Reviewerly/exHarmony huggingface dataset:
어린이 예술통합무용 교육의 지식 확장 기능 연구 :꿈다락 토요문화학교 주말예술캠퍼스 ‘별별캠프’ 2018 프로그램 구조를 기반으로

This study observed the knowledge education structures of contemporary dance through children’s arts integrated dance education programs. This study viewed arts integrated dance and contemporary dance as synonyms and explained dance experience forms (methods) as grounds for knowledge creation. It explored knowledge education expandability as meaning and interpretation (inference) and not as knowledge of subjects and content as children’s arts integrated dance education program structures. As observed in the program, making inferences of the everyday world and the significance of the space (symbolic experience) that participates in the creation and change of knowledge as self-discovery can newly be organized into a space in which historical, intellectual, artistic, and technical (medium) meanings are connected and knowledge creation systems (structures) such as media, records, memories, and storage (transmission, preservation) operate as simultaneity in dance experiences. Program development imagines knowledge generated through cultural and historical paths and constructs knowledge that creates meaning through lived experience, and it can present media and recording methods that act as knowledge and relationships between records and memories as experience structures and this signifies the expandability of knowledge education that confirms cultural identity and newly forms relationships through the experience of relational positions and the process in which our memories change into knowledge from records in which knowledge was formed.
Automatic Sound Level System : Constant volume at all times

Studies have shown that music has plenty of positive effects on performances in working environments. The purpose of this project was to reap those benefits by developing a prototype that could aut ...
Reform and Exploration of Blended Learning in Design Performance Technique Course

Design performance technique course is a fundamental course in environmental art major, which is of practical and operational use. In face of the existing problems in traditional teaching, the author has worked out an on-line and off-line blended learning method based on the teaching concept of MOOC, committed to integrating optimal teaching resources with actual class experience so as to make the best of advantages and supplement the shortcomings, give full play to features of different teaching environments and set up a deep learning system of information reception, experience and internalization. In such manner.This paper analyzes the blended learning in design performance techniques course, The establishment of the course teaching mode mainly includes to perfected the learning resource library, the design of teaching activities and the construction of multivariate evaluation mechanism. Through continuous teaching practice and reflection, the teaching philosophy is reshaped and the teaching mode is mixed with a variety of teaching methods to stimulate students' interest to a greater degree,learning will turn to active learning and study efficiency will be promoted. At the same time, it is expected to provide reference for teaching workers.
LibGuides: Reserve a Seat: Discovery Library Spaces

The library has a space for everyone. Discover your spot. Find out where you want to study or work in the library without visiting in person. There is personal tour of the spaces or a picture is worth a 1000 word
UTILIZAÇÃO PRÁTICA DE WORD EMBEDDING APLICADA À CLASSIFICAÇÃO DE TEXTO

Text classification aims to extract knowledge from unstructured text patterns. The concept of word incorporation is a representation technique that allows words with similar meanings to have a similar representation, in order to incorporate reasoning characteristics about their use and meaning. The aim of this article is to analyze the work already published on the use of embedded words applied to the classification of texts, to propose a practical application that demonstrates its effectiveness. This study contributes to proving the effectiveness of the use of word incorporation applied to text classification, having reached an accuracy rate of around 73%.
LibGuides: The Writing Center at Henry Ford College: HFC Writes

This is a repository for workshops, handouts, and other materials to support student and faculty writing at HFC. Resources from the WCILO Team
LibGuides: Identifying Sources in Works Cited Lists and Bibliographies: Periodical Articles

Works cited lists are very effective ways to find relevant sources for your research. In order to be able to make use of the information in works cited lists, you must be able to identify the kind of source it is: is it a book, a chapter in a book, a jour
Comparative Analysis of Techniques for Data Minimization for Recommender System algorithms

Recommender systems (RS) often use a large amount of data for a marginal gain in performance. This thesis investigates the data minimization in Recommender Systems, which is not well studied in the literature. This thesis extends the data minimization principles advocated in GDPR and studies its effects on recommender systems. Minimizing data not only reduces storage and transmission requirements but also has the potential to improve privacy and increase training and prediction speeds. This thesis investigates the effects of reducing the amount of data used to model a recommender system. It evaluates the accuracy of the Biased Matrix Factorization (BMF) algorithm by varying the training data on the MovieLens 10 million ratings (ML-10M) dataset. In this thesis, four data minimization techniques were used. We reproduced one pervious work and proposed three new data minimization techniques. In the first technique, we confirmed previous work concerning training data analysis, where the data outside the selected temporal window were dropped. The second data minimization technique, user profile truncation, retained the recent N ratings for each of the users while truncating the historical ratings. The third technique improved the user profile truncation by selectively truncating a percentage of user's historical ratings. In the fourth technique, a long user profile was split into smaller pseudo-user profiles. Analysis of the results is conducted. The most interesting results come from the third data minimization technique. Here, we show that truncating a percentage of the least recently active long user-profiles does not damage the performance and may slightly help. 60% of the long users can truncate their profiles to 20 ratings with minimal impact on the performance. Based on the results, we conclude that a substantial amount of data can be dropped without a large impact on performance. The results hold for the ML-10M dataset. It should hold for other datasets. The privacy implications of data minimization warrant future work. The proposed techniques serve as a guide for future research in data minimization of recommender systems.
Human-Object Interaction Detection: A Quick Survey and Examination of Methods

Human-object interaction detection is a relatively new task in the world of computer vision and visual semantic information extraction. With the goal of machines identifying interactions that humans perform on objects, there are many real-world use cases for the research in this field. To our knowledge, this is the first general survey of the state-of-the-art and milestone works in this field. We provide a basic survey of the developments in the field of human-object interaction detection. Many works in this field use multi-stream convolutional neural network architectures, which combine features from multiple sources in the input image. Most commonly these are the humans and objects in question, as well as the spatial quality of the two. As far as we are aware, there have not been in-depth studies performed that look into the performance of each component individually. In order to provide insight to future researchers, we perform an individualized-study that examines the performance of each component of a multi-stream convolutional neural network architecture for human-object interaction detection. Specifically, we examine the HORCNN architecture as it is a foundational work in the field. In addition, we provide an in-depth look at the HICO-DET dataset, a popular benchmark in the field of human-object interaction detection.
Service Centric Targeted Analysis Attribute Based Data Encryption and Decryption for Cloud Environment

Security is the important fact considering centralized service in cloud. As the mostorganizations has shifted their focus and data to the cloud environment which allows the users toaccess various service that are distributed by the CSP (Cloud Service Provider), the couplingbetween the data and data owner gets reduced. This introduces huge challenge in monitoring andcontrolling the access of data as well as security among the data access. To handle this severalapproaches has been recommended by various researchers which are restricting the access aswell as encrypting the data with different techniques and schemes. However,the securityperformances achieved by the techniques are not up to the expected level which introduces dataleakage in noticeable level. To handle this issue and to improve the performance in data security,a novel Service Centric Targetive Analysis with ABE as (SCTA-ABE) is proposed in this paper.The method analyzes the target of malicious user by monitoring the access logs of variousservices with the access profile being maintained for different users. By monitoring the logs ofspecific service, authentication classes produce the attribute level of access by the set ofattributes are identified as sensitive and classified under different level.This method performs attribute based data encryption with dynamic encryption standards and keys. The results provesthe proposed system produce higher performance compared that any other system
Cross-platform Framework Comparison : Flutter a React Native

The development of apps in a cross-platform framework is something that has been appearing more over the latest years. But the knowledge of knowing which of the two popular frameworks, React Native ...
Hybrid Cloud Migration Challenges. A case study at King

Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-pr ...
Research Guides: Electronic Resources at The Evergreen Library: Home

This guide aims to bring together all the electronic resources (e-books, e-journals, databases, streaming media) and digital content available through The Evergreen State College Library.
Mining for Process Improvements: Analyzing Software Repositories in Agile Retrospectives

Software Repositories contain knowledge on how software engineering teams work, communicate, and collaborate. It can be used to develop a data-informed view of a team's development process, which in turn can be employed for process improvement initiatives. In modern, Agile development methods, process improvement takes place in Retrospective meetings, in which the last development iteration is discussed. However, previously proposed activities that take place in these meetings often do not rely on project data, instead depending solely on the perceptions of team members. We propose new Retrospective activities, based on mining the software repositories of individual teams, to complement existing approaches with more objective, data-informed process views.
Gender Equality and Electoral Violence in Africa: Unlocking the Peacemaking Potential of Women

We examine the impact of gender equality on electoral violence in Africa using micro-level data from the sixth round of Afrobarometer surveys. The sample covers 30 countries. We find that gender equality is associated with lower electoral violence. Quantitatively, our estimates show that an increase in female-to-male labor force participation ratio by 1 percentage point is correlated with a reduction of the probability of electoral violence across the continent by around 4.2 percentage points. Our results are robust to alternative ways to measure electoral violence and gender equality, as well as to alternative specifications. The findings of this paper support the long-standing view that women empowerment contributes to the reduction of violence and underscore the urgency of addressing gender inequality in Africa.
Towards Highly Specialized, POSIX -compliant Software Stacks with Unikraft: Work-in-Progress

Increasingly, embedded devices are being equipped with ARM processors. Because of ease-of-use and widespread support for drivers and applications, Linux is often used as the OS of choice, even though it consumes a significant amount of the device's limited resources and its large attack surface presents opportunities for exploits. In this paper we propose Unikraft, a fully librarized operating system and build tool which allows for generating specialized OSes and software stacks targeting specific applications, while removing unneeded functionality. As a proof of concept, we port Unikraft to the Raspberry Pi 3 B+ and to a Xilinx Ultra96-V2. On these boards, Unikraft is able to boot in 88-158 milliseconds, consume only hundreds of KBs of memory when running real-world application such as NGINX, all the while providing visible reductions in power consumption compared to Linux distributions. Unikraft is an open source project and can be found at unikraft.org.
Relación entre la eficiencia del aprendizaje usando los soportes impresos o digitales y el rendimiento académico de los estudiantes de posgrados en modalidad virtual de la universidad EAN

This research seeks to identify the correlation of learning efficiency in the use of printed and digital media and their academic performance that postgraduate students have under the virtual modality of EAN University. It was evidenced that: learning efficiency and academic performance have a strong positive relationship, that the type of support used for reading the contents of the study units (whether digital or printed support) does not have a significant relationship with the academic performance, since respondents prefer to make a combined use of digital and printed media; and additionally it was evidenced that about a little more than half of the population under study print digital content
Active Learning Based Relation Classification for Knowledge Graph Construction from Conversation Data

Creation of a Knowledge Graph (KG) from text, and its usages in solving several Natural Language Processing (NLP) problems are emerging research areas. Creating KG from text is a challenging problem which requires several NLP modules working together in unison. This task becomes even more challenging when constructing knowledge graph from a conversational data, as user and agent stated facts in conversations are often not grounded and can change with dialogue turns. In this paper, we explore KG construction from conversation data in travel and taxi booking domains. We use a fixed ontology for each of the conversation domain, and extract the relation triples from the conversation. Using active learning technique we build a state-of-the-art BERT based relation classifier which uses minimal data, but still performs accurate classification of the extracted relation triples. We further design heuristics for constructing KG that uses the BERT based relation classifier and Semantic Role Labelling (SRL) for handling negations in extracted relationship triples. Through our experiments we show that using our active learning trained classifier and heuristic based method, KG can be built with good correctness and completeness scores for domain specific conversational datasets. To the best of our knowledge this is the very first attempt at creating a KG from the conversational data that could be efficiently augmented in a dialogue agent to tackle the issue of data sparseness and improve the quality of generated response.
LibGuides: Library - UJ Innovative Learning HUB: Technologies & 4IR

Welcome to the UJ Innovative Learning hub. The focus will be on resources aimed at support for Blended Learning and 4IR technology.
Constructiveness-Based Product Review Classification

Promoting constructiveness in online comment sections is an essential step to make the internet a more productive place. On online marketplaces, customers often have the opportunity to voice their ...
Program Similarity Techniques and Applications

Author(s): Nichols, Lawton Higgins | Advisor(s): Hardekopf, Ben | Abstract: The world is full of programs. More are written every day, and so the corpus of written code is ever-increasing. The entropy of all this code, however, is not increasing as fast as one might expect. Many programs are identical or very similar to others, and this is due to many possible reasons: for example, software engineers reusing code or students solving the same programming assignment. Similar code also occurs naturally when programs are updated---there the old and new versions are close relatives of each other, and this can be exploited. Discovering and exploiting similarity is useful in areas as disparate as program analysis and automated student feedback.Program similarity is not a solved problem, and my work advances the field of program similarity research along two axes: methods and applications. This work has involved the development of new similarity methods as well as the application of those methods to solve problems in a new or more effective way.
Deception patterns on Social Media

The presence of social media has led to the emergence of deception patterns based on social media characteristics which all influence its users. Social media is the new norm in society and the service providers there continue to struggle with addressing these patterns as well as try to protect their users from being influenced by deception based on social media characteristics. In this study, we draw on related literature to conceptualise a model which delineates eight social media characteristics used in deception as privacy, identity, presence, relationship, reputation, groups, conversation and sharing. This model is evaluated using data collected from eight social media users and interview transcripts from the Zuckerberg files between the years 2004 and 2020. The results show that deception in social media is patterned around personal information and false identities, among others. The results also show that trust and strength of ties are among the reasons why users are influenced into deception (Less)
Dealing with Failures for Execution Consistency in Context-aware Systems

In this paper, we consider a symbolic mechanism designed to help guide the performance of actions of a Belief-Desire-Intention (BDI) agent under both concurrency and relevance criteria. Behind the planning activity which can optimistically estimate the relevance of traces, we propose to directly supervise the best effort execution of the intentions as to keep track of the most relevant ones in case of failures. To support the presented method, a typical use case is given that targets the automated guidance of an autonomous vehicle.
La relación educativa en propuestas formativas en línea Estudio de caso desde las percepciones de los estudiantes

Universities are currently undergoing virtualization processes that operate on their structural bases and must be interpreted in the context of the transformations that societies undergo. At the beginning of the century, Garrison, Anderson and Archer (2000) introduced the Community of Inquiry (CoI) model which describes how learning takes place within a community, through the interaction of three nuclear elements that make up the core of an educational experience: cognitive presence, social presence and teacher presence. In this framework, the creation of links is presented as a vital necessity in any training intervention and a prevalent factor in the development of academic commitment, especially in the field of higher education. In line with the above, we propose to investigate how interpersonal relationships –and more specifically the teacher-student link– affect the development of academic commitment in university students of a distance-taught career, studied through a virtual platform. This approach to our object is materialized from the students' perspective through a qualitative methodology, of an exploratory-descriptive nature, framed in a case study. The “teacher-student link” emerges associated with the “affective dimension”, a component of the “social presence” element in the CoI model. Its properties are: "accompaniment", "positive reinforcement", "generosity" and "stimulation". In this way, the affective dimension and the vocation for proximity to the student transcend the physical space, and online interventions are configured as powerful generators of interpersonal relationships. This translates into a reciprocal treatment, since a relationship of presence and proximity between the participants of a curricular path is established, producing interactions that allow a real knowledge of the other. Additionally, generation of interpersonal links is defined as a nuclear factor in the development of academic commitment in online training proposals. From a relational perspective, the strengthening of interpersonal links has a central impact on education which is also verified in the virtual space, evidencing a marked personalization of the process.
Aplikasi Pengolahan Data Sewa Kios Pada Primer Koperasi Kartika Viyata Yudha

Information systems today have an important role in the progress of an organization, including in the business world. The problem that often arises in the rental business is the transaction system that is still manual, namely by relying on receipts or books in filing company data. Similar to the Kartika Viyata Yudha Cooperative Primer, of course this will make it difficult to control transaction data and reports. An application is needed that can help the system to process data, transaction data and reports that can provide useful information to interested parties for the problem. Kiosk rental application aims to facilitate managers or employees in conducting data processing. Kiosk rental applications that are made later will be web-based. The programming language used in making this kiosk rental information system is PHP and database programming using Mysql. This kiosk rental application provides financial statement information in the form of rental reports. This application can help the performance of managers and employees in processing agency data, increasing agency quality in kiosk rental transactions, producing fast and accurate information.
Digital Library Federation 2019 Capacity Presentation Script

Script notes for the presentation Adventures in determining a digitization lab's capacity at the 2019 Digital Library Federation Forum. UNT's Digital Projects Unit explores ways to determining their output capacity.