Catalytic properties and electronic structure of copper ions in Cu-ZSM-5

The effect of ion exchange conditions, such as Si/Al ratio, precursor copper salt, pH and concentration of the solution, on the catalytic activity in SCR of NO by propane and on the electronic state of copper ions in Cu-ZSM-5 has been studied. The NO conversion in NO SCR by C₃H₈ has been found to reach a maximum value at Cu/Al ratio about 0.37–0.4 and remain constant at higher Cu/Al.

ESR and UV–vis DR spectroscopy have been used to elucidate stabilization conditions of copper ions in Cu-ZSM-5 zeolites as isolated Cu²⁺ ions, chain copper oxide structures and square-plain oxide clusters. The ability of copper ions for reduction and reoxidation in the chain structures may be responsible for the catalytic activity of Cu-ZSM-5. These transformations of copper ions are accompanied by the observation of intervalence transitions Cu²⁺–Cu⁺ and CTLM of the chain structures in the UV–vis spectra.     

Exponential Stability of Interval Dynamical Systems with Quadratic Nonlinearity

This article proposes an approach for investigating the exponential stability of a nonlinear interval dynamical system with the nonlinearity of a quadratic type on the basis of the Lyapunov’s direct method. It also constructs an inner estimate of the attraction domain to the origin for the system under consideration.     

Catalytic cracking in presence of an aromatic addition

Fluidized bed catalytic cracking of vacuum gas oil fractions in the presence of extract from phenol purification of heavy lubricating oil fraction as an aromatic addition was investigated. Results show that, at the optimum concentration of the addition, coke formation on the catalyst decreases by 50 to 70% while the content of olefinic hydrocarbons in gasoline decreases, with a corresponding increase in the content of paraffin/naphthene hydrocarbons. The yield of gasoline increases, while its octane number increases by about two units.     

Coercivity and domain structure of nanograined Fe–C alloys after high-pressure torsion

The microstructure and magnetic properties of binary hypo- and hyper-eutectoid Fe–C alloys were studied. The investigations have been carried out on the samples in the as-cast state, after a long annealing at 725 °C and on the specimens after the high-pressure torsion (HPT). The deformation was carried out at the ambient temperature and the pressure of 5 GPa. The grain size after HPT is in the nanometer range. Long annealing leads to a drastic decrease of the coercivity in comparison with the as-cast alloys. In all alloys the coercivity H _c increases with increasing carbon content. The distance L between pinning points for domain walls decreases with increasing carbon content. Increase of the coercivity and decrease of L are more pronounced below the eutectoid concentration. The coercivity of the nanostructured samples is higher than that of the as-cast alloys. Due to the pinning of domain walls by the cementite particles, the hysteresis loop in the coarse-grained alloys both in as-cast and annealed states has a narrowing near the zero magnetization.     

Interactive exploration of data traffic with Hierarchical Network Maps

Network communication has become indispensable in business, education and government. With the pervasive role of the Internet as a means of sharing information across networks, its misuse for destructive purposes, such as spreading malicious code, compromising remote hosts, or damaging data through unauthorized access, has grown immensely in the recent years. The classical way of monitoring the operation of large network systems is by analyzing the system logs for detecting anomalies. In this work, we introduce hierarchical network map, an interactive visualization technique for gaining a deeper insight into network flow behavior by means of user-driven visual exploration. Our approach is meant as an enhancement to conventional analysis methods based on statistics or machine learning. We use multidimensional modeling combined with position and display awareness to view source and target data of the hosts in a hierarchical fashion with the ability to interactively change the level of aggregation or apply filtering. The interdisciplinary approach integrating data warehouse technology, information visualization and decision support brings about the benefit of efficiently collecting the input data and aggregating over very large data sets, visualizing the results and providing interactivity to facilitate analytical reasoning     

Asymptotic Stability of Interval Time-Delay Systems

In this paper we consider the asymptotic stability of linear interval time-delay systems on the base of using Lyapunov's direct method and methods of interval analysis. A sufficient condition of asymptotic stability is obtained using the concept of Lyapunov-Krasovsky functional.     

Optical–microphysical properties of smoke haze from Siberian forest fires in summer 2012

A comprehensive experiment on the study of dynamics of optical and microphysical characteristics of submicron aerosols in the near-ground air layer was carried out in June–August of 2012 under conditions of extremely strong smoke haze originating from vast forest fires in Siberia. Variations of the spectral angular scattering coefficients and the degree of linear polarization in the visible wavelength range are studied, as well as the mass concentrations of dry fractions of aerosol and black carbon, relative content of black carbon (BC fraction), single scattering albedo, particle size distribution function, complex refractive index of the particulate matter, and parameter of condensation activity of aerosol. Peculiarities of differences between optical and microphysical characteristics of near-ground aerosol in smoke haze and under smokeless conditions are revealed. This study is important for validation of results of remote sensing of the composition of smoke haze and background atmosphere obtained from satellite data and sun photometric measurements at the Aerosol Robotic Network (AERONET).     

Particle Swarm Optimization and Pure Adaptive Search in Finish Goods’ Inventory Management

Abstract

Inventory management deals with a tradeoff between the benefits of keeping stocks of goods that allows fulfillment of the customer’s demand, and the cost of carrying inventory. Inventory control techniques are very important components and the most organizations can substantially reduce their costs associated with the flow of materials. This paper presents new inventory management model based on particle swarm optimization and pure adaptive search global optimization algorithm in production-inventory system. The proposed model is focusing on planned level of demand for finished goods, production and raw materials cost, production capacity as the norm, change of the production cost and inventory capital cost, all of which are typical factors in automobile manufacture industry. The model determines different factors such as the minimizing inventory quantity, minimizing inventory value, and minimizing production cost based on demand for production items. The model is tested with original real-world dataset obtained from the automotive company Lear from US and its factory in Novi Sad, Serbia.     

An approach to efficient business intelligent system for financial prediction

A concept of business intelligent system for financial prediction is considered in this paper. It provides data needed for fast, precise and good business decision support to all levels of management. The aim of the project is the development of a new online analytical processing oriented on case-based reasoning (CBR) where a previous experience for every new problem is taken into account. Methodological aspects have been tested in practice as a part of the management information system development project of “Novi Sad Fair”. A case study of an improved application of CBR in prediction of future payments is discussed in the paper. This paper is originally presented at The International Conference on Hybrid Information Technology 2006, at the special session on “Intelligent Information Systems for Financial Engineering”, November 2006 in Cheju Island, Korea.     

Psychological capital and self‐reported employee creativity: The moderating role of supervisor support and job characteristics

Although the positive effect of psychological capital (PsyCap) on employee performance is well documented, the conditions under which PsyCap exerts the most influence on creativity warrant further research. Complementing and extending prior studies, we theorize and examine how two critical contextual factors (supervisor support for creativity [SSC] and job characteristics) effectively activate PsyCap associated with self‐reported employee creativity. Drawing on an interactional perspective, we use trait activation theory to examine the moderating effects of SSC and job characteristics on the relationship between PsyCap and self‐reported employee creativity. Through rigorous hypotheses testing (N = 356 individuals from multiple industries in Chinese firms), our results demonstrate that both SSC and job characteristics positively moderate the PsyCap–creativity relationship. Additional analyses reveal that PsyCap is most effective at enhancing creativity when both SSC and job characteristics are high. Implications of these findings for theory, future research and practice are discussed.