Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic Role Labeling in Chinese Using HowNet

Semantic Role Labeling (SRL) has significant impact on many application systems, such as Machine Translation, Information Extraction, Question-Answering, Text Summarization and Text Data Mining. Therefore research on SRL is important for natural language understanding, and so far a number of algorithms, mostly statistically oriented, have been proposed in this field. Statistical algorithms must deal with the problem of data sparseness. In our initial study, we found that most words appear only a small number of times, and other words are absent completely in the training set. Only a small number of frequent words supply sufficient data for training. To solve this problem, we developed a backoff model based on HowNet. In this study, we demonstrate the benefit of applying the knowledge from HowNet to Semantic Role Labeling by experimenting with four selected Chinese words. Our system employs a statistical approach, which was trained on 208 sentences and tested on 89 sentences. We extracted various lexical and syntactic features, including the phrase type of each constituent, the headword, and the position and distance from the predicate to the constituent in question and voice. Comparing the result with knowledge support of HowNet to the result without it, we found distinct improvement when using HowNet. The study also reveals that the system can be improved by applying more information from HowNet, introducing full parsing information, enriching the feature set, and using more appropriate probability estimation model.
Electrostrictive Mechanism of Radiation Self-Action in Nanofluids

The electrostriction mechanism of beam self-focusing in nanofluids is theoretically investigated. An analytical solution of the diffusion equation, which describes the dynamics of particles in nanofluids, was obtained and studied. Explicit expressions for the nonlinear part of the refractive index and concentration lens focal length are presented. It is shown that there is a limit on the radiation intensity associated with the physical and hydrodynamic characteristics of the phenomena in these processes.
Trade Openness and Gender Discrimination

This paper investigates the impact of trade liberalization on gender wage discrimination. We employ a simple method that is able to capture the direct impacts of openness at the industry level on the gender wages. We find evidence that increasing openness is associated with narrowing wage gap, which results mainly from men's wages declining. This is consistent with the Becker's (1957) proposition that competition reduces discrimination in the labor market.
An Improved KNN Classification Algorithm based on Sampling

K nearest neighbor (KNN) algorithm has been widely used as a simple and effective classification algorithm. The traditional KNN classification algorithm will find k nearest neighbors, it is necessary to calculate the distance from the test sample to all training samples. When the training sample data is very large, it will produce a high computational overhead, resulting in a decline in classification speed. Therefore, we optimize the distance calculation of the KNN algorithm. Since KNN only considers the k samples of the shortest distance from the test sample to the nearest training sample point, the large distance training has no effect on the classification of the algorithm. The improved method is to sample the training data around the test data, which reduces the number of distance calculation of the test data to each training data, and reduces the time complexity of the algorithm. The experimental results show that the optimized KNN classification algorithm is superior to the traditional KNN algorithm.
ANALISIS KUALITAS AUDIT TERHADAP MANAJEMEN LABA AKUNTANSI: STUDI PENDEKATAN COMPOSITE MEASURE VERSUS CONVENTIONAL MEASURE

This study investigates the effect of audit quality on earnings management behavior using a variety of audit quality proxies, either using a single proxy or a joint test of some proxies of audit quality. The study proposed a new composite measure of audit quality called the Audit Quality Metric Score (AQMS), which represents the dimension of competence and independence of audit quality. The study compared the validity of the conventional and the multidimensional measurement of audit quality. With a sample of 1,152 firm-years panel data of non-financial companies listed in the Indonesia Stock Exchange (IDX) for the year 1999-2007, the study found a negative effect of audit quality over the accrual earnings management, whether using conventional or multidimensional measures of audit quality. These findings are consistent with the previous findings. The study did not find evidence that composite measure of audit quality has higher validity than conventional measures. Rather, we found evidence that Big 4 as a single proxy of audit quality has higher validity compared to the other proxies or using AQMS. The findings of this study are robust due to sensitivity test that support the main findings. Keywords: accrual earnings management, audit quality, composite measure, audit quality metric score (AQMS) --- Penelitian ini menguji pengaruh kualitas audit terhadap perilaku manajemen laba menggunakan sejumlah proksi kualitas audit, baik menggunakan proksi tunggal maupun pengujian bersama dari beberapa proksi kualitas audit. Studi ini mengajukan sebuah pengukuran kualitas audit baru berupa pengukuran kualitas audit composite yang disebut Audit Quality Metric Score (AQMS), yang merepresentasikan dimensi kompetensi dan independensi dari kualitas audit. Studi ini membandingkan validitas ukuran kualitas audit yang bersifat multidimensi dengan ukuran konvensional. Dengan menggunakan sampel 1.152 tahun- perusahaan dari perusahaan terdaftar non-keuangan di Bursa Efek Indonesia (BEI) untuk data panel tahun 1999-2007, studi ini menemukan pengaruh negatif kualitas audit terhadap manajemen laba akrual, baik menggunakan pengukuran kualitas audit konvensional maupun multidimensi. Temuan ini konsisten dengan temuan penelitian sebelumnya. Studi ini belum menemukan bukti bahwa pengukuran multidimensi kualitas audit memiliki validitas yang lebih tinggi dibandingkan pengukuran konvensional. Sebaliknya, ditemukan bukti bahwa Big 4 sebagai pengukuran kualitas audit tunggal memiliki tingkat validitas yang lebih tinggi dibandingkan dengan proksi-proksi lainnya maupun menggunakan AQMS. Temuan studi ini bersifat robust setelah mempertimbangkan hasil pengujian sensitivitas yang mendukung temuan pengujian utamanya. Kata kunci: manajemen laba akrual, kualitas audit, pengukuran composite, audit quality metric score (AQMS)
Cook’s Local Influence in Generalized Linear Models via the Shape Operator

In this paper we develop an algorithm for assessing the effect of small perturbations of the data on the validity of a postulated generalized linear model. The procedure is based on the geometric notion of shape operator, a single mathematical object that gathers together all the normal curvatures of a given influence graph or hypersurface. In addition to introducing relevant theoretical notions and explaining the foundations of the local influence assessment method in a generalized linear model with a canonical link, we provide a detailed example of application together with the explicit R code implementing the algorithm.
COLLABORATION IN SMART SERVICES – THE RIGHT WAY TO GO?

Many current manufacturers provide not only tangible products to their customers, but also services which are accompanying their products. Moreover, manufacturers add smart services to their service offerings. Applying the change toward smart services is not easy, especially in SMEs where many of businesses struggle with lack of money, insufficient digital technologies or unskilled employees. The aim of the study mentioned in this paper explores current situation in SMEs and their attitudes related to collaboration with other subjects on their markets. To address the research objective, a qualitative multi-case study was conducted among seven Czech electrotechnical SMEs, which have already started with smart service development. The findings can indicate two approaches of collaboration based mostly on the owners’ enthusiasm for smart services, management’s age and the length of running their business. The study is unique in highlighting the problems of smart services in SMEs in the Czech Republic, where the industrial sector is still dominant in comparison to other European countries.
The use of new technologies among in-service Colombian ELT teachers

This study reports on the impact of the Masters in english language Teaching with an emphasis on Autonomous learning environments from the Universidad de la Sabana. The report highlights how graduates from 12 cities from 9 departments throughout Colombia are using Information and Communication Technologies (ICT) for english language learning in order to promote autonomy. The data that has been gathered thus far reveals that teachers are becoming much more comfortable in evaluating ICT tools in accordance with their teaching context, the strengths and opportunities of ICT tools and their consequent improvement on language teaching, while promoting the development of autonomous learners.
Short-term Traffic Flow Prediction Method Based on Balanced Binary Tree and K-Nearest Neighbor Nonparametric Regression

Real-time and accurate short-term traffic flow prediction is a key issue and difficult in traffic control and guidance. Using data mining and large data-driven principle, nonparametric regression is a better method to resolve shortterm traffic flow prediction. But there are two main obstacles that case base is difficult to be generated and search is slow. For this reason, this paper presents a short-term traffic flow prediction method based on balanced binary tree and KNEAREST NEIGHBOR NONPARAMETRIC REGRESSION (KNN2NPR). Case base is generated through clustering method and balance binary tree structure. K-nearest neighbor nonparametric regression improves accuracy of prediction and fulfills the real-time requirement. The prediction example in this paper demonstrates that this method is effective. Keywords-short-term traffic flow prediction; nonparametric regression; clustering; balanced binary tree
Neighbors Can Make You Sick: Hygiene Behavior and Health

While the rst order eects of access to clean water, and of personal hygiene and sanitation on health have been well documented, the eects of community hygiene and sanitation, along with personal hygiene and sanitation, have not been comprehensively studied. In this paper, incorporating the features of models from agricultural household (Bardhan and Udry, 1999) and reciprocal externalities (Dasgupta, 1993), we present a simple model of health externalities of households’ hygiene and sanitation, showing how the choices of one household aects ill-health incidences of other households. Then using micro level survey data of 1,530 households in rural Uttarakhand, India, we show that both household and community hygiene are signicant inputs in the determination of households’ ill-health incidences (i.e. diarrhea, cholera, typhoid, dysentery, worm infestation and jaundice), with the latter having greater impact than the former, over and above eects attributable to households’ socioeconomic status. That is, there is a large health externality of a household’s hygiene and sanitation. In the presence of such health externality of households’ hygiene and sanitation, which is strongly associated with the access to safe water, universal access to safe water may be required to combat water-related illnesses. This implies that the governments’ consideration of alternative proposals to improve water services must be informed by health externalities in households’ hygiene and sanitation, and in the provision of water across communities.
Reconnoitering the Influence of Socio-demographic Factors on Internet Addiction

Internet addiction (IA) has gradually emerged as a detrimental mental health problem, especially amongst youngsters. The current study endeavoured to ascertain the determinants of IA amidst this at-risk population, by conducting an exploratory cross-sectional study among 307 undergraduate students of a public university. Information about sociodemographic characteristics, Internet usage patterns, and responses to Internet Addiction Test (IAT) were gathered through self-report questionnaires. Findings indicated no significant gender difference in the IA scores. Time spent online and academic achievements were found to be significantly associated with IA, across gender. Regression analysis indicated that only race/ ethnicity profile (for male students), time spent online (for female students) and monetary expenditure on internet usage (across gender) were independent predictors of IA. Considering that gender differences in IA were not highlighted by the present study, further studies are recommended so as to have a thorough understanding of IA amongst the susceptible younger demographic.
Empirical Evaluation of Classifiers' Performance Using Data Mining Algorithm

The field of data mining and knowledge discovery in databases (KDD) has been growing in leaps and bounds, and has shown great potential for the future[10]. Data classification is an important task in KDD (knowledge discovery in databases) process. It has several potential applications. The performance of a classifier is strongly dependent on the learning algorithm. In this paper, we describe our experiment on data classification considering several classification models. We tabulate the experimental results and present a comparative analysis thereof. Key word- Knowledge discovery in databases, classifier, data classification.
MICROSATELLITE-BASED SIBSHIP RECONSTRUCTION AND ESTIMATION OF GENETIC RELATEDNESS IN THE ENDANGERED LABEO CALBASU (HAMILTON 1822) (CYPRINIDAE: CYPRINIFORMES)

The microsatellite genotyping technique was used to reconstruct sibship and estimate pairwise relatedness among individuals of Labeo calbasu collected from four natural and one hatchery stocks. The mean values for the number of alleles, observed and expected heterozygosity and polymorphic information content of the five microsatellite markers used for genotyping 165 individuals were 6.00, 0.622, 0.743 and 0.699 respectively. Deviation from HardyWeinberg expectation was detected at four of the five loci. The number of reconstructed half-sib family was lowest in the Hatchery sample. The number of full-sib family was lowest in the Jamuna river sample and highest in the Haor sample. The numbers of reconstructed families were fewer in the real sample compared to the simulated sample of the same number of unrelated individuals. The mean relatedness coefficients rxyW was found to be highest in the Jamuna river sample and lowest in the Hatchery sample, though no difference was observed in mean rxyLR values of the five samples. The misclassification rates estimated based on the relatedness coefficients were found to be quite high, ranging from 11.17 (Unrelated-Fullsib) to 32.02% (Halfsib-Fullsib) and more loci need to be analyzed for accurate separation of related individuals from unrelated ones.
Internet usage among undergraduate nursing students: A case study of a selected university in South Africa

Background: Globally, the internet is becoming an increasingly indispensable tool in academic institutions and the workplace. Nursing students are required to use the computer and the internet to search for information and to use various software, for which computer and internet literacy are essential. Despite becoming an important tool for teaching and learning, literature reflects an under-utilization of the internet in academic and non-academic settings for a number of reasons. This article explores the general internet usage of undergraduate nursing students at a selected university in South Africa. Methods: A quantitative, non-experimental, exploratory descriptive design was used, with 115 undergraduate nursing students participating in the study. Data was collected using a questionnaire survey after obtaining ethical clearance from the university’s ethics committee and were analysed descriptively. Results: The findings revealed that the internet was used for various purposes including; academic (96.5%); communication (82.6%), pleasure (71.3%), and work-related activity (53.9%). Facebook (77.4%) was the most commonly used social network. Constraints encountered in using Barriers to the use of the internet include restriction of access to certain sites (62.6%), very slow internet connection (55.7%), little training on how to use internet facilities (38.3%), and a limited number of computers (37.4%). Conclusions: Contrary to other studies, this study shows that students do use the internet for a number of reasons, and recommend structured support on how to use if for academic purposes.
Fast Luminosity Monitoring using Diamond Sensors for the Super Flavor Factory SuperKEKB

Super luminous flavor factories, as SuperKEKB in Japan, aim to achieve very high luminosity thanks to a newly employed concept, the nano-beam scheme, where ultra-low emittance beams collide at very large crossing angle. Luminosity optimisation and dynamic imperfections require fast luminosity measurements. The aimed precision, 10 3 in 10 ms, can be achieved thanks to the very large cross-section of the radiative Bhabha process at zero-photon scattering angle. As a result of huge particle fluxes, diamond sensors are chosen to be placed just outside the beam-pipe, downstream of the interaction point, at locations with event rates consistent with the aimed precision and small enough contamination by backgrounds from single-beam particle losses. We will present the results concerning the investigation of the optimal positioning of our diamond sensors, taking into account the rate of Bhabha particles as well as their interactions with the beam pipe material.
Simulation of low-depth quantum circuits as complex undirected graphical models

Near term quantum computers with a high quantity (around 50) and quality (around 0.995 fidelity for two-qubit gates) of qubits will approximately sample from certain probability distributions beyond the capabilities of known classical algorithms on state-of-the-art computers, achieving the first milestone of so-called quantum supremacy. This has stimulated recent progress in classical algorithms to simulate quantum circuits. Classical simulations are also necessary to approximate the fidelity of multiqubit quantum computers using cross entropy benchmarking. Here we present numerical results of a classical simulation algorithm to sample universal random circuits, on a single workstation, with more qubits and depth than previously reported. For example, circuits with $5 \times 9$ qubits of depth 37, $7 \times 8$ qubits of depth 27, and $10 \times (\kappa > 10)$) qubits of depth 19 are all easy to sample. We also show up to what depth the sampling, or estimation of observables, is trivially parallelizable. The algorithm is related to the "Feynmann path" method to simulate quantum circuits. For low-depth circuits, the algorithm scales exponentially in the depth times the smaller lateral dimension, or the treewidth, as explained in Boixo et. al., and therefore confirms the bounds in that paper. In particular, circuits with $7 \times 7$ qubits and depth 40 remain currently out of reach. Follow up work on a supercomputer environment will tighten this bound.
Investigations on Multiscale Fractal-textured Superhydrophobic and Solar Selective Coatings

Functional coatings produced using scalable and cost-effective processes such as electrodeposition and etching lead to the creation of random roughness at multiple length scales on the surface. The first part of thesis work aims at developing a fundamental mathematical understanding of multiscale coatings by presenting a fractal model to describe wettability on such surfaces. These surfaces are described with a fractal asperity model based on the Weierstrass-Mandelbrot function. Using this description, a model is presented to evaluate the apparent contact angle in different wetting regimes. Experimental validation of the model predictions is presented on various hydrophobic and superhydrophobic surfaces generated on several materials under different processing conditions. Superhydrophobic surfaces have myriad industrial applications, yet their practical utilization has been severely limited by their poor mechanical durability and longevity. Toward addressing this gap, the second and third parts of this thesis work present low cost, facile processes to fabricate superhydrophobic copper and zinc-based coatings via electrodeposition. Additionally, systematic studies are presented on coatings fabricated under different processing conditions to demonstrate excellent durability, mechanical and underwater stability, and corrosion resistance. The presented processes can be scaled to larger, durable coatings with controllable wettability for diverse applications. Apart from their use as superhydrophobic surfaces, the application of multiscale coatings in photo-thermal conversion systems as solar selective coatings is explored in the final part of this thesis. The effects of scale-independent fractal parameters of the coating surfaces and heat treatment are systematically explored with respect to their optical properties of absorptance, emittance, and figure of merit (FOM). Investigations on Multiscale Fractal-textured Superhydrophobic and Solar Selective
Evaluation of soybean meal as protein source for Argyrosomus Regius (Asso, 1801) (Sciaenidae)

The meagre (Argyrosomus regius) is a carnivorous fish which requires diets with higher protein content, causing an increment in diets cost. A way to diminish this cost is to use vegetable meals like soybean meal (SB). So the aim of this trial was to determine the optimum inclusion level of defatted soybean meal in experimental diets for this species. 800 fishes (165 g) were distributed in 8 tanks, two replicates per treatment. Four isoproteic (50% CP) and isolipidic (17% Cl) diets were formulated with four levels of soybean meal inclusion, 0, 15, 30 and 45%. The trial lasted 107 days. Meagre fed diets 15 and 30% obtained the highest final weight. There were no significant differences among treatments in the feed conversion rate (FCR) and the protein efficiency (PER). According to the quadratic regression, the optimum SB inclusion to maximize thermal growth coefficient (TGC) was 26.4% and for FCR was 27.6%. No significant differences were observed in energy, protein and amino acid retention among diets. The inclusion of SB in meagre diets can generate a decrease in the use of fish meal and in turn reduce the cost of producing meagre Mediterranean aquaculture industry. Key words: Argyrosomus regius, fish meal replacement, defatted soybean meal, economic analysis.
The Effect of Camera and Light Source Characteristics on Image Quality in Machine Vision Application in Food Industry

Machine vision technology has been used in a variety of agricultural and food industries applications ranging from planting and postharvest operations to food processing and inspection. High quality image has an essential role in successful application of machine vision technology. To acquire the best image for a specific application, an appropriate camera along with correct light source must be chosen. In the present work, two different types of light sources, namely LEDs and Fluorescent along with two models of camera namely, Proline and Telecam were used. The completely randomized experiment was carried out and 10 standard RAL white card images were captured during each treatment. The RGB values of images were extracted by Image processing toolbox of Matlab software. Comparisons were made between these values and those of standard card values i.e. 255 using SPSS software. LEDs along with camera Telecam proved to be an appropriate combination if high quality images are desired.