Reviewerly/exHarmony huggingface dataset:
Intake

OpflowVolume 46, Issue 9 p. 2-2 Departments Intake First published: 03 September 2020 https://doi.org/10.1002/opfl.1418Read 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. Volume46, Issue9September 2020Pages 2-2 RelatedInformation
Diagnostic Complex Of Psychological Support Of Families With Problem Children

The article presents a diagnostic complex of psychological support for families with problem children, the main purpose of which is to study and understand the essence of the family problem, its carriers and the potential for solving the dysfunctions. The diagnostic stage captures the signals of the problem situation with the subsequent construction of the appropriate logic for the further diagnostic study. Trusting contact is established with all participants in the problem situation, assistance is provided in verbalizing the problem, joint assessment of the possibility of its resolution. The final part of this stage is a clear definition of the problem. Comprehensive psychodiagnostics consists of the initial diagnosis to study the strengths and weaknesses of family members, identify and solve problems that arise during family interaction, conducting the diagnostic minimums in order to analyze the dynamics of functioning and overcome possible difficulties. Further work provides in-depth psychological diagnosis of members of the nuclear family system.
Music Computer Technologies in Music Studies at School of the Digital Age (Aspect of Musical Notation)

The development of music computer technologies in the late 20searly 21st century has significantly expanded the ways of obtaining information.High-tech information educational environment requires the search for new approaches and fundamentally new systems of education in the School of the Digital Age.The global applicability of the music computer technologies (MCT), provide new, in fact, limitless possibilities of selfrealization, stimulate the rapid development of intelligence, raising training to a new level; compatibility with traditional musical technology creates conditions for the continuity of musical eras and styles, their interpenetration and synthesis, reinforcing the interest in musical culture in general.In musical practice the big distribution has acquired a new class of musical instruments that includes keyboards, synthesizers, workstations, multimedia computers etc.Among the main objectives worked up by contemporary pedagogics in music, the authors focus their attention on the actual possibilities of digital technologies in enriching and enhancing the role of traditions that have been crystallized in practice of musical pedagogics for many centuries.The authors of the article discuss opportunities of music computer technology system for learning music and describe the experience of their use in their research and pedagogical practice with using the 'Soft Way to Mozart ' system
Indefinite Integrals of Generalized Intuitionistic Multiplicative Fuzzy Functions

In this chapter, based on the two kinds of derivative operations.
The New Technique Enhancing of Automatic Speech Recognition System for ODIA Language using HTK Based On Hidden Markov Model (HMM)

The purpose of this paper is to address the application to an Indian Regional Language, ODIA of a single word Automatically Speech Recognition System (ASRS). The toolkit is based on Hidden Markov Model (HMM). The details was obtained from 8 ODIA Language speakers. The program is then qualified for 205 different terms in ODIA. Samples from six separate speakers have again been obtained. This is then evaluated in real time. A GUI has been created to enhance the system's interactivity. We used and introduced the test framework for development of the GUI JAVA application. A comprehensive model of an ASR framework was developed to explain each HTK resource using HTK library modules and software. The findings of the experiment indicate that the overall machine efficiency is 93.45%.
New Method for Load Balancingin Cloud Computing

Internet, since the beginning of its work, has undergone many changes one of the latest changes is how the internet cloud computing. New technologies cloud computing offers because of features all kinds of facilities to the users as a service. Each evolution, change and novel concept in the world of technologies has its own problems and complications. Accordingly, benefiting from cloud computing is no exception to this rule and it has challenged researchers and proponents in this research domain. Indeed, some major challenges in cloud computing are: load balancing, safety, reliability, ownership, data backup, data portability and supporting several platforms. One challenge for such matters in the field of cloud computing is load balancing optimization in the cloud. The so-called cloud computing, including virtualization, distributed computing, networking, software and Web services. With respect to the ever increasing significance of load balancing in cloud computing the researchers in this paper intended to improve load balancing by using a novel method. The related studies were reviewed, evaluated and compared with each other. The efficiency of the proposed method was analyzed and compared with those of other studies. The results of the present study revealed that the proposed method is better than other dynamic virtual machine (VM) consolidation algorithms in terms of reducing SLA (service levels agreement) violation and the amount of transmitted data volume transmission has to present a better performance than other methods.
Effect of Exposure of Smartphone Use on Visually Evoked Potential (VEP) in Healthy Adults

Aims:To assess and compare VEP parameter (amplitude and latency of P100) in healthy adults (MBBS students) using smartphone. Objectives:• To record P100 (latency, amplitude) in 1 st year MBBS students using smartphone for less than three hours and for more than three hours after sunset• To record P100 (latency, amplitude) MBBS students using smartphone for duration of less than three years and for more than three years• To Compare P100 (latency, amplitude) 1 st year MBBS students using smartphone for less than three hours and for more than three hours after sunset• To Compare P100 (latency, amplitude) MBBS students using smartphone for duration of less than three years and for more than three years Settings and Design: Neurophysiology Lab at the department of Physiology, JNMC, Sawangi (Meghe), Wardha. Method and Material:A cross sectional study was done in 50 healthy MBBS studentsfrom JNMC.Results: There is significant difference in the mean values of P100 latencies of right and left eye and in the mean values of P100 amplitude of right and left eye in individuals with exposure of less than three and more than three hours per day after sunset. Conclusions:We conclude that nocturnal use of mobile phones especially in the bright light exposes an individual to the blue light resulting in various deleterious effects.
Real-Time Face Detection and Tracking

Face detection, face tracking, and Object identification is the first process in applications such as face detection-based attendance marking system, video surveillance, and tracking of human faces in case of emergency. The main objective of our project is to detect and track the moving human faces with a permanently placed fixed camera. We propose a general moving face detection and tracking system.Our project mainly focuses on the moving human face detection in a situation, let us say, the people moving together are meeting with each other and are detected as the people as long as they stay in the situation. This can be done with the help of an Image Difference Algorithm with the python programming language support, and also that the time period for each and every frame can be calculated.
Introduction to the Special Issue on Software Engineering in Practice

Software: Practice and ExperienceVolume 51, Issue 4 p. 689-690 EDITORIAL Introduction to the Special Issue on Software Engineering in Practice Judith Bishop, orcid.org/0000-0002-2892-1632 Department of Computer Science, Stellenbosch University, Stellenbosch, South AfricaSearch for more papers by this authorKendra M. L. Cooper, Corresponding Author kendra.m.cooper@gmail.com orcid.org/0000-0003-4771-1371 Independent Scholar, Kelowna, Canada Correspondence Kendra M. L. Cooper, 255 Aurora Crescent, Kelowna, BC, V1X 7L8, Canada. Email: kendra.m.cooper@gmail.comSearch for more papers by this author Judith Bishop, orcid.org/0000-0002-2892-1632 Department of Computer Science, Stellenbosch University, Stellenbosch, South AfricaSearch for more papers by this authorKendra M. L. Cooper, Corresponding Author kendra.m.cooper@gmail.com orcid.org/0000-0003-4771-1371 Independent Scholar, Kelowna, Canada Correspondence Kendra M. L. Cooper, 255 Aurora Crescent, Kelowna, BC, V1X 7L8, Canada. Email: kendra.m.cooper@gmail.comSearch for more papers by this author First published: 25 November 2020 https://doi.org/10.1002/spe.2932 Read 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. Volume51, Issue4Special Issue: Introduction to the Special Issue on Software Engineering in PracticeApril 2021Pages 689-690 RelatedInformation
Fast Forward with your VCR: Visualizing Single-Video Viewing Statistics for Navigation and Sharing

Online video viewing has seen explosive growth, yet simple tools to facilitate navigation and sharing of the large video space have not kept pace. We propose the use of single-video viewing statistics as the basis for a visualization of video called the View Count Record (VCR). Our novel visualization utilizes variable-sized thumbnails to represent the popularity (or affectiveness) of video intervals, and provides simple mechanisms for fast navigation, informed search, video previews, simple sharing and summarization. The viewing statistics are generated from an individual's video consumption, or crowd-sourced from many people watching the same video; both provide different scenarios for application (e.g. implicit tagging of interesting events for an individual, and quickly navigating to others' most-viewed scenes for crowd-sourced). A comparative user study evaluates the effectiveness of the VCR by asking participants to share previously-seen affective parts within videos. Experimental results demonstrate that the VCR outperforms the state-of-the-art in a search task, and has been welcomed as a recommendation tool for clips within videos (using crowd-sourced statistics). It is perceived by participants as effective, intuitive and strongly preferred to current methods.
Scalable Semiparametric Inference for the Means of Heavy-tailed Distributions

Heavy-tailed distributions present a tough setting for inference. They are also common in industrial applications, particularly with internet transaction datasets, and machine learners often analyze such data without considering the biases and risks associated with the misuse of standard tools. This chapter outlines a procedure for inference about the mean of a (possibly conditional) heavy-tailed distribution that combines nonparametric analysis for the bulk of the support with Bayesian parametric modeling – motivated from extreme value theory – for the heavy tail. The procedure is fast and massively scalable. The work should find application in settings wherever correct inference is important and reward tails are heavy; we illustrate the framework in causal inference for A/B experiments involving hundreds of millions of users of eBay.com.
Latent Dirichlet Allocation

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.
Negotiated Contracts for Cloud Services

Abstract This chapter examines negotiated contracts for cloud services. Given that the use of cloud services has now become widely accepted and in light of the fact that providers' standard contract terms have evolved if not improved, do customers still deem it necessary to seek to negotiate contracts and if so, which issues are typically focused on? Are providers willing to negotiate or have they hardened their attitudes to negotiation? The chapter outlines providers' perspectives on cloud contract terms and customers' perspectives on cloud contracts including the role of integrators. It looks at the factors that customers take into account when considering specific terms, including whether or not to negotiate the terms in question or look at other methods of risk mitigation. The fact that data breach response and liability for data breaches tops the list of most-negotiated terms suggests that cloud providers and customers are still grappling with the General Data Protection Regulation's (GDPR) requirements and trying to come up with terms that will satisfy both customers' and providers' needs.
Design and Implementation of a Low-cost Particle Image Velocimetry System for Undergraduate Research and Education

Abstract Design and Implementation of a Low Cost Particle Image Velocimetry System for Undergraduate Research and Education The advent of Particle Image Velocimetry (PIV) has allowed experimental fluid dynamicsmeasurements to be realized in significantly higher detail than standard sensors and devices designed tomeasure pressure and volume flow rate. PIV setups can be used to determine the entire flow field in aregion of interest. These devices are quickly reshaping the field; however, the barrier to entry issignificant cost ­ often approaching $100,000. This paper focuses on the details of creating a costeffective and portable PIV system that can be used in undergraduate research and education as well asdemonstrations for K­12 education. The usefulness of PIV may be its most important aspect in the field experimentation; it is notnecessarily its most useful application in education. One difficult task in K­12 and undergraduateeducation is keeping students engaged and interested in a particular subject. The mathematical details offluid dynamics can be highly tedious, but a cost effective PIV system could change this and allow fluidmechanics to be explored at a much earlier time in education with very visual results that are also usefulfor quantifying flow fields. In this paper we describe our efforts at the University of _________ to design and implement alow­cost PIV system. The design has progressed iteratively: first as a summer project for incomingfreshmen as a part of an extant National Science Foundation (NSF) STEM Talent Expansion Program(STEP) Grant, then as a part of undergraduate research (UGR) as part of several local UGR studentgrants, then for senior capstone design projects aimed at design of systems to make qualitymeasurements to support our overall research goals. Details of design, costs, strengths, and challengesare presented. We now seek to engage K­12 students with PIV, our initial ideas regarding this directionare discussed.
A Comparative Study of Different Printed Documents to Estimate the Type of Printer Used

Printer examination in questioned document examination has become a necessity in the present time due to the progressive use of printers in the creation of documents as compared to that of handwritten documents and also the counterfeiting of documents printed by different printers.
Departing from Bayesian inference toward minimaxity to the extent that the posterior distribution is unreliable

A Bayesian model may be relied on to the extent of its adequacy by minimizing the posterior expected loss raised to the power of a discounting exponent. The resulting action is minimax under broad conditions when the sample size is held fixed and the discounting exponent is infinite. On the other hand, for any finite discounting exponent, the action is Bayes when the sample size is sufficiently large. Thus, the action is Bayes when there is enough reliable information in the posterior distribution, is minimax when the posterior distribution is completely unreliable, and is a continuous blend of the two extremes otherwise.
Tera-scale coordinate descent on GPUs

Abstract In this work we propose an asynchronous, GPU-based implementation of the widely-used stochastic coordinate descent algorithm for convex optimization. We define the class of problems that can be solved using this method, and show that it includes many popular machine learning applications. For three such applications, we demonstrate at least a 10 × training speed-up relative to a state-of-the-art implementation that uses all available resources of a modern CPU. In order to train on very large datasets that do not fit inside the memory of a single GPU, we then consider techniques for distributed learning. We show that while such techniques do not necessarily allow one to achieve further speed-up, they do allow one to train on datasets that would otherwise not fit into memory. We thus propose a distributed learning system that uses the synchronous CoCoA framework to distribute the global optimization across GPUs, and our novel asynchronous algorithm to solve the corresponding local optimizations within each GPU. We benchmark such a system using a 200 GB dataset that consists of 1 billion training examples. We show by scaling out across 16 GPUs, we can train an SVM model to a high degree of accuracy in around 1 min: a 15 × speed-up in training time compared to a state-of-the-art CPU-based implementation that uses 640 threads distributed across 8 CPUs.
De-Speckling of Ultrasound Images Using Local Statistics-Based Trilateral Filter

Speckle noise in ultrasound images is a major hindrance for the automation of segmentation, detection, classification and measurements of region of interest, to assist clinician for diagnosing pathologies. Speckle noise occurs due to constructive and destructive interference of the echo signals reflected from the target and has a granular appearance. Various techniques have been devised for speckle reduction. Most of these techniques are based on adaptive filters, wavelet transform and anisotropic diffusion filters. In this paper, a new speckle reduction technique based on the trilateral filter and local statistics of the image has been developed. The local speckle content of the image influences the trilateral filtering. The trilateral filter is a robust edge preserving filter which considers the similarity of neighboring regions in terms of adjacency, intensity and edge details. Hence, the new method preserves the finer details of the ultrasound images in the process of filtering speckle noise. The proposed technique is validated using synthetic, simulated and real-time clinical ultrasound images. Comparison of the proposed technique with the existing speckle removal algorithms in terms of quality metrics such as MSE, PSNR, UQI, SSI, FoM has been made and best results are obtained for the proposed technique.
The Dark Web

The Dark Web is its own clandestine network of thousands of websites that most of us do not even know exist, much less how to access. The Dark Web uses its own tools to keep users anonymous and their activities hidden. The Dark Web is so well concealed that the full extent of its use remains largely the topic of hushed conversations. From black market drug sales to child pornography, the Dark Web operates at two extremes of the Internet, from venues for anonymous whistleblowing on one end to unguarded censorship on the other. This article provides a primer for those interested in learning more about the “known unknowns” of the Dark Web. Readers will find an excellent opening manuscript for the newly launched International Journal of Cyber Research and Education as it sets the stage for future research in cyber security and law enforcement. The paper will examine three foundational questions for the reader: What constitutes the ‘deep/dark/underground' web and keeps it obscure and remote from the community of legitimate users? How can websites that occupy the same virtual space range exist in two parallel dimensions from discoverable to undiscoverable? And finally, how do the actors on the Dark Web mature from novice to advanced? Is it the same process followed by users of the known web? In the corpus of this article, the authors will briefly examine how online markets exist simultaneously on the Internet, serving clients in both known online environments as well as the more secretive, anonymous online world. They will examine how nefarious actors migrate from the “good” web to become novice and then advanced users of the “evil” environments. To the neophyte user, the process introduced herein may appear relatively straightforward. In truth, the notion that any but the most staunchly dedicated practitioner can become a vetted participant in the ‘dark web' is inconceivable. Even so, with the sheer volume of actors operating in numerous underground forums and marketplaces, the impact remains significant and growing geometrically. Government and industry from all over the globe are hindered in their ability to track and identify the truly advanced actors operating in these more secretive environments. We shall soon see why this is the case.