Sharif Digital Repository

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... 

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... 

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... 

Current Global Positioning Systems (GPS) are unreliable for indoor positioning, leading to an increased demand for indoor navigation and tracking services. This research utilizes wireless technologies such as Bluetooth and Wi-Fi to provide these services by installing devices in the environment that connect to objects or individuals. To ensure the system's practicality, attention must be given to hardware optimization, cost reduction, and easy installation. The system should be applicable in large indoor environments such as hospitals and buildings, assisting with navigation. Key challenges include positioning accuracy, implementation costs, and energy consumption. This thesis presents... 

This research examines the impact of indirect network effects in platforms on the likelihood of success for platform complements. The main question addressed by this study is: How does a larger number of complements in a platform ecosystem, through access to diverse resources and knowledge, influence the enhancement of innovation and the likelihood of success for platform complements? While the expansion of indirect networks creates more opportunities for innovation and access to resources on one hand, it may also lead to negative effects such as increased competition among complements and user confusion on the other. The goal of this research is to provide a comprehensive answer to these... 

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... 

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... 

Researchers are continuously investigating the factors influencing the burden of disease. Studying these factors contributes to improving the health status of communities. Although previous studies have addressed the impact of digital technologies on health improvement, the effect of information and communication technology (ICT) usage on the disease burden in countries has not been empirically studied. Therefore, this study examines this impact and considers the level of development of countries as a moderating factor. Results from a panel data set of 1,079 observations across 83 countries over 13 years indicate that the use of information and communication technology reduces the disease... 

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 aim of this research is to examine the impact of digital platforms on the sustainable development of countries. This study employs a quantitative approach to determine the relationship between the development of digital platforms and sustainable development from economic and environmental perspectives. To achieve this, a composite index for the development of digital platforms is defined based on previous studies. Subsequently, data for its sub-indicators are collected from reliable international databases such as the World Bank, the International Telecommunication Union, and others, enabling the calculation of this index for 42 countries during the period 2014 to 2022. The results of... 

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... 

The processing of audio signals can be very widely used in the Internet of Things because by using audio signals, valuable information can be obtained from the activities of the environment. Environmental sound processing and investigation can be used in applications such as industrial troubleshooting security systems, etc. For this, it is necessary to build a sound recognition and classification system. In this thesis, we have evaluated the features obtained from feature engineering and feature learning and the use of various machine learning methods for the audio event classification system. To test and evaluate the system, known data in this field have been used. Finally, by proposing an... 

Artificial intelligence, as the most important topic of the current decade include various aspects such as artificial neural networks, pattern recognition, machine learning, audio and image processing, and random number generation. To implement hardware hosting artificial intelligence algorithms, a system must be designed with very high processing power, utilizing parallelism and consuming low energy. The best example of such a system is the human brain. For this reason, different structures of bio-inspired or neuromorphic computational systems have been designed taking inspiration from the human brain and are called bio-inspired or neuromorphic computation systems. The limitations of CMOS... 

One of the main problems in proton computed tomography is the reduction of the spatial resolution of the image due to multiple Coulomb scattering of protons while passing through the material. Estimating the most likely path of protons inside the material can be beneficial to solve this problem. In this regard, artificial neural networks, as one of the innovative solutions in the field of machine learning, have helped to improve the accuracy of estimating the most likely path of protons. In this study, an artificial neural network with an adaptive moment estimation optimization algorithm was designed to estimate the most likely path of protons. The network was trained using data obtained... 

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...