Reviewerly/exHarmony huggingface dataset:
PENGARUH MEDIA ULARTANGGA TERHADAP HASIL BELAJAR SISWA PADA PEMBELAJARAN IPS SDN 1 PARDAWARAS

This research is motivated by of their problems in elementary school social strudies is the lck of demand by            strudents. There are many factors that make strudent do not much like learning IPS because IPS that since the mterial contains more social topics that are rote, the methode or media is very helpful ketercapaiannyya a lesson. Thus the          researchers to find out the influence of the of the media snake leader in improving learning outcomes of student in elementary school social strudies about the kindoms of Hindu-Buddhist in Indonesia. the method use in this research inquasi-experimental design with nonequivalent control grup. Instrumen use is the achievement test with multiple         choice. From processing and data analysis conducted on differences in student learning outcomes using conventional        learning model (classroom control) with the use of media snake leader (class experiment) proved there is a differencein the acquisition value of the posstest and the normal gain whice the class that use the conventional model in the category hight with a mean value of Ngain less effective. Ehereas the experimental class acquisitiom posttest value are at very hight category with a mean value of Ngain quite effective. It can be concluded on the use of media snake leader in SD Negeri 1 Pardawarasheavily influence the social studies students.
Research on the Evaluation Method of Software Static Quality based on AHP

Static analysis tools generate a lot of information about the software. We proposed the evaluation index of the software quality based on the information, and calculated the weight coefficient of the evaluation index by using the AHP method, then established the software static quality evaluation model. The result of 8 software projects shows that this method can evaluate the software quality objectively and quantitatively, also provide decision & guidance for software maintenance.
APLIKASI UNTUK MENDIAGNOSA KECANDUAN INTERNET TERHADAP MAHASISWA/I PERGURUAN TINGGI BERBASIS WEB DENGAN MENGGUNAKAN METODE FORWARD CHAINING

The rapid development of technology makes everything easier. As time passes, technology is growing and human needs can be easily fulfilled. The problem in technological development that is going faster every day is that the development can not be stopped, but the standard of human need for technology will be higher.Researchers write the meaning of application and internet addiction which is the topic of this scientific work. The researcher is using the Forward Chaining method in the process of making this application and using the Waterfall model as a system development method. Researchers also include the understanding of the internet, and the object that researcher researched, which is college student.Researcher gather information by questionnaires and literature study, collecting information such as student data from various colleges and reviewing for books, journals and websites for reference to this research.This website is created to determine the internet addiction of college students in general so college students and parents can find out the impact and find solutions for those who have Internet addiction.Through the research process and the website development that has been done, the researcher concludes that the website that the researchers has created can be useful for students to determine the level of internet addiction owned by the student. Key words : Diagnose Application, Forward Chaining Method, Internet Addiction, College Student,  Web.
Rectangular Flows for Manifold Learning

Normalizing flows are invertible neural networks with tractable change-of-volume terms, which allows optimization of their parameters to be efficiently performed via maximum likelihood. However, data of interest is typically assumed to live in some (often unknown) low-dimensional manifold embedded in high-dimensional ambient space. The result is a modelling mismatch since -- by construction -- the invertibility requirement implies high-dimensional support of the learned distribution. Injective flows, mapping from low- to high-dimensional space, aim to fix this discrepancy by learning distributions on manifolds, but the resulting volume-change term becomes more challenging to evaluate. Current approaches either avoid computing this term entirely using various heuristics, or assume the manifold is known beforehand and therefore are not widely applicable. Instead, we propose two methods to tractably calculate the gradient of this term with respect to the parameters of the model, relying on careful use of automatic differentiation and techniques from numerical linear algebra. Both approaches perform end-to-end nonlinear manifold learning and density estimation for data projected onto this manifold. We study the trade-offs between our proposed methods, empirically verify that we outperform approaches ignoring the volume-change term by more accurately learning manifolds and the corresponding distributions on them, and show promising results on out-of-distribution detection.
Data Exploration of online product reviews and prospective

The online shopping websites of today are providing one of many information services by writing the consumer review and encouraging rapid growth through the general comments of consumers [1]. For better understanding of these consumer reviews the available relationships among the crucial pieces of the review namely product aspects and opinions are to be explored. Reviewing and implementing content-based recommendations has a major impact on consumer opinions written on product reviews today [2]. Visual exploring these crucial pieces helps to uncover the nous and adjectives written in them. Subsequently, the quantified details of these adjectives are useful in downstream task of machine learning [3] in predicting the product recommendations. However, many text explorations have produced and visualized the characteristics and the outputs of the language model [4] namely word count, character length, word sequences. By profiling the reviews data by using summarization techniques and analyzing the expected relationships the corresponding insights are obtained in the clearer manner. The focus of this Exploratory Data Analysis (EDA) is to explore the crucial pieces of reviews which are nouns and adjectives scripted by the reviewers and to understand the polarities of these pieces so that the statistical recommendations based on polarities (aggregated to sentiments) are useful in explaining the obtained recommendations by using ontological analysis.
Ensemble incremental deep multiple layer perceptron model – sentiment analysis application

Purpose The purpose of this paper is to enhance the accuracy of classification of streaming big data sets with lesser processing time. This kind of social analytics would contribute to society with inferred decisions at a correct time. The work is intended for streaming nature of Twitter data sets. Design/methodology/approach It is a demanding task to analyse the increasing Twitter data by the conventional methods. The MapReduce (MR) is used for quickest analytics. The online feature selection (OFS) accelerated bat algorithm (ABA) and ensemble incremental deep multiple layer perceptron (EIDMLP) classifier is proposed for Feature Selection and classification. Three Twitter data sets under varied categories are investigated (product, service and emotions). The proposed model is compared with Particle Swarm Optimization, Accelerated Particle Swarm Optimization, accelerated simulated annealing and mutation operator (ASAMO). Feature Selection algorithms and classifiers such as Naïve Bayes, support vector machine, Hoeffding tree and fuzzy minimal consistent class subset coverage with the k-nearest neighbour (FMCCSC-KNN). Findings The proposed model is compared with PSO, APSO, ASAMO. Feature Selection algorithms, and classifiers such as Naïve Bayes (NB), support vector machine (SVM), Hoeffding Tree (HT), and Fuzzy Minimal Consistent Class Subset Coverage with the K-Nearest Neighbour (FMCCSC-KNN). The outcome of the work has achieved an accuracy of 99%, 99.48%, 98.9% for the given data sets with the processing time of 0.0034, 0.0024, 0.0053, seconds respectively. Originality/value A novel framework is proposed for Feature Selection and classification. The work is compared with the authors’ previously developed classifiers with other state-of-the-art Feature Selection and classification algorithms.
Bitcoin miners agree to form council amid meeting with Elon Musk

Tesla CEO Elon Musk participated in a meeting with Bitcoin miners over the weekend, following concerns he raised publicly about the environmental impact of the cryptocurrency that sent prices tumbling.
Preliminary study on using vector quantization latent spaces for TTS/VC systems with consistent performance

Generally speaking, the main objective when training a neural speech synthesis system is to synthesize natural and expressive speech from the output layer of the neural network without much attention given to the hidden layers. However, by learning useful latent representation, the system can be used for many more practical scenarios. In this paper, we investigate the use of quantized vectors to model the latent linguistic embedding and compare it with the continuous counterpart. By enforcing different policies over the latent spaces in the training, we are able to obtain a latent linguistic embedding that takes on different properties while having a similar performance in terms of quality and speaker similarity. Our experiments show that the voice cloning system built with vector quantization has only a small degradation in terms of perceptive evaluations, but has a discrete latent space that is useful for reducing the representation bit-rate, which is desirable for data transferring, or limiting the information leaking, which is important for speaker anonymization and other tasks of that nature.
Popularization Trend of Adaptive Data Compression Algorithm Based on Philosophy of Psychology Applied in English Adaptive Teaching

NOTICE OF RETRACTION: While investigating potential publication-related misconduct in connection with the ICIMTech 2021 Conference Proceedings, serious concerns were raised that cast doubt on the integrity of the peer-review process and all papers published in the Proceedings of this Conference. The integrity of the entire Conference has been called into question. As a result, of its investigation, ACM has decided to retract the Entire Conference Proceedings and all related papers from the ACM Digital Library.
The DataCite Technology Stack

DataCite is a DOI registration agency that enables the registration of scholarly content with a persistent identifier (DOI) and metadata. This content can then be searched for, reused, and connected to other scholarly resources. But how does the underlying infrastructure enable this? In this blog post, we will describe what we have built to make this work. This is a fairly technical post, as I tried to go a little deeper into the details.
The effect of Previewing Strategy on Reading Comprehension of Tenth Grade Students at SMK Darul Anwar Singojuruh in Academic Years 2019/2020

The objective of the research is to know whether the students taught by using Previewing Strategy get better reading comprehension in descriptive text score, because the observation showed that students have low score reading comprehension in descriptive text. The research design of this research was pre-experimental desaign. The respondents of this research were the tenth grade students of AK class at SMK Darul Anwar, that consisting of 31 students. To collect the data the researcher uses test as the instrument. The data were collected through multiple chioce. The test is given before and after the treatment. The treatment is using Previewing Strategy as a media in teaching and learning reading comprehension descriptive text.The computation result of t-test is 10.66. The result of computation value is consulted to the
Degree-Specific Topology Learning for Graph Convolutional Network

Graph Convolutional Networks (GCNs) have gained great popularity in various graph data learning tasks. Nevertheless, GCNs inevitably encounter over-smoothing with increasing the network depth and over-fitting specifically on small datasets. In this paper, we present an experimental investigation which clearly shows that the misclassification rates of nodes with high and low degrees are obviously distinctive. Thus, previous methods such as Dropedge that randomly removes some edges between arbitrary pairwise nodes are distant from optimal or even unsatisfactory. To bridge the gap, we propose the degree-specific topology learning for GCNs to find a hidden graph structure that augments the initial graph structure. Particularly, instead of training with uncertain connections, we remove edges between the high-degree nodes and their first-order neighbors with low similarity in the attribute space; besides, we add edges between the low-degree nodes and their connectionless neighbors with high similarity in the attribute space. Experiments conducted on several popular datasets demonstrate the effectiveness of our topology learning method.
Comparative study of Conventional and Reciprocal Recommendation System

Recommendation systems provide an intelligent way to navigate through an ocean of options available at users’ disposal and present information that they perceive to be useful and worth trying out. Recommender Systems (RS) are assistance in the form of software, tools or algorithms that may guide a target user in making decision by proposing him recommendations based on his interests. In conventional recommendation system we have active elements on one side (Person) and passive elements in others side (Products). Success is determined by only one side (user–side) who is seeking recommendation, but the other way is not possible. Reciprocal recommendation is a special case of recommendation system where both sides we have active participants (people) and their mutual agreement is mandatory for a successful relation. Many social websites’ core task is to recommend people to people. The objective of this article is to do a comparative study of conventional and reciprocal recommendation system and study the domain of applications and the approaches used for the implementation in the recommendation system.
THE CONTRIBUTION OF SOCIAL SUPPORTS TO MEDIA LITERACY

This study was aimed to determine the contribution of social support to media literacy on social inclusion-based village library users. Media literacy as an effort to improve skills and also people's welfare needs to be improved as an educational effort towards a prosperous society. With social inclusion-based media literacy, farmers, housewives, traders, who in fact are library users of social inclusion-based village libraries can use the internet to learn new skills, improve product quality, and sell online. This study revealed the contribution of social support in improving media literacy in social inclusion-based village libraries. This quantitative study collected 74 research subjects using a social support scale and a media literacy scale compiled by the researcher. There are 74 subjects in this study. Research subjects are library users who no longer go to school and work as farmers (35 subjects), traders (5 subjects), housewives (28 subjects), and laborers (10 subjects). Based on gender, there were 61 female subjects and 13 male subjects. The criteria for the subjects in this study included: (1) social inclusion-based village library users, (2) not working in the formal sector, (3) not pursuing education. The measurement scale in this study is arranged according to Likert scale model which consists of several favorable and unfavorable attitudes. The results revealed that the higher the social support, the higher the media literacy tends to be in social inclusion-based village library users. In this study, it is known that the effective contribution of social support with media literacy is equal to the coefficient of determination (R2) of 0.516, this means that social support is able to contribute to the media literacy variable by 51.6%, while 48.4% is explained by other variables.
RETRACTED: Research on the Cultivation of “Double Division Type” Teachers in Higher Vocational Colleges Based on the Analysis of Big Data from the Perspective of Production Teaching Integration

Abstract With the rapid iterative expansion of information-based big data technology, based on the analysis of the difference representation, dynamic expansion process and stage characteristics of “double qualified” teachers, it is not difficult to find that there is still a lack of unified evaluation and evaluation standards for “Double Division Type” teachers in China, which cannot meet the demands of expansion and the training of teachers in higher vocational colleges. Based on this, this paper first analyses the relevant theory of “double qualification” teacher training, secondly analyses the problems encountered in the cultivation of “Double Division Type” teacher team based on the big data, and finally gives the training strategy of “Double Division Type” teacher team in vocational colleges from the perspective of production teaching integration.
A STUDY ON THE STUDENTS’ PERCEPTION OF UTILIZING WHATSAPP AS A TOOL OF TEACHING LISTENING TO ASSIST DISTANCE LANGUAGE LEARNING

Listening is one of the skills in English which should be mastered well by the person who learns it. As the foreign language, it is not easy for the Indonesian students to master this skill. Moreover during the lockdown period of Covid-19 epoch when the students have distance language learning as the government policy, the process of teaching and learning especially teaching listening becomes more difficult. The use of tool is so important to support the process of teaching and learning in this situation. WhatsApp is chosen as the tool in the process of teaching and learning. This study aims to explore the English undergraduate students’ perception of the utilizing WhatsApp as a tool of teaching listening to assist distance language learning. The data were analyzed using questionnaire and interview. After analyzing the data, the research findings show that students have positive perception towards the use of WhatsApp for learning listening. It is an easy, fun, pleasant and good tool to use in the teaching learning process. It makes the students enthusiasm to learn and can help them to get the listening audio material which they must listen easily.
ModelFlex : Parameter Tuning for Flexible Design of Deep Learning Accelerators

Algorithmic optimizations are applied to neural networks models to decrease their compute and memory requirements for efficient realization on embedded platforms. A feedback form the target platfor ...
Pengaruh Media Tiga Dimensi Untuk Meningkatkan Hasil Belajar Siswa Pada Materi Kubus Dan Balok Di Kelas V Sd Negeri 21 Mendo Barat

The problem in this research is the low of study result of class V student at SD Negeri 21 Mendo Barat and the absence of media used in the lesson of Mathematics. The purpose of this study is to determine the influence of Three Dimensional Media to improve student learning outcomes on the material of cubes and blocks in Class V SD Negeri 21 Mendo Barat.This research uses quantitative research with pre experimental method (The One Group Pretest-Posttest Design). The sampling technique in this study used saturated sampling. The sample of this study is the entire class V amounted to 34 students. Data collection techniques used in the form of a written test that consists of 5 essays namely pretest and posttest. The prerequisite test used is the Liliefors test to test the normality of the data. Based on Liliefors test results obtained that the data is normally distributed.Based on hypothesis test data analysis from the result of t-test related data pairwise with tcount > ttable (11,95 > 2.03), hence can be interpreted that Ha accepted and H0 rejected. So from the results of the research shows there are positive effects of three-dimensional media to improve student learning outcomes on materials cube and beam class V SD Negeri 21 Mendo Barat
Virtual reality app on Milky Way solar system, case study:Kebraon II Public Elementary School, Surabaya, East Java,Indonesia

6th grade students of Kebraon II Public Elementary School at Surabaya, Indonesia, learn the introduction to astronomy about the solar system. However, they don’t understand some basic concepts, such as the differences of rotation and revolution, shape and size of planets and other celestial bodies. In addition, they are not interested in studying astronomy, because of the books consisting of large amount of text and black-and-white still images. To spark the students’ interest on astronomy, we create an interactive application which features virtual reality (VR) to introduce astronomy. It features the solar system and other celestial bodies with their information (orbital time, rotation time, revolution time, etc.), as well as solar and lunar eclipse animation and information, in accordance with Indonesia’s Ministry of Education 2006 curriculum, KTSP (Kurikulum Tingkat Satuan Pendidikan, School-Based Curriculum). The application is developed for Samsung Gear VR using Unity 5. Users will be able to see the whole solar system and navigate using a Bluetooth-enabled, Android compatiblegamepad, and interact with celestial bodies to see their information. The application is black-box tested to teacher and 10 students. All students are more interested in astronomy, concluding that this app can be used as an alternative medium to introduce astronomy.
Library Class and Subject Guides: Licensure Resources: Home

In addition to resources you have used in your classes, you will find online and hard copy exam preparation books.
LibGuides: Grade KG Library Guide, PXES: Back to School

A guide to library materials and lesson outlines that support KG curriculum at Shanghai American School, Puxi Campus. Stories to Begin the Year
Reading Attitude among Elementary School Students in China: A Comparison between Regions of Different Economic Development

This paper describes the results of a study examining the difference between reading attitudes of children in regions with different levels of economic development. The Elementary Reading Attitude Survey of McKenna and Kear was translated into Chinese by the researcher to measure the reading attitudes of students in Shanghai and Ya'an and 208 results were analyzed with independent t-test. It was found that there were significant differences between overall reading attitude and academic reading attitude between children in regions with different levels of economic development, but no significant difference was found in the children's recreational reading attitude.
LibGuides: Grade 1 Library Guide, PXES: Light & Shadow Puppets

Materials to help support Grade 1 literacy units, including Small Moments, . . . . .(to be completed as the 2020-21 School Year progresses)