Sharif Digital Repository

Evaporation is one of the main parameters of the mass transfer from earth to the atmosphere, which annually transfers more than 65 billion cubic meters of water. Worldwide, evaporation consumes 25% of the energy input and plays a key role in restoring 60% of the precipitation to the atmosphere. Small changes in the water budget and evapotranspiration (ET) in arid and semi-arid areas can cause a large change in ecosystem health. Lake Urmia Basin has been taken into huge consideration due to steepest decline in lake level in the last three decades. Estimating evapotranspiration of this basin is important for the study of agricultural water consumption, hydrological modeling, water resources... 

With the growth of the number of online service providers and the need to innovate in these services, in this study, the processes and the journeys taken by visitors of a website that provides employment services and employment insurance has been analyzed. In this research, process mining techniques and predictive process monitoring were implemented. With the use of a supervised and unsupervised learning algorithm, it attempted to identify the customer journeys' output and the existing patterns that lead to the complaint. In the first step, the website event log is extracted. Afterward, by using frequency-based encoding methods, the journeys traveled by users were clustered based on the... 

In order to survive in today's business world, which is changing at a very fast pace, organizations can detect deviations even before they occur, quickly and with a high percentage of confidence, by analyzing their processes, in order to prevent disruptions in the processes. by monitoring the information systems that automatically execute business processes, it is possible to ensure the correct implementation of the existing processes. For this purpose, various techniques for monitoring business processes have been presented so that managers have a comprehensive and real view of how implement processes and be able to identify possible deviations in the future and try to fix them because the... 

In recent years, several studies have been conducted in the field of data mining techniques in the field of process mining with the aim of improving the performance of organizations. Predictive process monitoring is a data-driven approach that helps business managers to improve the status and conditions of their organization. In this approach, the event log, which includes a set of completed examples of a process, is received as input, and machine learning methods are used to predict the outcome and results of the organization's processes before the process is completed. This prediction can include the prediction of the final result, the next event, the time remaining until the completion of... 

The inventory costs constitute a significant portion of the supply chain costs. Therefore, choosing an optimal inventory policy for orders is of great importance. The aim of this research is to find the optimal inventory policy for a distribution center in a three-tier supply chain consisting of a manufacturer, a distribution center, and a retailer. This research simulates a supply chain in agent-based framework and optimizes it using reinforcement learning. The optimization KPI in this research is the mean daily cost of the supply chain. Finally, the result obtained from reinforcement learning is compared with the optimized result of AnyLogic and the mean daily cost in the model optimized... 

Business processes are an essential part of every business as they provide insights on how to optimize and make them more efficient. Predictive Business Process Monitoring has garnered significant attention in recent years due to its capability to forecast process outcomes and predict the next activity within an ongoing process. In the last few years, there have been works that focused on deep learning and its applications in predicting the next activity. Some research used Long Term Short Memory, while others used Convolutional Neural Networks. However, long term short term memory models have the constraint of relatively slow training, while Convolutional Neural Networks are fast but may... 

The analysis of customer journeys has gained significant attention due to the critical role of customer behavior data in enhancing business decision-making and formulating strategies for customer acquisition and retention. By segmenting customers based on their journey patterns, businesses can offer personalized recommendations, thereby improving customer engagement and loyalty. Additionally, predicting the next steps in a customer’s journey based on historical data allows for timely and appropriate interventions at various touchpoints. By understanding where customers are in their journey, businesses can provide targeted recommendations that increase the likelihood of converting potential... 

To maintain adaptability, businesses should anticipate changes in their environment. The commonly employed forecasting method within corporate circles is the bottom-up approach, which relies on historical data for projecting future trends. However, research suggests that this approach often falls short of accurately reflecting real-world events. This has led to the adoption of dynamic systems modeling, a technique grounded in the assumption of stable conditions. This method effectively replicates the system's current state, thereby assisting in predicting future behaviors over a longer timeframe. The dynamic systems modeling approach was employed in this study, underscoring the imperative... 

Providing quality hospital services depends on the efficient and correct implementation of processes. Therapeutic care processes are a set of activities that are carried out with the aim of diagnosing, treating and preventing any disease in order to improve and promote the patient's health. The purpose of this study is to use process mining techniques to discover and improve healthcare processes. The case study of this research is a psychiatric hospital in Shiraz. The approach implemented in this research consists of three main stages including data pre-processing, model discovery phase, and analysis phase. Three algorithms including Heuristic Miner, Inductive Miner, and ILP Miner were used... 

The foreign exchange market, commonly known as Forex, is one of the largest and most significant financial markets in the world, attracting the attention of numerous investors on a daily basis. One of the main challenges faced by traders in this market is the accurate prediction of currency prices. Although Forex market forecasting is highly popular, the inherent complexity of this market continues to make accurate prediction a persistent concern. In recent decades, remarkable advancements have occurred in the field of machine learning, particularly in deep learning. These developments have also influenced the Forex market, resulting in the publication of numerous research articles aimed at... 

Behran Mehr Peyma (BMP) is an elevator equipment producer and trader in Iran which was established in 2004. At first they are producing some regular parts of elevator and then during these years they are trying to improve their work and expand their business till they have the 15% market share in elevator market in Tehran.In this thesis I am trying to use the SWOT and PETS methods to show the exact situation of BMP comparing to the whole market considering the competitors.During this reduction in the market I suggest to BMP to change some policies and use some of its strength to attract some new customers, changing their brand name and find a relation to contribute in some tenders and... 

Medical needle interventions are a common technique for accessing tissue structures.In these procedures, needles are used, for example, to extract biopsy samples, brachytherapy, and to insert drugs. In TRUS guided prostate brachytherapy application, Physicians used ulterasound imaging to steer the needle and insert radioactive seeds into cancerous tumors to irradiate surrounding tissue over several months. Prostate rotation, deformation, and unavailability of imaging data during part of the insertion path result in misplaced seeds. To overcome these problems, in this research, we modeled the prostate, its membrane and the surrounding fatty tissue as linearly elastic homogenous material, and... 

This study has investigated the effects of different environmental conditions on the bond at the interface between two fiber reinforced polymer (FRP) layers. A total of 945 single lap splice coupons with three bond length were made using wet lay-up technic. There were used three unidirectional fabrics and one type of epoxy resin. A Uniaxial tensile test was performed on samples after 2, 4, 12, 20, 28, 36 and 48 weeks of exposure. Also series of test were conducted in order to determine the minimum lap splice length of single splice FRP samples. The experimental results indicated reduction of bond strength in glass specimens that was 17 % after 48 weeks of exposure while for same amount of... 

Deep learning, as a subdivision of machine learning, attempts to model high-level concepts by using a deep graph, consisting of several layers of linear and nonlinear transformations. Implementing these algorithms on hardware is a big challenge.¬This project offers a system in which various hardware methodologies can be used to implement deep learning algorithms side by side. The overall structure of the system consists of high-level programming interfaces for implementation and expression of machine learning algorithms by the user, which will be available as libraries in a high-level programming language such as Python, Ruby, and Julia. These interfaces allow the user to evaluate their... 

Trip distribution is the second step of the four-step travel demand modeling. Like other travel demand models, the most important objective of trip distribution models generation is forecasting the travel data of a year in the future. On the one hand, extensive changes in cities’ urban structures and people’s travel behavior during the years brings up the essential question of how temporally stable and transferable trip distribution models are? This question becomes even more important when the more complex structure of trip distribution models compared to models such as trip generation is considered. On the other hand, it is logical to assume that the consideration of the effects of urban... 

Articular cartilage has limited repair capability following traumatic injuries and current methods of treatment remain inefficient. Reconstructing cartilage provides a new way for cartilage repair and natural polymers are often used as scaffold because of their biocompatibility and biofunctionality. The goal of cartilage tissue engineering is to design a scaffold with proper pore structure and similar mechanical properties to the native tissue. In this study Porous scaffolds prepared from silk fibroin, chitosan and gelatin blends with varying ratio of silk fibroin and gelatin by freeze drying method were characterized for physicochemical, mechanical and biological properties. Among the...