Reviewerly/exHarmony huggingface dataset:
Informative-Communicatory Space of Education in the Russian Federation: Genesis and Development Patterns in the Digital Age

In the context of the formation of the foundations of the global information society, the usage of information technologies in the educational sphere is becoming particularly relevant.The relevance of the study is determined by the following factors: -Trends in virtualization, networking, and digitalization that reveal themselves in virtually unlimited access to information and actualize the question of the algorithm for selecting it in the global world; -Inconsistency of the system of educational interactions that acquire a virtual nature.The main contradictions are: contradiction between information that includes non-constructive information flows and the need to obtain relevant knowledge; -Deformation of the traditional axiological scale and the formation of new values and meanings, which does not contribute to solving problems related to the selection and systematization of information in the educational process; -Information on the modern educational process defines goals and tasks in a new way.Within the framework in the article the main approaches are used while defining the concept are highlighted and characterized; the prerequisites for the emergence of the informative-communicatory space of education in the global context are outlined; the regularities of development of informativecommunicatory space of education is revealed.
Effective Pedestrian Detection and Tracking in Varying Light Conditions

Despite all significant advances in the detection of pedestrians transmitted by computer vision for driver assistance, it remains a challenging issue. Several studies have been conducted to develop the accuracy of pedestrian detection of intelligent surveillance systems. However, person detection in outdoor conditions is a difficult problem due to the variation in lighting, shadows and occlusions. In this paper we have proposed new methodology for pedestrian detection and tracking under varying light condition for advanced driver assistance system. The main aim of the proposed systems is to avoid collision of vehicles with the pedestrians while driving on roads. It is very difficult to detect a pedestrian due to the varying light conditions (night time, fog). With the proposed systems another way of driver provision is realized, which can pay off the weaknesses of the human visual system. The evaluation is done on firsthand dataset that constructed for this purpose as well as on the freely available KAIST multispectral dataset. Three kinds of databases were tested, taking into account various environmental factors with daytime, night time and fog. Experiments shows proposed system is strong and works successfully.
FingerPro and D-MixSIAR: New fingerprinting development approaches for tracking sediment provenance

1 .pdf copy (1 Pag.) of the abstract published by the Organization. © Author(s) 2018. CC Attribution 4.0 license.
Hacia una caracterización lingüística de las interacciones en WhatsApp

The emergence of new communicative contexts and new forms of interaction has led to changes in the ways of communicating. Some authors speak of a new communicative paradigm caused by a new level of interaction arisen in the technological context. In this article, we focus on a new technology that can be included in the so-called computer mediated communication: WhatsApp. The aim of this work is to study WhatsApp interactions understood as a particular type of computer-mediated talks. Specifically we will: 1) Characterize the language used in WhatsApp interactions at every linguistic level, from phonetics to pragmatics, through morphology, vocabulary and syntax. 2) Analyze how the absence of nonverbal communication (paralanguage and kinesics) in such interactions is managed. 3) Determine whether WhatsApp interactions are manifestations of spoken or written language, or, on the contrary, they are a new type of language that cannot be classified as oral or written. And 4) determine whether WhatsApp interactions can be qualified as conversational.
Design of Learning Modules Writing Narrative Text Based on Project Based Learning (PjBL) by Using Mobile Devices

Every aspect of education continues to experience innovation after the internet, digital tools and technological gadgets have been easily accessed everywhere marked by online reading, electronic books and audio books along with printed material. Based on that, this study aims to develop learning modules for learning to write narrative texts based on project based learning using mobile devices. This type of research is R&D (research & development). The development model used is a 4-D model (define, design, develop, and assess). The research instruments used were questionnaires, observation sheets, interview guides, and tests. In this paper, the results of the study are more focused on discussing the design of the developed learning modules. By understanding the design, readers can develop learning modules based on project based learning for types of narrative texts at various levels of education. The module design that was designed was validated by experts and concluded that the module was categorized as very valid and could be tested.
Workshop on Personalized Access to Cultural Heritage: PATCH'20

ACM PATCH 2020, organized in conjunction with the 28th International Conference on User Modeling, Adaptation and Personalization, is the latest event of the PATCH series, started in 2007 and held within the UMAP and IUI Conference series. We summarize the main ideas addressed in the papers accepted for publication in the workshop proceedings and for presentation at the event.
Measurement-induced geometric measures of correlations based on the trace distance for two-qubit X states

Abstract We apply the modified Brodutch and Modi method of constructing geometric measures of correlations to obtain analytical expressions for measurement-induced geometric classical and quantum correlations based on the trace distance for two-qubit X states. Moreover, we study continuity of the classical and quantum correlations for these states. In particular, we show that these correlations may not be continuous.
A Web-based Interactive Transcription Tool for Encrypted Manuscripts

Manual transcription of handwritten text is a time consuming task.In the case of encrypted manuscripts, the recognition is even more complex due to the huge variety of alphabets and symbol sets.To speed up and ease this process, we present a web-based tool aimed to (semi)-automatically transcribe the encrypted sources.The user uploads one or several images of the desired encrypted document(s) as input, and the system returns the transcription(s).This process is carried out in an interactive fashion with the user to obtain more accurate results.For discovering and testing, the developed web tool is freely available 1 .
Causality, Responsibility and Blame in Team Plans

Many objectives can be achieved (or may be achieved more effectively) only by a group of agents executing a team plan. If a team plan fails, it is often of interest to determine what caused the failure, the degree of responsibility of each agent for the failure, and the degree of blame attached to each agent. We show how team plans can be represented in terms of structural equations, and then apply the definitions of causality introduced by Halpern [2015] and degree of responsibility and blame introduced by Chockler and Halpern [2004] to determine the agent(s) who caused the failure and what their degree of responsibility/blame is. We also prove new results on the complexity of computing causality and degree of responsibility and blame, showing that they can be determined in polynomial time for many team plans of interest.
Dengue Trend Prediction by Learning Long Term Sequences

This paper formulates memory based learning long short-term sequences to forecast the dengue trend. We believe that this is the first work that shows how to use Long Short Term Memory Network to predict/forecast and determine the dengue trend. This problem of dengue trend prediction can be formulated as a temporal time series regression problem. Long short-term memory networks (LSTM) are the special kind of neural networks solve vanishing and exploding gradient problem that traditional neural networks suffered. LSTM networks have the ability to learn the temporal relationship of time series data and can handle the long-term dependency problems. We explore different LSTM regression methodologies and compare and report their accuracies to confirm the efficacy of our proposed method.
Securing Data of Biotechnological Laboratories Using Blockchain Technology

A few years ago blockchain technology was used in cryptocurrency. Nowadays, a variety of diverse areas are seeing the benefits of applying this technological approach to their needs. One way transactions without reverse mode is making blockchain a desirable platform for maintaining data. The authenticity, transparency and authorization of it make it ideal for healthcare or laboratory data systems. Research data should be authorized by a specific employee and never changed. The information collected should be never forged or falsified. Designing a blockchain system with access and permission rules is ideal in such a situation. In this article, we present the adaptation of blokchain technology to medical research laboratories and diagnostics. Afterwards, an RSA signature user can store information of any type and size. The new SHA-3 hash function is used to bind blocks together. This technological path makes laboratory workflow more efficient and fulfills restriction on medical laws.
Distinctive Type of Fall Detection Methods Using Wearable Device Safety and Security of Elderly Person

Falls is a main risk for the elderly man living without assistance. Rapid and fall detection events can reduce the rate of Humanity and raise the chances to survive and independent living of old person. In the last few decades, several technological and medical treatment solutions for detection of falls were published, but most of them suffer from vital limitations. We will discuss the various challenges and concept related to fall detection system for elderly person, A lot of research being conducted is being aimed at finding solutions for helping the elderly and their caretakers in case of incidences of falls; fall detection mechanism and notification alarms in case of falls have been developed in order to reduce fall consequences. Recently, the medical and behavioral history of elderly patients has also been taken into account for predicting the possibility of falls and devising better fall likelihood prediction systems.
Analysis of Multi-Cultural Education Contents of ‘Family Life’ areas of Middle school Home Economics Textbooks

The purpose of this study is to analyze how the contents of multi-cultural education are reflected in the home life of middle school technical and home textbooks reflecting the 2015 revised curriculum. To this end, first of all, we examined whether the middle school part of the 2015 revised (technical / home) curriculum was analyzed. Also, based on the Kim and Yoon(2011), we analyzed the contents of multi-cultural education in text, visual data, learning activity, and evaluations. This article is presented in five categories of family life. The contents of multi-cultural education were analyzed in visual materials, learning activities and evaluations. The research results are as follows. First, the 2015 revised Practical (Technology / Family) curriculum emphasized multi-cultural education and suggested related learning contents systems, achievement standards, and teaching and learning directions and evaluations. Second, based on the analysis concept suggested by Kim and Yoon’s study (2011), the analysis of multi-cultural education contents in the home life area of middle school technical / home textbooks showed that ‘understand Korean cultural / social situation’ among the categories of multi-cultural education contents. And ‘democratic community-oriented’ were the most frequent, more than two-fifths of the total. As a result of examining the contents of multi-cultural education by area, it was found that the contents of multi-cultural education were the highest in human development and family. In particular, the frequency of sub-elements such as ‘Change in Korean society’, ‘Conflict resolution’, ‘Understanding communication methods’, and ‘Self identity’ were high. In addition, the contents of multi-cultural education in five textbooks were divided into knowledge, skills, and values according to the composition of textbooks (text, visual materials, learning activities, and evaluation). In addition, the evaluation area showed a very small distribution as a whole, indicating that more multi-cultural contents need to be included in the evaluation area. In addition, the evaluation area showed a very low frequency as a whole, so it was found that the multicultural content needs to be included more in the evaluation area. This is to propose a textbook composition of multicultural education content and a discussion on teaching methods.
Comparative Study of Machine Learning Algorithms for Social Media Text Analysis

This paper highlights the way different machine learning algorithms are used in analyzing social media text. This is the internet age. People make use of online forums, blogs posts, tweets etc. to communicate with each other. As a result of increased social networking, amount of data generated is enormous. This data is an excellent source of information in all walks of life ranging from business, marketing, trends analysis and prediction etc. Sentiment analysis refers to identification of user-generated text as positive or negative or neutral automatically. This classification of sentiments into classes can be done based on the document, Sentence, Feature or Aspect. This paper presents how machine learning techniques are used for analyzing sentiments expressed on Twitter platform. Comparative study of these machine learning techniques is done for better understanding.
Investigation of Microsoft Services in Real Time Applications

Microsoft services includes notifications, analytics, monitoring and support for coding and execution. These services help application designers share code, test applications, and track potential issues. Microsoft Azure, a scope of use programming dialects, including JavaScript, Python, .NET, and Node.js. It likewise offers types of service like, for example, Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). One of the programming language C# is often used to create almost anything, but is especially strong at building Windows desktop applications and games. It also can be used to develop web applications and has become increasingly popular for mobile development too. Cross-platform tools like Xamarin allow apps written in C# to be used on almost any mobile device. It is a broadly useful language intended for creating applications on the Microsoft stage and requires the .NET system on Windows to work. C# is frequently thought of as a cross breed that takes the best of C and C++ to make a really modernized language. In this paper, C# being one of the Microsoft service, is great for game development. The most popular game engine for developers on Earth is Unity and Unity uses C# for game code. Though the fact that the .NET system underpins a few other coding dialects, recently C# is flourishing and is now one of the most well-known tools to work on.
WS07.5 Pilot study - exercise response and enjoyment of virtual reality in an inpatient stay

Airway clearance is a cornerstone of treatment for young people with CF.There is potential to reduce the severity of health decline (reducing hospitalised bed days, IVABs, burden of care and reductions in respiratory function) through early intensive physiotherapy (PT).Early communitybased PT has been shown to decrease hospitalisation and ED presentations in CF populations.Hospital in the Home (HITH) may be a pathway for children with CF to avoid hospitalisation.Objectives: Pilot study to assess effectiveness of an early, home based PT HITH admission at i. avoiding hospitalisation and ii.reducing admission related costs (to patient and hospital) for patients deemed at risk.Method: Patients deemed at imminent risk of hospitalisation for respiratory exacerbation between April 2017-June 2018 were considered.A 2-week RAAP physiotherapy only HITH admission was provided to optimise airway clearance, inhalation therapy and exercise.Twice daily sessions in week 1, daily in week 2 with medical reviews pre, mid and post.Treatment provided at home or school.Outcomes: Hospitalisation avoided (no readmission 6 weeks post discharge), time to next admission, estimated hospital bed days/days of IVABs saved and satisfaction survey.Results: Nine of 12 patients avoided hospitalisation.Three were hospitalised before or on day 14.Average time to next admission was 219 days (range 49-476) or 7.2 months; 2 patients have not been hospitalised.Based on a 14-day admission, 126 estimated bed days were saved.Patient/Carer satisfaction and perceived effectiveness with RAAP was a median 10/10.Conclusion: This pilot was shown to be a successful pathway to avoid hospitalisation for respiratory exacerbation in the majority of patients.An estimated 126 bed days/days of IV antibiotics were saved.RAAP was well received with overall satisfaction, perceived effectiveness and benefits rated highly.These results are encouraging and we have begun a follow up investigation.
A New Encoding Algorithm for a Multidimensional Version of the Montgomery Ladder

We propose a new encoding algorithm for the simultaneous differential multidimensional scalar point multiplication algorithm d-MUL. Previous encoding algorithms are known to have major drawbacks in their efficient and secure implementation. Some of these drawbacks have been avoided in a recent paper in 2018 at a cost of losing the general functionality of the point multiplication algorithm. In this paper, we address these issues. Our new encoding algorithm takes the binary representations of scalars as input, and constructs a compact binary sequence and a permutation, which explicitly determines a regular sequence of group operations to be performed in d-MUL. Our algorithm simply slides windows of size two over the scalars and it is very efficient. As a result, while preserving the full generality of d-MUL, we successfully eliminate the recursive integer matrix computations in the originally proposed encoding algorithms. We also expect that our new encoding algorithm will make it easier to implement d-MUL in constant time. Our results can be seen as the efficient and full generalization of the one dimensional Montgomery ladder to arbitrary dimension.
Creating of Transnational Cooperation Network as a Factor of Competitiveness

Abstract The paper presents good practices and selected problems of creating cooperation networks. The basics of creating and disseminating new forms of cooperation between enterprises and universities have been described. Based on the implemented international project “3DCentral - Catalyzing Smart Engineering and Rapid Prototyping”, selected conclusions from creating network and management of many project activities including innovative technologies are presented.
Improving Practical UC-Secure Commitments based on the DDH Assumption

At Eurocrypt 2011, Lindell presented practical static and adaptively UC-secure commitment schemes based on the DDH assumption. Later, Blazy et al. (at ACNS 2013) improved the efficiency of the Lindell's commitment schemes. In this paper, we present static and adaptively UC-secure commitment schemes based on the same assumption and further improve the communication and computational complexity, as well as the size of the common reference string.
From Textual Information Sources to Linked Data in the Agatha Project

Automatic reasoning about textual information is a challenging task in modern Natural Language Processing (NLP) systems. In this work we describe our proposal for representing and reasoning about Portuguese documents by means of Linked Data like ontologies and thesauri. Our approach resorts to a specialized pipeline of natural language processing (part-of-speech tagger, named entity recognition, semantic role labeling) to populate an ontology for the domain of criminal investigations. The provided architecture and ontology are language independent. Although some of the NLP modules are language dependent, they can be built using adequate AI methodologies.
Exploration for magmatic Ni–Cu–Co sulphide deposits in a convergent tectonic setting – a case study in southeast Sweden

"Exploration for magmatic Ni–Cu–Co sulphide deposits in a convergent tectonic setting – a case study in southeast Sweden." Applied Earth Science, 129(2), pp. 86–87
Considerations about the quality of UML and GML application schemas

Abstract Exchange of and access to spatial data is the principal goal of any Spatial Data Infrastructure, therefore, one of the key concepts of SDI is interoperability, especially semantic and syntactic. Whereas application schemas and quality issues are one of the aspects that have to be considered to ensure a successful data interchange in SDI. Two types of application schema are widely used in the European SDI as well as in the Polish SDI. They cover both semantic and syntactic interoperability and are an integral parts of spatial data specifications and relevant regulations in the form of data models. However, working out accurate and correct application schemas may be a challenge. Additionally, faulty or too complex application schemas can influence the ability for valid data interchange, and consequently, prevent achieving interoperability within SDI. Therefore, the capability to examine and estimate the UML and GML application schemas quality seems to be a worthwhile and important issue in the context of semantic and syntactic interoperability in SDI. The main subject of this article it to set out the context of performed studies, among others, the role of application schema in the interoperable data exchange, issues related to the concept of quality and its measures.
Anomaly Detection and Prototype Selection Using Polyhedron Curvature

We propose a novel approach to anomaly detection called Curvature Anomaly Detection (CAD) and Kernel CAD based on the idea of polyhedron curvature. Using the nearest neighbors for a point, we consider every data point as the vertex of a polyhedron where the more anomalous point has more curvature. We also propose inverse CAD (iCAD) and Kernel iCAD for instance ranking and prototype selection by looking at CAD from an opposite perspective. We define the concept of anomaly landscape and anomaly path and we demonstrate an application for it which is image denoising. The proposed methods are straightforward and easy to implement. Our experiments on different benchmarks show that the proposed methods are effective for anomaly detection and prototype selection.