Reviewerly/exHarmony huggingface dataset:
Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models

Tractable Deep Probabilistic Models (TPMs) are generative models based on arithmetic circuits that allow for exact marginal inference in linear time. These models have obtained promising results in several machine learning tasks. Like many other models, TPMs can produce over-confident incorrect inferences, especially on regions with small statistical support. In this work, we will develop efficient estimators of the predictive uncertainty that are robust to data scarcity and outliers. We investigate two approaches. The first approach measures the variability of the output to perturbations of the model weights. The second approach captures the variability of the prediction to changes in the model architecture. We will evaluate the approaches on challenging tasks such as image completion and multilabel classification.
Peningkatan Kemampuan Menulis Teks Laporan Hasil Observasi dengan Menggunakan Metode Pemodelan pada Siswa MTs Negeri 4 Bantul

The study aims to improve the ability to write the text of the observation report using modeling methods. This research was conducted in the students of the VII-A Madrasah Tsanawiyah Negeri 4, the semester of the year, 2019/2020. This research uses class action methods. Data collection techniques using tests and validity of data are obtained through the validity of the process and the validity of results. The results showed that: (1) Learning to write the text of an observation report using modeling methods can improve the student's ability to write the text of the observation report. This is seen from the average value of the ability to write the text of an observation report before the action is 56.04, increasing to 61.7 on cycles 1 and 77.96 on cycle II. Increased average score from pre-action to cycle I, amounting to 4.90, and to cycle II by 12.67. Increased total average score from pre-action to cycle II by 17.57. (2) The enhancement of the learning process using modeling methods can be seen from the enthusiasm, attention, and activity of students so as to improve the quality of learning to write the report of the observation result and positive change for students. Therefore, the use of modeling methods in learning to write the text of an observation report can be more interesting and enjoyable.
Normative Design for Society and Anticipatory Technology Development: A Double Challenge for Design Research

This paper analyzes the increasing use of design tools and methods towards societal goals, and the interrelated approach to technology development it necessitates.Specifically, we argue that design research can assist in developing an anticipatory approach to technology development, which in turn widens future design possibilities.The paper proceeds in four steps.First, a distinction is made between different approaches to normative design, contrasting a precautionary approach (in which societal goals are constraints to design) from a directive approach (in which these goals are situated as design requirements).Second, a similar distinction between two types of normative technology development is made: precautionary (in which technology is created that safeguards societal goals) and directed (in which technology is created that realizes these goals).Third, an alternative approach to technology development is presented, aimed at enabling future technologies to realize precautionary or directed normative design for societal goals, termed anticipatory normative technology development.Such an anticipatory approach is thus conceptualized as an important enabler of normative design.Fourth, questions of how design research can support normative design is explored, highlighting two key roles: design research can create methods for normative design, and it can provide tools for anticipatory normative technology development that enables future normative design.Related to the latter, design research can draw from its established knowledge and methods for driving innovation.To contextualize this analysis, a running example is used throughout: the development of autonomous vehicles for reducing light pollution.Developing the navigation and sensors of autonomous vehicles to operate in low-light conditions is shown to anticipate an emerging social and environmental goal, thus creating the possibility for future normative design innovations.
MANAGEMENT OF PROFESSIONAL ADAPTATION OF BACHELORS OF SOCIAL WORK

Черникова Елена Геннадьевна
Secure Event Logging Using a Blockchain of Heterogeneous Computing Resources

Secure logging is essential for the integrity and accountability of cyber-physical systems (CPS). To prevent modification of log files the integrity of data must be ensured. In this work, we propose a solution for secure event in cyberphysical systems logging based on the blockchain technology, by encapsulating event data in blocks. The proposed solution considers the real-time application constraints that are inherent in CPS monitoring and control functions by optimizing the heterogeneous resources governing blockchain computations. In doing so, the proposed blockchain mechanism manages to deliver events in hard-to-tamper ledger blocks that can be accessed and utilized by the various functions and components of the system. Performance analysis of the proposed solution is conducted through extensive simulation, demonstrating the effectiveness of the proposed approach in delivering blocks of events on time using the minimum computational resources.
Estimation of Risk in Software Re-engineering Projects

Although re-engineering is often used as a means to reduce the risk, reduce costs and maintain the operation of deriving the software, but re-engineering cannot avoid risk.Risk is a probability of occurrence of some unwanted and harmful event to the project.These events can result in cost overruns, schedule slippage, or failure to meet their project goals.Simulation is an important technique for calculate the probability of risk in software reengineering projects.This paper is aimed at implementing a simulator in Monte Carlo algorithm and Matlab language which estimates the probability of risk during project completion.
TECHNOLOGY OF IDENTIFYING ANTIPATTERNS IN ANDROID PROJECTS WRITTEN IN KOTLIN LANGUAGE

The problem of the lack of instruments for identifying the characteristics of low-quality code in Android projects that are written in the Kotlin language is determined.A review of modern approaches for identifying antipatterns in program code is accomplished.The analysis of the methods used to find problems with code in Android projects is performed.DECOR and Paprika approaches are considered.Conclusions are drawn about the importance of finding design flaws in program code for the mobile software development and its further support.An antipatterns identification approach for Kotlin language program code in Android projects is proposed.An algorithm for identifying low-quality Kotlin code is presented.The technology for detecting poor quality code characteristics consists of four stages: collecting metrics about an analyzed software system, building a quality model, converting a quality model into a graph representation, and identifying predefined antipatterns.The collection of metrics, including the search for both Androidspecific and object-oriented metrics of Chidamber and Kamerer, is proposed to be implemented through parsing source code and converting it into an abstract syntax tree using the KASTree library.The implementation of KASTree library usage is offered through the Adapter design pattern.The construction of a quality model is implemented using the Paprika tool, supplemented by a number of introduced metrics.Conversion of quality model exactly into graph representation is used to identify antipatterns in order to ensure the speed and quality of complex queries execution for identifying antipatterns.Antipatterns identification using database queries is based on various template rules, including the Catolino rules.Different features of applying the Cypher query language to a graph database are used to represent the rules in form of queries.Results of the work can be used in development of software for poor quality code identification in mobile applications written in Kotlin language, as well as in studies of mobile development antipatterns for this language.
Mind and Map Method: Upaya Meningkatkan Keterampilan Menulis Teks Deskripsi pada Siswa MTs Negeri 4 Bantul

This research aims to improve the writing ability of text descriptions through learning by using the mind and map method in 25 students of the VII-F MTs Negeri 4 Bantul Semester in the year of the 2019/2020 course. The study uses class action methods, consisting of two cycles covering the planning, implementation, observation, and reflection stages. Data collection techniques using writing tests, observations, field records and photo documentation. The results showed that learning with the mind map method can improve the activity and skills of students writing the description text, both in terms of process and product. It is demonstrated by the enhancement of students in intensified student interest, kekondusifan the photo observation process to create mind map, student intensified in doing independent task, kekondusifan students when a student is presenting, and kekondusifan students during reflection activities. Quality improvement of the process positively impacts the product quality improvement. It is seen in the test results writing the description text from the pre-action stage until cycle 2 increased by a pre-action of 52%, I cycle 76%, and cycle II 96%. The mind map method is one of the learning method of writing that is able to improve the activity and skills of the student writing the description text.
Implementation of Secure Voting System using Blockchain

It is very challenging to build a secure voting system that offers fairness and privacy of current voting schemes.In this implementation paper, we evaluate an application of blockchain as a service to implement distributed electronic voting systems.Our objective is to provide a decentralized architecture to run and support a voting scheme that is open, fair, and independently verifiable.Our proposed solution implements the protocol which achieves fundamental e-voting properties as well as offer a degree of decentralization and allow for the voter to change/update their vote and the experimental result shows that our proposed solution is beneficial for the existing and upcoming voting system.
AutoSurvey: Automatic Survey Generation based on a Research Draft

This work presents AutoSurvey, an intelligent system that performs literature survey and generates a summary specific to a research draft. A neural model for information structure analysis is employed for extracting fine-grained information from the abstracts of previous work, and a novel evolutionary multi-source summarization model is proposed for generating the summary of related work. This system is extremely used for both academic and educational purposes.
An Algorithm for Computing Average Mutual Information using Probability Distribution Smoothing

There is continuing interest in using Average Mutual Information (AMI) to quantify the pair-wise distance between dataset profiles. Among several algorithms used to find a numerical estimation of AMI, the histogram method is the most common since it provides simplicity and least cost. However, this algorithm is known to underestimate the computed entropies and to overestimate the resulting AMI. Kernel Density Estimator (KDE)-based algorithms advanced to alleviate such systematic errors rely on bin-level smoothing. In the present work, we propose an alternative algorithm that uses smoothing on the probability distribution level. We consider several smoothing functions, both in the probability space and in its frequency space. An experimental approach is used to investigate the effect of such modification on the computation of both the entropy and the AMI. Results show that, to a significant extent, the present method is able to remove systematic errors in computing entropy and AMI. It is also shown that the present algorithm leads to better reconstruction of multivariate time series when AMI is used in conjunction with their independent components.
Evaluation of domain ontology requirements in e-tutor framework

The domain module within Intelligent Tutoring Systems is used to describe the course topics including the knowledge units and competencies. Ontology is a good solution for knowledge management as it can provide a standardized way and a reasoning engine for the related knowledge management tasks. In this paper, we analyze the functionality of the usual OWL-based ontology construction and set the main requirements to enhance the usability of the ontology knowledge modelling language. Based on these shortcomings, we set the main requirements against an efficient ITS domain ontology description language. This language should be based on simplified Manchester syntax and it should contain additional structural elements too.
Dual-Enhanced Registration for Field of View Ultrasound Sonography

Extended Field of View Ultrasound Sonography (EFOV-US) uses the existing ultrasound images for image stitching, so as to display the shape and scope of organ occupation and the relationship with surrounding tissues comprehensively. However, there are still some problems in Extended Field of View Ultrasound Sonography, such as matching error and unstable quality of image stitching. In view of these problems, we propose Dual-enhanced EFOV-US method that overcomes the limitation and produces higher quality results. Firstly, the gray enhancement method is used to improve the image contrast and reduce the noise interference. Then the super-resolution method based on the generative adversarial network is used to improve the resolution of the ultrasonic image further and increase the number of feature point matching between stitching images. The high quality ultrasound wide-range image is gotten by stitching and fusing the double enhanced image. The experimental results show that the proposed method is effective and practical.
Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract)

Identifying people in historical photographs is important for interpreting material culture, correcting the historical record, and creating economic value, but it is also a complex and challenging task. In this paper, we focus on identifying portraits of soldiers who participated in the American Civil War (1861-65). Millions of these portraits survive, but only 10-20% are identified. We created Photo Sleuth, a web-based platform that combines crowdsourced human expertise and automated face recognition to support Civil War portrait identification. Our mixed-methods evaluation of Photo Sleuth one month after its public launch showed that it helped users successfully identify unknown portraits.
Analysis of Consumer Data in Diff’s Reflexology with Tableau Method

Data management is essential in a company even though it has not an easy process. Diff’s Reflexology still records data on consumer data manually and already has data records of each patient that has been treated with various existing treatments. Diff’s Reflexology still has problems in terms of effectiveness and efficiency because it still records it manually. The lack of efficacy is indicated by the amount of consumer data that has been lost since the first Diff’s Reflexology was established. This research aims to produce useful information so that Diff's Reflexology can increase its effectiveness and efficiency. Data analysis in this study was carried out using the Tableau application, and the research method used was a qualitative research method with a descriptive approach. The results showed that in the last three quarters in 2019, the type of Massage treatment was the highest type of treatment for both male and female consumers. The number of male consumers in Diff's Reflexology was more per month compared to female consumers who are in the fourth quarter of 2019 has 624 male consumers and 366 female consumers. It was found that the productivity of the therapists was different from both male and female therapists, and massage treatment was the highest gross income source with a total of 65 million rupiahs for three quarters.
Symmetrical Trapezoidal Normal Distribution and its Parameter Estimation

The trapezoidal rule is applied for construction a new distribution based on normal distribution, is called trapezoidal normal distribution under the same conditions.Furthermore, we illustrate the parameter estimation of the trapezoidal normal distribution using standard differential evolution (DE) algorithm for the sample sizes equal to 10 to 100.The results show the K-S statistic of the trapezoidal normal distribution is less than the K-S statistic of the normal distribution of each sample size data.
The ICT and New Scenarios for Diversity

Research is a process aimed at seeking new knowledge, in this case, it will seek to find alternative ways in the field of new technologies that serve to support special educational needs. Society demands these technological contributions to solve problems and allow man to work with greater ergonomics; the school, a social institution, also needs these resources so that all students can build a functional and meaningful teaching-learning process. The Educational System proposes an education that meets the educational needs of all students; and from these pages it is intended that new technologies are a way of supporting that attend to diversity.
Development of education in the context of state management of the quality of life of the population in the Republic of Kazakhstan

Object: This paper aims is to identify current trends and challenges to providing quality and affordable education to the population through the analysis of the process of state management of the quality of life in education, and to propose recommendations on how to resolve the said challenges and improve the quality of education in the Republic of Kazakhstan.Methods: The following methods were used during the research: empirical, analytical, synthetic and comparativelogical ones.Results: The article explores the education system of the Republic of Kazakhstan as a key branch of the social sector and the most important aspect in the state management of the quality of life of the country's population. In particular, we have seen into the indicators that characterize the following: coverage of children with preschool education, dynamics of secondary, technical and professional, higher and postgraduate education, inclusive education development, all of which are aimed at comprehensive development, creativity and strategic thinking, the ability to adapt to different personal conditions and contribute to improving the quality of life of the population, and consequently, sustainable socioeconomic development of the country.Conclusions: As a result of the research, we have identified issues, the solution of which shall help to improve the quality of educational services and ensure their accessibility. We have formulated conclusions and proposals to improve the effectiveness of strategic management of the education system to achieve a decent level of quality of life for the population in the Republic of Kazakhstan. Recommendations formulated and proposed by the authors can be used by research centers involved in national research, by public associations and public administrations directly for the elaboration of state programs, strategic plans in education and in the process of improving the quality of education management system as a component of the quality of life of the Republic of Kazakhstan population as a whole.
A Study on the Mode of Innovation and Entrepreneurship Training for College Business English Majors

&lt;p&gt;With the deepening of reform and opening up, China's economy has stepped into the fast track of high-speed development. In order to meet the needs of this situation, it is an inevitable trend for business English majors in colleges and universities to strengthen innovation and entrepreneurship learning. Training innovative and entrepreneurial talents for the society is also the need of higher education reform. Based on the social needs and the advantages of business English majors in colleges and universities, this paper explores the training mode of innovation and entrepreneurship talents suitable for economic development, and integrates business English education in colleges and universities into innovation and entrepreneurship education, so as to improve students' understanding of innovation and entrepreneurship education and further enhance their ability of innovation and development.&lt;/p&gt;
Language Independent Sequence Labelling for Opinion Target Extraction (Extended Abstract)

In this paper we present a language independent system to model Opinion Target Extraction (OTE) as a sequence labelling task. The system consists of a combination of clustering features implemented on top of a simple set of shallow local features. Experiments on the well known Aspect Based Sentiment Analysis (ABSA) benchmarks show that our approach is very competitive across languages, obtaining, at the time of writing, best results for six languages in seven different datasets. Furthermore, the results provide further insights into the behaviour of clustering features for sequence labeling tasks. Finally, we also show that these results can be outperformed by recent advances in contextual word embeddings and the transformer architecture. The system and models generated in this work are available for public use and to facilitate reproducibility of results.
Peran Ontologi dalam Pengembangan Sistem Rekomendasi pada Domain Online Learning

As online learning resources increase exponentially on the World Wide Web, online students have difficulty choosing the most suitable and relevant learning material that meets their learning needs due to information overload. Online learning recommendation system is used to predict the preferences or ranking of learners' targets on learning objects for the purpose of generating recommendations. However, the Recommendation system is considered to lack the ability to resolve semantic interoperability issues with heterogeneous sources of information. The purpose of this study is to discuss the role of ontology in the development of recommendation systems in the online learning domain. There are four electronic journal databases selected as references, namely IEEE, Science Direct, Springer Link, and ACM Digital Library. This study obtained 9 articles that were synthesized to answer research questions. This study shows that the involvement of ontology for knowledge representation in the recommendation process can improve the accuracy and quality of recommendations and at the same time help to overcome the weaknesses associated with conventional recommendations.