Reviewerly/exHarmony huggingface dataset:
Latent semantic network induction in the context of linked example senses

The Princeton WordNet is a powerful tool for studying language and developing natural language processing algorithms.With significant work developing it further, one line considers its extension through aligning its expert-annotated structure with other lexical resources.In contrast, this work explores a completely data-driven approach to network construction, forming a wordnet using the entirety of the open-source, noisy, userannotated dictionary, Wiktionary.Comparing baselines to WordNet, we find compelling evidence that our network induction process constructs a network with useful semantic structure.With thousands of semanticallylinked examples that demonstrate sense usage from basic lemmas to multiword expressions (MWEs), we believe this work motivates future research.
English-Myanmar Supervised and Unsupervised NMT: NICT’s Machine Translation Systems at WAT-2019

This paper presents the NICT's participation (team ID: NICT) in the 6th Workshop on Asian Translation (WAT-2019) shared translation task, specifically Myanmar (Burmese) -English task in both translation directions.We built neural machine translation (NMT) systems for these tasks.Our NMT systems were trained with language model pretraining.Back-translation technology is adopted to NMT.Our NMT systems rank the third in English-to-Myanmar and the second in Myanmar-to-English according to BLEU score.
Current Trends in the Study of Object-Oriented Programming in Higher Education

The article examines the current methodological and technological problems of software development, based on an object-oriented approach in the field of programming. The relevance of the topic is determined by the general need to develop a methodology for teaching object-oriented programming based on object-oriented design. In this paper the problems of teaching object-oriented programming to students studying at the Faculty of Mathematics majoring in teacher education are formulated. The methodology for development of object-oriented projects related to the implementation of mathematical abstractions and structure classes is proposed. The object-oriented programming enables one to take advantage of the object-oriented approach not only at the design stage, but also at the stage of their implementation, testing and maintenance. The creation of object-oriented modeling projects for mathematical systems and structures facilitates the development of skills for problem formulation and highlighting abstractions and objects of a given subject area and the relations between them.
The Effectiveness of Adobe Flash CS5 Learning Media on Explanatory Text Material in Public Senior High School 1 Padang Bolak

The aims of this study is to find out the effectiveness of Adobe Flash CS5 Learning Media. This research was carried out in Public Senior High School 1 Padang, Bolak 2018/2019 Academic Year. Implementation of treatment (treatment) in the form of learning activities that are tailored to the education calendar. The population of this research and development are students of Public Senior High School 1 Padang Bolak. The result of this study The effectiveness of student learning outcomes tests got an average score of 81% with the criteria of "good" before using Adobe Flash CS5 learning media on learning to write explanatory texts got an average score of 68.7% with the criteria of "enough".
Colour fast‐match for precise vehicle retrieval

The explosive growth of vehicles has increased the importance of intelligent traffic system. However, compared with face recognition, vehicle retrieval has not attracted the attention of researchers in vision community. Precise vehicle retrieval has always been a challenging task because it requires the retrieval of all vehicles with the same visual attributes from a large number of vehicles with subtle visual differences. To handle this, the authors propose to implement precise vehicle retrieval using an improved fast affine matching colour image retrieval method based on the features of annual inspection label area. Moreover, regional colour constant and hue and saturation feature are introduced to the proposed method so as to settle the illumination change problem in the real surveillance scene. To fully evaluate the proposed algorithm, they perform experiments on the ReIDcar and VehicleID datasets, which differ in data scale and image quality. The experimental results show that the presented algorithm outperforms traditional methods in vehicle retrieval. It is verified that the extracted features and the feature matching method can distinguish subtle differences between vehicles.
High-speed 3D shape measurement with the multi-view system using deep learning

In this paper, we propose a high-speed three dimensional (3D) shape measurement with the multi-view system using deep learning. Common stereo matching methods are based on block-matching or graph cuts to build the global correspondence of stereo images and obtain the dense disparity map. For fringe projection profilometry (FPP), a large number of stereo matching algorithms have been proposed to enhance the accuracy and computational efficiency of stereo matching and acquire the disparity map with sub-pixel precision by using phase constraint, geometric constraint, and depth constraint. However, the universality and precision of these methods are still not enough which is difficult to meet high-precision and high-efficient 3D measurement applications. Inspired by deep learning techniques, we demonstrate that the deep neural networks can learn to perform stereo matching after appropriate training, which substantially improves the reliability and efficiency of stereo matching compared with the traditional approach. Besides, to acquire 3D results with high performance, the optimal design of the patterns projected by the projector is discussed in detail, and the relative spatial positions between the cameras and the projector are carefully adjusted in our multi-view system. Experimental results demonstrate the stereo matching method using deep learning provides better matching efficiency to realize the absolute 3D measurement for objects with complex surfaces.
Students Error Analysis In Using Past Continuous Tense

The purpose of this study was to analyze the students’ error in using past continues tense. The specific objectives were to analyze kinds of error made by the students, to analyze the dominant kind of the students’ error and further more to found out their probably causes. In analyzing data, the writer were giving test to the students to measure the students’ results of their ability and analyze their cases in their study on using past continues tense. The writer took points in every student works, counted it and analyzed. This study were using quantitative descriptive research, in which include counted on analyzed and present the result of study by described on concluding it. The data took from the population of the second grade of SMP Muhammadiyah Aimas were include two class and the writer took the sample from12 (twelve) students from one class. The students of this study had been studied the theory of past continues tense before it. First step in collecting data the writer gave explanation related the theory of past continues tense to follow up the students’ memories in understanding, share the worksheet then explaining the instruction of the test before gave the test. By the observation to the students’ result test, she found four kinds of the students’ error with the frequency: error in addition= 53 (25, 24%), error in omission= 60 (28, 57%), error in miss-formation = 57(27, 14%), and error in miss-ordering = 40 (19, 05%) and the most dominant error was error in omission = 60 (28, 57%). The causes of error were classified based on the theory by John Norris (carelessness, first language interference, and translation), analyzed on the students’ results test.
AN ANALYSIS OF STUDENTS’ ERRORS IN USING SIMPLE PAST TENSE IN TRANSLATING NARRATIVE TEXT

Error may appear when students put the English grammatical incorrectly. Errors is mostly occurred in English as the foreign or second language. The aim of this study is describing kinds of errors are made by the seventh semester students of English department in Madura University on the use of simple past tense in a translated narrative text. The research method used in this study is descriptive qualitative. The subject is seventh semester students of English department which consist of 15 students. The instruments used is translating test. The data is analyzed by collecting the data from students, identifying the errors based on its grammatical errors, classifying them into errors classification, and calculated them into percentage. The results showed that the students' errors can be classified into four kinds of errors, which are 25% for omission errors, 5.36% for addition errors, 62.5% for missed formation errors, and 7.14% for missed ordering errors. There are total 56 errors occurred which is dominated by missed ordering errors. The teachers recommended to make a clear understanding related to differentiate grammatical differences between Indonesia and English. Further, students need to practice it more often. The other researchers can provide techniques to increase students’ English grammatical understanding, especially in simple past tense usage.
Unsupervised Visual Ego-motion Learning for Robots

Despite changing conditions and mobile objects in its environment, the goal of an autonomous robot is to navigate without any human operator. For achieving this, the knowledge of both the dynamic state of the robot and the 3D structure of the environment must be known. While discretizing a continuous image sequence, three types of motion can be observed: 1) a mobile camera (or a robot as in this study) capturing a static scene, 2) independent moving objects in front of a static camera, or 3) simultaneously moving camera and independent objects in the environment at any given time. One of the challenges is the existence of one or multiple mobile objects in the environment which have independent velocity and direction with respect to the environment. In this work, a visual ego-motion estimation with unsupervised learning for robots by using stereo video taken by a camera mounted on them is introduced. Also, audio perception is utilized to support visual ego-motion estimation by sensor fusion in order to identifying the source of the motion. We have verified the effectiveness of our approach by conducting three different experiments in which both robot and object, sole robot and sole object motion were present.
Gesture Recognition Using LFMCW Radar and Convolutional Neural Network

With the continuous enrichment of human-computer interaction, gesture recognition technology plays an increasingly important role in various fields, especially in the non-contact and low-light conditions. In order to overcome the limitations of traditional visible optical sensors, such as low-light, occlusion and privacy, a gesture recognition system based on linear frequency modulation continuous wave (LFMCW) radar is proposed. By preprocessing the LFMCW radar intermediate frequency (IF) signals, the time series of the two-dimensional range-doppler(R-D) maps of the gesture is obtained. The R-D map series is taken as the three dimensional convolutional neural network (3D-CNN) input samples, and the gesture features are extracted via convolution layer and pooling layer, and the gesture features are classified and identified via the fully connected soft-max classifier. To explore the application of the extracted gesture features, a 77GHz radar system is applied, and six kinds of gestures are designed to verify the performance of classification and recognition. The experimental results show that the gestures can be classified and recognized effectively and the real-time recognition accuracy of the whole system can reach about 94%.
Information model of production system management

Improvement of production systems of the organization is carried out through the introduction of quality management systems, changes in the model of production organization, the use of modern approaches to improve product quality and customer satisfaction. Measurement, evaluation and analysis of the production system allows to set the direction of activity to improve production processes and to develop activities aimed at ensuring the effectiveness of the whole system. The production system is an open system, it is connected and exchanged with the external environment information, resources, etc. the production system is Called the operating system, which consists of three subsystems: processing subsystem, directly related to the technological processes of raw materials and semi-finished products conversion into finished products; support subsystem, which performs auxiliary functions necessary for the implementation of the main technological processes; planning and control subsystems that receive and process information from the internal and external environment of the organization. The task of building an automated information system is connected with the need to integrate with the subsystem of data collection and analysis, visual representation of information for decision-making at all levels. Building an information management system of the production system is impossible without a powerful infrastructure, without a single information system support and process control. The proposed information system will help to automate the processes of management of the organization, quickly form the strategic and tactical goals of the organization. Within a given period of time, data will be collected and analyzed from the internal and external environment, timely analysis of deviations of the values of indicators from the planned values. The results of information processing will be timely visualized both for each employee and the production system of the organization as a whole.
AESTHETIC MUSIC EDUCATION OF PERSONALITY IN THE CONTEXT OF V. O. SUKHOMLYNSKYI’S IDEAS

The article highlights the issues of musical and aesthetic education of the individual based on the analysis of the theoretical provisions of the pedagogical heritage and experience of Vasyl Sukhomlynskyi. The attention is focused on the actual and proven experience of the teacher-innovator methods of musical and aesthetic education of the younger generation in modern school. It is established that in the process of formation of musical values in children it is necessary to develop their attention, to learn to see, understand and create beauty. It is important to clarify the place and role of music as a means of influencing the emotional development of the younger person, to clarify the principles of the organization of the process of aesthetic education of school pupils by means of musical art, to substantiate the necessary methods of this direction of education. The article emphasizes that the most important task of aesthetic education, according to V. Sukhomlynskiy, is an attempt to teach a child to see the beauty of the world, the beauty of human relations, spiritual wealth, kindness, cordiality, and on this basis to assert the beauty in itself. Aesthetic education, according to the teacher, has a diverse relationship with all spheres of spiritual life of the individual and the team. The outstanding teacher generalized not only theoretically, but also practically proved inseparable unity of aesthetic feelings of the person, with his world Outlook and moral beliefs. In the belief of the person intellect and feelings merged together. Aesthetic education, argued V. O. Sukhomlynskyi, just boils down to the formation of the world of human feelings, manifested in the beautiful and ugly, in the sublime and low. Due to the fact that the educational process is based on positive aesthetic feelings, aesthetic education of the student gives him a “certain orientation” in cognitive and creative activities, in satisfying his spiritual needs. It covers all spheres of the spiritual life of the emerging personality.
Language, Communication, and Law: Dismantling Binary Opposition in the Pre-Adjudication Sphere

Language is a 'big house' for every science, there is no single science that does not use language as an intermediary instrument including Law.Language in the field of law is used no more than a way to formulate laws and track fallacies.On the other hand, the language in the form of speech as a form of communication has never been seriously studied in the Law.This study focuses on language models of speech in verbal communication conducted by Investigators/Prosecutors with the public.The method used in this study is normative juridical based on secondary data in the form of primary legal materials, secondary legal materials, and tertiary legal materials obtained based on library research.Based on the normative juridical research method, we use several approaches, namely philosophical approaches, conceptual approaches, language approaches, participatory approaches, and case approaches.Based on this, spoken language in verbal communication has a psychological impact on ordinary people who intersect with the law in the context of practice.This study propose several changes in Indonesian criminal procedural law.
Dependence on Blockchain Technology for Future Cybersecurity Advancement: A Systematic Analysis

Purpose:The aim of this research is to thoroughly analyze blockchain with respect to the role it plays in cybersecurity, and how this role may affect the future of blockchain and cybersecurity.Also, gaps are identified along with the shortcomings that cause these gaps.This research also identifies possible solutions to the gaps or issues.Method: the research approach used here is a review of the literature using the systematic-analysis technique.Other works that address various aspects of blockchain are analyzed in-depth to show its effectiveness.Results: there is a great possibility that blockchain is one of the future's greatest cybersecurity solutions.Among the major issues include quantum computing, user habits, and conflicting interests.All these issues have various ways through which they can be addressed effectively in order to brighten the future of blockchain's applicability in cybersecurity.Conclusion: blockchain, as it is, promotes fraud in cryptocurrency and therefore needs modification.Blockchain only needs reinforcement from technologies such as Artificial Intelligence and Machine learning to make it the future's most dependable cybersecurity provider.
[Temporal structure and dynamic neural mechanism in visual attention].

Attention shapes what we see and what we act upon by allocating limited resources to certain parts of visual display in a selective and adaptive manner. While most previous studies in visual attention mainly focused on the attentional distribution over space or features, recent studies have revealed that temporal dynamics also plays a crucial function in visual attention. This paper reviews the representation, function and neural mechanism of temporal dynamics in visual attention from the following four aspects: (1) Tracking dynamic structure of external stimulus by attention; (2) Intrinsic dynamic characteristics of attention; (3) Time-based multiple object representation; (4) Relationship between visual dynamics and classical attentional phenomena. We propose that the dynamic structure and temporal organization are fundamental to visual attention, and the research on it might provide new solutions to many unresolved issues in visual attention research.
Hyperbolic ordinal embedding

Given ordinal relations such as the object i is more similar to j than k is to l, ordinal embedding is to embed these objects into a low-dimensional space with all ordinal constraintspreserved. Although existing approaches have preserved ordinal relations in Euclideanspace, whether Euclidean space is compatible with true data structure is largely ignored,although it is essential to effective embedding. Since real data often exhibit hierarchicalstructure, it is hard for Euclidean space approaches to achieve effective embeddings in lowdimensionality, which incurs high computational complexity or overfitting. In this paper wepropose a novel hyperbolic ordinal embedding (HOE) method to embed objects in hyperbolic space. Due to the hierarchy-friendly property of hyperbolic space, HOE can effectivelycapture the hierarchy to achieve embeddings in an extremely low-dimensional space. Wehave not only theoretically proved the superiority of hyperbolic space and the limitationsof Euclidean space for embedding hierarchical data, but also experimentally demonstratedthat HOE significantly outperforms Euclidean-based methods.
Incremental Hashing with Undersampling

Most of current hashing methods are proposed based on the assumption that the database is stationary. However, this assumption is not always true as the data environment is sometimes non-stationary. When new images being added to the database, data distributions of existing classes may change and new classes may also appear which result in concept drifts. The problem of concept drifts is unavoidable in non-stationary data environments. Incremental Hashing (ICH) is an effective method for image retrieval in non-stationary data environments with concept drifts using multiple hash tables. In ICH, new concept is adapted by training new hash table using the most updated data chunks. However, images in the new data chunk may not be all informative for updating. To enhance the efficiency of ICH, ICH with Undersampling (ICHUS) is proposed to select informative samples in the new data chunk for the training of new hash table to adapt to the non-stationary data environment. Experimental results show that ICHUS yields a better retrieval performance than ICH and state-of-art non-stationary hashing methods.
Continuity of university education as a resource of regional university transitivity

The article is devoted to revealing the resources of transitive changes of a regional university as a “node” of inter-territorial and inter-level educational movements. The factors of continuity of transition between the Bachelor’s and Master’s education levels as a resource for educational transit of students are discussed. This student transit resource should be used for transitive changes in a regional university in response to global trends in the demand for “lifelong education” and the need to reduce the intensity of interregional educational migration. The article defines the functions of lifelong education as a resource for the transitivity of a regional university, proposes management and organizational measures for maintaining and improving the educational programs of master’s programs at regional universities, and substantiates their socio-economic efficiency.
IMPLEMENTASI DATA MINING MENGGUNAKAN METODE DESKRIPSI UNTUK MENGETAHUI POLA PENENTUAN PENERIMA BANTUAN SISWA MISKIN (BSM) DI SMP N 3 DOLOKSANGGUL

Poor Student Assistance is very helpful for students to meet the needs in learning activities and in completing the students themselves is very supportive in government programs that have to study nine years (preferably up to the upper secondary level), to help smooth the Poor Student Assistance which is directly to students and this does not aim for students who excel because it considers the condition of students. To find out the pattern of determining poor students' assistance recipients can be done by utilizing student data and poor student aid recipient data. Searching for patterns of determining students who receive aid from poor students is expected to be able to analyze the factors that greatly affect the recipients of poor student assistance. The method in accordance with the above problems using the Description Method, Description is one of the uses of data mining to explore and collect a lot of data. The description method is useful for characterizing or describing a condition, history, object.Keywords: Data Mining, Poor Student Assistance, Method Description