Sharif Digital Repository

Single image super-resolution (SISR) is a known difficult problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions.The problem of Super Resolution has applications in many areas and industries where, for example, it can reduce the cost and time of re-imaging in many fields including the medical industry. In the satellite industry, distortions are eliminated and geographic information increases with clarity. In the astronomical industry, image recognition and computation become easier with super resolution. Also in many other important fields, for example, car license plate imaging, image quality enhancement can have significant effects for... 

Since the start of Covid-19 pandemic lately in 2019 from Wuhan in China, a lot of countries encountered it. Healthcare sysytems are the most important system against pandemics so it is needed to measure the efficiency of healthcare systems against Covid-19 in order to find best practices. In this research, a 3-phased method is proposed to evaluate the performance of the healthcare systems. In the first phase, countries are clustered, in the second phase the DEA model is applied in 2 separate parts, in one part with considering clusters and in another without it. In the third phase resilience is introduced for Covid-19 and then it is used as a criterion beside two other criteria, DEA result... 

Since investing in the stock market is always known as one of the ways to increase capital, many researches have been done in the field of portfolio selection in order to provide methods to earn more profit and control investment risk. One of the influential factors in increasing the profit from the portfolio is the proper prediction of future of shares. Therefore, in many research, various methods and tools have been used to predict the future of shares more accurately. One of these tools is forecasting the market regime. In this research, harmonic patterns have been used to predict the market regime. Also, based on the harmonic patterns, the scope of entry into the transaction, the... 

Control charts are one of the most important statistical process control tools used in monitoring processes and improving the quality by decreasing the variability of processes. In spite of various applications for multi-attribute control charts in industries and service sectors, only a few research efforts have been performed in developing this type of control charts. The developed multivariate control charts are all based on the assumption that the quality characteristics follow a multivariate Normal distribution while, in many applications the correlated quality characteristics that have to be monitored simultaneously are of attribute type and follow distributions such as multivariate... 

Nowadays due to the advancement in technology, most of the production processes consist of several dependent stages and the quality characteristics of products at each stage depends not only on the operation at the current stage but also to the quality characteristics at the upstream stages. In other words, the disturbance in the quality characteristics of each stage would propagate to the downstream stages and affects the quality of the products at downstream stages. This property is referred to as the cascade property of multistage processes. However, the most of the conventional SPC tools were developed based on the assumption of processes with single stage or processes with multiple... 

Nowadays, investigating the factors affecting traffic models from different aspects such as metropolitan planning according to the present conditions can help high-level decision-makers and also, at the micro-level, help the travelers to make appropriate decisions for scheduling affairs, route selection, and vehicle type selection. Given the importance of this topic, a framework will be presented in this study that will evaluate the impact of some identified factors such as travel distance, climate, and urban events, and then all these factors will be presented in mathematical formulas. In the end, based on the model, the travel time will be predicted. In this framework, gene expression... 

Today, many real-world datasets such as social network data and web pages can be shown as graphs. Community detection and clustering of these big graphs has many applications in different fields like recommender systems in social networks and Diag- nosis of diseases in communication networks among proteins. A cluster in a graph is a sub-graph with many internal and few external edges. A new method for local cluster detection around an existing vertex is introduced in this paper. This method applies random walk algorithm for cluster detection. The time complexity of this algorithm based on the graph size is polynomial. Therefore, it can be used for clustering of big graphs. The experimental... 

Performing analysis and forecasting is crucial. Better forecasting will lead to better decisions. One method for predicting the future is time series analysis. In reality, it is common for an intervention to occur and alter the characteristics of a time series. In recent years, interrupted time series analysis has been receiving a lot of attention. A new forecasting method for interrupted time series has been developed in this study. This is a system dynamics-based approach. At every stage of the approach, system thinking is incorporated. In order to model the effects of a given intervention, common modes of behavior in dynamic systems are used. Furthermore, control theory has been used to... 

Using an efficient method to manage inventory systems is always a challenging issue in supply chain optimization. In supply chains including perishable goods, it is possible to reduce waste and other costs by identifying uncertain demand patterns and managing inventory levels at different stages of the supply chain. Considering the uncertainty and complex conditions of supply chains in the real world, in order to create a suitable model to express these conditions, various uncertain factors must be considered, each of which affects the supply chain inventory level in some way. In this research, a multi-level perishable supply chain model with uncertain demand, lead time and deterioration... 

The outpatient clinics have some features that make them different from other types of the clinic. Something that must be paid attention is adherence to appointments by outpatients, which have an undeniable effect on the productivity of the Outpatient Appointment System. In most of the outpatient clinics, outpatients are supposed to schedule their appointment in advance. As a result, if patients do not come to the health center based on their scheduled appointment, and they do not inform the health center about their absence, not only will the clinic become deprived of the opportunity to utilize its resources efficiently, but also healthcare access for other patients will reduce. The rate of... 

By considering the environmental factors, outpatient scheduling has become more efficient, and the closer these factors are to the actual situation, the more accurate the scheduling is. This study aims to schedule outpatients in such a way that in addition to bringing the hypotheses of the problem closer to the real world, its implementation can be done more easily. On the other hand, medical centers, due to their nature, do not consider the income in their objective function. Therefore, another contribution of this study is considering the income of medical centers in such a way that not only will it increase patient satisfaction, but also it maximizes the revenue of the medical center.... 

Making money and maintaining the value of assets has always been one of the most important concerns of people. Real estate is one of the essential human needs, but it is also considered an investment tool for individuals. In addition to individuals in a family, various groups and organizations such as policymakers, analysts, banks and financial institutions, taxpayers, and real estate investors are directly or indirectly affected by the dynamic characteristic of the housing market. Therefore, forecasting the exact amount of housing value in the future is very important. Factors that can improve this forecasting's accuracy include considering the relationship between housing value and... 

In recent years, energy storage systems have received widespread attention from researchers to increase the reliability of the power grid. These systems have different types that compressed air system is of special importance due to its high stored energy and long life. In this system, the surplus of electricity generated from renewable energy sources or grid electricity at low power consumption is compressed and stored in a tank. When there is a need for power consumption or peak power consumption, compressed air will generate electricity by passing through the turbine and will help the network. Large-scale type of the system requires special geographical location for air storage; for this... 

In recent years, requirement engineering and goal modeling have gained more attention among different organisations. Therefore, different methods have been designed to discover stakeholders’ requirements and translate them into process and organizational goals. Various goal models have been introduced to represent these goals and their relations towards each other. Still, these methods are manual representations of different process scenarios and do not relate to the actual behavior. In 2014, Map Miner Method (MMM) was introduced to discover intentional process models from event logs. MMM uses Hidden Markov Model (HMM) as a means to represent the process as a map model of strategies and... 

One of the challenging issues in machine learning is the problem of data imbalance. Data imbalance occurs when the number of samples from one or more classes significantly exceeds or falls behind that of other classes. The existence of data imbalance in a dataset often leads to misleading accuracy of models, inadequate prediction of minority class, and a lack of generalization. Data imbalance can be observed in various datasets such as fraud detection, disease diagnosis, email spam detection, and fake news detection. To address this issue, various methods have been proposed, categorized into four groups: data-level, algorithm-level, cost-sensitive, and ensemble approaches. In this study, two...