Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstrator of Automatic Minuting

This paper introduces the approach of team ABC for the ﬁrst shared task on Automatic Minuting (AutoMin) @ Interspeech 2021. This shared task aims to create minutes from multiparty meetings. Automatic Minuting is a challenging task in the domain of natural language processing and sequence-to-sequence transformation. In Task A, we generated rational minutes from a given meeting transcript by developing a system that utilizes the knowledge of pre-trained language models to generate dialogue summaries. Our model splits the given transcript into multiple pairs of utterances and roles (speakers). These pairsarethensummarizedindependentlybyapretrainedBART model. Our proposed system generates the briefest and detailed summary of meeting transcripts concerning coverage, adequacy, and readability. The result for this task was amongst the best in Human Evaluated Scores: Adequacy: 4.46/5.00, Grammatical: 4.45/5.00, Fluency: 4.18/5.00, and Automatic Evaluated Scores: ROUGE-1: 0.28, ROUGE-2: 0.07, ROUGE-L:0.16. Furthermore, We used six similarity matrices to determine whether or not a derived minute is from the given tran-scriptsorthegivenminute(TasksBandC). Theaccuracyscores of tasks B and C were 95.00% and 91.00%, respectively. Index Terms: automatic minuting, summarization
Effects of Fiber Content on Mechanical Properties of UHPFRC with Coarse Aggregates

: Ultra-High Performance Fiber Reinforced Concrete (UHPFRC) is a relatively new construction material with superior mechanical properties. The addition of fibers in UHPFRC has been recognized to significantly enhance its tensile strength, post-cracking ductility and energy absorption capacity. This study investigates the influence of fiber content on the mechanical properties of UHPFRC with coarse aggregates. By applying the Brouwers design method, UHPFRC with a maximum particle size of 8 mm is achieved. The incorporation of coarse basalt aggregates reduces the powder volume fraction in the matrix, and hence brings economic and environmental benefits. Experiments are conducted to investigate the effects of fiber content on the tensile and compressive strengths, as well as the flexural behavior of the UHPFRC. The results show that the compressive strength of the UHPFRC is almost independent on the fiber content. On the contrary, the tensile and the flexural strengths are significantly increased with the increase of the fiber content, and consequently the toughness of the UHPFRC composite has a prominent enhancement with the addition of the steel fibers as well.
A NOVEL FILTER BASED MULTIVARIATE FEATURE SELECTION TECHNIQUE FOR TEXT CLASSIFICATION

Text classification is a technique of assigning the known class label to the unknown textual documents. This technique assign single label or multiple labels to a specific document based on the content in the document. These techniques are used in various applications such as sentiment analysis, authorship analysis, fake news detection and spam email classification. In the text classification process, the words in the documents are considered as features. The most important words which are having more differentiating power are considered in the representation of a document. Identification of such words or features is a primary step in the classification process. The high dimensionality of data description is a primary issue in text classification. Huge number of features in the analysis not only decreases the performance of classification but also increase the computational time. In this work, a new feature selection technique based on Category specific Feature Distribution without Redundancy Information (CFDRI) is proposed to identify best informative features and eliminating the redundant features. The effectiveness of proposed feature selection technique is compared with existing techniques such as mutual information, information gain, chi square and relative discriminative criterion. The traditional Bag of Words technique is used to designate the documents as vectors. Term frequency and inverse document frequency measure is used to compute the vector value in the document vector representation. Various machine learning algorithms such as Decision Tree, Support Vector Machine, Naïve Bayes, k-Nearest Neighbour, Logistic Regression and Random Forest are used to generate the learned model. Six popular text classification datasets are used in this experiment to train different learning algorithms. The proposed feature selection technique obtained best accuracies for text classification when compared with the popular solutions for text classification.
SOLVING SUDOKU USING ARTIFICIAL NEURAL NETWORKS

- This paper provides an overview of different models of artificial and convolutional neural networks and discusses the advantages of using the Adam optimizer over some other optimization algorithms. Proposed ANN models will be used for solving a Sudoku game. A detailed analysis of data processing before model training is given, and a comparison of the obtained results is made.
Multiple Piecewise Constant Active Contours for Image Segmentation using Graph Cuts Optimization

In the paper a multiple piecewise constant (MPC) active contour model is proposed to extract foreground and background of digital images. The region-based model of active contour without edges, i.e. the CV model [11] has difficulties to handle images having inhomogeneous object and background or multiple objects with different features such as color, texture or shape. Based on CV model we propose to model the interior and exterior of the evolutional curve by multiple constant intensity values instead of one constant. The constants can be obtained by clustering the interior region and the exterior region into multiple sub-regions. For better boundary capture capability, the geodesic active contour (GAC) is incorporated into the proposed MPC model to constraint the evolution of the curve. We show that the new model can be effectively solved by the graph cuts algorithms with less computational costs. Numerical experiments show that the new model can effectively segment difficult images with inhomogeneous object and background, and has superior performance compared to the original CV model. The introduction of GAC into the proposed MPC model is also demonstrated to have better boundary locating properties
Nutritional Status of Children under Five Years of Age among Internally Displaced Populations and Non-displaced in Burkina Faso

The objective of this study was to assess the nutritional status of displaced and non-displaced children in a context of security crisis in North Center of Burkina Faso. The study population comprised 205 internally displaced children and 167 non-displaced children, all aged 6 to 59 months, and their mothers/primary caregivers living in the commune of Kaya in North Center of Burkina Faso. Children were selected using a two-stage cluster sampling procedure. This cross-sectional study was carried out between June-July 2020. Demographic characteristics, child nutrition and health status, and maternal and household information were collected from mothers through interviews. The distribution of different nutritional status, such as underweight, stunting and wasting and malnutrition-related factors was analyze. The overall prevalent rates of underweight, wasting and stunting were 20.4%, 13.7% and 33.6%, respectively. In the group of displaced children, these were 21.5%, 12.2% and 37.1%, while in the non-displaced, they were 19.2%, 15.6% and 29.3%, respectively. The mean nutritional indices were found to be significantly lower among the displaced children than non-displaced ( P <0.001). The present study revealed that in the multivariate analysis, diarrhoea and ARI, mother’s BMI < 18.5 kg/m 2 , LBW < 2.5 kg, household size of five and above using a latrine and source of drinking water were positively associated with malnutrition of children in both communities. Prevention of malnutrition should be given a high priority in the implementation of the ongoing primary health care programmes with particular attention paid to the displaced populations.
Analytical and Numerical Solutions of the Modiﬁed Coupled Burgers’ Equations

—In this work, we study the coupled Burgers’ equations and the modiﬁed coupled Burgers’ equations, which including nonlinear viscous terms. The Hopf-Cole transfor- mation method is applied to obtain the analytical solutions. The explicit ﬁnite difference schemes are used to evaluate the numerical solutions. In addition, we compare the numerical solutions with the analytical solutions for the selected initial and boundary conditions. Moreover, the behaviors of the modiﬁed coupled Burger’ equations with varied viscosity coefﬁcients are also investigated.
Oświetlenie skuteczne biologicznie na stanowiskach pracy zmianowej

Potential health risk for health of rotating shift worker could be related to two main categories: circadian rhythm disturbances, which affect irregular sleep-wake rhythm and acute melatonin suppression after exposure to blue light. The important risk factors of shift worker are: excessive fatigue and insomnia, which could lead to limited work performance, errors and occupational accidents. The aim of this article is to present the upto-date knowledge concerning USAGE THE non-visual light effects on human body for designing the biologically effective lighting on shift workstations (Biologically effective lighting on shift workstations). Słowa kluczowe: praca zmianowa, rytm okołodobowy, fotodetekcja wzrokowa, bodziec cyrkadialny
Examining the Effects of Book-Tax Differences on Stock Price Manipulations

Previous studies have reached varying conclusions regarding the implications of earnings management using conventional measurements. Addressing these inconsistencies, this study examines 8,723 firm-years from 2004-2010 and develops a measure of earnings management from book-tax differences that reflects both accruals management and taxable income related earnings manipulations. The new measurement is shown to be more comprehensive than conventional earnings management measures focusing on accruals management alone. We use the new measure to study stock price manipulation and find companies can manipulate share prices because investors do not react instantaneously to earnings management accruals and respond with a positive bias in the current year.
Comparative Analysis of Qualitative and Quantitative Phytochemical Evaluation of Selected Leaves of Medicinal Plants in Jaffna, Sri Lanka

The traditional system of medicine in Sri Lanka has shown much better improvement, has fewer side effects, and is less expensive than modern synthetic drugs in the treatment of many diseases. The objective of the present study was to comparatively evaluate the qualitative and quantitative analysis of phytochemical constituents of leaves of Murraya koenigii (L.) Spreng. , Tinospora cordifolia (Wild) Hook.f. , Enicostemma axillare (Lam) A. Raynal, and Gymnema sylvestre R. Br. were collected from Jaffna District. The shade-dried leaves were powdered and extracted with ethanol using the cold extraction technique. These ethanolic extracts were subjected to phytochemical analysis using recommended laboratory techniques. The one-way analysis of variance (ANOVA) and Tukey's multiple comparisons at probability value (p <0.05) were used in the statistical analysis of the data. Phytochemical screening showed the presence of alkaloids, flavonoids, tannins, terpenoids, steroids, saponins, phenols, and glycosides. Murraya koenigii shows the highest phenol and alkaloid contents (1960.71±66.88 and 19.42±0.26). Enicostemma axillare shows the highest flavonoid and tannin contents (22.27±0.86 and 1.26±0.017). Therefore, E. axillare and M. koenigii can be used as nutraceuticals in traditional medicine.
Practical Nearly-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering

In many graph-clustering applications, over-whelming empirical evidence suggests that communities and clusters are naturally overlapping, calling for novel overlapping graph-partitioning algorithms ( OGP ). In this work, we intro-duce a framework based on two novel clustering objectives, which naturally extend the well-studied notion of conductance to overlapping clusters and to clusters with hybrid vertex- and edge-boundary structure. Our main algorithmic contributions are nearly-linear-time algorithms O (log n ) -approximation algorithms for both these objectives. To this end, we show that the cut-matching framework of (Khandekar et al., 2014) can be extended to overlapping partitions and give novel cut-improvement primitives that perform a small number of s - t maximum ﬂow computations over the instance graph to detect sparse overlapping partitions near an input partition. Crucially, we implement our approximation algorithm to produce both overlapping and hybrid partitions for large graphs, easily scaling to tens of millions of edges, and test our implementation on real-world datasets against other competitive baselines.
Prevalence of the Risk of Cardiovascular and Gastric Problems Among Male Workers of Textile Industries in Relation to Shift Work

Textile industry touches the lives of all people in one or the other ways. In Rajasthan state particularly, textile mills represent an important economic sector. In Pali district, with highest number of textile mills in the state, the work never stops. It is a round the clock operating sector where shift work is highly prevalent. Different shift work systems have potentially different impacts on the health of the workforce, disturbing the circadian rhythm, an essential biological function and also inducing sleep deprivation. This characteristic makes shift work one of the most widespread work environment risk factor. The disruption of circadian rhythm may have an adverse impact on cardiovascular and gastrointestinal functioning of the body. Right from the secretion of acid to digestion of food, appetite and diet, everything gets disturbed. The present study was conducted in textile mill of Pali city with the objective to study the risk of cardiac and gastric problems in relation to shift work among male workers. Total of 400 male workers were studied, out of which 200 were non-shift workers and 200 were shift workers. Anthropometric measurements, food intake, blood pressure and lipid profile of the subjects were taken along with data on cardiac and gastric problems. The results showed significant difference between BMI ( 2 χ =14.2, p=0.0008) and waist hip ratio ( 2 χ =5.2, p=0.0226) of shift and non shift workers. Majority (84.50%) of the shift workers faced sleep related problems. Results on food intake showed comparatively more deficient daily intake of nutrients like fiber (7.21 g), β carotene (1842.89 μg), and folic acid (99.03 ìg) in shift workers with respect to recommended dietary allowances and an overconsumption of fats (37.72 g). Alcoholism ( 2 χ =17.3, p=0.0001) and smoking habit ( 2 χ =14, p=0.0029) was found to be significantly higher among shift workers. Comparatively higher segment of shift workers suffered from hypertension (56.0%), stress (70.50%), disturbed appetite (87.50%), stomach upsets (90.0%), nausea (88.50%), heartburn (85.0%) and breathlessness (34.0%). Shift workers also had higher mean levels of all lipid profile fractions and relatively more subjects fell into the category of high risk (20.50%) of CVD. Based on the results, it can be concluded that shift work affects sleep, food intake, BMI, WHR, BP, stress levels, alcohol intake, smoking habits and lipid profile of the subjects, thus increasing the risk of health problems like cardiovascular and gastric diseases.
A SURVEY OF SOCIAL ENGINEERING ATTACKS: DETECTION AND PREVENTION TOOLS

Rapid, technological advancements have facilitated communication between people and made sensitive information available via networks and social media platforms, which may not be fully protected, facilitating the occurrence of violations and threats via social engineering attacks. The aim of social engineering attacks is to deceive people and corporate workers into revealing their sensitive information such as passwords and usernames, as well as spreading malware. It is easier for criminals to exploit humans' natural tendency to trust rather than using technology and software. Therefore, social engineering attacks are considered one of the most dangerous attacks that violate the privacy and safety of individuals and organizations. The basic principles of social engineering attacks, their stages of implementation, classifications and types, as well as methods and procedures for reducing these attacks, are covered in this study
Political Determinants of the Location Choice and Entry Mode of Chinese Outward FDI

2 CHAPTER 1INTRODUCTION . 7 1.1 Background . 7 1.2 Organization . 9 CHAPTER 210 REVIEW OF LITERATURE . 10 2.1 Political Factors and their Expected Influences . 10 2.2 Tax Factors and their Expected Influences . 17 2.3 Natural Resources and their Expected Influences . 18 CHAPTER 3 DATA . 20 3.1 Sample . 20 3.2 Source of Data . 20 CHAPTER 4 EFFECTS OF POLITICAL FACTORS ON THE LOCATION CHOICE OF CHINESE OUTWARD FDI . 21 4.1 Methodology . 21 4.1.1 Conditional Logit Model . 21 4.1.2 IIA Problem . 22 4.1. 3 Mixed Logit Model . 23 4.2 Control Variables and their Expected Effects . 24 4.3 Empirical Analysis . 28
A Fast Variational Method for Surface Reconstruction from Sets of Scattered Points

This paper introduces an eﬃcient method based on total variation-based functionals to solve the reconstruction problem of closed surfaces from a set of unorganized points in R 2 and R 3 . Recent developments in optimization have provided fast, accurate, and robust algorithms to solve total variation-based problems in imaging. We propose to use the eﬃcient split-Bregman method to solve the problem of surface reconstruction without tuning any parameter and without using any additional information such as surface normals. Our surface reconstruction algorithm can handle dense and sparse collections of data points, while being robust to the presence of outliers. Our experiments show that our algorithm is fast and can recover surface details while using no more and often less information than related methods
Effects of Treasury Single Account on Cost of Revenue Generation in Nigeria

: Treasury Single Account policy is a Public Financial Management reform under the world bank that came into full force in Nigeria in the year 2015, this was aimed at addressing impediments to effective cash management within the Federal Government. The objective of this study is to examine the effect of treasury single account policy on the cost of revenue generated since its inception in Nigeria.The survey research design was adopted in the study. The staff of Accountant General’s office, Auditor General’s office, Central Bank of Nigeria and the Federal Ministry of Finance served as the population of study of which a sample of 389 was determined and copies of the questionnaire were accordingly administered them through judgmental sampling technique. Data collected were analysed using Linear Regression analysis. From the analysis, it was revealed that the Treasury Single Account has significant negativeeffect on cost of revenue generation. The implication of this is that it cost the federal government about N16 billion since adoption and these charges have been pushed back to the citizens by November 2018.In view of this, it is recommended that the Federal Government should intensify its efforts on regulating, harmonizing and if possible absorb portion of these charges to reduce the burden on the citizens.
Clinical implications of a cervical myodural bridge

The existence of a previously unreported nivodural bridge at the level of the atlanto-occipital junction suggests a direct and dynamic central-peripheral connection which na y be directly related to some instances of idiopathic head and neck pain. Artificially functioning the muscular component of the bridge appears to influence the cerebrospinal fluid system by directly affecting dural tension. Because the tnyodural bridge has a direct influence upon the dura mater, a component of the reciprocal tension membrane s ystem that is also a pain-sensitive structure, we propose that it offers a possible association between cervical musculature and headache pain.
A new decade for social changes

In the present study, two time periods were selected to obtain critical data, the first period is 2010-2019, and the second one is 2022. The literature related to winter sports tourism from 2010-2019 and 2022 was checked to review the history of winter sports tourism in China. Winter sports tourism development in China was obtained from 2010-2019 and 2022. The comparative analysis of a large amount of data found that the development of China's winter sports tourism industry is linear, and the overall development level is rising. Before 2015, China's ski resort infrastructure was poor, the number of people involved in winter sports tourism was low, and the demand for winter sports tourism in China had to be met abroad. After Beijing won the right to host the 2022 Winter Olympics and Winter Paralympics in 2015, China proposed to let 300 million people Participation in winter sports, and the country officially vigorously developed the winter sports industry. 2016-2022, China's winter sports tourism heavy asset projects close to 1 trillion, and the total investment reached 2.47 trillion yuan. China's winter sports characteristics in the town gradually increased, improving the construction of ski resort infrastructure, deep excavation of cultural connotations, and active propaganda. Whether the number of people involved in skiing, the category of people involved in skiing, or the level of participants in skiing has a greater changed than before.
BOND GRAPH MODEL – INTELLIGENT ONLINE DIAGNOSTICS FOR EDUCATION

Nowadays, the control of physical systems is the result of many steps, from design to implementation, modelling and analysis, Especially in the field of education and innovation. It is often necessary to know in advance the performance of the system under study and in this case a mathematical model is more than useful. For economic and performance reasons, it is often necessary in certain situations to have a precise representation of physical phenomena, which leads to complex models and the mathematical tools are not always adapted to the models obtained. For several decades, the most exploited representation has probably been the state representation, or an extension of this form for non-linear models. For some time now, the algebraic approach has been used to discover other characteristics of the models, or at least a new interpretation of properties well known to automaticians. However, these techniques are difficult to use for the uninitiated, and the representation by a link graph model allows to reconcile all the theoretical concepts, which are necessary in the different design phases. Some analysis techniques for design are proposed by bond graph modelling for linear models, but can be quite easily generalised for more general models. In this paper, the bond graph tool proves its intelligence in the implementation of monitoring systems, and in particular an intelligent design support. The causal properties of the bond graph allow to analyse the necessary monitoring conditions before and after the design to generate diagnostic algorithms in a generic way. The following approach is illustrated on a DC motor.