Reviewerly/exHarmony huggingface dataset:
USE OF ONTOLOGY IN INFORMATION SYSTEM TO ASSIST IN THE FORMATION OF AN INDIVIDUAL EDUCATIONAL TRAJECTORY OF STUDENTS

This work examines the problem of individual educational trajectory in Ukraine. During research, it was found that this issue is considered mainly from a theoretical aspect, which results in the lack of effective and convenient tools for practical implementations to solve the problem. The analysis of existing methods and means of solving the problem has been carried out. The results of the analysis indicate that the implemented information systems partially satisfy the needs of students in the formation of an individual trajectory. Objective. Develop an information system model to help in the formation of an individual educational trajectory for students of higher educational institutions, taking into account the needs of leading IT companies and studentsвЂ™ inclinations. Aiding students in the formation of an IET is based on a set of recommendations formed based on student preferences. Method. To solve the problem information system model was developed, which uses two main modules to operate. First module allows its user to pass a career guidance test and second module provide the semantic algorithm to determine disciplines best suited for user based on his professional inclinations. LevensteinвЂ™s algorithm using ontology was chosen as a semantic algorithm. Results. During research information system was developed which allows students to receive recommendation for formation of individual educational trajectory. Conducted experiments with random input data had shown the system is fully functional and performing its task. All operational aspects of the system are presented in this work using UML diagrams. Conclusions. Forming recommendations for an individual educational trajectory is a complex process that requires a significant amount of resources. The use of information technologies allows to simplify this process, and the development of an information system вЂ“ to automate it and make it accessible. The implementation of the information system model made it possible to understand all the subtleties of the process of forming recommendations and ensure their accuracy. The operation of the information system was ensured by the use of two modules to determine the userвЂ™s professional orientation and search for the appropriate discipline. The process of finding a discipline that will match the professional inclination of the user is based on work with semantics, for which the ontology was used. The use of ontology in the process of determining semantic proximity using the Levenshtein algorithm made it possible to obtain semantic units that are as close as possible to the studentвЂ™s professional inclinations and ensure the most accurate result when formulating recommendations.
Dampak Gerakan Literasi KM-4 di SDN Gaddong 2

The purpose of writing this journal is to describe the impact of the literacy movement implemented at SD Negeri 2 Makassar. This aims to broaden students' insights and foster students' interest in reading, because reading various knowledge can lead to success. The teaching campus is a place where students are given the opportunity to gain experience in terms of teaching and can devote themselves to placement schools. Through this teaching campus, we are implementing the literacy movement at our placement school, SD Negeri Gaddong 2 Makassar. In the initial observation of the assignment, there were several students who were still passive in reading, paying attention to efforts to increase students' reading literacy with literacy movements, various kinds of activities related to literacy so that they could slowly foster students' love for the literacy movement. The activities implemented are the reading literacy movement 15 minutes before the learning process, and the implementation of a literacy club and the creation of a reading corner.
The Common-Neighbors Metric Is Noise-Robust and Reveals Substructures of Real-World Networks

Real-world networks typically display a complex structure that is hard to explain by a single model. A common approach is to partition the edges of the network into disjoint simpler structures. An important property in this context is locality—incident vertices usually have many common neighbors. This allows to classify edges into two groups, based on the number of the common neighbors of their incident vertices. Formally, this is captured by the common-neighbors (CN) metric, which forms the basis of many metrics for detecting outlier edges. Such outliers can be interpreted as noise or as a substructure. We aim to understand how useful the metric is, and empirically analyze several scenarios. We randomly insert outlier edges into real-world and generated graphs with high locality, and measure the metric accuracy for partitioning the combined edges. In addition, we use the metric to decompose real-world networks, and measure properties of the partitions. Our results show that the CN metric is a very good classifier that can reliably detect noise up to extreme levels (83% noisy edges). We also provide mathematically rigorous analyses on special random-graph models. Last, we find the CN metric consistently decomposes real-world networks into two graphs with very different structures.
Optimization of Fuzzy C-Means with Alternating Direction Method of Multipliers

Among the clustering methods, K-Means and its variants are very popular. These methods solve at each iteration the first-order optimality conditions. However, in some cases, the function to be minimized is not convex, as for the Fuzzy C-Means version with Mahalanobis distance (FCM-GK). In this study, we apply the Alternating Directions Method of Multiplier (ADMM) to ensure a good convergence. ADMM is often applied to solve a separable convex minimization problem with linear constraints. ADMM is a decomposition/coordination method with a coordination step provided by Lagrange multipliers. By appropriately introducing auxiliary variables, this method allows the problem to be decomposed into easily solvable convex subproblems while keeping the same iterative structure. Numerical results have demonstrated the significant performance of the proposed method compared to the standard method, especially for high-dimensional data.
CONSTITUTIONAL RESEARCH OF THE AXIOLOGICAL BASIS OF THE TRAINING OF MASTERS OF HUMANITIES IN UNIVERSITIES

In the article, taking into account the results of the methodological and theoretical substantiation of the scientific foundations of professional training, a systematic analysis of the data of the ascertainment experimental work on the study of the axiological foundations of the educational process was carried out in order to develop the target and technological blocks of the context-professional model of the training of future masters (culturalists, historians, religious studies, philologists, philosophers).The tasks of ascertaining research include: 1) to find out how the respondents understand the essence of the master's training system on axiological grounds; 2) identify and systematize the leading groups of values and value attitudes, according to the master's students; 3) to determine possible options for prospective improvement of the content, technologies and methods of training specialists on axiological grounds.Methods of ascertaining research: questionnaire (frequency analysis of answers); ESE content analysis; expert assessments; computer quantification; observation; quantitative and qualitative display of data; ranking; stepwise statistical processing.On the basis of theoretical research, experimental examination and generalization of materials, the development of the axiological foundations of the context-professional model of training future masters in the humanitarian field is determined in the perspective of the research; it was analyzed that the educational training environment should be based on the principles of axiology and open learning: reliance on information technologies; design of modern content of education; development of innovative methods of formation and development of the valuable component of professional competences; solving the problems of measuring the quality of education; changes in the traditional role of the teacher as a translator of knowledge and mastering the role of a mentor, senior colleague, consultant, scientific supervisor.
Finance-induced Innovation: A New Mechanism Explaining Finance-Inequality Relationship

&#x0D; &#x0D; &#x0D; This paper uncovers a new mechanism through which financial development affects in- come inequality. We first revisit the effect of financial development on inequality using a panel of 94 countries from 1980 to 2017. The results show that both credit and equity markets development are positively related to different measurements of inequality, and the results are robust to endogeneity tests and other specifications. We then show empirically that this positive finance-inequality relationship can be explained by finance-induced innova- tion, especially by the finance-induced high-technology innovation. We further find that this mechanism seems to be more important than other innovation-related factors in explaining the finance-inequality relationship in low- and middle-income countries.&#x0D; &#x0D; &#x0D;
Toward Interpretable Machine Learning: Constructing Polynomial Models Based on Feature Interaction Trees

As AI has been applied in many decision-making processes, ranging from loan application approval to predictive policing, the interpretability of machine learning models is increasingly important. Interpretable models and post-hoc explainability are two approaches in eXplainable AI (XAI). We follow the argument that transparent models should be used instead of black-box ones in real-world applications, especially regarding high-stakes decisions. In this paper, we propose PolyFIT to address two major issues in XAI: (1) bridging the gap between black-box and interpretable models and (2) experimentally validating the trade-off relationship between model performance and explainability. PolyFIT is a novel polynomial model construction method assisted by the knowledge of feature interactions in black-box models. PolyFIT uses extracted feature interaction knowledge to build interaction trees, which are then transformed into polynomial models. We evaluate the predictive performance of PolyFIT with baselines using four publicly available data sets, Titanic survival, Adult income, Boston house price, and California house price. Our method outperforms linear models by 5% and 56% in classification and regression tasks on average, respectively. We also conducted usability studies to derive the trade-off relationship between model performance and explainability. The studies validate our hypotheses about the actual relationship between model performance and explainability.
Use of Blockchain Technologies in Smart Cities

Abstract: A city is called a smart city where every citizen gets quality government services using the technologies like Information and Communication Technology (ICT). ICT also helps in providing operational efficiency in information sharing with the public. Smart cities promote better quality of life by using modern technologies and economic growth. Blockchain helps in end-to-end data transfer with great efficiency, transparency and security. Every data is stored in a block which has a hash value also considered as digital signature. In this paper, it is discussed how we can use Blockchain technologies to promote smart cities and provide better services. Also, it discusses various challenges and trends in use of blockchain technology in building smart cities.
ISE pages

Fuzzy sets introduced to overthrow the uncertainty of an object. Interval valued intuitionistic fuzzy sets in topological structure space is an extension of fuzzy sets. Interval-valued intuitionistic multi fuzzy set theory is a capable tool for commerce with ambivalence of expertise in information systems. The motive of this paper is to present interval valued intuitionistic multi fuzzy completely generalized semiprecontinuous mappings and provide some of their properties. Also we proved the relation between various types of interval valued intuitionistic multi fuzzy continuous mappings.AMS Subject Classification (2010): 54A40.
Provenance and tectonic setting of the Middle Eocene lower Akhoreh Formation, Nain area, Central Iran, assessed using petrography and geochemistry

The Middle Eocene Akhoreh Formation is superbly exposed in the western corner of the Central-East Iranian Microcontinent (CEIM). This formation covered the northeastern flank of the Cretaceous Nain Ophiolite Mélange (NOM) and is adjacent to the Paleogene Urmieh–Dokhtar Magmatic Arc (UDMA) formed in the southwest of the CEIM. This terrigenous succession is composed of a thin basal conglomerate followed by mostly pink to purple sandstones alternating with shales. The clast composition and clast imbrication of the conglomerates show local source areas towards the north-north-east. Modal components of lower Akhoreh Formation sandstones reveals immature lithic arkose (Q 8 F 48 L 44 ) and feldspathic litharenite (Q 8 F 44 L 48 ) sandstones that are rich in mafic and ultramafic igneous and volcanic rock fragments. Mafic to ultramafic source rocks are also indicated by geochemical data (enrichment of Mg, Cr and Ni and Cr/V) in the sandstone and shale samples analyzed. However, geochemical data suggests an intermediate igneous rock origin for the shale samples studied, most likely from the nearby continental arc. Based on petrographic data, these sandstones have characteristics of a transitional to undissected arc tectonic setting. Geochemical discrimination diagrams using major and trace elements indicate an oceanic island arc tectonic setting for the lower Akhoreh Formation sandstones and shales, probably due to a predominance of ophiolitic source rocks. Furthermore, the chemical index of alteration and modal analysis indicate a weak to moderate degree of chemical weathering with arid climatic conditions in the source area. The exhumed NOM, together with the UDMA in the southwest, were dominant sources of sediment to the lower Akhoreh Formation, that lay to the northeast in a local retroarc basin of the Central Iranian Microplate, during the Middle Eocene.
Shape complexity in cluster analysis

In cluster analysis, a common first step is to scale the data aiming to better partition them into clusters. Even though many different techniques have throughout many years been introduced to this end, it is probably fair to say that the workhorse in this preprocessing phase has been to divide the data by the standard deviation along each dimension. Like division by the standard deviation, the great majority of scaling techniques can be said to have roots in some sort of statistical take on the data. Here we explore the use of multidimensional shapes of data, aiming to obtain scaling factors for use prior to clustering by some method, like k-means, that makes explicit use of distances between samples. We borrow from the field of cosmology and related areas the recently introduced notion of shape complexity, which in the variant we use is a relatively simple, data-dependent nonlinear function that we show can be used to help with the determination of appropriate scaling factors. Focusing on what might be called “midrange” distances, we formulate a constrained nonlinear programming problem and use it to produce candidate scaling-factor sets that can be sifted on the basis of further considerations of the data, say via expert knowledge. We give results on some iconic data sets, highlighting the strengths and potential weaknesses of the new approach. These results are generally positive across all the data sets used.
The Use of Alphabet Flash Cards Learning Media in the Process of Learning While Playing at the Community Learning Activity Center in North Sulawesi Province

The development of the out-of-school education sector has a strategic role in improving the quality of human resources. In order to increase motivation and learning achievement of citizens learning to read, learning media is needed in the form of alphabet cards that are used by learning resources to develop learning models while playing for learning citizens. The purpose of this research is to: 1) design alphabet card learning media in the application of the development of the learning process, 2) applying the development of the learning process, and 3) finding the effectiveness of the implementation of the development of the learning process of reading while playing through the learning media of alphabet cards for citizens learning literacy in PKBM, North Sulawesi Province. This study has used the ”research and development” method, following the stages of ADDIE model development research (analyze, design, develop, implement, and evaluate) in 4 districts: 1) South Bolaang Mongondow, 2) East Bolaang Mongondow, 3) Talaud Islands, and 4) North Minahasa. This research is designed for 2 years and the first year, 2022, has been carried out in 3 stages, namely: 1) analyze stage, 2) design stage, and 3) development stage. Meanwhile, for the second year, there will be 2 stages, the implementation stage and the evaluation stage. It was concluded that: 1) prototype product design of Alphabet Card Learning Media can be understood and mastered by learning citizens; 2) the application of the development of the learning process is carried out through stages: (1) Recruitment of tutors, learning residents, and forming study groups; (2) Conducting training of trainers (TOT) for tutors; and (3) trials development; 3. The learning process is effective because: (1) The learning residents who were formerly literate but forgot their letters have re-learned them. (2) An improvement in the cognitive abilities of learning citizens; (3) A better ability to put letters together to form meaningful words; (4). Citizens who are learning become more involved. It is suggested that: 1) The teacher must develop an adaptable lesson plan; 2) The following aspects require revision: (1) the physical card alphabet’s size in both height and width; (2). For the sake of IPR and patent rights, a unique logo is required. 3). At the implementation and evaluation stage, this study must be continued.&#x0D; Keywords: learning to read, while playing, alphabet cards
A New Training System Using VR Will Rev Up the Baseball Industry Like Never Before

By accurately reproducing various pitches of actual pitchers in virtual space and visualizing the movements of athletes using a sensing function, the baseball-simulation system that we provide achieves more efficient and effective training for athletes.This system also provides baseball fans with a new means of enjoying the sport by enabling them to stand-in virtual space-in the batter's box and play against the pitching of a real pitcher.This system represents a new initiative that has never been available before, and it is generating interest within the industry.
Building threat resilience into ecosystem strategy

Purpose As businesses in a wide range of industries increasingly adopt digital ecosystems, the benefits include opening up new and untapped customer segments and channels, enabling access to new and untapped talent pools and expanding previously unexplored modes of innovation. Ecosystems – defined as digitally enabled networks that enhance value propositions by linking business functions, suppliers, distributors, partners, customers and other stakeholders – are now an engine that drives performance. Multiple studies confirm that value creation and competitive advantage are increasingly tied to organizations’ ability to engage partners and stakeholders. IBM Institute of Business Value’s most recent research has found that revenue growth of ecosystem leaders outpaces others by a five-to-one ratio. Design/methodology/approach Yet despite these notable successes there is also a dark side to digital ecosystem engagement. Large ecosystems have become a central to business strategy while little attention has been paid to the potential for cyber threats. Increased openness of business operations can result in greater risk. Findings Security must graduate into a central enabler of business transformation. If businesses do not fundamentally rethink their security equation, ecosystems and the trust on which they are built, which often take years and billions of investment dollars to build, can be squandered in minutes by ever-growing security threats. Practical implications Large ecosystems have become a central to business strategy while little attention has been paid to the potential for cyber threats. Originality/value Mature, risk-mitigated ecosystems are starting to resemble a mature supply chain, where some risks are precluded by design, some partners are favored based on established trust criteria and remaining risks are explicitly managed transactionally as part of the partner relationship.
Quo Vadis Teacher Education?

This introduction outlines the topic, aim, and structure of the volume. With this collection of chapters, we aim to “push a diversity of notions of ‘innovation’” (Sriraman, 2017, p. viii) into the area of teacher education (including teacher education research). In that respect, innovations in three different domains are distinguished: pedagogies, technologies, and societies. In the domain of pedagogies, which serves as the ‘core’ of teacher education programs, four types of processes leading to innovations in teacher education (research) are addressed: reflective, emotive, cognitive, and didactic-instructional processes. In the domain of technologies, teacher educators are required to accept the double-sided reality of technological tools, i.e. their potentials and their limits. This is accompanied by the need to use competency frameworks such as TPACK (Mishra & Koehler, 2006) or DigCompEdu (Redecker & Punie, 2017) more systematically, to conduct critical research on modern tools in the area of Artificial Intelligence (AI) and, eventually, to utilize the transformative potential of digital tools in the international context. In the domain of societies, we claim that teacher education (research) generates innovations in areas that seemingly reside outside teacher education programs, such as multilingualism, societies’ changing expectations of modern literacies, societal polarization, and teacher shortage.
Teaching Speaking in Communicative Skills Through Snowball Throwing

The purpose of writing this paper is to describe teaching speaking in the communicative skill subject throughsnowball throwing method. In speaking, many students still get some difficulties, because probably, they worriedabout their grammar mistakes. The teacher can use snowball throwing method to make students enjoyable to learnspeaking. This method provides an efficient way of getting students to share their different ideas or perspective andcan help students master spoken english. It is suitable for the students because it helps the students to understandhow to speak well. It is usually used a ball and it is made from a paper or rubber and the ball will be thrown torandom student and once the student get the ball, he or she will have a chance to speak in the classroom. When theteacher conducts teaching and learning speaking through snowball throwing method, the students will be enjoyablein learning process. And it is recommended that the teachers consider to use snowball throwing method as one ofthe teaching speaking methods in the class.