Sharif Digital Repository

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... 

One of the most important factors of reducing durability of concrete structures is corrosion of steel reinforcement in concrete. In this paper, corrosion behavior of reinforcing steel in concrete is investigated in two different methods of protection based on neural network. As regard the first method, pozzolanic additives with optimized percentage were added to Concrete mix design (the percentage of these additives are 25% Weight of cement of fly ash, Micro silica with 10 percent of weight of cement and 25% of Blast Furnace slag weight of cement). In the second approach of protection, 0/5 percent weight of cement of ferrogard 901 inhibitor is added to basic mix concrete design and the... 

One of the most important issues among defense is the increasing of the defense power using present facilities. Therefore, optimal setting and arrangement of equipment by considering different air-to-earth attack of enemy without knowing of properties and capabilities of available systems may not be possible. So, using defense equipment considering properties of them, and paying attention to existence restrictions and effective elements can have an effective role with the design of suitable algorithm.The main purposes of this thesis are: maximization of the efficiency of a defense system against. aerial invader targets, achieving the best arrangement of defense equipment based on suggested... 

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... 

In this research, an intelligent and integrated system for elderly fall detection monitoring based on CCTV cameras has been designed and implemented. The system consists of three main components: a fall detection device, a central server, and a mobile application. The fall detection algorithm runs in real time on a Raspberry Pi 4B board and combines classical methods with deep learning techniques. Specifically, an SVM model is employed in the classical stage, while Convolutional Neural Networks (CNN) and MoveNet models are utilized in the deep learning stage to enhance accuracy. To ensure security and privacy, the system incorporates end-to-end encryption and secure HTTPS-based... 

Graph learning problem aims to infer a meaningful graph structure from a dataset that can effectively represent the relationships among its data points. With the emergence of graph signal processing, efficient methods for graph learning have been introduced, which leverage the smoothness assumption of signals to learn the underlying graph. However, these methods typically require access to all data points, while in practical applications this is not always feasible. In this Master's Thesis, an optimization problem is proposed that simultaneously learns the underlying graph and estimates the missing data points from a dataset of graph signals. To solve the proposed optimization problem, a... 

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... 

In the current situation and considering the economic conditions, entrepreneurship and self-employment are important factors of business growth. To prepare people in this field, there is a need for effective training that can motivate people. Identifying the effective methods and different dimensions of the entrepreneurship education framework that can lead to setting up a successful program for training people and facilitate the way to achieve the goal of education is one of the important goals of this research. By studying the literature from 2010 onwards, this research systematically examined 96 articles and tried to improve the framework of entrepreneurship education that was stated in... 

Among various neutron sources such as fission reactors, radioisotopic sources, photoneutron reactions, and others, the spallation neutron source has attracted significant attention due to advantages like high flux, notable neutron yield, and a broad energy spectrum. The spallation process occurs when high-energy light particles, typically protons in the order of giga-electron volts, collide with heavy targets such as lead or mercury. This interaction produces a large number of neutrons, protons, deuterons, pions, and other particles. To increase neutron production efficiency and achieve a desirable energy spectrum, a target system composed of a target, moderator, and reflector is used. In...