Reviewerly/exHarmony huggingface dataset:
Lead Generation For Replacement Windows

Replacement Windows Lead Generation Generation of new Replacement Window Manufacturer and Distributor leads and customers is both an art and a science. ...
LibGuides: Banjo: About the Players

All about banjos - what they are, their history, who plays them, & how to learn Some of the iconic banjo players, and how to learn about others
%%title%% %%page%% %%sep%% From Beginner to Pro

Learn WordPress with Bangeez is a tutorial series we created for ourselves as well as other WordPress enthusiasts to learn and improve their knowledge of the most famous Content Management System in the World....
2015년 개정 교육과정에 따른 고등학교 경제 교과서 단원별 구성의 교육과정 부합성 분석

The purpose of this study is to analyze whether the composition of high school economic textbooks written according to the 2015 revised curriculum is consistent with the curriculum. To this end, we examined the content elements and achievement criteria of the curriculum, and analyzed the differences and characteristics in terms of the composition of the textbooks. The chapters of these high school economic textbooks reflect the five areas of the high school economic curriculum, which is consistent with the economic curriculum. On the other hand, the composition of sections differed by textbook. Even though the concept of elasticity is removed from the curriculum, all textbooks deal with the concept. This result shows the gap between the 2015 revised curriculum and the textbook. For the terms of gross domestic product or gross national income, the textbooks did not specify nominal and real variables. As the curriculum does not specify the concept of interest rate in the content elements, the textbooks also differed in explaining the real interest rate. This implies that formal review by professional groups such as the Korean Economic Association and the Korean Economic Education Association is necessary in the process of revising the economic curriculum.
ІНФОРМАЦІЙНІ ТЕХНОЛОГІЇ ОЦІНЮВАННЯ ЗНАНЬ СТУДЕНТІВ ПРИ ДИСТАНЦІЙНОМУ НАВЧАННІ НА ОСНОВІ ХМАРНИХ ТЕХНОЛОГІЙ

In this article general approaches to the usage of information technologies in the students` knowledge evaluation during distance learning based on cloud computing technologies are revealed. The role of information technologies in the modern learning process is defined. It is pointed out that nowadays the Ukrainian education stays on the stage of reformation. It is remarked that the changes which take place in the organization of teaching and educational process in higher education establishments are directed to the implementation of the competence-based approach. The definitions of notions `digital competence` and `informational and digital competence` are given. The analysis of the Law of Ukraine `About Education` concerning implementation of the distant study mode is performed. The mechanism of the usage of cloud computing technologies in order to evaluate students` knowledge during distance learning is described; it is paid attention to the advantages of cloud computing technologies. The usage of Google-services and cloud computing technologies during the educational process according to the distant study mode is considered.
LibGuides: Teaching with Primary Sources - Create Your Own Cabinet of Curiosity: Getting Started

This guide includes details to complete a remote learning exercises in materiality and help gain a sense of the physical nature of objects.
Intent classification through conversational interfaces : Classification within a small domain

Natural language processing and Machine learning are subjects undergoing intense study nowadays. These fields are continually spreading, and are more interrelated than ever before. A case in point ...
Раскрыццё праблемы экзістэнцыяльнай адзіноты ў кантэксце адказнасці за ўласны выбар (на прыкладзе рамана В. Казько «Неруш»)

Liubchanka A. A. The Problem of Existential Loneliness in the Context of Responsibility for One’s Own Choiсe (on the Example of the Novel Nerush by V. Kazko). The article discusses the problem of existential loneliness followed by responsibility for one’s own choice, on the basis of the novel Nerush by V. Kazko. The image of the main character, his actions and motivation, the influence of minor characters on the protagonist are analyzed in detail in the philosophical paradigm of existentialism. The author draws attention to the role of symbolic images in the the novel’s problematics, understanding other problems of existentialism: the absurdity of being, existential abandonment, choice in the marginal situation, and alienation.
An Analysis of Code Mixing Used by Students in Learning English

This research focused on analyzing the use code mixing in the terms of types and most dominant type used by students at SMA N 1 Bandar Baru. The objective of this study is to measure the frequency of code mixing occurrences and the most dominant type that students used. The research methodology used in this research was descriptive qualitative method. The subjects of this research were the students at SMA N 1 Bandar Baru. The subject are selected by using random sampling which the researcher randomly chooses the students from eleven grade. This research used observation in collecting the data. The researcher observed, recorded the data and take notes from the beginning until the end of the class. The data collection was done in three meetings a week and was take 90 minutes in one meeting. The result form observation shows that there were three types of code mixing used by students in in learning process, namely intra sentential code mixing , intra lexical code mixing and involving change of pronunciation. Intra sentential code mixing was the dominant type used by students in learning process, with total 72 utterances which is 61 utterances (85%) included intra sentential code mixing, 7 utterances (10%) included intra lexical and 4 utterances (5%) included Involving change of pronunciation.
LibGuides: Public Services Guide: Borrowing Policies

Guides for services, systems, machines, procedures, policies, and financial functions for all who may work at Bierce Library Service Desk Student, faculty, staff, community patron, visiting OhioLINK check out & renewal time periods
Tinjauan Literature tentang Knowledge Management: Definisi Konseptual, Dasar Teoritik dan Praktik Knowledge Management, serta Perkembangan Penelitiannya dalam Bidang Ilmu Manajemen dan Pendidikan

The main goal of this paper is to perform in-depth theoretical review and analysis the fields of knowledge management (KM) and explore development about KM in management literature, including trend in educational context. To address these purposes, first, we analyze and summerize few theoretical basis about KM which include definitions, stages about KM and theoretical foundation, and its evolution as well; second, we conduct a comprehensive review about the major approaches to design the KM system from different perspectives including knowledge representation and organization, knowledge sharing and performance measure for KM; third, we identify KM research trend in management and education studies
ENVRI knowledge base: A community knowledge base for research, innovation and society

&amp;lt;p&amp;gt;The Horizon 2020 ENVRI-FAIR project brings together 14 European environmental research infrastructures (ENVRI) to develop solutions to improve the FAIRness of their data and services, and eventually to connect the ENVRI community with the European Open Science Cloud (EOSC). It is thus essential to share the reusable solutions while RIs are tackling common challenges in improving their FAIRness, and to continually assess the FAIRness of ENVRI (meta)data services as they are developed.&amp;amp;#160;&amp;lt;br&amp;gt;The FAIRness assessment is, however, far from trivial. On the one hand, the task relies on gathering the required information from RIs, e.g. information about the metadata and data repositories operated by RIs, the kind of metadata standards repositories implement, the use of persistent identifier systems. Such information is gathered using questionnaires whose processing can be time-consuming. On the other hand, to enable efficient querying, processing and analysis, the information needs to be machine-actionable and curated in a knowledge base.&amp;lt;br&amp;gt;Besides acting as a general resource to learn about RIs, the ENVRI knowledge base (KB) supports RI managers in identifying current gaps in their RI&amp;amp;#8217;s implementation of the FAIR Data Principles. For instance, a RI manager can interrogate the KB to discover whether a data repository of the RI uses a persistent identifier service or if the repository is certified according to some scheme. Having identified a gap, the KB can support the RI manager in exploring the solutions implemented by other RIs.&amp;lt;br&amp;gt;By linking questionnaire information to training resources, the KB also supports the discovery of materials that provide hands-on demonstrations for how state-of-the-art technologies can be used and implemented to address FAIR requirements. For instance, if a RI manager discovers that the metadata of one of the RI&amp;amp;#8217;s repositories does not include machine-readable provenance, the ENVRI KB can inform the manager about available training material demonstrating how the PROV Ontology can be used to implement machine-readable provenance in systems. Such demonstrators can be highly actionable as they can be implemented in Jupyter and executed with services such as mybinder. Thus, the KB can seamlessly integrate the state of FAIR implementation in RIs with actionable training material and is therefore a resource that is expected to contribute substantially to improving ENVRI FAIRness.&amp;lt;br&amp;gt;The ENVRI KB is implemented using the W3C Recommendations developed within the Semantic Web Activity, specifically RDF, OWL, and SPARQL. To effectively expose its content to RI communities, ranging from scientists to managers, and other stakeholders, the ENVRI-FAIR KB will need a customisable user interface for context-aware information discovery, visualisation, and content update. The current prototype can be accessed: kb.oil-e.net.&amp;amp;#160;&amp;lt;/p&amp;gt;
Geometrical Regret Matching of Mixed Strategies

We argue that the existing regret matchings for Nash equilibrium approximation conduct jumpy strategy updating when the probabilities of future plays are set to be proportional to positive regret measures. We propose a geometrical regret matching which features smooth strategy updating. Our approach is simple, intuitive and natural. The analytical and numerical results show that, continuously and smoothly suppressing unprofitable pure strategies is sufficient for the game to evolve towards Nash equilibrium, suggesting that in reality the tendency for equilibrium could be pervasive and irresistible. Technically, iterative regret matching gives rise to a sequence of adjusted mixed strategies for our study its approximation to the true equilibrium point. The sequence can be studied in metric space and visualized nicely as a clear path towards an equilibrium point. Our theory has limitations in optimizing the approximation accuracy.
LibGuides: Shared Regional: Home

Information about the Shared Regional Agreement between the UVA and UNC-Chapel Hill Libraries
Modeling, Learning and Reasoning with Structured Bayesian Networks

Author(s): Shen, Yujia | Advisor(s): Darwiche, Adnan Y | Abstract: Probabilistic graphical models, e.g. Bayesian Networks, have been traditionally introduced to model and reason with uncertainty. A graph structure is crafted to capture knowledge of conditional independence relationships among random variables, which can enhance the computational complexity of reasoning. To generate such a graph, one sometimes has to provide vast and detailed knowledge about how variables interacts, which may not be readily available. In some cases, although a graph structure can be obtained from available knowledge, it can be too dense to be useful computationally. In this dissertation, we propose a new type of probabilistic graphical models called a Structured Bayesian network (SBN) that requires less detailed knowledge about conditional independences. The new model can also leverage other types of knowledge, including logical constraints and conditional independencies that are not visible in the graph structure. Using SBNs, different types of knowledge act in harmony to facilitate reasoning and learning from a stochastic world. We study SBNs across the dimensions of modeling, inference and learning. We also demonstrate some of their applications in the domain of traffic modeling.
LibGuides at USA: PSC 586: Health Administration: Example Topic / Search Term Generation

This course is in support of the University of South Alabama's PSC 586: Health Administration course.
Research Guides: Electronic Reserves (Temporary Service): Home

This guide lists the items available while the libraries are operating under remote services.
LibGuides: OverDrive: Returning

This guide will take a look at OverDrive and give you a general understanding on how it works, what it is, and how you can use it.
EMCC Libraries: Moving Online Help for Instructors: Interesting Resources

This lib guide has information for instructors on how to set up your distance classes Here is where we have put interesting educational resources that have been made available during this time.
Design and implementation of computational models for film assessment and classification

Machine Learning is impregnating every industry and every area of our lives, so it madesense that it was applied to a field as linked to technology as cinema. Big productioncompanies as Netflix have already started to use algorithms to find ways of telling storiesthat are more appealing to the audiences.But good films still fail in the box office, so this project tackles the supposition ofassessing the quality of a film, based on the standards of a particular film festival, inorder to try to predict the failure or success a film will have. This project will work ina restrained environment but the suppositions made could be extrapolated to featurefilms, with the proper resources and time.We will analyze what features make each film unique, what descriptors can give ushidden information about the video and the audio and how this features can be fed tocomputational models to predict weather a film will end as Finalist or not of a givenfilm festival.
När tekniken möter juridiken – Hur förhåller sig den svenska upphovsrätten till AI-genererade alster?

The emergence of Artificial Intelligence (AI) poses a number of challenges to copyright law. The existing copyright regulations provide protection for works created by human beings. At the same time, advances in AI and deep machine learning have enabled AI systems to generate creations of literature, music and images, which are traditionally associated with the human domain.The thesis investigates the generating process of AI-creations and whether any copyright infringements could occur in relation to, for example, the exclusive reproduction right of the existing works which are used as input in the AI system. When algorithms in the AI systems read and look at protected content, the temporary copying takes place. Although generally the author's exclusive right may be restricted pursuant to 11 a URL §, by allowing certain use of temporary copies without the author's permission, in the thesis it is stated that the exception is not applicable to temporary acts of reproduction that occur during the generating process of AI-creations. The second comprehensive part of the thesis focuses at the end result generated by an AI system, namely the AI-creation. The thesis investigates the significance of the AI system using the existing works as inspiration in their own creative process and whether the AI-creation constitutes derivative or new, independent work. In order for a creation to qualify as work in accordance with the Swedish Copyright Act, the creation has to be original in the sense that it is the author's own intellectual creation. The concept of originality has been harmonized through the practice of the ECJ and, consequently, the within the meaning herein should, for instance, reflect the author's personality. The thesis investigates whether an AI-creation is generally able to obtain copyright protection depending on the amount of the human effort invested in the creation process.The possible entry of AI into copyright law has required an examination of the fundamental motives thereof, in order to investigate how AI creations fit in the sphere of copyright law and whether they could meet the criteria for the AI creations to be protected with copyrights or neighboring rights. However, it seems that the arguments of the natural rights defend the human-made creations and seem to exclude AI-generated creations from copyright protection. The incentive theory does not make a difference of who creates creations, instead copyright protection is regarded as an incentive for more creations to be created and distributed to society. Although AI is not encouraged by financial incentives, the creators behind the AI systems may be. The study finds that if AI development is to continue, the relevant copyright regulations must be introduced and adjusted to fit the purpose. Amendments to the concept of originality are suggested as well as potential introduction of new neighboring rights to cover the subject. Furthermore, legal exemptions with respect to the use of temporary copies arising from AI's generating process should be implemented.
Analisis Clustering Daerah Rawan Banjir Menggunakan Fuzzy C-Means (Studi Kasus: Bakorwil 2 Jawa Timur)

Floods can endanger human life, such as damaging people's houses, damaging public facilities or infrastructure and residents' agricultural land. The study of flood-prone areas can be a reference to determine the possible magnitude of losses and can be a series of government efforts to reduce disaster risk to be more effective. One area in Indonesia that is prone to flooding is Bakorwil 2 East Java, especially during the rainy season. To map or classify flood-prone areas in this study using Fuzzy C-Means. Clustering results show that 94 sub-districts in Bakorwil 2 East Java are best clustered into 5 clusters, there are 6 sub-districts which are classified as vulnerable areas with very high risk of flooding and as many as 63 sub-districts are included in flood-prone areas with very low risk.
A Study And Research Is To Bring Awareness Of Increased Activity Of Cyber-Attacks Directed At Financial Institutions (Online banking information security versus hackers)

In this article discuss four scenarios concerning cyber crimes exclusively bound for at financial institutions and give detailed examples. Also, I will converse the malevolent and URL zone bank malware Trojans that is at this time causing safety issues and threats to some financial institutions. Expected results from study and research is to bring awareness of improved movement of cyber-attacks aimed at at financial institutions, call for a global grouping against cyber-pirates, and point out that financial institution's have a accountability to defend and protected in sequence as custodians of their customer's responsive/heritage data online.
THE ROLE OF NEED FOR STRUCTURE IN TECHNICAL ANALYSIS AND HOW IDENTIFYING INFORMATION IN PRICE MOVEMENTS RAISES TRADERS’ CONFIDENCE

Technical analysis (TA) is a tool believed to support investor’s investment decisions. Even if research has demonstrated that TA cannot be used to make systematic profits over a long time period, it could potentially bring psychological payoffs to its users in the form of enhancing their confidence. In an experimental study we show that: (1) chartists demonstrate overconfidence in TA usage, believing that they are better than they actually are in TA formation recognition, and that; (2) the act of naming an observed trend as a TA formation brings extra confidence to the chartist, regardless of whether this is a real TA sequence or a random sequence. Thus, both naming an existing TA formation as a TA formation and naming a random sequence as a TA formation result in greater confidence. Also, irrespective of the high popularity of TA among investors, there are marked individual differences in TA followers. In a questionnaire study, we demonstrate that declared positive attitudes toward TA correlate positively with  high need for (cognitive) closure (as measured by the Need for Cognitive Closure Scale; NFCS), specifically, desire for predictability.
Simultaneous Classification of Sets of Images Using Deep Learning and Clustering

Classification of cell images is conventionally done manually in hematology laboratories by medical technologists. CellaVision aims to automate this work in order to make the analysis process faster, better and more flexible. The automatic classification is currently done by processing each individual cell image through a Convolutional Neural Network. This methodology does not exploit any correlations that might exist between cells from the same blood sample. We suggest a method to first compress the images of a whole sample using a Convolutional Neural Network and a Variational Autoencoder, then cluster these compressed data points using DBSCAN clustering and Bayesian Optimization, and finally assign a cell class to each cluster using statistical tools such as Earth Mover's Distance. We used data from CellaVision's system DC-1 to train a Convolutional Neural Network with 90.68% accuracy on training data and 82.85% accuracy on test data. This was used both as a benchmark and as the foundation to our method. We managed to enhance the accuracies to 90.90% on training data and 83.13% on test data by applying our method. We explored the feasibility of using our method on mixed cell data from different systems, but the results were not as good as on DC-1 data. Applying our method on images of handwritten digits from the MNIST dataset could be made advantageous by forming customized subsets of images. This indicates that our method is versatile enough to use on general image data, provided that correlations within the subsets exist. (Less)
The Exploratory Role of Explainable Artificial Intelligence

Models developed using machine learning (ML) are increasingly prevalent in scientific research. Because many of these models are opaque, techniques from Explainable AI (XAI) have been developed to render them transparent. But XAI is more than just the solution to the problems that opacity poses—it also plays an invaluable exploratory role. In this paper, we demonstrate that current XAI techniques can be used to (1) better understand what an ML model is a model of, (2) engage in causal inference over high-dimensional nonlinear systems, and (3) generate algorithmic-level hypotheses in cognitive science.
Call Center Manager's Guide to Service Level Agreements | AVOXI

Measuring the Service Level (SL) of your organization can help you make informed decisions regarding your workforce and the company. Call center ...
LibGuides: Diversity, Equity, and Inclusion in STEM: Home

A guide to resources related to underrepresented groups in science, technology, engineering and mathematics.
Noreen Reale Falcone Library: How to Use Subject and Course Research Guides: Home

This tutorial will show you how to use subject and course research guides to help you with research for your classes.
LibGuides: APA 7th Edition: Social Media

This guide will help you simplify the APA citation style, which is primarily used by disciplines in the business, social sciences, health, and education fields. The official guide is published by the American Psychological Association.