Reviewerly/exHarmony huggingface dataset:
COMPOSITES 1: An Exploration into Real-Time Animated Notation in the Web Browser

COMPOSITES 1 for Modular Synthesizer Soloist and Four Accompanists is a real-time, graphically notated work for modular synthesizer soloist and four accompaniment parts that utilizes the power of Node.js, WebSockets, Web Audio, and CSS to realize an OS-agnostic and web-deliverable electroacoustic composition that can be accessed on any device with a web browser. This paper details the technology stack used to write and perform the work, including examples of how it is used compositionally and in performance. Recent developments in web browser technology, including the Web Audio API and Document Object Model (DOM) manipulation techniques in vanilla JavaScript, have improved the possibilities for the synchronization of audio and visuals using only the browser itself. This paper also seeks to introduce the reader to the aforementioned technologies, and what benefits might exist in the realization of creative works using this stack, specifically regarding the construction of real-time compositions with interactive graphic notations.
Perawatan dan Perbaikan Peralatan Listrik Rumah Tangga bagi Masyarakat Rukun Tetangga 04 - Rukun Warga 09 Kelurahan Bunulrejo – Kota Malang

Maintenance and repair of household electrical appliances for the Rukun community Residents 04 Bunulrejo Village / Kec. Blimbing - Malang City, gives additional the skills and motivation for the Rukun Community of 04 Bunulrejo Village for practice maintenance and repair of household electrical appliances for the Rukun community Residents 04 Bunulrejo Village. Besides that it can also improve skills addition to the community of Rukun Tetangga 04 Kelurahan Bunulrejo in the field of care and repair of household electrical appliances for the 04 Rukun Tetangga community in the Village Bunulrejo that applies in this era&#x0D;
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy

Anonymized smartphone-based mobility data has been widely adopted in devising and evaluating COVID-19 response strategies such as the targeting of public health resources. Yet little attention has been paid to measurement validity and demographic bias, due in part to the lack of documentation about which users are represented as well as the challenge of obtaining ground truth data on unique visits and demographics. We illustrate how linking large-scale administrative data can enable auditing mobility data for bias in the absence of demographic information and ground truth labels. More precisely, we show that linking voter roll data---containing individual-level voter turnout for specific voting locations along with race and age---can facilitate the construction of rigorous bias and reliability tests. Using data from North Carolina's 2018 general election, these tests illuminate a sampling bias that is particularly noteworthy in the pandemic context: older and non-white voters are less likely to be captured by mobility data. We show that allocating public health resources based on such mobility data could disproportionately harm high-risk elderly and minority groups.
Cryptocurrency Crimes – Need for a Comprehensive Global Crypto Regulation

Cryptocurrencies offer new and unprecedented challenges to sovereign states’ ability to regulate and enforce laws governing its monetary policy, security, and trade. However, for the technology involved in Cryptocurrency's border-less transaction, there appears a need for the international community’s endeavor to develop policies to increase sovereign states’ control on the use of cryptocurrency.In the context as set above, the article gives a glance on the global law enforcement action on the Cryptocurrency crimes. The rationale for Cryptocurrency regulation from perspective of monetary policy of State, crimes such as Money Laundering, terrorist financing and tax evasion and Consumer Protection laws is also taken up for study in the present work. The work suggests that there is need for private-public co-operation for bringing an effective regulation on Cryptocurrency transaction. In conclusion, it is opined that there is need for a comprehensive global Crypto regulations for controlling the Cryptocurrency crimes.
Low-noise and high-power laser systems for quantum computing

Quantum computing architectures where atom-laser interactions form the basis of qubit manipulation, such as trapped ion and Rydberg systems, are leading the progress towards universal quantum computation. M Squared is developing many of the advanced laser systems that are underpinning this progress, including systems that are designed to implement quantum logic gates with optical and hyperfine qubits with high fidelity. High power systems that are enabling the scaling of qubit numbers are also being developed. These systems are described, along with an account of how the requirements of lasers for quantum computing experiments are expected to evolve in the future.
Using deep learning for pixel-defect corrections in flat-panel radiography imaging

Purpose: Flat-panel radiography detectors employ thin-film transistor (TFT) panels to acquire high-quality x-ray images. Pixel defects occur due to circuit shorts or opens in the TFT panel. The defects may degrade the image quality, as well as lower the production yield, and eventually raise the production cost. Hence, it is important to develop an appropriate defect correction algorithm for acquired images. Traditional correction algorithms are based on a complicated adaptive filtering technique, which exploits neighbor pixels, to faithfully preserve the edge components. Because of the complexity of the traditional sophisticated approaches, optimizing their correction performances is difficult. Approach: We considered various pixel-defect correction algorithms based on different deep learning models, such as the artificial neural network (ANN), convolutional neural network (CNN), concatenate CNN, and generative adversarial networks (GAN). We considered two cases of maximal defect sizes, 3×3 and 5×5 pixels , and conducted extensive learning experiments to find the best structures of the learning models using the mean square error (MSE) as the loss function. Results: To conduct experiments, practical chest x-ray images were acquired from a general radiography detector. The MSE values of the correction results from ANN, CNN, concatenate CNN, and GAN were 69.40, 75.13, 68.21, and 73.77, respectively, and were much smaller than that of the conventional template match correction method. Conclusions: A concatenate CNN showed the best defect-correction performance. However, ANN could achieve a similar correction performance with much smaller encoding complexity. Therefore, the single-layer ANN can efficiently conduct defect corrections in terms of both correction and complexity.
Big Brother Goes to School

Few sectors are more affected by COVID-19 than higher education. There is growing recognition that reopening the densely populated communities of higher education will require surveillance technologies, but many of these technologies pose threats to the privacy of the very students, faculty, and staff they are meant to protect. The authors have a history of working with our institution’s governing bodies to provide ethical guidance on the use of technologies, especially including those with significant implications for privacy. Here, we draw on that experience to provide guidelines for using surveillance technologies to reopen college campuses safely and responsibly, even under the specter of covid. We aim to generalize our recommendations, so they are sensitive to the practical realities and constraints that universities face.
Analysis, design and development of a framework focused on augmented reality applications: Medical rounds case

Augmented reality is a technology that opens doors to experience interactions with virtual and real-world elements.It provides an opportunity to acquire knowledge and practical skills through software.However, it is not an easy task to determine the qualities and features that an augmented reality framework must possess to lay the foundations to build a structure focused on augmented reality.Therefore, in this work, we propose a framework focused on augmented reality applications without a specific domain area.We conduct a review of different frameworks for augmented reality.In order to define the characteristics, components, and the overall structure of our framework, a review of the most relevant literature in the field was carried out.As a result, we designed a framework focused on augmented reality without a specific domain area.Finally, we conclude that the structures, components, and features for an augmented reality framework vary greatly depending on the requirements or characteristics used for each approach.
External Reflection Recognition for Glass Walls Surface

Most buildings in modern cities contain many glass facades to show the modern flavor of architectural design and street view, gradually increase the intensity of the lighting, which is also the first choice for most green and energy-saving buildings. However, the strong reflectivity of the glass facade allows street view or sky to be reflected on the surface of the building, while the transparency allows the visualization of internal objects and interferes with the monitoring of the glass building itself. Such features increase the difficulty of urban building monitoring. In this paper, a multi-layer-separation algorithm based on semantic segmentation method is proposed to realize non-contact monitoring of glass buildings, which separate the reflection and the real object from the monitoring images.
The weight distribution of some irreducible cyclic codes

In this paper, the weight distribution of the irreducible cyclic codes over [Formula: see text] with length [Formula: see text] and dimension [Formula: see text] is settled for a few special cases. These irreducible cyclic codes have two weights or three weights or four weights.
Prototype of Remote Sensing Data and Information System Based on Open Source Technology to Support Disaster Management

Fast, precise and accurate remote sensing information is expected to increase support for disaster management in building an accountable disaster management system, as well as being a reference in disaster emergency response activities, according with Law No.24/ 2007 about disaster management. One of the functions of the Remote Sensing Utilization Center (Pusfatja) is to disseminate remote sensing information to users according to the Law Number 21 of 2013 Article 22 paragraph 1. The purpose of this project is to analyze the web-based information and disaster data systems. The method is used in this project is to make this system using open technology. The steps are taken in this project are identification of technological components and general architecture evaluations to facilitate the development, design and implementation of the system by updating, repeating testing and integrating open source software. The results showed that the system using prototype could implement and teste successfully. The prototype fully operate can be developed so that it can use for decision makers as a response to disaster activities in Indonesia and also as a reference in innovating technology and Geospatial information.
Mobile Robot Path Planning using Q-Learning with Guided Distance and Moving Target Concept

Classical Q-learning algorithm is a reinforcement of learning algorithm that has been applied in path planning of mobile robots. However, classical Q-learning suffers from slow convergence rate and high computational time. This is due to the random decision making for direction during the early stage of path planning. Such weakness curtails the ability of mobile robot to make instantaneous decision in real world application. In this study, the distance aspect and moving target concept were added to Q-learning in order to enhance the direction decision making ability and bypassing dead end. With the addition of these features, Q-learning is able to converge faster and generate shorter path. Consequently, the proposed improved Q-learning is able to achieve average improvement of 29.34-94.85%, 18.29-29.69% and 75.76-99.50% in time used, shortest distance and total distance used, respectively.
Patterned De-Duplication On Dependable Data Subcontracting With Three Error Detecting Techniques On Cloud Computing

Recently, cloud computing is usually a la mode. Cloud services that provide knowledge outsourcing on a cloud, numbers of users access these services to store an oversized quantity of data on the cloud. Several existing systems have limitations, i.e., loss of availableness, loss, and corruption of data loss of security, and merchandiser lock-in. Existing DEPSKY System beats the Limitations; in any case, it comes up short on a mistake identification instrument and accompanies high computing prices. To beat this downside, I propose a singular economical De-duplication on Dependable Encrypted knowledge Outsourcing on Cloud With quick Recovery. My main goal is to urge obviate perennial files on the cloud; therefore, whenever a user uploads any file 1st checking de-duplication, subsequently, the three error detection ways verify files shadows area unit hacked or not efficiently; finally quick recovery technique recovers files quicker than existing ways. My novel satisfies all elementary security needs further as I perform above existing schemes.
Optimizing optical precision of an image using curved focal plane technology

The quality of an image captured by the human eye is typically better than that obtained relative to artificial images created by cameras or telescopes. This is because humans have curved retinas. In contrast, conventional imaging cameras have flat sensors that are not well matched to the curved focal surfaces of a camera lens or telescope objective. Thus, the image cannot be at the same focus across the entire sensor field of view. It is hypothesized that as the surface of the sensor approaches the curvature of the camera lens or telescope, the image quality increases. To test this, a commercially available ray tracing software was used. The curvatures were varied from flat (0 mm) to 12 mm. As the curvature reached 9 mm, the Petzval curvature, the quality of the captured images from the camera significantly improved. However, as the curvature increased beyond 9 mm, the quality of the artificial image decreased. In addition, a simulation of a classical Cassegrain telescope was also made. For the telescope, the curvatures were varied from 0 mm to 500 mm. As the curvature approached the telescope’s focal surface curvature of 350 mm, the distortion decreased. In addition to the optical simulations, two images were generated: one with a camera and the other by a reconstruction process. The latter was reconstructed by using the central part of images taken along that curve to create an image. A comparison of these images demonstrates the superior image produced with the latter method. Devices such as cameras and telescopes with curved focal plane array detectors produce images with higher quality than those produced using devices equipped with flat focal plane array detectors.
MICROCONTENT PATTERNS AND EFFICIENCY IN YOUTUBE VLOGS: A CASE STUDY OF THE JEFFREE STAR YOUTUBE CHANNEL

Within the context of the digital, Computer-Mediated Discourse (CMD) of New media microcontent is of great importance as it provides the first contact and impression the user has with the content which is to follow. It needs to attract the audience to content which is not directly available and needs further steps to be taken by the user in order to access the actual information/product. For this purpose, microcontent needs to provide information about the content it pertains to (be it only textual or a combination of textual and audio-visual content). However, it has the additional function of providing the motivation which is necessary for the users/viewers to invest their time and attention in a particular video.Being a specific type of New Media and a digitally-native discourse, the YouTube platform and its content are highly representative of the modern tendencies, such as the extremely short attention span of users, the specific ways people read online as opposed to reading paper-based documents, as well as the satisficing strategies users apply when they interact with online sources of information.These specificities of the context in which microcontent needs to function within the YouTube platform underscore the importance of upholding the regulative principle of efficiency in formulating the textual aspect of the microcontent itself. As the author of the present article has stated in previous research, the enhanced efficiency of headlines in CMD can be discussed in relation to the consistent an repetitive application of sets of design patterns, which serve as templates providing empty slots to be filled with new elements (2013, 2015, 2017a, 2017b, 2018a, 2018b). In addition, the quality of microcontent can be further enhanced in terms of processing ease through the use of numerals, as they have the ability to serve as an “anchor” - “stop the wandering eye and attract fixations, even when they are embedded within a mass of words that users otherwise ignore” (Nielsen, 2007).The theoretical propositions of the article are discussed within the context of a case study of one of the most popular English-language YouTube channels, namely the Jeffree Star Channel. This particular channel has been chosen due to the undeniable success of the microcontent it employs as indicated by the metrics on the Social Blade global analytics platform (Social Blade, 2020) - 2 174 101 159 video views and 17.5 million subscribers as of February 28th, 2020 (“Social Blade Jeffreestar User Summary”, 2020) .The article approaches the subject and the object of research by employing the following methods: web-based corpus-analytical approach; computer-mediated discourse analysis and qualitative analysis of relevant quantitative results. It does not claim to be either statistically representative or conclusive but instead aims to illustrate a specific case of successful employment of pattterns for creating microcontent in terms of efficiency within the framework of You Tube.
Fluxo de trabalho para uma animação com render em tempo real

This paper presents the workflow for developing an animated short film, Fio, using real-time rendering. Real-time rendering is a recently commercially available alternative and has drastically reduced rendering time.Rendering means graphically processing an image, or layers of images, so that it can be displayed after processing, immediately. It is a critical step in computer graphics and determines the quality of the final image and the time required for it to be available for display. Previously, rendering required many minutes for each image frame, with multiple and costly processors. Currently, one render per frame is achieved in less than a second, with an equivalent look and a smaller amount of processing.To render in real time, the graphics engine Unreal Engine, a pioneer in this type of solution, was used. For this type of use, to render scenes, the software is free. Software of relevance in the creative industry were chosen as well, such as Autodesk Maya for animations and modeling, zBrush for sculptures, Substance Painter and Photoshop for composing textures, Audition for soundtracks, Premiere for editing. The engine itself has tools for lighting and composition. Other experimental alternatives were tested in the workflow, such as the use of hand-drawn textures with pastel chalks.This paper will introduce each step of the workflow for producing an animated short film, with the preparation of the scene adjustments to be imported by the Unreal engine at the end. The first minute of this animation is accessible in https://vimeo.com/503536788.
Histology, White Blood Cell

White blood cells, or leukocytes (Greek; leucko=white and cyte = cell), are part of the immune system participating in both the innate and humoral immune responses. They circulate in the blood and mount inflammatory and cellular responses to injury or pathogens.
Evaluation of the Application of Training in Higher Education Institutions as a Technology of Active Learning

The article considers the form of pedagogical activity - learning. The analysis of principles of training in the course of preparation of future experts of higher educational institutions is carried out. Issues related to types of trainings are considered. The advantages of conducting a lesson in the form of training are determined. The efficiency of application of educational social and pedagogical technology is substantiated. The most successful types of trainings in the training of specialists are evaluated. The article defines the concept of training. The article considers in detail the features and technologies of active learning, defines the nature and principles of methods of this learning.
Acoustics and the Modern Theatre

Acoustic design of performing art centres and auditoria has radically changed since the end of World War II. Once a black art, or with limited scientific techniques, room acoustics as a science was initiated by Wallace Clement Sabine in the early 20th century. The search for such new parameters started around 1950 and also took into consideration how the human ear processed audio information. The principle of an acoustic scale model is to reproduce an auditorium geometry and introduce materials mimicking those of an audience or a reflector with absorption matching those which may exist in the hall, further refining the reverberation time predictions. Room acoustic computer modelling software is able to predict different acoustic parameters such as Reverberation Time and Early Decay Time (EDT), timbre with the Bass Ratio (BR), objective measures for vocal and musical clarity, Strength (G), Early Lateral Energy Fraction (LF80) or the Speech Transmission Index (STI).
Application Of Expert System To Diagnose Pests And Diseases In Coffee Plant Using Web-Based Naïve Bayes: Application Of Expert System To Diagnose Pests And Diseases In Coffee Plant Using Web-Based Naïve Bayes

Every year the demand for coffee in Indonesia is increasing, this is because coffee is a plantation that has long been cultivated and is one of the livelihoods of the people in Indonesia. Moreover, the high level of exports makes coffee plants very influential for the country's economy and foreign exchange. Besides the many needs, the spread of pests and diseases in coffee plants is one of the problems that must be addressed immediately. Based on the existing problems, the author finally designed an expert system created to diagnose coffee plant diseases using The Naive Bayes method, which is one of the simple classification methods which in return can give a probability value for each disease that is raised. This system can help coffee planters to identify diseases in coffee plants. The test results in this study were able to produce an accuracy level of 92% so that this system can be used to diagnose pests and diseases in coffee plants.