Reviewerly/exHarmony huggingface dataset:
Application of Big Data Visualization in Urban Planning

Abstract During the past ten years, with the process of urbanization accelerates, urban population has increased sharply. Traffic congestion, noise pollution, garbage treatment and other problems, which make the traditional urban planning methods difficult to shoulder this heavy responsibility. At the same time, intelligent city and the construction of informationize is also developing rapidly, the practice and research of big data in urban planning industry are widely used. Large scale data visualization is one of the most important steps in big data. Not only can the data be expressed in visible form to improve the efficiency of data analysis, but also human-computer interaction can be carried out. To overcome these problems, this paper studies the problem of urban planning based on large scale data visualization. Firstly, it extends the concept and model of big data visualization to the significance and framework of applying big data visualization to urban planning. Then through the case of visualization of traffic data and environmental sound data, we can see that both quality and efficiency have been significantly improved. Furthermore in order to stimulate future research in this field, we also highlight the major opportunities and challenges, as well as potential important research directions for urban planning.
Face Identification System using Deep Learning Method at Low Lighting Resources

The topic of identifying people in low light using near infrared cameras has recently attracted increased attention in biometric systems due to its benefits of the less sensitive to illumination levels. Currently, deep learning facial recognition models provide the best accuracy results for various databases of visible faces. Unfortunately, the desired performance cannot be achieved using only pre-trained deep learning facial recognition models for near infrared image databases. In this paper, we present a NIR-VIS image translation model which is available to translate from near infrared facial images into their corresponding visible images. The evaluation performances are presented by applying the pre-trained face embedding model on two different NIR databases of facial images.
Developing of Thesaurus Software to Increase the Writing Quality of the Thesis of the Students at the German Language Department

The use of academic vocabulary is very important to increase the writing skills and quality of the academic writing of the students. Therefore, Thesaurus software needs to be developed that contains about the academic vocabulary that help the student’s writing and increase the quality of their academic writing, and to reduce the plagiarism. The purposes of the research are; (1) to develop of German language vocabulary with a Thesaurus software that increase the quality of academic writing in German (2) to see the effectiveness of German language vocabulary with a Thesaurus software in increasing the quality of academic writing. The special purpose of the research is increasing the quality of student’s academic writing from German Language Department at the Universitas Negeri Medan with the use of Thesaurus software for German language vocabulary. The method used is the ADDIE Model with five phases: Analysis, Design, Development, Implementation and Evaluation. The data is taken from the academic writing of the students of German Language Department and the books that used in the Wissenschaftliches Schreiben’s (Academic Writing) course and then developed into the German Language academic vocabulary Thesaurus software.
Measurement of User Satisfaction Level in the Bina Darma Information Systems Study Program Portal Using End User Computing Satisfaction Method&#x0D;

Information systems study program portal is a website developed by Bina Darma University that aims to be a media for promotion and academic information system study programs. User satisfaction is the most important thing to be a benchmark for developers of information systems study program portals to improve the quality of their websites so that users are more satisfied and do a lot of searching activities, especially academic activity searches. But so far the information systems study program portal developer does not yet know the shortcomings of the information system study program portal, so analysis is needed to measure the level of user satisfaction. In an effort to achieve User Satisfaction with the portal of the bina darma information system study program which has the si.binadarma.ac.id domain, researchers used the end user satisfaction method (EUCS). The EUCS instrument includes five components: content, accuracy, format, ease of use, and schedule. The data in this study were collected with a questionnaire instrument that was distributed to students from the information systems study program. Furthermore, the data obtained were processed using SPSS software version 24. The sampling technique used in this study was simple random sampling. The results of this study are expected to be a reference to improve the quality of information systems study program portals.&#x0D; &#x0D; Keywords: website, user satisfaction, EUCS
Two-Stream Time Sequential Network Based Hand Gesture Recognition Method Using Radar Sensor

This paper proposes a deep learning based twostream time series hand gesture recognition method using the frequency modulated continuous wave (FMCW) radar. Firstly, we collect the hand gesture data by the FMCW radar, and the range and Doppler of the hand gesture are estimated by the 2 dimensional Fast Fourier Transform (2D-FFT). Then, the angle of hand gesture is estimated by Multiple Signal classification (MUSIC) algorithm. Afterward, we construct the Range- Doppler Map (RDM), and generate the Angle-Time Map (ATM) via multiframe accumulation. The interference in RDM is filtered out by peak interference cancellation, and the hand gesture feature in RDM and ATM are enhanced by wavelet transform. A systematic of two-stream time series neural network is designed for gesture feature extraction and classification. The experimental results show that the recognition accuracy rate for each type hand gesture of the proposed method is higher than 95%.
How to Answer Comparison Questions

“Which city has the larger population, Tokyo or New York?”. To answer the question, in general, we necessarily obtain the prior knowledge about the populations of both cities, and accordingly determine the answer by numeric comparison. Using Machine Reading Comprehension (MRC) to answer such a question has become a popular research topic, which is referred to as a task of Comparison Question Answering (CQA). In this paper, we propose a novel neural CQA model which is trained to answer comparison question. The model is designed as a sophisticated neural network which performs inference in a step-by-step pipeline, including the steps of attentive entity detection (e.g., “city”), alignment of comparable attributes (e.g., “population” of the target “cities”), contrast calculation (larger or smaller), as well as binary classification of positive and negative answers. The experimentation on HotpotQA illustrates that the proposed method achieves an average F1 score of 63.09%, outperforming the baseline with about 10% F1 scores. In addition, it performs better than a series of competitive models, including DecompRC, BERT.
A Pragmatic Study of Junior High School Teachers’ Speech Act of Criticism from the Perspective of Politeness Principle

Recently, there are limited specific researches on the pragmatic strategies of teachers&amp;#39; criticism from the angle of the Politeness Principle, among which most of them argue that teachers should adopt appropriate politeness strategies when criticizing students. However, only a few researchers point out that Leech&amp;#39;s Politeness Principle is &amp;quot;other&amp;quot; oriented and neglects &amp;quot;self,&amp;quot; which is too absolute, ideal, and unsuitable in teacher and student relations. In this paper, the author illustrates the true nature of politeness in teacher-student relations is that teachers should pay attention to self, show politeness to the students, and consider the third party (parents). Finally, the writer illustrates some politeness strategies, including criticizing with a sense of humour, criticizing in vague language, adopting empathy and showing politeness to a third party to show appropriate politeness to the students to make the criticism effective. The purpose is to make some middle school teachers recognize how to criticize appropriately.
Development of Problem Based Learning Book for Indonesian Language and Literature Subject at Junior High School"

Problem-based learning connects new problems that exist in daily life. It optimizes the ability to think through the process of group work and experimental activities. The students have difficulties in solving problems. They have little experience and are not highly motivated. It makes them unable to explore what students have. The conventional methods lack of training in critical thinking for students. This causes students to lack confidence to play an active role in the learning process. Based on these problems, the present study therefore developed the Indonesian language learning materials for Grade 7 at the junior high school level using the Problem Based Learning model.
Research on Design and Experience of Immersive Virtual Reality Psychological Relaxation Game Based on Image

Abstract With the continuous progress of digital media technology and the rapid development of the game entertainment industry, people have put forward more demands on the display mode and immersion of games. Immersive stereoscopic display game based on game engine supports multi-machine and multi-projection display under various display environments, and has good stereoscopic effect and immersion feeling. The effect of psychological relaxation is highly related to immersive virtual reality environment. The relaxing effect in immersive environment is better than that in non-immersive environment. The more immersive the environment, the stronger the sense of presence, and the better the relaxing effect. With the improvement of virtual reality technology and the popularity of equipment, it provides a convenient and feasible way for the general public to obtain self-discipline of psychological relaxation. The effect of psychological relaxation is highly correlated with the immersive virtual reality environment. The relaxation effect in the immersive environment is better than that in the non-immersive environment. The more immersive the environment, the stronger the sense of presence and the better the relaxation effect.
Design and implementation of adaptive technology for teaching mathematics to school children based on integrated diagnostic approach to subject preparation and competence development

The development of school teaching systems to enable effective adaptive communication of information requires specific pedagogical solutions to several important theoretical and methodological problems .These include 1) the discernment of basic characteristics needed to diagnose and improve the quality of subject preparation for schoolchildren, 2) clarifying the role of the teacher in the structure of adaptive learning process, and 3) finding ways to integrate adaptive content into the framework of courses on mathematics. The purpose of our study was to determine theoretical and methodological foundations of teaching mathematics to schoolchildren taking into account their level of ability with the consequent development of appropriate adaptive content. The basic characteristics that underpin the concept of adaptive learning which contributes to both individual profiles of student ability to learn and subsequent success outcomes are: proficiency, motivation to learn and level of mathematical knowledge. The evaluation of individual profile structure of schoolchildren determines the choice of methodologies for presentation of adaptive content in ways allowing development and motivation. The system of educational process management developed in this way includes both content-methodical and procedural-technological components. This makes it possible to automatically evaluate the level of each students' mathematical training (knowledge, motivation, development) and to ensure continuous improvement. This system can also be used by secondary teachers of mathematics as a part of extracurricular activities, or as a distance learning support. In addition, the recommendations for structuring multi-level problem material can be used by mathematics teachers to self-construct adaptive sets tasks at various stages of teaching mathematics. As a result, students have the opportunity to improve their own profile of learning success, particularly by solving a chain of tasks.
IMS-LIP-KM: Extension of IMS-LIP Standard for Modeling a New User Profile

This research presents a solution for modeling the user profile of E-Learners.This solution combines the cognitive and technological sides.It's based on known standards and methods.IMS-LIP standards are extended and adapted so as to build an architecture that better solves problems related to cold start and information overload.This solution was implemented and the experiment was conducted in order to test how efficient it is.The experiments show results that are satisfying and that outperform similar solutions.
“Digital Gangsters”: Are Facebook and Google a Challenge to Democracy?

Amsterdam Law Forum (ALF) is the student-run 'International Law Journal' of VU University. Every year ALF publishes a winter, spring, and summer issue. The journal consists of three sections; scientific articles, opinion articles, and commentaries. As of this year, ALF also creates a section for inaugural speeches. In addition, ALF hosts a conference in spring with a relevant legal theme, where renowned speakers are invited to share their perspectives. Overall, ALF is a topical journal that provides a platform for established scholars and young academics to share knowledge, opinions and experiences and to make contributions to the international law discourse. Staff, PhD students and master students who have written a very good thesis are invited to submit an article to ALF. What is learned in the cradle is carried to the tomb: we are looking forward to sharing your articles on our website!
Ink protection of security documents

Security documents are valuable documents protected by a mixture of security fea­tures, starting from security paper, inks, printing techniques, and additional security prop­erties. However, this article will discuss the main security features, supported by genuine and forged examples, to demonstrate the most frequent modern use of security features to protect valuable documents, and giving useful hints to detect forgeries and imposters as well.
THE INFLUENCE OF ICE BREAKER TO STUDENTS’ MOTIVATION IN TEACHING ENGLISH

This research is aimed at exploring ice breaker technique in teaching English for student at Junior High School in Cimahi. Based on the important of teaching English in Indonesia as foreign language. So by doing ice breaking before learning, it is expected that students can focus on the learning English process. In this research the writer used case study and qualitative research method. The subject of this research was on of an English teacher at One of Junior High School in Cimahi. The instrument of this research are observation, and interview. The result of this research is students’ to be focus and fun on learning English in the class.
Image superresolution technique: A novel approach for leaf diseased problems

Superresolution is a concept to increase the resolution. The main objective of this paper is the study of iterative curvature based method for super-resolving low resolution of a leaf diseased images. The domain specific prior is incorporated into superresolution by the means of iterative curvature SR based estimation of missing high frequency details from infected leaf images. The model is composed of two step pixel filling approach. Through this proposed work, fine edges of SR images are preserved without applying complex mathematical algorithms based on wavelet, fast curvelet, etc. In this paper, we have validated proposed scheme over 9 infected leaf images of various crops like soybean, cotton, rose, citrus family etc. shows better result in visual as well as subjective quality as that of complex multi frame SR algorithms like reconstruction and registration along with less computational time. This concept is most useful for agricultural expert for helping our farmers for exact leaf disease detection and accurate remedial actions. The experimental result shows the best visible SR result of an infected leaf along with MSE and PSNR i.e. Statistical results. It also shows the comparison of proposed method with the existing techniques successfully.
Automatic Phase Picking From Microseismic Recordings Using Feature Extraction and Neural Network

High-accuracy microseismic phase picking is fundamental to microseismic signal processing. Phase picking methods based on deep learning show great potential dealing with low signal to noise ratio (SNR) data but need enormous training data. However, it's not easy to obtain a big size of field datasets and label them manually to train the neural network. In this paper, a novel method is proposed by applying feature extraction (Gammatone Feature) and neural networks to pick phases automatically. The feature extraction scheme aims to train the neural network using a relatively small size of training datasets. To test the performances of the proposed method, synthetic datasets were obtained by numerical simulation and used to train the neural network. Both synthetic datasets and field datasets were used to test the neural network for picking P- and S-phases of microseismic events. The results of phase picking illustrate that: (1) feature extraction scheme in the training stage can help reduce the size of training datasets; (2) The neural network can be trained well just by synthetic data and phase picking results are accurate and satisfying when the method was tested by both synthetic and field datasets.
Wavelet Transform Application Based on Matlab Simulation

Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) are two combined technologies to provide the spectral efficiency and high data rate required for 4G, 5G wireless systems. Discrete Wavelet Transform (DWT) is presented as an alternative for Fast Fourier Transform (FFT) since there is no necessity for Cyclic Prefix (CP) due to the overlapping properties of DWT. By a simple replacement of the FFT with DWT in MIMO OFDM system, an improvement of performances has been detected which leads to a new system scenario DWT-based MIMO-OFDM. In this thesis, such a system is simulated and the performance of Bit Error Rate (BER) is analyzed to determine the different types of wavelets in various channel condition with different modulations (4, 16, 64 -QAM). Therefore, DWT-based MIMO-OFDM in comparison with DFT-based MIMO-OFDM system was investigated using MATLAB simulation software. And besides, I would like to refer to use Neural Network algorithms to replace Wavelet transform in the next research.
Solving Delete Free Planning with Relaxed Decision Diagram Based Heuristics

We investigate the use of relaxed decision diagrams (DDs) for computing admissible heuristics for the cost-optimal delete-free planning (DFP) problem. Our main contributions are the introduction of two novel DD encodings for a DFP task: a multivalued decision diagram that includes the sequencing aspect of the problem and a binary decision diagram representation of its sequential relaxation. We present construction algorithms for each DD that leverage these different perspectives of the DFP task and provide theoretical and empirical analyses of the associated heuristics. We further show that relaxed DDs can be used beyond heuristic computation to extract delete-free plans, find action landmarks, and identify redundant actions. Our empirical analysis shows that while DD-based heuristics trail the state of the art, even small relaxed DDs are competitive with the linear programming heuristic for the DFP task, thus, revealing novel ways of designing admissible heuristics.
ANALISIS VOLATILITAS CRYPTOCURRENCY, EMAS, DOLLAR, DAN INDEKS HARGA SAHAM (IHSG)

This research was conducted to analyze cryptocurrency volatility. Gold, Dollar Index, and Composite Stock Prices Index in the Indonesia Stock Exchange (IDX) variable are used as independent variables. The cryptocurrency objects in this study are Bitcoin and Ethereum which have the largest market capitalization. The data used in this study is from 1st January 2017 to 31st December 2019. This study uses GARCH analysis. The result of this study indicates that the volatility of Bitcoin and Ethereum is not influenced by other variables, but it is influenced by the prices of each Bitcoin and Ethereum at past prices. This shows that the cryptocurrency market is an inefficient market.
Relation Extraction via Attention-Based CNNs using Token-Level Representations

Relation extraction is an important task in the field of natural language processing (NLP). Most existing methods usually utilize word-level representations, ignoring massive information from the texts. To address this issue, we utilize BERT to pretrain token-level bidirectional contextual representations from raw sentences, then employ a Transformer encoder to train token-level representations mentioned above again. To capture the most important information of the sentences, we employ a convolutional neural network (CNN) with entity-aware attention to extract high-level features from these token-level representations of the sentences. On the SemEval-2010 Task 8 dataset, our model achieves 87.8% F1-score and outperforms several previous models without rich prior knowledge.
MACHINE LEARNING TECHNIQUES TO PREDICT IN-HOSPITAL CARDIOVASCULAR OUTCOMES IN ELDERLY PATIENTS PRESENTING WITH ACUTE MYOCARDIAL INFARCTION

The ability to predict the cardiovascular outcomes in elderly patients presenting with acute myocardial infarction can aid in clinical decision-making. We sought to determine whether machine learning techniques can be used to predict in-hospital cardiovascular mortality and major bleeding after the
A critical review on “Halliday’s Introduction to Functional Grammar” by M. A. K Halliday, revised by Christian M. I. M Matthiessen (2014)

Matthiessen ( 2014) is considered to be an invaluable textbook for students and researchers of linguistics, especially of functional linguistics, discourse analysis and literary studies and also for those with broader educational concerns.As a novice researcher in Systemic Functional Grammar, a critical review by chapters of this edition has been carried out with great efforts.An evaluation on the features of this edition from various perspectives has also been implemented.