Reviewerly/exHarmony huggingface dataset:
Evaluation and Comparison of Temperature-Based Models for The Prediction of The Monthly Average of Daily Global Solar Radiation for Baghdad City- Iraq

The solar energy is the major source of power for the future and an important source of renewable energy in Iraq and the world. Suitable climate conditions for solar energy are available in Iraq, especially the high temperature in the summer season which extends for more than six months in the year. Hence, the global solar radiation is abundant with high intensity, which is very essential in applicable models for researchers and solar applications. Therefore, nine first-order regression empirical equations of Angstrom-type correlations were used to estimate the more appropriate global solar radiation model for Baghdad city. Two equations were developed empirically in this work, using the most available and easy to get meteorological data, which is the temperature value in various forms. The results of the comparison between the real and calculated values showed reasonable agreement for most equations (including the development of R2- at 99%) as well as the least values of types of errors RMSE and MBE. As an exception, two equations of models failed in this study because of inability to apply to such climate conditions of Baghdad city.
Research Guides: Copyright Considerations for the Harvard Community in Shifting Courses from In-Person to Online During the COVID-19 Crisis: Home

By the Copyright First Responders, Harvard Library Office for Scholarly Communication (This document is evolving and subject to change. Last updated March 25, 2020.)
Audit Informasi pada Sistem Informasi Perpustakaan ITS Surabaya (SPITS): Studi Kasus Bagian Pengolahan dan Layanan di Perpustakaan ITS Surabaya

This study discusses the audit information in the information system of the library ITS Surabaya (SPITS). The purpose of this research is to inventory the needs and use of information on the management and the users of the library in the activities collection and processing services in hopes of providing inputs (recommended) in the the development of an integrated information system in the library of ITS Surabaya. Data collected by observation, documentation, interviews and questionnaires. Data research results were analyzed with descriptive qualitative approach through several stages of the model audit information Susan Henczel which is one of the methodology of the audit the information by applying the stages of planning, data gathering, analysis data, and the evaluation of the data.  From the results of the research note that the implementation of the automated information system based SPITS used nowadays are still having some problems, which is still not providing some of the information that is required on either the management or users of the library. For it to do the audit information so that it can serve as inputs or recommendations in the plan of development of the software SPITS (the ITS Library information system) integrated
High Efficient Secure Data Deduplication Method for Cloud Computing

Deduplication technology helps reduce the overhead of cloud storage services, which clearly benefits the development of the increasingly big-data-driven society. However, data stored in the cloud is usually in an encrypted form since users request high levels of data security and privacy. Thus, data encryption brings new challenges to deduplication in cloud computing, making deduplication for encrypted data more challenging. Because conventional deduplication solutions cannot handle encrypted data, and there are various problems with existing deduplication schemes, this paper proposes an improved scheme based on ownership challenge and proxy re-encryption to enhance its security performance and attain an efficient and secure deduplication. A theoretical analysis and computer simulation is performed to evaluate its performance. The performance analysis shows that the scheme is efficient and has good attack resistance in the big data deduplication for cloud computing.
PERANCANGAN MEDIA INTERAKTIF LOGIKA PEMOGRAMAN UNTUK MENARIK MINAT BELAJAR SISWA PADA SMK NEGERI 1 MESJID RAYA

This study aimed to design interactive learning media of Programming Logic using Adobe Flash CS6 applications, and determined the effect of student interest in those media. This research was conducted at SMK Negeri 1 Mesjid Raya which students of multimedia class X as the sample. The method of this study was the research and development area. There were several stages carried out for the research process, which started from the concept, design, material collection, process, testing and distribution. The technique of data collection used a questionnaire. This media application has been tested and validated by the experts of multimedia. The results of this study was the coefficients test obtained 2 variables that affect interest, namely the media and material. The effect of attracting students' learning interest using this media gets 52.7% results. Threfore, it can be concluded that interactive media programming logic can influence to attract students' learning interest.
LibGuides: Topics in Business, Industry, and Marketing Research: About

Recommended resources for business, industry, and marketing research by RCAD faculty and librarians.
Web and Browser Security

We now aim to develop an awareness of what can go wrong on the web, through browserserver interactions as web resources are transferred and displayed to users. When a browser visits a web site, the browser is sent a page (HTML document). The browser renders the document by first assembling the specified pieces and executing embedded executable content (if any), perhaps being redirected to other sites.
Online Training for Franchises through a Learning Management System

It is well known that, for every company, the resource time is a factor of impact on its productivity. At present, the technical support area has taken a relevant place in companies, this is caused by the demand for learning and recovery of activities of employees, a client or managers. The training of a new staff in a company implies investment of the time of one or more people to know various processes and procedures, therefore, it is very important to support training courses in Learning Management Systems (LMS for their acronym in English), which are increasingly demanding due to their availability of resources, flexibility of topics and compliance with a required scope. The work shows the reciprocal influence between two development methodologies of a training course within an e-learning system for residents in the area of ​​technical support, using tools to create didactic content, embedded code, the results determine that the good use of This material has allowed staff to involve less or no amount of time to train a new employee. The success of the tool has challenged the development of training for other areas.
A Collaborative-Filtering Recommendation Based on the Trust Network

Many recommendation algorithms are proposed for the internet business system. However, many researches are focus on the model of users, items and their relation-ships. Recently, some studies proposed to use the trust relationships among users to optimize the accuracy of recommendation. But many studies recently did not consider the indirect trust relation between users. In our manuscript, we proposed an hybrid approach to mine the indirect and direct trust relation between any two users in the data set. Based on experiments used the real world public data set, our algorithm outperforms the other state-of-the-art approaches recently in the accuracy.
LEKSIKOGRAFIK GEOMETRİK PROGRAMLAMA (LGP)

The paper presents the Kuhn-Tucker conditions and duality theory for the lexicographic minimization problem: iex m in{F (x)|x e R n,G (x ) < O mj where F and G are vector valued functions form R„ -~*RS and Rn —>Rm , respectively. The lexicographic duality is then applied for problems with polynomials in the objectives and in the constraints.
DIGITAL LITERACY STRATEGY IN THE INDUSTRIAL REVOLUTION ERA 4.0

Digital literacy development can be done in the realm of schools, families, and communities. With digital literacy in schools, students, teachers, education personnel, and school principals are expected to have the ability to access, understand, and use digital media, communication tools, and networks. In family digital literacy, parents are the frontline in the digital literacy process in the family domain. Father and mother are the first and foremost educators. Community digital literacy can be developed through study groups, youth clubs, hobby communities, and community organizations. Digital literacy learning must also involve an understanding of universal values that must be obeyed by each user, such as freedom of expression, privacy, cultural diversity, intellectual rights, copyrights, and so on. Digital literacy enables a person to interact well and positively with his environment. Thus, digital literacy needs to be developed in families, schools, and communities as part of lifelong learning. Keyword: digital literacy, industrial revolution 4.0
PENERAPAN ADABOOST UNTUK MENINGKATKAN AKURASI NAIVE BAYES PADA PREDIKSI PENDAPATAN PENJUALAN FILM

For economists and financial experts predicting the success of doing business is very interesting. With the data analytics the prediction process has been facilitated by the past data stored to find out what will happen in the future. This research was conducted to facilitate the film industry players in considering the factors that can influence the income of the film to be produced. The naive bayes method is a popular machine learning technique for classification because it is very simple, efficient, and has good performance on many domains. But naive bayes has a disadvantage that is very sensitive to too many features, thus making the accuracy to be low, in this case the adaboost method to reduce bias so that it can and improve accuracy from naive bayes. Validation is done by using 10 fold cross validation while measuring accuracy using confusion matrix and kappa. The results showed an increase in the accuracy of Naive Bayes from 83.22% to 84.44% and the kappa value from 0.706 to 0.731. So that it can be concluded that the application of adaboost on 2014 &amp; 2015 CSM film data is able to improve the accuracy of the Naive Bayes algorithm
Assessment of Knowledge of Student Nurses regarding Use of Simulation: A Modern Learning Approach in Nursing

Introduction: The use of simulation as teaching methodology is becoming increasingly prevalent in healthcare practice and there is an increased and widespread use of simulation as a learning approach. Objective: The present study is aimed at assessing the knowledge of student nurses’ regarding the use of simulation as a learning approach. Materials and Methods: Descriptive research design was used to assess the knowledge of 34 student nurses selected using convenient sampling technique, studying in Rufaida College of Nursing, Jamia Hamdard. A structured questionnaire was developed to assess the knowledge of student nurses regarding simulation and data was analyzed using descriptive statistics. Result: The study findings revealed only 8.82% of student nurses were having above average knowledge regarding simulation, majority (52.94%) of them were having average knowledge and 38.23% were having below average knowledge regarding simulation as a learning approach. Conclusion: Student nurses are future health care workers and need to understand about the importance of simulation as a modern learning approach. There is an absolute dearth of implementing novice educational tools and total dependence of traditional teaching methodology, which is to some extent reducing the learning capacity of the current generation as it is non-aligned with the rapidly progressing technology. Teachers need to embrace newer educational tools to ensure improvement in knowledge retention and skill building of student nurses, thereby ensuring patient safety. How to cite this article:James MM, Rahman J. Assessment of Knowledge of Student Nurses regarding Use of Simulation: A Modern Learning Approach in Nursing. Int J Nurs Midwif Res 2019; 6(4): 34-38. DOI: https://doi.org/10.24321/2455.9318.201930
Logan Library: New Temporary Databases: Home

This page provides links to new temporary databases being offered for use during this time of online learning.
LibGuides: eBooks: Find eBooks

Finding and reading eBooks at University of South Wales An introduction to eBooks and how you can find them.
A Simple Anonymous GSS-API Mechanism

This document defines protocols, procedures and conventions for aGeneric Security Service Application Program Interface (GSS-API)security mechanism that provides key agreement without authenticationof either party.
LibGuides: Zoom: Zoom vs. Google Hangouts

This guide shows you how to use Zoom, with a focus on Zoom for classroom use by instructors.
Software design of intelligent interactive autonomous learning system

Aiming at the problems of poor quality of service, low performance of system cluster and low accuracy of parameter calculation in current software design method of autonomous learning system, a software design method of intelligent interactive autonomous learning system is proposed. Through system architecture design, system module design, system interaction design, system network design and system database design, the overall structure of interactive autonomous learning system software is constructed, and the project parameters and capability parameters are calculated by maximum likelihood method and expert estimation method. According to the user's own ability, personalised test questions and learning content are set for users, and the software design of autonomous learning system is realised. The experimental results show that the proposed method has high quality of service, good cluster performance and high accuracy of parameter calculation.
LibGuides: Online Research Using the WOU Library: Subject & Course Guides

This guide provides general information for students on how to use library resources remotely.
THE CRITIQUES AND IDEOLOGIES SHARED IN THE INAUGURATION SPEECH OF DONALD TRUMP (A STUDY OF CRITICAL DISCOURSE ANALYSIS)

&lt;em&gt;This paper investigates the Critical Discourse Analysis (CDA) in studying the inauguration speech of Donald Trump at the Capitol Hill, Washington DC on January 20, 2017. The objective of the study is to uncover the hidden messages regarding ideologies shared and critiques appointed to Obama’s presidency. The paper uses the theory of CDA by Norman Fairclough by focusing on the three aspects of research which are (1) micro or linguistic analysis, (2) Mezzo or discursive analysis, and (3) macro or contextual analysis. The three dimensional model of CDA is aimed to uncover the ideologies shared and critiques appointed to based on linguistic features, socio-political aspect, and discursive practice. The American Dream is represented in seven issues risen which are (1) US economic condition during Obama’s presidency, (2) US political condition during Obama’s presidency, (3) US social condition during Obama’s presidency, (4) The concept of making America great again, (5) Anti-radical Muslim immigrants, (6) America First, and (7) Nationalism. The result of the study reveals that the speech brought some ideologies or thoughts shared to the audiences and might change the people’s perception on Obama’s two periods of presidency who is considered as failure.&lt;/em&gt;
The Current Situation of Vocational Education for High School Students and Orientation in Developing Differentiated Teaching Based on The New National Curriculum

Differentiated teaching is a current trend that emphasizes the ideology of democratizing schools, contributing to the diversion of students. Differentiated teaching develops capacity, creates learners’ interests, and turns passions into learning motivation. Thereby, career orientation for students was formed. This study aims to understand some aspects related to vocational education for high school students in Vietnam and suggesting some directions for developing differentiated teaching based on the new national curriculum. Participants were 146 teachers, 33 managers, and 366 students at high schools in Vietnam. Findings revealed that vocational education at high schools had some limitations and was unable to support students in choosing career according to their interest, capacity, and personality. Difficulties shared by teachers and managers in vocational education were both due to subjective and objective reasons, including challenges of the educational system and related social problems. Based on our findings and the references from other countries, we suggest three different orientations in developing differentiated teaching based on particular subjects or credits.
DATA MEANING: ABORDĂRI METODOLOGICE MODERNE DE CERCETARE

In the article are presented some modern methodological research approaches of Meaning. Are introduced.some methodological aspects of the development of artificial intelligence systems. This article reviews the philosophical discourse  Can machines think? by Alan Turing. The purpose of the research was: (a) the development of an electronic course Data and (b) the application of the Meaning components in developing artificial intelligence products. The electronic course Data was developed at the Faculty of Economic Sciences, The State University of Moldova and implemented in the education process.
Solving the Problem of Acquiring Labour Resources for a Long-Term Period

The authors of the work set the task of acquiring and using for a long period a certain set of labour resources for the production of a given list of works in specified volumes at certain time intervals. The problem in its structure is a dynamic distributive problem. The aim of the work is to develop a mathematical model of a dynamic distributive problem. To solve this problem, a constraint decomposition scheme is used. After decomposition by constraints, the problem is considered as a piecewise smooth optimization problem. The method of non-smooth penalty functions is used to account for non-trivial constraints. Such an integrated approach to solving the problem is rational. The developed mathematical model can be used to calculate the distribution of labour resources for a long-term period in various sectors of the economy.
RETRACTED ARTICLE: Clustering Optimization Algorithm for Blockchain Systems Based on Big Data Analysis

The clustering optimization is the need of the hour for the blockchain systems where the distributed data are generated in large volumes and mining of data is mandatory for analyzing the data. The poor clustering may lead to increase in outliers, poor analysis of data and instability in data. It may also slow down the data processing phase if clustering is not performed in a controlled and systematic manner. Therefore, this has motivated us to perform this research study. The objective of the study is to design a clustering optimization algorithm for blockchain systems based on big data analytics. A large number of related variables in the blockchain system are transformed into a small set of uncorrelated variables to remove noise and redundancy. The complex data dimensionality reduction is also performed. On this basis, K-means clustering algorithm is used for comparison and also to randomly select a centroid and then our proposed algorithm is adopted to cluster the data generated by blockchain system after dimensionality reduction, and the initial clustering center is obtained to collect similar data. At the same time, the self-identification intersection is used. The weighted K-means clustering algorithm is used initially to calculate the cluster center and then the heuristic algorithm is used for clustering of aligned data which realizes the clustering optimization of the blockchain-based generated data. The proposed clustering optimization has good clustering effect, greater stability, and fast convergence speed and is not affected by outliers as per the results obtained.
Thwarting Cache Side Channel Attacks with Encryption Address-Based Set Balance Cache

The deterministic memory-to-cache mapping used by cache side channel attack causes the leakage of sensitive information such as secret keys, which seriously threatens user security and highlights the need to defend against this kind of attack. Recent table-based secure cache design requires more space to store the entry while a purely encryption-based design needs complex encryption units to ensure robustness. What is more, the newer attack algorithm enabling faster eviction set discovery may still break such defenses. Even though increasing the association of cache can be a potential solution, it introduces too much redundancy cache access and storage overhead. In this paper, we eliminate this problem. We present Encryption address-based Set Balance Cache (ESBC), a novel cache design to mitigate cache-based side channel attack. ESBC encrypts an address into two-level sets and displaces the data from a primary set into the secondary set when the primary set is full. The two-level mapping structure increases the complexity for attackers to build eviction sets, which is a vital step for the conflict-based attack. Furthermore, we adopt two different optimized variants from a temporal perspective, ESBC with remapping (ESBCR), which serves dynamic-remapping, and spatial perspective, ESBC with multi-mapping (ESBCM), which performs multi-mapping to improve the robustness. Our security analysis reveals that these designs can confuse the exploitation of conflicting addresses. Simulation-based evaluation on SPEC2017 shows 0.24% instruction per cycle (IPC) degradation for ESBCR with 1% remap rate. While the reduction of ESBCM that has five potential secondary sets is 0.69%. What is exciting is that both miss per kilo instructions (MPKI) and miss rates are even reduced because of the efficient cache usage. The storage overhead of these two variants is only 0.87%. By comparing the two schemes, we can observe that though ESBCR brings less performance overhead, the ESBCM has better scalability.
Pemanfaatan Data Mining Dalam Memprediksi Kasus Positif Covid-19 Di Kota Palembang Menggunakan Algoritma K-Nearest Neighbors

Covid-19 was first detected in Indonesia in early March 2020. The province of South Sumatra has more than 20,000 confirmed cases of Covid-19, 15,914 from Palembang City. The Covid-19 pandemic still shows no signs of ending. This can be seen from the increase in positive cases of Covid-19 every day. In making decisions on policies and decisions related to handling Covid-19, positive cases are still an important influence in this regard. Therefore, it focuses on predicting positive cases of Covid-19 in Palembang City. The data used in this study are data taken from the official website of the Palembang City Health Office as many as 153 data with 14 parameters. From 153 data, it is divided into 80% training data and 20% testing data. The variable used in this study is the daily number of confirmed cases of Covid-19 in Palembang City. KNN is used as a model to make predictions. From the research conducted, the RMSE results were 209,362. The results of this prediction can be used as input for research related to the prediction of positive cases of Covid19 in the city of Palembang.