Sharif Digital Repository

Genetic heterogeneity within a tumor, which occurs during cancer evolution, is one of the reasons for treatment failure and increased chances of drug resistance. Cancer cells initially derive from a mutated progenitor cell, resulting in shared mutated genes. Throughout the course of tumor formation and progression, the occurrence of new mutations is possible, leading to the generation of cancer cells with various mutated genes. An appropriate approach is to identify the sequence of mutations that have occurred in the tumor, which can be inferred from single-cell sequencing data. Singlecell data provides valuable information about branching events in the evolution of a cancerous tumor. In... 

Occurrence of scouring around the seabed pipelines can lead to pipe failure and pose a serious threat to the marine environment, economic losses and waste of oil and gas. Therefore, to prevent the occurrence of scouring, by simulating this phenomenon and identifying the parameters affecting it, we can help to design a more efficient placement of pipes in the seabed. Various methods such as potential flow theory and turbulent single-phase and two-phase models have been proposed to simulate this phenomenon. The purpose of this article is to simulate and investigate the effective parameters of this phenomenon by combining computational fluid dynamics and separate elements. The innovation of... 

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... 

Creating any project requires investment, time, and resources. Many construction projects have failed despite considerable money invested in them. A common cause of this failure is improper planning. One of the most important parts of project planning is the feasibility study which is missing in many projects in Iran. However, the fundamental reasons that prevent construction project managers and owners from efficiently performing feasibility studies in their projects have not been investigated in the country yet. In this study, we aim to evaluate this aspect of the construction projects in the country by investigating the structure of feasibility studies in the building construction... 

The first step in improving traffic safety and reducing damage to road users is to evaluate traffic safety and identify black spots, which is possible in statistics-based methods using traffic accident data from previous years. One of the disadvantages of statistical methods is the existence of a series of limitations in collecting accident data and spending a lot of time and money. The purpose of this research is to provide a technique to evaluate traffic safety and estimate the number of accidents using the traffic conflict technique and extreme value theory modeling. The method of conducting this research is based on image processing, recording, and analysis of the conflict index of two... 

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... 

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... 

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.... 

In the last decade, Intrusion Detection Systems has attracted attention due to their importance in network security, but still they've shortcomings. Generating a lot of low level alerts is the main problem. Many of these alerts are actually false positives. One suggested solution is Alert Correlation Analysis. Because of false positives alert correlation techniques are not able to build accurate scenarios, but the accuracy of alerts can be verified with the aid of the information logged in the host systems. In this dissertation after surveying the current alert correlation techniques, a model will be introduced to effectively verify the generated alerts and to apply correlation techniques to... 

Web service plays an important role in software development. Since Web service can be used in small scale and large scale environments, many different entities may participate in each interaction. Regarding situation, a lot of information is available around these entities. This kind of information is called context. In some cases, context information is used to provide outputs which are called context-aware systems.
The main challenging issue in producing a context-aware system is context modeling and sharing. Semantic Web and its ontology languages are the most promising solution to context modeling. In pervasive computing many ontologies are proposed for this purpose, but little... 

Protein multiple sequence alignment is one of important problems in biology which no polynomial time algorithms is known for it yet. Due to importance of this problem, several methods have been developed to find an approximate solution for it. Approximation algorithms, Evolutionary algorithms and Probabilistic methods are some of these methods. According to evolutionary nature of this problem, evolutionary algorithms and specifically genetic algorithms can be a potential good solution method for this problem. In this project we have a survey on using genetic algorithms for this problem and after mentioning benefits and draw backs of existing methods, we develop a method for improving one of... 

Today many applications produce data stream that grow continuously over time. Classification is an important task in mining this data. One of the major challenges in classification of data streams is that the underlying concept of data may change over time; this needs updating the classification model. Many of traditional classification algorithms are adapted for classifying data streams. Evolutionary algorithms are stochastic methods that have been successfully applied to a wide range of optimization problems. Harmony search is a new evolutionary algorithm that convergence to global optimum and can be applied to discrete and continuous data. The evolutionary nature of classifying data... 

Sensor Observation Service (SOS) which is defined by Open Geospatial Consortium (OGC) Sensor Web Enablement group is a Web service specification in order to standardize the way sensors and sensor data are discovered and accessed on the Sensor Web. Multiple instances of this service can be implemented around the world, providing huge amount of data every moment. Each of these services operates in specific domain of knowledge (thematic), spatial and temporal dimensions. One way to reveal the underlying data over all of them is to provide an architecture for data integration to allow the user to query sensor data without the knowledge of the infrastructure components. In this research, a novel... 

Semantic relation extraction is one of the challenging information extraction’s steps. The main task of relation extraction is finding of relationships in text corpus using Machine Learning methods. There are plenty of usage for relation extraction such as providing information for Question Answering systems, protein interaction detection in biomedical corpora and ontology population. There are many research take placed in this area in which relation extraction task is defined as a classification problem and in most of them, this problem is solved by SVM method. Results of recent research imply that current state of relation extraction methods are far from appropriate state that is... 

Recently, data stream has been popular in many contexts like click sequences in web pages, obtained data from sensor networks and satellite data. A data stream is an ordered list of points that should be used once. Clustering of these kinds of data is one of the most difficult issues in data mining. Due to the high amount of data, the traditional clustering algorithms are not suitable for this family of problems. Many data stream clustering algorithms have been proposed in recent years considered the scalability (largeness) of data, but most of them didn’t attend to the following issues. •The quality of clustering can be bad over the time. •Some of the algorithms cannot handle arbitrary...