Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Income Inequality Across Countries and Over Time: The Standardized World Income Inequality Database

Objective: This article documents wide-ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years. Methods: Two k-fold cross-validations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability. Results: The cross-validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality datasets. Conclusion: Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross-national research on income inequality.
Frequency domain identiﬁcation of synchronous machines by multisine excitation

Modelling and identification of synchronous machines has attracted much attention during the past decades. Although the standstill frequency response (SSFR) method has become standardized (IEEE Std. 115) it has some disadvantages (e.g. it is a time consuming method). To overcome these, the use of multisine excitation has been proposed in the literature. In this paper the use of multisine excitation for the frequency domain identification of synchronous machines is discussed. The selection of the applied excitation signal and the measurement set-up are dealt with. The obtained frequency domain data can be used in different applications, examples are given in this paper. Furthermore the extraction of a parametric model from the nonparametric frequency domain data is discussed. Measurement results and their processing are discussed for different types of synchronous machines to demonstrate that multisine frequency domain identification can be applied to extract the parameters (inductances) of permanent magnet synchronous machines. These parameters can then be used to study the influence of saturation or can be applied in the simulation and control of permanent magnet synchronous machines.
Modular Audio Platform for Youth Engagement in a Museum Context

Today, cultural organizations such as museums are seeking new ways to attract and engage audiences. Augmented reality and digital storytelling applications are considered very promising. The target is to provide more interactive experiences for an audience highly familiar with digital interaction. Typically, these experiments utilize separate individual applications. If a cultural institution would like to utilize for example augmented reality and digital storytelling in their service offering they have to acquire, learn and manage each technology and application separately. Indeed, it seems that there is no general-purpose IT platform that is modular and expandable. In addition, visual presentation has been dominant in digital systems. In contrast to this trend, we have chosen to concentrate on audio presentation. The purpose of this thesis is to support museums and other cultural institutes in their mission to attract young visitors by offering engaging experiences. The main goals of the thesis were to develop a modular and easy-to-use audio story-sharing and audio-augmented reality platform, and evaluate the usefulness of the platform by measuring the level of engagement of participating youth in a workshop context. Design-science research methodology was used for audio platform component development, and mixed-methods were used to study the utility of platform components as case studies. At a more detailed level this means that the expandable and modular platform was developed incrementally one component at a time. When developing Audio Digital Asset Management, action research was used. For the Soundscape Mixer development, combined action research was used until the software was in the phase after which a separate evaluation method was used in the phase. For the Audiostory Sharing development design-science research with separate building and evaluation methods was used. After implementation and testing the audio platform also from the usability angle, we moved on to engagement research. Workshops were organized in order to demonstrate the usage of the audio platform. During the workshops engagement was researched using mixed method, namely quantitative self-report questionnaires and qualitative methods in the form of observations. We have succeeded in developing a modular and versatile audio platform. All of the hardware is commonly used including Android phones. Software-wise the backend system is based on open
Acquirer Overvaluation and Stock Payment in M&A Transactions: What Explains the Spurious Correlation?

The widely cited empirical relation between equity misvaluation and the choice of merger currency has been recently called into question in a substantive manner. How can it be that the academic community was misled by this spurious correlation for more than a decade? We investigate this question and show that, most likely, failing to account for the abolishment of pooling in 2001 is the culprit. We start by arguing that pooling was the accounting method of choice for highly-valued acquirers, and that failing to control for this regulatory incentive (and the eventual disappearance of that incentive) leads to invalid inference. We finally confirm these arguments with new empirical results: (i) the relation between acquirer valuation and the choice of mode of payment disappears in analysis of U.S. mergers with fresh data that post-date 2001; (ii) this relation also fails in examination of data from Europe and Australia, environments where pooling was either not allowed or almost never used; (iii) this relation is absent even in analyses of pre-2001 subsamples of U.S. mergers that did not use pooling. We conclude that the abolishment of pooling played the role of an endogenous omitted variable, leading to the erroneous interpretation of empirical evidence.
Knowledge, Attitude and Practices of Kegel Exercise among Postnatal Women, in Al Madinah Al Munawarah, Saudi Arabia

Background: Kegel exercise role in strengthening the pelvic floor muscle in the treatment of prolapse and urinary incontinence and improve mobility and relieves pain Aim; The study aims to assess the knowledge and attitude and practices of kegel exercise among postnatal women in Al Madinah Al Munawarh, Saudi Arabia. Study design: This study utilized descriptive quantitative cross-sectional study design. Study Setting: The study was conducted of the postnatal ward in Maternity and Children's Hospital in Al Madinah Al Munawarh, Saudi Arabia. From April to December 2019. Sample: the study carried out among 152 of postpartum mothers. Tools that used in this study; Tool I: An interviewer-administered questionnaire in Arabic language was used in this study, it composed of three parts targeting the research objectives. Tool II: was concerned with knowledge of women regarding kegel exercises. Tool III: - concerned two parts: Part one: This part related to women's attitude towards kegel exercises. Part two: This part related to women's practices about kegel exercises. Results: the study found that 44.7% of the sample was in the age group 26-31 years old, 75.0% were multigravida, 85.5% had no miscarriage, 67.1% had vaginal delivery, and 50.0% have 1-3 children. 25% of the sample reported media as their source for information on kegel exercise. 62.7% of the sample had satisfactory knowledge. 72.4% were categorised as having ‘somewhat favourable’ overall attitudes towards kegel exercises. 57%of the mothers have not performed kegel exercise. 38.5% of the participants were correctly practised kegel exercise in sitting or standing position. While 29.7% was correctly practised kegel exercise in lying down position. Conclusion; Women’s knowledge concerning the kegel exercise in the postnatal period is reasonable and their attitude was favourable, but the mothers had the poor practice of kegel exercises. Recommendation; Mothers should be informed and trained to kegel exercises properly by educational courses.
The Role of Target Task Pre-Exposure in Resource Training

In contrast to part training, which emphasizes the practice of task components, resource training proceeds by practicing mental processes that are transferable to whole-task performance. Although previous research supports its effectiveness in skill acquisition, it is unclear whether pre-exposure to the whole task is necessary to realize its benefits. Here previous methodology involving resource training of a bargraph recognition task (Boles, 1997) is adapted by measuring performance benefits relative to an unrelated baseline task. Statistical comparison to the previous results indicates that pre-exposure to the whole task is not a necessary precondition for effective resource training. The results bode well for the usefulness of resource training in situations where the exact target task is unknown in advance, as in early flight or sports training.
A Robustness Study for Low-Channel-Count Cross-Talk Cancellation Systems

Cross-talk cancellation makes the reproduction of binaural audio possible through loudspeakers. This is typically achieved by employing a digital signal processing network that controls the acoustic pressure at the listener’s ears. Although this can be achieved by using only two loudspeakers, there has been a recent tendency of using loudspeaker arrays, which increase the robustness to source errors and reduce room’s response influence. This document presents a numerical study on the trade-off between cross-talk cancellation performance and the number of channels of a loudspeaker array. Special attention is given to the conditioning of the array and how this is affected by inaccuracies in the driver response for different numbers of loudspeakers: 2, 3, 4, 5, and 7.
Eigenimage Processing of Frontal Chest Radiographs

The goal of this research was to improve the speed and accuracy of reporting by clinical radiologists. By applying a technique known as eigenimage processing to chest radiographs, abnormal findings were enhanced and a classification scheme developed. Results confirm that the method is feasible for clinical use. Eigenimage processing is a popular face recognition routine that has only recently been applied to medical images, but it has not previously been applied to full size radiographs. Chest radiographs were chosen for this research because they are clinically important and are challenging to process due to their large data content. It is hoped that the success with these images will enable future work on other medical images such as those from CT and MRI. Eigenimage processing is based on a multivariate statistical method which identifies patterns of variance within a training set of images. Specifically it involves the application of a statistical technique called principal components analysis to a training set. For this research, the training set was a collection of 77 normal radiographs. This processing produced a set of basis images, known as eigenimages, that best describe the variance within the training set of normal images. For chest radiographs the basis images may also be referred to as “eigenchests”. Images to be tested were described in terms of eigenimages. This identified patterns of variance likely to be normal. A new image, referred to as the remainder image, was derived by removing patterns of normal variance, thus making abnormal patterns of variance more conspicuous. The remainder image could either be presented to clinicians or used as part of a computer aided diagnosis system. For the image sets used, the discriminatory power of a classification scheme approached 90%. While the processing of the training set required significant computation time, each test image to be classified or enhanced required only a few seconds to process. Thus the system could be integrated into a clinical radiology department.
A study on interaction between pile and prefabricated vertical drain in soft clay

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Output feedback variable structure adaptive control of a flexible spacecraft

Abstract Based on the variable structure model reference adaptive control theory, a new control system for the control of an orbiting flexible spacecraft, using output feedback, is designed. The spacecraft consists of a main rigid body to which elastic appendages are attached. For the purpose of control, a moment generating device is located on the rigid hub. For the derivation of control law, it is assumed that the parameters and the structure of the nonlinear functions in the model are unknown. It is shown that in the closed-loop system including the variable structure model reference adaptive control system designed using bounds on uncertain functions, the pitch angle tracks given reference trajectory and the vibration is suppressed. Digital simulation results show that the closed-loop system has good transient behavior and robustness to the uncertainties, unmodeled dynamics, and disturbance inputs.
Integrating Network Management for Cloud Computing Services

Abstract : Cloud computing is known to lower costs of corporate IT. Thus enterprises are eager to move IT applications into public or private cloud. Because of this trend, networks connecting enterprises and cloud providers now play a critical role in delivering high-quality cloud applications. Simply buying better devices is not viable for improving network quality, due to high capital costs. A more attractive approach is to better utilize network resources with proper network management. However, there are two problems with current network management: separately managing network components along the end-to-end path, and heavily relying on vendor-specific interfaces with devices.
Multi-Scale Supercomputing of Large Molecular Aggregates: A Case Study of the Light-Harvesting Photosynthetic Center

Numerical solution of the quantum mechanical Schrodinger equation is required to model electronic excitations in the light-harvesting photosynthetic complexes composed of up to millions of atoms. We demonstrate that the modern supercomputers can be used to treat electronic structure calculations in such large molecular aggregates if proper multi-scale massive-parallel approaches are applied. We show that the three-level parallelization scheme based on the novel numerical algorithms assuming fragmentation of a light-harvesting complex allows us to reduce considerably the high scaling of ab initio quantum chemistry methods. More specifically we applied the time-dependent density functional theory based upon the fragment molecular orbital presentation FMO-TDDFT implemented at the modern supercomputers to obtain a realistic estimate of the electronic excitation in the complex. The application shows a good overall scaling.
EXPLORING THE FACTORS INFLUENCING ETHICAL CONSIDERATIONS IN REPORTING ON MIGRATION ISSUES IN LATVIAN NEWS MEDIA

This article analyses the perceived importance of various influences on the ways in which Latvian local and national news media (print, online, TV, radio) have reported on migration issues and the process of accepting asylum seekers in Latvia during the last years. Previous studies indicate that the framing in media content depends on a large number of considerations such as general principles of ethical reporting, the established cultures inside media, and – in many cases – the individual perceptions of the “right” and “wrong” of the journalists and editors. The current study applies a qualitative approach drawing on 13 semi-structured interviews with media editors. The data analysis reveal how the perceptions of various individual, procedural and cultural influences intersect with the journalist perceptions of media roles, responsibilities and duties in a democratic society. Based on the results, suggestions are made about the opportunities of lifelong learning training development for journalists.
Evaluating Morningstar Wide Moat Stocks through the Business Cycle

The evaluation of stock selections by portfolio managers is a topic commonly addressed by academics in finance. In particular, there is great interest to find portfolio managers that consistently outperform the market. In this article, we evaluate the market returns of Morningstar’s “StockInvestor” Wide Moat portfolios: The Tortoise and the Hare. The Wide Moat portfolio stocks are companies that Morningstar analysts identify as having a sustainable advantage estimated to last at least 20 years. Comprised of these Wide Moat Stocks, the Tortoise portfolio is comprised of slow and steady growth stocks while the Hare portfolio is comprised of stocks with faster, but less steady growth. While portfolio returns are typically compared to the overall market index, this basic comparison ignores statistical factors in stocks that have been shown to produce above-average returns. This study evaluates Morningstar’s portfolios to determine if Morningstar’s portfolio managers select stocks that outperform through the business cycle, or if the returns are explained by the Fama-French 3-factor model. In this study, we analyze both portfolios from 2007 to 2012. In addition to looking at the entire period performance, this study also isolates the recessionary period from 2007 to 2009 to see if the Wide Moat portfolios outperform in a recession. Furthermore, in order to investigate what other factors may be underlying the identification and selection of wide moat stocks, an analysis is conducted to determine how industry competitiveness and concentration is reflected in the stock selection of Morningstar’s portfolio managers.
Performance analysis of the RAID 5 disk array

While the processor and memory performance of computers continues to improve, I/O performance has remained relatively constant. Strategies to achieve better I/O performance than current disk systems have been investigated to address the growing I/O bottleneck. One effort is the RAID (Redundant Arrays of Inexpensive Disks) Level 5 disk array. RAID 5 offers increased parallelism of I/O requests through the disk array architecture and fault tolerance through rotated parity. Although RAID 5 offers the promise of improved I/O performance, such gains must be quantified. Accurate analytical modeling can be used to quantify and predict the I/O request response time for different workloads. While previous analytical models to calculate the I/O request response time have been constructed, they often rely upon simplifying assumptions or computational bounds, which are accurate for certain values of the possible workload parameters. This paper presents an analytical performance model to compute the mean steady state response time of a RAID 5 I/O request under a transaction-processing workload. By carefully considering individual disk accesses, the arrival process of disk requests, and correlation between disk requests, an accurate model for a wide range of the workload parameters is developed. <<ETX>>
A new approach to query segmentation for relevance ranking in web search

In this paper, we try to determine how best to improve state-of-the-art methods for relevance ranking in web searching by query segmentation. Query segmentation is meant to separate the input query into segments, typically natural language phrases. We propose employing the re-ranking approach in query segmentation, which first employs a generative model to create the top k candidates and then employs a discriminative model to re-rank the candidates to obtain the final segmentation result. The method has been widely utilized for structure prediction in natural language processing, but has not been applied to query segmentation, as far as we know. Furthermore, we propose a new method for using the results of query segmentation in relevance ranking, which takes both the original query words and the segmented query phrases as units of query representation. We investigate whether our method can improve three relevance models, namely n-gram BM25, key n-gram model and term dependency model, within the framework of learning to rank. Our experimental results on large scale web search datasets show that our method can indeed significantly improve relevance ranking in all three cases.
Should Central Banks Issue Digital Currency?

We study how the introduction of a central bank-issued digital currency affects interest rates, the level of economic activity, and welfare in an environment where both central bank money and private bank deposits are used in exchange. Banks in our model are financially constrained, and the liquidity premium on bank deposits affects the level of aggregate investment. We study the optimal design of a digital currency in this setting, including whether it should pay interest and how widely it should circulate. We highlight an important policy tradeoff: while a digital currency tends to promote efficiency in exchange, it can also crowd out bank deposits, raise banksfunding costs, and decrease investment. Despite these effects, introducing a central bank digital currency often raises welfare.
Creating a biomedical ontology indexed search engine to improve the semantic relevance of retreived medical text

Medical Subject Headings (MeSH) is a controlled vocabulary used by the National Library of Medicine to index medical articles, abstracts, and journals contained within the MEDLINE database. Although MeSH imposes uniformity and consistency in the indexing process, it has been proven that using MeSH indices only result in a small increase in precision over free-text indexing. Moreover, studies have shown that the use of controlled vocabularies in the indexing process is not an effective method to increase semantic relevance in information retrieval. To address the need for semantic relevance, we present an ontology-based information retrieval system for the MEDLINE collection that result in a 37.5% increase in precision when compared to free-text indexing systems. The presented system focuses on the ontology to: provide an alternative to text-representation for medical articles, finding relationships among co-occurring terms in abstracts, and to index terms that appear in text as well as discovered relationships. The presented system is then compared to existing MeSH and Free-Text information retrieval systems. This dissertation provides a proof-of-concept for an online retrieval system capable of providing increased semantic relevance when searching through medical abstracts in MEDLINE.