Assessment of Climate Change Impacts on Allocation of Shared Water Resources (Case Study: Lake Urmia Basin, Zarineh Rud)

, M.Sc. Thesis Sharif University of Technology Karimi, Fatemeh (Author) ; Abrishamchi, Ahmad (Supervisor)

Abstract

Nowadays, climate change is one of most important environmental challenges in all over the world. In addition to climate change, population growth, increase in water demand, which surpasses available resources so that the water system cannot meet the demands, and the subsequent growth in the development of water resources plans make watershed management become a challenging issue . In the last decade, due to significant reduction of precipitation, continuous increase in water development plans and utilization of too much water for agricultural and other uses, water inflow to the lake Urmia has reduced. Furthermore, Urmia lake have a strategic location which flows in three provinces of East...

The Impact of Corporate Governance on the Survival of the Organizations

, M.Sc. Thesis Sharif University of Technology Yadaei Amnab, Masoud (Author) ; Mashayekhi, Alinaghi (Supervisor)

Abstract

This study examines the impact of Corporate Governance on the survival of firms. The main goal in this research is to find the most important factors of Corporate Governance affecting the survival of a firm. Research method is qualitative. Survival is binary. It means whether a firm is alive or bankrupt. All samples used in this research are alive, but they are different in the extent they hope to be alive. So, first of all the criteria that estimate the hope of survival of a firm are defined using the literature of survival. In the next step, some firms are selected that are different in the extent they hope to survive. Next, these firms are compared in their quality of Corporate...

Bankruptcy Forecasting for Companies and Providing Counterfactual Scenarios to Change the Bankruptcy Class According to Financial Statement Data

, M.Sc. Thesis Sharif University of Technology Haji Hajikolaei, Maryam (Author) ; Akhavan Niaki, Taghi (Supervisor)

Abstract

Bankruptcy is an important issue in the economy that can have extensive financial and social consequences on individuals and society. Timely warning to managers and providing analysis may prevent bankruptcy. Many studies have been conducted on the application and implementation of machine learning techniques to predict bankruptcy. Many bankruptcy prediction models produce incomprehensible outputs for the user. Therefore, they are called black box algorithms. Implementation of advanced models inevitably requires interpretability for users to understand the result and trust. Since most machine learning methods are "black box", explainable AI, which aims to provide explanations to users, has...