Reviewerly/exHarmony huggingface dataset:
Development of an Intelligent Subsystem for Operating System Incidents Forecasting

The object of research is a subsystem for prediction server platform’s incidents, which operates on the basis of the Windows OS family. One of the most problematic places when planning measures to prevent the harmful effects of network attacks such as dDOS, hardware failures etc for the server system is to obtain an effective model for predicting incidents of the operating system.In the course of the research, methods of formation and research of the time series, exponential smoothing, elements of the theory of machine learning based on the method of group accounting (GMDH) are used. To obtain accurate and reliable forecasts of the operation of the intellectual subsystem for forecasting incidents, elements of the theory of heuristic self-organization and a specific implementation of this theory, the GMDH, are used. An algorithm is obtained and a software implementation of an intelligent system for predicting incidents of operating system operation and the main characteristics of its operation is developed. This became possible as a result of the analysis of the constructed model of the intruder, the system log of security incidents and the use of the GMDH. A mechanism is proposed for generating a sample of OS incident events based on the Windows system event log. The testing of the proposed forecasting system based on test samples allows to state that the forecasting results obtained with various settings of the machine learning system and parameters (degree of the reference polynomial, number of variables in the characteristic polynomial model, number of selection series) are satisfactory. As a result of applying the created algorithm for forecasting incidents of OS operation, it is shown that the use of a large number of polynomial models in GMDH allows one to obtain a forecasting system that is qualitatively superior to systems based on classical regression models and methods. Due to this, a much more accurate forecast can be obtained than the classical regression methods or the method of exponential smoothing, compared with similar methods. The percentage of false calculations using GMDH is less than 4 %.
A Unified System for Monitoring and Forecasting Emergencies in the Republic of Uzbekistan

nThe general goal of monitoring hazardous phenomena and processes in nature and the technosphere is to improve the accuracy and reliability of forecasting emergencies by combining the intellectual, information and technological capabilities of various departments and organizations involved in monitoring certain types of hazards. Monitoring data serve as the basis for forecasting. In the general case, forecasting is a creative research process, as a result of which hypothetical data about the future state of an object, phenomenon, process are obtained.
Review of neural modelling on cardiovascular rehabilitation active processes by using cycloergometers

Abstract publicado en EUROSIM 2019 Abstract Volume. ARGESIM Report 58, ISBN: 978-3-901608-92-6 (ebook), DOI: 10.11128/arep.58
Representation learning on knowledge graphs: embedding models and applications

In this work the research activities and the results obtained in thedevelopment of machine learning solutions to support inclusive digital storytelling activities based on Knowledge Graph within the European project MEMEX, founded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 870743, will be presented. In particular we are going to investigate the impact of the best performing embedding state-of-the-art models in the link prediction task of MEMEX Knowledge Graphs on the ability to extract node partitions in an unsupervised context. This is motivated since an important principle for representational learning is that the representations should benefit learning algorithms to exploit commonalities between different learning tasks to share statistical strength and transfer knowledge across tasks. In our experiments we observed the limits of Knowledge Graph embedding models in learning representations that share this properties across different tasks (Link Prediction and Clustering) and promising results consideraing information beyond the participation of entities and relationships in plausibility of facts.
Development of Learning Modules Women’s Cloth Making Based E-Book

The research is development of an E-book based learning module for the Women's Clothing course. The purpose of this research is to develop learning modules of Women's Clothing course based e-book with Flipbook Maker aplication. The result is electronic module of Women's Clothing course. Based on the results of expert judgment, the module of Women's Clothing course based e-book is one of the learning media the valid and practical to used in the learning process.
Prediction Of Medicine Consumption Using Machine Learning

The provision of pharmaceutical drugs in quantities accurate to consumption is an crucial point in the pharmaceutical industry and storage of medicines, as the production of large quantities of unnecessary drugs cause to a longer storage of drugs which is worthless. In the meantime most of the medicines have a short storage life.. A recurrent neural network with Long-Short Term Memory LSTM has been used by deep learning. The proposed methodology is founded on the seasonal number of prescription required quantities with the number of quarters as indicators. The purpose of this research is to forecast the drugs amount needed for one year. The proposed method is evaluated using two types of evaluation. The first one is based on MSE and the visualization of the actual data and forecasted data. The proposed method has reached a low value of MSE and the visualization graph is semi-identical, whereas the second evaluation method compares the result of the proposed method with traditional forecasting method. Multiple linear regression is a traditional prediction method used with the data set, whose results are relatively good and promising compared to the results of the traditional method.
LibGuides: Resources for Communication and Rhetorical Studies: Getting Started

This guide is intended to connect students with resources for Communication and rhetorical studies.
Applying Machine Learning to the Task of Generating Search Queries

In this paper we research two modifications of recurrent neural networks – Long Short-Term Memory networks and networks with Gated Recurrent Unit with the addition of an attention mechanism to both networks, as well as the Transformer model in the task of generating queries to search engines. GPT-2 by OpenAI was used as the Transformer, which was trained on user queries. Latent-semantic analysis was carried out to identify semantic similarities between the corpus of user queries and queries generated by neural networks. The corpus was convert-ed into a bag of words format, the TFIDF model was applied to it, and a singular value decomposition was performed. Semantic similarity was calculated based on the cosine measure. Also, for a more complete evaluation of the applicability of the models to the task, an expert analysis was carried out to assess the coherence of words in artificially created queries.
공공서비스가 삶의 질에 미치는 효과와 정책속성 - 농촌노인들의 삶의 질 평가를 중심으로 -

This study is an experimental study that examines the policy attributes that local governments should choose to manage the quality of life of rural residents. The analysis data used raw materials for the survey of the welfare status of farmers and fishermen surveyed by the Rural Development Administration. The analysis method used Quantile Regression. The policy attributes of public services were interpreted on the basis of Peterson (1981)’s theory of policy types and the discussion of Holland (2015). According to the analysis results, the higher the quality of life, the greater the importance of the relationship between the safety sector and the neighbors. The effective policy attributes for improving quality of life in rural areas are the policies of local governments where policy benefits can directly go to individuals, or lead to social improvement. It shows that the higher the level of safety and the quality of life of our neighbors, the greater its importance.
Global Challenges of the XXI Century: Categorization and Representation in Texts

The paper discusses the representation of global risks, essential for the year 2019, in texts and infographics. “The Global Risks Report 2019”, presented at World Economic Forum 2019, published texts and infographics on the issue. The goal of the research was to study how infographics for global risks interconnection (Figure 3, p.7) can be paralleled with the cognitive categorization of global risks concepts. The methods used are conceptual analysis and cognitive modelling. The methodology was posed as interdisciplinary research from the stance of cognitive sciences: cognitive linguistics, sociology, computer science. The result of the study demonstrated that the visualization, created by the computer program for infographics design, represents significant cognitive links, parallel to the concept links in a category of global risks, based on text representations. The text-based category was modelled as the centre-periphery cognitive model, with many chains, identical to computer-made links in infographics design. The two models, compared and described in the paper, led the researchers to the conclusion, that both computer cognitive modelling, represented in inforgraphics and cognitive categorization modelling, based on texts, can be considered as compelling visualizations of a complicated cognitive category.
LibGuides: Mathematics, Science and Technology Education: Library E-Resources

This guide will help students to easily access resources that are available in their libraries
LibGuides: LSC 595 Spring 2021 Merchant Professional Field Experience: Evidence of Learning Outcomes

This guide contains record of my field experience at Concord Free Public Library in the Spring 2021 semester
Timeliness of earthquake magnitude estimation from the prompt elasto-gravity signal &amp;#160;using Deep Learning

&amp;lt;p&amp;gt;Mass redistribution during large earthquakes produces a prompt elasto-gravity signal (PEGS) that travels at the speed of light and can be observed on seismograms before the arrival of P-waves. PEGS carries information about earthquake magnitude and the temporal evolution of seismic moment, therefore it could be used to both improve the accuracy of current early source estimation systems and speed-up early warning. However, PEGS has been detected for only a handful of very large earthquakes so far, and its potential use for operational early warning remains to be established. In this work, we study the timeliness of magnitude estimation for subduction earthquakes in Japan using PEGS waveforms by means of Deep Learning and Bayesian uncertainty analysis. Given the paucity of PEGS observations, we train the model on a database of synthetic seismograms augmented with empirical noise in order to simulate more realistic waveforms. We use about 80 stations from the Japanese F-Net network and from networks with data available through IRIS.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Under this experimental setup, we find that our model is able to track the moment release for earthquakes with a final Mw above 8.0, with a system latency that depends on the signal-to-noise ratio of PEGS. The application of our model to the Mw=9.1 Tohoku-Oki earthquake shows a latency of about 50 s after which the model is able to track well the evolving Mw of the earthquake. After about 2 minutes from the earthquake origin time, a reliable estimate of its final Mw is obtained. Similar performances in terms of timeliness of final Mw estimation are observed for the relatively smaller Hokkaido earthquake (Mw=8.1) although with higher uncertainty.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Our results highlight the potential of PEGS to enhance the performance of existing tsunami early warning systems where estimating the magnitude of very large earthquakes within few minutes is vital.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;
Utilización de los materiales didácticos digitales con el GeoGebra en la Enseñanza de la Matemática

La seleccion, creacion y uso de materiales didacticos es una actividad esencial de los docentes, en particular para los educadores matematicos, por tanto, se ofrecen algunas consideraciones sobre la utilizacion de los materiales didacticos digitales en la ensenanza de la matematica, que han desplazado a un segundo plano los materiales didacticos tradicionales, motivados por la situacion que vive el mundo a raiz de la pandemia de la COVID-19. Se analizan las especificidades de los materiales didacticos digitales partir de su definicion, asi como los resultados de investigaciones relacionadas con el uso de estos materiales en la ensenanza en el contexto de la ensenanza digital, considerada como un salvavidas de la educacion en tiempos de pandemia. Se realizan algunas consideraciones didacticas relacionadas con la seleccion, creacion y uso de materiales didacticos digitales con el GeoGebra, lo cual depende de multiples factores y por tanto no es estatica, tambien se resalta sinteticamente la utilizacion de materiales didacticos digitales para la ensenanza aprendizaje de la matematica con este software.Palabras clave: Materiales didacticos, GeoGebra, didactica, software, matematica. ABSTRACTThe selection, creation and use of didactic materials is an essential activity of the educational ones, in particular for the mathematical educators, therefore, they offer some considerations on the use of the didactic digital materials in the mathematics teaching that you/they have displaced to a second plan the didactic traditional materials, motivated by the situation that the world lives soon after the pandemic of COVID-19. The specificities of the didactic digital materials are analyzed to leave of their definition, as well as the results of investigations related with the use of these materials in the teaching in the context of the digital teaching, considered as a lifeboat of the education in times of pandemic. They are carried out some didactic considerations related with the selection, creation and use of didactic digital materials with GeoGebra, that which depends on multiple factors and therefore it is not static, it is also stood out synthetically the use of didactic digital materials for the mathematics teaching learning with this software.Keywords: Didactic materials, GeoGebra, didactics, software, mathematics.
Экологическая опасность загрязнения почв урбанизированных территорий горнорудного региона

Introduction. The article presents the results of the study of the quality of soil cover in the cities located in the mountainous areas of the Trans-Urals in the Republic of Bashkortostan. The object of the study was the soil of lands for various purposes in cities of Uchaly, Sibay, and Baymak. In the study of soils of industrial zones, there were taken samples adjacent to the dumps and tailing dumps of mining production at a distance of up to 500 m. In the recreational zone there were included the territories of parks, in the residential zone - all micro-districts where the population of the city resides. There were investigated territories of collective gardens located near sources of pollution. Material and methods. The gross content of heavy metals and their mobile forms extracted from the soil of ammonium acetate buffer at pH 4.8 were determined by atomic absorption. Generally accepted ecological values of maximum permissible concentrations (MPC) and regional geochemical background (RGF) were used to estimate the degree of soil pollution. To assess the degree of soil pollution, the total ZC index was calculated using the formula proposed by Yu. E. Saet. Results. As a result of the study, in all studied samples of the soil excess of MPC on gross forms on the content of Cu, Zn, in some cases, Mn, Cd, Co was revealed. Calculations of the General norm of Zc showed urban soil lands of all types of purpose by gross content to belong to the category of permissible pollution. The level of soil contamination with heavy metals in all the studied cities is higher in soils for industrial purposes. Increased level of mobile forms of Cu, Zn, Mn, Cd was revealed in all studied soil samples. The soils of the residential zone of Baymak according to the content of mobile forms belong to the moderately dangerous category of pollution, the rest of the studied soils had an acceptable category of pollution. In the cities of Sibay and Uchaly, the territories adjacent to the quarry dumps belong to a particularly dangerous category of pollution. Conclusion. The level of soil contamination with heavy metals in urban areas of the Mountainous region of the Republic of Bashkortostan is determined by the type of destination of urban land. The most polluted are the soils of industrial zones located in close proximity to mining enterprises. The ecological danger of pollution is that in this zone there is a part of residential neighborhoods with knots, as well as garden cooperatives, where potatoes, vegetables and fruit and berry crops are grown.
LibGuides: ICS 634 Project Management: Home

The class helps to develop a definition and understanding of a project, its components, and the challenges and management of a project. The objective is to help make use of project management skills.
Financially Ever After: A Thesis on Cryptocurrency and the Global Financial Economy

This paper reveals the struggle for regulatory balance between ensuring progressive innovation and stifling fraudulent sophistry in the emerging disruptive blockchain economy. With a particular focus on cryptocurrencies, it envisions a practical solution in technological advancement that combines economic considerations and monetary policy in the roll-out of and implementation of a framework for the health of the financial economy - the Competitive Popularity Approach (CPA).The CPA framework is a three-part framework that draws from elements of market capitalisation, competitive business strategies and technological advancement to encourage innovation while maintaining regulatory supervision over the financial sector. It considers the possibility of harnessing technological advancement by providing a theoretical incentive for developing a multi-dimensional, self-regulating ecosystem through the promising potential of blockchain technology in order to achieve a semblance of the balance we desire.With the state adoption of the core tenets of this framework on a sufficiently international scale, the financial sector may witness an exponential transformation for the better.The framework essentially directs us to create, integrate and regulate. This may sound simple but is in fact a complex, intricate web of details which are not as easy to achieve. The paper discusses this framework in a manner that is neither perfect nor complete. At best, it could be described as skeletal. This is necessarily the consequence of the relatively nascent state of the technology in spite of its ground-breaking potential. There is still a lot about the technology that we have to uncover, uncertainties about the effectiveness of legal manoeuvres we have to experiment, and a number of factors we may have not even foreseen yet to even regard as worth considering. The debate has only just begun. Whether or not the blockchain economy will live up to the revolution it is predicted to create is still riddled with uncertainty. Yet regardless of what policymakers ultimately decide, there is no denying that this phenomenon is not disappearing anytime soon. It is hoped that the CPA framework will jumpstart a chain reaction for a discussion that will inspire us to take a step towards a bold new normal financially ever after.
A Study of Knowledge Management Alignment with Production Management: A Study of Carpet Manufacture in Kurdistan Region of Iraq

The manufacturing sector has been profoundly impacted by advances in project management knowledge. As a result, it is critical to optimize service development processes in every project. The aim of this research was to increase cement manufacturing production by applying knowledge management concepts and Knowledge management as a mediator. The study was conducted at various cement manufacturing facilities in Iraq's Kurdistan province. To quantify production improvement in cement companies, the researchers examined four facets of knowledge management: Knowledge creation, Knowledge storage management, knowledge sharing, and Knowledge application, with Knowledge management serving as a mediator. To conduct the current analysis, the researchers used a quantitative research approach in the form of a survey. The questionnaire was randomly distributed to 140 administrative employees of various cement manufacturing companies in the Kurdistan region. The researchers did, however, collect 128 completed questionnaires. To assess developed research hypotheses, the study used hierarchical multiple regression analysis and the Sobel test. The findings indicated that all knowledge management elements (Knowledge creation, Knowledge storage development, knowledge sharing, and Knowledge application) had a clear and important positive relationship with increased production at carpet manufacturers in Iraq's Kurdistan region. Additionally, the findings indicated that all knowledge management concepts with a mediator (project management development program) had an indirect positive and important relationship with increased production at cement manufacturing facilities in Iraq's Kurdistan region.
The Use Of Digital Gaming Technologies In Solving The Problems Of Environmental Education

This paper defines the theoretical justification and the possibility of using digital gaming technologies in the process of solving the problems of environmental education at various stages of the general educational system. A theoretical review of mobile, computer applications and the practical possibility of their use in accordance with the age and individual characteristics of students in the process of environmental education are brought in the article.
Use of the systematic analysis method in teaching the "unsaturated hydrocarbons" subject in organic chemistry in general secondary schools

The use of the systematic analysis method in the organic chemistry teaching to secondary school students is covered and lesson plans are presented. The unsaturated hydrocarbons subject has been systematically analyzed.
Exploring the efficacy of Zoom as MALL tool in Pakistan

- Since its outbreak COVID-19 has transformed society and particularly the learning and teaching methods. This research tends to investigate the impact of zoom as Mobile Assisted Language Learning (MALL) tool in Pakistani context. The population of this study comes from Lahore where 120 learners were the sample. Two groups i.e. controlled and experimental were made. Pre and posttest was applied to explore the performance of the groups. The conventional group was taught by other learning methods whereas the experimental group learnt through zoom using MALL. The outcomes reflected that the experimental group learners performed significantly better than the controlled group. The results thus proved the efficacy and value of zoom as a major MALL tool
DI Library: Senior Project (ID 395): Welcome

DI Library's guide to books, websites, and other resources for students in Senior Project Introduction to DI Library's guide for ID V students.