Studies on Preparation, Characterization and Ammoxidation Functionality of Zirconium Phosphate-Supported V2O5 Catalysts

Zirconium pyrophosphate (ZrP₂O₇) was synthesized from zirconyl chloride and phosphoric acid. A series of ZrP₂O₇-supported V₂O₅ catalysts, with the oxide loading ranging from 2 to 8 wt.%, was prepared by wet impregnation method. These catalysts were characterized by various techniques like X-ray diffraction, BET surface area, pore size distribution, FT-IR spectroscopy, acidity measurements and X-ray photoelectron spectroscopy. Their catalytic functionality was evaluated in the ammoxidation of 2-methyl pyrazine (MP) to 2-cyano pyrazine (CP). The V₂O₅/ZrP₂O₇ catalysts are found to be highly active and selective. FT-IR profiles of used catalysts indicate the interaction of ammonia with vanadia. The physico-chemical properties of the catalysts are correlated with their activity and nitrile selectivity. IICT Communication No. 050602.     

Evaluating Web software reliability based on workload and failure data extracted from server logs

We characterize usage and problems for Web applications, evaluate their reliability, and examine the potential for reliability improvement. Based on the characteristics of Web applications and the overall Web environment, we classify Web problems and focus on the subset of source content problems. Using information about Web accesses, we derive various measurements that can characterize Web site workload at different levels of granularity and from different perspectives. These workload measurements, together with failure information extracted from recorded errors, are used to evaluate the operational reliability for source contents at a given Web site and the potential for reliability improvement. We applied this approach to the Web sites www.seas.smu.edu and www.kde.org. The results demonstrated the viability and effectiveness of our approach.     

Regularized least squares fuzzy support vector regression for financial time series forecasting

In this paper, we propose a novel approach, termed as regularized least squares fuzzy support vector regression, to handle financial time series forecasting. Two key problems in financial time series forecasting are noise and non-stationarity. Here, we assign a higher membership value to data samples that contain more relevant information, where relevance is related to recency in time. The approach requires only a single matrix inversion. For the linear case, the matrix order depends only on the dimension in which the data samples lie, and is independent of the number of samples. The efficacy of the proposed algorithm is demonstrated on financial datasets available in the public domain.     

Effect of P/Fe ratio on the structure and ammoxidation functionality of Fe-P-O catalysts

Bulk FePO₄ catalysts, with varying P/Fe atomic ratio in the range of 1–1.6, were prepared and characterized by XRD, FT-IR, TPR, Potentiometric titration, Laser Raman, TEM, XPS and TG/DTA techniques in order to study the influence of P/Fe atomic ratio on the nature and extent of the active phase formation. The data obtained from XRD and Laser Raman techniques suggested predominant formation of the quartz type iron phosphate at close to stoichiometric P/Fe ratio, but as the ratio increased beyond 1.4 a progressive transformation of monomeric phosphate into its polymeric form was observed. XPS spectra reflected the presence of iron in its 3+ state when P/Fe ≤ 1.2 and exists as Fe²⁺ and Fe³⁺ when P/Fe ≥ 1.4. The catalytic properties of these iron phosphates were studied in the vapor phase ammoxidation, taking 2-methylpyrazine (MP) to 2-cyanopyrazine (CP) as an example. The ammoxidation activity of the catalysts was found to be proportional to the extent of quartz phase formed which in turn was proportional to the redox property, as observed by the oxidation functionality of the catalysts in benzyl alcohol transformation. However, the selectivity to nitrile was found to be dependent on the acid strength of the catalysts.     

Rapid estimation and quantification of sucrose content in fruit juices using Fourier transform infrared–attenuated total reflectance (FTIR–ATR) spectroscopy

An uncomplicated and rapid procedure has been developed for the quantitative analysis of sucrose in fruit samples (grape, pineapple, mango) through attenuated total reflectance–Fourier transform infrared absorbance measurements (ATR–FTIR). FTIR analysis takes considerably reduced time compared to the other classical methods. To calibrate the method, we used firstly, different concentrations of pure sucrose (from 1 to 5 %) and registered their IR maximal wavenumbers and peak intensity. The spectral peak of sucrose for each sample lies between 1057 and 1061 cm^?1. DNS method was used to analyse the content of sucrose by using spectrophotometry. The wave length used for analysing is 540 nm. Also high performance liquid chromatography was used to analyse the sucrose content in the fruit juices. By comparing the retention time of sucrose standards and the sample juices, sucrose concentration was identified and quantified. The results of all three experiments/techniques support each other by justifying that the mango has the high content of sucrose followed by pineapple and grape.     

Discovering mappings in hierarchical data from multiple sources using the inherent structure

Unprecedented amounts of media data are publicly accessible. However, it is increasingly difficult to integrate relevant media from multiple and diverse sources for effective applications. The functioning of a multimodal integration system requires metadata, such as ontologies, that describe media resources and media components. Such metadata are generally application-dependent and this can cause difficulties when media needs to be shared across application domains. There is a need for a mechanism that can relate the common and uncommon terms and media components. In this paper, we develop an algorithm to mine and automatically discover mappings in hierarchical media data, metadata, and ontologies, using the structural information inherent in these types of data. We evaluate the performance of this algorithm for various parameters using both synthetic and real-world data collections and show that the structure-based mining of relationships provides high degrees of precision.     

Dynamic model for power systems with multiple FACTS controllers

Computer simulation and analysis of power systems are necessary for both planning and operation. This requires an appropriate mathematical model of the system that includes many inter-related linear/nonlinear differential and algebraic equations. Such mathematical model is also needed for the design of globally coordinated controllers to improve power system dynamic performance and stability. This paper presents a procedure for finding comprehensive dynamic models of power systems fitted with shunt and/or series connected FACTS controllers such as STATCOM, SSSC, and UPFC. In this procedure, individual components of a power system are modeled using appropriate frame of references. Then all related equations are transformed to a common network frame of reference and tied to each other through the Y-matrix of the transmission network. The procedure is tested on the Western System Coordinating Council (WSCC) test system including FACTS controllers by performing computer simulations of the system for three-phase short circuit faults. MATLAB/Simulink software package is used for the simulations.