Reviewerly/exHarmony huggingface dataset:
My Continuing Journey from Logic to Computational Argumentation

This paper begins with a brief account of how I started out as a young logician studying modal logic with the hope that it would be useful when applied to evaluating real examples of arguments found in natural language texts.The exposition moves on to relate how my interests shifted to the study of argumentation in informal logic, and from there to computational systems combining defeasible argumentation schemes with argument mapping (diagramming).The story ends by leading to recent collaborations with three young logicians and computer scientists who are continuing on the path of my journey.
A Study on Security and Privacy related Issues in Blockchain Based Applications

In recent years, Blockchain has become increasingly popular in secured transactions. The blockchain is considered to be highly advantageous over other similar technologies because of its unique and significant feature that allows us to attach a time stamp to its entity called, a block. The stamps are useful to identify each transaction as an independent atomic unit. Although technology has been successfully applied in some areas, still there are some threats associated with it. For example, if the data stored on the chain are not secured, it is quite possible that hackers may control the entire chain by using attacks like ‘majority attack’. The purpose of this paper is to highlight the possible types of blockchain security threats and the available techniques to manage them. In order to achieve this, a complete survey has been presented, taking into considerations, the current state of the research areas particularly in security and privacy aspects. Some of the novel ways of mitigating the risks of blockchains have also been discussed. This paper would hopefully help blockchain research scholars and application users.
Reversible Data Hiding based on Horizontal and Vertical Pixel Pair Selection in Dual Stego Images

Dual steganography provides two stego images after embedding the secret data. This paper proposes a novel data hiding method that selects the pixel pairs in a horizontal and vertical direction. In 2017 Ki-Hyun proposed a data hiding scheme which selects the pixel pair based on a gap function. This gap function based pixel pair selection is complex. Since the gap function estimation needs a separate comparison to select a pixel pair. The proposed method alternatively selects the horizontal and vertical pixel pairs, which avoids the use of gap function. This method initially estimates a modulus matrix using modulus function, for every intensity in x, y direction. The secret data is converted to base -3 number format before embedding. While embedding a base -3 number it will produce two-pixel pair alternatively along the horizontal direction and vertical direction. In the extraction phase, original cover image can be reconstructed by averaging dual stego images. The proposed data hiding method provides a high PSNR and SSIM than the traditional methods.
Social Media and Improved Learning Achievement in Junior High Students of Coastal Pangkep

Research on the Analysis of the Relationship between the Use of Social Media and Improving Student Learning Achievement in the Pangkep Regency Coastal Region, with the aim to determine the frequency and duration of social media use for students related to learning.And to analyze the relationship between the use of social media and the improvement of students' learning achievements in the Coastal Region Middle School.By using a quantitative approach that is distributing questionnaires to second and third grade junior high school students.The data expected from this questionnaire is, the use of social media both in terms of frequency of use and duration of use.As for other data collected through the report cards of each respondent, to analyze whether there is an increase in learning achievement is associated with a tendency to use social media related to school learning, especially in coastal areas which incidentally the quality of education is still low.The results showed that all respondents had the opportunity to open social media with different frequencies in searching and searching for information related to learning in school.The frequency in question is; one to two times a week, three to four times a week, five to six times a week and more than six times a week.While the duration of searching for learning information also shows numbers ranging from; one to fourteen minutes, fifteen to thirty minutes, thirty-one to forty-four minutes and more than forty-four minutes.
Fuzzy Logic Controller

In this research paper, the impact of water pH on detergent was measured by constructing a Fuzzy Logic Controller (FLC) based on Intuitionistic Fuzzy Numbers (IFNs) by incorporating three linguistic inputs and one output as taken by Saeed. M. et al. [1]. The inference process was carried out using MATLAB fuzzy logic toolbox and the results were compared with FLC based on fuzzy numbers. The objective of the study was the comparison of FLC based on intuitionistic and fuzzy numbers. The results showed that FLC based on IFNs is approximately the same but has more precise values. So, IFNs based FLC can be used in the Instinctive Laundry System.
The Irrational Attitude of the Teacher as a Factor Hindering Professional and Personal Development (Acme)

The article is devoted to the issue of psychological support for the teacher’s professional and personal development in the framework of advanced training, the main task of which is to develop self-improvement motivation in the profession and create conditions for uncovering the teacher’s professional and personal potential. Some theoretical approaches and traditions are analyzed with respect to stereotypes, irrational attitudes, distortions of personality thinking that impede active professional growth, as well as ways of overcoming them among teachers. The article deals with the main stages of group work to overcome the irrational attitudes of teachers in the process of advanced training.
Probabilistic photovoltaic power forecasting model based on deterministic forecasts

This paper presents an original probabilistic photovoltaic (PV) power forecasting model for the day-ahead hourly generation in a PV plant. The probabilistic forecasting model is based on 12 deterministic models developed with different techniques. An optimization process, ruled by a genetic algorithm, chooses the forecasts of the deterministic models in order to achieve the probability distribution function (PDF) for the PV generation in each one of the daylight hours of the following day in a parametric approach. The PDFs, which constitute the probabilistic forecasts, are a mixture of normal distributions, each one centred in the forecasts of the selected deterministic models. The genetic algorithm chooses the deterministic forecasts, the variance of the normal distributions and their weights in the mixture. In a case study the proposed model achieves better forecasting results than the obtained with the conditional quantile regression method applied to the same data used to develop the deterministic forecasting models.
Sequential Cooperative Bayesian Inference.

Cooperation is often implicitly assumed when learning from other agents. Cooperation implies that the agent selecting the data, and the agent learning from the data, have the same goal, that the learner infer the intended hypothesis. Recent models in human and machine learning have demonstrated the possibility of cooperation. We seek foundational theoretical results for cooperative inference by Bayesian agents through sequential data. We develop novel approaches analyzing consistency, rate of convergence and stability of Sequential Cooperative Bayesian Inference (SCBI). Our analysis of the effectiveness, sample efficiency and robustness show that cooperation is not only possible in specific instances but theoretically well-founded in general. We discuss implications for human-human and human-machine cooperation.
Constraint-Based Privacy Preserving-Path Computation Element

Information privacy and protection is fundamental in the context of path computation. When a path computation client (PCC) requests the shortest path between two nodes from a path computation element (PCE), it desires to do so while protecting the sensitive information carried by the query as well as the overall topology of the network. The authors provide a novel framework to compute the shortest path, between a source and a destination, subject to a constraint, represented in the case by a required minimum bandwidth, while preserving the privacy of both client and server. By employing a secure homomorphic encryption scheme, the PCE can blindly compute the path while being oblivious to the content of the encrypted queries. The output of the PCE computation is an encrypted path that is only decipherable by its original secret key. The implementation using the homomorphic scheme over the integers from Van Dijk, Gentry, Halevi, and Vaikuntanathan (DGHV) shows promising results that the authors analyze in detail throughout this paper.
The Readiness of Accounting Students in Facing the Effect of Industrial Revolution 4.0

This research is a descriptive qualitative research. The purpose of this study is to explore the knowledge of accounting students on the Industrial Revolution 4.0 and their impact on accounting. In this digital age the role of accountants has changed to become a provider of insight data, advisors, partnering with technology, and developing into new areas. For this reason students are required to master Industrial Technology 4.0. Respondents in this study are accounting students at UPN Veteran Yogyakarta who have taken financial accounting courses. Data collection techniques are carried out through questionnaires. The questionnaire contains the level of student knowledge of the Industrial Revolution 4.0; the impact of the industrial revolution on accounting and the ability of students to integrate the Industrial Revolution Technology 4.0. The number of students who became research respondents was 237. Based on the frequency distribution, it can be concluded that 9.3% from 237 students really understand Industrial Revolution 4.0 ; 19% from 237 students really understand the effect of Industrial Revolution 4.0 on Accounting ; and only 14.3%  from 237 students who really understand the integration of industrial revolution 4.0 on accounting and business.
RESEARCH AND IMPLEMENTATION OF GEODETIC DATABASE SYSTEM

Abstract. With the gradual formation of the space technical system of National Geodetic Datum, the storage management and application services of the geodetic data have been developing rapidly. This paper studies Geodetic data content, characteristics, classification principles and classification methods in the geodetic technology system and initially forms a standard classification system of geodetic data. On the basis of studying the key technical links to the modern Geodetic Datum comprehensive data acquisition, storage, management and service, this paper has tackled the real-time data optimal storage based on DBFS technology. Technical problems such as multi-dimensional data integration and docking of the software, building a safe and standardized management and the geodetic data service system, coordinating the application of network resources, storage resources, computing resources and other soft and hard environment elements, achieving efficient management and service of land, sea and air integrated observation data results, greatly improving the management ability and application service level of Geodetic data, for surveying and mapping. Business operation of the benchmark database provides support and promotes the social application on geodetic results.
Requirements Communication in Safety-Critical Systems: an extended literature overview

Context: Safety-critical systems (SCS) must be carefully planned since inadequate or misunderstood requirements have been recognized as the major cause of safety-related catastrophes. Objective: We investigate the inte- gration and requirements communication in the requirements engineering (RE) process among different parties when developing SCS. Method: We used a Sys- tematic Mapping Study as the basis for our work. Results: We analyze several aspects such as challenges, domain, requirements activity, languages, tools, sta- keholders involved, communication format, and safety standards. Conclusions: This information contributes to setting up possible collaborative networks and as a reference when developing new research projects.
Layered Embeddings for Amodal Instance Segmentation

The proposed method extends upon the representational output of semantic instance segmentation by explicitly including both visible and occluded parts. A fully convolutional network is trained to produce consistent pixel-level embedding across two layers such that, when clustered, the results convey the full spatial extent and depth ordering of each instance. Results demonstrate that the network can accurately estimate complete masks in the presence of occlusion and outperform leading top-down bounding-box approaches. Source code available at https://github.com/yanfengliu/layered_embeddings
Risk analysis of construction diversion scheme

The determination of diversion risk in the construction of water conservancy and hydropower projects is a key problem related to the guarantee of project safety, saving project investment, giving full play to benefits in advance and facilitating construction. According to the design data, considering the influence of the uncertain factors such as hydrology and hydraulics, this paper analyses the relationship between the elevation of the upstream cofferdam and the upstream design water level, uses the Monte Carlo method to simulate the construction flood process and the discharge capacity of the diversion buildings, makes statistical analysis and determines the risk corresponding to the upstream water level distribution of the cofferdam and the water retaining height of the cofferdam, and establishes the calculation model of the construction diversion risk.
ABILITY TO ANALYZE THE CHARACTERISTICS OF THE POETRY "MUNAJAT 212" STUDENTS OF THE UNA FKIP

This study aims to describe the ability to analyze poetic linguistic characteristics Munajat 212 by Indonesian language and literary education study program students, especially students who sit in semester 6. Representation analyzes the linguistic characteristics of poetry covering several aspects, including 1) Language Compaction, 2) Election Typical words, 3) concrete words, 4) Study, 5) Rhythm or Rhythm, and 6) Typography. The short-term goal of this study is that students are able to know how to analyze the linguistic characteristics of poetry, especially the poem Munajat 212.While the long-term goal in this study is that students are able to apply their abilities in analyzing the linguistic characteristics of poetry in school students and being able to become a reliable poet by applying the linguistic characteristics of the poem. The data for discourse analysis obtained mean values of 83.51, mode 83, median 83, variance 1.11, SD 1.05, highest score 86, and lowest value 82.Based on the results obtained and the results of interviews, it was found several obstacles faced by students in analyzing the linguistic characteristics of poetry Munajat 212, namely: student mastery in analyzing the linguistic characteristics of poetry is still low as evidenced by the data obtained from the analysis of poetic language characteristics, and the lack of understanding of students about analyzing the linguistic characteristics of poetry. Keywords : Ability, Analyzing, Characteristics of Poetry Language
Cross-Platform Measurement on Ad Exchanges

As a key component of online advertising ecosystem, Ad exchange platform (ADX) has been studied extensively. However, existing work is mainly for studying individual ADX platform, and they are not suitable for measuring and comparing the performance of different ADXs. A challenge for comparing the performance of multiple ADXs is as follows: How to enable different ADXs to acquire the same piece of information from a same user, such that we can accurately compare their performance according to the ads they delivered to the same user. For this purpose, in this paper, we propose a parallel cross-platform measurement method, which creates a user (a virtual role) to access the webpages jointly monitored by different ADXs to enable these ADXs to acquire the user-profile from the same user. We collect ads that the ADXs deliver to same user, and compare their ad targeting performance based on these ads. The results validate the efficiency of our proposed method.
Manifold-based Test Generation for Image Classifiers

Neural networks used for image classification tasks in critical applications must be tested with sufficient realistic data to assure their correctness. To effectively test an image classification neural network, one must obtain realistic test data adequate enough to inspire confidence that differences between the implicit requirements and the learned model would be exposed. This raises two challenges: first, an adequate subset of the data points must be carefully chosen to inspire confidence, and second, the implicit requirements must be meaningfully extrapolated to data points beyond those in the explicit training set. This paper proposes a novel framework to address these challenges. Our approach is based on the premise that patterns in a large input data space can be effectively captured in a smaller manifold space, from which similar yet novel test cases---both the input and the label---can be sampled and generated. A variant of Conditional Variational Autoencoder (CVAE) is used for capturing this manifold with a generative function, and a search technique is applied on this manifold space to efficiently find fault-revealing inputs. Experiments show that this approach enables generation of thousands of realistic yet fault-revealing test cases efficiently even for well-trained models.
Uma Lide de Cartazes.

Emerging from a partnership between the Master’s Degree in Design from ESMAD (Escola Superior de Media Artes e Design, Instituto Politécnico do Porto) and Arquivo Municipal da Póvoa de Varzim, the project Uma Lide de Cartazes, consist in the creation of animated posters as an improved form of advertising, inspired by the materials gathered from the archive.This study is centered around the concept of new technologies and media to enhance the static nature of traditional bullfight posters. Handles technologies as augmented reality, animations and the internet to achieve new interactive and dynamic ways to engage aesthetics and convey information. The results indicate that the use of animation dynamically changes the poster layout elements and informations captivating the viewer as well as changing the poster message. The changes can be viewed by anyone using a smartphone and with the help of augmented reality app, such as Artivive.
Presence in VR experiences -- an empirical cost-benefit-analysis

Virtual reality (VR) is on the edge of getting a mainstream platform for gaming, education and product design. The feeling of being present in the virtual world is influenced by many factors and even more intriguing a single negative influence can destroy the illusion that was created with a lot of effort by other measures. Therefore, it is crucial to have a balance between the influencing factors, know the importance of the factors and have a good estimation of how much effort it takes to bring each factor to a certain level of fidelity. This paper collects influencing factors discussed in literature, analyses the immersion of current off-the-shelf VR-solutions and presents results from an empirical study on efforts and benefits from certain aspects influencing presence in VR experiences. It turns out, that sometimes delivering high fidelity is easier to achieve than medium fidelity and for other aspects it is worthwhile investing more effort to achieve higher fidelity to improve presence a lot.
Providing scientific and methodical support to the system of education libraries under the Ministry of education and science of Ukraine and the national academy of educational sciences of Ukraine: experience of V.O. Sukhomlynskyi SSPL of Ukraine

The paper covers the activity performed at V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine, which functions as a coordination, scientific and methodological centre within the system of education libraries under the Ministry of Education and Science of Ukraine and the National Academy of Educational Sciences of Ukraine during the period from 2000 to 2019. Here are the main directions of scientific and methodical work performed at the library: methodical study of changes taken place in certain libraries as well as the system of education libraries in general; development of conceptual, organisational, administrative, regulatory and methodological documents; providing specialists of education libraries with methodological and advisory assistance (including remote help) on library work; expert-diagnostic visits to education libraries for the purpose of library management consulting; creation of the system of methodical publications covering all areas of activity performed by education libraries; maintaining the functioning of the system of education libraries as a single system; introduction of library innovations into the work of education libraries; improvement of professional skills of the specialists of education libraries using different forms and methods; providing access to information resource on librarianship, bibliography studies, bibliology, documentation studies, and information activity in order to meet the professional needs of librarians, educators, and students; scientific cooperation with leading libraries of other systems, departments, institutions, and organisations, regardless form of ownership (including foreign establishments), etc. In the future, the scientific and methodical work of V. O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine will be focused on searching for, systematising and transforming progressive knowledge in the field of library science, as well as on generating new ideas that will further the innovative development of education libraries.
Generalized Autoregressive Neural Network Models

A time series is a sequence of observations taken sequentially in time. The autoregressive integrated moving average is a class of the model more used for times series data. However, this class of model has two critical limitations. It fits well onlyGaussian data with the linear structure of correlation. Here, I present a new model named as generalized autoregressive neural networks, GARNN. The GARNN is an extension of the generalized linear model where the mean marginal depends on the lagged values via the inclusion of the neural network in the link function. A practical application of the model is shown using a well-known poliomyelitis case number, originated analyzed by Zeger and Qaqish (1988),