ENTERPRISE MANAGEMENT IN THE CONTEXT OF EXPANDING THE SCOPE OF BLOCKCHAIN TECHNOLOGY

The method of creating an automated enterprise management system is considered. The method is based on the ideas of the imitation approach and fuzzy mathematics. Real-time enterprise planning is the goal. The method is relevant in the context of setting up the market for goods and services with the expansion of e-commerce. The model of the formation of the plan of the enterprise for the execution of the orders received is considered.

Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics

Text-to-image generation models represent the next step of evolution in image synthesis, offering a natural way to achieve flexible yet fine-grained control over the result. One emerging area of research is the fast adaptation of large text-to-image models to smaller datasets or new visual concepts. However, many efficient methods of adaptation have a long training time, which limits their practical applications, slows down research experiments, and spends excessive GPU resources. In this work, we study the training dynamics of popular text-to-image personalization methods (such as Textual Inversion or DreamBooth), aiming to speed them up. We observe that most concepts are learned at early stages and do not improve in quality later, but standard model convergence metrics fail to indicate that. Instead, we propose a simple drop-in early stopping criterion that only requires computing the regular training objective on a fixed set of inputs for all training iterations. Our experiments on Stable Diffusion for a range of concepts and for three personalization methods demonstrate the competitive performance of our approach, making adaptation up to 8 times faster with no significant drops in quality.Comment: Code: https://github.com/yandex-research/DVAR. 19 pages, 14 figure

Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture

Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called Fusion Brain, the first competition which is targeted to make the universal architecture which could process different modalities (in this case, images, texts, and code) and solve multiple tasks for vision and language. The Fusion Brain Challenge combines the following specific tasks: Code2code Translation, Handwritten Text recognition, Zero-shot Object Detection, and Visual Question Answering. We have created datasets for each task to test the participants' submissions on it. Moreover, we have collected and made publicly available a new handwritten dataset in both English and Russian, which consists of 94,128 pairs of images and texts. We also propose a multimodal and multitask architecture - a baseline solution, in the center of which is a frozen foundation model and which has been trained in Fusion mode along with Single-task mode. The proposed Fusion approach proves to be competitive and more energy-efficient compared to the task-specific one

Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions

The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy. However, execution of instructions in real or simulated environments requires verification of the feasibility of actions as well as their relevance to the completion of a goal. We propose a new method that combines a language model and reinforcement learning for the task of building objects in a Minecraft-like environment according to the natural language instructions. Our method first generates a set of consistently achievable sub-goals from the instructions and then completes associated sub-tasks with a pre-trained RL policy. The proposed method formed the RL baseline at the IGLU 2022 competition.Comment: 6 pages, 3 figure

Beta-gamma systems and the deformations of the BRST operator

We describe the relation between simple logarithmic CFTs associated with closed and open strings, and their "infinite metric" limits, corresponding to the beta-gamma systems. This relation is studied on the level of the BRST complex: we show that the consideration of metric as a perturbation leads to a certain deformation of the algebraic operations of the Lian-Zuckerman type on the vertex algebra, associated with the beta-gamma systems. The Maurer-Cartan equations corresponding to this deformed structure in the quasiclassical approximation lead to the nonlinear field equations. As an explicit example, we demonstrate, that using this construction, Yang-Mills equations can be derived. This gives rise to a nontrivial relation between the Courant-Dorfman algebroid and homotopy algebras emerging from the gauge theory. We also discuss possible algebraic approach to the study of beta-functions in sigma-models.Comment: LaTeX2e, 15 pages; minor revision, typos corrected, Journal of Physics A, in pres

Quality Criterion of the Loading and Transport System Operation at Open-Pit Mines

Loading and transport operations at open-pit mines are performed mainly by heavy loading & transport systems (LTS). One of the main problems of the LTS is a rather low level of its operation quality, mainly due to the imbalanced influence of various factors on the efficiency of the joint operation of shovels and trucks as parts of the LTS. In this article we formulate, derive and analyze a functional criterion for assessing the LTS operation quality at open-pit mines. The rationale, general principles of the functional criterion formation, its general form for mixed (heterogeneous) truck and shovel fleets, which are typical for modern mining LTSs, are presented. For this purpose, modern methods of data collection and processing, mathematical modeling, analysis and synthesis are used. The possibility of assessing the LTS operation quality is very important for identifying the main directions of improving its operational performance and operation quality, for reaching an optimization of the key performance indicators by the quality criterion, and, as a result, for a possible saving of resources during the open-pit mining of minerals

Operation Quality Indicators for Shovel-Truck Systems at Open-Pit Coal Mines

Stripping and mining operations at open-pit coal mines are performed mainly by heavy shovel-truck systems (STS). One of the main problems of the STS is a rather low level of its operation quality, an objective assessment of which is an important step in identifying the causes of low quality and effective ways to improve it. The purpose of assessing the STS operation quality is defined as a functional criterion. The next important step of the assessment is to choose the set of indicators that most characterize the STS operation quality. In this article we present the rationale, the general principles for the formation of quality indicators set, the sources and the main dependencies for its determination. For this purpose, modern methods of data collection and processing, analysis and synthesis are used. The ability to assess the STS operation quality is very important for identifying the main directions of improving its operational performance, reaching the optimization of the key performance indicators by the quality criterion, and, as a result, for the possible saving of material and technical resources in the open-pit mining of minerals

Assessment of the shovel-truck system operation quality at open-pit mines in Kuzbass

Assessment of the shovel-truck system (STS) operation quality is based on the well-known method of non-expert assessment of the quality of mining machines. The methodology is based on the fundamental principles of qualimetry and allows making the assessment of functionally homogeneous machines of different sizes, types and designs based on the functional criterion of the machine, which determines its main purpose. In this work, the quality assessment is made not for a single machine, but for a set of machines, taking into account their interaction. Assessment of the STS operation quality allows us to create a basis for the selection of priority areas for its improvement. The work uses methods of mathematical modeling, data collection and processing, statistics, analysis and synthesis. A comprehensive quality assessment makes it possible to predict the level and select priority areas for improving existing STSs or STSs being projected

Modeling the operation of mining shovel-truck systems

Load and haul operations at open-pit mines are performed by shovel-truck systems (STSs). One of the main problems of STS is the low level of its operation quality. A means of improving the STS operation quality is its optimization, based on a systems approach, according to which the operation of system components is studied by analyzing the operation of the STS as a whole. The issues of optimal design of open-pit mining machines were being addressed. They all consider separate machines. Interpretations for mining STSs, however, have not been made. With regard to the optimization of the STS performance indicators, the systems approach consists in their optimal coordination with each other, provided that they meet the requirements for the STS operation. The optimization of the STS performance indicators is carried out according to its mathematical model, which includes the objective function and restrictions, represented in the form of linear regression analysis equations, directly linking the corresponding output performance indicators with the parameters being optimized. It is proposed to use generalized estimates as an optimization criterion, and single indicators of the STS operation quality as the parameters being optimized. This simplifies optimization and increases its accuracy, as well as provides the best degree of consistency of the parameters being optimized between themselves and the external environment

Assessment and prospects for improving the technical level of surface mining machines

Assessment of the technical level of surface mining machines is carried out according to a special method of expert-free assessment of min- ing machine quality, known as the G.I. Solod’s technique. The technique is based on the basic principles of qualimetry and allows to assess functional- ly homogeneous machines of different sizes, types and designs based on the functional criterion of the machine that determines its main purpose. Assessment of the technical level of mining machines creates the basis for choosing priority areas for its improvement and development of scientifi- cally-based methods for the optimal design of machines. In this regard, the aim of the work is a comprehensive assessment of the technical level of surface mining machines to increase it and optimize their parameters. For this, methods of mathematical modeling, statistics, data collection and pro- cessing, analysis and synthesis were used. The developed methodology for integrated assessment provides the ability to control the quality of a surface mining machine at all stages of its life cycle: design, manufacture, opera- tion