Reviewerly/exHarmony huggingface dataset:
Кузница актерских кадров

The article is devoted to the 100th anniversary of the regional state budget professional educational institution P. I. Ivanov-Radkevich Krasnoyarsk College of Arts, which made a great contribution to the cultural life of Siberia. The history of its origin, formation and development is described. The research method is an analysis of the formation of the Krasnoyarsk State College of Arts in the historical context. Research boundaries - a chronological framework covering the period from the 1970s to the present. Among the famous graduates of the College are Timofey Spivak, Ivan Korytov, Roman Ridzel, Dmitry Zlobin, Vasily Selyukov and others, who are proud not only within Russia, but also abroad. The teaching staff of the College – Larisa Arefieva, Elena Andreyevna Gorelova. The author of the article expresses his sincere hope that the Ministry of culture will revive the forge of musical and theatrical personnel, and many more future theater stars will come out of the walls of the College of arts, which will sparkle in the sky of Russian theaters.
La promoción de la lectura en la Carrera de Comunicación Social en las universidades ecuatorianas

Se aborda la promocion de la lectura en la formacion del profesional de la carrera de Comunicacion Social y las dimensiones basicas que la distinguen. La logica del trabajo tuvo en cuenta la utilizacion de diversas tecnicas y metodos de investigacion del nivel teorico y empirico. Se requiere de un proceso de ensenanza-aprendizaje que se exprese en la promocion de la lectura como una herramienta de intervencion pedagogica, integradora y sistemica, que implica la planificacion de acciones formativas, con sus dimensiones basicas, en correspondencia con las exigencias de la formacion de profesionales.Palabras clave: Promocion, lectura, universidad, dimensiones basicas. ABSTRACTIt addresses the promotion of reading in the training of the career of Social Communication career and the basic dimensions that distinguish it. The logic of the work took into account the use of various techniques and research methods at the theoretical and empirical level. It requires a teaching-learning process that is expressed in the promotion of reading as a pedagogical, integrative and systemic intervention tool, which involves the planning of training actions, with its basic dimensions, in correspondence with the requirements of training of professionals.Keywords:Promotion, reading, university, basic dimensions.
Penerapan Metode Transformasi Brovey Pada Pembesaran Citra Ultrasonografi (USG)

In the process of taking an ultrasound image or the results of long-distance imaging with a telescope or the results of medical recordings including x-rays, ultrasound or scans, there are often disturbances in the form of light distortion, noise or other disturbances that cause objects in the image to be unclear or blurry. Medical ultrasonography (sonography ) is an imaging diagnostic technique using ultra sound that is used to image internal organs and muscles, their size, structure, and wound pathology, making this technique useful for examining organs. Obstetric sonography is commonly used during pregnancy. Image processing applications are increasingly widespread as in the medical world, image processing has a very large role in everyday life. In the field of ultrasound medicine or better known by the abbreviation USG is widely used in medical. Enlargement or zooming is a process carried out to enlarge an image. The enlargement process certainly has blur in the image so that the image will look like boxes. And there is a change in the size of the image This happens because in the enlargement process, the resolution that compiles the image becomes smaller to reduce it. Image enlargement is one of the fields in digital image processing that is getting enough attention because of the large need to obtain a better view or view of an image as for the method used is the brovey transformation method. Brovey transformation method is an easy method for combining data from different sensors. In this thesis will be discussed on how to create an image enlargement application using the brovey transformation method. This application was built with Matlab 2013 as an editor for editing programs
Dealing with Newly Emerging OOVs in Broadcast Programs by Daily Updates of the Lexicon and Language Model

This paper deals with out-of-vocabulary (OOV) word recognition in the task of 24/7 broadcast stream transcription. Here, the majority of OOVs newly emerging over time are constituted of names of politicians, athletes, major world events, disasters, etc. The absence of these content OOVs, e.g. COVID-19, is detrimental to human understanding of the recognized text and harmful to further NLP processing, such as machine translation, named entity recognition or any type of semantic or dialogue analysis. In production environments, content OOVs are of extreme importance and it is essential that their correct transcription is provided as soon as possible. For this purpose, an approach based on daily updates of the lexicon and language model is proposed. It consists of three consecutive steps: a) the identification of new content OOVs from already existing text sources, b) their controlled addition into the lexicon of the transcription system and c) proper tuning of the language model. Experimental evaluation is performed on an extensive data-set compiled from various Czech broadcast programs. This data was produced by a real transcription platform over the course of 300 days in 2019. Detailed statistics and analysis of new content OOVs emerging within this period are also provided.
V[R]ignettes

Originally titled A Million and Two, V[R]ignettes is a series comprising virtual reality crafted microstories. Each individual microstory, or vignette, is designed to encourage a kind of "narrative smearing"---where traditional story techniques are truncated and mutated into smears (kinetic actions and mechanics, collagelike layered building blocks, visual distortions, dual-tiered text annotations) that require a reader/interactor to make active choices in order to navigate each microstory space (storybox). The microstories presented are part of the ongoing V[R]ignettes Series. When exploring each microstory, a reader will experience poetically dense language (such as letters bracketed in words---requiring rereading---that are designed to expand and enhance meaning potentials) and various visual, textual and technological elements that require direct audience input (such as: Do you choose to view each microstory in a 3D or VR space---through a virtual reality headset or a mobile phone or computer monitor? Do you set each microstory to autopilot or navigate the experience through manual annotation click-throughs and spatial manipulations? Do you choose to use the model inspector and view the microstories without any post-processing effects, or in wireframe? Do you choose to enable audio? Do you read only the title fields or entire paragraphs?). Such smears are also designed to be combined by the reader to create a story-piecing system that's circular in nature, where a reader/interactor is encouraged to experience each microstory multiple times, in multiple ways. For instance, when experiencing "In the Skin of the Gloam," if a reader chooses to read only the title line of each annotation, they'll experience a minimal poetic (title) text version. If they instead read the rest of the annotation accompanying each title line, the narrative is accented differently. If they choose to manipulate (scale, rotate, zoom) the 3D models in the space (and/or if they engage autoplay or, in the case of "Wracking in the Upper Bubble," read the wall text only), a reader's experience will be markedly different from those choosing to experience each microstory in a VR space (where teleportation is an option and the spatial dimension is crucial). To load each microstory, readers press the white arrow in the middle of each V[R]ignettes storybox (and if viewing on a mobile device, they need to make sure to view each storybox in full screen mode). After clicking on the white arrow, to begin reading the text they click on the "Select an annotation" bar at the bottom of each storybox screen. From there, they get to choose how they experience all other narrative smearing possibilities. If they need help with navigation and controls, they can click the "?" located at the bottom right side of each storybox.
Case Study: Architecting a Solution to Detect Industrial Control System Attacks

This case study presents an anomaly detection solution to prove the power of machine learning algorithms to identify anomalies, such as cyber intrusions, within the domain of Industrial Control Systems (ICS). Industrial Control Systems have extended lifecycles and employ few, if any, security mechanisms. The research objective is to provide a novel, scalable analytic capability that passively collects physical sensor and network layer data and then visualizes the output of data models with detected anomalies. Additionally, the capability is deployable and customizable for the intricacies of ICS environments with the objective of early identification of attacks such as scanning, network mapping, targeting, and other processes. This research is a novel approach to early detection of ICS threat activity with visualizations to deliver prompt incident response.
Використання віртуальних серверів та платформ на основі хмарних сервісів у практико-технічній підготовці ІТ-фахівців

The article is devoted to substantiating the feasibility of using cloud technologies in theeducation of technical disciplines of future IT specialists. An overview and complete analysis ofvirtual servers and platforms based on cloud services in the context of their use in the training offuture IT professionals. It is shown that in light of the development of multidisciplinary areas ofresearch and relevant educational programs, the Application as a Service cloud organizationmodel, which provides the development and use of composite programs - a set of interconnectedcloud services focused on the overall task, deserves special attention. The conducted analysis ofeducational and professional training programs for information technology specialists inUkraine has made it possible to identify models of cloud services that are appropriate to use inthe process of teaching regulatory disciplines of technical direction. Based on the experienceand comparison of distance learning technologies and cloud technologies, as well as userobedience, the advantages of using cloud technologies for different categories of participants ofthe learning process and the model of provision of cloud services are identified, which areappropriate to use in the process of teaching regulatory technical disciplines of futureprofessional and practical training information technology professionals. According to theresults of studying the experience of using cloud technologies in the training of IT specialists, itis advisable to use the following models of cloud services in the training of information science:«software as a service», «platform as a service» and «infrastructure as a service» based onvirtual information technology machines and pedagogical technology of distance learning. Oneof the clear advantages of using cloud technology in the training of future IT professionals atuniversities is the ability to use modern virtualization tools as an effective tool for gainingpractical skills.
INSIGHT And ANALYTICS FROM GIT REPOSITORIES

Git Repositories are critical in the collaborative world of Software Development. We have been actively developing applications that allows developers to visualize the data that Git stores. The application extracts raw data and presents it in readable charts, highlighting file changes and author contributions. We seek to utilize our application to help developers gain insight into their applications and help build a firm foundation in Git for new developers and students. Through our analysis we hope to identify commit trends within projects so developers can track the state of their projects and identify progress.
Facial Landmarks Detection under Occlusions via Extended Restricted Boltzmann Machine

Facial landmarks encode critical information about face, which plays an important role in human communications. Accurate detecting and tracking facial landmarks have great potential value in intelligent user interfaces such as human-computer interactions. However, for face images with sever occlusions which may happen in real life such as hand occlusion, gesture occlusion and etc, detecting the facial landmarks is still a challenging problem. In this paper, we present a robust facial landmark detection method for image with occlusions based on Restricted Boltzmann Machine (RBM). We first present a face shape prior model which is constructed based on RBM to model the spatial shape patterns of the face. The detection process is accomplished by combining the prior shape model with the image measurements of facial landmarks. The low accuracy image measurements can be refined by the shape information embedded in the prior model. For the landmarks with severe occlusions, we firstly evaluate and determine the facial landmark occlusions, and replace their image measurements. The new image measurements are then fed into the prior model as evidence to predict the true locations. Evaluation on 3 databases demonstrates that the proposed method can detect facial landmarks accurately under severe occlusion, and achieved significant improvement over the current state of the art methods.
Geometric Transformation in Content Based Image Retrieval – A Survey

In today’s digital era, most of the information is in the form of images. So to find relevantinformation from large available image dataset is a challenging task, which is focused by many researcherssince last two decades in the form of Content Based Image Retrieval (CBIR). Many algorithms adopted forCBIR to improve the performance but still there is scope to further improve retrieval performance byconsidering deep learning with geometric transformation in CBIR. The purpose of this paper is tocategorize and evaluate different algorithms invented in this front during period 2000 to 2017. The paperconcludes with future directions for research in this research area for new researcher.
TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification.

Diagnosing diseases such as leukemia or anemia requires reliable counts of blood cells. Hematologists usually label and count microscopy images of blood cells manually. In many cases, however, cells in different maturity states are difficult to distinguish, and in combination with image noise and subjectivity, humans are prone to make labeling mistakes. This results in labels that are often not reproducible, which can directly affect the diagnoses. We introduce TIMELY, a probabilistic model that combines pseudotime inference methods with inhomogeneous hidden Markov trees, which addresses this challenge of label inconsistency. We show first on simulation data that TIMELY is able to identify and correct wrong labels with higher precision and recall than baseline methods for labeling correction. We then apply our method to two real-world datasets of blood cell data and show that TIMELY successfully finds inconsistent labels, thereby improving the quality of human-generated labels.
DAOLOT: A Semantic Browser.

The goal of the Semantic Web is to allow the software agents around us and AIs to extract information from the Internet as easily as humans do. This semantic web is a network of connected graphs, where relations between concepts and entities make up a layout that is very easy for machines to navigate.At the moment, there are only a few tools that enable humans to navigate this new layer of the Internet, and those that exist are for the most part very specialized tools that require from the user a lot of pre-existing knowledge about the technologies behind this structure. In this article we report on the development of DAOLOT, a search engine that allows users with no previous knowledge of the semantic web to take full advantage of its information network. This paper presents its design, the algorithm behind it and the results of the validation testing conducted with users. The results of our validation testing show that DAOLOT is useful and intuitive to users, even those without any previous knowledge of the field, and provides curated information from multiple sources instantly about any topic.
PENGARUH PENGGUNAAN BUKU CERITA â€œAKU DAN LEMBONGANâ€ DALAM PEMBELAJARAN SUBTEMA LINGKUNGAN TEMPAT TINGGALKU TERHADAP MINAT BACA DAN HASIL BELAJAR SISWA KELAS IV SD

This study aimed to investigate the effect of the use of storybooks on reading interest and learning outcomes in fourth grade students of Elementary School XIII Buleleng District. Of the 157 students of the population, 64 students were designated as samples drawn by random sampling technique. Data collected by the reading interest questionnaire, while learning outcomes data collected by objective tests. Data analysis technique used in this research is Manova. The result of the research shows that: 1) There are differences of reading interest between students who are taught by accompanying by a story book and taught only using the 2013 Curriculum Book on learning Subtheme of My Neighborhood in fourth grade students of Elementary School XIII Buleleng District, 2) there is a difference in learning outcomes between students who were taught by accompanied by a story book and taught only using the 2013 Curriculum Book on learning Subtheme of My Neighborhood in fourth grade students of Elementary School XIII Buleleng District, 3) there are differences of simultaneous reading interest and learning outcomes between students who were taught accompanied by a story book and taught only using the 2013 Curriculum Book on learning Subtheme of My Neighborhood in fourth grade students of Elementary School XIII Buleleng District. Keywords: Storybook, Learning Outcomes, Reading Interest
Il contributo della Linguistica Educativa italiana alla ricerca sui bisogni speciali

The present paper provides a quantitative and qualitative analysis of the Italian studies on Special Educational Needs conducted in the field of Educational Linguistics (EL) which are currently included in the Library of Language Education in Italy. Overall, the results show that EL research on special needs is neither a recent phenomenon nor a marginal area of studies. As a consequence, considering that general research on special needs has been promoting an interdisciplinary approach, EL should play a major role when the issues of language learning in educational environments are taken into consideration.
Development of an IoT-based and cloud-based disease prediction and diagnosis system for healthcare using machine learning algorithms

Internet of Things (IoT) refers to the practice of designing and modelingobjects connected to the Internet through computer networks. In the past fewyears, IoT-based health care programs have provided multidimensionalfeatures and services in real time. These programs provide hospitalization formillions of people to receive regular health updates for a healthier life.Induction of IoT devices in the healthcare environment have revitalizedmultiple features of these applications. In this paper, a disease diagnosissystem is designed based on the Internet of Things. In this system, first, thepatient's courtesy signals are recorded by wearable sensors. These signals arethen transmitted to a server in the network environment. This article alsopresents a new Hybrid Decision Making approach for diagnosis. In thismethod, a feature set of patient signals is initially created. Then thesefeatures go unnoticed on the basis of a learning model. A diagnosis is thenperformed using a neural fuzzy model. In order to evaluate this system, aspecific diagnosis of a specific disease, such as a diagnosis of a patient'snormal and unnatural pulse, or the diagnosis of diabetic problems, will besimulated.
Prediction Skills, Reading Comprehension and Learning Achievement in Vihiga County Kenya. Addressing Constraints and Prospects

Prediction skill may be used in reading comprehension passages as encapsulated in interactive approach instruction. Prediction skills assist learners to decode the meaning of comprehension passages by constructing guesses about the contents of texts to be read in comprehension passages. Learners in Vihiga County register low achievement in English language examinations than peers in neighbouring counties over the years. The performance is much weaker in comprehension passages than grammar sections. Although there are low grades, the nexus between use of prediction skills and learners&amp;rsquo; achievement in reading comprehension passages has not been assessed. This study applied the Solomon Four Non-Equivalent Group Design to obtain primary data from 279 primary school learners and 8 teachers in 2017. Multiple linear regression used generated two models, one for the experimental group (Model 1) and one for the control group (Model 2). Findings indicate that the influence of prediction skills on learner achievement in reading comprehension passages was significant in experimental, but insignificant in the control groups. However, influence was stronger in the experimental than in the control groups, suggesting that training English language teachers on correct application of prediction skills improves learner achievement in reading comprehension passages. The study recommends need to: sensitise teachers on textbook usage, while supplementing with improvised materials; guide learners through titles; as well as update teacher training curriculum by integrating inter alia, emerging instructional methods embracing Information and Communication Technology and entrenching innovation in resource mobilization and use.
Type Theory Unchained: Extending Agda with User-Defined Rewrite Rules.

Dependently typed languages such as Coq and Agda can statically guarantee the correctness of our proofs and programs. To provide this guarantee, they restrict users to certain schemes - such as strictly positive datatypes, complete case analysis, and well-founded induction - that are known to be safe. However, these restrictions can be too strict, making programs and proofs harder to write than necessary. On a higher level, they also prevent us from imagining the different ways the language could be extended.In this paper I show how to extend a dependently typed language with user-defined higher-order non-linear rewrite rules. Rewrite rules are a form of equality reflection that is applied automatically by the typechecker. I have implemented rewrite rules as an extension to Agda, and I give six examples how to use them both to make proofs easier and to experiment with extensions of type theory. I also show how to make rewrite rules interact well with other features of Agda such as η-equality, implicit arguments, data and record types, irrelevance, and universe level polymorphism. Thus rewrite rules break the chains on computation and put its power back into the hands of its rightful owner: yours.