Sharif Digital Repository

According to the rise of turnover and pace of trading, accelerating of analysis and making decision is unavoidable. Humans are unable to analyze big data quickly without behavioral biases so, using machines to analyze big data seems critical. Hence, financial markets tend to apply algorithmic trading in which some techniques like data mining and machine learning are notable. OLPS which sequentially allocates capital among a set of assets aiming to maximize the final return of investment in the long run, is the core problem in algorithmic trading. This article presents an online portfolio selection algorithm. The online portfolio selection sequentially selects a portfolio over a set of assets... 

The purpose of this study is to model the long-term effects of taxes on different aspects of private cars upon auto ownership and use, and thereby auto industries in producing more fit cars, so as to minimize auto emission. It involves used car market, different car demands and auto industry production. The study follows some previous studies in this area and tries to enhance the various aspects of the model by directing it toward a more real situation. In order to visualize the effects of the model, it has been applied on the case of Shiraz in 1378. It has been shown that the model was able to reduce air pollution and fuel consumption by 90% and 50%, respectively, as compared to the “Do... 

Ambient Intelligence is a new paradigm in information technology that creates environments able to detect and respond to users needs, actions, behaviors and feelings. In the presence of interaction conflicts, user trust plays an important role in accepting Ambient Intelligence environments for living, working, etc. Our main hypothesis is that higher conflict density results in a greater loss of trust in mixed-initiative Ambient Intelligence environments. In this thesis, we propose a comprehensive research method for measuring trust in Ambient Intelligence environments using both crowdsourcing and university surveys. We conduct both web-based experiments and physical experiments to gather... 

The Darcy’ law is valid for low velocity or low Reynolds number where merely viscous force is responsible for pressure loss in the porous media. At higher velocity, because of inertial forces and turbulency, the pressure loss would be higher than Darcy’ law estimates; therefore at these flow regimes the Darcy’ law is no longer valid. Hence, consideration of Non-Darcy flow effect is necessary to sufficiently model high gas velocity effects. The velocity is high in gas reservoirs especially those ones that are considered for underground gas storage. In this study, the effects of Non-Darcy flow on several parameters such as; estimation of differential pressure, flowing bottom hole pressure,... 

Author identification using statistical methods is a branch of authorship attribution which is one of important problems in natural language processing. Using different statistical methods, an anonymous text is attributed to an author. One of the primary parts of the task is to choose the appropriate stylistic features of the text in order to study the significances of style. These features must be quantitatively studied and could be extracted in lexical level, character level, and syntactic or semantic levels. The next step is text classification in which different machine learning methods such as decision tree, Artificial Neural Networks, Naïve Bayes and other methods could be used.... 

Air pollution is a prevalent and pressing issue in Tehran, with significant impacts on both the environment and human health. this study uses statistical techniques, such as Pearson correlation, to determine the direction of influence of meteorological parameters on air pollutant concentrations, and Convergent Cross Mapping to quantify the causal relationship between meteorological parameters and ambient air pollutant concentrations, as well as feedback effects. Additionally, the research delves into the correlation between consumption of fossil fuels and air pollutants, as well as the relationship between lung cancer incidence and mortality by histological subtype and long-term exposure to... 

Air pollution in major cities has been a concern for over half a century, but its impact on public health has grown significantly in recent years, causing severe physical, mental, and financial harm. This project aims to propose effective policies to mitigate air pollution by focusing on the transportation sector. Transportation demand is analyzed through four scenarios, each addressing changes in public transportation usage, the promotion of cycling and walking culture, the penetration of digital solutions, and flexible working hours. The project, using the Huvaal model, forecasts transportation demand in 2050 under various population and climate conditions, based on artificial population...