Reviewerly/exHarmony huggingface dataset:
Empowerment of CIRC Model in Building Competency Writing Prosa-Based Video

Writing skills are one of the most important skills that students must master in order to communicate indirectly. The research aims to determine the students ' competence in writing prose through the empowerment of video-based CIRC models. The method used is quasy experiments with the design of one group pre-test and post-test. The subject of research is the elementary school student of Cisitu district 5th grade Cisitu subdistrict, which consists of 25 students, consisting of 8 men and 17 female 17. The instrument used is observation and test. Observations were made to see the activities of learners when implementing a video-based CIRC model, while tests were conducted to gauge student competence in writing videobased prose. The data obtained consists of two types namely qualitative data and quantitative data. The quality data is by using the observation sheet of student activity, while the quantitative data is processed by
A Survey of the Mixed Use of He/She for Chinese Freshmen in English Majors

The mixed use of he/she in oral English is a hot topic in the field of second language acquisition in the past decades and the related study is numerous. However, there are few studies on the misuse of the two pronouns in oral English for English majors in Chinese universities. This study aims to explore the current situation and characteristics of he/she misuse in oral English of Chinese freshmen majoring in English and analyze the factors that cause the misuse, so as to arouse the learners&amp;rsquo; awareness of the error. This study focuses on two research questions: (1) What are the characteristics of he/she misuse in spoken English of Chinese freshmen majoring in English? (2) What are the reasons for the misuse? Based on the selected spoken language materials, this study explores the mixing types and error rate of he/she and analyzes the characteristics of the misuse through data. Through the questionnaire, this thesis study investigates the causes of the misuse. It is found that the mixed use of pronoun he/she is serious in the spoken language of English major freshmen, especially the misuse of &amp;ldquo;she&amp;rdquo; into &amp;ldquo;he&amp;rdquo;. The factors that cause the misuse are complex, involving mother tongue, attention distribution and working memory, pronunciation relationship, transfer of training, and social environment and personal factors, among which the analysis from articulatory phonetics deserves more attention.
PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA KE PROVINSI BALI MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK

Bali has an increasing tourism potential. This is evidenced by the increasing number of foreign tourist visits to Bali Province each year. Although Bali's tourism trends have continued to increase over the past few years, efforts to improve the quality of Bali tourism need to be made. One way is to do forecasting. To support improvement efforts in Bali's tourism sector, the author created a forecasting system for foreign tourists to Bali province using artificial neural network methods with back propagation algorithms. Artificial Neural Networks with back propagation algorithms are neural network algorithms by finding optimal weight values. The forecast results using the binary sigmoid activation function were obtained by 489,862 foreign tourists in November 2019 with MAPE at 1.62% and 487,342 foreign tourists in December 2019 with MAPE of 11.78%. The forecast results using the bipolar sigmoid activation function were obtained by 493,200 foreign tourists in November 2019 with MAPE of 0.95% and 484,090 foreign tourists in December 2019 with MAPE of 12.37%.
Desain Media Pembelajaran Fisika Berbasis Web Blog Pada Materi Translasi Dan Rotasi Kelas X SMK Bunda Auni Bekasi

The purpose of this study is to: (1) determine the design of web blog-based learning media in Physics lessons that can improve the understanding of class X students on the material of translation and rotation at SMK Bunda Auni Bekasi. (2) know the process of making physics learning media based on web blog. (3) knowing student responses after using physics learning media based on web blog. The method used in this research is descriptive qualitative which is carried out at SMK Bunda Auni Bekasi. The data collection technique used a questionnaire distributed to 29 students of class X Vocational High School. The research data was used to determine the design process of learning media based on web blogs and the responses of class X students to the products that have been made. The results of this research show that the students' responses to the design of physics learning media based on web blogs are based on a questionnaire assessment of 29 students, namely with a percentage of 79.7% of the ideal score and classified as "Good" and can be used as an alternative learning media.
Scrutinizing Individual C- Trans Plus DRTA Method to Increase Student's Reading Comprehension

The objective of this research is to explain the development of Individual C-Trans plus DRTA Method in improving students’ reading comprehension among the eighth-grade Students of SMP Negeri 40 Bulukumba. The researcher used A Classroom Action Research (CAR) in this research. The researcher had conducted two cycles, where each cycle consisted of two meetings. It employed a reading test as an instrument. A number of the subject of the researcher were 31 students in XI class. Those consist of 13 men and 18 women. The findings consisted tests, students’ reading comprehension, and observation results. The first cycle of the first meeting was 57,58 and the second meeting was 63,54 and then the researcher tried to do the next cycle and the result in cycle II that was increasing of students score. In cycle II of the first meeting was 77,90 and the second meeting was 81,61. The conclusion of the research using C-Trans plus DRTA is able to improve the students’ reading comprehension (main idea) at the eighth grade. It was proved by the students’ achievement in cycle II was higher than cycle I and D-Test where in cycle I the students’ mean score reading comprehension becomes first meeting was 57,58 and the second meeting was 63,54, cycle II of the first meeting was 77,90 and the second meeting was 81,61. Based on the research findings, the implementation of Individual C-Trans plus DRTA Method showed success in improving reading comprehension.
Modeling the process of future physical education teachers’ training for innovative educational activities

The article deals with the currently essential problem of improving the quality of future physical education teachers’ training in accordance with the innovative development trends in the Russian Federation. The authors place special emphasis on the modeling of the training process of Bachelors in Physical Education. The article provides insight into the concept of “physical education teachers’ innovative educational activity”. The main content of the paper considers the theoretical substantiation of the structural and logical model as a theoretical construct of training Bachelors in Physical Education for this type of activity. The authors highlight the model’s methodological, substantive, procedural and logical elements, which imply future teachers’ mastering the optimal level of readiness for innovative educational activities.
Devil's in the Details: Aligning Visual Clues for Conditional Embedding in Person Re-Identification

Although Person Re-Identification has made impressive progress, difficult cases like occlusion, change of view-pointand similar clothing still bring great challenges. Besides overall visual features, matching and comparing detailed information is also essential for tackling these challenges. This paper proposes two key recognition patterns to better utilize the detail information of pedestrian images, that most of the existing methods are unable to satisfy. Firstly, Visual Clue Alignment requires the model to select and align decisive regions pairs from two images for pair-wise comparison, while existing methods only align regions with predefined rules like high feature similarity or same semantic labels. Secondly, the Conditional Feature Embedding requires the overall feature of a query image to be dynamically adjusted based on the gallery image it matches, while most of the existing methods ignore the reference images. By introducing novel techniques including correspondence attention module and discrepancy-based GCN, we propose an end-to-end ReID method that integrates both patterns into a unified framework, called CACE-Net((C)lue(A)lignment and (C)onditional (E)mbedding). The experiments show that CACE-Net achieves state-of-the-art performance on three public datasets.
Research Guides: Marketing and Advertising: Websites

This is a guide to key marketing and advertising resources, both at USC and within the marketing industry.
Narrative Mikrostruktur

Abstract Text comprehension is based on the literal content of sentences and pragmatic enrichment. Theories of pragmatic enrichment in the literature include enrichment of narrative texts, but also pragmatic content conveyed by presupposition triggers. Taking texts by Ror Wolf as my test case, I illustrate that our capacity of pragmatic enrichment can be abused to understand paradoxical content, even though the literal content of the text seems coherent at the surface level. This shows that pragmatic enrichment in narration is a genuine part of language processing and must not be equated with commonsense reasoning.
Divideup: A Generic Improvement Approach for Supervised Learning Using Dataset Partition with Finer Semantical Information

Supervised learning technologies represented by neural networks have made great progress in many fields. In particular applications such as image recognition and natural language processing, the entire computing process is completely handed over to the machine learning algorithm to directly learn the mapping from the feature space to the expected output, without considering much of the semantical information and domain knowledge of the data. In this paper, we propose a generic data refinement approach called divideup, which incorporates finer semantical information into the dataset to obtain a prediction model capturing more detailed information in the training data. By providing the information theory, we have high confidence that the learned model trained with the refined dataset has better prediction accuracy than the original one. We conduct extensive experiments on different datasets with the state-of-the-art neural network architectures such as ResNet and DenseNet. The experimental results show that divideup improves the prediction accuracy of all these deep learning architectures on the original test set. The divideup approach is also applied to other machine learning models such as random forest, XGboost and SVM. The results supports the conclusion that the refined training data obtained by divideup produces better prediction accuracy of the learned model.
Quantum d-separation and quantum belief propagation

The goal of this paper is to generalize classical d-separation and classical Belief Propagation (BP) to the quantum realm. Classical d-separation is an essential ingredient of most of Judea Pearl's work. It is crucial to all 3 rungs of what Pearl calls the 3 rungs of Causation. So having a quantum version of d-separation and BP probably implies that most of Pearl's Bayesian networks work, including his theory of causality, can be translated in a straightforward manner to the quantum realm.
Filtering a Signal in a Fuzzy Filter Based on the Area Ratio Method

Purpose of reseach. Digital signal filtering allows real-time noise reduction in electronic devices. Currently, there are many different digital filters, differing in speed, computing power, algorithms and restrictions on the conditions of use. One of these filters is the Kalman filter, but adjusting the gains of this filter is very complicated by the process of additional experiments and collection of statistical information. Therefore, in this paper, the authors consider a simplified algorithm for finding the control coefficients of a fuzzy digital filter with defuzzifier based on the area ratio method and investigate the influence of the area ratio method parameters on signal filtering, thereby achieving the goal of improving the accuracy of the fuzzy digital filter. Methods. For the algorithm for finding the control coefficients of the digital filter, a fuzzy logic apparatus was used. The control factors are determined using a defuzzifier based on the area ratio method. Results. In the course of experimental studies, the mean square error RMSE was calculated for a fuzzy digital filter using the area ratio method, the center of gravity method and the Kalman filter. Based on the results obtained, it was concluded that the fuzzy filter based on the area ratio RMSE method is 5.43 times less than for the Kalman filter and 2.77 times less than for the defuzzifier based on the center of gravity method. The results obtained prove the effectiveness of using a fuzzy digital filter with the area ratio method. Conclusion: This article considers an algorithm for the operation of a fuzzy digital filter, simulates a fuzzy digital filter and a Kalman filter in the Simulink system and calculates the RMSE values for a fuzzy digital filter with the area ratio method and the center of gravity method, as well as the Kalman filter.
Discriminative Pre-training for Low Resource Title Compression in Conversational Grocery

The ubiquity of smart voice assistants has made conversational shopping commonplace. This is especially true for low consideration segments like grocery. A central problem in conversational grocery is the automatic generation of short product titles that can be read out fast during a conversation. Several supervised models have been proposed in the literature that leverage manually labeled datasets and additional product features to generate short titles automatically. However, obtaining large amounts of labeled data is expensive and most grocery item pages are not as feature-rich as other categories. To address this problem we propose a pre-training based solution that makes use of unlabeled data to learn contextual product representations which can then be fine-tuned to obtain better title compression even in a low resource setting. We use a self-attentive BiLSTM encoder network with a time distributed softmax layer for the title compression task. We overcome the vocabulary mismatch problem by using a hybrid embedding layer that combines pre-trained word embeddings with trainable character level convolutions. We pre-train this network as a discriminator on a replaced-token detection task over a large number of unlabeled grocery product titles. Finally, we fine tune this network, without any modifications, with a small labeled dataset for the title compression task. Experiments on Walmart's online grocery catalog show our model achieves performance comparable to state-of-the-art models like BERT and XLNet. When fine tuned on all of the available training data our model attains an F1 score of 0.8558 which lags the best performing model, BERT-Base, by 2.78% and XLNet by 0.28% only, while using 55 times lesser parameters than both. Further, when allowed to fine tune on 5% of the training data only, our model outperforms BERT-Base by 24.3% in F1 score.
PREDIKSI KELAYAKAN NASABAH KREDIT MENGGUNAKAN TEKNIK PENGGABUNGAN KLASTERISASI EXPECTATION-MAXIMIZATION DAN KLASIFIKASI NAÏVE BAYES

Customer Data Credit has not been utilized to recognize patterns that can be used to predict New Credit Clients. However, Credit Client data does not have a class label for the classification. Therefore, the Credit Client data is processed first using EM clusteration (expectation-maximization) method to classify the class so that it can be classified using the Naive Bayes classification. The purpose of this research is to create a data mining model for the prediction of new Credit Customers Feasibility with combined method of EM Classification and Naive Bayes Classification. From 540 Credit Customers data, there are 142 data of Credit Clients that become cluster 0 or Bad Credit Customer and there are 398 Data of Credit Clients that become cluster 1 or good Credit Customers. The accuracy level of Naive Bayes classification after using EM clusterization has an average accuracy of 99.2437% and an average error rate of 0.7563%. Thus the combined method of EM clustering and Naive Bayes classification using WEKA can be concluded to be used to predict the feasibility of New Credit Clients.
Materiality, Contingency and Emergence of Compositional Material

If there is one idea that unites the manifold and often evasive conceptions of materialism, it is the immanence of form. Materialism, thus conceived, is the idea that matter is not shaped into form by something external to it, but rather itself harbours formal potential. Aesthetic, musical, biological, physical, and social forms can be understood as the product of emergent material processes. They can be conceived as contingent encounters that have taken form. Such a notion of materialist morphogenesis challenges anthropocentric assumptions about the nature of creative processes, relinquishing the idea of artistic practice as mastery over the material. This article focuses on compositional approaches to sound that explore the emergent material generation of form. It proposes a notion of materiality as a non-monist, non-hierarchical, and unpredictable interaction of different temporal, material, spatial and conceptual levels. By discussing works by Georges Aperghis, Helmut Lachenmann, Ashley Fure, and Aaron Cassidy, it deals with ways in which compositional practices, understood as situated and relational explorations of material potentials, embrace material contingency and the emergence of form.
Astrophysics visual analytics services on the European Open Science Cloud

The European Open Science Cloud (EOSC) aims to create a federated environment for hosting and processing research data, supporting science in all disciplines without geographical boundaries, so that data, software, methods and publications can be shared seamlessly as part of an Open Science community. This work presents the ongoing activities related to the implementation and integration into EOSC of Visual Analytics services for astrophysics, specifically addressing challenges related to data management, mapping and structure detection. These services provide visualisation capabilities to manage the data life cycle processes under FAIR principles, integrating data processing for imaging and multidimensional map creation and mosaicking and data analysis supported with machine learning techniques, for detection of structures in large scale multidimensional maps.
A qualitative case study on politics between professors and education officials

본 연구는 교육정책을 만들어 가는 과정에서 대학교수와 교육관료 사이의 관계 특성을 분석해 보고자 하는 연구이다. 이를 위해 대학교수와 교육관료를 대상으로 심층면담 중심의 질적 사례 연구를 수행하였다. 본 연구 결과 몇 가지 의미 있는 현상이 드러나고 있는데, 우선 대학교수와 교육관료가 각각을 바라보는 인식이 드러났다. 대학교수들이 바라 본 교육관료의 모습으로는 소신형, 혁신형, 기능형, 승진형, 버티기형, 상명하복형, 갑질형 등이 있는 것으로 나타났고, 반대로 교육관료들이 바라 본 대학교수의 모습으로는 도움을 주는 교수, 사명가형 교수, 총론만 장황한 교수, 정치적 교수, 활용하기 편한 교수, 개인적 친밀함을 유지하려는 교수, 사적 이익 추구형 교수 등이 있는 것으로 나타났다. 서로 이러한 모습을 보이는 대학교수와 교육관료가 만나 교육정책을 만들어 가는 일을 하는데, 이들이 만나 일하는 과정에서 나타난 관계의 정치학적 특징은 문법의 괴리, 기능적 공생, 상호 전문성 불신, 눈치 보기의 계층화 등 크게 네 가지였다. 이러한 본 연구 결과는 우리나라 교육정책 추진 과정의 총체적 부실 모습을 보여주고 있다는 점에서 의미가 있다.The purpose of this study is to analyze the relationship feature between professors and education officials. For That purpose, I conducted qualitative case study based on in-depth interview aimed at professors and education officials. The findings of this study are as followings. Firstly, professors appreciate education officials as type of belief, type of innovation, type of function, type of promotion, type of endurance, type of command and discipline, type of overusing own power etc. Secondly, education officials appreciate professors as type of helping, type of calling, type of lengthy, type of politician, type of utilizing, type of private intimacy, pursuiting of profit etc. Thirdly, I found four characteristics of politics between professors and education officials. Those are 1) gap of relational grammar, 2) functional symbiosis, 3) mutual distrust on professionality, 4) hierarchical pussyfooting etc. Conclusionally I found the overall poor of Korean system on educational policies.
An Interdisciplinary Approach To Education As A Basis For Urban Development Management

Currently, fundamental changes are taking place in human resourcing of the economy, which is reflected both in the emergence of new specialties that are extremely in demand on the modern labour market and in the gradual reduction in the need for some professions and their predictable disappearance. In our opinion, the rapid development of digital technologies and their widespread application form new requirements for professional culture of a modern specialist, which is reflected in the gradual transformation of educational programs which are aimed at more complete compliance with the requirements of the digital economy. This article substantiates the relevance of improving the personnel training system in order to provide the labour market with specialists in creating a comfortable living environment, identifies the problem of lack of working skills in the digital economy and also considers such an aspect of the labour market as the emergence of new specialties at the junction of different areas of knowledge. As a result, the authors proposed directions for the further development of the personnel training system, among which there is an integration of the interdisciplinary approach in the framework of educational programs in various specialties, as well as the development of an optimal combination of the number of lecture and practical classes in order to most fully ensure that the content of the educational program meets modern requirements for specialists in conditions of a digital transformation of all spheres of life of the population.