Reviewerly/exHarmony huggingface dataset:
Multi-view Subspace Clustering with Joint Tensor Representation and Indicator Matrix Learning

Multi-view subspace clustering (MVSC), as an extension of single-view subspace clustering, can exploit more information and has achieved excellent performance. In particular, the MVSC methods with sparse and low-rank basing have become a research priority as they can improve the clustering effect in an effective way. However, the following problems still exist: 1) focusing only on the connections between two views, ignoring the relationship of higher-order views; 2) performing representation matrix learning and indicator matrix learning separately, unable to get the clustering result in one step and obtain the global optimal solution. To tackle these issues, a novel sparsity and low-rank based MVSC algorithm is designed. It jointly conducts tensor representation learning and indicator matrix learning. More specifically, the Tensor Nuclear Norm (TNN) is utilized to exploit the relationships among higher-order views; besides, by incorporating the subsequent spectral clustering, the indicator matrix learning is conducted during the optimization framework. An iterative algorithm, the alternating direction method of multipliers (ADMM) is derived for the solving of the proposed algorithm. Experiments over five baseline datasets prove the competitiveness and excellence of the presented method with comparisons to other eight state-of-the-art algorithms.
The Use of Hedges for Observing Cooperative Principles in Joe Biden versus Donald Trump Debate in the 2020 American Presidential Election

This study discussed the use of Hedges to observe cooperative principle rule, especially in debate. As is known that in a debate, usually a moderator gives questions to the debaters and the debaters try to answer the question. And when they are not sure about their answer, hedges are used which function to make things fuzzier as defined by Lakoff (1975). This study’s aims are to analyze the use of hedges for observing the cooperative principles rule and to analyze the interlocuter’s responses in the 2020 American presidential election debate between Joe Biden versus Donald Trump. The researcher adopted the theory about understanding hedges from Lakoff, (1973), the hedges’ function from Fraser (2010), and the cooperative principle theory from Grice maxim (1983). This research is qualitative research and to analyze the data the researcher uses discourse analysis. The sources of the data were the transcripts and the videos of Joe Biden and Donald Trump’s presidential debate. From the results of the study, the researcher found that the 2020 American presidential candidate, Joe Biden, broke the maxim quality 4 times and obeyed the maxim quality once, for the maxim quantity Biden neither broke nor obeyed the maxim quantity. while for maxim relation, Biden broke 5 times and obeyed once, and for maxim manner, Biden broke once and 0 obeyed with maxim manner. While the 2020 American presidential candidate, Donald Trump broke the maxim quality 4 times and obeyed the maxim quality once, for the maxim quantity Trump neither broke nor obeyed the maxim quantity. while for maxim relation, Trump broke 5 times and obeyed once, and for maxim manner, Trump broke once and 0 obeyed with maxim manner. Keywords: Hedges, Cooperative Principle, Joe Biden, and Donald Trump debate
Determining Computer Opponent’s Actions in Strategy Game Using K-Nearest Neighbour Algorithm

Advances in computer technology allow various devices to complete complex computing, especially in the entertainment industry and the biggest example is games. Strategy game is the type of game that most often gets an Artificial Intelligence or AI system implemented to imitate human behaviour when playing games. Many game AI systems are predictable so players get bored quickly, so adaptive and simple AI is needed to make it easier for game developers. K-Nearest Neighbour is a classification algorithm with supervised learning, this algorithm will be used in this study. The research method tests the level of accuracy in determining the class by providing a sample of data which is divided into training data and test data. The measure of the level of accuracy is calculated using the confusion matrix after the test table is obtained. The results of the study concluded that the K-Nearest Neighbour algorithm can determine computer opponents fairly well. More data samples are needed as data training to increase the level of classification accuracy.
Application of Machine Learning Algorithm for Determining Elective Courses in Informatics Study Program

Informatics study program at Nurul Jadid University does not have a general concentration of knowledge, so that sometimes the selection of elective courses by students is not quite right. This study aims to classify the concentration of knowledge with a data mining approach which can then be used as a recommendation for selecting elective courses by students. In this study, we implement a machine learning algorithm to provide recommendations to students regarding what interests are more suitable to be taken based on the values ​​of prerequisite courses in previous semesters. Student data was obtained from the Head of the Center for Data and Information Systems (PDSI) at Nurul Jadid University with 70 student data from Nurul Jadid University batch 2018. The machine learning algorithm used is Neural Network with Python programming language, the tools used are Google Collab. At the beginning of data collection, then pre-processing is carried out to prepare the dataset in order to get good results, and model training is carried out. After training on the model, then further testing is carried out on the model to determine the performance of the model. The result of the accuracy value in the training model process is 0.83 or 83% and the accuracy of the test data is 0.79 or 79%.
Revisiting the English Textbook Accessibility based on the Universal Design Learning Principles

Textbooks based on the teaching and learning process should be relevant to any students including students with disability, there are a lot of textbooks that are not suitable enough to provide accessible material. The goal of this study was to evaluate Universal Design for Learning (UDL) concepts in 2 online modules on UDL that were taught over one semester alongside English as a Foreign Language (EFL) lectures. The module is divided into 10 chapters that each discuss one of five categories of exploratory texts. To clarify the ULD concepts used in the curriculum, this research applied Textbook analysis using the Center for Applied Special Technology (CAST 2018) design framework. The results demonstrate that more ULD concepts, which notably provide multiple means of engagement, representation, and action &amp; expression, can be used to provide better accommodation for blind students to support inclusion in educational materials. In addition, a strong desire to use the UDL concepts in their future teaching is encouraged through university modules. There is a discussion of restrictions and repercussions.
Stylistic Features of Internet Relay Chat IRC as a Medium of Computer-Mediated Communication

This study is a quantitative-qualitative, descriptive study in one of the mediums of computer-mediated communication, CMC. It attempts to investigate some stylistic features in the medium of Internet Relay Chat IRC that are used by online chatters. The data of this study are gathered from open access chatrooms through screen shots. The number of screen shots that are used in the analyses is (30) screen shots. The findings reveal that chat systems allow chatters to use different stylistic features such as graphic features, orthographic features, discourse features, flaming, spamming, spoofing, trolling, and lurking. The most frequent features are orthographic features such as “abbreviation, acronyms and punctuation”. These features are widely used in internet relay chat to save time, effort and as economy expressions.
Analysis of Research Subjects and Research Topics on ErHu in Korea: Focusing on Comparative Studies of Master’s and Doctoral Dissertations

The purpose of this study is to analyze a total of 17 papers from the first Erhu- related thesis published in 2001 to 2022 and to suggest future tasks to be solved. To this end, the research type, topic, and methodology of the theory were thoroughly analyzed in this study. As a result of the study, there are 7 comparative studies between Haegeum and Erhu, 3 studies on Erhu works in Korea and China, 2 studies on musical instruments or performance techniques, and 2 pieces of computer music. In addition, there was one study on the improvement of Haegeum, a joint study of Chinese folk music and vocal music and Erhu, and one study on Erhu's artistic management. In the beginning, a comparative study of Haegeum and Erhu was conducted mainly with Koreans, but the Chinese gradually started to participate. The subjects of the study were the composition of the instrument itself, the basic playing method, and the old related works. As a research methodology, the most used methods were the formal structural analysis and musical analysis of the work, and the comparative analysis of instruments. In this study, future challenges for Erhu in Korea were presented based on these results.
Development of a New Layout for Serial Labels to Reduce Interruptions in TV Lines Caused by Difficulty Reading Barcodes

With the advent of new technologies and the growing market demand, companies have been looking for ways to improve the efficiency of their production processes, introducing innovations from the elimination of waste, reduction of rework and incongruity of information due to manual data entry . The objective of this article is to demonstrate that it is possible to mitigate or eliminate stoppages in the TV production process, caused by difficulty in reading barcodes printed on a thermal transfer printer, with intelligent and innovative solutions supported by quality tools. In the search for the resolution of these problems, this work was developed in three chapters. Chapter I begins with an introduction that presents the problem to be dealt with, what types of bar codes are adopted in the company, addresses the quality tools that were used as support in the search for the solution of the problem and also the general objective and the specifics that were defined by the researchers. Chapter II briefly presents the methodology that was applied for the development of this work, the concept of efficiency and effectiveness in the production system, details the quality tools used (PDCA, Brainstorming, 5 Whys, Ishikawa Diagram, 5W2H) to find a viable solution to the problem being addressed. It discusses the most used types of bar codes, two-dimensional and linear, among others, their structural compositions, the encoding and decoding processes, the check digit and the methods that cover the detection of incorrect typing. Chapter III presents a proposed solution for the company, based on a vastly detailed analysis of the flowchart of each area involved in the printing process and the use of barcode labels, the materials used in the printing process, which information systems are used as well as the layout and method used for printing. The result of this study tends to contribute to other enterprises that have similar bar code printing processes, since its application aims to reduce or eliminate line stops, acting directly on the bar code failures that cause so much stoppages. line, demonstrating that disruptive thinking associated with intelligent change contributes positively to the company's results by improving process and information flow, contributing to increased efficiency and reduced rework.
Pengaruh Fasilitas Belajar dan Motivasi Belajar Terhadap Prestasi Belajar Peserta Didik Pada Mata Pelajaran IPS di UPTD SDN Wilayah I Kecamatan Bontoa Kabupaten Maros

The good learning achievement of a number of students is believed to be the simultaneous influence of the standard of completeness of learning facilities in schools and students' learning motivation. This assumption has resulted in, at least, empirical evidence and different field data sources in several case studies for similar themes, included in this study. Conducted from June to August in class V - UPTD SDN Region 1 Bontoa District, Maros Regency as a locus. This research is an Ex-post facto quantitative study that focuses on the moment of a certain phenomenon that has become a past event to find out both the causal factors and the impact of the event. Proportionate Stratified Random Sampling was used as a sampling technique, where 125 students were randomly assigned in this study according to the Slovin formula. Data collection is done by distributing questionnaires to respondents, namely class V students. The questionnaire uses an inverted number scale with two categories, where the favorable category starts from numbers from 1 to 5 and Unfavorable vice versa (from 5 to 1). In addition to descriptive analysis as one of the mathematical model approaches used in analyzing the relationship between one or several independent variables that are categorical, numeric, or both with one dichotomous categorical dependent variable - logistic regression analysis is also used. Partial tests are included to determine the significance of the effect each independent variable separately, so that it can be seen whether the existing assumptions are acceptable or not. The hypothesis is accepted if t-count &gt; t-table or p &lt; = 0.05. The results obtained show that learning facilities have a less significant effect on learning achievement. While the motivation variable has a significant influence.
Perception and Effect of Undergraduate English Language Students have about Studying Literature

The purpose of the study is to examine the Perception and Effect of Undergraduate English Language Students have about Studying Literature. The findings of this study have some implications for ESL students studying literature in the language classroom. The fact that literature has been used to make English language teaching and learning more interesting, even at the lower levels of learning, goes a long way to support the argument that literature should be encouraged in English language teaching and learning in Ghanaian schools. Poetry, drama, and prose have all been employed in the teaching and learning of various components of the English language. However, the critical function of literature in ESL students' language learning cannot be realized without a shift in the mindset of the stakeholders. According to the findings of this study, many undergraduate students have a negative attitude toward the study of literature. School authorities must also encourage parents to buy enough literary materials for their children and also encourage them to read them. This will help the students to develop good reading habits which will in turn improve their attitude toward the study of literature. Creative programmes could also be developed using current technologies which will make students develop good reading habits.
THE CONTENT ANALYSIS OF BAHASA INGGRIS TEXTBOOK USED IN THE FIRST CLASS OF SENIOR HIGHT SCHOOL 1 NAN SABARIS

This research was based on varieties textbook circulating in learning. The method used in this research is descriptive research method, by analyzing the book "English" Semester 1 published by the Ministry of Education and Culture, English Language Book Revised 2017. The instrument used by the researcher was the Assessment rubric from the National Education Standards Agency Badan Standar Nasional Pendidikan (BSNP) and Documentation. The data were analyzed by using the conformity tabulation of the BSNP rubric and the range category in percentage form. The results of this study indicate that the total percentage obtained is 93.75% and is included in the Good category. This total percentage is obtained from the score on Material Completeness in 5 chapters getting a score of 4 or reaching 95% of the completeness of the material and 1 chapter getting a score of 1 or less than 95% of the completeness of the material. The in-depth score obtained in 5 chapters gets a score of 4 or 95% of the specified in-depth and 1 chapter gets a score of 1 or less than the specified 95% in-depth. The percentage assessment on the Social Function from Chapters 1-6 gets a score of 6 or reaches 95% of the social function provisions of the BSNP. The percentage value of Generic Structure here is 5 chapters getting a score of 4 or meeting 95% of the Generic Structure standards available in the BSNP rubric and 1 chapter getting a score of 1 or the achievement of Generic Structure is less than 95%, the percentage results from Linguistic Features in all the subjects studied are from the chapter 1-6 get a score of 4 or the percentage of achievement from Linguistic Features reaches 95%. The percentage achievement for Supporting Materials has 3 assessment points, namely Relevance, Development of Life Skills and Development of Diversity Insight. Here in chapters 1-6 each gets a score of 4 or reaches 95% of each category. So based on the results that have been examined in this study, the percentage category of achievement of this book is included in the Good category.
The Queer Aut of Failure

I, a Mad, autistic, multiply-disabled person, began my PhD in Cultural Studies in September of 2020. I started to make my home in graduate school during the COVID-19 pandemic, fully online, and I've excelled, calling into question normative assumptions of in-person socialization, education, and collaboration as superior to their virtual counterparts. In this article, I reflect on the cripistemic pedagogies of failure that facilitated a neuroqueered and transMaddened transition to Zoom-based graduate life. I will also consider email, text messages, and video calls as equalizing mediums in which both formal and fugitive spaces can open for queercrip collaboration across borders, timezones, and access needs. Lastly, I will tell the stories of technological 'failures' that I have experienced—miscommunications, failing internet, time delays—as generative possibilities rather than indictments of a non-normative learning. Necessarily imperfect and rife with humorous, intriguing, and profoundly human failures, as well as surprising and generative openings, pandemic education has ushered in new queercrip, transMad, ways of knowing and teaching that have uniquely benefitted me. Far from a circumscribed or lacking educational landscape, I argue, post-COVID academia is filled with pedagogical and epistemological openings, holes through which new disabled and Mad scholars, myself included, can make ourselves a beautifully imperfect home space. I invite you inside.
Automatic mapping and localization in large-scale cyclic using K-nearest neighbours

Localization is considered one of the essential topics in autonomous mobile robots.With the improvements of the robotic industry in the past decades, robot localization has become more interesting: from unknown to known environments, from complex to simple environments, from dynamic to static environments [1], and from long-term to short-term localization [2].In traditional approaches, robots' locations can be acquired using a fixed router in a predefined area, and the location of a particular robot can be evaluated depending on the distance of the robot from several routers, ultra-wide band (UWB) [3] and Wi-Fi localization [4] are used.However, these approaches depend on external setup and they are essentially used in small-scale environments.
Comparative study on sentimental analysis using machine learning techniques

With the advancement of the Internet and the world wide web (WWW), it is observed that there is an exponential growth of data and information across the internet. In addition, there is a huge growth in digital or textual data generation. This is because users post the reply comments in social media websites based on the experiences about an event or product. Furthermore, people are interested to know whether the majority of potential buyers will have a positive or negative experience on the event or the product. This kind of classification in general can be attained through Sentiment Analysis which inputs unstructured text comments about the product reviews, events, etc., from all the reviews or comments posted by users. This further classifies the data into different categories namely positive, negative or neutral opinions. Sentiment analysis can be performed by different machine learning models like CNN, Naive Bayes, Decision Tree, XgBoost, Logistic Regression etc. The proposed work is compared with the existing solutions in terms of different performance metrics and XgBoost outperforms out of all other methods.
Recent Activities of Frontiers in Education Committee of IEE Japan, from 2021 to 2022

This paper explains our movement of 2021-2022. Agenda is as follows. Technical Committee on Frontier in Education, Cooperation with Ethics Committee, Cooperation with Committee on Social Engagement, Special Topic Session in 2022 Annual Conference of Fundamentals and Materials Society, and Member.
Light People: Professor Guangcan Guo

The Nobel Prize in Physics 2022 was awarded to French physicist Alain Aspect, American physicist John F. Clauser, and Austrian physicist Anton Zeilinger, in recognition of their contributions to the research of quantum information, a clear indication that we are entering the era of quantum information.In China, a scientist has played herald in quantum research since as early as the 1980s. He introduced quantum optics and quantum informatics to China, a virgin land in terms of quantum research back then. That scientist is Academician Guangcan Guo.Out of personal interests and his good sense as a scientist, Prof. Guo took it upon himself to take on quantum optics when little was known about it in China. He trained many students and launched China's first academic conference on quantum optics, which helped to accelerate the development of quantum optics in China.In the early 1990s, he took on another challenge, shifting his research focus to the emerging subject of quantum informatics. His work helped to establish China's current leading position in this interdisciplinary field. Today, China leads the world in quantum USB drives and quantum chips.Now in his 1980s, Prof. Guo is still working tirelessly at the front line of scientific research, doing science popularization, and teaching students. He is ready for the third big challenge of his life-to reveal the mysteries of the classical world and the quantum world.Next, please follow "Light People" into the mysterious "quantum world", and feel the beauty of science.
A High-Efficiency Quantum Memory

The physical platform we use in this thesis is an isotope of the alkali atom rubidium, $$^{87}$$ Rb.
Identifikasi Objek Cagar Budaya Candi Mahligai Berbasis Citra Digital Menggunakan Mask R-CNN

Object detection is determining the existence of an object and its scope and location in an image. Excessive historical relics and it is generally difficult for humans to remember all the names. One of the fields of science that supports in facilitating human work is confidence score. The main problem in confidence score is how to recognize images and make use of the images they capture. The purpose of this research is to identify the image of Mahligai Temple. This research uses the Deep Learning Mask R-CNN algorithm as a detection of image objects that can recognize cultural heritage sites. The application is carried out on the image of Mahligai Temple. The results using Confussion Matrix and obtained an accuracy of 82.0%, precision 78.57% and recall 88.0%. Single Class identification done successfully at the threshold value 0.776 with error percentage of 18%.