Reviewerly/exHarmony huggingface dataset:
MOZAMBIQUE: Debt Ruling

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 57, Issue 4 p. 22981A-22981B Policy and Practice MOZAMBIQUE: Debt Ruling First published: 07 June 2020 https://doi.org/10.1111/j.1467-6346.2020.09492.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume57, Issue4June 2020Pages 22981A-22981B RelatedInformation
Signal Regression

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Whole Child

The idea of the whole child typically includes social, emotional, cognitive, psychological, and physical components. Shaping pedagogy to include, account for, and develop all these parts is the goal of whole child education. If done well, outcomes include students who are self-regulated, collaborative, emotionally regulated, passionate, creative, democratically engaged, and adaptable. A major concern is that the vision for successfully teaching the whole child schooling is well aligned with neoliberal values for selfhood. The approximation to an ideal representation of self governs evaluations and efficacy of this focus. In this regard, whole child schooling is not about bringing all the contents of students into the context but shaping environments in order to realize a vision for the ideal person, one which shares many qualities with the ideal neoliberal self.
Secure hash algorithm-based multiple tenant user security over green cloud environment

This paper proposes a green cloud multi-tenant trust authentication with secure hash algorithm-3 (GreenCloud-MTASHA3) scheme to eliminate the unauthorised tenant access. GreenCloud-MTASHA3 scheme provide security over the multiple tenant requests by referring the confidentiality, integrity and availability rate. Confidentiality refers to limiting the unauthorised tenant's green cloud data access using the additive homomorphic privacy property in proposed scheme. Additive homomorphic privacy property-based encryption function is developed to improve the privacy preserving level. To attain the integrity level between the tenant requests and green cloud server machine in GreenCloud-MTASHA3 scheme an encrypted trust data management process is carried out. Trustworthiness of tenant request is measured to maintain the consistency level on security with minimal computational time. The proposed scheme attains the confidentiality, integrity and availability rate on communicating task. Experiment is conducted on factors such as secure computation confidence, authorised tenant computational time and space taken on storing encrypted data.
The adopting factors of campus mobile software applications

Many criteria are used for evaluating the quality of campus mobile software utilisation, though largest of those standards are interdependent or interactive, making it challenging to efficiently separate and enhance the position of campus mobile software applications. This study aims to solve this problem by using a various multicriteria decision-making approach, including decision-making trial and evaluation laboratory (DEMATEL), DEMATEL-based analytical network process (DANP), and the VIKOR method. The relationship between operating standards and value-added assistance content providers can be followed to determine relationship and feedback issues to fit the demands of the mobile communications trade.
Suggestions for discussing curriculum amendments in <East Asia History>

Contrary to the fact that East Asia has won the empathy as a new method of history research in the history academia, there are still negative viewpoints on the formation of < East Asian History > in history education. Thus, in the condition of facing the revision of curriculum in 2022, and the complete application of high school credit system in 2025, this study considered the effectiveness of < East Asian History > as an elective subject, and also suggested the desirable look of < East Asian History >. The meanings of < East Asian History > are as follows. First, it is meaningful because it aims for the common peace and prosperity, which has been even presented by Korea that was a victim of colonization in East Asia. Second, it is meaningful as the measures for uniformly solving the problems with the education of national history and world history in Korean history education. Third, it is meaningful as the first textbook developed before academic researches, contrary to the textbooks following the academic researches and general development process of curriculum and textbook. Considering the reality of East Asia as the ‘necessity to form the East Asian community’ based on such meanings, the < East Asia History > has sufficient meanings to exist as an elective subject in the necessity of education for understanding East Asia, and also cultivating the talent to support the relations of East Asia. However, based on such meanings and necessities, in order to realize it as the academia aimed to implement, and also to become a significant choice of subject to students, it should become the regional history thoroughly composed of subjects focusing on modern & contemporary history including Southeast Asia. However, the current performance might not be good enough to fully realize the < East Asian History > including Southeast Asia. Thus, if it is started in the method of connecting Southeast Asia focusing on consultative East Asia, the contents of textbook could be secured.
Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach (Preprint)

<sec> <title>BACKGROUND</title> Deep learning models have attracted significant interest from health care researchers during the last few decades. There have been many studies that apply deep learning to medical applications and achieve promising results. However, there are three limitations to the existing models: (1) most clinicians are unable to interpret the results from the existing models, (2) existing models cannot incorporate complicated medical domain knowledge (eg, a disease causes another disease), and (3) most existing models lack visual exploration and interaction. Both the electronic health record (EHR) data set and the deep model results are complex and abstract, which impedes clinicians from exploring and communicating with the model directly. </sec> <sec> <title>OBJECTIVE</title> The objective of this study is to develop an interpretable and accurate risk prediction model as well as an interactive clinical prediction system to support EHR data exploration, knowledge graph demonstration, and model interpretation. </sec> <sec> <title>METHODS</title> A domain-knowledge–guided recurrent neural network (DG-RNN) model is proposed to predict clinical risks. The model takes medical event sequences as input and incorporates medical domain knowledge by attending to a subgraph of the whole medical knowledge graph. A global pooling operation and a fully connected layer are used to output the clinical outcomes. The middle results and the parameters of the fully connected layer are helpful in identifying which medical events cause clinical risks. DG-Viz is also designed to support EHR data exploration, knowledge graph demonstration, and model interpretation. </sec> <sec> <title>RESULTS</title> We conducted both risk prediction experiments and a case study on a real-world data set. A total of 554 patients with heart failure and 1662 control patients without heart failure were selected from the data set. The experimental results show that the proposed DG-RNN outperforms the state-of-the-art approaches by approximately 1.5%. The case study demonstrates how our medical physician collaborator can effectively explore the data and interpret the prediction results using DG-Viz. </sec> <sec> <title>CONCLUSIONS</title> In this study, we present DG-Viz, an interactive clinical prediction system, which brings together the power of deep learning (ie, a DG-RNN–based model) and visual analytics to predict clinical risks and visually interpret the EHR prediction results. Experimental results and a case study on heart failure risk prediction tasks demonstrate the effectiveness and usefulness of the DG-Viz system. This study will pave the way for interactive, interpretable, and accurate clinical risk predictions. </sec>
Estimation of Agent-Based Models Using Bayesian Deep Learning Approach of BayesFlow

This study examines the possibility of applying the novel likelihood-free Bayesian inference called BayesFlow proposed by Radev et al. (2020) for the estimation of agent-based models (ABMs). BayesFlow is a fully likelihood-free approach, which directly approximates a posterior rather than a likelihood function by learning an invertible probabilistic mapping between parameters and standard Gaussian variables, conditional on simulation data from the ABM to be estimated. BayesFlow certainly achieved superior accuracy to the benchmark method of Kernel Density Estimation-MCMC of Grazzini et al. (2017) and the more sophisticated method of Mixture Density Network-MCMC of Platt (2019), in the validation tests of recovering the ground-truth values of parameters from the simulated datasets of a standard New Keynesian ABM (NK-ABM). Furthermore, the truly empirical estimation of NK-ABM with the real data of the US economy successfully showed the desirable pattern of posterior contraction along with the increase in observation periods. This deep neural network-based method holds general applicability without any critical dependence on pre-selected design and high computational efficiency. These features are desirable when scaling the method to practical-sized ABMs, which typically have high-dimensional parameters and observation variables.
Web-Based Privacy-Preserving Multicenter Medical Data Analysis Tools Via Threshold Homomorphic Encryption: Design and Development Study (Preprint)

<sec> <title>BACKGROUND</title> Data sharing in multicenter medical research can improve the generalizability of research, accelerate progress, enhance collaborations among institutions, and lead to new discoveries from data pooled from multiple sources. Despite these benefits, many medical institutions are unwilling to share their data, as sharing may cause sensitive information to be leaked to researchers, other institutions, and unauthorized users. Great progress has been made in the development of secure machine learning frameworks based on homomorphic encryption in recent years; however, nearly all such frameworks use a single secret key and lack a description of how to securely evaluate the trained model, which makes them impractical for multicenter medical applications. </sec> <sec> <title>OBJECTIVE</title> The aim of this study is to provide a privacy-preserving machine learning protocol for multiple data providers and researchers (eg, logistic regression). This protocol allows researchers to train models and then evaluate them on medical data from multiple sources while providing privacy protection for both the sensitive data and the learned model. </sec> <sec> <title>METHODS</title> We adapted a novel threshold homomorphic encryption scheme to guarantee privacy requirements. We devised new relinearization key generation techniques for greater scalability and multiplicative depth and new model training strategies for simultaneously training multiple models through x-fold cross-validation. </sec> <sec> <title>RESULTS</title> Using a client-server architecture, we evaluated the performance of our protocol. The experimental results demonstrated that, with 10-fold cross-validation, our privacy-preserving logistic regression model training and evaluation over 10 attributes in a data set of 49,152 samples took approximately 7 minutes and 20 minutes, respectively. </sec> <sec> <title>CONCLUSIONS</title> We present the first privacy-preserving multiparty logistic regression model training and evaluation protocol based on threshold homomorphic encryption. Our protocol is practical for real-world use and may promote multicenter medical research to some extent. </sec>
Track Fitting

Abstract Track fitting is an application of established statistical estimation procedures with well-known properties. For a long time, estimators based on the least-squares principle were—with some notable exceptions—the principal methods for track fitting. More recently, robust and adaptive methods have found their way into the reconstruction programs. The first section of the chapter presents least-squares regression, the extended Kalman filter, regression with breakpoints, general broken lines and the triplet fit. The following section discusses robust regression by the M-estimator, the deterministic annealing filter, and the Gaussian-sum filter for electron reconstruction. The next section deals with linearized fits of space points to circles and helices. The chapter concludes with a section on track quality and shows how to test the track hypothesis, how to detect outliers, and how to find kinks in a track.
Effects of Virtual Reality and Non–Virtual Reality Exercises on the Exercise Capacity and Concentration of Users in a Ski Exergame: Comparative Study (Preprint)

<sec> <title>BACKGROUND</title> Recently, ski exergames have been gaining popularity due to the growing interest in health improvement. Conventional studies evaluating the effects of ski exergames only considered exercise capacity and overlooked concentration. Ski exergames consist of a motion platform for exercise and virtual reality (VR) content in the game. The VR content enhances the exercise capacity and concentration of the user by providing a challenging goal. </sec> <sec> <title>OBJECTIVE</title> The aim of this study is to evaluate the effects of VR and non-VR exercises on the exercise capacity and concentration of users in a ski exergame. </sec> <sec> <title>METHODS</title> To examine the effects of the VR content in ski exergames, we performed 2 experiments, non-VR exercise and VR exercise, where participants exercised on the motion platform. If a user performs an exercise without using any VR content, it is a non-VR exercise. Contrastingly, in the case of VR exercise, a user exercises according to the VR content (a downhill scenario). In addition to the range of motion (ROM) of the ankle and rated perceived exertion (RPE) to assess exercise capacity, we used electroencephalography (EEG) to assess users’ concentration. </sec> <sec> <title>RESULTS</title> We evaluated the effects of the VR content by comparing the results obtained from VR and non-VR exercises. The ROM of the ankle with VR exercise was wider than that with non-VR exercise. Specifically, ROM of the ankle was 115.71° (SD 17.71°) and 78.50° (SD 20.43°) in VR exercise and non-VR exercise, respectively. The RPE difference between the 2 exercises was not statistically significant. The result of the sensorimotor rhythm waves (which are concentration-related EEG signals) was more favorable for VR exercise than non-VR exercise. The ratios of sensorimotor rhythm wave in EEG were 3.08% and 2.70% in the VR exercise and non-VR exercise, respectively. </sec> <sec> <title>CONCLUSIONS</title> According to the results of this experiment, higher exercise capability and concentration were achieved with the VR exercise compared with non-VR exercise. The observations confirm that VR content can enhance both exercise capability and concentration of the user. Thus, the ski exergames can be used effectively by those who, in general, do not like exercise but enjoy games. </sec>
Random Signals

This pioneering, course-tested text is the first to combine communications theory with the physics of optical communications. Comprehensive and rigorous, it brings together an in-depth treatment of the physical characteristics of the guided lightwave channel with the study of modern methods of algorithmic-based communication in time and space. The many different levels at which a lightwave communication signal can be described are integrated to provide a unified explanation of how a commonplace bit stream is transformed into a physical lightwave, how that lightwave travels through an optical fiber, and how it is then transformed back into the bit stream. Background fundamentals such as linear systems and electromagnetics are explained in relation to modern topics such as channel models, encoding, modulation and interference, and end-of-chapter problems are provided throughout. This is an essential text for students taking courses on optical communications, as well as researchers and professionals working in the area.
Information Platform 'Hypermethod' for Studying the Discipline of 'Physical Culture'

With the introduction of modern technology into the educational process, it is important to consider how it can be applied in physical education teaching. The article deals with the peculiarities of implementing the individual educational pathway (IEP) of part-time students of the Ural State University of Physical Culture in the framework of a virtual learning system on the ‘HyperMethod’ platform. Our research was aimed at studying the effectiveness of the distance learning system in the process of the physical education of students. Based on the analysis and synthesis of scientific and methodological literature and pedagogical research, an assessment of the quality of the educational process was carried out. For the purpose of ensuring remote forms of learning, lecturers of the Physical Education faculty created an online- course on the Physical Culture discipline. Students were able to study the lecture material, read the assessment criteria, submit their own projects and receive a review at their convenience. Through a review of the results of the assessment tasks, the most difficult questions for the students were identified and the methods of delivering the learning material were adjusted. The final stage of the educational process for students studying in the HyperMethod environment was conducted in the form of an independent monitored test. The students were tested by means of automated tools via the test assignment database. The analysis of the results of teaching the students during the winter session of 2019/20 demonstrated the successful performance of all of them. Based on the analysis and synthesis of the results of the conducted pedagogical study, we can conclude that the introduction of distance learning has contributed to an increase in self-organisation, students’ knowledge level and teachers’ professional competence.
Central bank digital currency and alternative currencies: parallel paradigms

Central bank digital currencies have been on the rise for the past few years, especially after the emergence of cryptocurrencies like Bitcoin, Ethereum, Ripple and others. Leading central banks like the People's Bank of China and Riksbanken (Swedish Central Bank), and some of the other central banks around the world have been looking to develop and test central bank digital currencies around the world. Nonetheless, the main question that we need to answer is if the cryptocurrencies or central bank digital currencies (CDBC) will become the main form of money in the future or will these currencies harmoniously co-exist within the economy paradigm? This paper applies monetary and political economy concepts to discuss how a potential central bank digital currency can be developed and how it would compete with cryptocurrencies. In conclusion, however, the introduction of a central bank digital currency will reduce the monetary policies issues rather than create new issues and this paper will explain how this can be achieved.
Seismic Soundoff — Coordinated by Andrew Geary

We at SEG were saddened to learn of Vladimir Grechka's death in an accident in Utah in early November. A memorial to Grechka will be published in an upcoming issue of TLE. On 8 October, Grechka was interviewed for SEG's Seismic Soundoff podcast. The following is a short excerpt from that interview, the entirety of which can be heard at https://seg.org/podcast/post/9180 .
Review on Cloud Computing and Cloud Security Issues

Review on Cloud-Computing and the security and privacy issues related with it.
The Technology Vendor’s Conference: An Information Technology Planning Success Story

This ease study describes the use of an information technology vendor conference to assure the smooth opening of the remodeled Central Library of the Multnomah County (Portland, Oregon) Library. Collaborative meetings with vendors provided the opportunity for hardware, telecommunications, integrated library system, and network vendors to meet with library staff to troubleshoot problems, share information, and anticipate situations. The meetings also provided library administration with the opportunity to underscore the importance of the opening. The article discusses the elements neccssary to make this approach a success and reports on events before, during, and after the opening of the new facility. [Article copies available for a fee from The Haworth Document Delivery Service: 1–800-342-9678, E-mail address: getinfo@hawortlipressinc.com]
Integrated Teaching Strategies Used by ESL Teachers: How are Strategies of Arts, Mathematics, and Sciences Correlated?

The philosophy and practices of STEAM education have been drawing influential attention over the past decade. Using the interdisciplinary and integrated framework of STEAM, this study aims to understand ESL teachers’ integrated teaching strategies of arts, mathematics, and sciences and examine the correlation among the domains of linguistic, artistic, musical, mathematical and logical, and science-related teaching strategies. Data collected from 67 ESL teachers in a Midwestern state were analyzed using the Pearson correlations. Results indicated that ESL teachers not only emphasize the traditional linguistic teaching strategies, but also integrate artistic, musical and mathematical, and sciences-related strategies in their classroom teaching. ESL teachers’ classroom teaching strategies of arts, mathematics, and sciences were highly and moderately correlated. Interpretations of the findings related to the integrated perspective of STEAM and implications for school leaders and ESL teacher educators were discussed.
Identifikasi Karakteristik Riset Interaksi Manusia dan Komputer di Indonesia: Alur, Metodologi, dan Arahnya di Masa Mendatang

Human and Computer Interaction is a multi-disciplinary field of study that focuses on designing computer technology that specifically looks at aspects of interaction between humans and computers. This research is a systematic literature review with the aim of investigating topics raised by Indonesian researchers in the field of Human-Computer Interaction and grouping research articles published based on HCI-Macro and HCI-Micro. This is done so that it is possible to know the impact on the outcomes of the research that has been done. Based on the grouping results obtained, as many as 95% of research articles fall into the HCI-Micro category. From these findings we propose ideas to next researchers to choose research topics in the field of Human and Computer Interaction that are able to have a greater impact in the HCI-Macro category.