A novelty-based multi-objective evolutionary algorithm for identifying functional dependencies in complex technical infrastructures from alarm data

In this work, a Multi-Objective Evolutionary Algorithm (MOEA) is developed to identify Functional Dependencies (FDEPs) in Complex Technical Infrastructures (CTIs) from alarm data. The objectives of the search are the maximization of a measure of novelty, which drives the exploration of the solution space avoiding to get trapped in local optima, and of a measure of dependency among alarms, which drives the uncovering of functional dependencies. The main contribution of the work is the direct identification of patterns of dependent alarms; this avoids going through the preliminary step of mining association rules, as typically done by state-of-the-art methods which, however, fail to identify rare functional dependencies due to the need of setting a balanced minimum occurrence threshold. The proposed framework for FDEPs identification is applied to a synthetic alarm database generated by a simulated CTI model and to a real large-scale database of alarms collected at the CTI of CERN (European Organization for Nuclear Research). The obtained results show that the framework enables the thorough exploration of the solution space and captures also rare functional dependencies.

Integrity Constraints Revisited: From Exact to Approximate Implication

Integrity constraints such as functional dependencies (FD) and multi-valued dependencies (MVD) are fundamental in database schema design. Likewise, probabilistic conditional independences (CI) are crucial for reasoning about multivariate probability distributions. The implication problem studies whether a set of constraints (antecedents) implies another constraint (consequent), and has been investigated in both the database and the AI literature, under the assumption that all constraints hold exactly. However, many applications today consider constraints that hold only approximately. In this paper we define an approximate implication as a linear inequality between the degree of satisfaction of the antecedents and consequent, and we study the relaxation problem: when does an exact implication relax to an approximate implication? We use information theory to define the degree of satisfaction, and prove several results. First, we show that any implication from a set of data dependencies (MVDs+FDs) can be relaxed to a simple linear inequality with a factor at most quadratic in the number of variables; when the consequent is an FD, the factor can be reduced to 1. Second, we prove that there exists an implication between CIs that does not admit any relaxation; however, we prove that every implication between CIs relaxes "in the limit". Then, we show that the implication problem for differential constraints in market basket analysis also admits a relaxation with a factor equal to 1. Finally, we show how some of the results in the paper can be derived using the I-measure theory, which relates between information theoretic measures and set theory. Our results recover, and sometimes extend, previously known results about the implication problem: the implication of MVDs and FDs can be checked by considering only 2-tuple relations.

Computational Scale-Up for Flood Fed/Starve Fed Single Screw Extrusion of Polymers

A novel scaling-up computer system for single screw extrusion of polymers has been developed. This system makes it possible to scale-up extrusion process with both starve feeding and flood feeding. Each of the scale-up criteria can be an objective function to be minimized, represented by single values or functional dependencies over the screw length. The basis of scaling-up is process simulation made with the use of the GSEM program (Global Screw Extrusion Model). Scaling-up is performed using the GASES program (Genetic Algorithms Screw Extrusion Scaling) based on Genetic Algorithms. Scaling-up the extrusion process has been performed to increase extrusion output according to the scaling-up criteria defined by the single parameters of unit energy consumption, polymer plasticating rate and polymer temperature, as well as by the process parameters profiles of the temperature and plasticating. The global objective function reached the lowest value for the selected process parameters, and extrusion throughput was significantly increased.

Methodology for determining the flow rate and temperature of generated hot water when calculating the thermal diagram of a hot water boiler room

The consumption and temperature of hot water produced by boiler units are calculated using such a quantity as the consumption of the consumed network water. The formulas represent functional dependencies connecting the obtained values not only with the consumption of heating water, but also with the consumption of hot water supplied for recirculation, for own needs and for the needs of the fuel economy. They take into account the losses of network and hot water. The formulas are obtained as a result of the joint solution of the equation for the total consumption of hot water and the equation for its partial costs.

Analysis of methods and methods of diagnosing internal combustion engines by non-assembly control methods

The question of interaction of schemes of diagnostics of engines by methods of non-disassembled control is considered, the analysis of existing methods is executed, and the use of the complex approaches increasing reliability of work of engines is offered. Methods of non-detachable diagnostics with modeling of deregulation of engine systems during operation and diagnosing the initial stages of structural and functional malfunctions are analyzed. The analysis allowed to determine the direct diagnostic parameters that unambiguously characterize the state of the object and indirect, associated with direct functional dependencies, and identify the most effective, in terms of determining correlations - direct diagnostic methods, which include, for example, indication of the working process in the engine cylinder. A relatively simple scheme of measuring and determining signals from several diagnostic elements simultaneously is proposed, from which we can conclude that information from one measurement channel can comprehensively characterize the technical condition of several elements of engine mechanisms or systems: vibration method, acoustic method, gas chromatography methods, indirect indication by determining the stress in the studs of the cylinder head, assessing the level of wear of parts on the metal content in the engine oil, as well as diagnosing the parameters of the uneven speed of the crankshaft. Analysis of methods and techniques for diagnosing internal combustion engines led to the conclusion that the method of diagnosing the uneven speed of the engine crankshaft is a promising direction in the development of methods of non-demountable diagnostics of internal combustion engines. residual life and monitor the technical condition of the engine.

Algorithm of the calculation of technological for several objects of technological standardization

Цель исследования – разработка алгоритма расчета технологических показателей отдельно по видам выпускаемой продукции для интегрированного целлюлозно-бумажного комбината при сбросе сточных вод после очистки сточных вод на единых очистных сооружениях промышленных стоков. Использован балансовый метод расчёта значений масс загрязняющих веществ, образующихся на тонну выпускаемой продукции ЦБК на основе масс загрязняющих веществ, образующихся во вспомогательных технологических процессах, с учетом очистки сточных вод на общепроизводственных очистных сооружениях. Технологические показатели установлены отдельно для продукции, нормируемой по беленой или небеленой целлюлозе. Если фактические значения технологических показателей превысят значения технологических показателей НДТ, то необходимо разработать водоохранные мероприятия по достижению этих показателей и, до момента их достижения, оплачивать негативное воздействие на водные объекты со стократным повышающим коэффициентом. Разработан алгоритм и функциональные зависимости расчета технологических показателей для ЦБК, выпускающих продукцию, содержащую в композиции беленую и небеленую целлюлозу. Алгоритм рассмотрен на примере условного ЦБК, выпускающего первичные небелёные и беленые волокнистые полуфабрикаты и продукцию полного цикла. К первичным волокнистым полуфабрикатам небеленым отнесены: хвойная и лиственная целлюлоза, ТММ, ХТММ; к первичным волокнистым беленым полуфабрикатам отнесены: беленая хвойная и лиственная целлюлоза, БХТММ; к продукции полного цикла отнесены бумага, картон и продукция их переработки. Алгоритм расчета состоит из пяти этапов: 1 – построение балансовой схемы расчета технологических показателей; 2 – расчет технологических показателей для первичных волокнистых полуфабрикатов небеленых; 3 – расчет технологических показателей для первичных волокнистых полуфабрикатов беленых; 4 – расчет технологических показателей для продукции полного цикла; 5 – расчет значений технологических показателей для каждого вида продукции с учетом очистки на общепроизводственных очистных сооружениях. The purpose of the study is to develop an algorithm for calculating technological indicators separately by types of products for an integrated pulp and paper mill when discharging wastewater after wastewater treatment at unified industrial wastewater treatment plants. A balance method was used for calculating the values of the masses of pollutants formed per ton of output from the pulp and paper mill based on the masses of pollutants formed in auxiliary technological processes, taking into account wastewater treatment at general industrial treatment facilities. Technological indicators are set separately for products rated for bleached or unbleached pulp. If the actual values of technological indicators exceed the values of technological indicators BAT, then it is necessary to develop water protection measures to achieve these indicators and, until they are reached, to pay for the negative impact on water bodies with a hundredfold increasing coefficient. An algorithm and functional dependencies for calculating technological indicators for pulp and paper mills producing products containing bleached and unbleached cellulose in the composition have been developed. The algorithm is considered on the example of a conventional pulp and paper mill, which produces primary unbleached and bleached fibrous semi-finished products, and full-cycle products. Primary unbleached fibrous semi-finished products include: coniferous and deciduous cellulose, ТМP, CТМP; primary fibrous bleached semi-finished products include: bleached softwood and hardwood pulp, BCTMP; full cycle products include: paper, cardboard and their processing products. The calculation algorithm consists of five stages: 1 – building a balance sheet for calculating technological indicators; 2 – calculation of technological indicators for primary fibrous semi-finished products, unbleached; 3 – calculation of technological indicators for primary fibrous semi-finished products bleached; 4 – calculation of technological indicators for full cycle products; 5 – calculation of the values of technological indicators for each type of product, taking into account cleaning at general production treatment facilities.

SEARCH FOR WAYS OF CONTROLLED MODIFICATION OF CHARACTERISTICS OF FUNCTIONAL UNITS OF ADAPTIVE AIR PURIFICATION SYSTEMS

Information on alkaline coordination nitrates of rare-earth elements of the cerium subgroup - precursors of promising modern multifunctional materials - on the conditions of their formation and existence, the nature of the chemical bond, the composition, structure, shape of the Ln coordination polyhedra, the type of ligand coordination, and the existence of isotypic series in stoichiometry are generalized. composition, structure, characteristic properties. The data obtained (as primary information) is the basis for the detection, identification, and control of the phase state of processing objects in the preparatory stages, the choice of criteria for the compatibility of the components in the formation of single-layer and layered nanostructured oxide composite systems of lanthanides and transition elements for general purposes, with catalytic and photocatalytic activity, coatings self-cleaning with hydrophilic properties; development of various combined methods for their activation and identification of technological functional dependencies; controlled modification of the properties of the obtained target products. To increase the photocatalytic activity of coating samples based on highly dispersed anatase TiO2, a methodology for chemical modification of oxidation centers in their surface layer with heat treatment in contact with thermolysis products of alkaline coordination lanthanide nitrate melts is proposed. An effective test photocatalytic destruction of organic substrates vapors has been discovered using ethanol as an example.Effective activation of the functioning of functional units in the composition of self-adjusting air purification complexes using new photocatalytically active three-layer perovskite-like oxide materials M2Ln2Ti3O10 (M - Li, Na, K; Ln - La, Nd) has been proven. The variability of such methods for creating and modifying the characteristics of polyfunctional coatings is determined by the number and individual properties of representatives of the natural series of lanthanides, alkali metals of the periodic system, the peculiarities of their cooperative behavior in the preparatory technological stages, conditions and methods of activation of formation processes, the nature of the substrate, and other factors.

Structurally constrained effective brain connectivity

The relationship between structure and function is of interest in many research fields involving the study of complex biological processes. In neuroscience in particular, the fusion of structural and functional data can help to understand the underlying principles of the operational networks in the brain. To address this issue, this paper proposes a constrained autoregressive model leading to a representation of effective connectivity that can be used to better understand how the structure modulates the function. Or simply, it can be used to find novel biomarkers characterizing groups of subjects. In practice, an initial structural connectivity representation is re-weighted to explain the functional co-activations. This is obtained by minimizing the reconstruction error of an autoregressive model constrained by the structural connectivity prior. The model has been designed to also include indirect connections, allowing to split direct and indirect components in the functional connectivity, and it can be used with raw and deconvoluted BOLD signal.The derived representation of dependencies was compared to the well known dynamic causal model, giving results closer to known ground-truth. Further evaluation of the proposed effective network was performed on two typical tasks. In a first experiment the direct functional dependencies were tested on a community detection problem, where the brain was partitioned using the effective networks across multiple subjects. In a second experiment the model was validated in a case-control task, which aimed at differentiating healthy subjects from individuals with autism spectrum disorder. Results showed that using effective connectivity leads to clusters better describing the functional interactions in the community detection task, while maintaining the original structural organization, and obtaining a better discrimination in the case-control classification task.