Sharif Digital Repository

One of the significant as well as fascinating utilization of thermoacoustic is combining heat pump and thermoacoustic refrigerator. By means of supplied heat from hear source, the heat pump generates acoustic power which will be absorbed by refrigerator and forwarded to the heat source afterwards. In other words, thermoacoustic systems, from the side of which heat is absorbed, produces chill in the opposite side. Due to the novelty as well as heavy and precise research requirements, these systems has been neither designed nor manufactured in our country yet. In this research a laboratory prototype from aforementioned systems has been constructed, thereby paving the way for enjoying and... 

Today, social networks have provided an environment for disseminating all kinds of information and news among the people. One of the challenges of ex-panding social networks is reading and trusting fake news propagating against accurate information. Fake news is false information that the author intention-ally produces and publishes. Due to the destructive effects of spreading fake news, determining the trustworthiness of news is one of the critical issues in the so-cial, political, and economic fields. In this research, we worked on detecting fake news on social media using multimodal data. To solve the problem of fake news detection, we used the text and images of the information. Transfer... 

In this thesis, we consider a network creation game in which, each player (vertex) has a limited budget to establish links to other players. In our model, each link has a unit cost and each agent tries to minimize its cost which is its local diameter or its total distance to other players in the (undirected) underlying graph of the created network. Two variants of the game are studied: in the MAX version, the cost incurred to a vertex is the maximum distance between that vertex and other vertices, and in the SUM version, the cost incurred to a vertex is the sum of distances between that vertex and other vertices. We prove that in both versions pure Nash equilibria exist, but the problem of... 

Based on fog computing paradigm, new applications have become feasible through the use of hardware capabilities of smart phones. Many of these applications require a vast amount of computing and real-time execution should be guaranteed. Based on fog computing, in order to solve these problems in is necessary to offload heavy computing to servers with adequate hardware capabilities. On the other side, the offloading process causes time overhead and endangers the real-timeliness of the application. Also, because of the limited battery capacity of the handheld devices, energy consumption is very important and should be minimized.The usual proposed solution for this problem is to refactor the... 

Investors highly value the ability to predict the behavior of the capital market. Over time, various methods have been introduced to forecast the future of this market and anticipate its movements. A novel approach to achieving this is by developing data-driven decision support systems that can assist investors in making informed trading decisions. The opinions of experts play a crucial role in shaping people's perception of the market, which ultimately affects its final behavior. In this study, we have created a decision support system that can help investors by considering the complexities and meaningful relationships between different aspects of the problem. We have developed frameworks... 

With the rapid advancement of artificial intelligence technologies, particularly large language models, the automatic generation of educational content has attracted significant attention among researchers and instructional designers. The importance of this topic lies in the fact that designing and developing educational courses is a time-consuming and costly process, while many educational institutions and instructors seek to leverage modern tools to provide learners with relevant, interactive, and effective content. At the same time, the quality of the content and its alignment with psychological principles of learning and instructional design play a crucial role in the effectiveness of... 

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... 

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... 

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... 

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,... 

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... 

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... 

With the expansion of the Internet of Things and the significant increase in latencysensitive applications, cloud computing is facing serious challenges. In order to solve the challenges of cloud computing and respond to the needs of delay-sensitive applications, the concept of edge computing is proposed. In edge-based infrastructures, computing resources are located near the network edge and end devices. These infrastructures can better serve latency and security sensitive applications that require low processing and high interaction with end devices. However, achieving the benefits of edge-based infrastructure requires optimal resource management. One of the effective steps for optimal use... 

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... 

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... 

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... 

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  

The need for a fast, light and affordable payment method, was a reason to produce multiple payment channel network on various of networks. To deploy and expand these networks, we need to deploy a profit model for new customers on the betweenness they add to network. In this research we maximum profit solutions for network with fixed payment cost and network with reduced betweenness profit for longer distances.At first, we suggest for a limited fund, we decide to make channels with most betweenness profit and prove it's a np-hard problem. Then for limited charge of making new channels, we show that it's a np-hard too. In graph of a path, we prove there is a solution based on length of path,... 

Strategic Network Formation defines how and why networks take particular forms. In many networks, the relation between nodes is determined by the choice of the participating players involved, not by an arbitrary rule. A "strategic2 modeling of network requires defining a network’s costs and benefits and predicts how individual preferences become outcomes. In strategic network formation it is important to look at the overall social benefit and to see if networks that players create manage to be efficient for the society in general. The code review process also referred to as peer review, stands out as a tried and tested method in a large palette of applications to allow... 

This paper is concerned with the Vehicle Routing Problem (VRP) in a fleet with customer loyalty. In this work, we consider priority for customers according to their loyalty and try to declare an objective function which concerns customers' satisfaction along other normal VRP objectives like route optimization