High-level Architecture For a Digital Oilfield: Features of the Transition to Data-driven Decision Management

This paper is devoted to the design of a distributed heterogeneous data warehouse of a digital oilfield. With increasing amounts of data collected from intelligent controllers and sensors, the lack of mechanisms for combining data from different sources and providing them to consumers affect the overall management efficiency. In addition, without it is impossible making the next logical step - the effective application of intelligent analysis methods. The paper describes the high-level architecture, as well as subsystems of operational management and decision support. The presented data are intermediate results of the project "Digital oilfield heterogeneous distributed data warehouse for informational support of decision-making processes"

High-level architecture for a digital oilfield: features of the transition to data-driven decision management

This paper is devoted to the design of a distributed heterogeneous data warehouse of a digital oilfield. With increasing amounts of data collected from intelligent controllers and sensors, the lack of mechanisms for combining data from different sources and providing them to consumers affect the overall management efficiency. In addition, without it is impossible making the next logical step - the effective application of intelligent analysis methods. The paper describes the high-level architecture, as well as subsystems of operational management and decision support. The presented data are intermediate results of the project "Digital oilfield heterogeneous distributed data warehouse for informational support of decision-making processes"

Methodical Approach to Developing a Decision Support System for Well Interventions Planning

The paper contains aspects of developing a decision support systems aimed for well interventions planning within the process of oil production engineering. The specific approach described by authors is based on system analysis methods and object model for system design. Declared number of problem-decision principles as follows: the principle of consolidated information area, the principle of integrated control, the principle of development process transparency. Also observed a set of models (class model, object model, attribute interdependence model, component model, coordination model) specified for designing decision support system for well intervention planning

Automated anomalies detection in the work of industrial robots

This article describes the results of the anomalies automated detection algorithm development in the operation of industrial robots. The development of robotic systems, in particular, industrial robots, and software for them is ahead of the tracking and managing technologies development. The operation of the digital production system involves the generation of a large amount of various data characterizing the state of both the specific equipment and the industrial system as a whole. Such a system produces a sufficient amount of data to develop machine learning models to analyze this data to solve problems such as forecasting and modeling. As part of the study, an experiment was conducted based on the equipment of the laboratory of industrial robots of Tomsk Polytechnic University. In the course of the research, the industrial manipulator moved loads belonging to different classes by weight. An algorithm was developed for the automated analysis of the values of the parameters of the consumed current and the position of the manipulator

Automated anomalies detection in the work of industrial robots

This article describes the results of the anomalies automated detection algorithm development in the operation of industrial robots. The development of robotic systems, in particular, industrial robots, and software for them is ahead of the tracking and managing technologies development. The operation of the digital production system involves the generation of a large amount of various data characterizing the state of both the specific equipment and the industrial system as a whole. Such a system produces a sufficient amount of data to develop machine learning models to analyze this data to solve problems such as forecasting and modeling. As part of the study, an experiment was conducted based on the equipment of the laboratory of industrial robots of Tomsk Polytechnic University. In the course of the research, the industrial manipulator moved loads belonging to different classes by weight. An algorithm was developed for the automated analysis of the values of the parameters of the consumed current and the position of the manipulator

Modeling the Process of School Shooters Radicalization (Russian Case)

Research on radicalization became relevant to the study of terrorism and violent extremism just two decades ago. The accumulated empirical data on terrorism have led researchers and experts to understand that radicalization is a predictor of violent actions by terrorists, violent extremists, and lone actors. Violent incidents committed by school shooters are not terrorist crimes, but there is good reasons for inclusion as terrorist crimes since they have similar mechanisms. The article aims to create a conceptual model of school-shooter radicalization and determine the distinguishing features of the process. The paper presents a theoretical and methodological base of content analysis concepts, political models, and terrorist radicalization on the different levels of study. Based on the content analysis results, we identify the significant gaps in the research field, consider the radicalization phenomenon in detail, substantiated the qualitative aspects of the school shooters radicalization, and propose a conceptual scheme. Psychological, behavioral, cognitive aspects of the school shooters radicalization reflect a holistic picture of the relationship between the process phases and changes in the parameters of the object’s state. The aspects of radicalization and this phenomenon's qualitative properties are interpreted as the determinants of the conceptual model. The model includes five stages, each of which is considered to be one of the components for the formation and acceptance of the idea of a violent way to solve a problem, but certainly do not act individually as the only component that leads to the actual implementation of the incident of a school shooting. An in-depth study of online social connections and warning signs, mobilization factors, behavioral trajectories, and imitation mechanisms can help scientists understand why school shooters are increasingly motivated to use violent means to achieve personal goals. We have outlined the possibilities and prospects of the model's application and directions for future research

The algorithm of forecasting of the oil well intervention effect

The paper reviews stages of oil well intervention effect forecasting. The proposed algorithm based on regression equation solution automates the process of oil well intervention effect forecasting. An assessment of the hydraulic fracturing effect was provided as a validation of the algorithm. According to assessments results, the suggested regression algorithm allows a 1.87-time decrease of an estimation error according to the error of central tendency

Automated anomalies detection in the work of industrial robots

This article describes the results of the anomalies automated detection algorithm development in the operation of industrial robots. The development of robotic systems, in particular, industrial robots, and software for them is ahead of the tracking and managing technologies development. The operation of the digital production system involves the generation of a large amount of various data characterizing the state of both the specific equipment and the industrial system as a whole. Such a system produces a sufficient amount of data to develop machine learning models to analyse this data to solve problems such as forecasting and modelling. As part of the study, an experiment was conducted based on the equipment of the laboratory of industrial robots of Tomsk Polytechnic University. In the course of the research, the industrial manipulator moved loads belonging to different classes by weight. An algorithm was developed for the automated analysis of the values of the parameters of the consumed current and the position of the manipulator

Method for Detecting Far-Right Extremist Communities on Social Media

Far-right extremist communities actively promote their ideological preferences on social media. This provides researchers with opportunities to study these communities online. However, to explore these opportunities one requires a way to identify the far-right extremists’ communities in an automated way. Having analyzed the subject area of far-right extremist communities, we identified three groups of factors that influence the effectiveness of the research work. These are a group of theoretical, methodological, and instrumental factors. We developed and implemented a unique algorithm of calendar-correlation analysis (CCA) to search for specific online communities. We based CCA on a hybrid calendar correlation approach identifying potential far-right communities by characteristic changes in group activity around key dates of events that are historically crucial to those communities. The developed software module includes several functions designed to automatically search, process, and analyze social media data. In the current paper we present a process diagram showing CCA’s mechanism of operation and its relationship to elements of automated search software. Furthermore, we outline the limiting factors of the developed algorithm. The algorithm was tested on data from the Russian social network VKontakte. Two experimental data sets were formed: 259 far-right communities and the 49 most popular (not far-right) communities. In both cases, we calculated the type II error for two mutually exclusive hypotheses—far-right affiliation and no affiliation. Accordingly, for the first sample, Я = 0.81. For the second sample, Я = 0.02. The presented CCA algorithm was more effective at identifying far-right communities belonging to the alt-right and Nazi ideologies compared to the neo-pagan or manosphere communities. We expect that the CCA algorithm can be effectively used to identify other movements within far-right extremist communities when an appropriate foundation of expert knowledge is provided to the algorithm