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... 

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... 

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... 

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... 

This thesis abstract addresses the use of process mining techniques when event data is stored at varying levels of granularity. While most techniques assume that events have the same level of granularity, real data is often stored differently. Pre-processing techniques allow for appropriate summarization of the data, which simplifies the output while retaining important process details. The goal is to ensure an interpretable output for stakeholders and different business teams without losing critical process points. However, adding new data as a feature to the dataset can be expensive, and at times, infeasible. Therefore, existing data is the only solution. To overcome this challenge, this... 

In the competitive world of software development, IT product development teams face numerous challenges and issues within business processes. In recent years, the combination of process mining and machine learning algorithms to optimize software development processes has gained attention. However, there is still a lack of a comprehensive model for identifying and conducting root-cause analysis of problems and providing solutions based on them in agile software development systems. The aim of this research is to find a solution for identifying and addressing issues in the software development process by modifying the change request workflow and examining various aspects of incidents. To... 

Dynamic portfolio optimization is one of the prominent problems in financial mathematics, for which numerous theories have been proposed to solve it. One of the solutions to this problem is the use of reinforcement learning. The main challenge with this method is that most reinforcement learning algorithms require a large amount of data, and therefore, the necessary data is often obtained not from the real world, but through simulations by estimating the parameters of a model. However, the approximation error of the parameters can propagate through the final solution, leading to inaccurate results. One approach to addressing this issue is the use of robust Markov processes and robust... 

Worldwide interoperability for Microwave Access (WiMAX) is one of the most dominant cell-based broadband wireless metropolitan access technologies. Packet scheduling algorithm specifies the packet transmission order. In WiMAX standard, packet scheduling algorithm is not defined and its efficient design is left for developers and researchers. The existing researches in the scope of uplink packet scheduling, which is the most challenging packet scheduling scheme, consider only one cell. However the uplink available resources might not be enough when there are many packets that should be scheduled. To solve this problem, we propose an algorithm that uses the load balancing mechanisms that are... 

Entrance of air to close water conduits occurs in many ways. This phenomenon makes displeasing effects on water transport structures. Two-phase flows in closed conduits are studied experimentally, numerically and theoretically. Even after decades, due to the complexity of the subject, these studies still require development and reformation. Numerical and theoretical two-phase models are often limited to a special regime of flow."Volume Of Fluid"(VOF) is a model for non-mixing two-phase flows. "Fluent" software uses this model in this field of flows. Volume of fluid is used successfully in some problems like dam break or rising bubbles. Main disadvantage of this model is distribution of the... 

In this project, polymer nanocomposites containing graphene oxide were prepared and used for adsorption of several cationic and anionic dyes. In most cases, these nanocomposites were prepared as three-dimentional polymer networks which contain graphene oxide. Nanocomposites with direct grafting of polymer chains onto the surface of graphene oxide were also prepared. Graphene oxide is an oxidized carbonaceous material with unique properties. This material has high surface area, good mechanical strength and various functional groups. Polymeric compounds with different functional groups, structures and properties can be prepared and used. By preparing composites of graphene oxide and polymers,... 

Common fracture treatments include open reduction and intramedullary nailing technology. However, these methods have disadvantages such as intraoperative X-ray radiation, delayed union or nonunion and postoperative rotation. Robots provide a novel solution to the aforementioned problems while having new challenges. The robotic system used in the study by providing more precise motion and exerting higher amount of forces makes the operation procedure more straightforward. In a normal operation 300-400 N of extension force would be needed which is fully provided by the surgen which leads to physical his/her (khastegi), by using the robotic system however, this force is simply provided without... 

Trac classication in today’s high-bandwidth networks is challenging, resource consuming, and inaccurate due to the high volume, velocity, and variety aracteristics of the network trac. Trac aracterization and Application identication teniques are widely addressed in the current literature. Due to the massive volume and streaming data in recent years, stream algorithms have been considered by many researers in dierent areas. Online application detection is an issue that has been addressed less frequently in literature. In this thesis, we investigate the performance of 10 dierent stream classication algorithms along with traditional classication algorithms. To generate a robust classier for... 

The purpose of the present study is to plan an industrial system, over a period of 10 years, so that over time, while supplying the required demand, to optimal resource utilization with regard to material reuse and recovery flows of losses as well as the use of renewable resources move to implement the concept of a circular economy. One of the main incentives for the transition to a circular economy is carbon tax policy, which has been taken into account. The results of the decision-making model based on cost and flow constraints indicate that the use of carbon dioxide as a by-product of Pars Petrochemical Extraction Unit in order to produce urea in Pardis petrochemical industry in addition... 

In the cloud computing environment, although many processing resources for application software with the volume of calculations The above is available, but it may not work for software that is sensitive to latency. In fact, due to the large distance between users and end devices to cloud servers, sending requests And the required data to the data centers requires a high bandwidth and therefore the data transfer time is also significant. In addition, cloud computing in platforms such as cloud-based IoT architecture faces other challenges such as connectivity, resource limitations of end devices, and security. In order to solve the challenges in the cloud computing environment and respond to...