Sharif Digital Repository

Water resources globally are facing significant stress due to overexploitation. In recent decades, the balance between the available water resources and the amount of water consumption in the catchment area of Lake Urmia due to human factors and natural phenomena like climate change has been severely disrupted. In the last 20 years, the cumulative impact of these factors has led to a dramatic reduction in Lake Urmia’s water level by over 8 meters, with a concomitant rise in water salinity. To address the hydrodynamic challenges of Lake Urmia, it is crucial to understand the upstream watersheds. Thirteen perennial rivers, primarily the Zarinehroud and Simineroud, fulfill the water rights... 

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... 

The increasing demand for communication bandwidth and limited spectrum availability have heightened the complexity of radio front-end circuits in IoT applications. Achieving spectral efficiency is a key challenge, particularly for IoT devices operating at specific frequency bands such as 315 MHz, 433 MHz, 868 MHz, and 915 MHz.Due to the limited linearity of the transmit path, harmonic distortion components, known as counter intermodulation (CIM) products, are generated. These CIM products can directly fall into the receiver (RX) band or enter it via cross-modulation, thereby degrading the frequency division performance. Additionally, CIM products can interfere with protected bands, violating... 

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... 

The Bullwhip effect is a phenomenon that refers to the amplification of demand variance as one moves upstream in a supply chain. This effect imposes additional costs on the supply chain and complicates inventory planning. Several factors contribute to the emergence of this phenomenon, one of which is demand forecasting. Since the demand faced by each level of the supply chain is uncertain, every level must first forecast demand in order to plan its inventory and meet customer requirements. However, this very process of forecasting contributes to the bullwhip effect. In this study, we investigate the impact of machine learning and deep learning forecasting methods, along with their...