Sharif Digital Repository

In this thesis we have studied slotted and unslotted ALOHA random access optical CDMA packet switching networks with a chip-level receiver structure. We used generalized optical orthogonal codes (GOOC) and Overlapping PPM (OPPM) signaling technique to improve system performance. The impact of physical layer parameters such as GOOC code cross correlation value and OPPM overlapping index on key performance benchmarks such as network throughput and delay are analyzed. We have also studied the stability of the network based on the number of backlogged users, using expected state drift. It has been shown that using GOOC instead of strict OOC improves the network average delay and throughput.... 

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... 

There are a lot of ways to measure the soil compaction but all of them have some deficiencies like low precision, soil destructive, time consuming and etc. The usual ways to measure the compaction in Iran are so traditonal and have the above problems. To solve these problems, modern ways like intelligent compaction is recomonded to decrease the time and cost of compaction. The observor can also control the compaction of all the soil point to prevent any offenses by making the network between the rollers.In new methods the soil compaction is calculated by measuring the roller vibratory and usage of fourier transform from the drum response . To compact the soil more precisely and more quickly,... 

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... 

Many public projects in Iran are being developed with the participation of the private sector. Complaints, however, have arisen in both the public and the private sectors in many public-private-partnership (PPP) projects. It is claimed that the current PPP standard-form contract is unable to properly handle project risks. This investigation was set to improve risk responses in the PPP standard-form contract in the country. A comprehensive list of 66 universal PPP project risks was prepared by review of various related international research efforts. The list was refined to 36 risk items for the country in consultation with PPP project experts and assessing two PPP cases. These risks were... 

Today, the correct management of construction projects in IRAN's water industry has become a severe concern for its managers. Construction projects of the water industry constitute a considerable part of the country's construction industry. Several significant Issues such as operation management, water industry projects, correct management of resources, crisis management in the water industry, increased productivity and useful life of structures, increasing productivity, and preventing water loss are among the determinative challenges in construction projects in Iran. One of the new methods for the correct management of the life cycle of projects in this area is the use of Building... 

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,... 

The municipality is an administrative, public and non-state institution that falls into the city district of the most countries’ administrative divisions. This institution has relatively autonomy and independent power. Municipalities are trying to apply the best approaches (Such as Building Information Modeling (BIM) as a procedure contributing the project management) to save time and money, as well as to satisfy the citizens in the implementation of civil projects. This study examines and evaluates the readiness of municipalities to modify the construction projects based on BIM. In addition, a pattern for identifying BIM applications, evaluating the organization readiness and the needs of... 

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... 

One of the most significant factors for the on-time and successful implementation of construction projects is contract management. Proper management of construction contracts and assessment of potential risks in the bidding process and before its signing have a significant impact on preventing or reducing the occurrence of claims and disputes between the contract parties at various stages of the project. In this research, using the latest deep learning (DL) and natural language processing (NLP) state-of-the-art methods, and various deep neural networks (DNN) architectures a model has been developed for extracting Persian contract risk-prone clauses. In addition, this study provides a... 

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... 

In construction projects, when the employer does not have enough knowledge or experience to implement and manage the project, or does not have enough time to implement the project, can hire a Management Contractor with sufficient experience and knowledge in the field of project management. On the other hand, the inability of the Management Contractor to manage the project or contracting with him in inappropriate way, not only causes additional costs for hiring the Management Contractor, but also causes the employer to suffer due to the inappropriate performance of the Management Contractor. Therefore, the utmost care should be taken in choosing the Management Contractor and contracting with... 

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... 

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