In this paper, a multi-layer perceptron (MLP) neural network (NN) is put forward as an efficient tool for performing two tasks: 1) optimization of multi-objective problems and 2) solving a non-linear system of equations. In both cases, mathematical functions which are continuous and partially bounded are involved. Previously, these two tasks were performed by recurrent neural networks and also strong algorithms like evolutionary ones. In this study, multi-dimensional structure in the output layer of the MLP-NN, as an innovative method, is utilized to implicitly optimize the multivariate functions under the network energy optimization mechanism. To this end, the activation functions in the output layer are replaced with the multivariate functions intended to be optimized. The effective training parameters in the global search are surveyed. Also, it is demonstrated that the MLP-NN with proper dynamic learning rate is able to find globally optimal solutions. Finally, the efficiency of the MLP-NN in both aspects of speed and power is investigated by some well-known experimental examples. In some of these examples, the proposed method gives explicitly better globally optimal solutions compared to that of the other references and also shows completely satisfactory results in other experiments.
In this paper a collection of iron objects from the Anatolian Seljuks Period, ca. 12th–13th century AD, are analysed and discussed from a metallurgical perspective. A total number of 21 iron-steel objects, small knives and flat bodied (with thin cross-section) arrowheads was examined. These objects are coming from the Seljuks’ cultural layers of Eğirdir (Isparta, Central Anatolian Caravanserai), Kubad Abad (Konya, Central Anatolian Sultan’s Palace Complex), and Samsat (Adıyaman, Eastern Anatolian Fortress). In the samples which were taken from iron tools, composite-like structures formed by different ferrous phases were revealed by metallography, SEM-EDX and micro hardness examinations. These structures are classified according to the production materials and techniques. The first group revealed signs of continuous forging and, in some cases, bloomery iron folding, which can lead to such composite-like structures. The second group consisted of tools which were produced from different starting materials which were forgewelded before or during shaping process. The crucible steel knives can be classified as another group, in which the composite-like structure exhibits totally different constituents leading to more homogeneous mechanical character. In modern times, composite materials have gained importance and become key engineering materials due to their outstanding specific properties. This study reveals that skilled Seljuks’ blacksmiths made similar materials design choices in the production of iron or steel objects, despite limited materials and metallurgical knowledge. and V příspěvku je diskutována kolekce železných předmětů z období rúmského sultanátu, ca 12.–13. stol. n. l., analyzovaná a hodnocená z metalurgického hlediska. Celkem 21 železných předmětů, menších nožů a plochých hrotů šípů (stenkým průřezem). Předměty pocházejí z kulturních vrstev rúmského sultanátu v Eğirdiru (Isparta, středoanatolský karavanseraj), Kubad Abad (Konya, středoanatolský sultanský pálácový komplex) a Samsat (Adıyaman, východoanatolská pevnost). Vzorky odebrané z železných nástrojů vykazovaly struktury podobné kompozitním, sestávající z různých strukturních fází vymezených pomocí metalografie, SEM-EDX a měřením mikrotvrdosti. Dané struktury byly kategorizovány podle užitých materiálů a techniky výroby. První skupina vykazovala známky kontinuálního kování a místy paketování svářkového kovu, které může vést k takovýmto jakoby kompozitním strukturám. Druhá skupina sestávala z nástrojů vyráběných z různých výchozích materiálů, které byly před nebo v průběhu tváření svařovány. Nože z kelímkové oceli lze klasifikovat jako další skupinu, ve které kompozitní struktura vykazuje naprosto odlišné složky, vedoucí k rovnoměrnějším mechanickým charakteristikám. V dnešní době nabyly kompozitní materiály velkého významu a díky svým výjimečným specifickým vlastnostem se staly klíčovými materiály strojírenství. Tato studie odhaluje, že zruční seldžučtí kováři volili podobnou materiálovou konstrukci při výrobě železných nebo ocelových předmětů, navzdory omezeným materiálovým a metalurgickým znalostem.
Reduction kinetics of P700+ after far-red radiation (FR)-induced oxidation in intact tobacco leaves was examined by analysing the post-irradiation relaxation of 810-830 nm absorbance difference. The reduction curve could be de-convoluted distinctively into two or three exponential decaying components, depending on the FR irradiance, the treating and measuring temperatures, and the extent of dark adaptation. The multi-phasic kinetics of P700+ re-reduction upon the turning off of FR irradiation is related to the heterogeneity of electron transport around photosystem 1 in thylakoid membranes. and Ming-Xian Jin, Zheng-Ju Yao, Hualing Mi.
This paper discusses the cluster analysis and visualisation tool, the self-organizing map (SOM). The pros and cons of different network sizes are discussed, in particular how they are suited to the purposes of direct data browsing and also the cluster analysis with U-matrices. The tree-structured SOM (TS-SOM) [4, 5] is proposed as a method of acquiring multi-resolution/multi-purpose mappings of a given input space. The TS-SOM is discussed in detail and a novel modification to the algorithm that improves its reliability as a multi-resolution visualization method is presented.
Accurate prediction of the Baltic index makes great difference to the strategic decision and risk avoidance of the enterprise. For the multi-step Baltic Supermax Index prediction, direct prediction and iterative prediction has its own advantages. Therefore, in this paper, in combination with direct and iterative prediction, based on Support Vector Machine (SVM), a hybrid multistep prediction model is put forward. In hybrid model, the output from the iterative model is a rough prediction and it need also be adjusted based on the output from the direct model. And weekly BSI data from January 2011 to November 2014 are used to test the model. The results show that the hybrid multistep prediction model based on SVM has high accuracy, and is feasible in the BSI prediction.
Cardiovascular dynamic and variability data are commonly used in experimental protocols involving cognitive challenge. Usually, the analysis is based on a sometimes more and sometimes less well motivated single specific time resolution ranging from a few seconds to several minutes. The present paper aimed at investigating in detail the impact of different time resolutions of the cardiovascular data on the interpretation of effects. We compared three template tasks involving varying types of challenge, in order to provide a case study of specific effects and combinations of effects over different time frames and using different time resolutions. Averaged values of hemodynamic variables across an entire protocol confirmed typical findings regarding the effects of mental challenge and social observation. However, the hemodynamic response also incorporates transient variations in variables reflecting important features of the control system response. The fine-grained analysis of the transient behavior of hemodynamic variables demonstrates that information that is important for interpreting effects may be lost when only average values over the entire protocol are used as a representative of the system response. The study provides useful indications of how cardiovascular measures may be fruitfully used in experiments involving cognitive demands, allowing inferences on the physiological processes underlying the responses., H. K. Lackner, J. J. Batzel, A. Rössler, H. Hinghofer-Szalkay, I. Papousek., and Obsahuje bibliografii
Total correlation (`TC') and dual total correlation (`DTC') are two classical ways to quantify the correlation among an n-tuple of random variables. They both reduce to mutual information when n=2. The first part of this paper sets up the theory of TC and DTC for general random variables, not necessarily finite-valued. This generality has not been exposed in the literature before. The second part considers the structural implications when a joint distribution μ has small TC or DTC. If TC(μ)=o(n), then μ is close to a product measure according to a suitable transportation metric: this follows directly from Marton's classical transportation-entropy inequality. If DTC(μ)=o(n), then the structural consequence is more complicated: μ is a mixture of a controlled number of terms, most of them close to product measures in the transportation metric. This is the main new result of the paper.
This paper studies a new model of social opinion dynamics in multiagent system by counting in two important factors, individual susceptibility and anchoring effect. Different from many existing models only focusing on one factor, this model can exhibit not only agreement phenomena, but also disagreement phenomena such as clustering and fluctuation, during opinion evolution. Then we provide several conditions to show how individual susceptibility and anchoring effect work on steady-state behaviors in some specific situations, with strict mathematical analysis. Finally, we investigate the model for general situations via simulations.
Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of the methods.
Fluorescence images of leaves of sugar beet plants (Beta vulgaris L. cv. Patricia) grown on an experimental field with different fertilisation doses of nitrogen [0, 3, 6, 9, 12, 15 g(N) m-2] were taken, applying a new multicolour flash-lamp fluorescence imaging system (FL-FIS). Fluorescence was excited by the UV-range (280-400 nm, λmax = 340 nm) of a pulsed Xenon lamp. The images were acquired successively in the four fluorescence bands of leaves near 440, 520, 690, and 740 nm (F440, F520, F690, F740) by means of a CCD-camera. Parallel measurements were performed to characterise the physiological state of the leaves (nitrogen content, invert-sugars, chlorophylls and carotenoids as well as chlorophyll fluorescence induction kinetics and beet yield). The fluorescence images indicated a differential local patchiness across the leaf blade for the four fluorescence bands. The blue (F440) and green fluorescence (F520) were high in the leaf veins, whereas the red (F690) and far-red (F740) chlorophyll (Chl) fluorescences were more pronounced in the intercostal leaf areas. Sugar beet plants with high N supply could be distinguished from beet plants with low N supply by lower values of F440/F690 and F440/F740. Both the blue-green fluorescence and the Chl fluorescence rose at a higher N application. This increase was more pronounced for the Chl fluorescence than for the blue-green one. The results demonstrate that fluorescence ratio imaging of leaves can be applied for a non-destructive monitoring of differences in nitrogen supply. The FL-FIS is a valuable diagnostic tool for screening site-specific differences in N-availability which is required for precision farming. and G. Langsdorf ... [et al.].