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... 

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... 

Soil-structure interaction may have a considerable effect on the response of the superstructure. One of the main steps in analyzing the soil-structure system is determining the soil impedances which vary with frequency. Although it is possible to analyze a dynamic system with complex frequency-dependent property matrices, this cannot be taken into account in most standard general-purpose softwares. In addition, the nonlinear behaviour of the structure can only be studied in time domain. Therefore, in the past two decades efforts have been made to replace the soil media with discrete models having a small number of degrees of freedom (DOFs) and a few springs, dashpots and masses with... 

The use of sandwich panels has become very common in recent engineering designs when the weight of the part or structure is important and we are looking to lose weight while maintaining strength. The mechanical properties of this type of structures, including yield stress, fatigue behavior and estimation of their life, failure modes, natural frequencies and resonance phenomena, etc. are affected by various factors, including geometric and environmental factors. Fatigue is one of the most common failures in these structures. Composite materials have complex structures. In these materials, due to the viscoelastic properties, the fatigue behavior changes with changing stress, stress frequency,... 

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... 

1,3-Dipolar cycloaddition reactions constitute one of the most fundamental reactions for construction of five-membered heterocyclic compounds Spiro and dispirooxindoles have become important synthetic targets as these structural frameworks form the core units of many naturally occurring molecules that possess abundant biological activities .In this report we used (E)-Aryl ideneindolinones as unusual dipolarophiles for synthesis of dispirooxindoles. In follow different bifunctional nucleophiles for example 1,3-dicarbonyl, phenol, thioindole can be used in synthesis of benzoxazocines We have reported a new and efficient synthesis of benzoxazocines via unique tandem 1,3-dinucleophilic addition... 

We have reported a new and efficient synthesis of a broad spectrum of heterotetracyclic thiopyranoindole via knovenagel hetero diels alder reaction.Fused pyrimidines have attracted considerable attention in synthetic organic chemistry because of their wide range of biological activities pharmaceutical and therapeutic properties, and antibacterial, antiviral, antitumor, and anti-inflammatory activities. We have reported a new efficient method for synthesis of pyrimidines fused to coumarine, uracile, cyclohexane and triamino pyrimidine structures. The major benefits of the current study are high yields, short reaction times, mild reaction conditions and available materials..We have also... 

The natural tissue of the bones consists of organic and inorganic parts. The bone mineral part contains calcium phosphate and its organic part is mainly of collagen fibers. The combination of these fibers and calcium phosphate makes the bone flexible and resistant to stresses. Many conditions, including osteoporosis and crashes, lead to fractures and cavities in bone. Bone cements are the most used materials used in orthopedic surgeries and spinal cord.The purpose of this study was to synthesis acrylic bone cement with properties determined by ASTM F 451 and Iso5833 for orthopedic applications, including joint replacement. Polymethyl methacrylate polymer was synthesized as the main component... 

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,... 

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 supplier selection problem is considered as one of the most strategic and critical issues for any organization. This issue is mainly relevant to traditional and manufacturing businesses. However, if we examine its relationship with the emerging concept of Vendor Acquisition, which has become increasingly significant in modern businesses and startups, the importance of supplier selection becomes even greater. Today, choosing the right supplier or vendor determines the level of success organizations achieve in any new project, and the performance of vendors plays a crucial role in shaping and directing these projects. This study aims to present a comprehensive framework for supplier... 

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...