Sharif Digital Repository

The application of biocatalysts in organic reactions refers to the use of enzymes, purified or crude, to increase the reaction rate. The usage of biocatalysts in organic reactions have many advantages, including biocompatibility, ease of separation, high yield, reusability without losing activity, high selectivity, and the use of water as the solvent. Furthermore, the carbon–carbon bond formation is one of the most important reactions in the synthesis of organic compounds, drugs, and biomolecules. Using enzymes in organic reactions can provide insightful information about the enzymes catalytic activities and paves the way for systematic investigation of their mechanisms. The enzymes... 

In this thesis, we analyze and compare switching and CPSP cryptography systems. CPSP is a dynamic system which can act as synchronized or self-synchronized stream cipher under specific conditions. To do the comparison, first we have a brief review of cryptography fundamentals like stream cipher systems, synchronized stream ciphers, and self-synchronized ones. Then, we consider chaos systems in general form and then we present their role in cryptography systems, and in continue by introducing switching cryptography systems and also CPSP cryptography systems, and analyzing their relation with self-synchronized stream ciphers, we do our statistical tests on them  

In recent years, the emergence of semi-supervised learning methods has broadened the scope of machine learning, especially for pattern classification. Besides obviating the need for experts to label the data, efficient use of unlabeled data causes a significant improvement in supervised learning methods in many applications. With the advent of statistical learning theory in the late 80's, and the emergence of the concept of regularization, kernel learning has always been in deep concentration. In recent years, semi-supervised kernel learning, which is a combination of the two above-mentioned viewpoints, has been considered greatly.
Large number of dimensions of the input data along with... 

Portfolio generating functions are positive twice continuously differentiable functions of the common or ranked market weights. The return on such portfolios related to the market with a stochastic differential equation that has two components: the logarithmic change in the value of the generating function, and a drift process that is of bounded variation. The goal of this study is to generalized portfolio generating functions theorem for ’ functions, in order to cover some important functions in economic such as Gini coefficients  

In this thesis we study one of the applications of algebraic topology to computer science and define some tools to analyze concurrent programs. For this purpose a geometric space is corresponded to every concurrent program and a partial order is considered on this space, so every path on it corresponds to an execution of the program. Some of these paths which are dihomotop (homotop in partial ordered spaces) with each other induce the same execution of the program. By defining “Fundamental Category” in which objects are points of the space and morphisms are dihomotopy classes, the space that should be analyzed shrinks to a smaller one. By defining component category in the next step, without... 

In this thesis we study three versions of K−theory. The most well-known vesrsion is topological K−theory, a generalization of Grothendieck works on algebraic varieties to the topological setting by Atyiah and Hirzebruch. Since its birth it has been an indespensible tool in topology,differential geometry and index theory. In the early 1970s C∗−algebraic version of K−theory introduced through associating two abelian groups,K0(A)and K1(A)to a C∗−algebra like A. These functors proved to be a powerful machine, making it possible to calculate the K−theory of a great many C∗−algebras. At last,algebraic K−theory is dealig with linear algebra over a ring R by associating it, a sequence of abelian... 

In this research, an optical processing method for DNA classification is presented in order to overcome the problems in the previous methods. With improving in the operational capacity of the sequencing process, which has increased the number of genomes, comparing sequences with a complete database of genomes is a serious challenge to computational methods. Most current classification programs suffer from either slow classification speeds, large memory requirements, or both. To achieve high speed and accuracy at the same time, we suggest using optical processing methods. The performance of electronic processing-based computing, especially in the case of large data processing, is usually... 

In this essay, by putting in the framework of linear-quadratic optimal control (LQ),we study and solve the mean-variance portfolio selection problem. Two models will be studied in our work; in one we assume that the price process satisfies a diffusion stochastic differential equation, while in the second model, we assume it to satisfy a jump-diffusion stochastic differential equation. In both models, a formula for the efficient frontier is obtained. This essay is mainly obtained from the works of the following articles and books:
1)X.Y. Zhou and D. Li, Continuous-Time Mean-Variance Portfolio Selection:A Stochastic LQ Framework. Applied Mathematics and Optimization. 42(2000),... 

Using customer relationship management systems has led to the formation of databases containing businesses customer information. Increased competition in the markets, limited resources and high costs of attracting new customers compared to retaining existing customers have made customer retention an inevitable subject for business owners. Meanwhile, insurance companies, which due to their long history have suitable databases of product information and their customers, have resorted to using their databases to manage the relationship with their customers. In this research, while predicting customers churn in health insurance, as one of the most widely used products of domestic insurance... 

Crude oil and petroleum products at the time of extraction, production and transportation cause serious contaminations in soil, water and environment. Biological methods have shown a promising effect for the cleanup of these hydrocarbon pollutants. Bioremediation employs the metabolic activity of microorganisms capable of using oil as their energy and carbon source. Biological methods are also less expensive than other cleanup technologies such as incineration and landfill. Large number of microbial stains have been discovered in nature, capable to degrade oil and petroleum products. Biological cleaning of oil contamination by microorganisms occurs naturally in the environment. It has been... 

Hybrid mobile applications combine the features of Web technologies and native mobile apps. Like Web applications, they are implemented in portable, platform independent languages such as HTML and JavaScript. Like native apps, they have direct access to local device resources. In these programs, web contents are loaded into a web component, called WebView, which can render HTML5 pages and execute JavaScript code. In order for the web content to access the system resources, which are isolated from the content inside Web-View due to its sandbox, bridges need to be built between JavaScript and the native code. developers usually use third party plug-ins for native side of application. hybrid... 

One of the most crucial aspects of financial risk management is risk measurement. Advanced AI-based solutions can provide the proper tools for assessing global markets, given the complexity of the global economy and the violation of typical modeling assumptions. A new strategy for quantifying stock portfolio risk based on one of the machine learning models known as Variational Autoencoders is provided in this dissertation. The suggested method is a generative model that can learn the stocks' dependency structure without relying on assumptions about stock return covariance and produce various market scenarios using cross-sectional stock return data with a higher signal-to-noise ratio. We...