Sharif Digital Repository

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... 

Interpreting data of infrastructures monitored to detect damage of a structural is one of the most challenging issues of structural health monitoring (SHM). Especially, when environmental factors such as temperature, wind and humidity affect the data and the situation become more complicated. In this study, two methods of analysis free model of moving principal components analysis (MPCA) and robust regression analysis (RRA) have recently been considered for monitoring infrastructures compared with a variety of methods of data interpretation and results are presented. In this study, the performance of different ways in different loading conditions and arrangement of sensors have been... 

The vital and influential role of railways in the socio-economic growth and development of countries, along with the high costs of rehabilitation and maintenance of its infrastructure, has made the existence of a comprehensive maintenance management system a necessity to not only elevate the level of service, reliability, and safety but also to minimize such repair costs. Accurate modeling of track deterioration is essential as one of the components of such systems.In this study, a large database from outputs of EM120, track recording machine, was provided for the years 2009 to 2018 and for all 18 railway zones of Iranian Railways (approximately 13,000 km railway track and 80 GB of data).... 

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... 

This research is focused on fabrication of TiO2 layers by electrophoretic deposition (EPD) for application as photoanode in Dye Sensitized Solar Cell (DSC). DSCs are third generation of solar cells, also known as the Grätzel cell, after its inventor Michael Grätzel. A DSC is composed of a porous layer of wide band gap semiconductor such as TiO2 and ZnO, covered with a molecular dye that absorbs sunlight, and a counter electrode contacted by a liquid redox electrolyte. Dye Sensitized semiconductor (photoanode) has important role in conversion of photon to electricity. To achieve higher efficiency, preparation of photoanode with high surface area resulted to enough dye adsorption is necessary.... 

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...