Reviewerly/exHarmony huggingface dataset:
Algorithm Optimization for Cold Start of Collaborative Filtering System

Abstract With the development of network technology, the amount of information on the network has grown and expanded rapidly with an exponential law, and its information organization is heterogeneous, diverse, and distributed. With the vigorous development of Internet information services, the scale of its information resources has also exploded. For ordinary users, the problems of “information trek” and “information overload” on the Internet are becoming increasingly serious. In order to solve the problem of information overload, recommendation system has become an indispensable tool for today’s e-commerce platform, which can help users find valuable information quickly. Collaborative filtering-based recommendation algorithms have been widely applied and studied in recommendation systems. Although the collaborative filtering algorithm has been widely used, there are still problems such as data sparsity, scalability, and cold start, which seriously limit the quality of recommendations. Therefore, collaborative filtering algorithms face many challenges. Especially recommendation systems using collaborative filtering technology. This article discusses the cold start system, the cold start user, and the cold start scenario. Effective use of project content information and user personal information is one of the effective methods to solve the cold start problem, that is, a hybrid recommendation technology combining information filtering and collaborative filtering. This paper proposes a hybrid recommendation technology that can better solve the cold start problem.
Curriculum development based on the graph model

The article discusses the approach to planning interrelated work within a given number of time periods using the example of the formation of a curriculum of a higher educational institution based on the competence model of students. It is proposed to consider the task of forming a curriculum as an optimization task of cutting-packing, solved with the help of an ordered graph. A logical model of the curriculum is developed in the form of an N-layer ordered graph in which the vertices correspond to the disciplines of the curriculum, and the arcs specify the relations of the preceding of disciplines in semesters, the temporal preceding (following) of disciplines is set using the discipline following matrix. As a criterion for the optimality of the curriculum, the criterion of the uniformity of the study load and the criterion of minimum fines, which reflects the degree of compliance with the given causal relationships between the disciplines of the plan, are considered. The UML diagram of the components of the software package for the formation of curricula is developed, the functions of the developed software package are described. The software implementation of the developed models and algorithms is completed. An experiment was conducted, various curriculum options were obtained and analyzed. Their optimality was estimated based on the proposed criteria, the characteristics of the constructed curriculum options are given, recommendations are given for choosing the final curriculum version, taking into account the established priorities
Cooking with ORCID: Understanding and Sharing ORCID Connections

Cooking with ORCID: Understanding and Sharing ORCID Connections was presented by Eric Olson, Brian Minihan, and Tom Demeranville at the ORCID ConsortiaWorkshop on May 20, 2019.
Non-intrusive Calibration for User Interaction based Gaze Estimation

In this paper, we describe a new method for acquiring calibration data using a user interaction process, which occurs continuously during web browsing in gaze estimation, and for performing calibration naturally while estimating the user's gaze.The proposed non-intrusive calibration is a tuning process over the pre-trained gaze estimation model to adapt to a new user using the obtained data.To achieve this, a generalized CNN model for estimating gaze is trained, then the non-intrusive calibration is employed to adapt quickly to new users through online learning.In experiments, the gaze estimation model is calibrated with a combination of various user interactions to compare the performance, and improved accuracy is achieved compared to existing methods.
ระบบบริหารงานสารสนเทศที่สัมพันธ์กับลักษณะองค์กรแห่งการเรียนรู้ ของสถานศึกษาสังกัดสำนักงานเขตพื้นที่การศึกษาประถมศึกษาราชบุรี เขต 2

The objectives of this research were to: 1) study the information management system of schools in Ratchaburi Primary Educational Service Area Office 2 as well as the characteristics of a learning organisation; 2) compare information management system and learning organisation characteristics in different sizes of schools operating under Ratchaburi Primary Educational Service Area Office 2; and 3) study the relationship between information management system and learning organisation characteristics of those schools. Sample used in research were 107 out of 148 schools operating under Ratchaburi Primary Educational Service Area Office 2. The sample size was selected based on krejcie & Morgan table at a 95 percent confidence level. Afterwards, stratified Random Sampling was used to determine the samples of which 48 small schools, 56 medium-size schools, and 3 large schools were selected. Data collection implemented using a 5 scale rating questionnaire with a reliability of .963. The analysis was developed via the use of frequency, percentage, mean, standard deviation, one-way ANOVA, and Pearson’s correlation coefficient.The results found:1) The information management system and learning organization characteristics were both found at a high level on the overall.2) Different school sizes do not incur differences in information management system or learning organization characteristics; and3) There is a positive relationship between information management system and learning organization characteristic at a statistical significance of .01
Different Norths – Visions of Scandinavia in Contemporary Italian Literature

The texts in this book are based on a selection of the paper presentations and Keynote lectures held during the Centre for Scandinavian Studies Copenhagen – Lund’s (CSS) second biannual international conference in the field of Scandinavian Studies.&nbsp; The conference took place in Lund, at the joint Faculties of Humanities and Theology of Lund University between May 16-18, 2019.&nbsp; This year’s theme was “Scandinavian Languages and Literatures Worldwide – Prospects and Challenges” and the central topics being researched and discussed were: Scandinavian Literature in the World Translations of Scandinavian Literature Scandinavian Children’s Literature in the World Linguistic and literary constructions of the North The Framing of Scandinavian Studies Worldwide Nordic Languages in the World / World Languages in the Nordic Countries The conference had three Keynote lectures: Språk och psykologiskt lokalsinne, by Sigrid Combüchen (Author and former Senior Lecturer at the Centre for Languages and Literature, Lund University) [see below] Region. Verden. Arkipelag – Nordisk litteratur og Tomas Tranströmers “Östersjöar”, by Dan Ringgaard (Professor at the School of Communication and Culture - Scandinavian Studies, Aarhus University) [see below] Beyond Noma, Björk and Bergman – How the Nordic Countries could increase their Soft Power, by Francisco Beltran (Senior Lecturer at the Department of Political Science, University of Toronto)&nbsp; Following long established international praxis in the field of Scandinavian Studies the texts are written in any of the Nordic languages or in English.
Pursuance of DWIRS Framework for Deep Web Exploration with Indexing and Ranking

We designed and developed a novel framework DWIRS for Deep Exploration with indexing and ranking. The purpose of DWIRS framework is to explore high quality contents from the quantitative Deep Web, with least possible effort, in the least possible time, irrespective of architectural dependencies and operating system related issues. It is imperative to perform indexing and ranking is the nucleus of the exploration process. The design of the proposed framework is carried out in three phases: Indexing, Standard Search and Ranking Search. In phase 1, the acquired Deep Web data is pre-processed through Tokenization, Stop Word Removal and Stemming. Then, indexing is performed for the Deep Web data. The exploration process is carried out based on the search keyword provided by the user. Cosine similarity measure is used in standard search. The search results are re-ranked by using BRF algorithm. The performance of DWIRS framework has been evaluated by developing a customized application on the collected Deep Web data sets. By comparing the results of standard search with that of ranking search, it is shown that retrieval effectiveness as well as the quality of search results has been improvised. Our experimental results revealed that the proposed framework works effectually.
Sistem Deteksi Lubang pada Pedesterian dengan Teknik Pengolahan Citra

Pothole Detection System on Pedesterian using Image Processing Techniques. The pedestrian areas in Indonesia are still far from optimal in facilitating the users or the pedestrians. Potholed pedestrian areas are found in many parts of the street. This issue can harm pedestrians, especially blind people. For this reason, research has been carried out to create a system that can detect and estimate hole distances by processing images using mono cameras that can help blind people. The methods used to detect holes are the Threshold + Blob Analysis method and the HSV method. The obtained results indicate the level of accuracy of hole detection using the Threshold + Blob Analysis method is better than the HSV method. The average accuracy level of Threshold + Blob Analysis is 88.91%, while for the HSV method is 86.82%.
Library Research Guides: Smart Cookies Start at IU Libraries!: IUCAT

Welcome new and incoming students! Learn about the IU Libraries and all that we can do to help you during your time as a student at IUB. Learning how to navigate through IU's catalog
INTEGRATED LICENSING INFORMATION SYSTEM (SIJITU) APPLICATION IN LICENSING SERVICE (A Study at Department of Capital Investment and One-Stop Integrated Services in Ponorogo District)

SIJITU (Integrated Licensing Information System) is an application developed by Department of Capital Investment and One-Stop Integrated Services (DPMPTSP) in Ponorogo District in order to provide effective, efficient, and transparent service in Non-Business Licensing Service. The reason behind SIJITU application is the rise of management information system so it can be utilized in the process of licensing service implementation at DPMPTSP in Ponorogo District. This research aims to identify, analyze, and describe SIJITU implementation in Non-Business Licensing Service at DPMPTSP in Ponorogo District that includes implementation strategy, resources involved, procedure and mechanism, and service improvement through SIJITU. This research is a descriptive research with qualitative approach. The method of data analysis used is data analysis of Miles, Huberman, and Saldana’s interactive model that involves data collection, data condensation, data presentation, and conclusion verification or description. The result of the research is that SIJITU application certainly helps the performance of public service in non-business license field that is held by DPMPTSP in Ponorogo District. Through SIJITU application, the service process can be done transparently with the tracking feature. DPMPTSP in Ponorogo District also tries to increase the officers’ ability through formal and non-formal education, and conducts socialization to the society regarding SIJITU application. Services procedure and mechanism through SIJITU can be known in details on the Standard Operating Procedure (SOP) of Licensing Service at DPMPTSP in Ponorogo District
Ideas for Digital #literacies lessons #edu407

Make a PodcastHere is my 2toPonder series and my son's podcast series. Want to make a podcast, just record on your phone or laptop and
Research Guides: TCC Libraries Material Pick-up: Pick-up Procedures

Instructions for checking out items from TCC Libraries including requesting an item, cancelling a request, and material pick-up instructions. Instructions for library material pick-up at each TCC campus library,
Information Theoretic Sample Complexity Lower Bound for Feed-Forward Fully-Connected Deep Networks.

In this paper, we study the sample complexity lower bound of a $d$-layer feed-forward, fully-connected neural network for binary classification, using information-theoretic tools. Specifically, we propose a backward data generating process, where the input is generated based on the binary output, and the network is parametrized by weight parameters for the hidden layers. The sample complexity lower bound is of order $\Omega(\log(r) + p / (r d))$, where $p$ is the dimension of the input, $r$ is the rank of the weight matrices, and $d$ is the number of hidden layers. To the best of our knowledge, our result is the first information theoretic sample complexity lower bound.
Security Risk Management Plan. Student Portal - Case Study

A student portal is a regularly utilized expression to describe the login page where students can give a username and password to access an instruction association's projects and other learning related materials. For instance, a student who has taken a crack at an online program may utilize a university portal to get to online course materials, for example, articles, lectures and recordings, facilitated on the school's data bases. university portal might be utilized to give data about the school, unique activities and events, course information, schedules, scholarly resources and contact data.
On Lightweight 4x4 MDS Matrices over Binary Field Extensions

Maximum Distance Separable (MDS) matrices are used as the main part of diffusion layers in block ciphers and hash functions. MDS matrices derived from MDS codes have the maximum differential and linear branch number, which provide resistance against some well-known attacks like differential and linear cryptanalysis together with the use of a nonlinear layer (e.g. S-boxes) in a round function of a block cipher. In this paper, we introduce generic methods to generate lightweight $k \times k$ involutory/non-involutory MDS matrices over $\F_{2^m}$ and present the lightest involutory/non-involutory $4 \times 4$ MDS matrices over $\F_{2^4}$ (to the best of our knowledge) by considering XOR count metric, which is defined to estimate hardware implementation cost. Also, the results are obtained by using a global optimization technique, namely Boyar-Peralta algorithm.
Further training of teachers as a condition for improving the quality of education

The concept of advanced training is considered in the article, and the issue of advanced training of teachers is also considered. The essence of the modernization of the contents of the courses of advanced training and retraining of personnel in the system of higher education is disclosed. The article describes the conditions of a socially-oriented economy of modern policy and strategy of the state in the development of the national education system. As well as the compendium for the development of the higher education system is given.
QoS-aware flow scheduling for energy-efficient cloud data centre network

It is highly valuable to achieve energy-efficient cloud data centres, which always act as the basic infrastructures. This paper thus aims at reducing the energy consumption of network devices in cloud data centres by flexible flow scheduling. For such an aim, it is necessary to guarantee the flow-level performance, which is a critical requirement for quality of service (QoS) in production data centres. Hence, this paper takes both energy reduction and QoS into account for flow scheduling, and then proposes a three-phase framework to control the energy consumption for cloud data centre network (DCN) while guaranteeing flow-level performance. The core idea is to turn off the unnecessary switches off. From extensive simulations, it is shown that our solution could not only reduce about 20% of energy on average than the case with all switches on, but also maintain good flow-level performance, stability and fault tolerance simultaneously.
Open PDF File: What is PDF and How to Open it

Open PDF File. What is PDF and How to Open it? Learn important information about how to open PDF file as well as other useful stuff in this guide. ...
Investigating EFL Saudi Students’ Vocabulary Improvement in Micro-blogging on Twitter at Imam University

This paper reflects the reality of today’s education and how it is governed by a digital native generation. Technology has become a crucial factor in people’s social and educational lives. In nearly every educational area, social networks are being used. This paper claims that the social networking sites of teaching English as a FL improve learners’ English language skills, as they become authors and readers. This study investigates how a particular social networking tool, which was Twitter, that could be used in improving foreign language vocabulary skills. The purpose of the study was to determine EFL Saudi female students’ improvements in vocabulary acquisition as well as their attitudes and motivation towards tweeting and reading others’ tweets. Further, this paper suggests including Twitter into language teaching because it is crucial to use technology in our courses in order to improve FL teaching methods. n
Teachers' Questions On Online Classes

Sari, Hani Puspita. 2020.Teacher Question On Online Classes. A Graduating Paper, English Education Department,Teacher Training, and Education Faculty, State Institute for Islamic Studies Salatiga. Counselor: Hanung Triyoko, S.S., M.Hum., M.Ed.Keywords: Teacher Question, Online Class, Qualitative Research The research is about analyzing teachers’ questionof State Institute for Islamic Studies (IAIN) of Salatiga on online classess. The objectives of this research are (1) to know the types of question asked by the teachers on online classand (2) to find out the reason why the teachers use the common question. The method of the research was Qualitative Research with descriptive qualitative method, there are observation, interview, coding, classifying, analyzing, and concluding.The result of the research shows thatthe types of questions most frequently used are short answer question. The teachers used as many 22 times,the most number, which is 34%. with a total percentage of 100%.Then yes / no question 21 times, 32%, questioning 10 times, 15%, clarify question 5 times, 8%, open-ended question 4 times, 6%, pre-plan question 2 times, 3%, and finally quizzing 1 times, as much as 2%. Soit can be drawn the results of the questions most often used in online classes are short answer questions with a percentage of 34% of 100% compared to other types of questions.The data shows that the reason why the teacher used mostly the chosen question is to make sure that the students’ understanding of the material and get what the point of the material also to confirm the students’ understanding.
Libraries: Creative Commons and Public Domain: Creative Commons

This guide explains how to find free images, videos, and sound files for your class projects and how to give proper attribution to the creator.
Insight into sentimental analysis

Sentiment analysis (also known as opinion mining ) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. It’s estimated that 80% of the world’s data is unstructured, in other words it’s unorganized. Huge volumes of text data (emails, support tickets, chats, social media conversations, surveys, articles, documents, etc), is created every day but it’s hard to analyze, understand, and sort through, not to mention time-consuming and expensive. Sentiment analysis, however, helps businesses make sense of all this unstructured text by automatically tagging it.
사하라이남 아프리카의 모바일 폰 혁명

Is the mobile phone bringing so much changes in Africa so that we can talk about a revolution ? The purpose of this article is to reply to this question. With this aim, we have analysed reasons why in Africa mobile subscriptions are significantly higher than fixed lines and we have also tried to find out what place the mobile phone takes in the society of Africans. In particular, we have examined why mobile money has grown so much that we call Africa ‘the global leader of mobile money’ and find out what changes have occurred in the lives of Africans with the penetration of mobile phones. We have also reported its political and social impact.What is obvious is that the mobile revolution has become a driver of economic growth and development in Africa through job creation, small business creation, distance learning and healthcare, as well as online financial services. More than that, the mobile phone revolution presents various social innovations and new business models.
Combating Domain Shift with Self-Taught Labeling.

We present a novel method to combat domain shift when adapting classification models trained on one domain to other new domains with few or no target labels. In the existing literature, a prevailing solution paradigm is to learn domain-invariant feature representations so that a classifier learned on the source features generalizes well to the target features. However, such a classifier is inevitably biased to the source domain by overlooking the structure of the target data. Instead, we propose Self-Taught Labeling (SeTL), a new regularization approach that finds an auxiliary target-specific classifier for unlabeled data. During adaptation, this classifier is able to teach the target domain itself by providing \emph{unbiased accurate} pseudo labels. In particular, for each target data, we employ the memory bank to store the feature along with its soft label from the domain-shared classifier. Then we develop a non-parametric neighborhood aggregation strategy to generate new pseudo labels as well as confidence weights for unlabeled data. Though simply using the standard classification objective, SeTL significantly outperforms existing domain alignment techniques on a large variety of domain adaptation benchmarks. We expect that SeTL can provide a new perspective of addressing domain shift and inspire future research of domain adaptation and transfer learning.
Cognitive analysis and the problem of modeling constructs

The article deals with the problem of modelling adequate constructs.The mentioned problem is related to the problem of appropriate methodology selection for the modeling an adequate construct.The methodology should ensure identification of the relationships within the construct, revealing the stable relations between the constants and variables.Practical implementation of interdisciplinary and polyparadigmatic methodology is considered as a real possibility for using cognitive analysis and modeling technologies.