Reviewerly/exHarmony huggingface dataset:
The Method for Linear Regression Models Constructing Based on the Sharing of Measured Data and Expert Assessments

The paper discusses the classical approaches to the construction of regression models on the basis of independent and dependent random variables distribution laws.Regression dependencies are one of the main tools for constructing empirical descriptive models, at present moment the theoretical apparatus for constructing regression models has been developed.In the paper analysis of approaches to the construction of the one-dimensional regression dependencies is carried out The analysis allows to conclude that the known methods for constructing of regression models focused on the processing of jointly observed measured data.The authors of the paper propose the method for constructing linear based on the sharing of measured data and expert assessments. Methodological basis for ensuring the comparability of measured data and expert analysis is to convert it to a form of random variables distribution laws. Transformation of expert assessments to the form of continuous random variables distribution laws allows to developed the formal procedure for the construction of linear regression based on the sharing of measured data and expert assessments. Due to the proposed method for constructing of linear regression dependencies in the paper is shown an example of the assessments calculating of paired correlation coefficient and parameters of linear regression dependencies Keywords-regression models, jointly observed measured data, the sharing of measured data and expert assessments, random variables distribution law, linear regression dependencies, paired correlation coefficient I.In [3], a method for constructing non-parametric onedimensional regression dependencies is described, based on
LibGuides: Collection Development & Analysis: Weeding Procedures

This is where you will find analysis information which will help you determine what to purchase for your discipline. These are procedures for weeding in all formats.
Research on Quality Analysis Model of Additional Comments Based on Text Analysis

Abstract Based on the idea of text analysis, this study analyzes the relevance of text topics, the emotional consistency of fist comments and additional comments, and the information contained in the text, then get out of the online quality assessment model. The calculation results can reflect the quality of additional comments, helping consumers and businesses to identify important information and make correct judgments.
Privacy-Preserving Biometric-Based Remote User Authentication

Biometric-based remote user authentication (BRUA) is a useful primitive that allows an authorized user to remotely authenticate to a cloud server using biometrics. However, the existing BRUA solutions in the client-server setting lack certain privacy considerations. For example, authorized user’s multiple sessions should not be linked while her identity remains anonymous to cloud server. In this work, we introduce a new framework for biometric-based remote user authentication, such that authorized users authenticate to an honest-but-curious server in an anonymous and unlinkable manner. In particular, we employ two non-colluding cloud servers to perform the complex biometrics matching. We formalize two new security models, including biometrics privacy and user privacy, for the proposed framework, and prove the security of the proposed framework in the standard model.
Musicians Institute Library: Guide to Citations: Citing Websites and Social Media

A guide for everyone explaining basics of different types of Citation: What their purposes are, how to do them, and why they are important.
Scheduling Algorithms for the Revised PDPSort

Parallel sorting algorithms for manycore CPU systems are needed in data science and big data era. The PDPSort (Parallel Dual Pivot STLSort) can be revised and extended to achieve higher and more stable Speedups. This paper experiments four scheduling algorithms, Always Left (LAL), Always Right (RAL), Longer Partition First (LPF) and Shorter Partition First (SPF). Eventually, the revised PDPSort can achieve faster Speedup by upto 7.35×, 4.83× and 4.43× over the STLSort on AMD R7-1700, AMD FX-8320, and Intel i7-2600 Linux systems, respectively. Moreover, the LPF algorithm yields more stable Speedup’s than others.
ACHIEVEMENT LEVEL OF CHINESE LANGUAGE AMONG THE PRESERVICE TEACHERS AT INSTITUTION OF TEACHERS EDUCATION

The purpose of this study was to investigate the level of Chinese Language mastery level among the trainee teachers at the Institute of Teacher Education. The selected trainee teachers comprise two different programs, namely the Bachelor of Education Program (PISMP) and the Postgraduate Education in Diploma Program (PDPLI). A total of 389 samples were selected from 16 Institute of Teacher Education throughout the country by using the group and simple random sampling method. The instruments consisted of a Chinese Language test that was used to measure their achievement in the Chinese language as well as a questionnaire aimed at measuring their Chinese Language proficiency level. The results showed that the Chinese Language test results for the PISMP trainee teachers showed a high passing rate of 99.63%, whereas the DPLI trainee teachers scored at average 72.28%. Furthermore, the overall comparison found that the majority of the trainee teachers master the language skills well in communication, reading and writing skills. However, the t-test indicated that there was a significant difference in Chinese Language achievement between the PISMP program respondents and the DPLI respondents with t = 19.76, p &lt;.05, η = .67. This meant that the level of proficiency in the Chinese Language skills of PISMP trainee teachers was better than that of the DPLI trainee teachers. Therefore, the Malay trainee teachers should regularly associate with native speakers to improve their understanding and mastery of Chinese Language, Linguistics and knowledge of Chinese Culture to enhancing the quality of their teaching in the classroom.
Application of Fuzzy Sugeno Method And SAW For Bandwdith Usage Optimization

Provide services of internet network quality and user satisfaction become a liability for a university. In the meet it is the most major note is the capacity of the bandwidth used. It is used as a parameter of network quality at the university, from the other side of the bandwidth management is also influential in creating the internet network quality. The calculation of the bandwidth needs require some variable value integer and produce a solution that is worth an integer also. By using a fuzzy logic method that works with the rules linguistic will be obtained a solution with an integer value. SAW method is used because it has several advantages compared with other methods, an excess of the SAW method compared to the models with other decision-makers lies in its ability to perform assessment is more appropriate because it is based the value of criteria weights and preferences already determined, the SAW can also complete the best alternative from a number of alternatives that exist because the process of ranking after determining the weights for each attribute The results obtained from the application of such methods at the university can determine the amount of bandwidth requirements overall and per division. The results obtained from testing the value of the presentation QoS of 93,75% the index is very good. With the method of fuzzy sugeno, SAW help optimize the performance of the use of network bandwidth and streamline network service quality at the university.
Study on the effect of flip learning through lecture evaluation

본 연구는 A대학교의 강의평가 자료를 이용하여 플립러닝이 강의평가에서 긍정적인 효과가 나타나는지 알아보는데 그 목적을 두었다. 2016년 1학기부터 2017년 2학기까지 4개 학기의 자료를 분석하였다. 그 결과, 첫째, 플립러닝은 이론수업보다 학습자의 참여도 및 지식, 관심의 향상도가 더 높았다. 둘째, 플립러닝은 이론수업보다 강의평가가 더 높았다. 셋째, 실기/실습 수업은 이론 수업보다 강의평가 총점, 학생존중 면에서 더 긍정적인 평가를 받았다. 넷째, 플립러닝 수업 내에서 강좌규모, 운영학기수, 직급, 자발적 참여여부 등 거의 대부분 유의한 차이가 없었다. 이상의 결과에 대해 논의하고, 시사점과 한계점을 제시하였다.The purpose of this study is to investigate the effect of flip learning using lecture evaluation data of A university. Data from four semesters were analyzed from the first semester of 2016 to the second semester of 2017. As a result, first, flip-learning shows higher improvement of learner s participation, knowledge, and interest than theoretical class. Second, flip learning has higher lecture evaluation than theoretical class. Third, flip-learning and practical / practice classes received more positive evaluations in terms of total lecture evaluation, appropriateness of feedback, and respect for students than traditional lecture classes. Fourth, there were almost no significant differences in flip-learning classes, such as the size of courses, the number of semesters of management, job titles, and voluntary participation. The results are discussed and the implications and limitations are presented.
Legacy soil maps from Brazil: organizing and providing layers in an interactive WebGIS.

Digital soil maps at appropriate scales are essential information for land use planning. Nevertheless, Brazilian soil information is scattered in several institutions and stored in several formats. In adition to that, this information have faced an interruption of its systematic soil survey program, providing difficult access to decision makers. In order to organize and safeguard the spatial data produced at the Brazilian Agricultural Research Corporation (Embrapa), a spatial data infrastructure was developed (IDE-Embrapa) where thematic collections related to soil have been gathered and published in a web environment. The objective of this work is to present the initiative of organizing the spatial data of Embrapa related to soil information through the development of the IDE-Embrapa. In order to achieve this goal, the spatial data that were stored in a previous geoinformation infrastructure developed by Embrapa Soils were shifted to the IDE-Embrapa infrastructure. The implementation of the IDE-Embrapa was performed using open source software, based on the Open Geospatial Consortium standards. The IDE-Embrapa infrastructure uses GeoNode platform, which integrates a geospatial database (PostGis) with a map server (GeoServer) and a metadata catalog (PyCSW), and is controlled by a Content Management System in the Web environment. Currently, 100 information layers and 60 documents were catalogued in the IDE-Embrapa Soils (geoinfo.cnps.embrapa.br). These data and metadata are already available for download. Maps represented by various territorial boundaries and scales were registered. The main maps of Embrapa Soils are already catalogued and are available to the user with their own colorpattern (styling) for each type of thematic map, allowed by incorporation of a file with the styled layer descriptor (SLD) format to each map. Soil maps, for example, are presented with the colors established according to the Brazilian Soil Classification System, which facilitates users to visualize the spatial distribution of soils in a given region. Currently, the IDE-Embrapa infrastructure is making available the Brazilian soil information available to any external user. This work is under construction and we hope soon to have all maps prepared by Embrapa Soils catalogued and available, in order to safeguard data and metadata, for ready use of these by society.
The Use Of Particles By The Second Semester Students Of English Program at Khairun University

The writer applied descriptive method and basic statisic. The data are collected through instruments those are essay test and multiple choice. Essay test is about  matching the synonym  of the particles and translating  the particles into Indonesian language. The data were analyzed and tabulated into rating scale and qualification. Based on the data, the students’ mastery in using particles can be categorized as poor score. This is proven by students’ mean score is 41.77% this is found out that only 3 respondents or 8.57% of them obtained good score 4 resoondents or 11.42% of them obtained sufficient score 10 respondents or 28.57% of them obtained poor score and 18 respondents or 51.42% obtained very poor score. Overall, the second semester students of English study program involved in this research could not use particles correctly
Using Instagram as Online Shopping Channel: Key Predictors of Consumers’ Purchase Involvement on Instagram in Saudi Arabia

This study examined key predictors of Saudi consumers’ purchase involvement on Instagram. An online snowball sampling approach was used to reach Saudis via social media, with 1,671 Saudis recruited as valid samples. Results suggested Saudis’ frequency of Instagram shopping, Instagram credibility, and Instagram seller credibility as three major factors toward Saudis’ purchase involvement. Saudis who reported higher Instagram credibility and Instagram seller credibility would be more likely to involve with online shopping on Instagram. As two personality variables (materialism and self-esteem) were not found as powerful as other experiential variables to impact Saudis’ purchase involvement on Instagram, marketing channel planners who intend to use Instagram as a key online shopping tool should attempt to secure shopping privacy and payment safety on Instagram. Moreover, as Saudis’ positive attitudes were activated toward seller credibility, privacy security, and payment security on Instagram, Instagram becomes an effective shopping tool for Saudi consumers.
Physicochemical and heavy metal analysis of well water obtained from selected settlements around Dangote cement factory in Gboko, Nigeria

Drinking water in developing countries especially Nigeria is susceptible to toxins as a result of effluents and pollutants. This study investigated the physicochemical characteristics and heavy metal contents of water samples collected from six different hand-dug wells from some settlements around Dangote Cement Plant Gboko. The concentration of all the physicochemical parameter studied were generally below maximum limits prescribed by WHO except for turbidity which was found in two of the samples opposite the factory (OF) and Tarhembe (T) to be 51.8 NTU and 17.5 NTU respectively which were higher than the maximum limit of (5.0 NTU) set by WHO. Total metal digestion of water samples was carried out using concentrated nitric acid (HNO 3 ). The digests were analyzed for heavy metals (Cd, Cr, Cu, Fe, Mn, Pb, and Zn.) using AAS. Results showed that Cd, Cr and Pb in all the water samples were not detected, the concentrations of Cu and Zn ranged from 0.01-0.05 mgL -1 and 0.08-0.13 mgL -1 respectively and were below the permissible limit set by WHO. The concentration of Fe and Mn ranged from 0.25-1.16 mgL -1 and 0.33-0.92 mgL -1 respectively and were found to be above the permissible limits recommended by WHO for drinking water. In this study, contaminants level were generally below the WHO maximum recommended limits except Fe and Mn contents which showed elevated values above the recommended levels, hence the need to put mechanisms in place to control the levels of these heavy metals in the well water sources around the area under study. Keywords: Atomic Absorption Spectrophotometer, Heavy metals, Ground water, WHO
LibGuides: Translation Studies: What if Adelphi doesn't have it?

This guide is designed to assist students in the Translation Studies program. Do not give up! Adelphi cooperative borrowing arrangements with other libraries around the state.
Parametric Synthesis of a Robust Controller Based on the Method of Dominant Poles

In the paper a linear control system described by its characteristic polynomial with interval coefficients including parameters of controller linearly is considered. Problem of the research is finding parameters of a controller guaranteeing dynamic characteristics of a system despite interval parametric uncertainty of its object. It is proposed to base a controller synthesis on root quality indices: minimal stability degree and maximal oscillability degree. Desired values of these indices will be provided with the help of dominant poles method. Applying this method consists in placing a pair of complex-conjugate dominant poles; all other poles — unrestricted poles — will be placed by defining a right border of their allocation area on a complex plane. To apply dominant poles method, a feature of stability degree and oscillability degree to be determined by images of certain vertices of a parametric polytope was used. To synthesize a controller, it is proposed to divide its parameters in two groups: dependent ones and unrestricted ones. The first group of controller parameters is to provide desired allocation of dominant poles in one of vertices of parametric polytope (a dominant vertex). Unrestricted parameters of a controller are to provide desired distance between dominant poles and allocation area of unrestricted poles. To find coordinates of a dominant vertex and verifying vertices providing unrestricted poles allocation, an interval extension of basic phase equation of a root locus theory was developed. This resulted in interval phase inequalities, whose solution allows finding coordinates of desired vertices of characteristic polynomials coeffi cients polytope. Knowing a dominant vertex polynomial and dominant poles allows expressing dependent parameters of a controller from unrestricted ones. Obtained expressions allow placing unrestricted poles in a desired area of a complex plane. To do this, a D-partition by unrestricted parameters of a controller is performed in all verifying vertices of parametric polytope of a system. After choosing values of unrestricted parameters from intersection of all stability domains obtain during D-partition, dependent parameters of a controller can be calculated. An example of synthesizing a PID-controller guaranteeing desired values of dynamics characteristics for an interval control system of the fourth order is provided.
Iterative Policy-Space Expansion in Reinforcement Learning

Humans and animals solve a difficult problem much more easily when they are presented with a sequence of problems that starts simple and slowly increases in difficulty. We explore this idea in the context of reinforcement learning. Rather than providing the agent with an externally provided curriculum of progressively more difficult tasks, the agent solves a single task utilizing a decreasingly constrained policy space. The algorithm we propose first learns to categorize features into positive and negative before gradually learning a more refined policy. Experimental results in Tetris demonstrate superior learning rate of our approach when compared to existing algorithms.
Cardiac Left Ventricular Ultrasound Image Sequence Recognition and Tracking

A novel approach combining faster region-based convolutional neural network (Faster R-CNN) with active shape model is proposed to automatically recognize and track cardiac ultrasound left ventricular image sequences in this work. Because the shape and appearance of the left ventricle vary considerably between adjacent images, conventional methods cannot effectively identify its position and then accurately track them. We propose a novel method, incorporating Faster R-CNN and active shape model, to automatically recognize, segment and track the cardiac ultrasound left ventricular image sequences. Compared with four state-of-the-art approaches, the proposed method has most of better performance in Sørensen-Dice coefficient, mean absolute deviation, and Hausdorff distance.
The weight distribution of families of reducible cyclic codes through the weight distribution of some irreducible cyclic codes

The calculation of the weight distribution for some reducible cyclic codes can be reduced down to the corresponding one of a particular kind of irreducible cyclic codes. This reduction is achieved by means of a known identity (see [3,Theorem 1.1]). In fact, as will be shown here, the weight distribution of some families of reducible cyclic codes, recently reported in several works ([2,5,7,11,12]), and that of others not previously reported, can be obtained almost directly by means of this identity.
Correction to: Introducing Informatics in Primary Education: Curriculum and Teachers’ Perspectives

In the original version of this paper the affiliation was correct only for the author Valentina Dagienė. For authors Tatjana Jevsikova and Gabrielė Stupurienė affiliation has been corrected to: Vilnius University Institute of Data Science and Digital Technologies, Vilnius, Lithuania.
Evaluation of speaker-dependent and average-voice Vietnamese statistical speech synthesis systems

This paper describes the development and evaluation of a Vietnamese statistical speech synthesis system using the average voice approach. Although speaker-dependent systems have been applied extensively, no average voice based system has been developed for Vietnamese so far. We have collected speech data from several Vietnamese native speakers and employed state-of-the-art speech analysis, model training and speaker adaptation techniques to develop the system. Besides, we have performed perceptual experiments to compare the quality of speaker-adapted (SA) voices built on the average voice model and speaker-dependent (SD) voices built on SD models, and to confirm the effects of contextual features including word boundary (WB) and part-of-speech (POS) on the quality of synthetic speech. Evaluation results show that SA voices have significantly higher naturalness than SD voices when the same limited contextual feature set excluding WB and POS is used. In addition, SA voices trained with limited contextual features excluding WB and POS still have better quality than SD voices trained with full contextual features including WB and POS. These results show the robustness of the average voice method over the speaker-dependent approach for Vietnamese statistical speech synthesis.
Eigenface recognition using PCA

Face recognition is changing and evolving domain for research. Face recognition can be applied for many variety of problems in image and film processing like criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are relatively simple and easy to implement. The algorithm uses Eigen faces which are derived from Eigen vectors of original images to recognize a person. The Eigen face approach uses principal component analysis (PCA) to extract the required features. PCA is the best method to find the lower dimensional space. It also gives efficient results in recognizing the person. This method can be further extended to distinguish the gender of a person and also to detect the variation in the facial expressions.
LibGuides: Federal Register Library: Overview

The Federal Register is the official journal of the federal government of the United States. The database is updated daily and its coverage is comprehensive, beginning from inception in 1936.