Reviewerly/exHarmony huggingface dataset:
Creating Data-Driven Personas

In this chapter, we review the literature on data-driven persona development. We discuss popular data-driven persona development algorithms to show the diversity of algorithmic approaches. We then summarize the primary challenges of data-driven persona development, pointing to the road ahead with general data-driven persona creation methods. We then demonstrate data-driven persona development with a detailed description of the Automatic Persona Generation (APG) system’s six stages. This is a data-driven persona development methodology employing non-negative matrix factorization to develop rich, holistic personas. We end the chapter by discussing other computer science domains’ contributions to this concept traditionally linked with HCI.
CREATING PEDAGOGICAL CONDITIONS FOR THE IMPLEMENTATION OF RESEARCH METHODS OF TEACHING USING IT AND STEM-TECHNOLOGIES IN GENERAL SECONDARY EDUCATION

The article analyzes the experience of introducing a research teaching method using IT and STEM technologies in institutions of general secondary education based on the implementation of the all-Ukrainian project “I am a researcher”. The concepts of educational and research activities, the readiness for its implementation and various aspects of the organization of such activities in the educational process are considered. The theoretical and methodological components (motivational-value, cognitive, practical-activity, reflexive-evaluative) of students’ readiness to carry out educational and research activities and teachers’ readiness to organize such activities have been determined. The levels of the readiness for research activities are characterized: high, sufficient and basic. The results of studies of the state of readiness for research activities of applicants for education using IT and STEM technologies for certain components, indicators and levels are presented. The article presents a description of the pedagogical conditions for the introduction of a research teaching method using IT and STEM technologies in general secondary education institutions as: the improving the content of educational provision and creating modern educational content based on the research teaching method and STEM approaches; development and implementation of a set of management decisions in experimental institutions on the basis of partnership interaction not only of all participants in the educational process, but also of local authorities, employers, business representatives and other stakeholders; creation of scientific and methodological support for the training of teachers and their acquisition of practical experience in the development of research competence of applicants for education based on STEM and IT approaches; participation of school teams in various festivals, competitions, competitions, other motivational STEM events and research areas. The complex of innovative educational products is presented, which includes educational and teaching aids of the I-researcher series for the middle level of education, the didactic system of natural-mathematical primary education “I am a 2.0 researcher” in the first cycle of primary school. The article reflects the promising trends in the further implementation of the research method of teaching using IT and STEM technologies in institutions of general secondary education on the basis of the didactic system of natural and mathematical primary education “I am a researcher 2.0”.
ԲԱՌԱՊԱՇԱՐԻ ՁԵՎԱՎՈՐՄԱՆ ՍԿԶԲՈՒՆՔՆԵՐԸ ՀՈՒԶԱՐՏԱՀԱՅՏՉԱԿԱՆՈՒԹՅԱՆ ՎԵՐՀԱՆՄԱՆ ԾՐԱԳՐԱԿԱԶՄՈՒՄ / THE PRINCIPLES OF SENTIMENT LEXICON GENERATION IN SENTIMENT ANALYSIS SOFTWARE

Sentiment analysis (SA) is an essential part of computational linguistics that aims at disclosing the polarity of the text. This process is mainly based on singling out sentiment lexicon since words and phrases are the main means of conveying sentiments. The main objective of this article is to present the principles of sentiment lexicon generation. The latter is mainly carried out through three approaches, namely manual approach, dictionary-based approach, and corpus-based approach. Each approach has its own peculiarities and can be used to make sentiment lexicon compilation accurate and relevant. Those approaches are intertwined and they complement each other perfectly. The topicality of the research is mainly determined by the development of information technology that promotes the dissemination of online content pertaining to several sentiments.
ԷԼԵԿՏՐՈՆԱՅԻՆ ՍՐԲԱԳՐԻՉԻ ՏՎՅԱԼՆԵՐԻ ՇՏԵՄԱՐԱՆԻ ԲԱՌԱՊԱՇԱՐԻ ՁԵՎԱՅԻՆ ՆԿԱՐԱԳՐՈՒԹՅԱՆ ԽՆԴԻՐՆԵՐԻ ՄԱՍԻՆ / ON THE ISSUES OF FORMAL DESCRIPTION OF THE DATABASE VOCABULARY OF THE ELECTRONIC SPELLCHECKER

The basis of any successful spellcheck system is not only skillfully developed software but also a rich database. In addition, the vocabulary to be included in the spellchecker database must be described formally. The process of formal description of a language is a difficult and challenging task, there are many problems related not only to the accuracy of the elaboration of the principles of formal description but also to the structural type of the language, to the peculiarities of the paradigms of declension and conjugation of words. Developing the principles of the formal description of a language, one should take into account the structural features of the language. To ensure the completeness of the formal description, it is equally important to clearly define the purpose for which the formal description will serve. Taking into account the peculiarities of the formal description of the Modern Armenian language and the difficulties related to them, in the framework of this article we examine the problematic issues of the formal description, present the ways of solving them, the principles underlying the creation of the electronic database for our spellchecker.
NATO and Artificial Intelligence

This chapter provides an overview of emerging Artificial Intelligence (AI) policies and strategies at the North Atlantic Treaty Organization (NATO). The integration of AI into military operations holds implications across tactical, operational and strategic decision-making. The authors discuss the role of NATO as a facilitator for consensus-building and common approaches among Allied nations according to two main pillars: how the Alliance may seek to access, develop, adopt, and integrate AI into national armed forces and into NATO’s common activities; and how the Alliance may seek to address the demand for principles of responsible state behaviour with respect to AI.
Understanding Police Reliance on Private Data

Private entities play a substantial and growing role across the criminal system. It is both impractical and undesirable to eliminate all private influences. Instead, policy makers can distinguish beneficial private influences from harmful ones by focusing on those private entities with the closest relationship to law enforcement. These entities have fewer incentives to guard against law enforcement overreach and thus deserve heightened scrutiny.
Kapampangan Language Endangerment: Its Significant Impact on the Predicting Factors Towards Junior High School Students

This study mainly aims to identify the significant impact of the predicting factors and the demographic profile towards the endangerment of the Kapampangan language among Junior High School students at Systems Plus College Foundation. The respondents' demographic profiles (age, city/municipality, and family status quo), as well as the nine predicting factors (Intergenerational Language transmission, Absolute numbers of speakers, Proportion of speakers within the total population, Loss of existing language domains, Response to new domains and media, Accessibility of written materials for language education and literacy, Governmental and institutional language attitudes and policies, Community members attitude towards their own language, and Amount and quality of documentation) based on the framework designed by Brenzinger et al. (2003), were observed in determining the endangerment of the Kapampangan language. This endeavour employed quantitative research using a descriptive- correlational study as it aimed to examine the significant impact of the respondents' profile and the predicting factors towards the endangerment of the Kapampangan language. This research study is under Probability Sampling, and Stratified Sampling Technique was used.Based on the results, the nine predicting factors are found to be contributing to the endangerment of the language. Meanwhile, through the gathered Pearson Correlation of each item, it was concluded that the demographic profile of the respondents and the nine factors have a significant impact on the endangerment of the Kapampangan language. It is also recommended that the demographic profile of the respondents and the nine predicting factors based on the framework of Brenzinger et al. (2003) are good descriptors to know the correlation of each variable. However, it is suggested that these variables must be modified to obtain a high correlation for the future development of this study, as correlation is inconsistent among factors. The questionnaire must also be modified and revalidated to obtain more accurate and consistent results with high correlation for further studies.
Subjectivity as a Prerequisite for Qualitative Development of Ukrainian Polygraphology

The subject of consideration is the analysis of the history of formation and current trends in domestic polygraphology with an emphasis on subjectivity as a mandatory component of further qualitative development of this area with the provision of state interests, including the interests of state security. Polygraph studies have been conducted by domestic specialists on a regular basis since 1998. In 22 years, this method of establishing the truth from the little-known, mythical, and since the 30s of the last century, traditionally unacceptable by our lawyers, has become well-known and generally praised by society. Publications on the positive results of polygraph examinations on high-profile criminal proceedings, official investigations, personnel inspections in law enforcement agencies and special services have contributed to the growing popularity of the method. The use of a polygraph in filming and television broadcasts on a number of Ukrainian channels, checking politicians for integrity, and public polygraph calls to political opponents and business competitors have become traditional. Analysis of attempts to introduce polygraph technologies in different countries shows that after the initial accumulation of knowledge and experience, the formation of a positive attitude of society, then especially important is the direction of regulatory and theoretical and methodological framework for the use of polygraph. Blind copying of someone else’s experience is inevitably accompanied by copying someone else’s mistakes, the harmful dependence of the pace, quality and vector of development of the polygraph of a particular state on outside influence.
Improving Measured Horizontal Solar Radiation Data: The Case Study-Asia Continent

Horizontal solar radiation is the main input of all solar power applications. Solar radiation data collecting from the ground-based meteorological station seems still the most reliable compared to others such as satellite databases. In literature, there is a number of recent studies that utilize directly old measure solar radiation data without any precaution. As a consequence, the solar system can be exposed to poor technoeconomic assessment. This paper attempts to find a close agreement to enhance the old measured data within the period 1971 and 2003 to make it more applicable for further studies and applications. Therefore, NASA POWER, PVGIS 5, Meteonorm software, and old measured data are used and compared to the new measured data (as reference). All measured data are collected from the World Radiation Data Centre (WRDC) published in various articles. Six distributed locations in the Asian continent are used as a case study for this paper. Statistical methods including Global Performance Indicator (GPI) are used to investigate and compare solar data sources. It is argued that the improvement of old measured data can be obtained either by the proposed method for each country or by a proposed hybrid of all solar data sources for any location in the Asian continent.
Design And Build Up Of Sphygmomanometer Based On Android Supplemented With Food Recommendations

Blood pressure is a measure of how strong the heart is to pump blood around the body. Abnormal blood pressure can occur due to high blood pressure (hypertension) or low blood pressure (hypotension). Data from the World Health Organization (WHO) in 2015 showed that around 1.13 billion people in the world have hypertension, meaning that 1 in 3 people in the world are diagnosed with hypertension. Therefore, a sphygmomanometer was designed that could digitally detect blood pressure and provide food recommendations to stabilize blood pressure. The detection of blood pressure is carried out by the oscillometry method where the oscillation value occurs when blood first flows into the artery after clogging. Systolic blood pressure is determined by multiplying the Mean Arterial Pressure by 0.8. Meanwhile, diastolic blood pressure is determined by multiplying the Mean Arterial Pressure by 0.5. The results of the blood pressure will be displayed on the LCD display and sent to the smartphone. On the smartphone, blood pressure results and food recommendations will be displayed through the android application to make it easier for patients to remember recommended foods and monitor their own blood pressure results without the help of a medical or doctor.
Effect of Different Threshold Levels for Binarization Method in Image Classification

Image processing is the most preferred technique in Computer-Aided Design (CAD) studies, and therefore the enhancement of image processing plays an essential role in the advancement of technology. The primary purpose of this study is to examine the effect of fixed threshold value on images of different sizes when using the binarization method in image processing. The analyzes are made based on the change in the detection accuracy percentage of the K-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Convolutional Neural Networks (CNN) classification methods on the MATLAB software platform. At the same time, the effect of the binarization threshold value on images with different pixel dimensions (8x8, 16x16, 32x32, 64x64, and 128x128) are investigated. CNN classification obtained the best accuracy percentage in the used malaria disease blood cell data 97.5%, followed by k-NN with 95% and SVM with 91.5%.
eToken Application for Generating the Digital Signature Using the USB Interface

This paper highlights some ways in which people can book, in a very simple way, a promotional package of e-commerce in tourist services, without the need for face-to-face communication. The entire transaction is executed online, but also in a secure way, ensuring the real identity of both the buyer and the seller. Users will benefit from various offers with a good value for money. Firstly, they will be able to follow the booking steps in a simple way, ideal for inexperienced users, with instructions and warning messages. Secondly, it is no secret that today's people are busy, the lack of time is more and more accentuated, and the online environment has gained ground in their lives. Along with online transactions, human or system errors have appeared, users being often put in unpleasant situations. One solution to this problem is the token device - a device with a special structure that incorporates cryptographic algorithms (symmetric and asymmetric) that allow the safe performance of cryptographic operations. In the application presented in this paper, both users and sellers digitally sign holiday booking documents, thus managing to provide beneficiaries with a strong reason to confirm that the digital document is created by the person who signed it, and the content of the digital document has not been modified since its date of issue.
On divisors of sums of polynomials

Let A and B be sets of polynomials of degree n over a finite field. We show, that if A and B are large enough, then A+B has an irreducible divisor of large degree for some A∈A and B∈B.
Data Mining and Analysis Algorithm of Smart City Network Information Resource Description Framework Based on Fuzzy Association Rules

Abstract Aiming at the problems of poor effect, low precision, and a long time frame in the current data mining analysis algorithm of the network information resource description framework (RDF), a data mining analysis algorithm of the network information RDF based on fuzzy association rules is proposed. Using association rule mining technology combined with fuzzy set theory, a fuzzy association rule algorithm is obtained to deal with quantitative data. Fuzzy c-means (FCM) is used to discretize continuous attributes, and the fuzzy concept pattern and its support and credibility are defined. Add a Mining Query flag to extend the SPARQL Protocol and RDF Query Language (SPARQL) syntax, define the user specified mining model, generate the corresponding project set and transaction, adopt the fuzzy association rule algorithm to generate fuzzy association rules, and realize the RDF data mining analysis of network information. The experimental results show that the network RDF data mining analysis effect of the proposed algorithm is good, which can effectively improve the network RDF data mining analysis accuracy and shorten the mining analysis time.
New models of classifier learning curves

In machine learning, a classifier has a certain learning curve i.e. the curve of the error/success probability as a function of the training set size. Finding the learning curve for a large interval of sizes takes a lot of processing time. A better method is to estimate the error probabilities only for few minimal sizes and use the pairs size-estimate as data points to model the learning curve. Searchers have tested different models. These models have certain parameters and are conceived from curves that only have the general aspect of a real learning curve. In this paper, we propose two new models that have more parameters and are conceived from real learning curves of nearest neighbour classifiers. These two main differences increase the chance for these new models to fit better the learning curve. We test these new models on one-input and two-class nearest neighbour classifiers.
Research on Sustainable Development Indicator Prediction of Regional Economic Subsystem Based on Artificial Neural Network

Sustainable development system is a “black box,” or at least a “grey box,” and it is not very clear whether there is a causal relationship between various factors. Artificial neural network can simulate the system realistically. In this paper, the artificial neural network BP model is used as a tool, and Matlab language is used to predict the indexes of regional sustainable development economic subsystem. Through data collection, network structure model design, program design, and network training, this study drew the indicator forecast chart, analyzes it, and finally puts forward suggestions. The results show that it is feasible to use an artificial neural network to simulate a sustainable economic subsystem.
LinkD: element-based data interlinking of RDF datasets in linked data

Abstract One of the main obstacles in publishing in a Linked Data way is to connect the dataset being published externally with related data sources in the cloud, known as Data Interlinking. This paper proposes LinkD, a new element-based interlinking approach. LinkD interlinks an RDF dataset, resulted from transformed semi-structured data, with its counterparts in the web of Linked Data. To provide similarity links, the existence of published data in the Linked Data cloud is done in the first place. Different algorithms for similarity measurement are employed while the domain of the dataset being interlinked is taken into account. The techniques utilised allow the processing of a large number of Linked Data datasets. The evaluation of LinkD shows high precision, recall and performance.
Professional Competence of the Head of the Club as a Component of Quality Out-of-school Education

The article substantiates the theoretical foundations of professional competence and defines the qualities that contribute to the pedagogical competence of the head of the club, emphasizing that the professional competence of an out-of-school teacher is a necessary and prerequisite for successful professional activity.&#x0D; Attention is focused on the fact that the formation of creative initiative personality is inextricably linked with the problem of professional training of out-of-school teachers, his ability to organize the educational process according to fundamentally new non-standard innovative technologies.&#x0D; The article states that an out-of-school teacher is an organizer of life activities for a competitor education who provides basic needs for creative self-realization and recognition. By activating personal resources, the head of the club creates favorable conditions for his creative development.&#x0D; It is determined that an out-of-school teacher who strives for professional growth is a creative person with a high level of development of creative skills, reflection, constant self-improvement and skills of pedagogical activity.
A mathematical analysis of EDAs with distance-based exponential models

Abstract Estimation of Distribution Algorithms have been successfully used to solve permutation-based Combinatorial Optimization Problems. In this case, the algorithms use probabilistic models specifically designed for codifying probability distributions over permutation spaces. One class of these probability models are distance-based exponential models, and one example of this class is the Mallows model. In spite of its practical success, the theoretical analysis of Estimation of Distribution Algorithms for permutation-based Combinatorial Optimization Problems has not been developed as extensively as it has been for binary problems. With this motivation, this paper presents a first mathematical analysis of the convergence behavior of Estimation of Distribution Algorithms based on Mallows models. The model removes the randomness of the algorithm in order to associate a dynamical system to it. Several scenarios of increasing complexity with different fitness functions and initial probability distributions are analyzed. The obtained results show: a) the strong dependence of the final results on the initial population, and b) the possibility to converge to non-degenerate distributions even in very simple scenarios, which has not been reported before in the literature.