Miracle-dz/UniFAR-FTUs huggingface dataset:
Text Mining and Visualization: Case Studies Using Open-Source Tools

Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributorsall highly experienced with text mining and open-source softwareexplain how text data are gathered and processed from a wide variety of sources, including books, server access logs, websites, social media sites, and message boards. Each chapter presents a case study that you can follow as part of a step-by-step, reproducible example. You can also easily apply and extend the techniques to other problems. All the examples are available on a supplementary website. The book shows you how to exploit your text data, offering successful application examples and blueprints for you to tackle your text mining tasks and benefit from open and freely available tools. It gets you up to date on the latest and most powerful tools, the data mining process, and specific text mining activities.
Revisiting Kuznets Hypothesis: An Analysis with Time Series and Panel Data

Significant impact of economic growth on poverty alleviation is eroded by high income inequality. This article revisits Kuznets Hypothesis which suggested that inequality and growth have an inverted U shaped relationship. This article differs from previous articles on this subject, by being broader in scope although remaining exploratory in nature. The article uses log quadratic model and level quadratic model, autoregressive time series analysis and panel analysis, expands the database by covering a time period 1963-1999, and a comparative time-series analysis using the augmented D-S inequality dataset (EHII2.3) and UTIP-UNIDO dataset as proposed by James K. Galbraith and Hyunsub Kum
Practical Percussion A Guide To The Instruments And Their Sources

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Review on Fault Diagnosis Theory and Application Based on Petri Nets

Fault diagnosis is an important research aspect in the area of discrete event system,which has great value to ensuring the safety of systems.Research on fault diagnosis based on Petri nets can be mainly divided into two classes, which are the study on diagnosiability theory and the study on the theory of fault diagnoser constructing algorithm.Similarly,the diagnosiability research can be divided into two aspects:diagnosiability and K-diagnosiability,while fault diagnoser constructing algorithm can also be further classified according to applying systems.Various study methods and conclusions for diagnosability and K-diagnosiability of fault diagnosis were reviewed,and the constructing methods of fault diagnoser in discrete Petri nets systems,continuous Petri nets systems and distributed Petri net systems were introduced,and their characteristics were analyzed in detail.Finally,the research directions and application problems for further study were discussed,which can provide directive significance.
Analyzing Musical Sound

Musicologists have several starting points for their work, of which the two most prominent are text and sound documents (i.e., scores and recordings). One aim of this chapter is to show that there are important properties of sound that cannot be gleaned directly from the score but that may be inferred if the reader can bring to bear knowledge of the acoustic properties of sounds on the one hand, and of the processes by which they are perceptually organized on the other. Another aim is to provide the musicologist interested in the analysis of sound documents (music recorded from oral or improvising traditions, or electroacoustic works) with tools for the systematic analysis of unnotated—and in many cases, unnotatable—musics. In order to get a sense of what this approach can bring to the study of musical objects, let us consider a few examples. Imagine Ravel’s Boléro. This piece is structurally rather simple, alternating between two themes in a repetitive AABB form. However, the melodies are played successively by different instruments at the beginning, and by increasing numbers of instruments playing in parallel on different pitches as the piece progresses, finishing with a dramatic, full orchestral version. There is also a progressive crescendo from beginning to end, giving the piece a single, unified trajectory. It is not evident from the score that, if played in a particular way, the parallel instrumental melodies will fuse together into a single, new, composite timbre; and what might be called the “timbral trajectory” is also difficult to characterize from the score. What other representation might be useful in explaining, or simply describing, what happens perceptually? Figure 8.1 shows spectrographic representations (also called spectrograms) of the first 11 notes of the A melody from Boléro, in three orchestrations from different sections of the piece: (a) section 2, where it is played by one clarinet; (b) section 9, played in parallel intervals by a French horn, two piccolos, and celesta; and (c) section 14, played in parallel by most of the orchestra including the strings. We will come back to more detailed aspects of these representations later, but note that two kinds of structures are immediately visible: a series of horizontal lines that represent the frequencies of the instruments playing the melody, and a series of vertical bars that represent the rhythmic accompaniment. Note too that the density, intensity (represented by the blackness of the lines), and spectral extent (expansion toward the higher frequencies) can be seen to increase from section 2 through section 9 to section 14, reflecting the increasing number, dynamic level, and registral spread of instruments involved.
A ROBUST ALGORITHM FOR NONDESTRUCTIVE TESTING OF WELD SEAMS

The detection of welding flaws by means of nondestructive inspection methods remains open to the development of new algorithms and methods of inspection. One of the most widely used techniques is radiographic analysis, which requires interpretation by trained inspectors. Unfortunately, manual inspection is subject to various factors that can alter performance in the detection of the faults. An automated welding fault segmentation algorithm is presented using a set of digitized radiographic images. The result of the study has allowed the development of the following scheme: first, use the median filter to reduce noise; second, apply the bottom-hat filter to separate the hypothetical faults from the background; third, determine the segmented regions by binary thresholding; fourth, use the filters provided by morphological mathematics to eliminate over segmentation; and fifth, use the watershed transform to separate the internal regions. The results of the study have generated a general ROC curve on a set of 10 images with an area Az=93.6%.
Property Disposition Matters: The Current Status of Land Bank Programs in the United States

Vacant and abandoned properties are a growing concern for cities across the United States. Such property has been linked to crime, declining property values, and poor health/mental health. Vacant and abandoned properties also place a financial and manpower burden on the cities in which they are located. Land banks – governmental entities with a focus on returning vacant and abandoned properties to productive use – are emerging as a strategy to address these properties. Purpose: The purpose of this research is to describe the current status of land bank programs in the United States. Methods: Information about land bank programs is gathered through content analysis of land bank program websites. Results: The information available on land bank websites is extremely inconsistent across land banks. Approximately one quarter of listed land banks had no website available, and those websites that were located contained extremely inconsistent – and largely inadequate – information. Conclusion: Studies on land bank effectiveness are needed to determine their impact on the return of vacant and abandoned properties to productive use. Such studies are made more difficult by the varying laws, regulations, and procedures governing the operation of each land bank. The information available on most land bank websites is not sufficient to provide a foundation for comparison between entities, and the improvement of publicly available data from land banks would likely benefit scholars and potential customers. Property Disposition Matters ii Table of
On the Simulation of Turbulent Fluid-Structure Interaction

The fluid-structure interaction (FSI) phenomena are relevant in a significant number of naturally occurring as well as industrial applications. Simulations of FSI have gained noteworthy attention with rapid advancements of computational technology in the last decade. Efficiency and accuracy of these simulations are still a concern, specially with a turbulent flow, the challenge is compounded by an additional computational cost for a turbulence modeling approach. Partitioned coupling approaches owing to software modularity and reusability are favored by engineers to solve FSI problems. The turbulence in flow is simulated through models with varying levels of complexity and computational requirements. In industrial applications, the use of Reynolds Averaged Navier Stokes (RANS) modeling of turbulence is dominant, whereas turbulence resolving approaches like Large-Eddy simulation (LES) are still not considered feasible due to computational requirements. To get as much accuracy by using as least as possible computer resources, a reasonable compromise are hybrid RANS-LES of turbulence, which are becoming more and more frequent. The goal of this work is to enable efficient and reliable simulations of FSI in turbulent flow. To this end, validation studies of three different turbulence modeling approaches available in the in-house flow solver FASTEST are performed. The structural subproblem in the coupling environment is solved with the Finite Element Method based code FEAP, while the data transfer and interpolation on non-matching grid interfaces can be handled with MpCCI or preCICE. For this work, the turbulence modeling approaches in FASTEST are extended with an implementation of the Wall Adapting Local Eddy (WALE) viscosity model for LES, and a validation study of the model is performed for a two dimensional periodic hill flow test case. An economical method based on a Poisson equation for the calculation of the nearest wall distance is also implemented, which is required by some turbulence models. The accuracy of the method is assessed with two computations on stationary grids. In turbulent flow simulations with moving grids, the height of cells on a wall changes and it can make a wall treatment approach unsuitable. This issue is addressed with an implementation of wall boundary conditions that work regardless of the first cell position in a boundary layer. The implementation is tested on stationary grids in a channel flow with a variation of the first cell height on the wall. A test of the method with an FSI test case showed satisfactory results. Validation studies of a RANS and a hybrid RANS-LES approach are performed with simulations of two FSI test cases. The two and three dimensional RANS and the hybrid RANS-LES produce a good agreement with the experimental results for oscillation characteristics of the structure. A hybrid RANS-LES and an LES is performed for another FSI test case with a very dense mesh. The LES and the hybrid RANS-LES on two different, but relatively dense meshes produced very similar results with a satisfactory prediction of the structural deflections.
Meta-analysis: An insight

Introduction Meta analysis is used when comparing of multiple studies that looked as similar are consolidated using statistical method. It is a quantitative approach for systematically combing results of previous research to arrive at a convergent conclusion. The historically meta-analysis dates back to 17th century studies of astronomy. Karl Pearson in 1904 mooted the idea of Meta analysis collating data of several studies of typhoid inoculation and used the information to aggregate from the outcomes of multiple clinical studies. The first meta-analysis was on Extrasensory Perception After Sixty Years, by J. G. Pratt, J. B. Rhine of Duke in1940. In the 1970s, more sophisticated analytical techniques were introduced Meta analysis by Gene V. Glass, Frank L. Schmidt and John E. Hunter. The Greek root ‘meta’ means ‘with’, ‘along’, ‘after’, or ‘later’ and meta-analysis is done after original analysis. Glass defined meta-analysis as the statistical analysis of a large collection of analysis resulting from individual studies, in order to integrate the findings. Meta-analysis has a quantitative, formal, epidemiological study design. A meta-analysis is a statistical analysis that combines the results of multiple scientific studies, undertaken by same or different researchers at more than one places as well as being accessed from one or more journals.
Impact of exposure to mass media on female empowerment: evidence from India

Purpose The purpose of this paper is to investigate if women’s exposure to mass media, i.e. television, radio, and print media, is a determinant of female empowerment in India. Indicators of empowerment include female autonomy in domestic decision-making, freedom of movement, financial knowledge and independence, attitudes regarding acceptability of violence against women, actual and desired fertility and use and decisions about contraception. Design/methodology/approach Data for the analysis come from two rounds of the National Family and Health Survey, a large-scale nationally representative household survey. First, ordinary least squares estimation is used to obtain the parameter estimates. To overcome endogeneity concerns, instrumental variables estimation is also used. Findings The results reveal a strong positive effect of exposure to mass media on women’s status in India. Research limitations/implications These findings highlight the effectiveness of mass media in influencing women positively. Originality/value This paper captures the cumulative effects of three types of media: television, radio and print media. It also takes advantage of the most recent data available together with using instrumental variables estimation to overcome endogeneity concerns.
Modelling innovation and the macroeconomics of low-carbon transitions: theory, perspectives and practical use

ABSTRACT Energy and climate policies may have significant economy-wide impacts, which are regularly assessed based on quantitative energy-environment-economy models. These tend to vary in their conclusions on the scale and direction of the likely macroeconomic impacts of a low-carbon transition. This paper traces the characteristic discrepancies in models’ outcomes to their origins in different macro-economic theories, most importantly their treatment of technological innovation and finance. We comprehensively analyse the relevant branches of macro-innovation theory and group them into two classes: ‘Equilibrium’ and ‘Non-equilibrium’. While both approaches are rigorous and self-consistent, they frequently yield opposite conclusions for the economic impacts of low-carbon policies. We show that model outcomes are mainly determined by their representations of monetary and finance dimensions, and their interactions with investment, innovation and technological change. Improving these in all modelling approaches is crucial for strengthening the evidence base for policy making and gaining a more consistent picture of the macroeconomic impacts of achieving emissions reductions objectives. The paper contributes towards the ongoing effort of enhancing the transparency and understanding of sophisticated model mechanisms applied to energy and climate policy analysis. It helps tackle the overall ‘black box’ critique, much-cited in policy circles and elsewhere. Key policy insights Quantitative models commissioned by policy-makers to assess the macroeconomic impacts of climate policy generate contradictory outcomes and interpretations. The source of the differences in model outcomes originates primarily from assumptions on the workings of the financial sector and the nature of money, and of how these interact with processes of low-carbon energy innovation and technological change. Representations of innovation and technological change are incomplete in energy-economy-environment models, leading to limitations in the assessment of the impacts of climate-related policies. All modelling studies should state clearly their underpinning theoretical school and their treatment of finance and innovation. A strong recommendation is given for modellers of energy-economy systems to improve their representations of money and finance.
Needs analysis for graphic design learning module based on technology & learning styles of deaf students

Abstract The field of Information Communication Technology has offered a promising future for deaf students. Web design, animation, and multimedia application design are a branch of graphic design area, which aim to aid their learning visually. However, most of the technical terms cannot be interpreted in Malaysian sign language. Moreover, the development of the existing curriculum is not geared in catering needs of deaf students and not tailored to their learning styles. With the development of technology, learning for deaf students could be improved. However, previous studies only focused on language development and there is meager research on curriculum development and teaching in the field of graphic design. Therefore, this study was designed to obtain the views of students on the learning needs of graphic design module based on technology and learning styles of deaf students. Questionnaires were distributed to 58 students in special education schools and vocational colleges in Malaysia who majored in graphic design. Descriptive analysis of the data indicated that there is a need for a learning module and the reasons include difficulties in learning animation, different learning styles, communication of sign language in learning, and the efficacy of technology in aiding teaching deaf students.
Mastering Technical Analysis

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Classification of Network Optimization Software Packages

Network optimization models and algorithms constitute a core research area of Mathematical Optimization and Computing. We present a wide range of state-of-the-art network optimization software packages and provide up-to-date definitions of the most important issues in algorithm engineering concerning fundamental network optimization problems. Furthermore, we discuss new concepts, trends, and emerging technologies in this research area. Apart from presenting important recent developments in network optimization and their impact on modern organizations and society, the proposed article is a classification of network optimization software packages with a special focus on solvers and benchmark collections. Finally, discussion is made regarding the societal impact and practical managerial significance of network optimization models and software tools.
Speaker Adaptation on Hidden Markov Model using MFCC and Rasta-PLP and Comparative Study

This work compares the performance of the Mel-Frequency Cepstral Coefficient (MFCC) and Perceptual Linear Prediction (PLP) features for developing a text-dependent speaker identification system. Continuously spoken Hindi speech sentences have been used to train the HMM models using HTK toolkit for each speaker separately. The experiments have been performed using a set of 200 continuously spoken sentences with vocabulary of 20000 isolated words using a database of 100 speakers. The results show an accuracy of 92.26% recognition when PLP features have been used and accuracy of 91.18% for MFCC features. A confusion matrix has been created for all the 20 test speakers based on the recognition scores obtained for each of these speakers and their confusion with other speakers. Performance has been compared in the closed set and open set conditions of testing and as it is expected, the performance in the closed set condition is far better than the open set. We propose that if PLP features are used in place of MFCC, they may provide improvement in speaker identification accuracy by reducing the cases of false acceptance.
Regional Sustainability, Individual Expectations and Work Motivation: A Multilevel Analysis

In the context of the recent labor shortages in Eastern European countries, Romania included, companies, organizations and decision makers need to strongly address the issue of labor motivation for increasing worker performance and also for attracting the scarce labor resources. The main goal of the research is to explore new determinants of work motivation, such as regional sustainability and also individual factors related to individual expectations. Therefore, the responsive methodology used for this purpose implies a multilevel econometric modelling, in which the first level regards individuals, and the second one consists in development regions. Moreover, the role of individual factors is tested using Vroom’s theory of expectations and filling a gap in the existing literature on work motivation in developing, post-communist economies. The main findings prove that one dimension of sustainability, namely social sustainability has a significant impact on work motivation, alongside with four dimensions of individual factors. Economic and environmental sustainability have no significant impact on work motivation in the case of Romanian workers.
SINA microblog data retrieval

With the large increase of SINA Microblog web users,analyses SINA Microblog data has aroused wide public concern.The data retrieval is a primary need for all these studies.This paper presents two data retrieval techniques based on opened APIs and web crawlers with webpage extraction.A program controls the methods and frequencies of the API queries for efficient data downloading via parsing of JSON objects.A traditional web crawler integrated with webpage extraction overcomes the shortcomings of opened SINA API interfaces that limit retrieval of the entire dataset without quantity and frequency limitations.Test results show that a combination of these two techniques allows complete data retrieval of SINA Microblog data.