Sharif Digital Repository

Today, with the expanding usage of wireless communication systems, the need for system which uses the spectrum efficiently is inevitable. Therefore, Cognitive Radio structures have be the center of attention, recently. In cognitive radio structures, the system tries to use the empty spectrum efficientlyin time, frequency, and space domain. Autonomous Vehicular Networks are interesting application, in which cognitive radio can be used. In such networks, due to high speed, the channel state changes drastically which negatively affects the system.Hence, in this thesis, an OFDM-based multiuser structure is designed which work properly in such condition. For designing the structure, a doubly... 

Steganography is method for communicating confidential information through a non-trustworth in way which hides the existence of communication. For improving the security of steganography statistical detectability must decrease as such as possible. Despite the fact, that the quality of the relation between statistical detectability and amount of distortion engendered by embedding is still an open problem, problem of detectability reduces to problem of management of pixel embedding in order to minimization of distortion. As in wet paper coding methods, an optimum (or approximately optimum) algorithm proportioned to Pixel-cost has been offered, the current problem of steganography is to find... 

In recent years, Intelligent Transportation Systems (ITS) have received special attentions both in research and in commercial areas. Increased infrastructure facilities, like surveillance cameras, has made this concept even more attainable than before. In this respect, the ability to automatically extract information from traffic images, as one of the key inputs of ITSs, is of great importance. With an increased number of surveillance cameras and the need for more accurate information regarding the road users and their interactions, in order to better city traffic management, building and repairing roads, trip time estimation, number of people per roads estimation and etc, using human... 

In today's world we are dealing with many devices and processes with the goal of efficiency and performance improvement. In many processes particularly chemical ones, the goal is to control the output according to its constraints in the way that the performance is economically efficient, such as reducing energy consumption and energy loss and increasing efficiency. In order to control a process with economical goals, an economical cost function is used and after determination of optimal values a controller is used to guide the process so can achieve them. Model predictive control (MPC) is very common in this economic control Due to advantages such as considering the problem constraints. In... 

With the advent of technology, small in size sensors, memory, speeding up the processor and lowering the cost, it is possible to build an embedded camera system. The goal of this project is to design and build an embedded camera system so it can execute any set of necessary algorithms as depending on the application. In this project, two models of embedded camera systems have been presented as an integrated system and a system with independent units. To design the integrated embedded system, ZYNQ processor is used and two structures are presented in the form of hardware-software and hardware design. In hardware-software design, image processing operations are done by software and in hardware... 

Smartphone sensors like accelerometer, gyroscope and magnetometer are very common nowadays. This gives us the opportunity for sensor-based activity recognition. This thesis's goal is to collect data from different smartphone sensors and then extract hand-crafted features and classify them using machine learning algorithms. Metro, bus, taxi, bicycle, running, upstairs, walking and standing are studied activities in this thesis. All above steps are covered in this research, later we want to present an activity recognition model and then test it through a web server, after that, we modify the model by proposing to change learning coefficient to gain better accuracy. Finally, an Android app was... 

The importance and vitality of focusing on sustainable transition and reducing carbon dioxide emissions are clear to everyone today. However, until recently, the impact of digitization as a major global trend involving the application of digital technologies to change and optimize various elements of business, society, and daily life on the environment and carbon dioxide emissions has been underestimated. Despite the growing amount of research in this field, according to current studies, the connection between digitization and carbon dioxide emissions is not clear. To achieve environmental and sustainable development goals, fossil fuel consumption and greenhouse gas (GHG) emissions must be... 

Artificial intelligence is a field that has made another revolution in the Fourth Industrial Revolution and has become one of the most widely used emerging technologies in the present era. Further investigation of the trends in this field shows that it has shown increasing growth in recent years. Also, in the future, this trend will continue and fundamental changes will occur in societies. For this reason, countries must definitely pay the necessary and sufficient attention to this field in their growth and development path. To achieve this growth path, it is intended to evaluate the status of leading countries in the field of artificial intelligence using two key variables in technological... 

Predicting traffic condition is one of the most important topics for traffic engineers and is a vital part of smart city. Extracting traffic behavior and realizing new traffic behaviors plays undeniable parts in big decision making of cities. On the other hand, progress of new technologies and devices for controlling and monitoring traffic caused the volume of traffic related data to grow exponentially. Velocity and variety of these data made normal data mining solution to fail in modeling and performing well. New data era has changed the view of large numbers of science and engineering majors. Traffic engineering also needs big data analytics for process of its own big data. Thus the need... 

Globally, bicycle sharing is one of the fast-growing solutions to climate change in the transport sector. However, what inequities may be reflected, exacerbated, or arose from its adoption and use? Relying on a qualitative research design involving interviews with bicycle sharing users, non-adopters, and daily observers of the cycling infrastructure (N = 36), site visits, and a literature review, we examine distributive, procedural, and recognition injustices in association with Bdood, an operating BSS in Iran, a developing country that allows for less-documented types of injustice to arise. In doing so, we utilize a comprehensive transport/mobility justice framework, drawn from the fields... 

The multi people tracking is considered a fundamental problem in computer vision, which has received considerable attention from academic and commercial fields. This issue deals with a set of proposed methods that track the movement path of several humans in a video-like sequence. The problem of multi people tracking is the foundation of other computer vision problems, including human gesture estimation, motion recognition, and behavioral analysis, and is mainly used in emerging fields such as automatic car driving, smart security, service robots, etc. Although many methods have been proposed and investigated to solve the above problem; But there are still serious challenges, such as severe... 

Traffic density estimation is one of the most challenging problems in Intelligent Transportation Systems. One of the important traffic information that is broadcasted to drivers is Traffic Density information. In many traffic control centers; human operators are responsible for estimating traffic density from captured video data. Increasing traffic cameras and constraint number of operators introduce an updating delay to broadcasted information. So it is important to have an automatic traffic density estimation system. In this thesis, machine vision is used to solve this problem. Supervised Image classification is our approach. In supervised Image classification, images are classified to... 

Statistical detectability is a feature of a steganalyzer that states its power for distinguishing between cover and stego images. A steganographer tries to design the steganography algorithm such that the steganalyzer could not detect the stego images. As a result, designing an efficient steganography algorithm (assigning the pixel cost) that could minimize the statistical detectability is an important objective in steganography. However, making a sensible relation between the pixel cost and statistical detectability is an open problem.
In this thesis, by modeling the steganalyzer using the LDA topic model, we analyze its error probability as a criterion of statistical detectability.... 

Audio signal processing is a greatly useful approach to the Internet of Things since analyzing prominent audio signals can provide valuable information about environmental activities. Environmental sound processing is used in applications such as mechanical systems diagnosis, industrial maintenance, security systems, etc. This approach requires the design and development of sound classification and detection systems. In this thesis, we have achieved 84.5% accuracy on optimizing the features (by feature engineering and feature learning) and exploiting different types of machine learning algorithms. Well-known databases such as ESC-50 have been used to test and evaluate the whole system. Among... 

Nowadays, using different types of data has shown significant impacts on analyzing the related systems. Growth in data volume, systems complexity and existence of error and obscurity in collecting the data, increased the necessity of inventing new data analysis methods. Location-based data is an important data type for such analyses which are collected from sensors in different places. These data besides other official organization's information like municipality or Google … provide us a bulk volume of raw data. Such collections of raw data are mostly diverse, heterogeneous, bulk and outspread. Inspite of that, raw data with machine learning algorithms lead to considerable practical... 

Climate change and its Environmental issues become fundamental challenges in recent years, and countries have to try find various solutions about it, such as developing renewable energy technologies. Multiple studies have been conducted on the importance of innovation in technology development and technological changes in different countries. Many studies have addressed the concept of the innovation system and evaluated the role of various institutions and actors. The innovation system as one of the concepts branched from the innovation system focuses on the importance of interactions between actors, the role, and nature of knowledge in a particular industry or sector. Hence, investigating... 

In the transportation industry, one of the most important and fundamental problems is the traffic of vehicles in the transportation roads. This problem is especially seen in large and densely populated cities such as Tehran. If traffic control is not done properly, it can lead to problems such as reduced traffic dynamics, environmental pollution, wasted drivers' time, disorder and loss of energy. If the traffic control is done after creating a traffic problem, it will not bring good results and will have low efficiency. For this reason, optimal traffic management and control has been raised as an important issue, especially in large cities. Predicting traffic flow is one of the important and... 

In this research, we delve into the challenges video game developers encounter when selecting an appropriate genre for their initial video games. The primary objective of this study is to identify the effective strategies enabling video game developers to successfully enter the competitive market. Within this context, 'success' is quantified by sales volumes and download counts. The video game industry is witnessing rapid growth, with its market size reaching $184 billion in 2023, according to Newzoo report. To address these inquiries, the study uses information from three different platforms, gathering data in a thorough way: PC games on Steam, Android mobile games on the Google Play Store,... 

The comfort of occupants has been a key driver behind the adoption of smart building technologies in recent years. To achieve this goal, machine learning methods have seen significant growth, with deep reinforcement learning emerging as particularly advantageous. Unlike advanced control strategies such as model predictive control, deep reinforcement learning does not require a physical model. Instead, learning occurs through the direct interaction of an intelligent agent with the environment, without the need for predefined datasets. This approach is further strengthened by its ability to adapt to dynamic conditions and effectively operate in large state spaces. Given that heating and...