Reviewerly/exHarmony huggingface dataset:
DATA MINING DENGAN ALGORITMA NEURAL NETWORK DAN VISUALISASI DATA UNTUK PREDIKSI KELULUSAN MAHASISWA

Graduating on time is the desire of all students, not only that graduating on time is an advantage for both parties, namely students and educational institutions. But the graduation status of students when predicted does not always produce predictions early, so that it can result in graduation not on time. This research was conducted using data of students who graduated for 4 years from 2016-2019. The classification method is an approach to grouping data in data mining, namely classifying data. This classification method can also be used to make predictions for information that has not been previously known. The classification data mining method that will be used is the neural network algorithm. Visualization to display recapitulation data visually more interesting and neural network algorithm to predict student graduation which is difficult to do manually. Attributes used in training data consist of Jenis Kelamin, Asal, Kelas, Jurusan, Umur, IPK, Tanggal Yudicium, Tahun Yudicium and Class Hasil. The attributes that become parameters are 9 attributes, of which 8 are predictor attributes and 1 are results attributes. Training and testing data by changing parameters, namely: Hidden Layer Size: 3, Training Time: 500, Learning Rate: 0.3, Momentum: 0.2 produces a classification showing the level of accuracy using a neural network algorithm is 92.83%. Displays some very complete reporting recapitulation, so that predictions and visualization of the data can help in graduating students and provide recommendations for appropriate actions and must be done by management or the authorities to make decisions.
Self-Competitive Neural Networks

Deep Neural Networks (DNNs) have improved the accuracy of classification problems in lots of applications. One of the challenges in training a DNN is its need to be fed by an enriched dataset to increase its accuracy and avoid it suffering from overfitting. One way to improve the generalization of DNNs is to augment the training data with new synthesized adversarial samples. Recently, researchers have worked extensively to propose methods for data augmentation. In this paper, we generate adversarial samples to refine the Decision boundaries of each class. In this approach, at each stage, we use the model learned by the primary and generated adversarial data (up to that stage) to manipulate the primary data in a way that look complicated to the DNN. The DNN is then retrained using the augmented data and then it again generates adversarial data that are hard to predict for itself. As the DNN tries to improve its accuracy by competing with itself (generating hard samples and then learning them), the technique is called Self-Competitive Neural Network (SCNN). To generate such samples, we pose the problem as an optimization task, where the network weights are fixed and use a gradient descent based method to synthesize adversarial samples that are on the boundary of their true labels and the nearest wrong labels. Our experimental results show that data augmentation using SCNNs can significantly increase the accuracy of the original network. As an example, we can mention improving the accuracy of a CNN trained with 1000 limited training data of MNIST dataset from 94.26% to 98.25%.
How to evalute the informativeness of online-courses for healthcare professionals in the framework of continuous education

To date, only a few researchers work on the issue of evaluating the quality of online courses. This problem is highly relevant, but not sufficiently developed. And its solution, in our opinion, is directly related to the assessment of the informativeness of online courses. The purpose of the study is to develop a set of principles for evaluating the informativeness of a special type of online courses, the interactive educational modules for continuing education of healthcare professionals. These modules are accessed through an online learning platform, the portal for continuing medical and pharmaceutical education.
Ontological aspects of the educational space

The article deals with the problem questions of modern Russian formation. The author opens and analyzes the interrelations which are available in educational space. The estimated characteristic of educational space and its components are given in the research. The author considers questions of perfection of an educational system and a payment of the faculty. The revealing of the importance of vocational counselling finds the place in the article. To the critical analysis is exposed componential model of education. The author in the negative plan gives an estimation of constant checks, accreditations, etc. The role of a humanitarian component in a technical university is shown.
Linguistic Principles of Cataloguing in Online News Library

The purpose of the study is to identify advantages of employing linguistic principles to organise an online news flow in line with formation of an online news library, which becomes an effective tool for creating an image in a crisis situation. Scientific novelty of the research lies in its interdisciplinary nature, which allows the author to conduct further study of the media information space and provide a scientific rationale for its systematisation. As a result, it is proved that in formation of an online library containing news about the Syrian crisis, principles of a traditional three-tiered library cataloguing system (alphabetical, systematic and thematic catalogues) possess a productive linguistic potential for creating an event image and help to carry out a comprehensive assessment of it.
Digital Intervention for Students with Learning Disabilities

The Systematic Literatur Review aims to reveal kinds of assistive technology that applied to students with a learning disability (LD) in several articles selected through the screening process in 2015-2020. The review was conducted on three online databases, they are ScienceDirect, Sage Journal dan Proquest. There were 7 articles reviewed from a total of 32 obtained from screening inclusion and exclusion criteria. Based on the analysis of several studies revealed that using digital intervention such as Smartpen, PC, and Smartphone which has had appropriate application, have supported and increased the performance of students with learning disabilities in the area of learning skills. The development of specific digital intervention on students with learning disabilities needs to be applied in future research.
MASTER STUDENTS OF A TECHNICAL UNIVERSITY

The article analyzes the socio-psychological qualities of Russian master students at a technical university. Since 2003 the Russian educational system is guided by the Bologna program, which implies a transition to a two-stage model. At the same time, master students remain a little-studied subject. Socio-psychological portraiture of undergraduates is an important task for monitoring the current state of the process of training highly qualified personnel. The research showed that the resulting generalized portrait shows that master students have abilities that can be directed both to managerial activities and to scientific ones. At the same time, clearly expressed introversion does not allow us to speak about the priority of management activities. Thus, at the moment, the problem of predicting the preferred leading type of activity after the master's degree is difficult.
연극교사 전문성 확립을 위한 연극교과 PCK(D-PCK) 탐색

This study discussed the concept, characteristics and components of the PCK (Pedagogical Content Knowledge) - the core of teacher''s professionality - and based on this, explored the concept and components of the PCK for drama subject-matter education(D-PCK). In doing so, it aimed at laying the theoretical groundwork for measures to extend professionality of drama teachers. For this, the study critically reviewed precedent research of other curriculums related with the subject of this study focused on literature review, and carried out research on mainly two areas as below. Firstly, it explored the concept, characteristics and components of the PCK. Secondly, it defined the D-PCK and explored its components to draw educational implications. As a result, the study defined the D-PCK as ‘the knowledge and skills for carrying out lessons in which teachers apply what they have for their knowledge of drama education to a given classroom situation and effectively convey it so as for learners to understand contents easily’. And in regard to components of the D-PCK, it drew ‘knowledge of the purpose of for teaching subject matter’, ‘knowledge of curriculum’, ‘knowledge of educational content’, ‘skills to express dramas’, ‘knowledge of pedagogy’, ‘knowledge of evaluation’, ‘knowledge of learning dramas’ ‘knowledge of teaching environment’ as well as totally 31 sub-factors. Building on this, the study explored the meanings of each component and educational implications, and suggested that the D-PCK could be an index for education of drama teachers for the expansion of their professionality. Based on these findings, the study suggested the necessity of establishment of drama pedagogy based on the D-PCK, development of criteria evaluating the appropriate D-PCK for drama teachers, experimental research to elucidate the formation and development levels of the D-PCK, research on instrument development for measuring and analyzing the D-PCK.
IMPROVING STUDENTS’ SPEAKING ABILITY THROUGH DEBATE TECHNIQUE

The study is aim to find out how to improve students' speaking ability in making questions, giving explanations, and answers based on the debate topic. The methodology of this research is a classroom action research which consisted of 3 cycles. The subject of this research was the students of Semester II Sistem Informatika of Informatica Technical Faculty 2019/2020, Potensi Utama University, which consists of 60 students. To collect the data, the researcher applied the observation checklist and fieldnotes. Through the observation checklist, the researchers observed students' activity in the classroom, and by using fieldnotes the researchers summarized the problem during debating process. Based on the research findings, the debate technique which was applied to the subjects of research reflected the improvement of students' speaking ability. Based on the result of the researchers’ observation using the observation checklist and fieldnotes, it can be seen that students' speaking ability in making questions and giving explanations have been improved. The percentage of students' activity in the classroom when debate, in the first cycle, was 42.83%, in the second cycle was 59.17%, and the third cycle was 85.17%. It indicated that debate technique had improved students' speaking ability in making questions and giving explanations.Keywords: Classroom Action Research, College Student, Debate Technique, Speaking Skill
An Evaluation of Sourcing Strategies’ Relationship with Software Development Project Performance

Background: The rapid improvement of technological infrastructure over the past three decades have led to increased connectivity and communication possibilities. This has allowed firms to develop s ...
THE DIVIDE AND CONQUER METHOD IN THE DENIABLE ENCRYPTION ALGORITHMS

The deniable encryption algorithms productivity increasing is investigated in this paper. This investigation is relevant because of effective schemes for information and its users protection. But these algorithms is very complex and lumped. It really affects them. That's why deniable encryption algorithms have not been widespread in data processing and information security systems. The execution time reducing methods and tools exploration is the main goal of this work. The divide and conquer method has been discussed and investigated in this paper. It has been implemented into the data processing system of the deniable encryption algorithms. Nothing modifies have been implemented into the base algorithm. It allows to make it universal and apply to other deniable encryption algorithms. The series of experiments have been completed by authors to verify the hypothesis. The base deniable encryption algorithm discussing is the first stage of investigation. Its vulnerabilities have been found and investigated. Another algorithm is based on the divide and conquer method applying. It has been implemented into the modified data processing system. The both algorithms efficiency has been investigated by the experiments with the real with public and secret information files. The experiments have been completed on the prepared equipment. This equipment simulates the user's workplace with real hardware and software. According to the results the deniable encryption algorithms productivity has been reached by the divide and rule method. Also the method has been verified by the different size encryption keys. The base deniable encryption algorithms have not been modified. The results have been compared with other authors' investigations. In the end authors' hypothesis has been proved. But some restrictions of this results reaching have been set by the authors.
Adaptive Convolution for Semantic Role Labeling

Semantic role labeling (SRL) aims at elaborating the meaning of a sentence by forming a predicate-argument structure. Recent researches depicted that the effective use of syntax can improve SRL performance. However, syntax is a complicated linguistic clue and is hard to be effectively applied in a downstream task like SRL. This work effectively encodes syntax using adaptive convolution which endows strong flexibility to existing convolutional networks. The existing CNNs may help in encoding a complicated structure like syntax for SRL, but it still has shortcomings. Contrary to traditional convolutional networks that use same filters for different inputs, adaptive convolution uses adaptively generated filters conditioned on syntactically informed inputs. We achieve this with the integration of a filter generation network which generates the input specific filters. This helps the model to focus on important syntactic features present inside the input, thus enlarging the gap between syntax-aware and syntax-agnostic SRL systems. We further study a hashing technique to compress the size of the filter generation network for SRL in terms of trainable parameters. Experiments on CoNLL-2009 dataset confirm that the proposed model substantially outperforms most previous SRL systems for both English and Chinese languages
The Geographical Name of the East Sea and the Concepts of Talent in Primary and Secondary School Songs in Korean East Coast

한일 간에 동해와 일본해 표기를 둘러싼 논쟁이 지속되는 가운데, 연구자들은 고문헌, 고지도, 지리 교과서 등을 중심으로 한반도와 일본열도 사이의 바다 명칭을 연구해 왔다. 그러나 노래 가사에 나오는 동해 지명을 분석한 연구는 이루어지지 않았다. 이런 관점에서 본 연구의 목적은 동해안에 위치한 초·중등학교 교가에 나오는 동해 지명과 기대하는 인재상이 무엇인가를 밝히는 것이다. 연구 결과를 요약하면 첫째는 동해 바다와 같이 맑고 푸르고 넓은 마음의 인간, 둘째는 동해 일출을 맞이하는 부지런한 역군, 셋째는 동해의 거센 파도와 같은 역경을 극복하는 한국인, 넷째는 동해의 아름다움을 바탕으로 한 애교심의 육성이다. 이처럼 교가에 나오는 동해 지명에는 오랫동안 학교 현장에서 불려 한국인의 정서가 녹아 있다. 한국인의 정체성이 담겨 있는 동해 지명은 우리의 문화유산으로 보존해야 할 대상이다.While debates over the names of the East Sea and the Sea of Japan continue between Korea and Japan, researchers have studied the geographical names of the seas between the Korean Peninsula and the Japanese islands, focusing on old documents, old maps, and geography textbooks. However, no research has has analyzed the geographical names of the East Sea in the lyrics of school songs. From this perspective, the purpose of the study is to clarify the geographical name of the East Sea and the expected concepts of talent in the elementary and secondary school songs in the east coast region of Korea. The results of the study include: first, a human being with a clear, blue and wide mind like the East Sea, second, a hard worker who greets the sunrise on the East Sea, third, Koreans who overcome a fierce wave of the East Sea and fourth, fostering school spirit based on the beautiful scenery of the East Sea. In this way, the East Sea geographical name has been used in the school songs for a long time, and Korean sentiment is melted in it. The geographical name of the East Sea which contains Korean identity should be preserved as a cultural heritage.
On the properties of the Boolean functions associated to the differential spectrum of general APN functions and their consequences.

We initiate a study, when $F$ is a general APN function, of the Boolean function $\gamma _{F}$ related to the differential spectrum of $F$ (and which is known to be bent if and only if $F$ is almost bent). We first list many open questions about it. We study its algebraic normal form and its bivariate representation. We characterize its linear structures and specify nonexistence cases; we show, for $n$ even, their relation with the bent components of $F$ . We pose three related open problems. We characterize further in terms of $\gamma _{F}$ the fact that a component function of $F$ is bent and study if the number of bent components can be optimal. We consider in particular two classes, one of which is that of APN power functions. We study more deeply the relation between the Walsh transform of $\gamma _{F}$ and the Walsh transform of $F$ . By applying the Titsworth relation to the Walsh transform $W_{\gamma _{F}}$ , we deduce a new relation satisfied by $W_{F}^{2}$ , which is as simple as Chabaud-Vaudenay’s characterization by the fourth moment of the Walsh transform (which is in fact a particular case of the new relation), and provides more information. From this new relation, we deduce, for a sub-class of APN functions, a lower bound on the nonlinearity, which is significantly stronger than $nl(F)>0$ (the only general known bound). This sub-class of APN functions includes all known APN functions. The question (which is another open problem that we state) arises whether this sub-class equals that of all APN functions, but our bound provides at least a beginning of explanation why all known APN functions have non-weak nonlinearity. We finally show how the nonlinearities of $\gamma _{F}$ and $F$ are related by a simple formula; this leads to a last open problem.
Towards Robust Explanations for Deep Neural Networks

Explanation methods shed light on the decision process of black-box classifiers such as deep neural networks. But their usefulness can be compromised because they are susceptible to manipulations. With this work, we aim to enhance the resilience of explanations. We develop a unified theoretical framework for deriving bounds on the maximal manipulability of a model. Based on these theoretical insights, we present three different techniques to boost robustness against manipulation: training with weight decay, smoothing activation functions, and minimizing the Hessian of the network. Our experimental results confirm the effectiveness of these approaches.
Analysis of discriminatory characteristics of a video sensor with an exponential correlation function

Abstract This article presents an analysis of the characteristics of the video sensors functioning both in the visible and “thermal” regions of the spectrum. The influence of errors caused by the non-linearity of the discriminatory characteristic (DC) in the idealized model is studied. The article is devoted to the refinement of the model, taking into account the constant exponent parameter and introducing its value into the algorithm implemented by the onboard video sensor.
Advances and Prospects in Machine Vision: a Critical Review Based on CiteSpace

In order to systematically analyze the development of machine vision, this article uses the citation visualization analysis software CiteSpace to analyze the relevant literature included in the CNKI journal database in 2010-2020 with “machine vision” as the key word, and draws out the research institutions and research on machine vision Personnel cooperation map, explaining the distribution of research forces in this field and scientific research cooperation; generating keyword co-occurrence network maps through CiteSpace, analyzing popular research areas of machine vision, and using keywords as the entry point, using software to generate keyword emergence The intensity meter and the machine vision Timeline view analyze its research hotspots, research frontiers and development trends.
The Creative Development’s Background for a Modern Teacher Within the Innovation Epoch

The article is devoted to the consideration of the theoretical aspects of studying the psychologically creative readiness of teachers for innovative activities. Psychological and pedagogical studies devoted to the study of this phenomenon are analyzed. An attempt has been made to identify the structure of the teacher's psychological readiness for innovative activity, which will make it possible to determine and develop psychological and pedagogical technologies for its formation among teachers. The concept of the level of pedagogical activity, which requires a restructuring of the motivational sphere of the teacher's personality, his value orientations, goals, attitudes, the hierarchy of external and internal stimuli, orientation, aspirations, interests, is also touched upon. Modern educational policy makes new demands not only on the content and technologies of teaching, but also, first of all, on the personality of the teacher. The teacher is required to be able to realize and transform himself in the process of performing professional activities, to rethink his professional expectations, to feel his involvement in what is happening, to be able to see and predict the results of his work. Only such a teacher is able to solve the urgent problems facing modern education, to create effective pedagogical conditions for ensuring the spiritual and moral development and education of schoolchildren.
Modifikasi Algoritma Kriptografi Klasik dengan Implementasi Deterministic Finite Automata melalui Partisi Pesan Asli berdasarkan Kriteria Pesan Bagian

Classical cryptography is study of securing a secret message (plaintext) into a hidden message (ciphertext) which in the process changes each character. The process of converting plaintext into ciphertext is called encryption, the reverse process is called decryption. There is monoalphabetic algorithm, which changes each plaintext letter paired wisely with one particular letter in the ciphertext. The weakness of this algorithm is that the encryption rules can be guessed by analysing the frequency of occurrence of letters. Meanwhile, in polyalphabetic cipher, an algorithm that allows the same letter to be encrypted into different letters. One of them is the Vigenere cipher, which uses keywords that can be repeated to add to the plaintext in the computation of integer modulo. However, this algorithm can be solved using the Kasiski method, because pattern of repeating keywords. In this research, a Deterministic Finite Automata computation model is applied to partition messages before being processed with keywords. Partitions that are formed based on the criteria of message parts ending by the letter E, as letters that often appear in English text. This can increase the security of classical cryptographic algorithms, because they cannot be attacked by frequency analysis or Kasiski methods.
A BLOCKCHAIN TECHNOLOGY PROPOSAL FOR INFORMATION FLOW MANAGEMENT IN CIVIL CONSTRUCTION WORKS

Civil construction faces major problems related to the traceability of its information flows, and among them, monitoring the progress of work in progress is one of the most critical.This is due to the limitations of the tools usually adopted in this industry.This article analyses the application of blockchain technology in the monitoring of construction works, aiming to develop a proposal that fills the gaps in the literature.The main works that implement blockchain technology in construction were selected to support the proposed approach.Finally, a proposal is presented in order to increase the confidence of information flows in civil construction.