Investigation of Hierarchical Fuzzy Inference Systems, when Obtaining Integral Estimates of the Analyzed Objects

The purpose of this paper is to study the patterns of the formation of output values in hierarchical systems offuzzy inference. Hierarchical fuzzy inference systems (HFIS) are used to aggregate heterogeneous parameters during the assessment of the state of various elements of complex systems. The use of HFIS allows avoiding the "curse" of the dimension associated with a strong increase in the number and complication of the structure of the production rule, which is characteristic of conventional fuzzy inference systems (FIS), which aggregate the results of interaction of different values of input variables in one knowledge base. As part of the research, numerical experiments were carried out to study the features of the formation of output patterns in HFIS, based on FIS using the Mamdani and Takagi-Sugeno algorithms. As a result of the experiment, it was shown that the output values of the studied HFIS tend to be grouped in the region of fixed values, and the output pattern itself acquires a stepwise character. The revealed property allows using HFIS to distribute the objects of the analyzed sample into groups of states. This property can be used to solve problems of distributing objects into groups in conditions when it is difficult to form a training sample for machine learning methods, but at the same time there is knowledge of the expert group about the features of the functioning of the object of research. Additionally, the paper investigates the features of the formation of output patterns depending on the parameters of the membership functions describing the input variables in HFIS, which are based on FIS using the Mamdani algorithm and HFIS, which are based on FIS using the Takagi-Sugeno algorithm.

The decision support system for conducting fire-prevention measures in woodlands

Purpose of the work is to propose provisions for the aggregation of parameters of a climatic and anthropogenic nature. Regulations are necessary to determine the rating of forest areas in terms of fire hazard level. As a result of the study, theoretical provisions for the aggregation of variables have been proposed. Variables are described on different metric scales and affect the final result in different ways. The provisions are based on the methods of the theory of fuzzy sets and fuzzy inference. The computational complex for determining the rating of the forest areas is implemented in the form of a hierarchical system of fuzzy inference. It is based on the Takagi-Sugeno algorithm. Simulation of the complex operation was carried out. As a result, it was concluded that the generated output pattern has a stepped nature. This makes it possible to classify the analyzed elements into state groups. This allows you to solve the problems of planning work on the implementation of preventive and/or preparatory measures to eliminate or prevent forest fires. The prospect of further research is the formation of decision support systems in the control processes organization of forest areas.

Transcriptomes of Electrophysiologically Recorded Dbx1-derived Inspiratory Neurons of the preBötzinger Complex in Neonatal Mice

Breathing depends on interneurons in the preBötzinger complex (preBötC) derived from Dbx1-expressing precursors. Here we investigate whether rhythm- and pattern-generating functions reside in discrete classes of Dbx1 preBötC neurons. In a slice model of breathing with ~5 s cycle period, putatively rhythmogenic Type-1 Dbx1 preBötC neurons activate 100-300 ms prior to Type-2 neurons, putatively specialized for output pattern, and 300-500 ms prior to the inspiratory motor output. We sequenced Type-1 and Type-2 transcriptomes and identified differential expression of 123 genes including ionotropic receptors (Gria3 and Gabra1) that may explain their preinspiratory activation profiles and Ca2+ signaling (Cracr2a, Sgk1) involved in inspiratory and sigh bursts. Surprisingly, neuropeptide receptors that influence breathing (e.g., μ-opioid and bombesin-like peptide receptors) were only sparsely expressed, which suggests that cognate peptides and opioid drugs exert their profound effects on a small fraction of the preBötC core. These data in the public domain help explain the neural origins of breathing.

Application of Reference Voltage Control Method of the Generator Using a Neural Network in Variable Speed Synchronous Generation System of DC Distribution for Ships

In the case of DC power distribution-based variable speed engine synchronous generators, if the output reference voltage is kept constant regardless of the generator engine operating speed, it may cause damage to the internal device and windings of the generator due to over-flux or over-excitation. The purpose of this study is to adjust the generator reference voltage according to the engine speed change in the DC distribution system with the variable speed engine synchronous generator. A method of controlling the generator reference voltage according to the speed was applied by adjusting the value of the variable resistance input to the external terminal of the automatic voltage regulator using a neural network controller. The learning data of the neural network was measured through an experiment, and the input pattern was set as the rotational speed of the generator engine, and the output pattern was set as the input current of the potentiometer. Using the measured input/output pattern of the neural network, the error backpropagation learning algorithm was applied to derive the optimum connection weight to be applied to the controller. For the test, the variable speed operation range of the generator engine was set to 1100–1800 rpm, and the input current value of the potentiometer according to the speed increase or decrease within the operation range and the output of the voltage output from the actual generator were checked. As a result of neural network control, it was possible to confirm the result that the input current value of the potentiometer accurately reached the target value 4–20 mA at the point where the initial speed change occurred. It was confirmed that the reference voltage was also normally output in the target range of 250–440 V.

Phonological Templates in Development

Based on cross-linguistic data from several children each learning one of eight languages and grounded in the theoretical frameworks of usage-based phonology, exemplar theory, and Dynamic Systems Theory, this book explores the patterns or phonological templates children develop once they are producing 20–50 words or more. The children are found to begin with ‘selected’ words, which match some of the vocal forms they have practised in babbling; this is followed by the production of more challenging adult word forms, adapted—differently by different children and with some shaping by the particular adult language—to fit that child’s existing word forms. Early accuracy is replaced by later recourse to an ‘inner model’ of what a word can sound like; this is a template, or fixed output pattern to which a high proportion of the children’s forms adhere for a short time, before being replaced by ‘ordinary’ (more adult-like) forms with regular substitutions and omissions. The idea of templates developed in adult theorizing about phonology and morphology; in adult language it is most productive in colloquial forms and pet names or hypocoristics, found in informal settings or ‘language at play’. These are illustrated in some detail for over 200 English rhyming compounds, 100 Estonian and 500 French short forms. The issues of emergent systematicity, the roles of articulatory and memory challenges for children, and the similarities and differences in the function of templates for adults as compared with children are central concerns.

Night-sky radiometry can revolutionize the characterization of light-pollution sources globally

The city emission function (CEF), describing the angular emission from an entire city as a light source, is one of the key elements in night-sky radiance models. The CEF describes the rate at which skyglow depends on distance and is indispensable in any prediction of light-pollution propagation into nocturnal environments. Nevertheless, the CEF remains virtually unexplored because appropriate retrieval tools have been unavailable until very recently. A CEF has now been obtained from ground-based night-sky observations and establishes an experiment successfully conducted in the field to retrieve the angular emission function for an urban area. The field campaign was conducted near the city of Los Mochis, Mexico, which is well isolated from other cities and thus dominates all light emissions in its vicinity. The experiment has proven that radiometry of a night sky can provide information on the light output pattern of a distant city and allows for systematic, full-area, and cost-efficient CEF monitoring worldwide. A database of CEFs could initiate a completely new phase in light-pollution research, with significant economy and advanced accuracy of night-sky brightness predictions. The experiment and its interpretation represent unique progress in the field and contribute to our fundamental understanding of the mechanism by which direct and reflected uplight interact while forming the CEF.

Extensions to AGraP Algorithm for Finding a Reduced Set of Inexact Graph Patterns

Most algorithms to mine graph patterns, during the searching process, require a pattern to be identical to its occurrences, relying on the graph isomorphism problem. However, in recent years, there has been interest in the case in which it is acceptable to have some differences between a pattern and its occurrences, whether these differences are in labels or in structure. Allowing some differences and using inexact matching to measure the similarity between graphs lead to the discovery of new patterns, but some important challenges, such as the increment on the number of found patterns, make the post-mining analysis harder. In this work we focus on two extensions of the AGraP algorithm, which mines inexact patterns, addressing the issue of reducing the output pattern set while trying to retain the useful information gained through the use of inexact matching. First, exploring a traditional approach, we propose the CloseAFG algorithm that focuses on closed patterns. Then, we propose the IntAFG algorithm to find a subset of patterns covering the original pattern set, while lessening redundancy among selected patterns. We show the performance of our approaches through some experiments on synthetic databases; additionally, we also show the usefulness of the reduced pattern sets for image classification.