Sharif Digital Repository

The use of hyperspectral images to detect food fraud has become popular and it is necessary to develop chemometrics methods for analyzing the data from these images. Additionally, food authenticity has become a major challenge, and the focus of this thesis is on developing multivariate methods in chemometrics to extract useful information from data obtained from food authenticity verification using hyperspectral imaging (HSI). This thesis consists of six chapters. In the first chapter, a brief introduction to the fundamentals of hyperspectral imaging and food authenticity verification is presented. In the second chapter, the data structure of these images and chemometric methods including... 

The main objective of this study is to evaluate the accuracy and performance of the vorticity confinement (VC) method implemented in a second-order finite volume flow solver for solving two-dimensional compressible mixing layer flows. The spatial discretization of the system of governing equations is performed by a second-order central difference finite volume method and a fourth-order Runge-Kutta method is used for the time integration. To have a stable solution, the second- and fourth-order numerical dissipation terms are applied. At first, two problems, namely, the advection of an isentropic vortex and the shock-vortex interaction are numerically solved and the effects of the confinement... 

In recent years, with increasing spills of oil and related petroleum products in the marine environment , the need for source identification of crude oil is increasing rapidly. Oil spill can have serious biological and economic impacts. There are many oil tankers on the surface of the sea and 0.68х109 kg crude oil spilled into soil per year . The source identification of oil spills can be a considerable challenge so these studies analytically and environmentally are important. The purpose of this study was to provide an update of the state-of-the-art of oil fingerprinting techniques to demonstrate the use of a rapid, inexpensive and useful technique for distinguishing between crude oils. In... 

We present a deep neural network to classify dermatological disease from patient images. Using self-supervised learning method we have utilized large amount of unlabeled data. We have pre-trained our model on 27000 dermoscopic images gathered from razi hospital, the best dermatological hospital in Iran, along with 33000 images from ISIC 2020 dataset. We have evaluated our model performance in semi-supervised and transfer learning approaches. Our experiments show that using this approach can improve model accuracy and PRC up to 20 percent on semi-supervised setting. The results also show that pretraining can improve classification PRC up to 20 percent on transfer learning task on HAM10000... 

Based on the importance of DNA/RNA binding proteins in different cellular processes, finding binding sites of them play crucial role in many applications, like designing drug/vaccine, designing protein, and cancer control. Many studies target this issue and try to improve the prediction accuracy with three strategies: complex neural-network structures, various types of inputs, and ML methods to extract input features. But due to the growing volume of sequences, these methods face serious processing challenges. So, this paper presents KDeep, based on CNN-LSTM and the primary form of DNA/RNA sequences as input. As the key feature improving the prediction accuracy, we propose a new encoding... 

Speech synthesis and its applications have been very attractive recently. The main purpose of this technique is to produce a speech signal with natural characteristics of human speech like prosody and emotion. Among all existing methods for speech synthesis, statistical parametric speech synthesis methods are more promising because ofhigher flexibility in comparison to other methods. One of the applications of speech synthesis is speech to speech translation. In these systems, the generated voice in target language should have the same characteristics as the input voice in source language. The main purpose of this research is to review and evaluate the cross lingual speaker adaptation... 

Surface piercing propellers are particular type of supercavitating propellers that are commonly used for High-speed vessels. Most studies on this type of propellers has been investigating the hydrodynamic forces. But in recent years with increase in SPPs diameter used in vessels, structural analysis of this type of propellers is considered. For this purpose, studies on the stresses exerted on the propeller structures under load is done with the help of Hydro elastic methods. In this type of analysis, structura of propeller is intended to be flexible and Displacements under pressure checked and Tensions resulting from it are studied.
The present Thesis using ANSYS software to analyze a... 

Pricing plays an important and essential role in the profit and income of companies. The importance of pricing is not only related to its role in the company's profitability, but it also changes the customer's understanding and loyalty towards the company and can create the company's reputation or destroy it. Determining the right price will increase product sales and increase customer loyalty and create a competitive advantage for the company. One of the most important and influential variables in product pricing is the amount of demand. The main challenge of companies for product pricing is the uncertainty in their demand. In order to deal with this problem, data-driven pricing is used.... 

The increasing demand for autonomous vehicles and reliable communication protocols and hardware interfaces, such as CAN bus and USB, underscores the necessity for stable clock sources that maintain a low temperature coefficient (TC) over wide temperature ranges. This demand is particularly emphasized in applications such as wearables, network sensors, downhole devices, WSNs, and IoT, where long-lasting battery life and frequency-stable clock sources over a broad temperature range (e.g. -20 °C to 100 °C) are crucial. Traditionally, variations in frequency caused by temperature have been mitigated by employing off-chip components like crystals or ceramic based oscillators, but this approach... 

Autonomous vehicles, as an integral part of intelligent transportation systems, will play a significant role in the future of transportation services. These vehicles have a high potential to improve road traffic capacity and the efficiency of transportation systems. One type of autonomous vehicle is the connected and autonomous vehicle (CAV), which can communicate with each other, roadside units, traffic control signals, and other infrastructures or devices. This study investigates the impact of autonomous vehicles and connected and autonomous vehicles on the traffic flow of the Tehran-Karaj freeway and vice versa, under various penetration rates and in a mixed traffic environment. In this... 

Noise or noise pollution, is defined as an unwanted sound, produced mostly by motor vehicles in urban areas. If the noise exceeds its limit, adverse effects on users and citizens are expected. Thus the assessment of the noise level and its comparison with allowable values is mandatory. Traffic induced noise depends upon different factors such as traffic, weather, and, sound barriers. Noise pollution study has a long history all over the world. Many studies, mostly representing the outdoor noise pollution models, have been done in recent years. This paper presents an assessment of traffic-induced noise in a heavily traveled tunnel, locally referred to as Resalat tunnel, which is located in...