Reviewerly/exHarmony huggingface dataset:
A Knowledge Mining Algorithm for E-Courseware Based on Query Likelihood Model

With the rapid development of Internet, various forms of online learning platforms have emerged. As a major form of knowledge presentation, a number of electronic courseware (e-courseware) have been uploaded to these platforms for users to learn and share. Extracting main contents of an e-courseware document to form a knowledge framework is of great helpful for learners to select and utilize some courseware documents for their self-learning process. But at present, there are few studies concentrated on the information extraction for e-courseware. In this paper, a knowledge mining algorithm for e-courseware is proposed to facilitate learners quickly grasp main knowledge points of the courseware. In order to effectively organize the knowledge framework, this algorithm firstly uses the IRAKE algorithm to get some key phrases in each page of the e-courseware, and then uses the MMS process to filter the phrases with similar meanings, finally uses the query likelihood model to retrieve the sentences related to these key phrases in all the pages of the e-courseware document. The algorithm has good performance in mining the knowledge covered by the e-courseware.
Mathematical physics with partial differential equations by James Kirkwood, pp. 478, £61.99 (paper), ISBN 978-0-12814-759-7, Academic Press (2018).

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
(1909-5496) Topological structures induced by L-fuzzifying approximation operators

This paper further studies topological structures induced by L-fuzzifying approximation operators, where Ldenotes a completely distributive De Morgan algebra. Firstly, the Alexandrov topologies induced by L-fuzzy relations are investigated with respect to L-fuzzifying approximation operators. Especially, the relationships among those Alexandrov topologies are discussed. Secondly, pseudo-similarity sets of L-fuzzy relations are proposed based on the Alexandrov topologies induced by upper and lower L-fuzzifying approximation operators. Meanwhile, the properties of pseudo-similarity sets are discussed, where some examples are presented to show the differences between similarity set of fuzzy relations and pseudo-similarity set of L-fuzzy relations.
Fuzzy C-Means Algorithm for Clusterization of Credit Card Usage

Credit cards are now familiar to the public. A credit card is a means of payment in lieu of cash in the form of a card issued by the bank to facilitate transactions for customers. Currently, there are various kinds of credit card issuing financial service companies in the world, including Indonesia. With various benefits so that credit is loved by all groups, so that everyone competes to use credit by choosing the desired bank. Data mining methods can provide solutions to extract knowledge from data by looking for certain patterns or rules from large amounts of data. One of the data mining methods is clustering, in which clustering is used to group data by grouping the data into several clusters. By using the credit card data set is divided into 3 clusters using the Fuzzy C-Means algorithm. Of the 3 clusters, the ones that are prioritized with the largest value are the clusters that are widely used by many people, which have a medium value, while the cluster with the smallest value is the cluster with the least interest.
LibGuides: Economics and Management: Economics

A guide to assist library users to easily find library resources related to Economics and Business management
DI Library: Oral Communication (GE 170): Books and Ebooks

DI Library's guide to helpful books and links for Oral Communication students DI Library's recommended books and ebooks for Oral Communication
Cross-model Back-translated Distillation for Unsupervised Machine Translation

Recent unsupervised machine translation (UMT) systems usually employ three main principles: initialization, language modeling and iterative back-translation, though they may apply them differently. Crucially, iterative back-translation and denoising auto-encoding for language modeling provide data diversity to train the UMT systems. However, these diversification processes may have reached their limit. We introduce a novel component to the standard UMT framework called Cross-model Back-translated Distillation (CBD), that is aimed to induce another level of data diversification that existing principles lack. CBD is applicable to all previous UMT approaches. In our experiments, it boosts the performance of the standard UMT methods by 1.5-2.0 BLEU. In particular, in WMT'14 English-French, WMT'16 German-English and English-Romanian, CBD outperforms cross-lingual masked language model (XLM) by 2.3, 2.2 and 1.6 BLEU, respectively. It also yields 1.5-3.3 BLEU improvements in IWSLT English-French and English-German tasks. Through extensive experimental analyses, we show that CBD is effective because it embraces data diversity while other similar variants do not.
FORMATION OF STUDENTS ' LEADERSHIP SKILLS IN THE LEARNING PROCESS

In this article, the authors highlight the methods of formation and development of managerial skills and special qualities of students in the process of teaching self-knowledge, spiritual and creative self-improvement. Reveals contradictions between the need to develop student’s leadership skills and the lack of development of their leadership problems. Studying the leadership qualities of students, the authors give psychological and pedagogical recommendations, consider leadership as a responsibility for the development of students leadership qualities, are ready to create and organize their own projects, make decisions and make choices, as well as quickly and purposefully adapt students to the society. It takes into account the need to focus on the formation of personal outgoing qualities, as well as on the acquisition of new skills and approaches to pedagogical self-development.
Augmented Reality Application Development for Elementary School Purpose

The world is being hit by a pandemic due to the COVID-19 virus outbreak. The changes brought by this virus are huge, one of which is school activities that are transformed into online learning. Online learning causes students to not do their own classroom learning. This causes students to become un familiar with their school properly, such as the layout of classrooms and school facilities. By using Augmented Reality the problem can be solved. Augmented Reality (AR) is the merging of real and virtual objects in a real environment with interactive results and presented in real time. AR can be used to modeling the entire shape of the school, making it easier for users to get information about the building from the school instead of walking manually. Users only need to install the app on their smarthphone and scan the specified QR code in order to be able to bring up the building object along with the information. The result of this research is an AR application which can provide information about the rooms and buildings at SDN 1 Padangsambian.
Development and testing new content and forms of organization of pedagogical internship of future primary teachers

The purpose of the research: search for new forms of organization of pedagogical internships of future primary school teachers and proving their effectiveness. The research methods: analysis and synthesis; systematization of theoretical and empirical research results; experimental method, observation, discussion and testing; comparison and generalization. Results. The possibility of passing pedagogical internship by future primary school teachers in distance mode has been considered, which would promote the formation of basic competences of primary school teachers in the conditions of distance learning. Recommendations for the organization of pedagogical internship remotely according to the Web-model have been formed. Testing of the recommended organizational form of pedagogical internship for future primary school teachers has been carried out. It has been revealed that it is an effective method of practical training of students in modern conditions, forasmuch as it promotes better acquisition of pedagogical competences, namely: professional-pedagogical, information-digital; social-civic and linguistic-communicative.
SURVEI METODE PENGUKURAN APLIKASI CHATBOT BERBASIS MEDIA SOSIAL

The design of Chatbot aims to facilitate social activities in all areas to be considered. Chatbot is one type of machine that can communicate with humans using natural language. Communication happening via chat is a written conversation. Chatbot is a form of application implementation from Natural Language Processing (NLP) that belongs to one branch of artificial intelligence or Artificial Intelligent (AI). Social Media now provides a service that allows developers to process and integrate chatbot applications. This paper aims to review the papers that build chatbot applications in various social media using various testing methods. The contribution of this paper is to determine which method is able to measure the level of chatbot accuracy well. This review paper will choose the equation of the most widely used test methods and social media from various papers so that further research is expected to implement the right testing methods and use better social media in terms of user experience, features, and services. The review paper shows that the Black-box and System Usability Scale testing methods are most used in the review paper. This testing method is a type of method that performs testing of the flow and how the chatbot works to achieve functional validation throughly.
Mixed Cross Entropy Loss for Neural Machine Translation

In neural machine translation, cross entropy (CE) is the standard loss function in two training methods of auto-regressive models, i.e., teacher forcing and scheduled sampling. In this paper, we propose mixed cross entropy loss (mixed CE) as a substitute for CE in both training approaches. In teacher forcing, the model trained with CE regards the translation problem as a one-to-one mapping process, while in mixed CE this process can be relaxed to one-to-many. In scheduled sampling, we show that mixed CE has the potential to encourage the training and testing behaviours to be similar to each other, more effectively mitigating the exposure bias problem. We demonstrate the superiority of mixed CE over CE on several machine translation datasets, WMT'16 Ro-En, WMT'16 Ru-En, and WMT'14 En-De in both teacher forcing and scheduled sampling setups. Furthermore, in WMT'14 En-De, we also find mixed CE consistently outperforms CE on a multi-reference set as well as a challenging paraphrased reference set. We also found the model trained with mixed CE is able to provide a better probability distribution defined over the translation output space. Our code is available at https://github.com/haorannlp/mix.
LibGuides: Free Online Software: Browsers

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 internet browsers
Essays in Empirical Economics

This thesis is composed of two essays in Empirical Economics. The first chapter titled Studying more to vote less. Education and voter turnout in Italy is co-authored with Lorenzo Rocco. In this study, we use Italian municipality data on education and voter participation in national elections to estimate the effect of schooling on voter turnout. By adopting a fixed effect instrumental variable identification strategy, we find that education reduces voter turnout, more so in municipalities with higher income, lower social capital, which experienced political misconduct in the past and have low institutional quality. Analysis with individual data confirms these results. We discuss several mechanisms to rationalize our findings ranging from the opportunity cost of time to disaffection and civic protest.The chapter is single-authored, and is titled Dialects, human capital and labour market This paper investigates whether linguistic similarity to Standard Italian affects educational attainment and labor market outcomes, by exploiting unique micro linguistic data on dialects spoken at the beginning of the 20th century in 338 Italian municipalities. Adopting the view that, historically, dialects were the native language of the population and Standard Italian a second language, I advance the idea that historical dialects influence contemporary outcomes. Reduced form estimates, exploiting within province variation, show that linguistic similarity to Standard Italian is positively associated with present day educational outcomes and incidence of occupations intensive in language skills.
PERANCANGAN SISTEM INFORMASI PERPUSTAKAAN PADA BALAI TAMAN NASIONAL KEPULAUAN SERIBU

Library is a source of information that is accessible for most people. With the rapid development of the existing technology, it is possible for each individual to create such an innovation or ideas that can simplify their work daily. By utilizing available websites with internet access, the making of digital library systems is one efficient solution for their organization’s publication tools.Balai Taman Nasional Kepulauan Seribu is one of governmental institutions that still use library in conventional way in managing their data and publication of their collection, therefore in this study the author aims to design a website-based library information system that facilitates the management of books data and research publication and library information systems publication tools so that information can be more accessible and could reach wider community.
Nilai Pendidikan Karakter pada Novel Chairul Tanjung si Anak Singkong dan Implementasinya dalam Pembelajaran Bahasa Indonesia di SMA

The background of writing this thesis is that, besides being used as reading material, a novel can also be used as a learning medium as a means of teaching the values of character education, the formulation of the problem in this study is what are the values of character education contained in Chairul's novel Tanjung Si Anak Cassava and how the relevance of the values of character education contained in the novel Chairul Tanjung Si Anak Cassava with subjects in high school. This research is a literature study by taking the object of the novel Chairul Tanjung Si Anak Cassava. The approach used is a descriptive method. Data collection uses the documentation method. Data analysis uses content analysis. In this study, researchers will reveal the values of novel character education and then will interpret its relevance to the subjects of Indonesian language and literature in high school. The research results show that there is a message of character education in the Chairul Tanjung Si Anak Cassava novel which includes religious, honest and work hard. There is relevance between the values of character education in the Chairul Tanjung Si Anak Cassava novel with the material and learning methods used in class XII high school learning that is about identifying novels.
ULD-NUIG at Social Media Mining for Health Applications (#SMM4H) Shared Task 2021

In this paper, we present the ULD-NUIG team's system, designed as part of Social Media Mining for Health Applications (#SMM4H) Shared Task 2021.We participate in two tasks out of eight, namely "Classification of tweets self-reporting potential cases of COVID-19" (Task 5) and "Classification of COVID19 tweets containing symptoms" (Task 6).The team conduct a series of experiments to explore the challenges of both the tasks.We used a multilingual pre-trained BERT model for Task 5 and Generative Morphemes with Attention (GenMA) model for Task 6.In the experiments, we find that, GenMA, developed for Task 6, gives better results on both validation and test data-set.The submitted systems achieve F-1 score 0.53 for Task 5 and 0.84 for Task 6 on test data-set.
Effectiveness of Organizing Students’ Self – Education with the Facilities of Media Resources in Educational Media Environment

New information communication technologies and digital media are changing our world and the way we learn. Therefore, the introduction of ICT in the professional activities of teachers in our time is inevitable. Information technologies open up new opportunities for improving the educational process, activate the cognitive activity of students and allow organizing the independent and joint work of students and teachers at a higher - creative level. With countless educational resources, ICT can help improve teaching and learning process. Teachers can use various of educational digital resources, among them, media resources contribute to increasing student engagement thus improving traditional teaching methods. The increasing use of ICT and digital technologies is stimulates a growing demand for new professional competencies. New requirements are being put forward for the professional competence of teachers in the context of the digitalization of the education system. In this context, it is about ICT, digital and media competencies of future teachers. This article reveals the methods for the development of these competencies through the organization of self-education of students in educational media environment. In educational media environment, which is offered by us, media resources introduced as open educational digital resources for self-learning modular short courses under the subject "Information Technologies in Education". The study showed that, media resources serve to enrich the educational process with visual materials and to increase the efficiency of student self-learning.
DAMPAK STRATEGI KAMPANYE SOSIAL MINAT BACA DI KOTA MAKASSAR

This research presents the impact of the social campaign strategy for reading interest in the city of Makassar. This research uses descriptive quantitative research methods with frequency distribution data analysis, the concept used is the campaign strategy and indicators of students' reading interest. The results showed that based on quantitative data, 71% agreed if they cared about information obtained about reading interest or anything related to reading, and also 59% of them strongly agreed that they got new knowledge and information after reading.
Boosting Deep Open World Recognition by Clustering

While convolutional neural networks have brought significant advances in robot vision, their ability is often limited to closed world scenarios, where the number of semantic concepts to be recognized is determined by the available training set. Since it is practically impossible to capture all possible semantic concepts present in the real world in a single training set, we need to break the closed world assumption, equipping our robot with the capability to act in an open world. To provide such ability, a robot vision system should be able to (i) identify whether an instance does not belong to the set of known categories (i.e. open set recognition), and (ii) extend its knowledge to learn new classes over time (i.e. incremental learning). In this work, we show how we can boost the performance of deep open world recognition algorithms by means of a new loss formulation enforcing a global to local clustering of class-specific features. In particular, a first loss term, i.e. global clustering, forces the network to map samples closer to the class centroid they belong to while the second one, local clustering, shapes the representation space in such a way that samples of the same class get closer in the representation space while pushing away neighbours belonging to other classes. Moreover, we propose a strategy to learn class-specific rejection thresholds, instead of heuristically estimating a single global threshold, as in previous works. Experiments on RGB-D Object and Core50 datasets show the effectiveness of our approach.
Transaction Fraud Detection (Anomaly detection) using Machine Learning

Now a day’s online shopping crazy thing for peoples. As well as many people uses Online transaction for many purposes. Transaction fraud is growing seriously. Therefore, the study on fraud detection is interesting and significant and we can say necessary. An important way of detecting fraud is to extract the behavior profiles (BPs) of users based on their historical transaction records, and then to verify if an incoming transaction is a fraud or not in view of Their BPs. Also we apply SVM, Adaboost, and Neural Network machine learning algorithm to see which one is giving the best result.
Desarrollo educativo y ciudadanía: universitarios y lectura en Santa Cruz de la Sierra, Bolivia

This article is the result of two years of research on reading among university students in Santa Cruz de la Sierra, Bolivia. The research that led us to produce the 2018 Study on the reading habits of university students in the city of Santa Cruz de la Sierra was developed in the context of reflections on the educational development of Santa Cruz de la Sierra, with the purpose of objectively and extensively exploring the higher education reading practices of students and generating a base of valid and pertinent information to enable competent educational institutions and people interested in the subject (teachers and university authorities, school teachers, librarians, cultural managers, publishers, booksellers, among others) to design relevant proposals, in order to disseminate and stimulate this basic competence for cognitive, academic and social development among the youth of our city.
Urgency Using The RUP Method in Developing Information System Disdukcpil Services, Subang District

The information system is defined as the process of delivering messages to one another, Disdukcapil of Subang district has problems in delivering messages, this study sees the urgency of development This research uses the RUP (Rational Unified Process) development method used when identifying a running system and describing the design. the system to be built with the aim of getting a system that is right for BPSB. The development analysis uses the RUP (Rational Unified Process) method as a tool in order to model the required business processes (business modeling) and define the system requirements to be created. In addition, this study uses the UML (Unified Modeling Language) tool. This study uses a case study as a method for data collection and retrieval where the research process begins by identifying a case to find a solution in the form of system development. Based on the results of the analysis, the running system still uses conventional methods, which results in the process of delivering information to consumers not optimal. Therefore, it is urgent to use the RUP method at Disdukcapil to make it easier for the public to control reports, KTP status and to be able to display data so that information delivery can run optimally. which resulted in the process of delivering information to consumers not optimal. Therefore, it is urgent to use the RUP method at Disdukcapil to make it easier for the public to control reports, KTP status and to be able to display data so that information delivery can run optimally. which resulted in the process of delivering information to consumers not optimal. Therefore, it is urgent to use the RUP method at Disdukcapil to make it easier for the public to control reports, KTP status and to be able to display data so that information delivery can run optimally.
Research Guides: Off Campus and Remote Access: Home

This guide provides information about EZproxy authentication to access the library's subscribes resources from off-campus.