Reviewerly/exHarmony huggingface dataset:
A simple graphic method to assess correlation

This study explores the correlation between two variables and to demonstrate a simple graphic method to assess their degree of correlation. Following the lead of early English biometricians, it has been tacitly assumed that the studied variables develop in the same direction: when variable A’s measurements are higher from one object to another, the measurements of variable B, also are higher. The customary measure of co-relation relies on a least squares fitted trend line, then assuming that the trend is more real than, and has priority over the individually recorded data. The situation changes when measurements of variables develop in opposite directions: The very first data set I used to perform a correlation analysis was a study of student grades achieved and the percentage of their having missed classes: the more a student was absent from class, the lower were his achieved grades. In that situation the accepted model of correlation analysis – the mathematically fitted straight line and the squared distance of each student’s record from that line - was not appropriate. The usual correlation coefficient contradicted visual evidence of those data because the model underlying that situation treats the individual data as having more reality value than the general trend, but not as deviations or errors. The visual appearance, the graph of that situation, resembles a rectangular triangle, formed by the horizontal and vertical axis as its catheters, and the hypotenuse formed by a line through and representing the highest data points. This image justifies the expression “Triangular correlation”.
Research on Life Cycle Model of Data for Handling Big Data-Based Security Incident

Artifact analysis is used to investigate various types and characteristics of attacks to the system in case of security incident. Moreover, the accuracy of security incident analysis varies depending on artifact data. However, highly developed network technology and generation of a massive amount of artifacts in today’s hyper-connected society make management difficult. The accuracy of analysis can increase if all artifacts regarding security incident are collected and saved, but this is associated with disadvantages of cost and efficiency in respect of managing artifacts. Therefore, this study aims to suggest the plan of effective handing of security incident in addition to the reduction of managerial load based on an “Artifact life cycle” model.
A Grammar-Aware Pointer Network for Abstractive Summarization

Pointer network (PN) has achieved breakthrough in recent years of text summarization research. But it only focuses on semantic relevance of the source sequence; in fact, the text should also comply with explicit grammar rules. The semantics and syntax are the two main granularities to research in this paper. In more detail, we proposed a grammar-aware pointer network (GPAN) for abstractive summarization, which not only tracks the key semantics of the original text, but also observes the syntax rules. To enforce the syntactic constraints, we get each word attached with the part-of-speech (POS) tag and syntactic dependency (DEP) tag and input them into the recurrent network when training the network. Then, we predict the POS and DEP at each decoder time step; by this way, we trying to let the model learn to track the grammar information of the ground truth. We evaluate our model on the benchmark dataset CNN/Daily Mail and GiGaword. The experimental results show that our model leads to significant improvements.
Interface design of prediction in selecting concentration at informatics engineering studies program using trend moment

Abstract Informatics Engineering Study Program applies curriculum which obligates the students of semester 4 to choose a concentration based on their interest. The head of Informatics Engineering Study Program is sometimes rather difficult to provide class for students because the class provided is usually less or more. The problem faced by the study program about class and lecturer is related to the students who have difficulty to determine concentration which will be chosen. This research aimed at designing interface of prediction in selecting concentration at Informatics Engineering Study Program by using trend moment. The method used consisted of data collection (literature study, interview), decision taking method of trend moment. System developing method used was by following the framework of System Development Life Cycle (SDLC), where one of the framework of SDLC is waterfall method (system planning, analysis, design and implementation). Many previous researches used title about designing structure and implementation of selecting concentration by using different methods. But in this research, the researcher proposed the title of which result merely focused till step of Interface design using Trend Moment.
Development of Film Production Mobile Learning Application for Android Platform

Abstract Over the years, the film has changed as well as the pattern of how audiences watch movies. Youngsters nowadays are very fond of shooting videos and uploading them online. However, mobile learning applications for filmmaking are limited. Therefore, this paper presents the development of a mobile learning application named Film Geek for the Android platform. The objective of this project is to design and develop three main learning modules for filmmaking which are screenwriting, cinematography and directing. The methodology of this project consists of three phases which are requirement identification, system design and development and testing and evaluation which is adapted from the prototyping model. This mobile learning application has been developed using Microsoft Xamarin, a native cross-platform mobile application development framework. Furthermore, Firebase Real-Time cloud database was chosen for storing the application and user’s data. Functional and usability testing has been performed to evaluate the developed mobile learning application. The result of the testing shows that the functionality of the mobile learning application completely works (100%) as expected. Also, the usability test result of this application using SUS instrument achieved 86.3% which is within the acceptability ranges.
Improvement of Students’ Initiative by a Project-based Learning that Targets all the Students of Every Department and Every Grade

National Institute of Technology, Kure College (Kure Kosen) has conducted Incubation Work (IW) since 2015 academic year. It is a Project-Based Learning that targets all the enrolled students of every department and every grade, which aims at the encouragement of students’ autonomous learning. In 2015 academic year, students committed to the project topics prepared by teachers. From 2016 academic year, students were allowed to organize their own project groups that share the same project goal, which would inspire students’ independence and initiative. Students answered to a questionnaire to review their own activities in IW after each academic year has passed. This paper reports students’ assessments on the activities in IW and the changes occurred to their initiative by analyzing their answers to the questionnaires conducted from 2015 to 2017 academic years. The students′ assessments of IW have improved over the three years. For their initiative, students on their own project topics were more active in independent actions and external activities compared with those on the teachers’ project topics. Thus, the richness of options that allows students organize their own projects is a significant factor in bringing out students initiative.
An adaptive and <scp>cost‐efficient</scp> migration to cloud approach in dynamic environments

Summary Due to the variety in available cloud providers along with the frequent changes in strategic objectives of an enterprise, migrating existing software components to the cloud has become a challenging decision in the software maintenance phase. “Financial” and “customer satisfaction” viewpoints are two important strategic objectives of all enterprises that greatly affect the decision about migration to the cloud. Moreover immense number of target cloud services with too many configurations and cost models has made the search space of possible migrations huge. Many existing approaches of software migration to the cloud have modeled the problem as deployment optimization of software components over available platforms, while in this research following a valid migration plan is intended rather than proposing a final optimal migration solution (deployment). A migration plan is a sequence of actions to be taken by the technical team to move the software components to the cloud stepwise. Since at each stage of the migration there might be many valid alternative paths to follow, a recommender module is proposed to direct the management by recommending the best migration plan out of all valid plans in a Labeled Transition System. The recommendation is based on the current state of the enterprise which is estimated using a two‐state Hidden Markovian Model by observing ambient signals. The empirical study showed that particularly in dynamic and changing conditions the proposed adaptive and plan‐oriented method succeeded in posing lower accrued maintenance costs on the enterprise over time with confidence 90% compared to the non‐adaptive method due to its reactive and self‐balancing nature.
Quantum attack-resistant signature scheme from lattice cryptography for WFH

With the emergence of quantum computers, traditional digital signature schemes based on problems such as large integer solutions and discrete logarithms will no longer be secure, and it is urgent to find effective digital signature schemes that can resist quantum attacks. Lattice cryptography has the advantages of computational simplicity and high security. In this paper, we propose an identity-based digital signature scheme based on the rejection sampling algorithm. Unlike most schemes that use a common Gaussian distribution, this paper uses a bimodal Gaussian distribution, which improves efficiency. The identity-based signature scheme is more convenient for practical application than the traditional certificate-based signature scheme.
Lightweight Photo-Realistic Style Transfer for Mobile Devices

Neural Style Transfer enables synthesizing an image in the style of a reference image with convolutional neural networks. Photo-realistic style transfer aims to retain the photorealism in the synthesized image. Many of the state-of-the-art photo-realistic style transfer techniques uses networks like VGG as the backbone effectively making it computationally expensive and infeasible for deployment in systems with limited resources like mobile devices. In this work, it is shown that lightweight VGG like networks can be trained with knowledge distillation technique to achieve similar performance with ~35x lesser model parameters. In addition, a novel and efficient method is proposed to train neural networks to learn the image smoothing operator to enhance the photorealism in the stylized images. The proposed improvements, thus makes it feasible to achieve effective and fast on-device photo-realistic style transfer.
A Study of Data Hiding Using Cryptography and Steganography

The information and data transmitted over the network may include critical and confidential which may be lead to intercept by unauthorized entities. In today environment, many Web site applications as financial, social, mobile application and many more require the personal information like name, address, mobile number, and bank information. So the perspective from the point of security of such data has a challenging work in today’s scenario. The end user must require his confidential information should be protected from an unauthorized access. The integrity of information or data must be preserved. So in this paper we are discussing two security techniques, namely as cryptography and steganography. These two techniques are widely for providing the security to our data when it is transmitting over the network. These techniques are used to hide the message from the third party. Here, the researcher has been presented a review on steganography and cryptography techniques. Then, we have compared both the techniques. It also aims how the combination of cryptography and steganography enhances security.
LBNet: A Model for Judicial Reading Comprehension

In this paper, a new model for judicial reading comprehension called LBNet that combines an end-to-end network with a BERT structure is proposed, which aims to answer questions from a given passage in judicial files. Firstly, BERT is used to extract the representation of the passage and the question, and. self-matching attention mechanism is introduced to refine the representation by matching the passage against itself, which can effectively encode information from the whole passage. In the question and answer model, the pointer networks is used to locate the positions of answers from the passages. Experimental results on the CAIL2019 datasets (Chinese Judicial Reading Comprehension), show that our model can achieve good results.
Evaluating the Success-History Based Adaptive Differential Evolution in the Protein Structure Prediction Problem

Proteins are vital macro-molecules for every living organism. As the exper imental determination of protein structures is costly and time-consuming, computational methods became an interesting way to predict proteins’ shape based on their amino acid sequence. Metaheuristics have been employed in the protein structure prediction problem through the years, with different characteristics and different knowledge sources. However, these methods are heavily dependent on parameter tuning, where wrong parameters might cause poor performance. Recently, adaptive strategies were proposed to deal with parameter tuning’s non-trivial task, leaving the algorithm to choose its parameters for each optimization step. Although adaptive metaheuristics are widely applied to benchmark problems, only a few were tested in the PSP problem. To contribute to the analysis of adaptive metaheuristics in the PSP problem, we explore in this work the capability of one of the CEC’14 winners: the Success-History based Adaptive Differential Evolution algorithm on the tertiary protein structure prediction problem. We tested the SHADE algorithm in eight different proteins and compared the algorithm to the other two classical non-adaptive differential evolution and the well-known self-adaptive differential evolution. Moreover, we enhanced the SHADE with domain knowledge from APL. Our results enlarge the research body in adaptive methods for the PSP problem, showing that SHADE is better than non-adaptive differential evolution approaches and competitive compared to self-adaptive differential evolution and related works.
학교 밖 역사교육을 위한 박물관 교육프로그램 다시 보기 - 대구교육박물관의 1일 현장체험학습을 중심으로 -

This study has started from two interests: an interest in museums where educate public history, and an interest in whether educational programs by public institutions with a big budget are operated appropriately for the educational purpose.One-day field study of the Daegu Museum of Education (hereinafter referred to as “field study”) targets elementary and middle school students. The field study is required to ensure high quality of education and publicness. It is because the field study is linked to extracurricular activities at schools with annually about 10,000 student participants and a large scale of investment in budget and manpower. In order to confirm the educational effectiveness of the field trip, this study has researched the actual operation and analyzed problems of the filed study from 2018 to 2019 by focusing on the operation plan review and satisfaction survey result.As a result, the following problems have been confirmed. First, the field trip seems to be lack of sufficient consideration in the process of targeting participants and designing the program. Second, the program content may be inadequate to meet the education goals and themes. The program composition can be insufficient for the intended subject. Third, the linkage with school education seems not to be properly maintained.In order to improve these aspects, the followings are proposed: First, it is suggested to readjust the education target of the field trip. Considering the exhibition contents and curriculum in the museum, it would be more appropriate to range in the participant between the sixth grade of elementary school and the third grade of middle school. Second, the contents and composition of the museum program should be reorganized to fully utilize the exhibition materials and to strengthen hands-on experience. In other words, students should be given more chances to involve themselves in research activities of the museum exhibition and to learn from the direct engagement. Third, it is also required to strengthen the linkage with extracurricular activities at schools. There should be proper interaction between the museum and schools so as to develop both pre-activities and review session at school.Based on the above, this study would propose a new alternative program in order for the Daegu Museum of Education to secure its identity as a public museum and to attain the purpose of student education.
MULTIMEDIA TECHNOLOGIES IN MODERN PERFORMANCE: "A WOMAN FROM THE PAST" IN THE SARATOV DRAMA THEATRE

Innovative directorial solutions in modern drama theater are still the subject of active study. Researchers are particularly interested in introducing multimedia technologies in theatre production. However, despite the fact that such performances have already become a common theater practice, many issues and aspects remain poorly understood. One of the most important questions is the functionality of multimedia stage techniques in a theatrical play. On the example of Saratov Drama Theatre's production "A Woman from the Past", staged in 2017 by director A. Sozonov, the author of the article analyzes the work of multimedia technologies, the director's search for the choice of multimedia stage techniques, the influence on the audience, as well as some features of the actor's existence in the play using multimedia. The study reveals the director's methods that enable him to work with stage and virtual space at a new level and influence the audience by creating a certain atmosphere in a play. This work is one of the first experiences in exploring the functions of multimedia stage techniques in modern dramatic performance.
Prospects for the Development of Cryptocurrency Regulation in Singapore

In this article are discussed the main prospects of development of cryptocurrency in Singapore, as it is widespread and used all over the world. The article covers the main points for the regulation of the cryptocurrency. There is a wide range of cryptocurrency trading platforms, and most of them are located in different countries, which leads to significant differences in terms of regulation by the authorities and, accordingly, different rules for users and companies. Several exchanges allow trading derivatives. A more detailed review would give a correct impression of the current situation in the world in terms of regulation of cryptocurrencies and future trends. Cryptocurrencies continue their development; the number of users of cyber money is steadily growing. The popularity of bitcoin has generated the creation of other cryptocurrencies that are developing along with bitcoin, but their popularity and capabilities are much less. In some countries, including Russia, the government started warning people that investing in “cash” equivalents could lead to losses in case if there is a collapse of cryptocurrency (bitcoin).
How to Catch a Moonbeam: From Model-Ware to Component-Ware Software Product Engineering

Models are an integral part of software systems Engineering (SSE). In SSE, modeling is the activity of creating the artifact – the model. Models are created according to the method of the modeling approach. An SSE endeavor comprises multiple modeling techniques for supporting multiple models. The recent scientific literature exhibits a plethora of sophisticatedly articulated philosophies, principles, definitions, and theories for models and modeling. There is a gap in linking the model to software systems generation by-passing the programming allowing unskilled programmers to develop software products. Such an endeavor requires organizing the software systems engineering as the engineering activities of the development of model-ware and software product generation through off-the-shelf component-ware. It also requires to engineer systems engineering methodology flexible and adapting to the community that practices software product development. This research presents the theory behind the computer-aided method engineering (CAME) approach that pioneered the engineering of models to generate component-based CASE (computer-aided software engineering) tools which are software products, by by-passing the programing or code generation. Paving way for unskilled programmers to design and develop software products. It enumerates the achievements of CAME and layout future directions for truly achieving model-ware to component-ware software plug and play product engineering as the potential technology for software systems engineering.
Stargazer: Toward efficient data analytics scheduling via task completion time inference

The fundamental challenge of data analytics scheduling is the heterogeneity of both data analytics jobs and resources. Although many scheduling solutions have been developed to improve the efficiency of data analytics frameworks (e.g., Spark), they either (1) focus on the scheduling of a single type of resource, without considering the coordination between different resources; or (2) schedule multiple resources by factoring in limited information about analytics jobs without considering the heterogeneity of resources. This paper presents Stargazer, a novel, efficient system that tackles diversity data analytics jobs on heterogeneous cluster by inferring the completion times of their decomposed tasks. Specifically, Stargazer adopts a deep learning model, which takes into considerations multiple key factors of diversity data analytics jobs and heterogeneous resources, to accurately infer the completion time of different tasks. A prototype of Stargazer is fully implemented in the Spark framework. Extensive experiments show that Stargazer can reduce the average job completion time by 21% and improve average performance by 20%, while incurring little overhead.
The surface code on the rhombic dodecahedron

I present a jaunty little $[[14, 3, 3]]$ non-CSS surface code that can be described using a rhombic dodecahedron. Do with it what you will.
Escenario sobre la aplicación de Aprendizaje Ubicuo en un Entorno Activo

Ubiquitous-Learning and its context sensitive applications (context-aware) has the potential to provide personalized and active learning, in addition to allowing the student to develop attitudes and aptitudes based on problem solving, progress monitoring, information, exchange of information, knowledge and collaboration process. Our contribution consists of the creation of a ubiquitous learning environment, which from a series of multimodal interfaces developed for an Environment Intelligence Environment and context sensitive applications, aims to influence teaching-learning activities through a laboratory of practices collaborative. The objective of the proposal is to implement the concept of Ubiquitous Learning (Ubiquitous Learning), providing the student with a space conducive, to generating knowledge and encouraging the development of cognitive skills. In this article, a description about the stage of the available technology in an Active Environment applied to the improvement of the academic performance of some subjects, where the student's evaluation is relate to their practical skills, that is, "The know-how".