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This article discusses the problem of accurate and efficient modeling of photovoltaic (PV) panels. It is a highly nonlinear problem. The following models were considered: a single diode model, a double diode model, a triple diode model, a four diode model, a module model (a poly-crystalline Photowatt-PWP201 module and a mono-crystalline STM6-40/36 module). The article presents a mathematical notation of these models, a detailed interpretation of their individual components, and a comparison of obtained results. To increase the effectiveness of modeling, a new population-based algorithm which can handle complex objective functions and a large number of decision variables was developed. This is important for the problem of identifying the parameters of PV cell models because each evaluation of the objective function requires calculating a set of points that determine the current–voltage characteristics. Moreover, in the considered problem a solution is searched with the use of the trial and error method. The proposed algorithm is called Micro Adaptive Fuzzy Cuckoo Search Optimization (μ AFCSO). The μ AFCSO algorithm uses several new mechanisms that were developed based on our experience with population-based algorithms. The use of these mechanisms has produced very good results in simulations. In the scope of simulation studies, the μ AFCSO algorithm was used for parameter extraction in six PV cell models and was also applied to optimize fifteen typical test functions. The test functions were considered in order to demonstrate that our algorithm can be used to solve typical problems processed using population-based algorithms. The results obtained in this study were compared with the results obtained using well-established algorithms. The results obtained in this work are better or comparable to them. [Display omitted] • The article focuses on modeling PV cells by identifying model parameters. • We present a wide collection of PV cell models and compare their accuracy. • We propose a new algorithm for identifying the parameters of the PV models. • Our method uses a population of individuals but has an original working formula. • We have achieved a very high modeling accuracy. [ABSTRACT FROM AUTHOR]

Identity verification based on the dynamic signature is an important issue of biometrics. Analysis of the signature dynamics, especially selecting partitions in order to improve processing precision, is very often used to evaluate whether a given signature is genuine. In our previous works we have presented methods for selecting partitions with a specific interpretation. They correspond to low and high velocity of the pen and low and high pressure of the pen in the initial, middle and final time phases of a signing process. In this paper we propose a new partitioning method which selects a specific, i.e. characteristic set of partitions for each user individually. The purpose of this approach is: (a) to increase the precision of signature processing, (b) to individually adapt the method to the specifics of the user signatures by eliminating redundant partitions, and (c) to simplify test signatures verification. The tests of the proposed method were performed using the BioSecure signature database. [ABSTRACT FROM AUTHOR]

Abstract: Verification of identity based on the analysis of dynamic signatures is an important problem of biometrics. The effectiveness of the verification significantly increases when the dynamic characteristics of signature (e.g. velocity of the pen) are considered. These characteristics are individual for each user and difficult to imitate. The effectiveness of the verification can be further improved by using partitioning. In this paper we propose a new method which uses partitioning. In our method partitions represent areas of high and low speed of signature and high and low pen׳s pressure. All selected partitions are used by our algorithm, but more important in the classification process are these partitions, in which the signatures of the user acquired during training phase are more stable. Moreover, final classification is interpretable. In this paper we present the simulation results of the proposed method for the two databases: SVC2004 and BioSecure Database. [Copyright &y& Elsevier]

Highlights: [•] We propose a new dynamic signature verification system using vertical partitioning. [•] In our algorithm partitions represent moments of signing process. [•] Our algorithm takes advantage of fuzzy sets and systems theory. [•] Our algorithm allows to extract knowledge about the signature verification. [•] Our algorithm takes into account hierarchy of partitions individually for each user. [Copyright &y& Elsevier]

In this work, we consider the flexible neuro-fuzzy systems of the Mamdani-type. When designing such systems to solve approximation problem, we should choose triangular norms used in inference and aggregation operators. This can be done by trial and error. In this work, we propose an algorithm that allows in an automatic way to choose the types of triangular norms in the learning process. The task of this algorithm is also an automatic selection of parameters of all functions describing the system. The algorithm uses an evolutionary strategy for its action and has been tested using well-known approximation benchmarks. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new class of neuro-fuzzy systems. Moreover, we develop a novel method for reduction of such systems without the deterioration of their accuracy. The reduction algorithm gradually eliminates inputs, rules, antecedents, and the number of discretization points of integrals in the center of area defuzzification method. It then automatically detects and merges similar input and output fuzzy sets. Through computer simulations it is shown that accuracy of the system after reduction and merging has not deteriorated despite the fact that in some cases up to 54% of various parameters and 74% of inputs were eliminated. The reduction algorithm has been tested using well-known classification benchmarks. [ABSTRACT FROM AUTHOR]

This paper presents original solutions from the field of intelligent expert systems for use in behavioral biometrics. They combine possibilities offered by biometric methods with the theory of fuzzy sets and the theory of population-based algorithms. Behavioral biometrics is concerned with learned behaviors such as a way of signing, movement, speaking, etc. However, these attributes trend to change over time. This is particularly important in a variety of fields including identity authentication. In this paper we present a new approach to the analysis of changes in behavioral characteristics. The purpose of the proposed approach is to predict values of features describing the so-called dynamic signature. It is the signature represented by waveforms describing a number of features including pen pressure and velocity. The proposed approach can be particularly useful in cases in which the interval between signature acquisition sessions is long. Our approach was tested with the use of the dynamic signature database called ATVS-SLT DB. It seems that the solutions proposed in this paper offer a new and interesting look at the solution of the problem of variability (aging) of biometric features. [ABSTRACT FROM AUTHOR]

Abstract: In the paper, the evolutionary strategy is applied for learning flexible neuro-fuzzy systems. In the process of evolution we determine: fuzzy inference (Mamdani type or logical type—described by an -implication), specific fuzzy implication, if the logical type system is found in the process of evolution or specific -norm connecting antecedents and consequences, if the Mamdani type system is found in the process of evolution, specific -norm for aggregation of antecedents in each rule, specific triangular norm describing aggregation operator, shapes and parameters of fuzzy membership functions, weights describing importance of antecedents of rules, and weights describing importance of rules, parameters of adjustable triangular norms, parameters of soft triangular norms. It should be noted that the crossover and mutation operators are chosen in a self-adaptive way. The method is tested using well known classification benchmarks. [Copyright &y& Elsevier]

Nanotechnology has opened numerous ways for physically realizing very sophisticated nanodevices that can be fabricated exclusively using molecular engineering methods. However, the synthesis procedures that lead to the production of nanodevices are usually complicated and time consuming. For this reason, the destination materials should be well designed. Therefore, numerical simulations can be invaluable. In this work, we present numerical simulations of the magnetic behaviour of magnetic units shaped into nanometric strips as a low dimensional layout that can be used as nano-systems of combinatorial logic. We showed that magnetic layouts that contain fewer than 16 magnetic units can take on a specific configuration as a response to the input magnetic field. Such configuration can be treated as an output binary word. The layouts that contained various numbers of magnetic units showed different switching characteristics (utterly different order of inverting of strips' magnetic moments), thus creating numerous combinations of the output binary words in response to the analog magnetic signal. The number of possible output binary words can be increased even more by adding parameters––the system's initial magnetic configuration. The physical realization of the model presented here can be used as a very simple and yet effective encryption device that is based on nanometric arrays of magnetic units rather than an integrated circuit. The same information, provided by the proposed system, can be utilized for the construction of a nano-sensor for measuring of magnetic field with the possibility of checking also the history of magnetization. [ABSTRACT FROM AUTHOR]

The synthesis routes are presented for the preparation of nanocomposites composed of nanocrystals placed inside SBA-15 silica pores. The procedures assume treating the silica channels as nanoreactors, where nanocrystals are created as a result of thermal decomposition of internal functional units. Its sizes and chemical composition can be modified by the change of functional group types and density inside silica channels. The procedure is demonstrated by the example of copper pyrophosphate quantum dots and silver oxide nanoparticles inside silica mezochannels. The method can be easily adopted to other types of nanocrystals that can be synthesized inside silica nanoreactors. [ABSTRACT FROM AUTHOR]

In this work, we have developed a chemical procedure enabling the preparation of highly ordered and vertically aligned mesoporous silica films containing selected contents of silver ions bonded inside the mesopore channels via anchoring propyl-carboxyl units. The procedure involves the electrochemically assisted self-assembly co-condensation of tetraethoxysilane and (3-cyanopropyl)triethoxysilane in the presence of cetyltrimethylammonium bromide as a surfactant, the subsequent hydrolysis of cyano groups into carboxylate ones, followed by their complexation with silver ions. The output materials have been electrochemically characterized with regard to the synthesis effectiveness in order to confirm and quantify the presence of the silver ions in the material. The mesostructure has been observed by transmission electron microscopy. We have pointed out that it is possible to finely tune the functionalization level by controlling the co-condensation procedure, notably the concentration of (3-cyanopropyl)triethoxysilane in the synthesis medium. [ABSTRACT FROM AUTHOR]

Nanophotonics is one of the most important branches of electronics. The search for and design of novel and more efficient laser-operated materials seems to be fully justified. Therefore, here, we show how to fabricate materials that have an enhanced non-linear optical response using a procedure of synthesis in a silica nanoreactor. We obtained the initial material through the precise functionalisation of SBA-15 silica using nickel phosphonate units that were anchored inside the silica channels by propyl chains, which was then transformed into an optically active nanocomposite after thermal processing. Using thermogravimetry, transmission electron microscopy (TEM), Raman vibrational analysis, and N 2 sorption analysis, we analysed the thermal behaviour of the initial functional material. All research that is connected with second- and third-order optical harmonic generation enables the structural changes in these materials and their influence on their optical properties to be explored. Nonlinear optical measurements confirmed our assumption that material that is prepared using silica nanoreactors can have precisely tailored properties, in this case, nonlinear optical properties. • The procedure of synthesis in silica nanoreactors was presented. • The obtained material synthesised presented superior NLO properties. • Porosity was utilised for inducing the charge displacement in crystals. • Thermal behaviour of functionalised SBA-15 was analysed. [ABSTRACT FROM AUTHOR]