On average control generating families for singularly perturbed optimal control problems with long run average optimality criteria

The paper aims at the development of tools for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems with long run average optimality criteria. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional (ID) linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with a numerical example.Comment: 36 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1309.373

Essays On The Economics Of International Remittances And Migration

Existing literature on international remittances recognizes the increasing importance of these transfers on economic development as well as their effect on the reduction of poverty in developing countries. However, the studies on this topic are still divided over the long-term effects of remittances, identifying instances when remittances have either positive or negative results. Probably the most important oversight of the literature on international remittances and migration is the lack of the regional dimension in the analysis, which is the focus of this dissertation. In the first chapter I propose a novel spatial dataset of remittances and spending from a nationally representative survey that I carried out in the Republic of Moldova in the first half of 2013. Based on these data, I build an empirical model that estimates average budget shares at the household level using the two-stage linear regression approach. The impact of remittances is evaluated by comparing marginal spending for households receiving remittances with their counterfactuals. In this essay, I perform the analysis at the national level and control effectively for the selection bias using a two-stage multinomial logit regression approach. The results at the national level are mixed and mostly appear to have negative implications on economic development of the country. The second chapter continues the analysis in the first essay. In this chapter, I analyze remittance flows with a model that estimates regional (urban and rural) budget shares of consumption and investment expenditure categories for rural and urban households. This model is an innovation in the literature on remittances because it provides a technique for estimating regional spending and evaluating the impact of remittances based on the location of spending, rather than the location of the household. The fundamental finding of the essay is that remittances influence the flight of productive capital out of rural areas into urban regions (a pattern similar to the crowding-out effect of the “Dutch Disease”). Thus, although rural regions have the highest frequency of households receiving international remittances, these transfers change the regional spending propensities of rural households, leading them to spend more on investment categories located in urban centers. The third chapter builds upon the results of the second essay. This study offers a new approach of analyzing the effect of international migration (and remittances, implicitly) on regional economic development by investigating their impact on the dynamics of local human capital concentration. It is a departure from the classic analysis of the effect of remittances/migration on educational attainment (school enrollment) or the links between international migration and brain drain. Instead, it uses probit and conditional logit estimation techniques to evaluate the effect of money flowing from international migration on the likelihood that left-behind household members with tertiary education migrate domestically, attracted by employment opportunities in urban areas. The regional choice model is grounded in random utility maximization theory, which also adds more clarity about the urban job choice alternatives in Moldova. The main findings of the paper support the hypothesis that international migration/remittances lead to an increase in the preference for urban jobs of the “left-behind” tertiary-educated household members, especially for individuals with rural origins located outside the “primate city” region

Reversible Logic Circuit Based Twiddle Factor Generation

An efficient hardware implementation of FFT algorithm become essential one in signal analysis domain, more specifically the twiddle factor calculation in FFT computation plays important role in the speed and efficiency of the complete process. World of computation needs the fast and efficient tools to match the need of present scenario, even though there are many methods proposed the Reversible Logic design became the promising area for improvement of speed and reduces the power consumption to a larger extent. In this paper a reversible logic based implementation of twiddle factor generation is proposed

A proposed data fusion architecture for micro-zone analysis and data mining

Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presents an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture

Solubility of mixtures containing soybean oil, ionic liquid and methanol

This paper presents data on mutual solubility of the binary (soybean oil + ionic liquid) and ternary (soybean oil + methanol + ionic liquid) systems, where ionic liquid stands for 1-butyl-3-methylimidazolium thiocyanate [C4MIM][SCN] or 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide [C4MIM][NTf2] or 1-butyl-3-methylimidazolium dicyanamide [C4MIM][DCA] or 1-butyl-3-methylimidazolium hexafluorophosphate [C4MIM][PF6] or 1-butyl-3-methyl imida zolium hydrogensulfate [C4MIM] [HSO4] or 1-decyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide [C10MIM][NTf2] or methyltrioctylammonium bis(trifluoromethylsulfonyl)imide [ALIQUAT][NTf2] or methyltrioctylammonium chloride [ALIQUAT][Cl]. Solubilities were determined by the cloud point titration method in the temperature range of 298 K to 343 K. Obtained results suggest that imidazolium based ionic liquids exhibit lower solubility in soybean oil than ionic liquids with the aliquat cation. Thus, aliquat based ionic liquids are good candidate to be used as co-solvents for biphasic (methanol + soybean oil) mixture

Can non typical traditional forms of sacral space serve as a guide in the development of new forms of religious architecture in Serbian Orthodox Church?

[Resumen] Este artículo presenta las posibilidades de desarrollo de nuevas formas de arquitectura religiosa en la Iglesia Ortodoxa Serbia, sobre la base de ciertas tradiciones. La situación actual en este ámbito se analiza con especial énfasis en los edificios y espacios religiosos atípicos. Los autores muestran que la dominación del tradicionalismo en la expresión arquitectónica no está basada en restricciones canónicas, sino el resultado del esfuerzo de establecer la continuidad interrumpida mediante la imitacion de formas de épocas anteriores. La libertad de creación arquitectónica en este campo se justifica observando con la variedad de las formas existentes a través de la historia, entre las cuales los zapis son particularmente interesantes.[Abstract] This paper presents the possibilities of the development of new forms of religious architecture in Serbian Orthodox Church, on the basis of certain traditions. Current situation in this field is analyzed with special emphasis on non-typical religious buildings and spaces. The authors show that the domination of traditionalism in architectural expression is not based on the canonical restrictions, but rather the result of striving to establish the interrupted continuity by replicating forms from previous époques. Freedom of architectural creation in this field is strongly supported with the variety of forms existing through history of which zapis is particularly interesting

An Adversarial Approach for Explainable AI in Intrusion Detection Systems

Despite the growing popularity of modern machine learning techniques (e.g. Deep Neural Networks) in cyber-security applications, most of these models are perceived as a black-box for the user. Adversarial machine learning offers an approach to increase our understanding of these models. In this paper we present an approach to generate explanations for incorrect classifications made by data-driven Intrusion Detection Systems (IDSs). An adversarial approach is used to find the minimum modifications (of the input features) required to correctly classify a given set of misclassified samples. The magnitude of such modifications is used to visualize the most relevant features that explain the reason for the misclassification. The presented methodology generated satisfactory explanations that describe the reasoning behind the mis-classifications, with descriptions that match expert knowledge. The advantages of the presented methodology are: 1) applicable to any classifier with defined gradients. 2) does not require any modification of the classifier model. 3) can be extended to perform further diagnosis (e.g. vulnerability assessment) and gain further understanding of the system. Experimental evaluation was conducted on the NSL-KDD99 benchmark dataset using Linear and Multilayer perceptron classifiers. The results are shown using intuitive visualizations in order to improve the interpretability of the results