Reviewerly/exHarmony huggingface dataset:
How to train your conditional GAN: An approach using geometrically structured latent manifolds.

Conditional generative modeling typically requires capturing one-to-many mappings between the inputs and outputs. However, vanilla conditional GANs (cGAN) tend to ignore the variations of the latent seeds which results in mode-collapse. As a solution, recent works have moved towards comparatively expensive models for generating diverse outputs in a conditional setting. In this paper, we argue that the limited diversity of the vanilla cGANs is not due to a lack of capacity, but a result of non-optimal training schemes. We tackle this problem from a geometrical perspective and propose a novel training mechanism that increases both the diversity and the visual quality of the vanilla cGAN. The proposed solution does not demand architectural modifications and paves the way for more efficient architectures that target conditional generation in multi-modal spaces. We validate the efficacy of our model against a diverse set of tasks and show that the proposed solution is generic and effective across multiple datasets.
ADJECTIVE AND NOUN CLAUSE LEXICAL DENSITY IN AN ENGLISH TEXTBOOK FOR SENIOR HIGH SCHOOL STUDENTS

This paper analyzed the lexical density of the adjective and noun clauses in an English textbook for senior high school students in Indonesia. It aimed to discover whether or not the textbook was suitable for the students in terms of lexical density. The researchers employed a content analysis approach to analyze data. There were 116 sentences, containing adjective and noun clauses, which were investigated. The researchers implemented the lexical density theory and the lexical density indicators to determine the average level of the lexical density measurements. Results showed that there were three lexical density levels found in those adjective and noun clauses. The three levels were low, medium, and high. The average level of the lexical density obtained from the adjective and noun clauses in the textbook was 47%, which was categorized as low lexical density. Thus, the researchers concluded that the English textbook for the tenth-grade students published by the Indonesian Government was appropriate for the students.
UPAYA MENINGKATKAN HASIL BELAJAR MELALUI PENDEKATAN PICTURE AND PICTURE PADA MATA PELAJARAN PENDIDIKAN KEWARGANEGARAAN

Abstract: In the learning process every teacher must know must know the models in teaching, so students can follow the learning well. One learning model that can be done is to use picture and picture model that can develop students’s abilities in obtaining material. In the learning process picture and picture the teacher shows the pictures to students in an sorted / paired into a logical sequence. These images are the main factors in the learning process from beginning to end. So students can focus and rull well. The learning has the characteristics of active, innovative, creative and fun. In conducting research in class 2 SDN 267 Griya Bumi Antapani we conducted 2 studies, namely the control class and the experimental class. In entering the control class we only use the lecture method while in the experimental class we use a picture and picture model with image media. From the result of the data that we obtained showed that the control class did not understand the material provided by the teacher while the experimental class understood the material provided by the teacher and could apply it in everyday life.
A Probe into the Sustainable Development of the Japanese Talent Cultivation by the Cooperation between Private Universities and Enterprises

With the increasingly frequent exchanges between China and Japan, many companies in China are in urgent need of high-quality Japanese professionals. In this context, private colleges and universities pay more and more attention to school-enterprise cooperation, hoping to further optimize the talent training model of Japanese majors through school-enterprise cooperation. This article starts from the analysis of the problems existing in the training of Japanese professionals in private universities, and focuses on the exploration of the sustainable development of the training of Japanese professionals in private colleges and universities, with a view to comprehensively improving the teaching quality of Japanese professionals in private colleges and universities, and delivering more talents to the society.
SemML: Reusable ML Models for Condition Monitoring in Discrete Manufacturing.

Machine learning (ML) is gaining much attention for data analysis in manufacturing. Despite the success, there is still a number of challenges in widening the scope of ML adoption. The main challenges include the exhausting effort of data integration and lacking of generalisability of developed ML pipelines to diverse data variants, sources, and domain processes. In this demo we present our SemML system that addresses these challenges by enhancing machine learning with semantic technologies: by capturing domain and ML knowledge in ontologies and ontology templates and automating various ML steps using reasoning. During the demo the attendees will experience three cunningly-designed scenarios based on real industrial applications of manufacturing condition monitoring at Bosch, and witness the power of ontologies and templates in enabling reusable ML pipelines.
MPCC: Matching Priors and Conditionals for Clustering

Clustering is a fundamental task in unsupervised learning that depends heavily on the data representation that is used. Deep generative models have appeared as a promising tool to learn informative low-dimensional data representations. We propose Matching Priors and Conditionals for Clustering (MPCC), a GAN-based model with an encoder to infer latent variables and cluster categories from data, and a flexible decoder to generate samples from a conditional latent space. With MPCC we demonstrate that a deep generative model can be competitive/superior against discriminative methods in clustering tasks surpassing the state of the art over a diverse set of benchmark datasets. Our experiments show that adding a learnable prior and augmenting the number of encoder updates improve the quality of the generated samples, obtaining an inception score of $$9.49 \pm 0.15$$ and improving the Fréchet inception distance over the state of the art by a $$46.9\%$$ in CIFAR10.
A NOVEL COLOR-BASED FEATURE EXTRACTION METHOD FOR SVM BASED SKIN SEGMENTATION

The colored digital images can be represented in different color spaces. The most used color space is Red-Green-Blue space. However, this space can be transformed to Luminance-Blue Difference-Red Difference space for extraction of light intensity information and Hue-Saturation-Value space. The defined features of color pixels give strong information about whether they belong to a human skin or not. In this paper, a novel color-based feature extraction method is proposed, which use both red, green, blue, luminance, hue and saturation information. The proposed method is applied on an image database consists of various people with diverse age, racial and gender characteristics. The obtained features are used to segment the human skin by using Support-Vector- Machine algorithm and finally the promising performance results are presented comparatively with the most-common methods in the literature.
Application Analysis of WF / HDPE Composite in Landscape Design

Abstract Based on the brief introduction of the basic concept of landscape design, the anti-aging properties of WF / HDPE composite with UV-326 absorbent and WF / HDPE composite with UV-P absorbent were compared, It is concluded that the UV-P modified WF / HDPE composite can replace the UV-326 modified WF / HDPE composite in landscape design, The effects of UV-P and UV-326 contents on the aging resistance of WF / HDPE composites were analyzed. The application of UV-P modified WF / HDPE composite in modern landscape design is presented, and the structure and application place of paving board are introduced.
New Voices Case Study by Karen Veitch

This New Voices Case Study was written by new professional Karen Veitch, Open Access Support Officer at the Hive Library in Worcester.
Deep Convolutional Neural Networks: A survey of the foundations, selected improvements, and some current applications

Within the world of machine learning there exists a wide range of different methods with respective advantages and applications. This paper seeks to present and discuss one such method, namely Convolutional Neural Networks (CNNs). CNNs are deep neural networks that use a special linear operation called convolution. This operation represents a key and distinctive element of CNNs, and will therefore be the focus of this method paper. The discussion starts with the theoretical foundations that underlie convolutions and CNNs. Then, the discussion proceeds to discuss some improvements and augmentations that can be made to adapt the method to estimate a wider set of function classes. The paper mainly investigates two ways of improving the method: by using locally connected layers, which can make the network less invariant to translation, and tiled convolution, which allows for the learning of more complex invariances than standard convolution. Furthermore, the use of the Fast Fourier Transform can improve the computational efficiency of convolution. Subsequently, this paper discusses two applications of convolution that have proven to be very effective in practice. First, the YOLO architecture is a state of the art neural network for image object classification, which accurately predicts bounding boxes around objects in images. Second, tumor detection in mammography may be performed using CNNs, accomplishing 7.2% higher specificity than actual doctors with only .3% less sensitivity. Finally, the invention of technology that outperforms humans in different fields also raises certain ethical and regulatory questions that are briefly discussed.
MENINGKATKAN HASIL BELAJAR SISWA MELALUI PEMBELAJARAN DENGAN MODEL DISCOVERY LEARNING PADA SISWA KELAS X MIPA 5 SMA N 1 BANTUL TAHUN PELAJARAN 2018/2019

This study aims (1) to describe the learning process with Discovery Learning models among students; and (2) Improve the learning outcomes in subject of Bahasa Indonesia by application of discovery learning models. The subjects of this study were students of class X MIPA 5 SMA N 1 Bantul at 2018/2019 Academic Year. The study was conducted in three months from January to the end of March 2019. This study was a classroom action research (CAR), carried out in two cycles. Each cycle consists of four activities: (1) planning, (2) implementation, (3) observation, and (4) reflection. There are five types of data collection techniques used in this study, i.e. (1) observation, (2) questionnaire, (3) guided interviews, and (4) documentation. The results of this study show that (1) Discovery learning learning models improved teacher performance in learning, improved the performance of students in learning, and obtained excellent responses from students; (2) Implementation of discovery learning models improved student learning outcomes. The average value of student learning outcomes with the discovery learning model in cycle I was 82 with sufficient predicate, then increased to 94 in cycle II with very good predicate. The learning completeness in cycle I was 81.25% and increased to 100% in cycle II.
Changes of Swimming and Combined Exercise of Moderate and Vigorous Intensity for 32 Weeks on Health-Related Physical Fitness and Physical Self-concept in Elementary School Boys Before Adolescence

The purpose of this study was to find out about health-related physical fitness and physical self-concept in 32 weeks of moderate to vigorous intensity swimming and combined exercise for male elementary school students before puberty. The subjects of the study consisted of 4th to 6th grade male elementary school students living in Jin-gu, Busan, with Turner stage 1 students. A total of 23 people participants in the study, including 9 swimming, 9 combined exercise and 8 control groups. In health-related fitness, interaction effects were shown in muscle strength, muscle endurance, flexibility, and cardiopulmonary endurance. In the physical self-concept, interaction effects were shown in regular exercise and total score. When elementary school boys before puberty were given moderate and vigorous intensity swimming and combined exercise, It was higher than control groups in terms of muscle strength, muscle endurance and flexibility among health-related fitness factors. And in cardiopulmonary endurance, combined exercise is higher than swimming group, and swimming group is higher than control group, so combined exercise is recommended to improve cardiopulmonary endurance. Among the physical self-concept factors, the combined exercise group was higher than the control group in regular exercise, and the total score was higher in swimming and combined exercise group. As a result, changes in physical self-concept have been shown to have a positive effect on preadolescent children by swimming and combined exercise.
Efektifitas Penggunaan Otak Kanan dan Otak Kiri terhadap Pencapaian Hasil Belajar Mahasiswa

This study aims to see an overview of the use of the right and left brain of STMIK Mataram students and how much it affects the achievement of their learning outcomes. This type of research is a descriptive study with a quantitative approach. Data collection was carried out through questionnaires and test questions. The data analysis technique was carried out by using descriptive statistics and simple regression analysis to determine the closeness of the correlation coefficient between the independent variable (X), namely the level of use of the right brain and left brain and the dependent variable (Y), namely student learning outcomes. The results showed that in general, the level of use of the students' right brain was moderate with a percentage of 34.375%. The number of students who think using the right brain in the very high category is 6.25%, the high category is 31.25%, the low and very low category is 25% and 3.125%. The level of use of the students' left brain is classified as moderate with a percentage of 56.25%. Students who think using the left brain are in the very high category of 9.375%, the high category is 15.625%, the low and very low category is 12.5% ​​and 6.25%. Meanwhile, for the achievement of learning outcomes in general, the learning outcomes score was classified into the low category with a value range of 53 - 65 as many as 12 people (37.5%), 8 people (25%) and very high respectively. 4 people (12.5%). While the determinant coefficient obtained was 31.7%. In other words, that the use of the right brain and left brain has an effect of 31.7% on the calculus learning outcomes achieved by students.
Data Analytics for Artificial Intelligence Research from 2018 to 2020

This paper is based on literature dataset about Artificial Intelligence from SCI and EL A series of indices, such as Documents, Times Cited, CNCI, Highly Cited Papers, Hot Papers and EI Controlled Terms are used to analyze the research status and trends in the field of artificial intelligence in 2018-2020. Based on Documents, Times Cited and CNCI, high-yield countries, high-yield institutions, high-impact countries and high-impact institutions are identified. Based on Highly Cited Papers, Hot Papers and EI Controlled Terms, the most productive topics and the most influential topics in AI subject are identified. The results show that: AI is the third most productive sub-field in the Computer Science, and it produces the most highly cited papers and hot papers; the three countries with most total paper output are China mainland, USA, and Japan, while the top three countries with highest average paper impact are USA, England and United Kingdom; China mainland has the most high-yield institutions, among which Tsinghua University ranks first; the most influential topics discussed in highly cited papers are Decision Making, Neural Networks, Convolution, Fuzzy Sets, Deep Learning, Learning Algorithms, etc.
THE SANCTIONING OF CRYPTOCURRENCY: POSITIVE AND NEGATIVE RAMIFICATIONS IN INDIA

A cryptocurrency is a form of currency that exists only digitally that does not have a central issuing or regulating authority. To prevent fraudulent transactions a decentralized system relies on the blockchain system to record and oversee transactions. Blockchain technology is a type of system used to record transactions, which makes it difficult to hack. Each block within the chain contains a variety of transactions, and each time a replacement transaction occurs on the blockchain, a record of that transaction is added to each participant’s ledger. Blockchain transactions are recorded with an unchanging cryptographic signature called a hash. To corrupt the blockchain, a hacker would have to change every block of a chain, which is constantly growing increasing the system security.
A Study on Construction of EFL Teachers’ Multiple Identities at Universities in the Context of IT-based Education Reforms

Based on narratives of four visiting scholars concerning their teaching experiences in the context of IT-based Education Reforms in China, this paper aims at exploring construction of EFL teachers’ multiple identities at universities and the factors that have afforded and constrained their identity construction. It can be concluded that the interviewees have succeeded in constructing their identities as practitioners, managers, guides and instructors through self-adaptation to the new roles and promotion of IT-based teaching competence, whereas they feel it hard to construct their  identity as the researcher. As to the supporting factors, professional training, learning projects on integration of information technology into curriculum teaching, public teaching contest and mentors’ guides contributed to formation of their identities. What’s more, inner-motivation, self-assessment, personal reflection were the significant individual factors that have impacted the EFL teachers’ construction of their multiple identities. However, burden of teaching tasks, lack of systematic training in academic research and few opportunities to communicate with leading experts in a certain field have constrained their construction of researcher’s identity. It is suggested that Chinese EFL teachers should enhance their multiple identities through all-round improvement of IT-based teaching ability and seek more opportunities to be engaged in academic research while the institutions should optimize the current promotion system to support EFL teachers’ engagement in their academic research for a win-win situation.
Preparation of a Multicultural Teacher at a University

The article is devoted to the urgent problem of modern education and upbringing of a multicultural teacher.The purpose of this article is to identify the ways and mechanisms of preparing a multicultural teacher in a university environment.The article discusses issues related to the understanding of multiculturalism, multiculturalism, means and mechanisms of its implementation in a multipolar educational environment.Particular problems arise when preparing a teacher for activities in a multi-ethnic and multicultural environment.Obviously, appropriate adjustments should be made to teacher education programs.We are talking about changes in theoretical training (knowledge of the principles, specifics, tasks of multicultural education), as well as the mastery of certain methods of such education.In multi-ethnic educational institutions, teachers who speak at least two languages -Russian and the language of one or another minority should work.Unfortunately, in modern pedagogy there are no clearly oriented goals of multicultural education, the ways to achieve which and the results obtained could be unambiguously and objectively diagnosed.The wider and more significant the goals of multicultural education, the more difficult they are applicable in practice.The target setting when creating educational, multicultural technologies will take the form of the expected result only when they are specific, personality-oriented and reflect the patterns of the educational process to the maximum.According to the rules, multicultural education strategy is built is a means of realizing respect for the pupil, while they are implemented in special forms that determine the conditions that ensure the effectiveness of the technology requirements.The higher the exactingness to a person, the more respect for him or her.The success of multicultural education depends on the nature of the student's inclusion in various activities, as well as on the form, method, and means of instruction.The effectiveness of the implementation of multicultural, educational technologies will largely depend on the pedagogical conditions in which they are implemented.Such pedagogical conditions include -erudition, multiculturalism, originality of the personality of the teacher, his ethical culture, interests, hobbies, etc.; tolerant attitude towards pupils, expressed in pedagogical tact, optimism; deep knowledge of the laws of the multicultural educational process and child psychology, knowledge of diagnostic methods, etc. Today's teacher should be aimed at the adoption of multiculturalism and humanization of the entire educational process, at creating a system of interaction with students in any multicultural environment.It is also necessary to take into account the characteristics of the student's personality, ethnicity, mentality, national culture, psychological, gender and other characteristics of the student.This article will be interesting to teachers of universities and educational institutions, specialists in the field of multicultural education.
아시아 주요국가 의료기기의 무역네트워크 분석

The global IMF predicts that Covid-19 pandemic will cause countries around the world to experience the worst recession since 1930. In 2020, Global trade in commodities declined by 11% in 2020, and the forecast for global economic growth was lowered to -3.0. Which is highly dependent on global trade cannot but be shocked by the Korea. However, Covid-19 pandemic has come as an opportunity from a crisis, and it is the domestic Bio-health industry such as medical devices area. This paper examines the influence position of Korea and Asian countries in the global medical device and network trade volume changed of the Asian countries increased during the period of H1N1 flu and MERS outbreaks since to 2012. The medical device trade network was analyzed by Eigen-vector and mediation centrality by utilizing the connection degree, by the which indicators are can evaluate the influence of nodes in the network in the medical device trade network analysis process.The purpose of the this paper is to examine the trade of medical devices in the post-corona era is expected to increase significantly, we will how Korea’s position is changing into the Asian countries and how it will affect the medical device industry in Korea.