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... 

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... 

Vulnerability of SRAM-based FPGAs to soft errors signals the importance of applying fault-tolerant methods in FPGAs used in safety-critical applications. Previous methods to protect SRAM-based FPGAs impose significant area and power overheads. Additionally, they suffer from susceptibility of configuration bits to Single Event-Multiple Upsets (SEMU). This thesis presents a Highly Available Fault-Tolerant Architecture (HAFTA) to protect SRAM-based FPGA designs against SEMUs in both configuration and user bits. In HAFTA, the entire design is duplicated and the main and replica flip-flops are compared at each clock cycle to detect any possible mismatch. To save the latest correct state of the... 

The fabrication of future electronic and optical devices will require advanced nanofabrication techniques that realize high spatial resolution and high precision in controlling size and position, and that are applicable to various materials. Near-field CVD (NF-CVD) was proposed to solve these problems with no need to perform nanolithography prcesses. NFCVD system has two major subsystems, first vacuum chamber and gas distribution system for delivering parent gases to the chamber and second, a nanopositiong system to keep the probe and the sample in the constant systems.In this dissertation we have set up a piezoelectric nanopositiong system and its driver modules. The positioning accuracy... 

In this study AZ91 alloy reinforced by SiC particles processed by semi-solid casting was produced by using electromagnetic stirrer. In order to prevent ignition and oxidation of the melted AZ91 alloy 1 Wt.% of calcium was added to the melt. In order to surface oxidation of SiC particles, they were heat treated in 1100 ᵒC for 2 hours before adding to the melt. Different methods of adding SiC particles to the melt were investigated. Particle distribution in the matrix was studied qualitatively and quantitatively using microscopic images and image analysis, respectively. It is shown that higher amount of reinforcement particle need to be added to the melt in multi-steps. Frequency versus... 

Helium, a valuable substance with unique properties, is widely used in various fields such as medicine, life sciences, electronic and military industries, and the industries which require low- temperature cooling. Driven by the increasing global demand for helium, research laboratories and industries are turning to small-scale refrigeration and liquefaction cycles. GM cryocoolers have found widespread applications in cryogenics due to its simplicity, high reliability and cost-effectiveness. The complexities of GM cryocooler performance pose significant challenges to achieving optimal efficiency and operation so developing a simplified model of the cycle is crucial. In this research, the... 

Pilot fatigue and increased cognitive load are primary contributors to fatal aviation accidents, especially in general aviation. However, pilots lack real-time, objective systems for monitoring their cognitive states. This dissertation introduces a cost-effective multimodal framework combining gaze tracking, control stick inputs, and Continuous Performance Test (CPT) scores to compute a cognitive performance stability index based on exceedance autocorrelation. Experiments were conducted in a single-engine Cessna simulator under IFR conditions with pilots of varying experience. Simulator data, gaze coordinates, control inputs, and CPT outputs were captured through automated software... 

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...