Selected aspects of complex, hypercomplex and fuzzy neural networks

This short report reviews the current state of the research and methodology on theoretical and practical aspects of Artificial Neural Networks (ANN). It was prepared to gather state-of-the-art knowledge needed to construct complex, hypercomplex and fuzzy neural networks. The report reflects the individual interests of the authors and, by now means, cannot be treated as a comprehensive review of the ANN discipline. Considering the fast development of this field, it is currently impossible to do a detailed review of a considerable number of pages. The report is an outcome of the Project 'The Strategic Research Partnership for the mathematical aspects of complex, hypercomplex and fuzzy neural networks' meeting at the University of Warmia and Mazury in Olsztyn, Poland, organized in September 2022.Comment: 46 page

The Extraction of Linguistic Knowledge Using Fuzzy Logic And Generalized Quantifiers

An algorithm for the extraction of linguistic knowledge from data records is presented. Generalized quantifier "many" and weights for individual variables can be included in the statement of the query. General outline of fuzzy logic deduction is introduced. The behavior of the algorithm is illustrated on "difficult order" example

Automatic Creation of Hypnogram

Polysomnography is an important diagnostic method used in sleep monitoring of patients with various sleep disorders. The formulation of a precise diagnosis requires correct evaluation and interpretation of polysomnography EEG and this evaluation is provided by a doctor. In order to save time, various automatic evaluations methods have been developed. One of these methods is based on signal division into 30 second long sections which are subsequently analyzed and reduced using adaptive segmentation and parameters are computed from these segments. Cluster analysis is used to divide individual segments and the class with biggest quantity of segments is called "priority class". Definition of sleep states is then based on priority class. The end result is a hypnogram and the average success rate of the proposed method is about 68%

Research on Advanced Soft Computing and its Applications (Introduction to the Special Issue)

The main objective for the research presented in this special issue is to advance theoretical basis in soft computing, for the purpose of improving applications. Why is this theoretical research needed? Because soft computing in general (and intelligent control and decision making in particular) are, in many aspects, still an art. To make this methodology easier to apply, we must use the experience of successful applications of fuzzy control, decision making or classification and extract formal rules that would capture this experience. To be able to do that efficiently, we must understand why some versions of soft computing methodology turned out to be more successful in some practical situations and less successful in others. In other words, to advance the practical success of soft computing methodology, we need further theoretical analysis of soft computing --- analysis targeted at enhancing its application abilities

Restoration management of cattle resting place in mountain grassland.

This study investigated the effect of restoration management of a weed-infested area, previously used as cattle resting place, on herbage production and nutrient concentrations in the soil and herbage. The experiment was undertaken from 2004 to 2011 at the National Park of Nízké Tatry, Slovakia. Three treatments were applied: (i) cutting twice per year, (ii) herbicide application, followed after three weeks by reseeding with a mixture of vascular plant species and then cut twice per year, and (iii) unmanaged. Treatments had significant effect on biomass production and concentration of nutrients in the soil and in herbage. Nutrient concentrations in herbage and in soil declined progressively under the cutting treatments and reached optimum ranges for dairy cattle at the end of the experiment when herbage N was less than 15 g kg-1 and herbage P was 3.4 g kg-1. There was also a strong positive relationship under the cutting treatments between soil nutrient concentrations and herbage nutrient concentrations for N, P, K, Mg and Ca. Although the cutting management as well as the combination of herbicide application with cutting management reduced nutrient concentrations in the soil and in herbage, the nutrient concentrations remained relatively high. We can conclude that restoration of grassland covered with weedy species like Urtica dioica and Rumex obtusifolius, with excessive levels of soil nutrients, cannot be achieved just by cutting and herbicide application

Atypical language representation in children with intractable temporal lobe epilepsy

This study evaluated language organization in children with intractable epilepsy caused by temporal lobe focal cortical dysplasia (FCD) alone or dual pathology (temporal lobe FCD and hippocampal sclerosis, HS). We analyzed clinical, neurological, fMRI, neuropsychological, and histopathologic data in 46 pediatric patients with temporal lobe lesions who underwent excisional epilepsy surgery. The frequency of atypical language representation was similar in both groups, but children with dual pathology were more likely to be left-handed. Atypical receptive language cortex correlated with lower intellectual capacity, verbal abstract conceptualization, receptive language abilities, verbal working memory, and a history of status epilepticus but did not correlate with higher seizure frequency or early seizure onset. Histopathologic substrate had only a minor influence on neuropsychological status. Greater verbal comprehension deficits were noted in children with atypical receptive language representation, a risk factor for cognitive morbidity. Main findings of the study: There was a significantly higher frequency of left handedness and worse immediate face recognition in the subgroup with dual pathology (FCD+HS). The patients with atypical fMRI language representation had lower global intellectual capacity, lower language skills, and more frequent status epilepticus in history. [Display omitted] •Atypical language representation is a significant risk factor for cognitive morbidity in pediatric patients with temporal lobe epilepsy.•Lesion type has only a small influence on the neuropsychological profile of these children

Managing temporal uncertainty in multi-mode Z-number fuzzy graph structures

In this paper we introduce an NP-hard optimization problem and examine preferences of decision-maker towards imprecise alternatives (modes) in a fuzzy temporal graph structure model. Fuzzy Z-number preference matrix is introduced and types of generalized precedence relations in fuzzy multi-mode resource-constrained project scheduling problem (F-MRCPSP) based on expert estimation are discussed. Implementation of Z-numbers allows handling uncertain data and modelling preferences of expert towards uncertain variables. Multi-mode way for activity performance allows considering temporal uncertainty, expert estimations, flexibility in switching from mode to mode and resource levelling profile problem. Geometrical interpretation for fuzzy multi-mode problem (F-MRCPSP) based on box packing is given

Modelling competing theories

We introduce a complete many-valued semantics for two normal lattice-based modal logics. This semantics is based on reflexive many-valued graphs. We discuss an interpretation and possible applications of this logical framework in the context of the formal analysis of the interaction between (competing) scientific theories.</p

Fuzzy modeling to ‘understand’ personal preferences of mHealth users: a case study

This case study evaluates to what extent personal preferences can be automatically derived from user event data in an mHealth setting. Based on a theoretical framework, user preferences are described using six classes. Based on this framework, a structure of six Takagi-Sugeno fuzzy inference systems was constructed and evaluated against baseline data from an official survey for measuring the framework's constructs. From this analysis, it was found that user preferences may be derived from user event data using fuzzy modeling with accuracy scores that are higher than a random predictor would typically achieve