Reviewerly/exHarmony huggingface dataset:
Environmental Concerns in Virtual Worlds: Interactive Experience of Ephemeral Life Beyond Borders

The Flutter of Butterflies Beyond Borders (2016) is an interactive digital installation by an interdisciplinary art collective teamLab based in Japan. The title of the artwork urges critical questions and implications such as, are the butterflies or the participants beyond the borders of digital technologies in this work? How and why are these borders shaped? If we consider the digital butterflies as the substitute for nature, who has control over nature beyond borders, digital technology, or human? The work situates the human body not only as a part of its natural environment but also as the dominant factor for shaping nature's future as well as the work's. Participants become gradually more aware of their behaviors that impact the continuity and well-being of the natural environment through the experience of intimate interaction with the artwork, particularly with their physical touch. By building a digitized nature installation, the artists create an experience not to prioritize the illusory sense of visuality but to increase and manipulate social awareness of the natural environment. This media artwork presents an exceptional and timely experience with its comments on the contemporary ecological turn through the entanglement of humans, nature, and technology.
THE CONCEPT OF TEACHING MATHEMATICS IN THE 1ST GRADE OF A GENERAL EDUCATION SCHOOL

The teaching of mathematics should reflect the global trends in the development of mathematical and pedagogical scientific thought. The authors develop guidelines for studying mathematics in the 1st grade based on the Federal State Educational Standard. Thus, the structure and the form of the textbook content are described by chapter. The theoretical part should allow students to complete screening questions, univariate and multivariate tests, problems, and exercises. Each chapter of the developed textbook is divided into paragraphs, and each paragraph is divided into items. One item of theoretical material contains either a new idea to study or a set of interrelated concepts that define a new idea. According to this, it is possible to form mathematical knowledge trajectories. So, there are broad opportunities to transform knowledge elements into multimedia forms, including presentations, videos, test modules, and other newly emerging means of representation and visualization, using the achievements of artificial intelligence. It is possible to define main themes such as natural numbers counting, acquaintance with geometric shapes, comparison of objects in the value and quantity, acquaintance with a squared paper and measurement standards, the study of objects position, the sets consideration, introduction to the algorithm concept can. The authors’ conceptual directions of teaching mathematics in the 1st grade provide the foundation for mathematical education in general education schools for all the years of study.
Information System for Disaster Mitigation Using Google Data Traffic

Abstract The Head of the Data Information Center and Public Relations of the National Disaster Management Agency predicts the potential for forest fires in 2018 will increase. The areas that are burned are border areas, both provincial/district/city borders because border areas are poorly supervised. This study aims to (1) Develop an Information System that can be used for Disaster Mitigation Using Google Data Traffic (2) Ensure that the developed Information System is suitable for use for Disaster Mitigation Using Google Data Traffic to obtain accurate traffic data. Google Data Traffic is a giant database used by the Google company to provide real-time traffic information through the Google Maps application. Google Maps uses multiple iterations of satellite cameras and uses Google Earth to map traffic including congestion information and the shortest possible path alternatives. The development method chosen is the Rational Unified Process (RUP). This research uses several methods in data collection including observation, interviews, and questionnaires. Interviews were conducted with prospective users of the application, namely firefighter drivers and people in disaster-prone areas. Questionnaires are used to provide a set of questions to respondents. In the determination test, the recall and precision values are calculated from the data generated by the developed system. While the function test uses descriptive data analysis techniques with the percentage feasibility formula. This research produces an application that can assist firefighters in carrying out their daily duties to be more effective and efficient and the test results on this application show that it is declared feasible in terms of efficiency, performance and compatibility.
Disciplinary Differences in Social Cataloging: A Comparison of LibraryThing Tagging of Works in Literature, History and Business

Samples of works from the literature, history and business collections of a university library were searched in the LibraryThing (LT) social cataloging platform. Match rates were obtained, and the subject headings and LT tags of matching titles recorded. The tags were then compared across the three fields. Finally, the nature of those tags representing new concepts was analyzed. Findings suggest that literature and history are much more represented on LT than is business, but that even for this field LT covers over half the library’s materials. While the amounts of tagging for literature, history and business were likewise very different, and the amounts that added retrieval value equally, or perhaps even more so, it was clear that access even to business titles could be greatly enhanced by social cataloging, when it was applied. This was reflected in the way that taggers focused on different types of concepts in the different fields, according to their audiences’ different search needs
Advanced Training of Teachers of Mathematics and Computer Science on the Basis of a Team Approach to Eliminate Methodological Defi ciencies in the Implementation of a Criteria-Based Assessment of Students’ Educational Achievements

The widespread introduction of a criterion system for evaluating the educational results of schoolchildren is an actual and significant direction of the development of domestic education. The article is devoted to the problem of eliminating methodological deficits of teachers in the development of criteria assessment tools for the current control of subject results of teaching mathematics and computer science in primary and high school. The article describes the method of organizing advanced training of teachers of mathematics and computer science on the basis of a team approach that contributes to the practical implementation of the intra-school system of current control of students ' academic achievements on a criterion basis. The article presents an approach to the implementation of an additional professional training program for teachers of mathematics and computer science on the basis of "team training", focused on the development of professional skills necessary for conducting procedures for the current control of subject learning outcomes, the Department of Mathematical Education and Computer Science of St. Petersburg Academy of Postgraduate Pedagogical Education.
Analysis of Classification and Calculation of Vehicle Type at APILL Intersection Using YOLO Method and Kalman Filter

Vehicles are a necessity that currently must be owned by the community, be it private vehicles or public transportation. However, with the increase in the number of vehicles, the government as the party that has responsibility for facilities and infrastructure does not keep pace with the increase in roads. This has resulted in frequent traffic jams, especially during busy times or working hours, thus overwhelming the authorized officers of both the Transportation agency and traffic police. To assist officers in the field in breaking down congestion that occurs with the help of CCTV monitoring installed in several sections of the APILL intersection, a real-time detection and calculation system is needed. The focus of the research is to optimize the Yolov3 algorithm in detecting and classifying vehicles by applying the Kalman Filter as a vehicle tracking method that has been classified. The dataset used for this research is the MSCOCO dataset with more than 300,000 object images. The test results of the two types of CCTV cameras that were carried out obtained the highest accuracy evaluation model of 53&#x0025; when the APILL was red because the Kalman Filter did not work optimally.
Analysis of Cell Phone Biometric Sensors and Security Risk of the Sensors

Biometric sensors are becoming more commonplace in today's world. These biometric sensors are especially common in today's smartphones. Billions of smartphones use these sensors for security purposes, and these are slowly but surely replacing traditional forms of password authentication. Biometrics are commonly used to unlock devices and also for purchases. In this chapter, the focus will be on the most common types of biometrics featured in phones along with the sensors associated with them. Next, an analysis of the security risk of these sensors along with common attacks to exploit these risks are discussed. Lastly, various ways to patch and combat these various risks will be discussed.
Prediction of Paddy Plant Height with Vermicompost Fertilizer Treatment on Tidal Land using ANFIS Method

The main problem in tidal land is high soil acidity, and the availability of nutrients in the soil is relatively low. Utilization of local resource vermicompost is used to improve soil conditions in tidal lands in order to increase crop yields. The parameter of paddy plant height has a very high correlation with paddy yields. This study aims to implement the ANFIS method to predict paddy plant height based on the treatment of vermicompost organic fertilizer. The dataset used for ANFIS training was taken directly from the observation data on the height of the paddy plant and the results of soil laboratory tests. The ANFIS process consists of 5 inputs consisting of fertilizer treatment, pH, N, P, K, and one output, namely paddy plant height. The results obtained from the training data process are that there are 486 rules and the error rate using MAPE is 3.53%, or the accuracy level of the prediction results is 96.47%.
Designing Project Management Application to Support Developer Productivity using Goal Directed Design Approach

Developer is one of the most important project resources to ensure software project can be finished within budget and project time limit. There were several problems that could lead to decreased developer productivity, such as distraction, lack of team awareness and miscommunication. Project management application can be utilized to help handling those problems. However, existing project management applications still have drawbacks on its interaction design, such as difficult to understand and cannot provide a broader view of project. This study aims to design of project management application using goal directed design (GDD) approach. The main goal of this study is to develop a project management application that can support developer productivity. Five phases of GDD were conducted, with end result of high-fidelity prototype that aligned with the goal of supporting developer productivity. Research was conducted using qualitative approach by interviewing 7 developers to understand users’ behavior, activity, goals, and problems. Collected data were analyzed resulting in persona, context scenario, features, usability goals and user experience goals. Achievement of the goal to support developer productivity was evaluated in the form of prototype’s usability goals, i.e., easy to use and efficient to use, and user experience goals, i.e., helpful and motivating. The result shows that prototype is easy to use with completion rate of 100% and Single Ease Question (SEQ) of 6.77 of 7, efficient to use with Time Based Efficiency (TBE) of 0.056 task/second, helpful with Intrinsic Motivation Inventory (IMI) value/usefulness of 6.63 of 7, motivating with IMI Relatedness 6.67 of 7 and IMI Perceived Competence of 6.83 of 7. Thus, the goal to support developer productivity is fulfilled as well through features and design of the prototype.
Decision Support System for Temporary Shelter Selection Using Hybrid AHP and TOPSIS

Waste that is generated will go into the first processing site, namely the Temporary Shelter – Tempat Pembuangan Sampah Sementara (TPSS). There are many considerations for choosing the best location TPSS that very important for supporting the collection of waste that will be transported to final disposal. The Jember Regency Environmental Service is an agency in charge of waste management, including the selection of TPSS locations. In its application, the selection of TPSS often results in human error. In addition, there is no standardized assessment system in the TPSS selection process. In this research, conduct the Decision support system to process of selecting the best TPSS location recommendation using hybrid method of AHP and TOPSIS. AHP is used to determine the weight of the criteria and TOPSIS is used for the selection process for TPSS candidates shown that feasible.
Towards a Novel Interoperability Management Scheme for Cross-blockchain Transactions

This study proposes a new interoperability management scheme for cross-blockchain transactions in which two private/public blockchains are linked-with a relay chain. The proposed scheme delivers compatibility among heterogeneous blockchains, and guarantees the correctness and consistency of transaction data exchanged. Evaluation results show the practicability of the proposed scheme.
A New Higher Order Differential of Enocoro-128v2

This paper reports the strength of a pseudorandom number generator Enocoro-128v2, which was published as a stream cipher by Hitachi, Ltd. in 2010, against higher order differential cryptanalysis. Enocoro-128v2 is one of the candidate recommended ciphers of CRYPTREC, which is a project for the e-Government in Japan, and specified in ISO/IEC 29192-3:2012. It takes a 128-bit secret key and a 64-bit initial vector as input, and the update function is applied 96 times in the initialization process. It has been reported that a 21 initialization rounds of Enocoro-128v2 is attackable by chosen IV distinguishing attack. In this paper, we focused on a higher order differential of the initialization process of Enocoro-128v2. As a results, we found a new 22-round higher order differential characteristic, in which 16-th order differential equals to constant by computer experiment. Exploiting this characteristic, we also show that a 22 initialization rounds of Enocoro-128v2 can be attacked with 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">16</sup> chosen IV.
A Specific Risk Evaluation System for Live Virtual Machine Migration Based on the Uncertain Theory

Benefiting from the convenience of virtualization, virtual machine migration is generally utilized to fulfil optimization objectives in cloud/edge computing. However, live migration has certain risks and unapt decision may lead to side effects and performance degradation. Leveraging modified deep Q network, this paper provided an advanced risk evaluation system. Thorough formulation was given in this paper and a specific integration method was innovated based on uncertain theory. Series experiments were carried on computing cluster with OpenStack. The experimental results showed deep Q network for risk system was reliable while the uncertain approach was a proper way to deal with the risk integration.
Comparison of Reinforcement Learning Algorithms for Motion Control of an Autonomous Robot in Gazebo Simulator

This article compares various implementations of deep Q learning as it is one of the most efficient reinforcement learning algorithms for discrete action space systems. The efficiency of the implementations for the classical Cartpole problem ported to the Gazebo environment is investigated. Then, these algorithms are compared for a self-created bipedal robot problem. Since the creation and configuration of a real robotic system is a laborious process, the initial debugging of the robot can be performed using the appropriate software that simulates the real environment. In our case, the Gazebo simulator was used. Using the simulator allows you to conduct research without having a real robotic system. In this case, it is possible to transfer the results from the simulator to the real system. The result of the study is the conclusion about the greatest efficiency of deep Q-learning with the experience reproduction mechanism. Also, the conclusion is that even for a robot with two degrees of freedom, Q-learning algorithms are not effective enough, and a comparative study with other families of reinforcement learning algorithms is needed.
GAN Theft Auto: Autonomous Texturing of Procedurally Generated Interactive Cities

We explore the possibility of producing photo-realistic and stylized videos from semantically segmented image sequences drawn from a procedurally generated interactive 3D environment. We evaluate our environment using the Cityscape and ACDC weather dataset to obtain swappable daytime, nighttime, and various weather texturings from our city. We further use the GTA V image dataset to showcase its feasibility on large interactive scenes for 3D animation and game texturing, demonstrating the ability to repurpose existing video game textures when generating our city. Our algorithm can be used to support video games by autonomizing both the environment generation process, as well as supporting researchers by providing a semantic testing environment for many city style-transfer algorithms. Video documentation at: https://tinyurl.com/vb63k87x
Getting Started

Let me begin with a single fact: we're shipping too much code to our users.
Cross-Lingual Summarization: English - Bahasa Indonesia

Progress of abstractive summarization has been accelerated since the introduction of sequence-to-sequence neural networks. Summarization is no longer limited to selecting words or sentences that exist in the source document as in the extractive approach, but can generate completely new words or sentences that have never appeared in the source document. Big push came from machine translation research with the introduction of attention mechanisms. Attention mechanism is the key to the information bottleneck problem in encoder-decoder model. Cross-Lingual Summarization (CLS) is the task of generating a summary in target language from source document in different language. Traditional methods split this task into two steps: summarization and translation. This paper describes a study on CLS without explicitly using translator, thereby reducing one step as in existing method. We incorporate multilingual embeddings in sequence-to-sequence neural networks with attention mechanisms to handle this task. Multilingual embeddings are used to represent words as if the source language and the target language are the same language. Experiments show comparable performance between monolingual summarization and cross-lingual summarization in Amazon Fine Food review data indicated by ROUGE scores which are only 1&#x2013;2 points apart.
An Improved Image Super-Resolution Reconstruction Method Based On LapSRN

With the gradual maturity of the traditional static image recognition field, super-resolution reconstruction based on deep neural networks is a research hotspot and difficulty in the field of computer vision. In particular, most single-frame image super-resolution methods have problems such as loss of high-frequency information, noise introduced in the up-sampling process, and difficulty in determining the interdependence between each channel of the feature map when reconstructing the predicted image. In order to solve the above problems, we introduce back projection mechanism into the LapSRN network in this paper. By introducing the back projection mechanism effectively improved the consistency between the extracted image feature data and the target feature data feature, and thereby improved the reconstructed image parameters. Experiments show that the improved network can achieve better performance than LapSRN.
English Master AMMU: Chatbot for English Learning

Effective communication is a very important aspect in every area to express one's own feelings and ideas. Lack of effective communication will adversely affect one's efficiency. Both for professionals and students, communication in the English language is very important and a necessity these days. As English is a language of everything, speaking skills needed to be the best to get better opportunities. English speaking skills can be improved in various ways. The most efficient way is to communicate with peers. It will help to improve speaking skills and reduce anxiety while talking. But most of the people do not feel great while talking to their friends as they feel a bit awkward. English Master AMMU (Automatic Mega-agent Managed User Guide) is a Google Assistant-based Chatbot that aims to improve users' spoken English skills. AMMU will interact with the user in a friendly way, as if they were speaking with a friend. Also, AMMU allows the user to study various basic and advanced portions of the English language, gives the user practice activities and quizzes. These combined features make AMMU different from other Google Assistant-based Chatbots.
Offline character recognition in transport logistic tables

Abstract The paper proposes the improved skeleton method of handwritten characters recognition, which is based on the filtering procedure and the principle of alternating shading schemes of skeletonized area on the 4- and 8-timeslinked raster. The procedure of high-frequency filtration based on discrete real cosine transformation or discrete complex Fourier transform with automatic selection of filtration parameters makes it possible to significantly improve the image quality of handwritten symbols, in particular, to eliminate in many cases thin bridges between the areas of symbol element representation. The principle of alternating the painting schemes along the 4- and 8-timeslinked raster makes it possible to get the wave front of the skeletonized area close to a circle. In this case, the broken lines representing the branches of the skeleton graphs retain the shapes of the symbols. Numerical experiments on the construction of skeleton sets and skeleton graphs for recognizable handwritten symbols located in the cells of the tables of logistic transport problems have been performed. Software implementation of the method is proposed.
Digital Education Strategy

This chapter analyzes and discusses key strategies for digital education. The chapter begins by examining and defining several key concepts, including global citizenship, digital citizenship, computational thinking, informational thinking, and systemic thinking. Next, the chapter analyzes the role of leadership in the age of digitalization and advocates for panoramic leadership. The chapter then discusses strategies and tools for teaching the digital humanities and compares STEM-based education with STEAM-based education. The virtual classroom is then analyzed, followed by a discussion of why Finnish schools excel in digital education. The chapter concludes by analyzing and discussing the architecture for digital schools and universities.