Sharif Digital Repository

Controlling dynamical systems is an important area of research, having many applications in related practical fields. One class of dynamical systems which have obtained ever-growing importance in recent years are networked dynamical systems, in which dynamic behavior is observed on nodes interacting in a networked setting. This is mainly due to the rise of complex networks, e.g. social networks, as an important and powerful method of capturing dynamic behavior that exists in different systems. One important aspect of such systems is that in many scenarios, actors that participate in them are selfish and act rationally based on their own self interest. Therefore guiding such systems to... 

Cancer is a complicated disease. So, cancer treatment can not be possible without understanding its complex behavior. Each of cells do inner operations spontaneously and have interactions on external environment. This feature of cells has caused to model their behaviors using multi-agents and considering each cell as an intelligent agent. Using this approach, a novel multi-scale agent-based model known as basic model has been introduced. Furthermore, two signaling pathways have been added to this model. For simulation, a new agent-based modeling framework has been proposed. After that, learning has been involved, for considering drug effects. Finally, by means of this model we can predict... 

Android phones are widely used now. Convenient user interface and various applications for these devices has played a significant role in their success. The wide usage of these devices besides the nature of their applications lead to collect lots of sensitive information on them. Consequently the protection of this information is very important. The unfamiliarity and the inattention of the most of smart phone users to security issues highlight the importance of the data protection and the privacy. The permission access in Android operating system is static and users should permit applications to access the requested permissions on installing them. Also these programs can use their... 

The competition for staying in the business world has intensified today with the rise of open-source and commercial software. As long as a software is tailor-made to suit the needs of users, it is so-called alive and can stay in the competition. So the maintenance phase is necessary to make changes to the software to meet the needs of users. To reduce costs associated with this phase, it is necessary to avoid software bugs. One way to avoid software bugs is to use peer code review. Peer code review has been recognized as one of the best software engineering principles of the last 35 years. This principle helps maintain the quality of the code due to changes made to parts of the code that... 

Representation learning methods on graphs have enabled using machine learning methods on graphs' discrete structure by transferring them to a continuous domain. As graphs' structures are not always static and may evolve through time, dynamic representation learning methods have recently gained scholars' attention. Several methods have been proposed to enable the model to update the embeddings graph changes, or new interactions happen between nodes. These online methods could significantly reduce the learning time by refreshing the model as the changes occur, so we don't need to retrain the model with the complete graph information. Moreover, by using the temporal information of interactions,... 

Stock price patterns are a technical analysis approach to forecast future trends with tremendous practical benefits. However, the current algorithms solely rely on machine learning techniques and deep neural networks which could be a problem in countries where data sets such as these are not available. We propose an algorithm based on geometry and mathematics for this problem, leading to an O(n^3logn + n^2k) complexity, where k is the number of triangular patterns  

Video games with respect to an ever Increasing player pool and Industry growth, have attracted a lot of attention in recent years. Dota 2, as one of the most successful games both in casual gamers’ community and E-sport community, is considered as a proper case study, however, most of the research done was limited to predicting games’ outcome. Despite The popularity, the rather unintelligent AI of the game has made quite a frustrating experience for new players. In this research, with a novel approach, hero features are used to predict their future positions. For this purpose, 35 professional games are collected and analyzed and 601 features are extracted. Then, suitable features are... 

Deep learning algorithms combined with supervision rely heavily on labeled data, posing challenges in the data labeling process. Addressing this issue, researchers in the field of machine learning have focused on developing approaches to reduce the dependency on labeled data and improve the efficiency of data collection for labeling purposes. This thesis investigates the training of a classification model using data collected through a human-in-the-loop system. Notably, this research pioneers the application of active learning techniques to differentiate between political and non-political Persian tweets. The dataset introduced in this study is the sole available collection for this specific... 

Content delivery networks play a significant role in improving the quality of internet services by placing the necessary content closer to users on servers. Currently, over half of internet traffic is delivered through these networks to end users. The efficiency of a content delivery network depends on various parameters, including the type of requested content, workload distribution methods, network topology, routing algorithms, caching policies, network server configurations, and resource allocation (shared or dedicated hardware resources). Additionally, the requests made to a content delivery network vary based on the type of service and even the time of day, making optimization a... 

Software-defined networking (SDN) is a network management approach that allows centralized control of the network independently from network hardware. As a network management method, SDN provides many capabilities not traditionally found in existing hardware-based networks. However, one of the significant challenges of SDN is the placement of the controller within the network. In SDN, the central controller must be able to efficiently route all data flows separately to end devices. Therefore, the placement of the controller in the network is crucial. However, controller placement in the network poses a major challenge as it needs to be appropriately and optimally positioned to enhance... 

Over the past few years, deep reinforcement learning(DRL) has been given a lot of attention in finance for portfolio management. With the help of experts’ signals and historical price data, we have developed a new reinforcement learning(RL) method. The use of experts’ signals in tandem with DRL has been used before in finance, but we believe this is the first time this method has been used to solve the financial portfolio management problem. As our agent, we used the Proximal Policy Optimization(PPO) algorithm to process the reward and take actions in the environment. Our framework comprises a convolutional network to aggregate signals, a convolutional network for historical price data, and... 

In the world of software development, Code Review is one of the most vital processes to ensure code quality and security. The textual content features in code review comments play a significant role in assessing quality and guiding the review process. This research aims to examine the importance and role of these features in identifying anti-social comments and improving code review processes. In this study, we first challenge the concept of toxicity in code review comments, which had previously been accepted as a concept in the field of code review. We focus on enhancing and automating code review processes by accurately and reliably detecting anti-social comments based on relevant... 

With the proliferation of electric vehicles (EVs), the batteries in millions of EVs are anticipated to become the most cost-effective method of energy storage. By using a bidirectional charger, energy can be stored in vehicles during off-peak hours and then returned to the grid during peak consumption times. The CLLC resonant converter is a suitable circuit for bidirectional power conversion in applications like bidirectional EV chargers. This thesis aims to reduce power losses and increase operating frequency by incorporating wide bandgap (WBG) transistors. Additionally, the use of planar transformers is pursued due to their low profile and the capability to control both magnetizing and... 

Portfolio optimization is a crucial concept in financial engineering, focusing on the efficient management of investment portfolios. In the realm of financial markets, a portfolio refers to a collection of investments held by individuals or companies, encompassing diverse assets. Specifically, a stock portfolio consists solely of stocks. The primary objective of portfolio optimization methods is to maximize returns while controlling risks. Within Tehran’s Stock Market, valuable data pertaining to the stock portfolios of big shareholders and their historical changes can be obtained. This dataset contains vital information that can be leveraged to optimize portfolios over time and formulate...