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Assessment of Well Tubing with Ovality in Cross Section by Numerical Modeling from the Perspective of Integrity Management
, M.Sc. Thesis Sharif University of Technology ; Raie, Mohammad (Supervisor)
Abstract
This study investigates the ovality on the burst pressure of the pipe inside the well. In the last decade, the use of natural offshore oil and gas resources has increased, and as a result, the importance of well integration as a major part of offshore platforms is clear. At the same time, accidents at oil and gas wells have economic and environmental consequences that underscore the importance of ensuring safe operation. Integrity management of fluid pressure wells has been developed to ensure the safe operation of wells. The functional area of integrity management begins with planning, then inspects and then evaluates, and eventually leads to corrective action, and this loop is repeated on...
Sentiment-Based Topic Analysis on Product Demand Prediction: Pre-Release and Post-Release Study
, M.Sc. Thesis Sharif University of Technology ; Aslani, Shirin (Supervisor)
Abstract
This thesis examines the impact of electronic word-of-mouth (e-WOM) on product demand forecasting, specifically in the context of video game consoles. This study examines the importance of emotion-based topics and their impact on demand forecasting at two stages of the product life cycle: pre-launch and post-launch. Using sentiment analysis and topic modeling, this study uncovers product sales drivers and captures evolving consumer sentiment throughout the product lifecycle. By integrating insights from diffusion theory and consumer information search theory, this research contributes to the field of demand forecasting using social media data. This research shows that by using the topics...
A Study of Intragroup Block-Trading Incentives on the Tehran Stock Exchange
, M.Sc. Thesis Sharif University of Technology ; Heidari, Mehdi (Supervisor) ; Ebrahimnejad, Ali (Supervisor)
Abstract
Using the data of the Tehran Stock Exchange, we analyze the characteristics and explanatory factors of major intra-group and out-of-group transactions and test the tunneling hypothesis in intra-group transactions. We find that out-of-group transactions can be largely explained by changes in control or management, firm size, and the type of the firm. However, intra-group transaction properties mostly depend on the difference between the parent company's cash flow rights in the buyer and seller companies. Also, in the final analysis, we conclude that many intra-group transactions are made to change the structure of the business groups, especially when investment companies buy shares of listed...
A proper transform for satisfying benford's law and its application to double JPEG image forensics
, Article 2012 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2012, 12 December 2012 through 15 December 2012 ; 2012 , Pages 240-244 ; 9781467356060 (ISBN) ; Razzazi, F ; Behrad, A ; Ahmadi, A ; Babaie-Zadeh, M ; Sharif University of Technology
2012
Abstract
This paper presents a new transform domain to evaluate the goodness of fit of natural image data to the common Benford's Law. The evaluation is made by three statistical fitness criteria including Pearson's chi-square test statistic, normalized cross correlation and a distance measure based on symmetrized Kullback-Leibler divergence. It is shown that the serial combination of variance filtering and block 2-D discrete cosine transform reveals the best goodness of fit for the first significant digit. We also show that the proposed transform domain brings reasonable fit for the second, third and fourth significant digits. As an application, the proposed transform domain is utilized to detect...
A novel forensic image analysis tool for discovering double JPEG compression clues
, Article Multimedia Tools and Applications ; Volume 76, Issue 6 , 2017 , Pages 7749-7783 ; 13807501 (ISSN) ; Razzazi, F ; Behrad, A ; Ahmadi, A ; Babaie Zadeh, M ; Sharif University of Technology
Springer New York LLC
2017
Abstract
This paper presents a novel technique to discover double JPEG compression traces. Existing detectors only operate in a scenario that the image under investigation is explicitly available in JPEG format. Consequently, if quantization information of JPEG files is unknown, their performance dramatically degrades. Our method addresses both forensic scenarios which results in a fresh perceptual detection pipeline. We suggest a dimensionality reduction algorithm to visualize behaviors of a big database including various single and double compressed images. Based on intuitions of visualization, three bottom-up, top-down and combined top-down/bottom-up learning strategies are proposed. Our tool...
Quantization-unaware double JPEG compression detection
, Article Journal of Mathematical Imaging and Vision ; Volume 54, Issue 3 , 2016 , Pages 269-286 ; 09249907 (ISSN) ; Razzazi, F ; Behrad, A ; Ahmadi, A ; Babaie Zadeh, M ; Sharif University of Technology
Springer New York LLC
2016
Abstract
The current double JPEG compression detection techniques identify whether or not an JPEG image file has undergone the compression twice, by knowing its embedded quantization table. This paper addresses another forensic scenario in which the quantization table of a JPEG file is not explicitly or reliably known, which may compel the forensic analyst to blindly reveal the recompression clues. To do this, we first statistically analyze the theory behind quantized alternating current (AC) modes in JPEG compression and show that the number of quantized AC modes required to detect double compression is a function of both the image’s block texture and the compression’s quality level in a fresh...
A novel forensic image analysis tool for discovering double JPEG compression clues
, Article Multimedia Tools and Applications ; Volume 76, Issue 6 , 2017 , Pages 7749-7783 ; 13807501 (ISSN) ; Razzazi, F ; Behrad, A ; Ahmadi, A ; Babaie Zadeh, M ; Sharif University of Technology
2017
Abstract
This paper presents a novel technique to discover double JPEG compression traces. Existing detectors only operate in a scenario that the image under investigation is explicitly available in JPEG format. Consequently, if quantization information of JPEG files is unknown, their performance dramatically degrades. Our method addresses both forensic scenarios which results in a fresh perceptual detection pipeline. We suggest a dimensionality reduction algorithm to visualize behaviors of a big database including various single and double compressed images. Based on intuitions of visualization, three bottom-up, top-down and combined top-down/bottom-up learning strategies are proposed. Our tool...
A part-level learning strategy for JPEG image recompression detection
, Article Multimedia Tools and Applications ; Volume 80, Issue 8 , 2021 , Pages 12235-12247 ; 13807501 (ISSN) ; Razzazi, F ; Behrad, A ; Ahmadi, A ; Babaie Zadeh, M ; Sharif University of Technology
Springer
2021
Abstract
Recompression is a prevalent form of multimedia content manipulation. Different approaches have been developed to detect this kind of alteration for digital images of well-known JPEG format. However, they are either limited in performance or complex. These problems may arise from different quality level options of JPEG compression standard and their combinations after recompression. Inspired from semantic and perceptual analyses, in this paper, we suggest a part-level middle-out learning strategy to detect double compression via an architecturally efficient classifier. We first demonstrate that singly and doubly compressed data with different JPEG coder settings lie in a feature space...