Reviewerly/exHarmony huggingface dataset:
NILAI-NILAI PENDIDIKAN KARAKTER DALAM NOVEL BUMI KARYA TERE LIYE DAN IMPLIKASINYA DALAM PEMBELAJARAN BAHASA INDONESIA

ABSTRACT The purpose of this study is to explain the value of character education in the novel Bumi by Tere Liye and how its implication in learning. This research is a qualitative study using descriptive methods. The data source is the novel Bumi by Tere Liye. The value of character education contained in the novel, including: (1) honesty, (2) discipline, (3) curiosity, (4) national spirit, (5) friendly and communicative, (6) fond of reading, (7) social care, and (8) responsibility. In total there are 18 data, the highest value is the value of curiosity character education. Kata Kunci: nilai pendidikan karakter, novel, Tere Liye
On the Application of Computer Technology in the Processing and Analysis of Fuzzy Information in English Interpretation

Abstract This paper discusses the problems existing in the fuzzy information processing in traditional English interpretation and some methods and techniques used in the processing to improve the efficiency of interpretation. At the same time, considering the translation principles that some interpreters must abide by, this paper puts forward a more efficient means of processing and analyzing fuzzy information in English interpretation through computer technology.
ShaneRun System Description to VoxCeleb Speaker Recognition Challenge 2020

In this report, we describe the submission of ShaneRun's team to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2020. We use ResNet-34 as encoder to extract the speaker embeddings, which is referenced from the open-source voxceleb-trainer. We also provide a simple method to implement optimum fusion using t-SNE normalized distance of testing utterance pairs instead of original negative Euclidean distance from the encoder. The final submitted system got 0.3098 minDCF and 5.076 % ERR for Fixed data track, which outperformed the baseline by 1.3 % minDCF and 2.2 % ERR respectively.
GANs & Reels: Creating Irish Music using a Generative Adversarial Network.

In this paper we present a method for algorithmic melody generation using a generative adversarial network without recurrent components. Music generation has been successfully done using recurrent neural networks, where the model learns sequence information that can help create authentic sounding melodies. Here, we use DC-GAN architecture with dilated convolutions and towers to capture sequential information as spatial image information, and learn long-range dependencies in fixed-length melody forms such as Irish traditional reel.
Research on Teaching Method of Computer Application Course Based on Evidence-based Teaching Method

Abstract The basis of computer application is not only useful for office automation, but also useful for the study of cognitive disciplines. For example, if you learn how to surf the Internet, you will use network resources to collect Chinese extracurricular books and find relevant literature. The experimental research includes the design of questionnaire survey, the development of teaching practice, the collection and collation and analysis of experimental data. This paper demonstrates the effectiveness of evidence-based teaching in computer application experiment teaching through sufficient data.
Learning Dyadic Data and Predicting Unaccomplished Co-Occurrent Values by Mixture Model

Dyadic data which is also called co-occurrence data (COD) contains co-occurrences of objects. Searching for statistical models to represent dyadic data is necessary. Fortunately, finite mixture model is a solid statistical model to learn and make inference on dyadic data because mixture model is built smoothly and reliably by expectation maximization (EM) algorithm which is suitable to inherent spareness of dyadic data. This research summarizes mixture models for dyadic data. When each co-occurrence in dyadic data is associated with a value, there are many unaccomplished values because a lot of co-occurrences are inexistent. In this research, these unaccomplished values are estimated as mean (expectation) of random variable given partial probabilistic distributions inside dyadic mixture model.
Review on Usage of Hidden Markov Model in Natural Language Processing

Hidden Markov Model (HMM) is a probabilistic graphical model, which allows us to calculate a sequence of unknown or unobserved variables from a set of observed variables. Predicting weather conditions (hidden) on the basis of types of clothes worn by someone (observed) is a simple example of HMM. The Markov process assumption is based on a simple fact that the future is dependent only on the present not on the past. HMM are useful as they are being able to model stochastic processes. Again human spoken language is a probabilistic language. Hence using a stochastic modeling technique, i.e., HMM, we can be able to achieve remarkable results in relatively limited scopes.
Learning to map between ferns with differentiable binary embedding networks

Current deep learning methods are based on the repeated, expensive application of convolutions with parameter-intensive weight matrices. In this work, we present a novel concept that enables the application of differentiable random ferns in end-to-end networks. It can then be used as multiplication-free convolutional layer alternative in deep network architectures. Our experiments on the binary classification task of the TUPAC'16 challenge demonstrate improved results over the state-of-the-art binary XNOR net and only slightly worse performance than its 2x more parameter intensive floating point CNN counterpart.
DRAG REDUCTION AND DEGRADATION CHARACTERISTICS OF NATA DE COCO SUSPENSION IN SPIRAL PIPE

Recently, the research of energy efficiency in some areas is an important topic to be developed. In fluid flow, some techniques are developed in order to decrease the pressure drop. Therefore, some researchers add several kinds of additives in order to obtain drag reduction. The purpose of this research is to investigate the effect of nata de coco fiber suspension due to the drag reduction characteristic in the spiral pipe. The experiment was conducted from low-to high-Reynolds number, up to 20,000. The percentage of drag reduction was calculated using the obtained experimental data, in presence of the drag reducing agent. The results showed that the addition of nata de coco fiber suspension into water can reduce drag either on circular pipe or spiral pipe. The maximum drag reduction of concentration 60 ppm for spiral pipe is about 24.7%, and for circular pipe is about 22.1%, at a Reynolds number of about 19,000. It was observed that the drag reduction tended to be constant, with an increase in concentration after 60 ppm. The nata de coco fiber solution tends to spread and flow straightly at the center of the experimental pipe, and a water layer develops at the wall. It reduces the wall friction and reaches the maximum drag reduction. Further, the nata de coco fiber suspension is good for the mechanical degradation effect. Based on this research, it can be concluded that nata de coco can be considered as a drag reducing agent.
Introduction: A sociosemiotic exploration of identity and discourse

Abstract Among the categories of the telecom and internet frauds, the online romance scam is of particular concern for its sharp rise of victim numbers and the huge amount of cost. A social semiotic approach could be used to investigate the victim identity of the online romance scam from the aspects of the (re)construction and interpretation of discursive practices. The range of papers in this section shows that the study of text, context and the way that people use semiotic resources to produce communication, to create and manage events and to interpret them.
Construction and Optimization of Educational Technology Course Knowledge Network

Teachers should not only understand the basic knowledge of the course, but also master the overall structural characteristics of the course, grasp the important and difficult point of the course, and optimize the knowledge structure of the course. This paper mainly applies complex network to the analysis of course knowledge structure to construct and optimize the knowledge network of Educational Technology course. Firstly, the textbook and syllabus of Educational Technology course are used as a data source, and the course knowledge network model is constructed. Secondly, the knowledge nodes and their relationships are determined, and the course knowledge network is constructed. Thirdly, by using topological sorting based on directed graph, the course knowledge structure is optimized. And the pre-optimized and optimized course knowledge network are compared and analyzed, it shows the optimized course knowledge structure has superiority. It proves that the optimized course knowledge structure is more hierarchical, sequential and structural, which can highlight the main line of knowledge and clear the learning ideas. Finally, according to the results of comparative analysis of the pre-optimized and optimized course knowledge network, the teaching suggestions are proposed, and it is to realize the aim of optimizing teaching.
Big Data in Preschool Dance Multimedia Teaching Dance Posture Correction

Abstract With the explosive growth of data and the enhancement of data openness, big data is quietly changing our daily work and life. This article mainly studies the application of big data in preschool dance multimedia teaching dance posture correction. Using a small sample control method, the body characteristics of the research subject were measured before the experiment and used as the index before the measurement; after 8 weeks of learning, the measurement was performed again and used as the index after the measurement. Then, the principle of feature plane similarity matching is used to analyze the motion posture. The experiment found that after 8 weeks of multimedia correction training, mild pelvic backwards accounted for 75% and moderate 22.2%. The results show that big data plays a technical support role in the correction of dance posture in preschool dance multimedia teaching.
Can the state of relevant neurons in a deep neural networks serve as indicators for detecting adversarial attacks?

We present a method for adversarial attack detection based on the inspection of a sparse set of neurons. We follow the hypothesis that adversarial attacks introduce imperceptible perturbations in the input and that these perturbations change the state of neurons relevant for the concepts modelled by the attacked model. Therefore, monitoring the status of these neurons would enable the detection of adversarial attacks. Focusing on the image classification task, our method identifies neurons that are relevant for the classes predicted by the model. A deeper qualitative inspection of these sparse set of neurons indicates that their state changes in the presence of adversarial samples. Moreover, quantitative results from our empirical evaluation indicate that our method is capable of recognizing adversarial samples, produced by state-of-the-art attack methods, with comparable accuracy to that of state-of-the-art detectors.
THE DEVELOPMENT OF SPIRITUAL AND MORAL QUALITIES OF THE INDIVIDUAL AS THE BASIS FOR THE FORMATION OF THE CIVIC POSITION OF STUDENTS

The problem of development of spiritual and moral qualities of modern students is discussed. It is noted that the orientation of young people to spiritual and moral values and the formation of personal qualities in accordance with this orientation develops in a complex conditions. In this regard, the task set by our state and society becomes urgent – to educate a spiritual and moral citizen of the country, able to solve complex problems not only personal, but also social. The program of formation of a civil position of student youth is presented. It is noted that it promotes formation of development of spiritual and moral qualities of the personality of student youth.
rProfiler -- Assessing Insider Influence on Enterprise Assets

Insider threat is a well-recognized problem in the cyber-security domain. There is good amount of research on detecting and predicting an insider attack. However, none of them addresses the influence of an insider over other individuals, and the spread of impact due to direct and indirect access to enterprise assets by having such influence. In this work, we propose a graph-based influence profiling solution called rProfiler that analyzes the data from multiple sources to determine the influence spread and calculate the probability of loss of data from an affected device using pertinent graph features. We also highlight multiple enterprise scenarios that may benefit from this work.
Assessing students’ errors in mathematical translation: From symbolic to verbal and graphic representations

Translation skills are very important possessed by students, but currently, there are still many students who have difficulty in translating between representations. The purpose of this study is to analyze students' errors in translating from symbolic representations to verbal and graphic representations. This research was descriptive study with qualitative approach. Tests are given to junior high school students. From the results of data analysis, it is obtained that in translating from symbolic to verbal forms (problems in daily life) that are following the given system of equations, students are still unable to make representations correctly. When students are asked to translate into graphical form, students are still unable to draw complete graphs and errors made by students are misinterpretation and implementation errors, so they cannot maintain the semantic congruence between source representation and target representation. Based on this, it is necessary to make a learning plan that can improve students’ ability to translate between representations.
Pengaruh Model Pembelajaran PBL Terhadap Aktivitas Belajar Dan Hasil Belajar Siswa Pada Materi Asam Basa

The objectives of this study is (1) to determine whether the learning activities of students who were taught with the Problem Based Learning model were higher than those of students who were taught using the Direct Instruction learning model (2) to determine whether the learning outcomes of students who were taught with the Problem Based Learning model is higher than the learning outcomes of students who are taught with the Direct Instruction learning model (3) to determine whether there is a correlation between student learning activities and student learning outcomes. The research instrument consisted of test instruments and non-test instruments. The analysis technique used is the right side test and correlation test or test (product moment). From the results of data analysis of learning outcomes obtained (1) student learning activities that were taught with the Problem Based Learning learning model (86,20) were higher than the learning activities of students who were taught with the Direct Instruction learning model (79,86) (2) learning outcomes students who are taught with the Problem Based Learning model (83.75) are higher than the learning outcomes of students who are taught with the Direct Instruction learning model (71.94) (3) there is a positive and significant correlation between student learning activities and student learning outcomes. taught by the Problem Based Learning model, the contribution of student learning activities to learning outcomes was 21.92% while 78.08% was caused by other factors.
An Overview of Innovations in Online Learning

Developments in technology have dramatically increased access to learning materials, and are rapidly changing the education landscape. With the rise of the internet and mobile phone technology, more education and learning can happen online—on laptop computers, tablets, and mobile phones. Online-based coursesOnline-based courses provide learning opportunities to everyone with internet access. Learners interested in a particular topic are brought together to learn collaboratively through discussion forums, tweets, and other internet resources. At primary school level, from Kindergarten to Grade 12 (K−12), online learning technologies have been successfully piloted and implemented in different parts of Asia. Many models have successfully increased student motivation and have helped to break the cycle of rote learning. Innovations in e-learning and blended learning provide new opportunities for learners and nations in Asia and the Pacific, as countries modernize their education, training, and skills development sectors. There is an unmistakable need to incorporate these new technologies to support the drive for universal access, and for enhancing quality and relevance education and training in these countries.
Continuous ZNN Models for Computation of Time-Varying Eigenvalues and Corresponding Eigenvectors

Computation of eigenvalues as well as corresponding eigenvectors of a time-varying matrix (i.e., with time-dependent elements) is attractive. A continuous Zhang neural network (ZNN) model is developed for computing the eigenvalues and corresponding eigenvectors of a time-varying real symmetric matrix. The global convergence to the theoretical eigenvalues and corresponding eigenvectors is proved by theoretical analysis. Meanwhile, the robustness analysis is also presented. In addition, the ZNN model is a dynamic system in essence, which indicates the potential practical implementations and applications. Moreover, numerical experiments are conducted in this paper, and the results verify the effectiveness of the ZNN model. Besides, an extensional ZNN model is discussed in the Appendix.
Application of Data Mining in the Coal Enterprises in ERP

Abstract With the development of science and technology, and to meet the need of the coal enterprise development, the ERP system has been more and more used in coal enterprises day-to-day management, and has played the increasing important role. With the wide application of ERP system, how to deal with a lot of data and information for reasonable application becomes the focus of attention. Data mining is an effective analysis and processing of various data technology, and is being applied in the coal enterprise ERP system. Firstly, the technology of data mining is introduced. Secondly the concrete application of data mining technology in coal enterprises ERP system is introduced and analysed.
Learning Contextualised Cross-lingual Word Embeddings for Extremely Low-Resource Languages Using Parallel Corpora.

We propose a new approach for learning contextualised cross-lingual word embeddings based only on a small parallel corpus (e.g. a few hundred sentence pairs). Our method obtains word embeddings via an LSTM-based encoder-decoder model that performs bidirectional translation and reconstruction of the input sentence. Through sharing model parameters among different languages, our model jointly trains the word embeddings in a common multilingual space. We also propose a simple method to combine word and subword embeddings to make use of orthographic similarities across different languages. We base our experiments on real-world data from endangered languages, namely Yongning Na, Shipibo-Konibo and Griko. Our experiments on bilingual lexicon induction and word alignment tasks show that our model outperforms existing methods by a large margin for most language pairs. These results demonstrate that, contrary to common belief, an encoder-decoder translation model is beneficial for learning cross-lingual representations, even in extremely low-resource scenarios.
Perancangan Sistem Deteksi Dini Bencana Banjir Menggunakan Teknik Pengiriman DTMF Berbasis Modul RF 433 Mhz Dan Arduino

Flood is one of the unpredictable natural disasters, especially in the rainy season. There are many effects for many people, such as they lose their property and sometimes have many victims due to floods. So that, estimation of water level is important to detect the basic risk of flooding. In this study used the Water Level (TMA) in form of a short message technique which is can be sent from radio waves and river water level sensors. The value of the sensors to know the highest river water level itself, so it does not need signals, internet networks and also pulse for it. The final result of this study is the water level information which is normal status, standby I, standby II, standby III or standby IV.Keywords: RF 433MHz, Flood, Arduino, Early Detection
Development of Basic English Grammar Teaching Materials Based on Situational Approach in English Language Education Study Program of Universitas Muslim Indonesia

This study is a research development of Basic English Grammar teaching materials in the English Language Education Study Program of the Faculty of Literature UMI. This study aims to obtain more effective teaching methods between Oral Approach and Teacher Center Learning or lecture methods. This research was conducted using the pseudo experiment method (quasi experimental research). Quasi Experimental Design in this design was used by two groups of subjects. One group was given a specific treatment (experiment), while the other was used as a control group. Both groups were given pre-test measurements. After that the group given treatment (Situational Based Approach) is an experimental group, then both groups are done measurement (post-test) or acquisition. Pre-test Group - Treatment - Post-test. Research site at UMI Faculty of Literature. The number of respondents as many as 50 students is divided into two groups, namely the experiment group and the control group of 25 people each. The results showed that there was a significant difference between the Oral Approach method and the Teacher Center Learning method or the lecture method in improving the student's learning outcomes in Basic English Grammar learning. The cause is that the Oral Approach method has a higher average and improvement compared to the Teacher Center Learning method or lecture method because the Oral Approach method brings more active students into learning. Although given the same material at the same time, but in oral approach method therefore students are active in the learning process. So, lecturers are just facilitators. While in the method of lecture students are only fixated on the explanation of teachers and students are less active in learning. Therefore, oral approach teaching method is more effective than Teacher Center Learning method on Basic English Grammar teaching.
MIL Competency Framework: Mapping Media and Information Competencies

This article explores a literature review on different proposals to assess media and information literacy (MIL) competencies in citizens seeking to define the fundamental MIL skills and competencies to be considered in national curricula and assessment schemes. The study is based on qualitative content analysis to map and systematize the main MIL frameworks, research reports, and their practical applications/experiences. This qualitative technique allows the combination of categories (dimensions) and correlation of individual indicators (skills and capabilities) to group subcategories (components). The study inquires Unesco’s framework, as well as the authors upon which this theoretical approach was built, together with the European Commission’s views on media education. It gathers their principal propositions on media competence assessment and sets a reflection on information literacy and Educommunication as a contribution strongly developed in the Ibero-American context. A broad analysis of digital competencies related to media and information literacy is also included in the study. A new interpretation is given to the studied concepts to draw a structured systematization of competences on media and information literacy that sets a framework to assess and design MIL programs, actions or curricula. Finally, it proposes a map of skills and competences in MIL that allows the future creation of methodologies and strategies for the visibility, promotion, strengthening or evaluation of MIL.