Reviewerly/exHarmony huggingface dataset:
ZIMBABWE: Exchange Rate Floated

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 57, Issue 2 p. 22909A-22909C Policy and Practice ZIMBABWE: Exchange Rate Floated First published: 12 April 2020 https://doi.org/10.1111/j.1467-6346.2020.09397.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 onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume57, Issue2April 2020Pages 22909A-22909C RelatedInformation
Extensions for Scientists: NumPy, SciPy, Matplotlib, Pandas

In this chapter, you will learn about the three most important modules for scientists: NumPy, SciPy, and Matplotlib.
Real-Time Face Detection and Recognition on Raspberry Pi using LBP and Deep Learning

Advancement in low power embedded systems in recent years help us in building portable real-time algorithms and applications. These embedded systems can be integrated into the Cameras used in Surveillance Systems to provide additional mid-level computer vision tasks like face detection and face recognition in person identification applications. This paper proposes face detection using Local Binary Patterns (LBP) and Haar cascades-based face recognition using Convolutional Neural Networks (CNN) derived from Lenet architecture. A database is created covering all challenges involved in face identification like illumination, orientation, expressions, disguise, and age factors. Two CNN architectures are proposed and compared for face recognition. The tasks are performed on Raspberry Pi in real-time, and analysis has been carried out on how well LBP and Haar cascades work in terms of accuracy and Frames per second (FPS) in real-time. The realtime results achieved are acceptable with the frame rate of 7.04 FPS with accuracy above 94%. Frame reading and frame processing are handled in separate threads on CPU and frame skipping, while detection and recognition have improved the frame rates significantly.
Math Functions and Data Sorting

In this chapter, I describe two sets of features. First, I describe the support for performing common mathematical tasks, including generating random numbers. Second, I describe the features for sorting the elements in a slice so they are in order. Table 18-1 puts the math and sorting features in context.
Fundamentals of Software Engineering (extended versions of selected papers of FSEN 2019)

Bug prediction aims at locating defective source code components relying on machine learning models. Although some previous work showed that selecting the machine-learning classifier is crucial, the results are contrasting. Therefore, several ensemble techniques, i.e., approaches able to mix the output of different classifiers, have been proposed. In this paper, we present a benchmark study in which we compare the performance of seven ensemble techniques on 21 open-source software projects. Our aim is twofold. On the one hand, we aim at bridging the limitations of previous empirical studies that compared the accuracy of ensemble approaches in bug prediction. On the other hand, our goal is to verify how ensemble techniques perform in different settings such as cross- and local-project defect prediction. Our empirical experimentation results show that ensemble techniques are not a silver bullet for bug prediction. In within-project bug prediction, using ensemble techniques improves the prediction performance with respect to the best stand-alone classifier. We confirm that the models based on Validation and Voting achieve slightly better results. However, they are similar to those obtained by other ensemble techniques. Identifying buggy classes using external sources of information is still an open problem. In this setting, the use of ensemble techniques does not provide evident benefits with respect to stand-alone classifiers. The statistical analysis highlights that local and global models are mostly equivalent in terms of performance. Only one ensemble technique (i.e., ASCI) slightly exploits local learning to improve performance.
Implementation of K-Nearest Neighbor Algorithm in Heart Disease Classification

The heart is an important organ that exists in the human body. The main function of the heart is to pump blood throughout the body through blood vessels. The WHO states that as many as 7.3 million people die from heart disease. In this study heart disease will be classified using the K-Nearest Neighbor algorithm. K-Nearest Neighbor algorithm is a classification algorithm based on the distance from data testing against training data with a pre-defined number of k. The results were obtained from performance measurements for the classification of heart disease with the K-Nearest Neighbor algorithm measured using the K-Fold Cross Validation algorithm, from an accuracy rate of 65.89%, a precision level of 66.27%, and a recall of 74.67%.
INTERNATIONAL TCHAIKOVSKY COMPETITION AS A PHENOMENON OF WEBCAST

The International Tchaikovsky Competition has been held for sixty years and has become a tradition with an intention to renew itself. An essential aspect of this is the webcast, which, being performed at the highest level, not only develops the established democratic orientation of this competition, but makes the competition a relatively independent artistic event. The empirical base of the research is Internet broadcasting of XV and XVI competitions. Method – a comparative analysis, performed in the context of cultural knowledge. The article analyzes the features of the modern Internet broadcast of the competition, which distinguish it from previous TV and Internet broadcasts. The specific difficulties of shooting musical events related to their duration and the static of what is happening, as well as the resources that were used by the director and operators of "Medici.tv" in the creative solution of these problems, were understood. It is shown that the perception of the online broadcast of the competition is not inferior in terms of artistic criteria to the impression that the listener who attends the concert receives, but this is a different impression, not canceling, but supplementing the traditional one. On this basis, the conclusion is formed that the Internet broadcasting enriches the artistic culture. It provides the audience with new opportunities for creative perception of an artistic work. In addition, the webcast allows the art critic to carry out research on the phenomena of the performing arts at a fundamentally different level, to increase the degree of reliability of the knowledge gained. Previously, the theory of performing arts relied on an unreliable empirical research base: a single viewing and listening to a concert version of a work and memories of it. Webcasting allows multiple viewing and listening, verification of the findings, including through the use of computer programs, which allows one to overcome the degree of subjectivity that is unacceptable for science, which is inevitably present in art criticism, based on the empirical experience of a researcher attending a concert, protects against the accidents of perception that lie in wait for the listener in the concert hall. And the theory of performance objectively becomes on a par with other branches of art history - the theory of painting, architecture, musicology, studying musical notation, etc. The webcast changed the status of the Tchaikovsky Competition. Initially, in 1958, it was conceived and implemented as, first of all, a socio-political event, marking the beginning of the period of the "policy of openness" pursued by the leadership of our country. Thanks to the webcast, the competition has become a completely self-sufficient event - it exists as a “piece of art”, which you can which can be enjoyed again and again, just as we re-read works of classical literature over and over again.
Congratulations ! JACIII Best Paper and Young Researcher Awards 2020

We are pleased to announce that the JACIII Awards of 2020 have been decided by the JACIII editorial boards. This year, the award winning papers were severely and fairly selected among 405 papers published in JACIII Vols. 21 (2017) to 23 (2019) and there was no entries that deserved the Best Review Paper award. The award ceremony was held online in order to prevent spreading of COVID-19. JACIII BEST PAPER AWARD 2020 Hiroki Shibata, Hiroshi Ishikawa, and Yasufumi Takama Crystalizing Effect of Simulated Annealing on Boltzmann Machine JACIII Vol.23 No.3, pp. 474-484, 2019. JACIII YOUNG RESEARCHER AWARD 2020 Yuto Omae Swimming Style Classification Based on Ensemble Learning and Adaptive Feature Value by Using Inertial Measurement Unit By Yuto Omae, Yoshihisa Kon, Masahiro Kobayashi, Kazuki Sakai, Akira Shionoya, Hirotaka Takahashi, Takuma Akiduki, Kazufumi Nakai, Nobuo Ezaki, Yoshihisa Sakurai, and Chikara Miyaji JACIII Vol.21 No.4, pp. 616-631, 2017. JACIII YOUNG RESEARCHER AWARD 2020 Caili Zhang Approach to Clustering with Variance-Based XCS By Caili Zhang, Takato Tatsumi, Masaya Nakata, and Keiki Takadama JACIII Vol.21 No.5, pp. 885-894, 2017.
Deep Learning Hyper Parameter Optimization for Video Analytic in Centralized System

A framework to perform video examination is proposed utilizing a powerfully tuned convolutional arrange. Recordings are gotten from distributed storage, preprocessed, and a model for supporting order is created on these video streams utilizing cloud-based framework. A key spotlight in this paper is on tuning hyper-parameters related with the profound learning calculation used to build the model. We further propose a programmed video object order pipeline to approve the framework. The scientific model used to help hyper-parameter tuning improves execution of the proposed pipeline, and results of different parameters on framework's presentation is analyzed. Along these lines, the parameters that contribute toward the most ideal presentation are chosen for the video object order pipeline. Our examination based approval uncovers an exactness and accuracy of 97% and 96%, separately. The framework demonstrated to be adaptable, strong, and adjustable for a wide range of utilizations.
Error Handling

This chapter describes the way that Go deals with errors. I describe the interface that represents errors, show you how to create errors, and explain the different ways they can be handled. I also describe panicking, which is how unrecoverable errors are handled. Table 15-1 puts error handling in context.
Organization of Initial Text Processing in the Uzbek Language Synthesizer

The development of modern methods and technologies requires the creation of light and simple forms of the human-machine interface. In this regard, computational linguistics plays an important role, especially synthesizers that generate speech signals from the text. This paper discusses the process of organizing primary text processing for the Uzbek speech synthesizer. Some tasks are performed to group the existing elements of the text and prepare them for dubbing. The types of syllables in the Uzbek language are studied, the issues of dividing words into syllables are considered.
Spatial Information Preservation in Graph Convolutional Neural Network

Convolutional Neural Networks (ConvNets or CNNs) are that class of Neural Networks that have confirm very effective in areas such as classification and image recognition. Graph convolution neural network is that area of work that deals with the generalization of well-established neural models like convnets on structured datasets as there are numerous important problems that can be framed as learning from graph data. This paper focused to overcome one of the major weaknesses GCNN poses i.e. GCNN are Translational Invariant means these neural models are unable to identify the position of one object with respect to another. For example, the model will predict a car if it sees a bunch of random car parts like wheels, steering, headlights, and so on because all the key features are there. So, the main problem is to identify that the car parts are not in the correct position relative to another. We performed the experiments on two benchmark datasets, MNIST and smallNORB, and the accuracies obtained with our proposed models are comparably high. Thus the technique is able to preserve the spatial relationship among objects in the given structured dataset is the main motivation behind this paper.
Data Integration Project in Robologee

Robologee is a sub-unit of PT. Bangun Satya Wacana is part of Kompas Gramedia which is focused in Education section for ages 7 to 12 years. Robologee is a diversification of the existing sub-units in PT. Bangun Satya Wacana. Robologee has branches located at Gramedia World so it is expected that it will have an impact on Gramedia traffic. Currently, Robologee is transforming in order to integrate data that will be stored in the cloud by Amazon Web Service.The goal of this project is that data can be accessed by various users and stored in one platform. In the analysis of the digital transformation project, 15 respondents have been determined who are parents as external customers. Based on the indicators used in DMM. It was found that Robologee's current condition is at the Advancing level. Based on the Roadmap this project is implemented for 1 year and consists of four stages. In the Budgeting analysis, Robologee has payback period of 1.7 years with an IRR of 7.512% greater than the expected return of 5% by the company. Then the NVP is in a positive number, so this project is feasible to implement.
Photonic Quantum Interfaces Among Different Physical Systems

Photonics provides an ideal platform for carrying and distributing quantum information because photons are individually addressable; they experience little or no decoherence due to extremely low thermal noise even at room temperature; and they are the fastest information carriers available. As such, photons are perfect candidates for interfacing qubits in different physical systems with different operating frequencies (e.g., photons, ions, atoms, and superconductors). The ability to build such interfaces opens newopportunities to access many different physical systems and build hybrid quantum technologies. This chapter summarizes recent progress on quantum interfaces among diverse media, such as photons, atoms, ions, and mechanical oscillators, which are pivotal technologies for building large-scale distributed quantum computing and communication networks, as well as for understanding fundamental quantum phenomena related with light-matter interactions.
SportsStore: Cart and Database

In this chapter, I continue the development of the SportsStore application, adding support for a shopping cart and introducing a database to replace the temporary repository I created in Chapter 35 .
Remote Network Monitoring Technology Based on Computer Technology

Abstract With the rapid development of Internet technology, using images to express the characteristics of things more direct, compared with text, audio, image expression content is more ambiguous, which makes the rapid increase of digital images on the Internet. Nowadays one of the hot directions of computer vision research is how to accurately and quickly retrieve the target image from a large amount of image data. This paper summarizes the development of image retrieval technology at home and abroad, and proposes an image search method based on color histogram and Chi-square distance. This paper discusses how to construct an image search system, which can search the image quickly, describe the color distribution of the photo with color histogram, divide the image into five regions, extract image features from the color histogram of each region, and then get the data set of multi-dimensional image features. Then the chi-square distance is used to calculate the similarity of color histogram, and the closest image is selected as the first similar image, which realizes the necessary logic of receiving query image and returning related results.
Regional beta‐amyloid and tau deposition: Results from the Framingham Heart Study

Abstract Background The Framingham Heart Study (FHS), a three‐generation community‐based cohort studying cardiovascular disease across the adult lifespan, has expanded to include positron emission tomography (PET) of beta‐amyloid (Aβ) and tau. Our aim is to characterize these pathologies in this unique sample and utilize the wide age range to assess the spatiotemporal ordering of emerging Aβ and tau. Method 211 clinically‐normal adults aged 33‐74 from FHS underwent Pittsburgh Compound B (PIB) and Flortaucipir (FTP) PET. PIB and FTP were regionally quantified in Desikan regions using distribution volume ratio (DVR) for PIB and standardized uptake volume ratio (SUVR) for FTP. Three approaches were used to identify early accumulating regions: 1. A series of Age*APOE linear models to identify regions accumulating earlier in the lifespan in ε4 carriers. 2. Identification of early regions as those more frequently elevated as previously used in older adults, with Gaussian mixture models (GMM) conducted to evaluate bimodality and set biomarker positivity thresholds for each region. 3. Applied the same frequency approach using well‐validated PIB GMM thresholds based on older adults from the Harvard Aging Brain Study (HABS). Result For PIB, significant Age*APOE interactions (Fig. 1) were seen across multiple regions previously implicated as early‐accumulating based on elevation frequencies from older adult samples, as well as the pars opercularis (p=0.005) and lateral parietal cortices (p&lt;0.04). PIB was significantly bimodal across all ROIs (LRT&gt;36.1, p&lt;0.001; Fig. 1). Application of GMM‐based regional positivity frequencies derived within FHS versus from HABS thresholds led to substantial discrepancies in the spatiotemporal ordering of PIB ( r s =0.30, p=0.17). Age*APOE effects were not detected for any tau regions, but inferior temporal (IT), middle temporal (MT), and amygdala (AM) increased with age (Fig. 2). Higher global Aβ was also associated with higher FTP SUVR in IT, MT, and a trend for AM, as well as inferior parietal and precuneus (Fig. 2). Conclusion Aβ and tau mainly follow spatiotemporal patterns consistent with prior evidence in older adult samples. GMM‐based methods used in older adult samples to dichotomize biomarker positivity may be suboptimal in younger samples. Continuous approaches may better capture early Aβ and tau in younger populations.
Type and Interface Composition

In this chapter, I explain how types are combined to create new features. Go doesn’t use inheritance, which you may be familiar with in other languages and instead relies on an approach known as composition. This can be difficult to understand, so this chapter describes some features covered in earlier chapters to set a solid foundation on which to explain the composition process. Table 13-1 puts type and interface composition in context.
Lesbian at the vanguard

This tribute considers the work of linguist and novelist, Anna Livia (1955–2007). Anna was a noted fiction writer before becoming a linguist and much of her work considered language play in literature. Anna brought her experience as a lesbian activist to queer linguistics, where she played an important role in establishing the field. Her work continues to be an important example of linguistic research on lesbians, an area that continues to be underrepresented in the field.
Using Arrays, Slices, and Maps

In this chapter, I describe the built-in Go collection types: arrays, slices, and maps. These features allow related values to be grouped and, just as with other features, Go takes a different approach to collections when compared with other languages. I also describe an unusual aspect of Go string values, which can be treated like arrays, but behave in different ways depending on how the elements are used. Table 7-1 puts arrays, slices, and maps in context.
Conversational Agent Embodying a Historical Figure using Transformers

In this paper, we discuss how transformers, the current state of the art solution for Question Answering (QA) can be applied for implementing a conversational agent that can offer accurate and informative answers to questions about any user-chosen historical figure.We use Wikipedia to obtain data for every personality chosen and an information retrieval engine to store the data and perform full-text queries for obtaining the context dynamically.We tested the performance and accuracy for the different transformer models, data store, and retrieval methods.The best result was obtained using an ALBERT model with a heuristic retrieval method.This solution obtained an F1 score of 66.06 and an Exact Match (EM) score of 42.22.
CONCEPTUAL FOUNDATIONS OF ARTISTIC AND AESTHETIC EDUCATION (Philosophical level of comprehension)

The article offers a new look at the artistic and aesthetic education system based on the anthropological platform, declared in the XXth century as a possible reference point in the development of humanitarian knowledge, humanities, humanities disciplines. Within the framework of philosophical anthropology, the conceptual foundations of artistic and aesthetic education, including basic scientific theories and methodological approaches, have been developed. The analysis of the theory of artistic perception and the theory of artistic creation highlights applied aspects aimed at understanding the operational mechanisms and stages of artistic communication as a whole, which includes, on the one hand, the position of the author of an artistic work in the context of his era, and the position of the recipient, whose intention largely determines the directions of artistic and aesthetic education. In this context, the recipient's practical comprehension of artistic image is of great importance, which allows to raise the level of artistic and aesthetic education to a fundamentally new level. Anthropocentric and synergetic methodological approaches, considered by the author in an anthropological way and based on the theories of artistic perception and artistic creativity, take into account multiple socio-cultural changes and the needs of the younger generation in the modern world.
The potential of timber-based buildings in terms of energy efficiency

The topic of energy efficiency is currently under discussion. One of the areas of energy efficiency is the energy efficiency of buildings. The thermo-technical requirements for building envelope structures are gaining increasing importance due to new legislation and technical regulations regarding the reduction of heating and energy demands of buildings over time and because of continuously increasing energy prices. Building construction and the operational costs of buildings are among the largest consumers of material and energy resources and environmental pollutants. Ecological constructions are a response to the current state of the environment. A suitable solution that represents ecological construction, operation and comfortable living is the construction of low-energy and passive houses based on wood. Wood-based buildings have many benefits that are particularly timely in the context of sustainability today. The aim of this paper is to introduce selected aspects of wood-based buildings in the context of energy efficiency and thus to reduce the adverse effects of construction on the surrounding environment.