Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Chinese Semantic Role Labeling Based on Binary Strategy

Chinese SRL(Semantic Role Labeling) is a cutting-edge technology in the field of Chinese information processing. Now it has become one of the hottest research areas in Chinese information processing research. In this paper, based on the analysis of the previous SRL theory, the Chinese SRL technology, the comparison of advantages and disadvantages, this paper classifies and discusses the basic algorithm ideas of Chinese SRL. At the same time, the thinking on the SRL system is formed and a Chinese SRL system based on the binary strategy is proposed. The system adopts a binary strategy SRL method, combined with a statistical method based on linear feature combination research, fusion of Chinese short-sentence analysis of the study, to achieve a binary strategy-based Chinese SRL system design and construction. Through the experimental comparison, it is proved that the SRL system based on the binary strategy has a good annotation effect.
Mind-Personality Relations from Childhood to Early Adulthood

We present three studies which investigated the relations between cognition and personality from 7 to 20 years of age. All three studies showed that general cognitive ability and the general factor of personality are significantly related throughout this age span. This relation was expressed in several ways across studies. The first investigated developmental relations between three reasoning domains (inductive, deductive, and scientific) and Eysenck’s four personality dimensions in a longitudinal-sequential design where 260 participants received the cognitive tests three times, and the personality test two times, covering the span from 9 to 16 years. It was found that initial social likeability significantly shapes developmental momentum in cognition and vice versa, especially in the 9- to 11-year period. The second study involved 438 participants from 7 to 17 years, tested twice on attention control, working memory, reasoning in different domains, and once by a Big Five Factors inventory. Extending the findings of the first, this study showed that progression in reasoning is affected negatively by conscientiousness and positively by openness, on top of attention control and working memory influences. The third study tested the relations between reasoning in several domains, the ability to evaluate one’s own cognitive performance, self-representation about the reasoning, the Big Five, and several aspects of emotional intelligence, from 9 to 20 years of age (N = 247). Network, hierarchical network, and structural equation modeling showed that cognition and personality are mediated by the ability of self-knowing. Emotional intelligence was not an autonomous dimension. All dimensions except emotional intelligence influenced academic performance. A developmental model for mind-personality relations is proposed.
Multi-physics Simulation of Heat Transfer in Pulse Electrochemical Machining (PECM) Process

A multi-physics model is presented for numerical simulation of temperature evolution during quasi steady state (QSS) in pulse electrochemical machining (PECM) process. A fluid model consisting of wall-model and Reynolds-averaged Navier-Stokes equations is used for solving low-Re electrolyte flow near the wall and turbulent flow of electrolyte in the middle channel. A method that the boundary conditions and bulk sources are averaged in time is introduced to make the time-steps not dictated by the time scale of the pulses and SS calculations cheap. The influence of reaction heat sources, joule heat source and inlet flow rate on temperature evolution has been investigated. Simulation results indicate that the influence of reaction heat source on electrode temperature is greater than the eletrolyte and most of the joule heat is carried away by the electrolyte flow.
Transition from Classic/Traditional to Agile: Critical Steps for Smooth Transition

The Internet economy has altered the rules of software engineering. Traditional development methodologies are too cumbersome to meet the rapidly changing requirements and short product cycles demanded by business. This paper introduces critical steps required for smooth transition from classic software development model to agile methodology as per my experience in service organization such as HCL Technologies that needed to learn agile methodology to support the transition. It also lists the popular methodologies, metrics that matter and agile estimation and planning techniques. Finally, it summarizes the whole paper. KEYWORDS: Classical Model, Agile Model, Transformation, Agile Methodologies, Metrics, Estimation And Planning.
Automatic Mapping of Student 3D Profiles in Software Metrics for Temporal Analysis of Programming Learning and Scoring Rubrics

The purpose of this chapter is to present an online system for a 3D representation of programming students’ profiles on software metrics that quantify effort and quality of programming from the analysis of source codes. In this representation, each student profile is a three-dimensional vector represented by a set of programming solutions developed by a student and mapped on 348 metrics of software during a programming course. Applying this profile representation, we developed a system with the following functionalities: generation of student’s timelines to verify the evolution of metrics in a sequence of programming solutions over a course, different visualizations of these variables, automatic selection of representative codes for composition of rubrics with less effort of evaluation and selection of metrics that more influence in scores attributed by teachers. The advantages of this system are to enable the analysis of where the learning difficulties begin, the monitoring of how a class evolves along a course and the dynamic composition of rubric representations to inform assessment criteria. The system proposed therefore presents itself as a relevant tool to assist teachers about decisions of an evaluative process, allowing in fact to assist students from the beginning to the end of a course.
Using Karaoke to Enhance Recognition of Chinese Words: A Cross-Languages Adoption

This study investigated the effects of Chinese karaoke on recognition and retention of the Chinese characters/words by the Iranian male junior high school learners (N=61, p<.05). In a posttest control group design, students in three English language institutes in Tehran were randomly divided into three groups of Text-only which received the Chinese words via merely a text; Song group which were taught the words via an audio song as well as the text; and finally, Karaoke group which received the words by karaoke, plus the text. The lessons were instructed in two consecutive 20-minute long periods at the end of their routine English classes. The subjects then were tested for their recognition of the 24 Chinese words in question. A One-way ANOVA was run to analyse the scores of the participants. The results revealed that students under Karaoke obtained significantly higher scores as compared to both Text-only and Sound groups. The results, however, did not show any significant difference between the scores of the Text-only and Sound groups. Furthermore, based on the experiment design of this study, this paper advocates consideration of the Arabic writing system as a substitute for the Romanized Pinyin when teaching Chinese to language learners who are familiar with Arabic.
The changing demand for skills in the Netherlands

This study examines the wage returns and changes in the returns for workers employed in occupations that are intensive in tasks requiring non-routine analytical and non-routine interpersonal skills in the Netherlands during the period 2001-2016. We match measures of skills from the US O*NET system to the International Standard Occupation Classification (ISCO). We combine these data with information on employment and wages from administrative data from Statistics Netherlands. We document an increase in the returns to analytical skills, from 9.4 percent in 2001 to 16.0 percent in 2016. Quantile regressions show that the increase in returns from analytical skills can be observed for workers in the lower-, middle-, as well as upper-end of the wage distribution. These findings suggests that non-routine analytical skills are increasingly rewarded on the Dutch labour market. This is consistent with the idea that computer technologies are complementary to the skills required to perform non-routine tasks. With respect to interpersonal skills, we only document a small increase in the wage premium for full-time workers in the upper-end of the wage distribution, from 5.8 percent in 2001 to 7.4 percent in 2016. This finding suggests that increased organisational complexity – induced by technological advances – has put greater demands on interpersonal and managerial skills.
Echocardiography in Different Clinical Situations Appropriate use to do Better

In the last 5 decades the utilization of ultrasound has greatly developed into echocardiography, generating a confused picture of the echocardiographic technique, with patients who do not always receive the right echocardiogram. Previous publications have reported a proposal for reclassification of Echocardiography based on function, competence, applications, proper machines and purposes is intended to give a coherent and adequate definition of requirements, in order to have appropriate use of the technique related to place where it is used, the clinical situation, the related function, the information expected, the exam indications and the educational pathway and requirements for the accreditation of the operators and echo-labs. In this paper we revisit these proposals emphasizing the importance to use echo properly and appropriately as well as the need to acquire accreditation through a defined educational pathway and training and the possibilities to use it widely in different clinical conditions.
The Influence of Training on Business Performance of Women Entrepreneurs: The Mediating Role of Innovation

This study examined the effect of Training (TR) on the Business Performance (BP) of women in Nigeria using Innovation (I) as a mediator in order to improve the business performance of women which in the long-run contribute positively towards the increase of the Nigerian GDP. Data required for the study was collected from the Women Micro, Small and Medium Enterprises (MSMEs) operating in the North-Western States of Nigeria using a survey design and stratified disproportionate sampling. A designed questionnaire has been distributed across the target population of 576 respondents through self-administration. In order to evaluate the proposed data, the study has adopted the Partial Least Squares-Structural Equation Modelling (PLS-SEM). The findings revealed that the mediating effect of Innovation on Training is an important strategic element for the enhancement of business performance among women in the MSMEs in Nigeria. The findings also revealed that the business performance of women in the MSMEs depends on the degree of Training that the women attend. Innovation was found to mediate the effects between Training and Business Performance of women. The findings of this study have provided important insights to women owners/managers of the MSMEs, policy makers and researchers to further understand the effects of Training on Innovation and the Business Performance of women in the MSMEs. Thus, women should also be encouraged to improve their Training on Innovation which may increase their business performance.
Sub-Acute and Sub-Chronic Effect of Chlorantraniliprole (Coragen® 20% SC) on Albino Rat

Pest control has been achieved by chemical pesticides for more than 70 years but their efficiency is decreased as a result of insecticides resistant problems and environmental concern. The significant increase in pesticide use has increased concerns about potentially adverse effects on human health and the environment. Therefore, alternative insecticides with a new mode of action are needed. The present work aimed to evaluate the toxic effect of the insecticide, chlorantraniliprole (Coragen® 20%SC) on liver and kidney biochemical parameters of albino rats with different sub-acute and sub-chronic doses. The pathological parameters of sub-acute and sub-chronic liver, kidneys and protein profile changes by chlorantraniliprole were assessed. Generally, the tested compound caused a slight decrease in body weight as compared with untreated ones. Also, it caused an increase in AST and ALT activities urea and creatinine. Therefore, a decrease of albumin, globulin and blood calcium content was observed. The present results also clarify our need to avert exposure of humans to chlorantraniliprole and recommend that all pesticides no matter how safe they are must be assessed for their toxicity.
Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting

In day-ahead electricity price forecasting (EPF) variable selection is a crucial issue. Conducting an empirical study involving state-of-the-art parsimonious expert models as benchmarks, datasets from three major power markets and five classes of automated selection and shrinkage procedures (single-step elimination, stepwise regression, ridge regression, lasso and elastic nets), we show that using the latter two classes can bring significant accuracy gains compared to commonly-used EPF models. In particular, one of the elastic nets, a class that has not been considered in EPF before, stands out as the best performing model overall.
Shoal: A Network Architecture for Disaggregated Racks

Disaggregated racks comprise a dense cluster of separate pools of compute, memory and storage blades, all inter-connected through an internal network within a single rack. However, their density poses a unique challenge for the rack’s network: it needs to connect an order of magnitude more nodes than today’s racks without exceeding the rack’s fixed power budget and without compromising on performance. We present Shoal, a power-efficient yet performant intra-rack network fabric built using fast circuit switches. Such switches consume less power as they have no buffers and no packet inspection mechanism, yet can be reconfigured in nanoseconds. Rack nodes transmit according to a static schedule such that there is no in-network contention without requiring a centralized controller. Shoal’s congestion control leverages the physical fabric to achieve fairness and both bounded worst-case network throughput and queuing. We use an FPGA-based prototype, testbed experiments, and simulations to illustrate Shoal’s mechanisms are practical, and can simultaneously achieve high density and high performance: 71% lower power and comparable or higher performance than today’s network designs.
RedTyp: A Database of Reduplication with Computational Models

Reduplication is a theoretically and typolog-ically well-studied phenomenon, but there is no database of reduplication patterns which include explicit computational models. This paper introduces RedTyp, an SQL database which provides a computational resource that can be used by both theoretical and computational linguists who work on reduplication. It catalogs 138 reduplicative morphemes across 91 languages, which are modeled with 57 distinct ﬁnite-state machines. The ﬁnite-state machines are 2-way transducers, which provide an explicit, compact, and convenient representation for reduplication patterns, and which arguably capture the linguistic generalizations more directly than the more commonly used 1-way transducers for modeling natural language morphophonology.
Migration Policy and Politics in the Receiving States.

This article explores the politics of migration policies in the receiving states. The author finds that "a survey of the politics of immigration in the major receiving states shows a strong pattern of restrictionism in the face of unprecedented pressures for entry but also amnesties exceptions on humanitarian grounds and hesitation to enforce the law. As individual states founder multilateral strategies abound but with scant success.Ironically the failure of states to deal with the crisis may reinforce national prerogatives and capacities with respect to immigration and strengthen rather than erode the distinction between economic migrants and refugees. " (EXCERPT)
Pattern Recognition of Movements on Bed Aimed at Prediction of Bed-leaving Behaviors: —Time-series Feature Learning Using Elman-type Feedback Counter Propagation Networks—

This paper presents a novel machine-learning-based method for bed-leaving detection using Elman-type Feed-back Counter Propagation Networks (EF-CPNs), which is particularly eﬀective for processing time-series signals. In our earlier study, we have proposed a method based on CPNs, a form of supervised model of Self-Organizing Maps (SOMs), to produce category maps to learn relations among input and teaching signals. In this study, we introduce a feedback loop in CPNs as the second Grossberg layer so that the time-series features can be learnt. Moreover, we develop an original caster-stand sensor using piezoelectric ﬁlms to measure, via bed legs, weight changes of a subject on a bed. The developed sensor has the features that it does not require a power supply for operations and can be easily installed on existing beds. We evaluate our sensor system by examining 10 people in an environment representing a clinical site. The mean recognition accuracy is 81.0%, while the mean recognition accuracy for the most important behavior terminal sitting is 98.0%. In view of the fact that most falsely recognized patterns belong to the categories of sleeping and sitting which are not so important for bed-leaving detection, we believe that the developed system can be applied to an actual environment as a novel sensor system requiring no restraint of patients.
Non-local mean filtering algorithm based on deep learning

Aimed at the problem that the traditional image denoising algorithm is not effective in noise reduction, a new image denoising method is proposed. The method combines deep learning and non-local mean filtering algorithms to denoise the noisy image to obtain better noise reduction effect. By comparing with Gaussian filtering algorithm, median filtering algorithm, bilateral filtering algorithm and early nonlocal mean filtering algorithm, the noise reduction effect of the new algorithm is better than the traditional method and the peak signal to noise ratio is compared with the early non-local mean algorithm. The performance is better.
Binary clusters produced with cluster beam deposition for electrochemistry and heterogeneous catalysis

This thesis describes the production, characterisation and catalytic performance of nanoclusters fabricated by cluster beam deposition using the magnetron sputtering, gas condensation technique. \(MoS_{2}\)-based clusters and Au-based clusters are demonstrated in electrochemistry (HER) and gas phase heterogeneous catalysis (CO oxidation), respectively. The atomic structure analysis of the clusters was performed with aberration-corrected scanning transmission electron microscope with high angle annular dark field (HAADF-STEM). Size-controlled \((MoS_{2}\)\()_{300}\) clusters deposited on amorphous carbon present an incomplete multi-layer structure with the absence of extended crystalline order. Such a layered structure was also found in \(Ni-MoS_{2}\) hybrid clusters [with a mass corresponding to \((MoS_{2}\)\()_{1000}\)] produced by dual target magnetron sputtering. Compared with \(MoS_{2}\) clusters, a significant enhancement in HER activity by \(Ni-MoS_{2}\) hybrid clusters was found. However, both \(MoS_{2}\) clusters (Mo:S = 1:0.9) and \(Ni-MoS_{2}\) clusters (Mo:S = 1:1.8) present a sulphur-deficient composition. In order to overcome the sulphur deficiency of the \(MoS_{2}\) clusters, a sulphur-enrichment technique based on a combination of sulphur addition (by sublimation) and annealing inside the cluster beam vacuum chamber was performed on size-selected \((MoS_{2}\)\()_{1000}\) clusters. This process led to a notable increase in extended crystallinity and a moderate increase in size (from 5.5 nm to 6.0 nm in diameter). Compared with \(Ni-MoS_{2}\) clusters, the sulphur-enriched \(MoS_{2}\) clusters show even more enhancement on the HER activities with more than 30-fold increases in exchange current densities. We have demonstrated a method of inhibiting the sintering of Au clusters in Au-based catalysis by exploring the stabilisation of supported Au clusters against sintering by alloying with Ti. Size-selected \(Au_{2057}\) (405, 229 amu) clusters and similar mass Au/Ti nanoalloy clusters (400, 000 amu) were produced by cluster beam deposition onto thin silica films. A strong anchoring effect was found in the case of Au/Ti clusters by HAADF-STEM experiments, consistent with DFT calculations by collaborators. Different sintering mechanisms were revealed between Au cluster dimers and Au/Ti cluster dimers. Preliminary CO oxidation measurements on Au and Au/Ti clusters indicates that Au/Ti clusters are promising as catalysts. Au/Ti clusters show catalytic activity on CO oxidation while Au clusters are non-active due to the serious sintering and the support effect.
Evaluation of depression frequency and temperamental characteristics in parents of children and adolescents with major depression

Depressive disorders in children and adolescents are caused by various risk factors. It is believed that the mood and temperament characteristics of the parent play a pretty decisive role on the relationship between the child, adolescent and their parents. The aim of this study is to examine the frequency of depression and temperament in parents of children and adolescents with major depression diagnosis. Parents of 102 children and adolescents between the ages of 7-18 with major depressive disorder were included in the study. Child Depression Inventory (CDI), Beck Depression Inventory (BDI), socio-demographic data form, and Temperament Assessment Scale (TEMPS-A) were applied to the children, adolescents and parents respectively. 86 (84.3%) mothers and 16 (15.7%) fathers were included in the study. Of the children and adolescents, 76 (74.5%) were girls and 26 (25.5%) were boys. The mean age of children and adolescents was found to be 14. 3Â±2.3 years. The mean age of parents was found to be 40. 3Â±6.16 years. In all cases, the number of patients with depression in their parents was 55 (53.9%). Depression scale scores were higher in the children of depressed parents (p=.000). Significant positive correlation was found between CDI scores of children and BDI scores of parents and between BDI scores adolescent and BDI scores of parents (consecutively r= 0.700, p= 0.000; r= 0.663, p