Reviewerly/exHarmony huggingface dataset:
Self-supervised Automated Mineralogical and Chemical Analysis for Hyperspectral Datasets

&amp;lt;p&amp;gt;Identification of unknown micro- and nano-sized mineral phases is commonly achieved by analysing chemical maps generated from hyperspectral datasets, particularly scanning electron microscope - energy dispersive X-ray spectroscopy (SEM-EDX). However, the accuracy and reliability are limited by subjective human interpretation and instrumental artefacts in the chemical maps. At the same time, machine learning has emerged as a powerful method to overcome the roadblocks. Here, we propose a self-supervised machine learning approach to not only identify unknown phases but also unmix the overlapped chemical signals of individual phases with no need for user expertise in mineralogy. This approach leverages the guidance of gaussian mixture modelling (GMM) clustering fitted on an informative latent space of pixel-wise elemental data points modelled using a neural network autoencoder, and deconvolutes the overlapped chemical signals of phases using non-negative matrix factorisation (NMF). We evaluate the reliability and the accuracy of the new approach using two hyperspectral EDX datasets. The first dataset was measured from an intentionally fabricated sample, where seven known mineral particles are physically overlapping with each other as well as the substrate. Without any prior knowledge, the proposed approach successfully identified all major phases and recovered the original chemical spectra of the individual phases with high accuracy. In the second case, the dataset was collected from a potential vehicular source of particulate matter air pollution, where identification of the individual pollution particles is complicated by the complex nature of the sample. The approach once again was able to identify the potential Fe-bearing ultrafine particles and isolate the background-subtracted elemental signal. We demonstrate a robust approach that potentially brings a significant improvement of mineralogical and chemical analysis in a fully automated manner. In addition, the proposed analysis process has been built into a user-friendly Python code with graphical user interface (GUI) for ease of use by general users.&amp;lt;/p&amp;gt;
Literature Representation using Character Networks based on Sentiment Analysis

In this study, we propose a method for expressing literary works using machine learning. The proposed method expresses novels by composing a network of characters appearing in the novel and identifying the flow of sentiment scores between characters who agree or oppose the main character. Characters, represented as nodes on the constructed network, are extracted via the name entity recognizer, whereas edges are constructed based on the emotional words described in the novel. Protagonist and antagonist groups on the character network are classified via signed graph clustering. The novel proceeds through the interaction between the characters, and the groups are segmented to emphasize this through character grouping and network construction. A novel is classified into four acts, and the emotions of each group are emphasized and expressed in each act. In this study, 20 novels are clustered using the proposed method; subsequently, they are compared and tested using other expression methods.
Assessing cyber security consumer support from technology retailers

The pandemic has significantly changed the way we work, and many organisations were not prepared for that shift. Many people are working from home but without the protections normally expected in an enterprise environment. Home workers find themselves dependent on the security features and services provided by the vendors of the technology they are using. But are these adequate?
The Samos earthquake event (Mw = 7, 30 October 2020, Greece) as case study for applying machine learning on texts and photos scraped from social networks for developing seismic intensity maps.

&amp;lt;p&amp;gt;Main purpose of current research article is to present latest findings on automatic methods of manipulating social network data for developing seismic intensity maps. As case study the author selected the 2020 Samos earthquake event (Mw= 7, 30 October 2020, Greece). That earthquake event had significant consequences to the urban environment along with 2 deaths and 19 injuries. Initially an automatic approach, presented recently in the international literature was applied producing thus seismic intensity maps from tweets. Furthermore, some initial findings regarding the use of machine learning in various parts of the automatic methodology were presented along with potential of using photos posted in social networks. The data used were several thousands tweets and instagram posts.The results, provide vital findings in enriching data sources, data types, and effective rapid processing.&amp;lt;/p&amp;gt;
Sparse hypergraphs: From theory to applications

给定正整数~$r,e,v$，如果某个~$r$-一致超图的任意~$e$~条不同边的并都包含至少~$v+1$~个顶点，则我们称其是~$(v,e)$-free~或者~$(v,e)$-稀疏的. 稀疏超图的概念是由~Brown，Erd{\\H{o}}s，S{\\o}s~在上个世纪七十年代提出的. 目前，研究给定顶点的稀疏超图所能包含最大边数的上下界已成为极值组合学研究领域内的核心问题之一. 该问题的研究方法丰富多变，涉及组合、概率、代数、数论等多个领域. 我们将介绍~Brown，Erd{\\H{o}}s，S{\\o}s~关于稀疏超图的两个重要猜想的最新进展，以及稀疏超图在极值组合与信息科学中的若干应用，包括朱烈教授曾作出突出贡献的完美哈希矩阵、可分哈希矩阵等几类信息安全中的研究问题. 此外，我们在某些参数下给出了完美哈希矩阵与~union-free~超图的新构造. 我们的构造改进了相应问题的已知最优下界.
THE SHARED RESEARCH FACILITIES "GEOSPECTRUM" OF THE GEOLOGICAL INSTITUTE SB RAS

The Shared Research Facilities "Geospectrum" of the Geological Institute SB RAS (Ulan-Ude) was created based on the analytical base of the Geological Institute SB RAS (GIN SB RAS, Ulan-Ude). Its equipment is used for isotopy of light elements, U-Th-Pb geochronology of igneous, metamorphic and sedimentary rocks. In addition, a large volume of mineralogical and geochemical research is carried out to solve petrological, geochemical, lithological-geochemical and environmental basic and applied problems.
Comparisons of Aboutness of OCLC FAST Headings and IMDb “Plot Keywords” for Documentary Films

This study analyzed OCLC Faceted Application of Subject Terminology (FAST) headings and Internet Movie Database (IMDb) “plot keywords” for a shared set of documentary films to determine how well the aboutness identified by the former was reproduced by the latter. A randomized list of documentary films held at the Iowa State University Library, a large academic research library, was created. The FAST headings were compared to each “plot keyword” used in the corresponding IMDb record to determine if they met one or more of the match types defined for this study: exact match, close match, broad match, narrow match, and closely-related match. In total, 604 FAST headings from 100 OCLC records were analyzed. This data was used to calculate breakdowns of average recall and average precision evaluating the IMDb records using the OCLC records. This study found that relatively little of the aboutness expressed by FAST headings was represented by the “plot keywords” in the corresponding IMDb records. The average recall and average precision of the IMDb records, judged as an attempt to reproduce the FAST headings, was 23.38% and 18.89%, respectively. By comparing OCLC and IMDb subject metadata for documentary films, this study advances scholarship on the relationship between professionally-created and user-created metadata.
A LEARNING PATH FOR MODULAR SYNTHESIS

Sound synthesizers appeared in the 1960s and since then they have revolutionized the music world. The first instruments were modular: cables had to be used to connect different sections of the instrument in order to produce sounds. In spite of their flexibility, their various disadvantages led the industry towards more compact, reliable and easy to use models. This approach made electronic synthesizers extremely popular, and nowadays they have a big influence in contemporary music. Despite the importance of the field, learning about sound synthesis is not easy: the concepts involved are sometimes quite technical, and the cost of the required gear is often very high. In this paper we propose the use of VCV Rack as an ideal environment to learn about sound synthesis. First of all, it simulates Eurorack, a compact modular synthesizer standard, and modular means flexibility, variety and the possibility of concentrating on the modules and concepts that the user wants. VCV Rack has a very big community of devoted users that offer videos and tutorials to learn at your own pace, it is free and it has a very friendly and efficient user interface that mimics the operation of a real modular synthesizer. In this paper we explore a few sound synthesis concepts with VCV Rack: visualizing the harmonic content of different waveforms, mixing sounds, beat frequencies, hard and soft synchronization of oscillators, filtering sounds, filter slopes, resonance, etc. We have used VCV Rack in two courses, and we have confirmed that it is a very adequate tool to illustrate the basic techniques of sound synthesis. But this is just the beginning, and with the hundreds of modules available in VCV Rack, and the active and helpful community of users, it constitutes a very good option for learning about sound synthesis in a zero cost and high quality environment.
Session 26 Overview: Highlighted Chip Releases: Systems and Quantum Computing

This session highlights innovations in Systems and Quantum Computing announced within the last year.As Moore's law is slowing down, products are moving towards complex system-level innovations to keep up with power and performance requirements.Quantum computing, which was once a dream, is becoming a reality with products on the horizon.These papers delve into practical system-related topics, mass-production related challenges and solutions (e.g., cost, reliability, thermal/voltage issues, packaging, etc.) in addition to circuit content and silicon measurement results.
Translation strategies of Koha for multilingual interface management

Purpose The automation of libraries has made a significant difference in the quality of service. All libraries seek to improve the quality of their services, and the library seems to be a frequent target for modernization efforts throughout the globe. Local dialects need specific translations to use library management software. A variety of languages are available to create open-source techniques. The integrated library management system Koha is gaining traction. The Koha software has been translated and made accessible to a worldwide audience in many languages. Design/methodology/approach This experiment was based on a controlled setting and a realistic observation of the Koha translation process. A sample of a population is selected to study and draw conclusions about the entire population. Findings Results are based on a statistical report made available on the Koha translation site for the gathering of sample data, which is based on sample data that has been collected and brought to light. This analysis demonstrates how to translate Koha software on a pootle server step by step using sting data inputs on different po files accessible in translation databases. Originality/value The authors of this paper explain the procedure of translating Koha software and provide a global overview of Koha software translation into different languages throughout the world. Therefore, it can be expected that the importance of Koha software will increase tremendously for the people of different languages through the method of translation.
5-year Efforts and Operational Results of Virtual Computer Classroom in TUAT

Tokyo University of Agriculture and Technology (TUAT) has provided a university information system based on BYOD (Bring Your Own Device) environment since April 2016. This university information system has provided a brand-new computer system for the classroom, called TUAT Virtual Computer Classroom (TUAT-VCCR), replacing old computer rooms and terminals. The unique feature of this system is to provide a platform-independent computer exercise environment by constructing a TUAT-VCCR that can be accessed via a web browser on an off-campus cloud. This article shares our 5-year efforts and operational reports of TUAT-VCCR and the knowledge gained from the operation.
A Comparative Study of Various Edge Detection Techniques for Underwater Images

Nowadays, underwater image identification is a challenging task for many researchers focusing on various applications, such as tracking fish species, monitoring coral reef species, and counting marine species. Because underwater images frequently suffer from distortion and light attenuation, pre-processing steps are required in order to enhance their quality. In this paper, we used multiple edge detection techniques to determine the edges of the underwater images. The pictures were pre-processed with the use of specific techniques, such as enhancement processing, Wiener filtering, median filtering and thresholding. Coral reef pictures were used as a dataset of underwater images to test the efficiency of each edge detection method used in the experiment. All coral reef image datasets were captured using an underwater GoPro camera. The performance of each edge detection technique was evaluated using mean square error (MSE) and peak signal to noise ratio (PSNR). The lowest MSE value and the highest PSNR value represent the best quality of underwater images. The results of the experiment showed that the Canny edge detection technique outperformed other approaches used in the course of the project.
An Intelligent Tutoring System for the Teaching of the Industry Equipment and its Student Modelling

This paper shows a model of Tutor-Help, an Intelligent Tutoring System oriented to train on functioning and operation of industrial equipment. Written in C++ v3.1, the system uses the OOP facilities, mainly the inheritance and polymorphism. The construction of the new industry and its subsequent operation with quality and efficiency, performing the established norms, requires an appropriate qualification of personnel who will work in it. Nowadays, for training and certification of operation personnel different computing systems are in use. These systems are very expensive and complex. The main disadvantage of them is that they are unique. During the last few years simulators and Computer Based Systems without adaptability for the user have been developed [DEF92]. Furthermore, the Artificial Intelligence techniques have been introduced to make these systems more powerful [DEF92, MDL92].
Fast and effective AI approaches for video quality improvement

In this work we present solutions based on AI techniques to the problem of real-time video quality improvement, addressing both video super resolution and compression artefact removal. These solutions can be used to revamp video archive materials allowing their reuse in modern video production and to improve the end user experience playing streaming videos in higher quality while requiring less bandwidth for their transmission. The proposed approaches can be used on a variety of devices as a post-processing step, without requiring any change in existing video encoding and transmission pipelines. Experiments on standard video datasets have shown that the proposed approaches improve video quality metrics considering either fixed bandwidth budgets or fixed quality goals.
The importance of integrating Digital Twins and Earth Observation to support resilient society applications in Cyprus

&amp;lt;p&amp;gt;This abstract explores the importance of integrating digital twins and earth observation for supporting natural disasters management in Cyprus. Indeed, this study shows how a digital twin will be developed based on existing sources of data like satellite imagery, maps, in situ data and other auxiliary data such as meteorological, hydrological data etc. This digital twin will be used to predict future conditions of a certain area of interest in Pafos District in Cyprus. The main aim is to update the proposed digital twin using satellite images such as Copernicus data for efficient decision making from the key stakeholders such as government and public authorities.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Several natural disasters have been identified in the national risk assessment of Cyprus as the main priorities such as floods, earthquakes, fires, landslides etc. In the proposed digital twin these four hazards will be considered. However, this abstract shows the prelimary results retrieved by examining the impact of floods in an area of interest in Pafos District area in Cyprus by integrating several data and techniques such as earth observation and hydrological modeling.&amp;lt;/p&amp;gt;
E-Commerce Websites as a Helping Tool for Collection Development in Libraries: A Case Study

The selection of books in libraries is a continuous and ongoing process, which the library has to approach the external market.This study has attempted to understand the effect and utility of e-commerce and e-commerce websites in the changing market environment.This study analyzes the provided information and facilities provided to the user to select books on popular e-commerce websites.Learners tried to learn the selection process of books of various types of academic libraries through descriptive research methods and the utility of e-commerce sites.The study suggests that e-commerce and publisher websites can be helpful along with the traditional tools used in the book selection process.
Extracting Rules from Neural Networks with Partial Interpretations

We investigate the problem of extracting rules, expressed in Horn logic, from neural network models. Our work is based on the exact learning model, in which a learner interacts with a teacher (the neural network model) via queries in order to learn an abstract target concept, which in our case is a set of Horn rules. We consider partial interpretations to formulate the queries. These can be understood as a representation of the world where part of the knowledge regarding the truthiness of propositions is unknown. We employ Angluin s algorithm for learning Horn rules via queries and evaluate our strategy empirically.
A Foundational Study on the Application of Contemporary Art to Art Education: From the Perspective of Education for International Understanding and Global Citizenship Education

본 기초 연구는 동시대 예술을 활용하는 미술 교육이 시대의 변화에 따른 국제이해교육과 세계시민교육을 시기적절하게 다룰 수 있는 중요한 교과로서의 기능을 담당할 수 있음을 제안하면서, 동시대 예술을 미술 교과에서 도입하고자 하는 시도를좀 더 구체화한다. 이를 위해, ‘국제이해교육’ 및 ‘세계시민교육’과 관련한 문헌 연구를 통해 ‘국제이해교육’과 ‘세계시민교육’ 개념에서 서로 겹치는 부분이 존재한다는 것을 확인하고 ‘동시대 이슈’, ‘다양성’, ‘관계와 연결’, ‘혼종과 변화’라는 키워드를 도출하였다. 그 다음 이 네 가지 키워드를 중심으로 동시대 예술의 영역에서 국제이해교육과 세계시민교육을 다루는데 도움이 되는 예술가 및 작품의 예시들을 살펴보았다. 그다음, ‘동시대 이슈’, ‘다양성’, ‘관계와 연결’, ‘혼종과 변화’의 키워드를 중심으로 수업 모형의 예시를 단계별로 구체화하여 제안하였으며, 미술 교육자의 큐레토리얼 역량을 강조하였다.This foundational study is based on the premise that there are overlapping areas within the concepts of Education for International Understanding and Global Citizenship Education. This study suggests that art education utilizing contemporary art can serve as an important subject that can dealt with Education for International Understanding and Global Citizenship Education in a timely matter. To support, key words such as ‘contemporary issues,’ ‘diversity,’ ‘relationship and connection,’ ‘hybridity and transformation’ were derived through literature review. Then, focusing on these four key words, examples of contemporary artists and works were examined. Finally, four exemplar educational models are suggested and the importance of art educators’ curatorial capability was emphasized.
SeisPPSD: an interactive web front-end and scalable HPC back-end for probabilistic power-spectral-density calculations

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Offering a web-interface alongside a back-end for the calculation of probabilistic power-spectral-densities (PPSD) is the main goal of this project. No simple out-of-the-box open-source solution is available so far. Moreover, researchers should get access to the information needed in a straightforward way.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;The project was initiated to process data routinely acquired at the KIT GPI seismological data center in order to enhance the quality control of the acquired data and station metadata. Furthermore, the PPSD gallery should develop into a starting point for further scientific research.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Here we present SeisPPSD, a comprehensive solution for the calculation and inspection of PPSDs building on existing ObsPy codes. Next to an intuitive gallery and archive which offers a fine granularity in time, the user can create PPSDs&amp;amp;#160;interactively, e.g. comparing the day and night noise levels. As well, plots with noise levels for distinct frequencies over time can be visualized.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;The web front-end is mainly written in HTML but using Python and Javascript for the interactive parts. The back-end is implemented in Python and is distributing the PPSD calculation in a scalable fashion to the HPC environment.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Apart from an easy to use web-interface, the researcher has access to an archive with the data derived product. This creates the opportunity for the researchers to customize plots with the already (pre-)calculated PPSD files. Furthermore, those files are relatively small and therefore uncomplicated to share with researchers outside. The PPSD-files can be used with the standard ObsPy module opening the possibility for further collaboration.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;
An integrated approach for environmental multi-source remote sensing

&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Remote sensing measurements have benefited from a great technological improvement, which has allowed a higher degree of automation while increasing spatial and temporal resolution of the collected data. Multi-&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160; scale and multi-frequency optical and radar satellite sensors, often adopted in an integrated manner, are starting to provide efficient solutions for controlling and monitoring rapidly evolving urban and natural areas. On the other hand, close range remote-sensing techniques, such as operated by UAV platforms, and innovative ground-based instruments offer, respectively, the chance to downscale the observation performing site-specific analysis at an enhanced resolution and to collect in-situ dataset for calibration and data quality. By improving the quantity and quality of the collected data, a better understanding of the in-going processes is possible and the setting up of a numerical forecast model for future scenarios.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Therefore, implementation of integrated techniques for environmental monitoring turns out to be a strategic solution to analyze hazardous areas at different spatial and temporal resolution. Research devoted to the optimization of data processing tools by means of AI algorithms has evolved with the aim of improving the level of information and its reliability. In this context, a great impact is linked to the availability of open data and open-source processing tools distributed after the Copernicus Program.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;A review of the available technologies for environmental monitoring is provided including examples on experimental cases in areas affected by natural hazards (volcanic eruptions, landslides, coastal erosion, flooding, etc.) and human activities that can produce incidental damages on the environment (urbanization, agriculture, infrastructures, landfills, dumpsites, pollutions, etc.). In addition, the same approach is useful for monitoring the degradation of the cultural heritage sites. Finally, the capability of collecting fat at a global level contributed to the analysis of environmental and economic impacts consequent the Covid-19 pandemic.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;