All-optical nonlinear pulse processing based on normal dispersion fiber-enhanced nonlinear optical loop mirror

A novel simple all-optical nonlinear pulse processing technique using loop mirror intensity filtering and nonlinear broadening in normal dispersion fiber is described. The pulse processor offers reamplification and cleaning up of the optical signals and phase margin improvement. The efficiency of the technique is demonstrated by application to 40-Gb/s return-to-zero optical data streams. © 2004 IEEE.

Serial correlation in the returns of UK capitalization based portfolios

This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA. © 2004 Taylor and Francis Ltd.

Catalytic systems based on carbon supports for the low-temperature oxidation of carbon monoxide

Catalytic systems containing palladium, copper, and iron compounds on carbon supports-kernel activated carbon and fibrous carbon materials (Karbopon and Busofit)-for the low-temperature oxidation of CO were synthesized. The effects of the nature of the support, the concentration and composition of the active component, and the conditions of preparation on the efficiency of the catalytic system were studied. The catalytic system based on Karbopon exhibited the highest activity: the conversion of carbon monoxide was 90% at room temperature and a reaction mixture (0.03% CO in air) space velocity of 10 000 h. It was found that the metals occurred in oxidized states in the course of operation: palladium mainly occurred as Pd, whereas copper and iron occurred as Cu and Fe, respectively. © 2008 MAIK Nauka.

Robot Control Using Inductive, Deductive and Case Based Reasoning

The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure that could form a kernel of an autonomous intelligent robotic system. One alternative structure is proposed in order to form a basis of an intelligent system that would be able to operate in complex environments. The proposed structure is very flexible because of features that allow adapting via learning and adjustment of the used knowledge. Therefore, the proposed structure may be used in environments with stochastic features such as hardly predictable events or elements. The basic elements of the proposed structure have found their implementation in software system and experimental robotic system. The software system as well as the robotic system has been used for experimentation in order to validate the proposed structure - its functionality, flexibility and reliability. Both of them are presented in the paper. The basic features of each system are presented as well. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are also sketched at the end of the paper.

Representations of Inverse Functions by the Integral Transform with the Sign Kernel

Mathematics Subject Classification: Primary 30C40

A quantum Jensen-Shannon graph kernel using discrete-time quantum walks

In this paper, we develop a new graph kernel by using the quantum Jensen-Shannon divergence and the discrete-time quantum walk. To this end, we commence by performing a discrete-time quantum walk to compute a density matrix over each graph being compared. For a pair of graphs, we compare the mixed quantum states represented by their density matrices using the quantum Jensen-Shannon divergence. With the density matrices for a pair of graphs to hand, the quantum graph kernel between the pair of graphs is defined by exponentiating the negative quantum Jensen-Shannon divergence between the graph density matrices. We evaluate the performance of our kernel on several standard graph datasets, and demonstrate the effectiveness of the new kernel.

An aligned subtree kernel for weighted graphs

In this paper, we develop a new entropic matching kernel for weighted graphs by aligning depth-based representations. We demonstrate that this kernel can be seen as an aligned subtree kernel that incorporates explicit subtree correspondences, and thus addresses the drawback of neglecting the relative locations between substructures that arises in the R-convolution kernels. Experiments on standard datasets demonstrate that our kernel can easily outperform state-of-the-art graph kernels in terms of classification accuracy.

Transitive state alignment for the quantum jensen-shannon kernel

Kernel methods provide a convenient way to apply a wide range of learning techniques to complex and structured data by shifting the representational problem from one of finding an embedding of the data to that of defining a positive semidefinite kernel. One problem with the most widely used kernels is that they neglect the locational information within the structures, resulting in less discrimination. Correspondence-based kernels, on the other hand, are in general more discriminating, at the cost of sacrificing positive-definiteness due to their inability to guarantee transitivity of the correspondences between multiple graphs. In this paper we generalize a recent structural kernel based on the Jensen-Shannon divergence between quantum walks over the structures by introducing a novel alignment step which rather than permuting the nodes of the structures, aligns the quantum states of their walks. This results in a novel kernel that maintains localization within the structures, but still guarantees positive definiteness. Experimental evaluation validates the effectiveness of the kernel for several structural classification tasks. © 2014 Springer-Verlag Berlin Heidelberg.

A quantum Jensen-Shannon graph kernel using the continuous-time quantum walk

In this paper, we use the quantum Jensen-Shannon divergence as a means to establish the similarity between a pair of graphs and to develop a novel graph kernel. In quantum theory, the quantum Jensen-Shannon divergence is defined as a distance measure between quantum states. In order to compute the quantum Jensen-Shannon divergence between a pair of graphs, we first need to associate a density operator with each of them. Hence, we decide to simulate the evolution of a continuous-time quantum walk on each graph and we propose a way to associate a suitable quantum state with it. With the density operator of this quantum state to hand, the graph kernel is defined as a function of the quantum Jensen-Shannon divergence between the graph density operators. We evaluate the performance of our kernel on several standard graph datasets from bioinformatics. We use the Principle Component Analysis (PCA) on the kernel matrix to embed the graphs into a feature space for classification. The experimental results demonstrate the effectiveness of the proposed approach. © 2013 Springer-Verlag.

A continuous-time quantum walk kernel for unattributed graphs

Kernel methods provide a way to apply a wide range of learning techniques to complex and structured data by shifting the representational problem from one of finding an embedding of the data to that of defining a positive semidefinite kernel. In this paper, we propose a novel kernel on unattributed graphs where the structure is characterized through the evolution of a continuous-time quantum walk. More precisely, given a pair of graphs, we create a derived structure whose degree of symmetry is maximum when the original graphs are isomorphic. With this new graph to hand, we compute the density operators of the quantum systems representing the evolutions of two suitably defined quantum walks. Finally, we define the kernel between the two original graphs as the quantum Jensen-Shannon divergence between these two density operators. The experimental evaluation shows the effectiveness of the proposed approach. © 2013 Springer-Verlag.

A New Class of Processes for Formalizing and Generalizing Individual-Based Models: The Semi-Semi-Markov Processes

2000 Mathematics Subject Classification: 60K15, 60K20, 60G20,60J75, 60J80, 60J85, 60-08, 90B15.

Simultaneous multichannel carrier-suppressed return-to-zero to non-return-to-zero format conversion using a fiber Bragg grating

A novel multichannel carrier-suppressed return-to-zero (CSRZ) to non-return-to-zero (NRZ) format conversion scheme based on a single custom-designed fiber Bragg grating (FBG) with comb spectra is proposed. The spectral response of each channel is designed according to the algebraic difference between the CSRZ and NRZ spectra outlines. The tailored group delays are introduced to minimize the maximum refractive index modulation. Numerical results show that four-channel 200-GHz-spaced CSRZ signals at 40 Gbits/s can be converted into NRZ signals with high Q-factor and wide-range robustness. It is shown that our proposed FBG is robust to deviations of bandwidth and central wavelength detuning. Another important merit of this scheme is that the pattern effects are efficiently reduced owing to the well-designed spectra response.

An incentivized auction based group-selling approach for demand response management in V2G systems

Vehicle-to-Grid (V2G) system with efficient Demand Response Management (DRM) is critical to solve the problem of supplying electricity by utilizing surplus electricity available at EVs. An incentivilized DRM approach is studied to reduce the system cost and maintain the system stability. EVs are motivated with dynamic pricing determined by the group-selling based auction. In the proposed approach, a number of aggregators sit on the first level auction responsible to communicate with a group of EVs. EVs as bidders consider Quality of Energy (QoE) requirements and report interests and decisions on the bidding process coordinated by the associated aggregator. Auction winners are determined based on the bidding prices and the amount of electricity sold by the EV bidders. We investigate the impact of the proposed mechanism on the system performance with maximum feedback power constraints of aggregators. The designed mechanism is proven to have essential economic properties. Simulation results indicate the proposed mechanism can reduce the system cost and offer EVs significant incentives to participate in the V2G DRM operation.

A vállalatok árképzési gyakorlata a versenyképesség szolgálatában (The pricing practice of corporates and the competitiveness)

A marketing-szakirodalom szerint az ár az egyik legfontosabb marketingeszköz, és a vállalati versenyképesség értelmezésében is meghatározó szerepe van. A megfelelő árképzés kialakítása ugyanakkor összetett folyamat, amely önmagában is külön képességnek tekinthető, és kell befektetést igényel. A szerző az elemzés során így arra volt kíváncsi, hogy a vezető, azaz a versenyképes vállalatok árazási gyakorlata mutat-e eltéréseket, és, ha igen, melyek azok a területek, amelyek leginkább összefüggnek az eredményességükkel. A háromszáz hazai vállalatra kiterjedő kutatás során azt találta, hogy a vezető vállalatok valamelyest másképp tekintenek az ár szerepére és szignifikánsan magasabb árszínvonalon értékesítenek. Ez nagyobb mozgásteret enged számukra, a versenytársak árkihívásaira így könnyebben tudnak árakciókkal válaszolni. Árképzési céljaikban azonban kevésbé mutatkoznak különbségek, mert számukra is kihívást jelent a válság, és nekik is több szempontnak kell egyszerre megfelelniük. Az árak meghatározásánál azonban több tényezőt vesznek figyelembe és jobban támaszkodnak a vevőkről szerzett információkra. ______________ According to the marketing literature the price is one of the most important marketing tools and it plays a dominant role in the interpretation of corporate competitiveness, as well. The appropriate pricing, however, a complex process that can be regarded as a distinct capability and it requires sufficient investment itself. In this analysis the author enquired if the pricing practice of the leading, that is, the most competitive companies has a different profile, and if yes, which areas are associated with the success of them. Based on the survey of 300 domestic organisations he found that the leading companies consider the role of price in a slightly different way and they price their products or services significantly higherthan the others. This let them some space to manoeuvre and they can react with price promotions when the competitors challenge them with price activities. Regarding the pricing objectives the author couldn’t identify differences. The leading companies are also affected by the economic crisis and they have to match many expectations at the same time but they take more factors into consideration when they set their prices and more likely use customer information.

Intenzitásalapú modellezés és a mértékcsere (Intensity-based modeling and thje change of measure)

A dolgozatban a hitelderivatívák intenzitásalapú modellezésének néhány kérdését vizsgáljuk meg. Megmutatjuk, hogy alkalmas mértékcserével nemcsak a duplán sztochasztikus folyamatok, hanem tetszőleges intenzitással rendelkező pontfolyamat esetén is kiszámolható az összetett kár- és csődfolyamat eloszlásának Laplace-transzformáltja. _____ The paper addresses questions concerning the use of intensity based modeling in the pricing of credit derivatives. As the specification of the distribution of the lossprocess is a non-trivial exercise, the well-know technique for this task utilizes the inversion of the Laplace-transform. A popular choice for the model is the class of doubly stochastic processes given that their Laplace-transforms can be determined easily. Unfortunately these processes lack several key features supported by the empirical observations, e.g. they cannot replicate the self-exciting nature of defaults. The aim of the paper is to show that by using an appropriate change of measure the Laplace-transform can be calculated not only for a doubly stochastic process, but for an arbitrary point process with intensity as well. To support the application of the technique, we investigate the e®ect of the change of measure on the stochastic nature of the underlying process.