Sentiment-Based Topic Analysis on Product Demand Prediction: Pre-Release and Post-Release Study

, M.Sc. Thesis Sharif University of Technology Behrad, Hossein (Author) ; 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 Behrad, Amin (Author) ; 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...

An approach to optimal dispatch of bilateral electricity contracts regarding voltage stability

, Article Power Plants and Power Systems Control 2006 ; Volume 39, Issue 7 , 2007 , Pages 65-70 ; 9780080466200 (ISBN) Mozafari, B ; Ranjbar, A. M ; Mozafari, A ; Amraee, T ; Sharif University of Technology

Elsevier Ltd 2007

Abstract

This chapter proposes a methodology for optimal dispatch of bilateral electricity contracts, which may endanger the system voltage stability in light of short-term operational planning of a deregulated power system. In this framework the value that each owner of a transaction is willing to pay reflects how much the electricity contract is important to be implemented physically. The proposed model dispatches optimally the bilateral transactions regarding the prices offered by owners of bilateral contracts for reactive power and transmission capacity utilization in one hand and, the total operational costs of reactive power resources in the other hand. The model also includes the limits...

An approach to optimal dispatch of bilateral electricity contracts regarding voltage stability

, Article IFAC Proceedings Volumes (IFAC-PapersOnline) ; Volume 5, Issue PART 1 , 2006 , Pages 65-70 ; 14746670 (ISSN); 9783902661081 (ISBN) Mozafari, B ; Ranjbar, A. M ; Mozafari, A ; Amraee, T ; Sharif University of Technology

IFAC Secretariat 2006

Abstract

This paper proposes a methodology for optimal dispatch of bilateral electricity contracts, which may endanger the system voltage stability in light of short-term operational planning of a deregulated power system. In this framework the value that each owner of a transaction is willing to pay will reflect how much the electricity contract is important to be implemented physically. The proposed model dispatches optimally the bilateral transactions regarding the prices offered by owners of bilateral contracts for reactive power and transmission capacity utilization in one hand and, the total operational costs of reactive power resources in the other hand. The model also includes the limits...

Reactive power management in a deregulated power system with considering voltage stability: Particle swarm optimisation approach

, Article Eighteenth International Conference and Exhibition on Electricity Distribution, CIRED 2005, Technical Reports - Session 1: Network Components, Turin, 6 June 2005 through 9 June 2005 ; Volume 6, Issue 2005-11034 , 2005 , Pages 55-58 ; 05379989 (ISSN) Mozafari, B ; Ranjbar, A. M ; Shirani, A. R ; Mozafari, A ; Sharif University of Technology

2005

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) Taimori, A ; 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) Taimori, A ; 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) Taimori, A ; 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) Taimori, A ; 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) Taimori, A ; 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...

Improvement of Corrosion Resistance of Concrete Sewer Pipes Against Microbial Corrosion

, M.Sc. Thesis Sharif University of Technology Mozafari, Ali (Author) ; Afshar, Abdollah (Supervisor)

Abstract

Microbiologically Influenced Corrosion (MIC) of concrete sewer ptpes and wastewater collection systems has been reported in many places of the world. Recently, numerous copper compounds have been used for bacterial growth control in sewer pipes. In this thesis, bath parameterswere optimized in order to maximize copper osmosis to the porous concrete matrix.Concrete pipes were electrochemically coated inCopper Lactate bath in a constant current mode (1=0.6 A), while temperature was set to 25, 50, 75 and 95
°Cand pH to 9,10 and 11. Specimens were then characterized by scanning electron

microscopy, optical microscopy, XRD andAAS. Copper Osmosis was highest in pH=9 and...

Solving the Network Design Problem by Surrogate Functions and Lower and Upper Bounds on the Objective Function at Different Levels of Budget

, M.Sc. Thesis Sharif University of Technology Mozafari, Hamid (Author) ; Poorzahedy, Hossein (Supervisor)

Abstract

The purpose of this research is to provide a method for finding a “good” solution to the network design problem with less computational efforts, faster than the existing conventional methods of solving this problem. Network design problem is the problem of selecting a subset of projects from a set of alternative projects so that to optimize the objective function (e.g., the total travel time in the network) subject to the set of existing constraints (e.g., budget). Due to the combinatorial and non-convex nature of the problem, its solution could be very cumbersome and time-consuming. Various methods have been proposed to solve this problem efficiently, providing good solutions at high...

Seizure Detection in Generalized and Focal Seizure from EEG Signals

, M.Sc. Thesis Sharif University of Technology Mozafari, Mohsen (Author) ; Hajipour, Sepideh (Supervisor)

Abstract

Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so...

Effects of regeneration heat exchanger on entropy, electricity cost, and environmental pollution produced by micro gas turbine system

, Article International Journal of Green Energy ; Volume 9, Issue 1 , Jan , 2012 , Pages 51-70 ; 15435075 (ISSN) Mozafari, A ; Ehyaei, M. A ; Sharif University of Technology

2012

Abstract

A new method has been employed in this research that optimizes a power generation system by maximizing the first and second law efficiencies and minimizing the entropy generation. Mass flow rates of pollutants and related external social cost of air pollution have been considered in estimating the electricity production cost. The effects of regenerative and CHP heat exchangers on power production, efficiencies, and production cost have been evaluated. The results show that a single regenerative heat exchanger lowers NOx, CO, and CO 2 emissions by 15%, 40%, and 0.4%, respectively, and decreases the electricity production cost by nearly 18%. A single CHP heat exchanger has little influence on...

A new type of hybrid features for human detection

, Article Proceedings - 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012 ; 2012 , Pages 237-240 ; 9781467329514 (ISBN) Mozafari, A. S ; Jamzad, M ; Sharif University of Technology

2012

Abstract

Human detection is one of the hard problems in object detection field. There are many challenges like variation in human pose, different clothes, non-uniform illumination, cluttered background and occlusion which make this problem much harder than other object detection problems. Defining good features, which can be robust to this wide range of variations, is still an open issue in this field. To overcome this challenge, in this paper we proposed a new set of hybrid features. We combined the Histogram of Oriented Gradient (HOG) with the new features called Histogram of Small Edges (HOSE) which is introduced in this paper. These two kinds of features have two different approaches for...

Automatic epileptic seizure detection in a mixed generalized and focal seizure dataset

, Article 26th National and 4th International Iranian Conference on Biomedical Engineering, ICBME 2019, 27 November 2019 through 28 November 2019 ; 2019 , Pages 172-176 ; 9781728156637 (ISBN) Mozafari, M ; Hajipour Sardouie, S ; Sharif University of Technology

Institute of Electrical and Electronics Engineers Inc 2019

Abstract

Detection of seizure periods in an epileptic patient is an important part of health care. However, due to the variety in types of seizures and location of them, real-time seizure detection is not straight forward. In this paper, we propose a method for seizure detection from EEG signals in datasets which have both generalized and focal seizures. The proposed method is useful in the situations that we have no prior knowledge about the location of the patient's seizure and the pattern of evolution of seizure location. In the proposed method, first, the artifacts are automatically reduced by Blind Source Separation (BSS) methods. Then, the channels are clustered into two clusters. After that,...

Cluster-based adaptive SVM: a latent subdomains discovery method for domain adaptation problems

, Article Computer Vision and Image Understanding ; Volume 162 , 2017 , Pages 116-134 ; 10773142 (ISSN) Sadat Mozafari, A ; Jamzad, M ; Sharif University of Technology

2017

Abstract

Machine learning algorithms often suffer from good generalization in testing domains especially when the training (source) and test (target) domains do not have similar distributions. To address this problem, several domain adaptation techniques have been proposed to improve the performance of the learning algorithms when they face accuracy degradation caused by the domain shift problem. In this paper, we focus on the non-homogeneous distributed target domains and propose a new latent subdomain discovery model to divide the target domain into subdomains while adapting them. It is expected that applying adaptation on subdomains increase the rate of detection in comparing with the situation...

Modeling and Control of gas turbine combustor with dynamic and Adaptive Neural networks

, Article International Journal of Engineering, Transactions B: Applications ; Volume 21, Issue 1 , 2008 , Pages 71-84 ; 1728-144X (ISSN) Mozafari, A. A ; Lahroodi, M ; Sharif University of Technology

Materials and Energy Research Center 2008

Abstract

This paper presents an Artificial Neural Network (ANN)-based modeling technique for prediction of outlet temperature, pressure and mass flow rate of gas turbine combustor. Results obtained by present modeling were compared with those obtained by experiment. The results showed the effectiveness and capability of the proposed modeling technique with reasonable accuracies of about 95 percent. This paper describes a nonlinear SVFAC (State Vector Feedback Adaptive Control) controller scheme for gas turbine combustor. In order to achieve the satisfied control performance, we have to consider the effect of nonlinear factors contained in controller. The controller is adaptively trained to force the...

An experimental and theoretical study of the effects of excess air ratio and waste gate opening pressure threshold on NOx emission and performance in a turbocharged CNG SI engine

, Article International Journal of Engineering, Transactions B: Applications ; Volume 28, Issue 2 , March , 2015 , Pages 251-260 ; 1728-144X (ISSN) Kharazmi, S ; Benisi, A. H ; Mozafari ; Sharif University of Technology

Materials and Energy Research Center 2015

Abstract

In this research, effects of excess air ratio and waste gate opening pressure threshold on NOx emission and performance in a turbocharged CNG SI engine are studied experimentally at 13-mode ECE-R49 test cycle. The engine power, boost ratio and charge air temperature are investigated experimentally at the cycle for different waste gate pressure thresholds. A code is developed in MATLAB environment for predicting engine performance and NOx and the results are validated with the research experiments. The effects of excess air ratio on the engine indicated power and specific fuel consumption as well as NOx emission are numerically investigated at WOT by the code. NOx emission of WOT is max at...

Towards IoT-enabled multimodal mental stress monitoring

, Article 2020 International Conference on Omni-layer Intelligent Systems, COINS 2020, 31 August 2020 through 2 September 2020 ; 2020 Mozafari, M ; Firouzi, F ; Farahani, B ; Sharif University of Technology

Institute of Electrical and Electronics Engineers Inc 2020

Abstract

Stress is a body's natural way of responding to any kind of demand or challenge that everyone experiences from time to time. Although short-Term stress typically does not impose a health burden, exposure to prolonged stress can lead to significant adverse physiological and behavioral changes. Coping with the impact of stress is a challenging task and in this context, stress assessment is essential in preventing detrimental long-Term effects. The public embracement of connected wearable Internet of Things (IoT) devices, as well as the proliferation of Artificial Intelligence (AI) and Machine Learning (ML) technologies, have generated new opportunities for personalized stress tracking and...