Reviewerly/exHarmony huggingface dataset:
Chapter 2: Data Types

Data are the primary concern of clustering algorithms. In terms of how data are organized, data can be divided into two types (Inmon and Linstedt, 2014; Pries and Dunnigan, 2015; Isson, 2018): structured data and unstructured data. Structured data have a regularly occurring format and can fit a conventional relational database. In contrast, unstructured data have no structure that is recognizable to a computer and come in different formats, such as text, image, audio, and video. In this chapter, we give a brief introduction of these data types.
Remedies

When taking a case of copyright infringement to court, there are a number of remedies available for the copyright holder, should the claim be successful. The types of remedies available are different for civil and criminal action. In civil proceedings the rightsholder may be able to obtain an injunction, damages, as well as any destruction or surrendering of infringing materials. In criminal matters, there is also the possibility that a person found guilty of copyright infringement can receive a prison sentence. This chapter will first cover the pre-action and temporary remedies that can be extremely beneficial for copyright holders; including interim injunctions and measures to preserve evidence. It then covers other types of injunctions, damages and lastly prison sentences. There are only a few minimum standards set at international level for copyright infringement remedies. This means that the type of remedies available depend on the country of the action, as well as the amount of damages or length or prison sentence that may be imposed. The international agreements do set out that countries will enable rightsholders to have effective action against infringement, including the availability of remedies that not only compensate the rightsholder but also act as a preventative deterrent to future infringements. Courts can grant preliminary remedies, meaning that they take action in a matter before it has been decided at trial, and permanent remedies which come after the outcome of the case is decided. The preliminary remedies are discussed in this chapter, followed by the permanent remedies. In addition, specific remedies that are available for dealing with online copyright infringement are discussed in the following chapter.
Elements of probability

Probability is introduced and its axioms specified. Conditional probability and the concept of independent events are studied.
DEVELOPMENT OF PRINCIPLES AND MEANS OF DIAGNOSTICS OF COMPETENCIES FORMED WHEN STUDYING DISCIPLINES OF THE MATHEMATICAL PROFILE IN STUDENTS OF TECHNICAL SPECIALTIES

The state of solving the problem of formation of mathematical competencies in the study of mathematical disciplines in technical students is clarified. Approaches to the diagnosis of mathematical training of students in the process of teaching mathematical disciplines at the university, which provide continuous, objective and timely information about the current level of mathematical training of students, as well as gaps and shortcomings in the formation of mathematical competence.&#x0D; The goals of diagnostics are formulated, which should reflect the structure and content of mathematical competence as a result of mathematical training. In the structure of mathematical competence, in accordance with the content of mathematical activity, it is appropriate to consider: possession of heuristic methods of finding solutions to problems; possession of methods for solving problems; knowledge of methods of mathematical modeling, application of mathematics in other areas.&#x0D; The analysis of prospects of application of automation of process of estimation of knowledge of students on the basis of computer testing is carried out that gives the chance to receive the full information on process and results of mathematical preparation of students, increase of motivation of their cognitive activity, development of reflection and skills of self-diagnostics.&#x0D; The advantages and disadvantages of using automated knowledge control systems are considered. With the help of such systems the differentiation of educational material is carried out, the interrogation providing objectivity of diagnostics of knowledge is carried out, results of training of students are fixed. Automated systems are focused on in-depth assimilation of information individually by each student.
Iteration/Looping

In this section we will look at the while loop and the for loop available in Python. These loops are used to control the repeated execution of selected statements.
Secure Auditing and Intelligent Compression in Cloud

As the cloud computing technology develops throughout the decennary, externalising data to store using cloud resource becomes a trend, which is benefited in heavy data management and maintenance. Notwithstanding, since the externalized cloud depository is not fully reliable, while achieving integrity auditing it elevate security treat on how to realize single instance storage in cloud. In this work, we study the problem of integrity auditing and secure intelligent compression on cloud data. Peculiarly, directing at attaining both eliminating duplicate copies of repeating data i.e., secure deduplication and integrity of data in cloud, we propose an auditing entity with a perpetuation of a MapReduce cloud, which helps audit the integrity as well as uploading of data after clients generate data tags having been collected in cloud.
STRUCTURE OPTIMIZATION OF DEEP BELIEF NETS IN THE APPLICATIONS OF IMAGE RECOGNITION.

Deep belief network (DBN) has become one of the most important models in deep learning, however, the un-optimized structure leads to wasting too much training resources. To solve this problem and to investigate the connection of depth and accuracy of DBN, an optimization training method that consists of two steps is proposed. Firstly, by using mathematical and biological tools, the significance of supervised training is analyzed, and a theorem, that is on reconstruction error and network energy, is proved. Secondly, based on conclusions of step one, this paper proposes to optimize the structure of DBN (especially hidden layer numbers). Thirdly, this method is applied in two image recognition experiments, and results show increased computing efficiency and accuracies in both tasks.
Technological displacement: The Coat Check interactive augmented reality installation in perspective

Technological Displacement: The Coat Check Interactive AR Installation in Perspective is a two-part dissertation that involves the research/creation of an augmented reality installation and a textual critique of displacement both as a socio-cultural phenomenon and a technology-driven status quo. Digital technologies involve a series of displacements from data storage and transfer to creating global networks. Going hand in hand with human mobilities technological displacement affects our lives and interactions deeply. Multimedia and digital overlaying of information and interconnectedness (mobile devices, tracking technologies, the internet...) make up our quotidian in various degrees, impelling us to be 'present' in time and places we actually are not. Technological displacement may be viewed as an extension of physical displacement of individuals and communities in that the need to reconcile, re-invent and innovatively market proximity becomes more and more an underlying theme of contemporary lives. Nowhere the reorientations of presence is more accentuated than 'augmented space', as described by Lev Manovich, "a physical space overlaid with dynamically changing information, multimedia in form and localized for each user." (219) It may be argued that our sense of reality is already 'augmented' by digital stimuli in many ways. Here I make the case that in an augmented or digitally enhanced environment we are displaced multiple times, or "multiplaced". Augmentation is superimposing multimedia to real space, blurring the boundary between the real and the virtual, creating a heterogeneous space defined neither by the standards of the virtual nor the real but the coexistence and cooperation of both. Augmented reality functions on the principle of multiple displacements in that real space is not a backdrop to multimedia: it is indispensable to the overall embodied experience. I created the Coat Check in 2011 using motion tracking technologies (Intersense IS900), specialized cameras (Point Grey 360 degree Spherical Vision Camera), screens (Fog Screen), software (Max/MSP), tools and applications (Snapdragon AR). The conceptualization of The Coat Check is based on an analogy between digital technologies and coat checks that are both storage, retrieval and displacement systems. The Coat Check also raises questions on identity and history as it refers to belonging, temporality, and mobility.
Prediction of Online News Popularity using Machine Learning

In today's world, online news is the source of news and information for many people. The popularity of online news can be dependent on various factors like the number of shares by the readers or the number of likes and comments on the news etc. In our research paper, we intend to find the best machine learning algorithm to predict the popularity of the news article. The dataset is taken from the UCI repository. We will apply five different algorithms such as random forest, logistic regression, etc and then compare the performance of these algorithms based on various performance measures such as accuracy and precision. Random forest showed the best results with the highest accuracy. Our work can be used by online publishers to predict the popularity before publication.
Complaint about ad for Boehringer BVD vaccine upheld

Veterinary RecordVolume 185, Issue 8 p. 220-220 News and reports Complaint about ad for Boehringer BVD vaccine upheld First published: 24 August 2019 https://doi.org/10.1136/vr.l5243Read 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 onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume185, Issue8August 2019Pages 220-220 RelatedInformation
COALESCENCE: An Android-Based Instructional Application with Augmented Reality for Chemistry Students

COALESCENCE is intended to let the Chemistry students learn and for Chemistry Teachers to use as a tool in teaching the subject. This application uses Augmented Reality to present information and 3D models of laboratory equipment, periodic elements, compound elements, and planet elements. Trivia and interactive quizzes are also provided to assess the user’s knowledge. Iterative Model was applied in project development. This application was created using Photoshop, Unity 3D, Blender, and Maya. In using the application, the minimum Android OS requirement is Android 6.0 (Marshmallow) and above. The test instruments used were Functionality, Compatibility, and Conformance test aligned with Android Core App Quality Standards. It got a 100% rating for the three test instruments’ used. In evaluation, Mobile Application Rating Scale was utilized with an average mean of “3.44”, the standard deviation of “0.17” and an interpretation with a “Highly Acceptable” feedback from the evaluators in all aspect of the application.
DL-RLSTM: An Anomaly Detection Framework for High Dimensional Time Series Data

With the development of communication technology and the popularization of Internet of Things (IoT) applications in daily life, anomaly detection for time series data has been paid more attentions. To mitigate the imbalance and incorrectness of data labels in anomaly detection, unsupervised anomaly detection has been widely used to detect abnormal data. Although a number of efforts on unsupervised anomaly detection has been developed, most of these schemes focus on detecting abnormal data with low-dimensional and achieve undulatory efficiency on detecting abnormal data with high-dimension. In addition, most of the existing schemes determine the data as abnormalities with the thresholds defined by expertise experience, resulting in undulatory efficiency on abnormal data detection as well. To address these issues, in our paper, an advanced Double Layer-RLSTM framework, namely DL-RLSTM, is proposed to detect the abnormal time series data with high-dimension effectively. Particularly, two neural network layers are considered in our DL-RLSTM framework, in which the RLSTM network is introduced in the first neural network layer to extract the temporal feature of time series data. The second neural network layer in our DL-RLSTM framework are served as the autoencoder to reconstruct temporal feature of time series data extracted by the first neural network layer. Different from the traditional projection-based dimensionality reduction, our DL-RLSTM framework can maximize the retention of temporal feature of time series data. Additionally, K-Means is introduced in our DL-RLSTM framework to determine the abnormal time series data according to the anomaly scores obtained from the autoencoder. By doing this, the participation of expertise experience on abnormality thresholds determination can be minimized. Via evaluations, the results show that our DL-RLSTM framework can achieve better detection efficiency on high dimensional abnormal time series data in comparison with existing schemes.
One-Stage Logo Detection Framework using AdaBoost Resnet50 Backbone

Logo is an important asset as it is designed to express identity or character of the company or organization that owns the logo. The advent of deep learning methods and proliferated of logo images sample dataset in the past decade has made automated logo detection from digital images or video an interesting computer vision problem with wide potential applications. This paper presents a novel one-stage logo detector framework in which the backbone of the proposed logo detector is a deep learning model which is trained supervisedly using gradient descent training algorithm and the target logo classes as input dataset. The experiment results showed that AdaBoost Resnet50 (0.58 MAP) as the logo detector backbone outperforms Resnet50 (0.56 MAP), VGG19 (0.32 MAP), and AdaBoost VGG19 (0.56 MAP).
A Machine Learning Model for Recommending Restaurants based on User Ratings

However, oftentimes people just search a restaurant by using word “restaurant”, while the word “restaurant” means differently to different individuals. For an Asian, it can mean a “Chinese restaurant” or “Thai restaurant”. How to correctly interpret search requests based on people’s preference is a challenge. Building a machine-learning model based on activity history of a registered user can solve this problem. The activity histories used by this research are reviews and ratings from users. This project introduces a data processing pipeline, which uses reviews from registered users to generate a machine-learning model for each registered user. This project also defines an architecture, which uses the generated machine-learning models to support real-time personalized recommendations for restaurant searching and type of foods good at those recommended restaurants. Finally, this project aims to develop a good machine learning model, different collaborative filtering methodologies are considered to predict restaurants using user ratings. Slope One, k-Nearest Neighbors algorithm and multiclass SVM classification are some of the collaborating methodologies are going to consider in this project.
Efficacy and Safety of Autologous Platelet Concentrate in The Treatment of aging of The Neck.

Introduction: Neck rejuvenation has a certain degree of difficulty, both due to its location and mobility, as well as its anatomical characteristics. Objective: To evaluate the efficacy and safety of intradermal microinjection of autologous platelet concentrate (APC) in the treatment of signs of neck aging. Method: An observational, analytical and longitudinal study was carried out in 60 patients from the Hospital Clínico Quirúrgico: “Hermanos Ameijeiras”, in the period between March 1, 2017 and March 31, 2020. The treatment was applied monthly for 1 year. The final evaluation was carried out 3 months after the end of the treatment. Results: 60 women with an average age of 45 ± 4.3 years were treated. After treatment, there were significant changes in the Glogau Photo Damage Scale (P = = 0.024), in the Global Aesthetic Improvement Scale (P &lt;0.002) and in the Allergan Neck Transverse Lines Scale (P = 0.013). The adverse events found were pain, inflammation and ecchymosis. The degree of satisfaction reported by the patients was good (10.0%) and very good (90.0%) (P &lt; 0.0012). Conclusions: The autologous platelet concentrate proved to be effective and safe to reduce the signs of aging in the neck, associated with a high degree of patient satisfaction.
Rancang Bangun Sistem Dashboard Akreditasi Program Studi (APS) Standar 5 Berbasis KPI

Accreditation is one form of approval and feasibility of universities or study programs conducted by the National Higher Education Accreditation Agency (BAN-PT). The purpose and benefits of higher education institution accreditation are to provide assurance that accredited tertiary institutions have met the quality standards set by BAN-PT. In order to be able to monitor and evaluate all activities to achieve the expected accreditation value, a management application is needed that is able to integrate the entire contents of supporting data one form of visualization that can describe it is the dashboard system. This research intend to establish an Accreditation Management Information System application with a dashboard appearance in the web-based Muhammadiyah University of Malang. This application is constructed using HTML, PHP, and Codeigniter Framework by using the MySQL storage format as a database. The development method used in system development is the Spiral development model. The results of this research are that the dashboard system can provide an overview of the position of accreditation values of the University, Faculty and Study Program, so that parties from each University management, Faculty and Study Program can take action to prepare and improve values to face future accreditation assessments. AbstractAccreditation is one form of approval and feasibility of universities or study programs conducted by the National Higher Education Accreditation Agency (BAN-PT). The purpose and benefits of higher education institution accreditation are to provide assurance that accredited tertiary institutions have met the quality standards set by BAN-PT. In order to be able to monitor and evaluate all activities to achieve the expected accreditation value, a management application is needed that is able to integrate the entire contents of supporting data one form of visualization that can describe it is the dashboard system. This research intend to establish an Accreditation Management Information System application with a dashboard appearance in the web-based Muhammadiyah University of Malang. This application is constructed using HTML, PHP, and Codeigniter Framework by using the MySQL storage format as a database. The development method used in system development is the Spiral development model. The results of this research are that the dashboard system can provide an overview of the position of accreditation values of the University, Faculty and Study Program, so that parties from each University management, Faculty and Study Program can take action to prepare and improve values to face future accreditation assessments.
Breathing Exercise

The Yale ReviewVolume 107, Issue 4 p. 40-50 FICTION Breathing Exercise Raven Leilani, Raven Leilani Work has been published in Granta, McSweeney's Quarterly Concern, Conjunctions, The Cut, and New England Review.Search for more papers by this author Raven Leilani, Raven Leilani Work has been published in Granta, McSweeney's Quarterly Concern, Conjunctions, The Cut, and New England Review.Search for more papers by this author First published: 20 January 2020 https://doi.org/10.1111/yrev.13555AboutPDF ToolsExport 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 onFacebookTwitterLinkedInRedditWechat Volume107, Issue4October 2019Pages 40-50 RelatedInformation
Robust and Accurate Human Tracking Algorithm for Handling Occlusion and Out of Plane Rotation

Robust and accurate human tracking using computer vision is acquiring more and more attention, seeking to meet the demands of the increasing number of applications. This paper presents a novel approach to handle occlusion and out of plane rotation. Both these issues are crucial and continue to be a challenge in all state of art algorithms of computer vision-based human tracking. In this paper a SURF oriented scheme based human tracker is proposed, which searches for the target human in expanded rectangular region surrounding the previous target location. There is an online update of object model by selecting fresh templates every time. Here, superimposition of keypoints obtained from previous templates is done on fresh template using Affine transformation. Whether it’s a pose change or not, is affirmed by affine transformation, by calculating aspect ratio of target enclosed region. An Autotuned classifier discriminates the case of occlusion and pose change and confirms tracking failure. The success rate and computational time proves the accomplishment of the proposed algorithm
Uneasy Lie the Heads: New American Library in Transition

The acquisition in 1960 of New American Library (NAL) by the Times Mirror Company of Los Angeles has become the archetype of the evils of book publishing mergers that have contributed to the decline of literary publishing in the United States. In February 1960, Blythe &amp; Company, which later received a $100,000 finder’s fee, prepared a report for NAL that noted the combined earnings of the Times Mirror Company at slightly under $5 million for 1959. A month later Times Mirror ordered a similar study of New American Library prepared by McKinsey &amp; Company, Los Angeles-based management consultants. Toward the end of 1962 McKinsey &amp; Company circulated its preliminary reassessment of NAL. The McKinsey recommendation for finding successors to Victor Weybright and Kurt Enoch seems to have fared better, at least at the outset. David Brown was hired in March 1963, reporting directly to Weybright.
USING FORMAL CONCEPT ANALYSIS TO EXPLORE HIDDEN KNOWLEDGE IN THE ASSESSMENT OF A MATH COURSE

Since the emergence of COVID-19, online teaching and e-Learning has become essential in education.Actually, in at our University, we have had to move to a complete online teaching framework through the Moodle e-learning system.As a result, we have had to deploy new material as videos in Youtube channels, new exercises, tasks, live teaching, etc that have generated a huge amount of data that contains interesting information.In particular, we have used randomly generated exams from a bank of quizzes to evaluate the students.In this paper, we analyze the results of these quizzes using Formal Concept Analysis tools in order to check the hidden knowledge in the assessment process with the goal of improving the developed material for next years.In addition, we will analyze how the different exercises and tests relate to each other so that we can use this information in the following courses to improve our lectures.