Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimensionality Reduction and Clustering of Text Documents

The human language is inherently unstructured. Human authors never follow the strict rules of grammar because their human readers possess cognitive abilities to interpret the semantic meaning of unstructured human written text. Since unstructured text possess ambiguities and uncertainties, using probabilities to model human language is a natural choice. The investigation of a widely used probabilistic model is the motivation of my survey here. This probabilistic model known as Latent Dirichlet Allocation (LDA), has seen widespread adoption in the field of information retrieval. As prelude to the introduction of LDA, I shall review the Latent Semantic Analysis (LSA) and Probabilistic Latent Semantic Analysis (PLSA) for historical interests. Finally, I briefly discuss Hierarchical Latent Dirichlet Allocation.
THE RELATIONSHIP BETWEEN WOMEN ' S EDUCATION WITH WOMEN ' S LABOR PARTICIPATION AND NATIONAL INCOME : A RESEARCH ON G 20 COUNTRIES

The purpose of this research is to reveal the relationship between women’s education, women's labor force participation and national income in G20 countries. The relationships between women's education, women's labor force participation and national income were analyzed by the panel data analysis method for the G20 countries for the period 1997-2018. Stability of series were tested by "Fisher ADF" and "Fisher PP" panel root tests and the series were determined to be I (1). Pedroni (2004) was used to test the existence of cointegration relationships between the series. The series were found to be cointegrated. The longand short-term relationships of the series were analyzed by the Panel DOLS method and it is determined that the increase of female schooling level increase the female labor force participation rate, increase of female schooling level and female labor force participation rate increase the per capita (real) national income. A two-way causality relationship was found between the ratio of women in higher education and national income per person. In addition, two-way causality relations between women's labor force participation rates and schooling rates at all levels of women were determined. In the study, it is concluded that in G20 countries, women's schooling rate increases the women's participation in the labor market and increases of women's schooling rate and female employment increase the national income per capita in countries.
Global studies of fuel retention and high-Z metal deposition pattern in the TEXTOR tokamak

MoF6 injection from a localised source into plasma edge in the TEXTOR tokamak was the last experiment before the final shut-down of the TEXTOR machine. During decommissioning all plasma-facing components (PFCs) became available for surface studies. Detailed mapping of Mo deposition was performed in order to determine its global migration. The concentration of Mo on PFC decays exponentially with distance from the source. The decay length is of the order of 0.1 m on the main PFC and 1 m on the receded components. Also the decay lengths modelled with the ERO code are between 0.15 – 1.3 m, depending on the anomalous cross-field diffusion coefficient. The inner bumper limiter is found to be the major repository for Mo. Material balance measurements show that only up to 22% of the injected Mo was detected on all the PFCs thus indicating a large fraction of injected Mo may have been pumped out before being deposited.
JRC TMA-CC: Slavic Named Entity Recognition and Linking. Participation in the BSNLP-2019 shared task

We report on the participation of the JRC Text Mining and Analysis Competence Centre (TMA-CC) in the BSNLP-2019 Shared Task, which focuses on named-entity recognition, lemmatisation and cross-lingual linking. We propose a hybrid system combining a rule-based approach and light ML techniques. We use multilingual lexical resources such as JRC-NAMES and BABELNET together with a named entity guesser to recognise names. In a second step, we combine known names with wild cards to increase recognition recall by also capturing inflection variants. In a third step, we increase precision by filtering these name candidates with automatically learnt inflection patterns derived from name occurrences in large news article collections. Our major requirement is to achieve high precision. We achieved an average of 65% F-measure with 93% precision on the four languages.
Applying Machine Translation to Psychology: Automatic Translation of Personality Adjectives

We introduce our approach to apply machine translation to psychology, especially to translate English adjectives in a psychological personality questionnaire. We first extend seed English personality adjectives with a word2vec model trained with web sentences, and then feed the acquired words to a phrase-based machine translation model. We use Moses trained with bilingual corpora that consist of TED subtitles, movie’ subtitles and Wikipedia. We collect Japanese translations whose translation probabilities are higher than . 01 and filter them based on human evaluations. This resulted in 507 Japanese personality descriptors. We conducted a web-survey ( N =17,751) and finalized a personality questionnaire. Statistical analyses supported the five-factor structure, reliability and criterion-validity of the newly developed questionnaire. This shows the potential applicability of machine translation to psychology. We discuss further issues related to machine translation application to psychology.
α Belief Propagation as Fully Factorized Approximation

Belief propagation (BP) can do exact inference in loop-free graphs, but its performance could be poor in graphs with loops, and the understanding of its solution is limited. This work gives an interpretable belief propagation rule that is actually minimization of a localized α-divergence. We term this algorithm as α belief propagation (α-BP). The performance of α-BP is tested in MAP (maximum a posterior) inference problems, where α-BP can outperform (loopy) BP by a significant margin even in fully-connected graphs.
QuoteMine : A Repository of Newsworthy Quotes

We present QuoteMine, a repository of newsworthy German language quotes that is automatically gathered from newswire text on the Web. The project is available online through a Web interface that allows users to query for all quotes of certain persons, all quotes that contain specific keywords, or both. Each quote is displayed with a link to the news article in which it was found, as well as an automatically computed sentiment value. Our system runs continuously, keeping up-to-date with the current stream of online news. In this demonstration, we illustrate the design of our system and show how relatively simple Information Extraction methods can be used on large amounts of text to create a large repository of structured data. We discuss present challenges and future ideas.
The Moderating Role of Employee Characteristics on the Relationship between Employee Trust of Top Management and Performance of Savings and Credit Cooperatve Societies ( SACCOS ) in Nairobi City County Kenya

The objective of this study was to establish whether employee characteristics significantly moderate the relationship between employee trust of top management and performance of SACCOs in Nairobi City County. The study population consisted of all 1065 SACCOs in Nairobi City County as at 31 st December 2014. A cross sectional survey research design was used to achieve the objective. Primary data was collected using two questionnaires, one for CEOs of the SACCOs and the other for the employees. The data analysis methods used were descriptive statistics, simple and hierarchical regression analysis. The results of the study were that employee characteristics significantly moderated the relationship between employee trust of top management and performance of SACCOs in Nairobi City County. This led to the conclusion that for employee characteristics to have a strong influence on SACCO’s performance employee must have trust in top management. The findings support the contingency theories that emphasize that the success of any managerial decision depends on prevailing situations. That is to say the effect of employee trust of top management on SACCO performance is moderated by employee characteristics. One limitation of the study was the low response rate of 30%. This needs to be improved in future research. It is recommended that more studies be undertaken to establish the moderating role employee characteristics can have on the relationship between trust and performance in many sectors and industries.
Mobility effects on the evolution of co-operation in emotional robotic agents

Simulating emotions within a group of agents has shown to support co-operation, in the prisoner’s dilemma game [8]. Recent work on simulating these emotions in agents has focused on environments where the agents do not move, that is, they are static and their neighbours are fixed. However it has also been shown that when an agent is given the ability to move, then the type of the environment affects how co-operation between agents evolves in the group of agents [11]. In this paper, we will explore the effects on co-operation when emotional agents are given the ability to move within relatively small and structured environments. We conclude that once mobility is introduced, different strategies are successful than in static agents. The successful strategies, regardless of environment type, respond quickly to defection, while not immediately reciprocating cooperation. The higher the density of the agents, the lower payoff all agents achieve. The further an agent travels, the higher its total payoff. The slower an agent is to copy another agent by imitating its strategy, increases its average payoff.
674-EFFECT OF WETTING ON FRICTION

When it comes to design of mechanical systems in a specific application, determination of the lubrication regimes and oil film efficiency is crucial. In this case, primarily physical phenomena of contact interactions can be predicted with current engineering models, such as for viscosity, film thickness (with all subsequent surfacerelated consequences), lubrication regimes, etc. It is evident that these phenomena include also the solid-liquid interactions. Accordingly, it is of key importance for the engineering design to understand the surface-oil physical phenomena in the lubrication performance of the DLC-coated systems. This work describes how different base oils and other more pure model lubricants influence the oil film formation and lubrication behaviour due to physical interactions with DLC coatings. Phenomena such as wetting and surface energy are discussed and slip at the oil-DLC interface is evidenced. The work shows how the Stribeck curve and lubrication regimes are changed due to use of DLC coatings with properties different from those in conventionally used materials, and this affects also the lubrication design. A newlydeveloped inverse calculation technique with ready-to-use diagrams in combination with conventional models, which allow tailoring of the lubrication conditions for DLC coatings is presented. A paramount effect on friction was shown and reported in last years, reaching up to 40 % reduction.
MODELLING AND SIMULATION OF THE NON-IDEAL MIXING BEHAVIOUR OF THE CRYSTALLIZATION STAGE IN A SUGAR FACTORY BATCH CRYSTALLIZER

A first principles model of a semi-batch crystallizer is proposed, taking into account the non-ideal mixing behaviour of the process. For this purpose, a twocompartment model is developed in order to predict the evolution of the variables related to the sugar crystallization in a more realistic way. The model is based on mass and energy balance equations. It also includes population balance equations to keep track of the sugar crystal size distribution (CSD). Finally, the model is adjusted and validated with real factory data.
Corporate Governance and F Companies

The article aims to investigate the relationship between corporate governance and financial performance by using the data of 61 Oman companies traded at Muscat Securities Market for a four-year period from 2013 to 2016. The models are divided into two groups. The first group constructed a corporate governance score which is the dependent variable; the second group used the components of the score separately as dependent variables. As independent variable, two types of indicators are used; market-based and accounting To reflect the market performance, Tobin’s q is used and as accounting-based indicators; return on asset profit margin, EBIT margin and net profit margin are used. The results showed that there are significant results between financial ratios and characteristics of corporate governance, but the overall relationship is weak in Oman context. Even though individual effects of some components of corporate governance are not significant, most models produced overall significant results. DOI: 10.32602/jafas.2018. 006
Focal attention models driven by image statistics

The visual system evolved to provide fast and adequate, and not necessarily the best, estimates of physical properties. One way in which the visual analysis has been speeded up is by analyzing only part of the scene in detail, with our foveae. The trade-off is that we must move our eyes to areas of interest for detailed analysis. Deciding where to move requires a fast selection process, ideally based on a moment-to-moment representation of potentially “important” regions in the natural scene. We propose the visual system does so by determining areas that deviate in a statistical sense from the rest of the visual scene. This information constitutes a statistical salience map that will drive gaze and attentional shifts.
The multilingual experience

Of the numerous factors affecting language development, a particular role has been assigned to Metalinguistic Awareness (MLA) as a major constituent of the cognitive development of experienced language learners, while being itself a key to accelerated language learning (e.g., Jessner, 2008 ). The present study explores the relationship between multilingual usage and MLA in French-speaking Quebeckers ( n = 66) with different language backgrounds who start to learn German after English in a formal setting. ‘Multilingual experience’ was operationalized by the frequency and the diversity of foreign language use across 10 different contexts of use. A reflexive dimension of MLA was assessed by means of the THAM-3 ( Pinto & El Euch, 2015 ), and complemented by think-aloud protocols produced during a multilingual translation task, which reflected an applied dimension of MLA. Multiple regression analyses suggest that both frequency and diversity of non-native language use in specifically literacy-based activities predicted the applied dimension of MLA.
Title Roles of the recG gene product of Escherichia coli in recombination repair : Effects of the △ recG mutation on cell division and chromosome partition

The products of the recG and ruvAB genes of Escherichia coli are both thought to promote branch migration of Holliday recombination intermediates by their junction specific helicase activities in homologous recombination and recombination repair. To investigate the in vivo role of the recG gene, we examined the effects of a recG null mutation on cell division and chromosome partition. After UV irradiation at a low dose (5J / m), /J.recG mutant formed filamentous cells with unpartitioned chromosomes. A mutation in the sfiA gene, which encodes the SOS-inducible inhibitor of septum formation, largely suppressed filamentation of recG mutant cells, but did not prevent the formation of anucleate cells. The sensitivity to UV light and the cytological phenotypes after UV irradiation of a recA recG double mutant were similar to a recA single mutant, consistent with the role of recG which is assigned at a later stage in recombination repair than that of recA. The recG ruvAB and recG ruvC double mutants were more sensitive to UV and showed more extreme phenotypes concerning filamentation and chromosome nondisjunction, both after UV irradiation and during exponential growth than either recG or ruv single mutant. The recG polA12 (Ts) mutant, which is temperature sensitive in growth, formed filamentous cells with centrally located chromosome aggregates when grown at nonpermissive temperature. These results support that RecG plays a role in processing recombination intermediates in recombination repair.
Recent progress and development on power DC-DC converter topology , control , design and applications : A review

Over the last few decennia, power DC/DC converters have been the subject of great interest due to its extensive increment of utilization in different applications. A thorough review on recent developed power DC/DC converters is presented in this paper. The study is focused on the topologies in different applications such as renewable energy, automobile, high-voltage and medium-voltage DC power systems, telecommunication, etc. In addition, an overview of the modulation techniques, the state-of-the-art of control strategies of well-established converters are discussed. Photovoltaic (PV) systems as the noticeable renewable energy resources generally suffer from poor conversion efficiency with instability and intermittent characteristics. Therefore, DC/DC converter with Maximum Power Point Tracking (MPPT) algorithm is essential to ensure maximum available power harnessed from the PV. Important features of DC/DC converters with MPPT are also figured with various performances. Furthermore, the design and optimization of different parameters are addressed systematically. Finally, the researcher’s future challenges and focusing trends are briefly described. For the next-generation converters design and applications, these are considered in details, and will provide useful framework and point of references.
DEEP NEURAL NETWORKS FOR ARTIFACT REMOVAL FROM DATA GENERATED BY NONLINEAR SYSTEMS : HEART RATE MONITORING

Overview Artifacts are disturbances in the measured signal not originating from the process itself. This paper addresses the problem of heart rate monitoring from photoplethysmography (PPG) sensor where artifacts caused by body movements affect the quality of the measurement signal. The PPG signal is processed by using the singular values decomposition technique to reduce signal noise. To remove the artifacts caused by physical activity of the subject, 3-dimensional accelerometer signal is used as the auxiliary signal and a novel spectral subtraction approach is proposed for signal processing. The denoised signal is windowed into consecutive time segments, and for each time-window of the processed signal and acceleration data, feature extraction is performed. Ground truth heart rate values are obtained from an electrocardiograph sensor during different types of physical activities to capture a broad range of heart rate variations. A fully-connected deep neural network is used to build a model from extracted features and actual heart rate values.
No . M 19 / 06 Solving multiobjective mixed integer convex optimization problems

Multiobjective mixed integer convex optimization refers to mathematical programming problems where more than one convex objective function needs to be optimized simultaneously and some of the variables are constrained to take integer values. We present a branch-and-bound method based on the use of properly defined lower bounds. We do not simply rely on convex relaxations, but we built linear outer approximations of the image set in an adaptive way. We are able to guarantee correctness in terms of detecting both the efficient and the nondominated set of multiobjective mixed integer convex problems according to a prescribed precision. As far as we know, the procedure we present is the first deterministic algorithm devised to handle this class of problems. Our numerical experiments show results on biobjective and triobjective mixed integer convex instances.
GKR: Bridging the Gap between Symbolic/structural and Distributional Meaning Representations

Three broad approaches have been attempted to combine distributional and structural/symbolic aspects to construct meaning representations: a) injecting linguistic features into distributional representations, b) injecting distributional features into symbolic representations or c) combining structural and distributional features in the final representation. This work focuses on an example of the third and less studied approach: it extends the Graphical Knowledge Representation (GKR) to include distributional features and proposes a division of semantic labour between the distributional and structural/symbolic features. We propose two extensions of GKR that clearly show this division and empirically test one of the proposals on an NLI dataset with hard compositional pairs.
Collecting domain specific data for MT: an evaluation of the ParaCrawlpipeline

This paper investigates the effectiveness of the ParaCrawl pipeline for collecting domain-specific training data for machine translation. We follow the different steps of the pipeline (document alignment, sentence alignment, cleaning) and add a topic-filtering component. Experiments are performed on the legal domain for the English to French and English to Irish language pairs. We evaluate the pipeline at both intrinsic (alignment quality) and extrinsic (MT performance) levels. Our results show that with this pipeline we obtain high-quality alignments and significant improvements in MT quality.
Enhancement method for rendered images of home decoration based on SLIC superpixels

Rendering technology has been widely used in the home decoration industry in recent years for images of home decoration design. However, due to the fact that rendered images of home decoration design rely heavily on the parameters of renderer and the lights of scenes, most rendered images in this industry require further optimization afterwards. To reduce workload and enhance rendered images automatically, an algorithm utilizing neural networks is proposed in this manuscript. In addition, considering few extreme conditions such as strong sunlight and lights, SLIC superpixels based segmentation is used to choose out these bright areas of an image and enhance them independently. Finally, these chosen areas are merged with the entire image. Experimental results show that the proposed method effectively enhances the rendered images when compared with some existing algorithms. Besides, the proposed strategy is proven to be adaptable especially to those images with obvious bright parts.
A STUDY ON DEEP AUTOENCODER BASED FAULT DETECTION IN TENNESSEE EASTMAN PROCESS

Data-driven modeling has been considered as an attractive approach for fault detection in chemical processes. Of special interest to industry are methods that represent nonlinear phenomena and detect complex faults. The growing area of deep learning offers new opportunities to fill this gap. In this paper, a semi-supervised deep learning method deep autoencoder (DAE) for fault detection in Tennessee Eastman Process (TEP) is proposed. The TEP process is a simulated benchmark for evaluating process control and monitoring method. The performance of the proposed method is evaluated and compared with Principal Component Analysis (PCA). The experimental results demonstrate that the proposed optimized five-layers DAE model for fault detection outperforms the standard PCA. Of special importance to real-world applications is its capability for automatic variable selection. In comparison to PCA it demonstrated higher prediction accuracy for most of the generated faults. Deep autoencoder has the potential to become an excellent approach for process monitoring and fault detection in chemical processes.