitavam a socializacao o trabalho dos alunos. Tendo como fontes artigos cientificos, livros e relatorios tecnicos em portugues e em frances, busca-se estudar a pedagogia fauriana em movimento na educacao brasileira. Palavras-chave: pedagogia personalizada e comunitaria, circulacao.