Comparison of Different Knowledge Representations for Complex Structured Objects in Solving AI Problems

The problem of knowledge representation for a complex structured object is one of the actual problems of AI. This is due to the fact that many of the objects under study are not a single indivisible object characterized by its properties, but complex structures whose elements have some known properties and are in some, often multiplace, relations with each other. An approach to the representation of such knowledge based on first-order logic (predicate calculus formulas) is compared in this paper with two currently widespread approaches based on the representation of data information with the use of finite-valued strings or graphs. It is shown that the use of predicate calculus formulas for description of a complex structured object, despite the NP-difficulty of the solved problems arising after formalization, actually have no greater computational complexity than the other two approaches, what is usually not mentioned by their supporters. An algorithm for constructing an ontology is proposed that does not depend on the methodof desc ribing an object, and is based on the selection of the maximum common property of objects from a given set.

On Lessons Learned From Distance Teaching and Learning

The coronavirus (COVID-19) epidemic in Russia forced colleges and universities to switch to distance teaching and learning. The instructors had to make an emergency move to the remote methods of teaching using various platforms. In the course of the distance learning period in midst of an on-going pandemic, the instructors acquired valuable experience in on-line lecturing, administering tests, conducting tutorials, examination sessions, office hours, etc. Distance teaching called for new educational technologies that would provide the quality of education comparable to the in-person teaching. Compared to the traditional teaching, the time needed to prepare for classes has increased. However, it turned out that thanks to the technologies developed to facilitate high-quality distance interaction, many of the methodologies developed for distance learning can be quite useful in traditional (in-person) learning as well. Using a course in Linear Algebra and Algebraic Structures taught to the freshmen at Saint Petersburg Electro-technical University as an example, this article demonstrates that it is possible to use some of the communication technologies–based methodologies to enhance in-person learning.

Integrated approach to revelation of anomalies in wireless sensor networks for water control cases

This article describes an approach to revelation of anomalies for Wireless Sensor Networks (WSN). It is based on the integration of visual data analysis techniques and data mining techniques. Feasibility of the approach has been confirmed on a demo case for WSN water management scenario. For verification we developed a software/hardware prototype of the network and a software model to generate the necessary data sets for the establishment of detection models and their investigation. The experiments carried out have shown a high quality of detection, which shows the applicability of the integrated approach to revelation of anomalies for use in practical cases.

Analysis of Wheat Samples Using the Calculation of Multifractal Spectrum

The computational analysis of wheat images to identify wheat varieties and quality has wide applications in agriculture and production. This paper presents an approach to the analysis and classification of images of wheat samples obtained by the method of crystallization with additives. In tests 3 concentration and 4 times for each concentration were used, such that each type of wheat was characterized by 12 images. We used the images obtained for 5 classes. All the images have similar visual characteristics, that makes it difficult to use statistical methods of analysis. The multifractal spectrum obtained by calculating the local density function was used as a classifying feature. The classification was performed on a set of 60 wheat images corresponding to 5 different samples (classes) by various machine learning methods such as linear regression, naive Bayesian classifier, support vector machine, and random forest. In some cases, to reduce the dimension of the feature space the method of principal components was applied. To identify the relationships between wheat samples obtained at different concentrations, 3 different clustering methods were used. The classification results showed that the multifractal spectrum as classifying sign and using the random forest method in combination with the principal component analysis allow identifying wheat samples obtained by crystallization with additives, being the highest average classi- fication accuracy is 74 %.

On the Classical Version of the Branch and Bound Method

In the computer literature, a lot of problems are described that can be called discrete optimization problems: from encrypting information on the Internet (including creating programs for digital cryptocurrencies) before searching for “interests” groups in social networks. Often, these problems are very difficult to solve on a computer, hence they are called “intractable”. More precisely, the possible approaches to quickly solving these problems are difficult to solve (to describe algorithms, to program); the brute force solution, as a rule, is programmed simply, but the corresponding program works much slower. Almost every one of these intractable problems can be called a mathematical model. At the same time, both the model itself and the algorithms designed to solve it are often created for one subject area, but they can also be used in many other areas. An example of such a model is the traveling salesman problem. The peculiarity of the problem is that, given the relative simplicity of its formulation, finding the optimal solution (the optimal route). This problem is very difficult and belongs to the so-called class of NP-complete problems. Moreover, according to the existing classification, the traveling salesman problem is an example of an optimization problem that is an example of the most complex subclass of this class. However, the main subject of the paper is not the problem, but the method of its soluti- on, i.e. the branch and bound method. It consists of several related heuristics, and in the monographs, such a multi-heuristic branch and bound method was apparently not previously noted: the developers of algorithms and programs should have understood this themselves. At the same time, the method itself can be applied (with minor changes) to many other discrete optimization problems. So, the classical version of branch and bound method is the main subject of this paper, but also important is the second subject, i.e. the traveling salesman problem, also in the classical formulation. The paper deals with the application of the branch and bound method in solving the traveling salesman problem, and about this application, we can also use the word “classical”. However, in addition to the classic version of this implementation, we consider some new heuristics, related to the need to develop real-time algorithms.

Ontology of Discrete Mathematics in Education

Currently, ontologies are widely used in computer science for the formalized representati- on of knowledge about various subject areas. Special formal languages for describing ontologies have been developed and are successfully used, which allow describing ontologi- es in a form that is accessible for use by both humans and computers.Among the various options for using ontologies, a special place is occupied by the use of ontologies in educati- on, since the systematization and ordering of knowledge, being the main competitive advantage of the ontological approach, is at the same time one of the main goals of the educational process. The article proposes original methods of constructing ontologies for use in the educational process of higher education. The central idea is the construction of faceted, in other words, multifaceted ontologies, in which different aspects of the same subject area are described by conceptually similar, but syntactically different means. This approach provides a more accurate and semantically adequate description while maintaining the known brevity and clarity of designations. As a language for describing ontologies, it is proposed to use the unified modeling language UML 2, which has proven itself in formalization in many cases. The presentation is based on the example of constructing an ontology of discrete mathematics, and the ontology diagrams given in the article are introduced into the educational processes of the Academic and Polytechnic Universities of St. Petersburg.

DBSCAN clustering method is applied to identify severe Traffic Accident (TA) hotpots on roads

DBSCAN clustering method is applied to identify severe Traffic Accident (TA) hotpots on roads. The research examines severe TA, defined as those that led to human damage (injury or death), in the city of Newton, MA and in the entire state of Massachusetts, USA from 2013 to 2018. DBSCAN algorithm was also applied to network-constrained uniformly distributed over road network data to locate threshold in number of points per cluster so that all more populated clusters identified in real data can be treated as statistically significant. For DBSCAN algorithm two types of distance metrics, Euclidean and over Network, were compared. It is found that both distances are equivalent on scale of 10 meters, which justifies hybrid approach to clustering: using Network distance only to generate uniformly distributed points needed for Monte-Carlo simulations. All clustering can be performed using Euclidean distances which is much faster and more memory efficient. Subsequent years analysis demonstrates the extend that hotspots identified are stable and occur consecutively for several years and hence may possess predictive value.

Teacher’s Computer Tools

The problems concerning e learning and distance learning are discussed. State regulations and assessments of teachers about preparedness our educational system to use new digital technologies are sited. It is suggested to start discussion about unification notions and terms attributed to educational digital technologies.

Teacher’s Computer Tools

The problems concerning e learning and distance learning are discussed. State regulations and assessments of teachers about preparedness our educational system to use new digital technologies are sited. It is suggested to start discussion about unification notions and terms attributed to educational digital technologies.

Assessment of the Potential of Scientific Activity Based on Scientometric Indicators

This article deals with issues of assessing the scientific activity of teams of performers when submitting applications to scientific funds. The purpose of the study is to develop new approaches to the use of scientometric indicators to assess the scientific potential of university teams when submitting applications to scientific foundations. Methodological foundations of the research: a systematic approach (considers science as a social institution in an indissoluble connection with society as a whole), a metasystem approach (considers the results of scientific activity as a metasystem, that is, a system with relatively independent components), a probabilistic-statistical approach (considers research activity as a probabilistic process), qualimetric approach (considers the productivity of scientific activity as a latent variable, reflected by a set of criteria). As a result, the authors proposed: an information model of the relationship between the requirements for a scientific project by the customer, and the level of compliance of the scientific potential of the team of performers and a methodology for assessing the scientific potential of the team of performers when applying for the competition. The information model forms the basis of the developed information system for supporting the project activities of ITMO University, which serves to improve the process and increase the efficiency of preparation of draft applications submitted by the university. The proposed methodology is implemented using scientometric indicators, through software algorithms for automated assessment of scientific potential. In the course of an experimental study, the authors have shown that the proposed approaches correlate with the effectiveness of participation in competitions. The proposed solutions have been successfully integrated into the ITMO University, management system.