Reviewerly/exHarmony huggingface dataset:
Blockchain-secured health wearables in smart homes utilising raspberry pi web of things gateways

Owing to the large-scale public health crisis arising from the Coronavirus Disease 2019 (COVID-19), the global health system could not adequately deal with the entirety of infections. Consequently, improvisations meant to complement the healthcare systems in remedying the pandemic emerged. “Hospital-at-home” improvisations include the use of wearable technology to triage patients within households before consulting the health institutions. The wearable devices collect physiological and activity data in order to detect or predict the prevalence of the disease. Unfortunately, Do-It-Yourself health improvisations expose citizens to security vulnerabilities and interoperability challenges. This study proposes the adaptation of a prototype developed prior to the pandemic in securing smart homes and to interoperate health wearable devices used in detecting the prevalence of COVID-19 before symptoms manifest. Focus is placed on: 1) Integration of wearables from different vendors to ensure interoperability using the Mozilla WebThings gateway on Raspberry Pi;2) Use of Hyperledger Fabric Blockchain to secure the data and allow for implementation of legal restrictions through software. The proposed user-centric wearables architecture enhances data privacy through edge and fog computing, whilst opening up Smart Homes to General Data and Protection Regulations (GDPR)-inspired “data portability” and personal data monetization opportunities. © IEOM Society International.
ОБ УСЛОВИЯХ УПРАВЛЯЕМОСТИ АНСАМБЛЯ ТРАЕКТОРИЙ ДИФФЕРЕНЦИАЛЬНЫХ ВКЛЮЧЕНИЙ

In this paper we consider the one model of dynamic system under conditions of indeterminacy – linear controllable differential inclusions. For the model of the control system the problem of controllability is researched. The necessary end sufficient conditions of controllability of ensemble trajectories are obtained.
The Electronic Portfolio of a Research University in the Mirror of Webliometrics

This article is a continuation of the series of articles devoted to the formation of university teacher’s portfolio, portfolio of supporting university, portfolio of classical university. Due to the imbalance in the country’s spatial development caused by the concentration of the country's scientific and technological potential in Moscow and Saint Petersburg, regional universities, first of all: research universities, are charged with the task of eliminating the imbalance in the country’s regional development under the conditions of state support of leading regional universities. The research university is considered as the object of research. The subject of the study is the electronic resources of science, education and support areas of the state economy included in the e-portfolio of the university. The methods of the study are webliometric and logical. The article considers the results of the research university e-portfolio webliometrics in order to develop recommendations for improving the management of research universities, which are tasked to prepare and concentrate the scientific and technological potential of the region in order to align the spatial space of Russia.
Characterizing and quantifying information conveyed by large neuronal populations

Author(s): Berkowitz, John | Advisor(s): Sharpee, Tatyana O. | Abstract: How neurons in the brain collectively represent stimuli is a long standing open problem. Studies in many species from leech and cricket to primate show that animals behavior, such as gaze direction or arm movement, often correlates with a measure of neural activitytermed the population vector. To construct it, one averages preferred stimuli for each neuron proportionately to their responses. However, the population vector discards much of the information contained in the activity of the population. In the first part of this thesis we show that for a broad class of common models of neural populations a sufficient statistic of the population response can be constructed that is guaranteed to transmit as much information about the stimulus as the population response. The statistic has fixed dimension, independent of the population size, and is valid even in the presence of intrinsic interneuronal correlations. This statistic turns out to be a re-weighted version of the population vector. We validate the performance of this statistic on a dataset of visual neural responses. Additionally we show that under certain conditions, this statistic can serve as a reconstruction of the stimulus itself. Quantifying mutual information between inputs and outputs of a large neural circuit is an important open problem in both machine learning and neuroscience. However, evaluation of the mutual information is known to be generally intractable for large systems due to the exponential growth in the number of terms that need to be evaluated. Here we show how information contained in the responses of large neural populations can be effectively computed for a class of models that generalize those considered in the first part of the thesis. Neural responses in this model can remain sensitive to multiple stimulus components. We show that the mutual information in this model can be effectively approximated as a sum of lower- dimensional conditional mutual information terms. The approximations become exact in the limit of large neural populations and for certain conditions on the distribution of receptive fields across the neural population. We empirically find that these approximations continue to work well even when the conditions on the receptive field distributions are not fulfilled. The computing cost for the proposed methods grows linearly in the dimension of the input, and compares favourably with other approximations.
LibGuides: Mathematics, Science and Technology Education: E-Newspapers and E-Magazines

This guide will help students to easily access resources that are available in their libraries
Benchmarking Deep Learning Testing Techniques A Methodology and Its Application

With the adoption of Deep Learning (DL) systems within the security and safetycriticaldomains, a variety of traditional testing techniques, novel techniques, andnew ideas are increasingly being adopted and implemented within DL testing tools.However, there is currently no benchmark method that can help practitioners tocompare the performance of the different DL testing tools. The primary objectiveof this study is to attempt to construct a benchmarking method to help practitionersin their selection of a DL testing tool. In this paper, we perform an exploratory studyon fifteen DL testing tools to construct a benchmarking method and have made oneof the first steps towards designing a benchmarking method for DL testing tools. Wepropose a set of seven tasks using a requirement-scenario-task model, to benchmarkDL testing tools. We evaluated four DL testing tools using our benchmarking tool.The results show that the current focus within the field of DL testing is on improvingthe robustness of the DL systems, however, common performance metrics to evaluateDL testing tools are difficult to establish. Our study suggests that even though thereis an increase in DL testing research papers, the field is still in an early phase; it is notsufficiently developed to run a full benchmarking suite. However, the benchmarkingtasks defined in the benchmarking method can be helpful to the DL practitionersin selecting a DL testing tool. For future research, we recommend a collaborativeeffort between the DL testing tool researchers to extend the benchmarking method.
A Statistical Approach for Context-Awareness of Mobile Applications.

Context-aware systems are able to sense and adapt to the environment. Mobile applications can benefit from context-awareness since they incur to context changes during their execution. A detailed understanding of the context is needed to know what a context-aware system should sense and adapt to. This paper introduces a statistical approach that helps in determining contextual situations that require adaptation. The approach starts from monitoring mobile context variables values, modeling their states, and deducing from these models a Markov chain model, where each state represents a contextual situation. Depending on transition probabilities and system quality at each state we can decide when it is necessary to apply context-awareness.
Features of Using Automated Control Systems at the Enterprises of the Hotel Business

The development of information technologies today implies opportunities for the development and implementation of automated systems in various applied areas, implying the need for information processing, the formation of various data representations. The modern economy operating in a competitive market, makes demands on the timeliness of information processing, the improvement of production organization technologies, the efficiency and long-term planning, forecasting and analysis of economic activities.
LibGuides: LI855XU Geography Collection LibGuide: Journals and Periodicals

This guide is meant to assist students at Dixie State University in finding resources within the new Geography Collection.
Study on the Teaching Practice Mechanism of the Course of Building Engineering Structure Detection

The reform and construction of the teaching content, teaching methods, assessment methods and experimental objects of the course of structural testing of building engineering is an important measure to build the course into a golden course of gender. Based on the analysis of the factors affecting the teaching of the course of structural detection of building engineering and the derivation of the evaluation model of the teaching effect, it is concluded that the innovation of the teaching content can be improved by optimizing the teaching content and constructing the network teaching platform, the modern teaching technology can be introduced into the experimental teaching to improve the teaching quality.The comprehensive consideration can be given in the course assessment, experimental preview, scheme formulation and trial the contents of experiment operation, test report and innovation improvement can comprehensively reflect the scientificity of curriculum assessment.The frontier of experimental objects can be improved by accumulating teachers' practical experience and professional engineering case analysis.
LibGuides: Faculty Services: Course Reserves

Max Chambers Library services for faculty Information on how to place items on course reserve
Should Artificial Intelligence Pay Taxes?

The tax system incentivizes automation, even in cases where it is not otherwise efficient. This is because the vast majority of tax revenue is derived from labor income. When an AI replaces a person, the government loses a substantial amount of tax revenue - potentially hundreds of billions of dollars a year in the aggregate. All of this is the unintended result of a system designed to tax labor rather than capital. Such a system no longer works once labor is capital. Robots are not good taxpayers. The solution is to change the tax system to be more neutral between AI and human workers and to limit automation’s impact on tax revenue. This would be best achieved by reducing taxes on human workers and increasing corporate and capital taxes.
Research on the error probability distribution of photovoltaic output prediction based on output fluctuation characteristics and Generalized Gaussian Mixture Model

Photovoltaic power output forecast error exists objectively and inevitably, and it can provide a guarantee for safe and stable operation of the power system through analyzing its characteristics. In this paper, the influence of predicted output fluctuation characteristics (predicted output amplitude and power variation) on prediction error was studied based on the analysis of variance (ANOVA) method. The prediction error conditions were classified into six types based on the clustering of numerical characteristics of predicted output. Then, a Generalized Gaussian Mixture Model (GGMM) was proposed to fit the prediction error distribution of each type of photovoltaic output. The mean absolute error (MAE), coefficient of determination (R 2 ), and root mean square error (RMSE) were used as accuracy evaluation indexes. The example analysis showed that the GGMM can satisfy the asymmetry and kurtosis diversity of the error distribution after division by conditions, and the fitting result is better than that of the normal distribution, improved Laplace distribution and t Location-Scale distribution model.
LibGuides: A Kid's Guide to Blended Families: Home

The purpose of this guide is to provide children (age 4-12) and parents with informational and recreational resources related to the topic of blended families.
LibGuides: Curriculum and Instructional Studies: Research Support

This guide will help students to access information resources on curriculum and instructional studies
An Effort to Increase the Concentration of Children at 5-6 Years Old using the Storytelling Methods at ST Theresia Kindergarten Binjai T.A 2014/2015

The case of this study is the lack of children’s concentration following the lessons, especially in terms of storytelling. Cause by the teaching method of teachers which is not apply storytelling in learning activities at schools. This study aims to determine whether the method of storytelling can increase the concentration of children aged 5-6 years at ST. Theresia Kindergarten Binjai  on 2014/2015. This type of research is a classroom action research (CAR) conducted in 2 cycles. Tools for Collecting the data using observation. The subjects of the study are 18 children, consisting of 8 girls and 10 boys. The results of the analysis average concentration of children increased to 80.5% which was still in the good category. From the results of the above research it can be concluded that by using the method of storytelling can increase the concentration.
Prediction of Solar Radiation Using Neural Networks Forecasting

Solar radiation and wind data play an important role in renewable energy projects to produce electricity. In Ecuador, these data are not always available for locations of interest due to absences of meteorological stations. In the scope of this paper, a low-cost automatic meteorological station prototype based on Raspberry technology was developed to measure the aforementioned variables. The objective of this paper is twofold: a) to present a proposal for the design of a low-cost automatic weather station using the Raspberry Pi microcomputer, showing the feasibility of this technology as an alternative for the construction of automatic meteorological station and; b) to use Forecasting with neural networks to predict solar radiation in Manta, Ecuador, based on the historical data collected: solar radiation, wind speed and wind direction. We proved that both technology feasibility and Machine learning has a high potential as a tool to use in this field of study.
LibGuides: Free Online Software: Storage Clouds

This LibGuide highlights some of the free software that is online. Microsoft Office, antivirus programs, Photoshop, among other programs and tools can be expensive. Why spend the money if you can get it for free? A list of some of the popular storage options
Impact of Information Technology Risks on Information Systems Security: A Field Study of Telecommunication Companies in Yemen

This study aimed to assess the impact of information technology risks on security of information systems by following an analytical method based on the structural equation modeling (SEM). The study population was seven telecommunication companies in Yemen. A questionnaire was distributed to 356 participants, but only 218 forms were valid for analysis. The data was analyzed by the partial least squares (PLS). The study findings revealed that information technology risks had a negative impact on the security of information systems. The study recommended that the security of information systems should be strengthened so as to maintain the confidentiality of information, its availability and safety from risks, and to cope with speedy developments in information and communication technology.
Efficient data clustering algorithm designed using a heuristic approach

Information retrieval from a large amount of information available in a database is a major issue these days. The relevant information extraction from the voluminous information available on the web is being done using various techniques like natural language processing, lexical analysis, clustering, categorisation, etc. In this paper, we have discussed the clustering methods used for clustering of large amount of data using different features to classify the data. In today's era, various problem solving techniques makes the use of a heuristic approach for designing and developing various efficient algorithms. In this paper, we have proposed a clustering technique using a heuristic function to select the centroid so that the clusters formed are as per the need of the user. The heuristic function designed in this paper is based on the conceptually similar data points so that they are grouped into accurate clusters. k-means clustering algorithm is majorly used to cluster the data which is also focussed in this paper. It has been empirically found that the clusters formed and the data points which belong to a cluster are close to human analysis as compared to existing clustering algorithms.
All guides: Using Videos in Canvas: Kanopy

This guide provides instructions on linking and embedding Library videos, including playlists and clips, in your Canvas course and Reading List.
중국인 유학생 대상 역사 문화 교육 방안 -주제 중심 접근법의 적용을 중심으로-

The purpose of this study is to select educational content fit for education on Korean history and culture for Chinese students studying in South Korea and search for practical educational methods for it. Chinese learners’ knowledge about the history and language of their own country can be utilized as a resource to broaden their intercultural understanding when they study Korean history and culture. For educational content, the investigator found a topic in Choi Chi-won, a Confucian scholar from Unified Silla, since he was a representative figure of enabling a historical recognition for cultural exchange between Korea and China, organizing specific content and devising proper instructional methods. The study first examined the concept of history and culture education for foreign learners and theme-based instruction, which is an approach to language education that organizes content around a selected topic. One of the theme-based instructional models, the Six-T's approach in Stoller and Grabe(1997) was consulted to design a lesson and organize educational material for concrete lesson examples. The present study proposed a method of history and culture education based on learners’ knowledge about their own culture and language and also their intercultural understanding instead of the old one-sided delivery method of Korean history and culture, thus holding its significance.(Busan University of Foreign Studies)
A Deep Dive Into Neural Network

A neural network is a chain of logics and algorithms which caters to the recognition of dependent entities and relationships in a set of data, in a manner works very much in the same manner as the regular homo sapien brain does. Henceforth, neural networks can extend their references to a configuration of neurons, which may have a synthetic setup as well, in addition to the natural one. Also, these neural networks are self-responsive to the variable inputs and generates the best outputs without any requirements of re-designing. The flowline covers up the content as follows: firstly we discuss the insights of what a neural network is in pure layman terms, henceforth the definition of CNN and NN have been showcased, after that the research literature sheds light on the actual model of our research and its representative technique has been showcased, with a code snippet excerpt which stands self-explanatory. The net bestows and the results of the proposed model have also been pasted along with. Then CNN has been talked about, a brief overview of what it actually is on broad notes, and why there arose a need of another model has been discussed therein. Lastly an implementation of CNN model using Keras (which had a key role part in our research) has been injected within.
LibGuides: Research Data Management: Archiving, Preservation and Publishing

A guide to managing outputs of research projects and handling issues such as copyright and data protection laws
LibGuides: U.S. Congressional Serial Set via HeinOnline: Browse the Serial Set

Based on the stellar guide created by Tara Kibler at HeinOnline. Browsing HeinOnline's U.S. Congressional Serial Set.
Communication Networks and Blockchain

When thinking about applying blockchain systems for telecommunication networks, we need to think about what benefits this blockchain technology will bring to the telecommunication system under consideration? How this blockchain technology when applied to telecommunication network is superior to traditional database solutions? What cost needs to be incurred when deploying blockchain technology to telecommunication networks? In this chapter, we discuss the answer to these questions and highlight the potential application of blockchain technology in various communication networks.
TV 자막 기능의 변화 양상 연구

This article deals with the role of subtitle in transferring information from the view of language symbolism. At first, the image had played the main role, which made the subtitle merely help with partial program management, additional information or compensate information to the part that needs more explanation. However, compared to the subtitle in entertaining programs in 2003, the subtitle in 2017 had opened up the whole different channel by putting the fun factor and helping the development of programs actively. Furthermore, it even has spread its role to story telling as it developed the programs itself. Thanks to this, producers have been able to add more fun factors by involving in the program directly and as much as they want. Moreover, in some programs, the subtitle even plays the role of the letters for writers as illustrating, explaining, and forming structure.
FIU Libraries: Library Grants Support: Grant Opportunities

A network and support structure for the FIU Libraries' grant proposal processes, including grant writing, funding agency communications, grant submission, post award grant management, grant closeout/reporting, and sustaining projects.
LibGuides: Marketing Outreach Toolkit: Corresponding LibGuides

This project consists of a monthly emailed checklist of outreach tasks that all build on one another to achieve large-scale goals. The idea is to frequently show stakeholders that the library is advancing campus priorities.
Analysis on the Application of XML Data of Cost Consultation Project

With the development of the construction industry, new technologies and processes continue to emerge.The extensive application of Internet big data has led to the rapid development of informatization in the cost of construction.In order to meet the needs of the owners, the cost consultation has continued to include more enriched services, and the requirements for quality have increased, which requires some valuable reference data.Hence, the data accumulation of cost consultation projects has become an important task.In recent years, people began to extract data from the past to guide future investment plans, so data extraction and applications have become popular.
학교 현장에서의 다문화이해교육 실천 -중학생 대상 다문화이해교육을 중심으로-

This study aims to argue to present a guidebook of multicultural education for middle school students and to learn how to teach accordingly. Therefore, the study will explore the teaching course of multi-cultural understanding education for middle school students, the contents of classes and media utilization, and the expected effects.(Multicultural Understanding Education Instructor)