Reviewerly/exHarmony huggingface dataset:
Virtual Musealization Using Video Game Engines. The Museu à beira do oceano by Lina Bo Bardi

This communication shows the experimentation with some new visualization techniques in real time offered by video games development environments such as Unreal, which is currently one of the most accessible and versatile.The work is proposed in such a way that would also serve to pay tribute to one of the great architects of history, the Italian-Brazilian Lina Bo Bardi, who, like so many other female architects, has generally been underestimated in the history of architecture. As a tribute to the work of Bo Bardi, one of his projects has been chosen; the Museu à beira do oceano, which finally failed to materialize, but fortunately there was enough graphic information for its virtual reconstruction.The result of this research work consisted of a three-dimensional modelling of the Museum, based on the information collected, and the generation of a virtual museum that allows its interactive and real-time visualization through Unreal Engine. These visualization techniques are very interesting as an informative medium and, especially in this case, because they will allow discovering an unrealized work in which the iconography and aesthetics characterizing the work of this unique architect are recreated.
Informational and analytical system for monitoring migration of migratory birds in Northern Kazakhstan

Abstract Nesting and stopping sites between nesting and wintering periods are of great importance for birds. The disappearance of these places as a result of human activity, the destruction of wetlands for use in agriculture does not allow birds to feed during the flight, which causes the death of birds during migration. The article is devoted to observations of migration of migratory birds of Northern Kazakhstan. The purpose of these observations is to track the population of birds, places of mass accumulation of migratory birds, wintering places. Modern satellite telemetry tools are used to monitor the route of movement and the time of stay of birds in certain local zones. Computer processing of data, stored on the server, allows to map the route, analyze, model and predict the behavior of birds during migration.
Security Technology.docx

Security professionals were surveyed using the Human Aspects of Information Security Questionnaire. Three research questions were asked and analyzed to determine issues and protocols used to protect sensitive information. &lt;p&gt;&lt;a&gt;&lt;b&gt;&lt;/b&gt;&lt;/a&gt;&lt;/p&gt;
A Closed Loop Controller Design Which Can Minimize the Wind Effects on a Parabolic Solar Tracker

In the present work, it was conducted a steady-state fluid analysis to obtain the aerodynamic coefficients of a Parabolic Solar Tracker (PST) for different azimuth and elevation angles. A computational fluid dynamic (CFD) wind flow analysis technique was applied to model an extreme weather condition called North Wind (NW), which can severely affect the PST under operational conditions. The North Wind case simulated was validated using experimental data without bottom effects in order to verify the degree of approximation between the results obtained with CFD approach. The obtained aerodynamic coefficients were used to: (i) establish both analytical and numerical models for each PST degree of freedom for dynamic analysis and simulation purposes, (ii) design different closed loop controllers which can minimize the wind effects and (iii) to establish a correct dimensioning of the control actuators.
Reclassification of ‘JISHI P, Q’ Internal Semantic type and Reanalysis of Korean Translation Meaning

This paper is based on the study of ‘JISHI P, Q' complex sentences and reinterpreted the logical connection of ‘JISHI P, Q'. Through various example analysis, the internal semantic relation of ‘JISHI P, Q' is classified in detail, and based on this, the meaning of the Korean corresponding to the ‘JISHI P, Q' is presented. The results of this study are as follows: 1. We have provided plenty of examples related to the ‘JISHI P, Q' to represent factual content. In addition, the grammatical features appearing in the sentence of the ‘JISHI P, Q' which represent factual content, are newly presented. 2.The ‘JISHI P, Q' expressing hypothetical or factual content is categorized and illustrated. This allows us to recognize that the ‘JISHI P, Q' can appear in many forms. 3.The Korean meanings corresponding to the ‘JISHI P, Q' in hypothetical and factual content are presented separately. ‘-더라도’ can be used in most ‘JISHI P, Q' constructs, but it can be applied mainly to hypothetical meanings, and ‘-아/어도’ is relatively natural when expressing factual meanings. In addition, ‘-ㅁ 에도’ and ‘-ㄹ지라도’ can also appear in factual meaning expressions, and sometimes ‘- 지만’ may be used. It is hoped that the results of this study can be helpful for the writing and education of grammar.
8 Ways to Boost Security for a Retail Business | Commercial Locksmith

If you operate any type of business, let alone a retail store, you may experience either a burglary or an attempted burglary at some point. To a certain ...
Adventures in Time: Working at the Limits of Music Notation

This article describes some of the work of the team of researchers working on project ‘Interpreting the Mensural Notation of Music: An Expert System Based on the Theory of Johannes Tinctoris’ (2017-2021) at Royal Birmingham Conservatoire, funded by the Arts and Humanities Research Council (AHRC). It was published on Arts and Minds, the official blog of the AHRC.
Sample Efficient Bayesian Reinforcement Learning

Artificial Intelligence (AI) has been an active field of research for over a century now. The research field of AI may be grouped into various tasks that are expected from an intelligent agent; two major ones being learning & inference and planning. The act of storing new knowledge is known as learning while inference refers to the act to extracting conclusions given agent’s limited knowledge base. They are tightly knit by the design of its knowledge base. The process of deciding long-term actions or plans given its current knowledge is called planning. Reinforcement Learning (RL) brings together these two tasks by posing a seemingly benign question “How to act optimally in an unknown environment?”. This requires the agent to learn about its environment as well as plan actions given its current knowledge about it. In RL, the environment can be represented by a mathematical model and we associate an intrinsic value to the actions that the agent may choose. In this thesis, we present a novel Bayesian algorithm for the problem of RL. Bayesian RL is a widely explored area of research but is constrained by scalability and performance issues. We provide first steps towards rigorous analysis of these types of algorithms. Bayesian algorithms are characterized by the belief that they maintain over their unknowns; which is updated based on the collected evidence. This is different from the traditional approach in RL in terms of problem formulation and formal guarantees. Our novel algorithm combines aspects of planning and learning due to its inherent Bayesian formulation. It does so in a more scalable fashion, with formal PAC guarantees. We also give insights on the application of Bayesian framework for the estimation of model and value, in a joint work on Bayesian backward induction for RL.
LibGuides: Using Primo, the Library catalog, to Find Books & Articles: The Basics

About the Library's tool for searching print and online collections for books, articles and more.
LibGuides: Using Primo, the Library catalog, to Find Books & Articles: How to Put Together a Search

About the Library's tool for searching print and online collections for books, articles and more. It is not magic. Mechanics of running searches.
Puzzles and Exercises

This chapter emphasizes the learning curve and blockchain’s implementation. Attempt the challenges presented here hands-on to develop your skill. Refer to the chapters relevant to the question to deep dive into domain areas that need further examination. As the vision of this book is to enable readers from technical as well as non-technical backgrounds to be a part of the blockchain ecosystem, attempting this chapter is one of the validators as well as a catalyst to innovate further.
W-Cell-Net: Multi-frame Interpolation of Cellular Microscopy Videos.

Deep Neural Networks are increasingly used in video frame interpolation tasks such as frame rate changes as well as generating fake face videos. Our project aims to apply recent advances in Deep video interpolation to increase the temporal resolution of fluorescent microscopy time-lapse movies. To our knowledge, there is no previous work that uses Convolutional Neural Networks (CNN) to generate frames between two consecutive microscopy images. We propose a fully convolutional autoencoder network that takes as input two images and generates upto seven intermediate images. Our architecture has two encoders each with a skip connection to a single decoder. We evaluate the performance of several variants of our model that differ in network architecture and loss function. Our best model out-performs state of the art video frame interpolation algorithms. We also show qualitative and quantitative comparisons with state-of-the-art video frame interpolation algorithms. We believe deep video interpolation represents a new approach to improve the time-resolution of fluorescent microscopy.
FPGA-Based Implementation of Basic ImageDenoising Techniques with Improved Genetic Algorithm

In this paper, a novel Denoising Techniques with improved Genetic Algorithm(GA) have been introduced to remove noise from digital images assumptions with frequency content of the image, implemented with FPGAs, Field Programmable Gate Arrays (FPGAs) is also known as Reconfigurable hardware in the form of has been proposed as a way of obtaining high performance for applications such us Image Processing (IP), even under real-time requirements. The programming capability of FPGAs gives them software while keep the act advantages of an application detailed solution. The results show the robustness in the improvement of PSNR, SSIM.
Understanding Experiential Qualities of Light-Touch-Matters: Towards a Tool Kit

The present paper is about the tools and strategies, designers adopt and develop to support their understanding of an underdeveloped smart material composite. Referred to as Light-Touch-Matters or in short, the LTM materials, the composition is proposed by materials scientists, integrating the two smart materials of flexible thin-film Organic Light-Emitting Diodes and piezo-electric polymers. In a project funded by European-Union, materials scientists and designers joined forces to further develop such smart material composites through early design input. In order to introduce and represent the LTM materials to designer’s prior their actual development, materials scientists mainly used abstract descriptions, ‘key’ physical properties and sensing/actuating function. Such representations, however, hardly capture the experiential qualities of LTM materials, which concern how they gratify our senses and what meanings, emotions and actions they elicit. This paper has conducted four design case studies to identify the design approaches and representational tools used and developed by designers for understanding, exploration and communication of the experiential qualities of these underdeveloped smart materials. Discussing the limitations of the identified tools in terms of capturing the dynamic and performative qualities, the paper draws further implications towards a future design Tool Kit.
AUTOMATED POLYP SIZE ESTIMATION WITH DEEP LEARNING REDUCES OVERESTIMATION BIAS

Aims Polyp size is directly correlated with risk of future CRC and growth invasiveness. Despite its big impact, endoscopists typically provide a visual size estimation, but several studies have reported low accuracies. We aim to enable more accurate in-vivo polyp size measurements and ultimately reduce clinical mis-sizing by endoscopists. Therefore, we developed an AI system that can objectively infer polyp size based on a reference tool in the endoscopic image.
Scalable importance tempering and Bayesian variable selection

We propose a Monte Carlo algorithm to sample from high dimensional probability distributions that combines Markov chain Monte Carlo and importance sampling. We provide a careful theoretical analysis, including guarantees on robustness to high dimensionality, explicit comparison with standard Markov chain Monte Carlo methods and illustrations of the potential improvements in efficiency. Simple and concrete intuition is provided for when the novel scheme is expected to outperform standard schemes. When applied to Bayesian variable‐selection problems, the novel algorithm is orders of magnitude more efficient than available alternative sampling schemes and enables fast and reliable fully Bayesian inferences with tens of thousand regressors.
Windtherm Fire: An MR System for Experiencing Breathing Fire of a Dragon

We present an interactive MR system in which hot wind is sent to a player’s face synchronously to the virtual environment. The system uses a VR accessory called Windtherm, which is attachable to a HMD, heats the air inside, and blows the wind with changeable forces and directions. We improve the device to work interactively to the virtual events. We also develop an MR content in which a player interacts with a small dragon and occasionally receives its breathing fire with simultaneous tactile stimulus of actual wind for enhancing the sense of presence in this fictitious world.
The Impact of Social Media on the Promotion of Commodities for Small Projects in the State of Kuwait

The current study aimed at identifying the impact of social media on promotion of commodities for small projects in the State of Kuwait. The study population consisted of all workers in small projects, and they numbered (720) workers. A simple random sample of (250) workers was chosen. The study concluded that there is a statistically significant effect of the elements of social media (conversations, groups, participation, partnership, relations) in promoting the commodities of small projects in the State of Kuwait; the study also reached a number of recommendations, the most important of which are: The need for those in charge to focus on social media, (Facebook, Instagram, Twitter and LinkedIn) as a means of communication with customers in order to promote of commodities for small projects in the State of Kuwait because of its characteristics and advantages, focusing on giving social media more care and attention to the mechanism of adopting credible and reliable information to reach those wishing to establish small projects in the State of Kuwait, as this information helps them in adopting their projects, the need for those in charge of social media to encourage the owners of implemented projects to share their own experiences and expertise to enhance  new projects owners. Keywords: Social Media, Promotion of Commodities for Small Projects, Kuwait. DOI: 10.7176/NMMC/89-03 Publication date: April 30 th 2020
Development of Integrated Dance Education Program for Applying Free Learning Semester

I have concluded that dance is the most suitable art for an Applying Free Learning Semester. The goal is to build teenagers’ career awareness and to develop an Integrated Dance Education Program, which I believe is essential. Upon searching the literature regarding the definition and management of the Applying Free Learning Semester, I realized that there are few dance programs when I looked through domestic and international pre-studies. Moreover, by theoretical consideration of integrated education, I realized that dance is the best curriculum to integrate with other subjects flexibly, especially when compared to other art genres. Thus, it is the most appropriate art curriculum to consider for the Applying Free Learning Semester.
Designing Anticipation Activity of Students When Studying Holomorphic Dynamics Relying on Information Technologies

In this paper, we consider the design of anticipatory activities aimed at development of students creativity at a higher education institution when studying holomorphic dynamics. Interpretation of anticipation as an ability to put forward hypotheses, that are subject to verification by means of analytical methods, has been specified. The connection between Mandelbrot set and the accompanying Julia sets has been noted. Using information and communication technologies, students put forward hypotheses related to Julia sets’ visualisation, and then use the analytical methods to identify the main frames of these sets. First, special cases are considered, then the obtained results are generalised. By analogy, other tasks are formed and their solutions are analysed. In our opinion, this approach makes it possible to organise students’ creative mathematical activity, develops their intuition, flexibility and critical thinking.
Simulation-Based Inference for Global Health Decisions

The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and containment strategies. Work in this setting involves solving challenging inference and control problems in individual-based models of ever increasing complexity. Here we discuss recent breakthroughs in machine learning, specifically in simulation-based inference, and explore its potential as a novel venue for model calibration to support the design and evaluation of public health interventions. To further stimulate research, we are developing software interfaces that turn two cornerstone COVID-19 and malaria epidemiology models COVID-sim, (this https URL) and OpenMalaria (this https URL) into probabilistic programs, enabling efficient interpretable Bayesian inference within those simulators.
Comparative Study of Korean-China Female moral books Focusing on 《Yeopbeom(女範)》and 《Yeopbeomchubrok(女範捷錄)》

The study refines the expressions of women's feelings through the traditional female education moral books “Yeopbeom” and “Yeopbeomchubrok” of Chosun and China Among the women’s edicts are “Yeopbeom,” written by Yeongbin of Joseon, and “Yeopbeomchubrok” written by Yu, a royal priest of the Qing dynasty. If the “Yeopbeomchubrok” classified the total number of subjects a woman should have into a broad system, “Yeopbeom” was a person-centered classification that highlighted the practical lesson. “Yeopbeom” is the story of more than half of Chinese virgin and virtuous woman compared to “Yeopbeomchubrok” in the Chinese Qing dynasty. Youngbin Lee could not have completely abandoned her maternal side, so she would have published a number of stories in her book in order to justify her actions, not her will. However, Mrs. Youngbin did not forget his role as king's wife. Mrs. Yu, the Incision woman of the Qing dynasty, also makes up the story of maternal instincts in the “Yeopbeomchubrok” with stories of the Queen’s internal dentistry, filial piety at the expense of oneself, which he hopes to keep in a painful and intense manner. However, Yoo also tried to bring women out of the world by forming a story about the country-conscious Chung. Both female moral books consisted of the story of life that conforms to the feminine image, or in the life of the times, that man wants in a patriarchal society, but it also shows the story as a woman in it.
Image resizing with minimum distortion

Displays became cheap and were combined with many devices, like camera, mobile, and so on…, so there has been an increased interest on resizing methods to make the image suitable and fill any screen size. Common and known methods like cropping or resampling can cause undesirable effects such as: losses in information or distortion in perception. Recently, content-aware image resizing methods have been proposed to get rid of these problems and produce exceptional results. Seam-carving produced by Avidan and Shamir has gained attention as an effective solution. This paper discussed about this method and used it to resize (minimize and maximize) four colored images vertically and horizontally respectively, and maintained the main features of the images by deleting or repeating only the uninfluenced features. The energy map was calculated that described the basic and influential details of the image using energy function. But instead of gradient function (as in Avidan and Shamir) entropy function was used to compute the energy of the images. A vertical or a horizontal seam of pixels with minimum energy values was either deleted or inserted to resize the image. Good results were obtained especially when the image contains spaces within its details. The work was programmed using Matlab2018a.
A Comparison of Multidimensional IRT Linking Methods

본 연구의 목적은 복수의 하위구인으로 이루어진 실제 검사 구조를 고려하여 모의실험을 통해 다차원 문항반응모형을 이용한 검사의 연계화 방법들의 정확성을 비교하는 것이다. 이를 위해 Oshima, Davey와 Lee(2000), Li와 Lissitz(2000), Min(2003)의 세 가지 분리추정과 동시추정방법을 이용하여 공통척도로의 변환을 수행하였다. 추정방법들의 비교를 위해 피험자 집단의 크기, 공통문항의 비율, 능력차원의 상관 조건 별로 결과를 도출하였다. 연구결과 전반적으로 동시추정방법이 분리추정방법들에 비해 양호한 연계화 결과를 보였다. 단, 능력 차원들의 상관이 낮으며 집단의 크기가 충분히 크고 공통문항의 비율이 높은 경우에는 분리추정을 이용한 연계화 결과의 정확성도 높게 나타났다. 이를 통해 다차원 검사들의 연계화의 일반적인 상황에서 동시추정방법의 사용을 제안하며, 분리추정방법을 이용하여 공통척도로 변환 시에는 충분한 피험자 수의 확보와 공통문항이 비율을 높일 필요가 있음을 제안한다.The purpose of this study is to compare the test linking methods using a multidimensional item response model through simulation technique by considering the actual test structure composed of several constructs. The transformation to the common scale is performed using three separate calibration methods: Oshima, Davey and Lee (2000), Li and Lissitz (2000), Min (2003) and concurrent calibration method. For comparison of calibration methods, results are derived from the number of examinee, the dimensional correlations and the ratio of common items. As a result of the study, the concurrent calibration method performs well in linking than three separate calibration methods. However, when the correlation of ability dimensions is low, the number of examinee is large enough, and the ratio of common items is high, the separate calibration methods also provides accurate linking results. In conclusions, concurrent calibration method has an advantage of multidimensional tests linking. And it is necessary to secure a sufficient number of examinee, increase the ratio of common items when transforming to common scale with separate calibration methods.
Check me out im a 15 year old rapper

Soundcloud is the worlds third largest streaming platform for music. Despite this, the website is riddled with spam comments that disturb user experience. This spam diers much in format and content from the email spam that we are used to seeing, and that most classic spam lters have been developed to detect. On soundcloud, 90% of spam comments are written by users wanting to self-promote their own music and contain plenty of slang and spelling errors. Our aim is to develop a machine learning model that can predict spam with a high accuracy for comments on this internet platform. We take several steps to process the data, such as removing stopwords and emojis, in order to facilitate analysis. We use python packages of the Natural Language Processing toolkit in order to process the data and train our algorithms. We test a Naive Bayes algorithm and two different Support Vector Machines (RBF and Linear kernel) to see which one performs best. Our results show that all three algorithms are still highly effective even when presented with the challenge of detecting spam in this different kind of data; The Support Vector Machine with RBF kernel performs best, predicting 97,3% of comments correctly in our test, but is slower to train than the Naive Bayes and with only a 2% difference in predictive precision. (Less)
Subject guides: Exams and Revision: Accessing e-books using DiscoverEd

How to get the most out of the Library and other University support for revising for and taking exams Learn how to use DiscoverEd to find e-books for your exams