Reviewerly/exHarmony huggingface dataset:
A study of digital literacy of 1 <sup>st</sup> year computer education students faculty of education Nakhon Phanom University

A study of digital literacy of 1st year students in Computer Education, Faculty of Education, Nakhon Phanom University. The main objective is to study the knowledge and skills of digital literacy in 1st year Computer Education students, Faculty of Education, Nakhon Phanom University. In addition, it observes the skills of new enrolled students in the university and surveys the opinion of the students about digital literacy and Information technology by using the concept of IC3 Digital Literacy Certification. The result shows that overall students have moderate knowledge of digital literacy according to IC3 Concept which included Online living, Key applications, and Computing fundamentals. Therefore, students need to be educated more about digital literacy in order to prepare themselves to enter digital society and career pathway with their specific capabilities.
Pedestrians Detection Based on the Integration of Human Features and Kernel Density Estimation

Kernel density estimation doesn't need the distribution hypothesis of the background characteristics, and also it does not need to estimate the parameters. Therefore, it can deal with moving object detection under complicated background, but the algorithm application is limited by the selection of kernel function bandwidth. In view of this problem, the method of integrating the human features and kernel density estimation is presented in this paper, aiming at the pedestrian detection. First of all, selecting the kernel function bandwidth through the priori information of moving object, then, based on kernel density estimation, extracting the foreground (i.e. moving object), and finally, once again using the human characteristic to detect the video pedestrians. The experiments show, compared with the traditional methods, the method introducing the priori information can greatly reduce the computing burden of kernel density estimation. Even with the changes of the light and the outside noise interference, the method presented in the paper can accurately detect pedestrians and no-pedestrians. This method can be applied to the vehicle, animal detecting, but a priori information plays an important role.
Design and implementation of the korean muallaf center application as a guide to praying and iqro procedures for korean muallaf

The number of Moslem populations increased rapidly by 70%. It includes the converts in South Korea. The development of Moslems in South Korea is marked by the development of mosques in Seoul, Busan, and Jeju. The number of converts in Korea is very high meanwhile the main constraint factor for Korean converts is the absence of prayer guide in Hangeul feature. Constraint experienced by the converts, the most important is prayer. This research developed the Android Application, named The Korean MuallafCenter, which is an application that helps the converts to include ablution, prayers, and easy-to-understand religious worship. The purpose of this research is to help the converts to understand the guidelines of Islam with Hangeul, so that they can practice it. The methodology of this research is by literature study, application design, implementation, and evaluation of the application usage. The results of this study are the Korean MuallafCenter Applications that have been used by Muallaf Korea, especially Ustadz, Imam, and Muallaf Public Figure, Olabora Song. They gave suggestions that the application requires the addition of a better Hangeul vocabulary usage and an approach to the Korean Society in accordance with its culture.
Distribution Preserving Network Embedding

The deep autoencoder network which is based on constraining non-negative weights, can learn a low dimensional part-based representation. On the other hand, the inherent structure of the each data cluster can be described by the distribution of the intraclass sample. Then one hopes to learn a new low dimensional feature which can preserve the intrinsic structure embedded in the high dimensional data space perfectly. In this paper, by preserving data distribution, a deep part-based representation can be learned, and the novel algorithm is called Distribution Preserving Network Embedding (DPNE). In DPNE, we first need to estimate the distribution of the original data, and then we seek a part-based representation which respects the distribution. The experimental results on real-world data sets show that the proposed algorithm has good performance in terms of cluster accuracy and adjusted mutual information (AMI).
The problem of the transition from oral communications to written ones: based on the Ancient Greek literature

The article is devoted to the problem of transition in Ancient Greece from oral culture to written one. Most foreign and domestic researchers associate the duration and instability of this transition with 1) peculiarities of organizing the political power, 2) the anthropomorphic specifics of Greek culture. The author proposes to analyze applying oral and written communications in the key works of such ancient Greek writers as Homer (Iliad, Odyssey), Hesiod (Theogony), Aeschylus (Petitioner), Aristophanes (Birds), as well as philosophical works of Plato (Fedr). It is established that the Ancient Greek authors, despite the possession of writing, guided in their works on oral communication and such forms of confidence in oral communication as personal testimony, religious oath, reinforcing all this belief in a possible religious punishment. As a result, the Ancient Greek authors either ignore or portray as secondary written communication in the absence of specially created institutional forms of trust. The author proposes an original hypothesis, in the context of which he explains this phenomenon by the inability of institutional forms of confidence created for oral communications to perform its function in the transition to written communications and «slows down» the transition process. The author’s hypothesis is based on the theory of documentary information, in which context the final transition to written communi­cations was completed only after the creation of institutional forms of confidencein written communications in the form of archives and libraries.
Study On New Technology Of Earthquake Early Warning

The earthquake early warning (EEW) system of China is in the stage of testing. It is still facing the common scientific and technological problems such as the problem of magnitude estimation with large uncertainty, the difficulty in quickly identifying rupture parameters and the irrational estimation of the shakemap especially for large events. Moreover, another big challenge for the EEW system of China is the special technical problem of sending tens-millions-level alarm message in sub-second. In order to solve these problems, a project named “Advanced technical development and field demonstration for earthquake early warning” has launched by the Science and Technology Ministry of China. This paper provides an overview of the current situation of EEW system construction and summarizes the key strategies proposed by this project for solving these problems.
Research and Evaluation on Adaptive Filtering of Computer Video Electromagnetic Leakage Emission Reduction Image

The reduction reception of computer video electromagnetic leakage emission is an essentially process of obtaining a video image by receiving an attenuated electromagnetic signal and adjusting the device according to parameters such as a line frequency and a field frequency. In this process, the received image contains a large amount of noise due to the influence of space and equipment noise. In this paper, a method of adaptive filtering image is proposed to improve the image effect, and objective evaluation and signal-to-noise ratio analysis are carried out.
Small Reviews (About the Event of Thought and the Crisis of Subject)

The following text is a response to the publication of the journal in the rubric “Philosophy and history of science”. This text is called “Small Reviews”. Why? First of all, because the author has not set the task of a comprehensive analysis of publications. The text focuses on the pedagogical pragmatics of the peer-reviewed articles. In D.G. Ryndin’s article the author was attracted by that part, where the pedagogical practice of M.K. Mamardashvili was analyzed. Assessing the article of D.G. Ryndin as a whole positively, the reviewer believes that the author failed to convincingly show the poetics of philosophical speech and the fundamental relationship between the content and form of philosophizing and adduces her arguments for such an assessment. In the article devoted to the epistemological crisis of the subject, the reviewer has found many sources for pedagogical reflection and formulated them in the form of several provisions that should obviously be guided by each teacher. The reviewer believes that if the authors gave due consideration to the pedagogical theory and pedagogical characteristics of the subject, they would have enriched the their ideas about the crisis of education, its causes and consequences.
The Where of Mineral Names: Gamagarite, Gloucester Mine, Gamagara Hills, Postmasburg Manganese and Iron-Ore Field, South Africa

The Postmasburg manganese and iron-ore field (Gutzmer and Beukes 1996; Cairncross, Beukes, and Gutzmer 1997) might be considered the poorer relative to its northerly neighbor, the Kalahari manganes...
Impact of Image Corruptions on the Reliability of Traffic Sign Recognition Using Machine Learning Technique

As autonomous driving gets closer to be widely applied, it is important to guarantee that traffic signs are recognized correctly. Due to change of light conditions and blockage by some other objects, traffic signs can sometimes be partially corrupted. In this paper, we evaluated how machine learning would respond to different types of image corruption by various degrees. Removing a higher percentage of pixels will gradually harm the recognition accuracy, and removal by blocks causes the biggest harm, which is consistent with human observation. Changing to various colors or a single color doesn't seem to cause significant differences. This study, by building a model for traffic sign recognition and evaluating its robustness to various types of image corruptions, provides insights into corruptions of datasets for machine learning in general, and provide potential concern for applying the well-trained model to a new test set with corruptions, which could be a concern for applying autonomous driving in certain areas.
Deep Learning for Minimal-context Block Tracking through Side-channel Analysis

It is well known that electromagnetic and power side-channel attacks allow extraction of unintended information from a computer processor. However, little work has been done to quantify how small a sample is needed in order to glean meaningful information about a program’s execution. This paper quantifies this minimum context by training a deep-learning model to track and classify program block types given small windows of side-channel data. We show that a window containing approximately four clock cycles suffices to predict block type with our experimental setup. This implies a high degree of information leakage through side channels, allowing for the external monitoring of embedded systems and Internet of Things devices.
Reusable Garbled Turing Machines Without FHE

Since Yao introduced the garbled circuit concept in 1980s, it has been an open problem to design efficient reusable garbled Turing machines/circuits. Recently, Goldwasser et al. and Garg et al. answered this question affirmatively by designing reusable garbled circuits and reusable garbled Turing machines. Both of these reusable garbling schemes use fully homomorphic encryption (FHE) schemes as required building components. Here, we use multilinear maps to design a reusable Turing machine garbling scheme that will not need any FHE schemes. Though it is not clear whether our multilinear map based garbling approach could be more efficient than FHE based garbling approach, the goal of this paper is to develop alternative techniques for resuable garbling schemes to stimulate further research in this direction.
Hierarchical Attention Networks for Different Types of Documents with Smaller Size of Datasets

The goal of document classification is to automatically assign one or more categories to a document by understanding the content of a document. Much research has been devoted to improve the accuracy of document classification over different types of documents, e.g., review, question, article and snippet. Recently, a method to model each document as a multivariate Gaussian distribution based on the distributed representations of its words has been proposed. The similarity between two documents is then measured based on the similarity of their distributions without taking into consideration its contextual information. In this work, a hierarchical attention network (HAN) which can classify a document using the contextual information by aggregating important words into sentence vectors and the important sentence vectors into document vectors for the classification was tested on four publicly available datasets (TREC, Reuter, Snippet and Amazon). The results showed that HAN which can pick up important words and sentences in the contextual information outperformed the Gaussian based approach in classifying the four public datasets consisting of questions, articles, reviews and snippets.
EDUCATION OF SENIORS WITH RESPECT TO THEIR COGNITIVE FUNCTIONS

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 1557-1562ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.0471Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
Fault Aware Software Engineering (FASE)

Human factors play a significant role in software development. When the human element is not considered in software development, it may lead to faulty software which may cause delays in software delivery. Faults in software are mostly because of human errors, which consequently results in software failure. Therefore, the ability to model developer-fault relationship will subsequently lead to the production of a proactive adaptive recommendation system that will profile developers' characteristics against fault characteristic. Subsequently, reducing the number of faults developers seed into code. The overall aim of this research is to reduce the number of faults developers introduce into code by modelling a developer-fault relationship which will be implemented into a profoundly new adaptive IDE plug-in. The objectives of this study are: to establish the personalities of developers that influence the introduction of fault in code by the developer; to determine the characteristics of faults that are influenced by the human personality; to identify the relationship between the fault characteristics and human characteristics; and model the relationship between the fault characteristics and human personality. This study provides conceptual knowledge, reports findings, and presents both real and hypothesised challenges facing software engineering community. The study will evaluate the personality of software developers using the IPIP-NEO five-factor-personality test and the SZZ algorithm to evaluate faults found in code from Open source repositories. The result of this study will be used for the implementation of the model in a proof-of-concept IDE plug-in that adapts to developers, helping them avoid introducing faults they are individually prone.
Fitting Geometric Primitives With Least Squares

This chapter presents the topic of fitting 3D geometric primitives, namely plane fitting, sphere fitting, 3D line fitting, and cylinder fitting. Different adjustment techniques presented in the previous chapters were used for the fitting problem such as adjustment with observations, adjustment with constraints, and the method of homogeneous least squares using the SVD decomposition. Illustrative examples supported by MATLAB codes are also given to illustrate the theoretical models.
Practical Reasoning in the Deliberations of an Intelligent Autonomous Agent

This chapter outlines possible future developments and prospects of computational argumentation systems on practical (means-end, goal-directed) reasoning in artificial intelligence by leading the reader through a series of simple examples, gradually leading to more complex examples. The Carneades Argumentation System is used to model the structure of the argumentation in these examples, and through this, it is shown how formal systems of deliberation dialogue need to be applied to problems posed by the more complex examples.
Real-Time, Remote, Interactive Recording Sessions

This chapter employs cloud-based word processor and spreadsheet tools and online file-sharing repositories to facilitate real-time workflows that allow us to collaborative and interact productively with people anywhere on the planet, provided they have an Internet connection. People in technologically advanced societies frequently engage in almost instantaneous communication with friends and colleagues across physical distance, often in remote locations, in the form of email, SMS, social media, and various messaging apps. Dropout affects real-time performance and music production, as it introduces glitches in the audio signal. Literature suggests, as anyone with experience in this area might expect, that latency is one of the fundamental challenges for attempting to engage in real-time, interactive music making over a network. The authors strongly believe that real-time, remote, interactive recording sessions are not simply a phenomenon that has occurred as a result of niche academic research projects.
Python Package for the Network Operator Implementation and its Application for Group Control System Synthesis Problem

One of the main problems of symbolic regression methods is how to encode mathematical expressions to make the structure concise and readable. Here we address to the problem of network operator’s matrix scarcity, which we resolve using python’s standard types. Our approach allows to get rid of zero elements bellow the main diagonal. Moreover, we introduce new parametric variation, which helps us to tune parameters during structural evolving. We provide a description of the network operator and algorithms for finding the optimal solution using the principle of small variations of the basis solution. Our new encoding scheme and the complex functional for the group control task then described. In the experimental part we introduce a new way to apply network operator with a variable number of arguments to the group control system synthesis problem. Along with this we use for the first time individual network operators for each robot. From the experiment we can see that provided tricks lead to results that are not inferior in the case of usual network operator shared by all robots.
Development of tools for testing technologies applied for monitoring knowledge level of the trainees educated within multifunctional technological educational system

The main purpose of this article is to present the contents of a number of modern innovative technologies for monitoring students' level of knowledge. To achieve it, the task of justifying the advantages of using the testing technology tools to control students' level of knowledge solved. In addition, the article shows the practical features of the use of testing technologies to monitor students' level of knowledge by creating an evaluation fund for educational discipline «Computer Science», which is an integral part of multifunctional educational technological complex in the «Manager-programmer of information systems», using a rating approach and multi-point measurement scales. The results are usable in practice of educational institutions work to control students' level of knowledge during the qualified specialist’s preparation.
Shared Context-Based Compression Paradigm for Ubiquitous Local Transmissions

Data compression is extremely important for all kinds of networking applications, but most existing compression algorithms are only based on utilizing the redundancy characteristics of data source. This paper proposes a novel compression paradigm, which explores another kind of redundancy that is provided by the correlated state information shared between sender and receiver of a local transmission. Such kind of redundancy reflects the knowledge of two peers about each other before a transmission really takes place, with the aid of possibly existing cloud data center or sensing interfaces equipped. We formulate a typical representation of shared context as inequality constraints for the general case in n-dimensional Euclidean space, and provide a constructive proof for the existence of a bijective mapping used for compression and decompression with the shared context. By experimenting on compressing geographic spatial-temporal data for efficient transmissions, analysis and simulation demonstrate that the proposed scheme outperforms the well-known Huffman coding and Delta algorithms in terms of compression ratio.
Information and communication system technology with VPN site-to-site IPsec

This research aims to solve network problems in Information and Communication Technology (ICT) project at Gelora Bung Karno (GBK) gym building. The ICT project was created for the 18th Asian Games event. The technologies used in ICT projects in GBK are VLAN (virtual lan) and Virtual Private Network (VPN). The problem in this ICT project is the end device must be connected through the two switched layers but using a different network. VLAN is a solution to divide the network segment without having to follow the physical condition of the device. This project was made by using four stages. Those stages are analysis, design, implementation and testing. On ICT systems, VLAN are used to divide network segments required for Access Point and CCTV requirements. VLAN are simulated in GNS3 and VMWARE software. As a result, access points and CCTV as end users are connected to the core routers in the network operational center via the layer two switch. The next problem is the lack of efficient monitoring and troubleshooting system. Monitoring and troubleshooting systems must be done from the Network Operational Center (NOC) in GBK. Monitoring and troubleshooting systems are more effectively done directly from the developer's local network by accessing the local network of ICT projects over the internet. This mechanism is called a VPN. VPN technology is used to access local networks that exist in ICT projects using the local network of related developer companies. The VPN uses IPSec as encryption for the packet data equality. The results show that VPN is able to connect local network in ICT GBK project with local network of developer company through internet.