Sharif Digital Repository

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 research focuses on examining and improving healthcare systems, particularly during crises and pandemics. Following disasters such as natural calamities and pandemics like COVID-19, healthcare systems face significant challenges due to the increased demand for medical services, creating a substantial threat to the population in the affected regions. This study emphasizes the importance of utilizing modern technologies such as the Internet of Things (IoT) and telemedicine systems in alleviating the pressure on healthcare systems. A combined approach of prediction and multi-objective optimization based on simulation is proposed in this study to improve resource allocation and demand... 

Deviations in business processes consistently impose significant financial and temporal costs on business owners and can lead to decreased customer satisfaction with organizations. Therefore, timely identification of deviations is a crucial and significant issue for business process managers. While extensive research has been conducted on the detection of antecedent deviations, predicting deviations before they occur—which could facilitate preemptive actions to prevent these deviations—has received less attention. In this context, the aim of this study is to predict two types of process deviations—temporal deviations and Rework deviations—using machine learning and deep learning algorithms,... 

In this thesis, we provide a comprehensive overview of the efforts made towards achieving the goals of Hilbert’s program, and evaluate how successful They are. We begin by discussing Gödel’s incompleteness theorems, and then as a first attempt we present a brief presentation of Gentzen’s consistency theorem. Subsequently, various research fields that branched out from these initial efforts are explored, encompassing the application of the Omega-Rule, reverse mathematics, and self-verifying systems. Furthermore, we present the concept of “Almost Finitistic Consistency” as an alternative approach within Hilbert’s program. In conclusion, a thorough assessment of the success of Hilbert’s program... 

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... 

Question answering systems are systems which get a question in natural language as input and present an explicit, appropriate answer to the question. One of the major components of automatic question answering systems is question processing component in which the input question is analyzed. The main goal of question processing phase is to determine the answer type through question classification. Rule-based, machine learning-based and hybrid approaches have been used in order to develop question classifiers among which machine learning-based ones have outperformed the others. This study’s main goal is to develop a question classifier for Persian open domain question answering systems.... 

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... 

Digital video is one of the biggest part of digital data. The first step of digital video analytics is shot boundary detection. We used overlapped partitioning beside color histogram in uncompressed data and macroblock type prediction in compressed data as feature and supervised classifiers for decision making. Tests on TRECVID 2006 shows 8.9% improvement of F-measure in uncompressed video and 5.3% in h.264 bitstream. Supplementary test is done on IRIB dataset which shows 5.7% improvement of F-measure in uncompressed and 3.2% in H.264. H.264 based algorithm is almost 7 times faster in comparison to the algorithm that includes decoding  

Due to the increasing spread of metal industries and the need for raw material as feed for electric furnaces in order to produce cast iron and steel, as well as scrap deficiency and rising prices, the use of sponge iron as a substitute for scrap was considered in this project Therefore, in order to achieve the chemical analysis of the sorel ingot that is special for spherical graphite cast iron production with low manganese and chromium content, the direct reduction process was carried out using tunnel kiln method on low-manganese iron ore concentrate.After the investigation on direct reduction parameters including the saggers and coal grading,the produced sponge iron has melted in... 

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... 

Fuel system is one of the most important parts of pulse detonation engine which has the responsibility of fuel, oxidizer and also purge gas in the different operational frequencies of engine. Although pulse detonation engines are sort of air breathing engines and purge gas and oxidizer one in the same unit in their structure, due to existence idea in the pulse detonation rocket engines coverage of functional condition, fuel, oxidizer and purge gas, will study it in three different structures.
In this study purpose is improvement of the pulse detonation engine of Sharif University which will provide as the possibility of safe functional condition and high operational frequency in... 

Auction is one of the most important and oldest institutions in economics, enabling resource allocation and trade of goods in the economy. Investigating the effects of changes in reservation price in auctions is an important question in auction theory research. In this study, focusing on a policy implemented by Yektanet, which involved altering the reservation price in auctions for advertising slots, we assessed its impact on advertiser costs. The implemented policy led to the activation of two distinct mechanisms, resulting in conflicting effects on the company's revenue. The first mechanism involved an increase in bid and intensified competition for ad placements on average, while the... 

Epistemic logic gets its start with the recognition of the systematic properties of epistemic concepts. These properties make epistemic concepts amenable for formal study, and become our tools to present logical models for them.“Certainty” is one of these epistemic concepts for which no comprehensive logical model has been presented so far.
Among the logical models that have been presented for “Certainty”, there are two main models which are more comprehensive than the others and all the other models may be extendable to one of them. In this thesis, these two main logical models that have been proposed for the concept of certainty are introduced and described from a philosophical... 

There are a lot of methods for the settlement of the reserve power market which can ultimately lead to a pattern of consumption and generation for each of the participants of the power market. After this step, however, justified and logical methods should be utilized for paying the reserving costs to the participants as in a long-term it can optimize the economic conditions of the market which can result in getting more realistic bidding from the participants. The current methods used for paying the reserving costs are mostly locational marginal prices and pay-as bid approach. By the same token, for receiving the reserving costs from the customers, some consider the desired reliability level... 

Recent advances in storage and processing, have provided the ability of automatic gathering of information which in turn leads to fast and contineous flow of data. The data which are produced and stored in this way, are named data streams. data streams have many applications such as processing financial transactions, the recorded data of various sensors or the collected data by web sevices. Data streams are produced with high speed, large size and much dynamism and have some unique properties which make them applicable in precise modeling of many real data mining applications. The main challenge of data streams is the occurrence of concept drift which can be in four types: sudden, gradual,... 

This thesis reviews briefly historical backgrounds and contexts of Darwin's theory and summarizes and describes his arguments in the Origin, and studies philosophical issues around Darwinism. This thesis includes four chapters: chapter one reviews historical line from Greek thinkers to ninteenth century scientists; chapter two summarizes ideas and arguments in the Origin; chapter three discusses some philosophical issues briefly; and chapter four is devoted to some conclusion