Sharif Digital Repository

Ionization chamber is used in radiotherapy for to get precise information from amount activity of radionuclide. Ionization chamber filled with Argon is used to measure the activity of brachytherapy radionuclide. This device measures the activity according to the produced current by the incident radiation. In order to obtain the precise activity of the radionuclide, it is necessary to the precise amount of the device calibration factor which relates the amount of the produced current to the activity. Because of little access to standard radionuclide and for appointing the activity of unknown samples, ionization chamber calibration is done indirectly and with the help of the simulation of the... 

Wind power is site dependent and is by nature partially dispatchable. Furthermore, good wind sites are far from grid. Due to these problems, and along with the existing limitations in the transmission networks, a comprehensive analysis over an extended time is needed to properly explore all potential wind sites for wind capacity allocation. This problem is computationally expensive and decomposition methods are required to break down this problem. Here Benders decomposition approach is used, which is a popular technique for solving large-scale problems, to decompose the original problem into a master and a subproblem. The master problem is a linear problem, which allocates wind capacity to... 

In the past few years, many research works on the controllable integration of metal nanoparticles and metal-organic frameworks were done, since the obtained composite material shows a synergism effect in catalysis and photocatalysis, drug delivery applications, gas, and energy storage, as well as sensing. For the first time, in this study, we employed template-assisted growth to synthesize Au-HKUST-1 Nanocomposite. XRD analysis entirely confirms that employing this strategy in synthesizing Au-HKUST-1 was wholly successful, and the plasmonic properties of this nanostructure were studied via UV-visible spectroscopy. In the course of synthesis, gold nanoparticles with 70nm diameter were... 

Single nucleotide polymorphs, There are changes caused by a mutation in a nucleotide in the Dena sequence. Mononucleotide polymorphisms are the most common type of genetic variation. Some of these changes have little or no effect on cells, while others cause significant changes in the expression of cell genes that can lead to disease or resistance to certain diseases. Because of the importance of these changes and their effect on cell function, the relationships between these changes are also important. Over the past decade, thousands of single disease-related mononucleotide polymorphisms have been identified in genome-related studies. Studies in this field have shown that the expression of... 

Age-related macular degeneration (AMD) is the most common cause of vision loss in those aged over 50. There are two main types of AMD, Wet and Dry form. Wet AMD is more severe though more treatable. There are three conventional treatments for AMD including laser therapy, surgery and intravitreal injection of anti-VEGF into the eye. Delivery of drugs to the posterior segment of the eye is still challenging and several implants and devices are currently under investigation for their ability to stimulate the retina, producing visual percepts. The application of intravitreal bevacizumab (Avastin) has expanded tremendously from the time of its introduction into ophthalmic care since 3 years ago.... 

In analyzing the structural organization of many real-world networks, identifying important nodes has been a fundamental problem. The network centrality concept deals with the assessment of the relative importance of network nodes based on specific criteria. Central nodes can play significant roles on the spread of influence and idea in social networks, the user activity in mobile phone networks, the contagion process in biological networks, and the bottlenecks in communication networks. High computational cost and the requirement of full knowledge about the network topology are the most significant obstacles for applying the general concept of network centrality to large real-world social... 

As a robust and accurate classification of tumors is necessary for successful treatment of cancer, classification of DNA microarray data has been widely used in successful diagnosis of cancers and some other biological diseases. But the main challenge in classification of microarray data is the extreme asymmetry between the dimensionality of features (usually thousands or even tens of thousands of genes) and that of tissues (few hundreds of samples). Because of such curse of dimensionality, a class prediction model could be very successful in classifying one type of dataset but may fail to perform well in some other ones. Overfitting is another problem that prevents conventional learning... 

Studies show that a large proportion of sent emails are spam. Spam is one of the major problems of e-mail users that result in wasting time and cost. To overcome this problem different ways are used, one of the best ways is detecting spam based on their contents. Separating legitimate e-mails and spam within their contents can be categorized as text classification. So machine-learning approaches are extremely applied in text classification, that machine-learning algorithms can be used for spam classification. However, in the majority of these algorithms, training phase is in a batch. Whereas using incremental learning algorithms is preferred in many applications, especially spam detections.... 

In single service wireless cellular networks, two types of call are defined; new call and handoff call. New call blocking probability and handoff call dropping probability are two major parameters of QoS. Some call admission control schemes are proposed for handling new and handoff calls in the cell for keeping these QoS parameters under suitable values. In this work, we will introduce some call admission control schemes and will show performance analysis, advantages and disadvantages of them (under different channel holding times and same channel holding times for new calls and handoff calls). Then we will focus on two schemes and based on their ideas, we will propose a new call admission... 

Decision making often has different effects and results with unequal importance. Most of classifiers try to minimize the rate of misclassified instances. These classifiers assume equal costs for different misclassification types. However, this assumption is not true in many real world problems and different misclassification types have different costs. These differences can be applied by introducing the cost in the process of learning. In this manner, total cost of misclassification will be the evaluation metric of classification. In order to apply this metric to the problems, new learning algorithms are needed. Cost-sensitive learning is the related area of machine learning which deals with... 

Cellular learning automata (CLA) is a distributed computational model that is introduced recently. This model is combination of cellular automata (CA) and learning automata (LA) and is used in many applications such as image processing, channel assignment in cellular networks, VLSI placement, rumor diffusion and modeling of commerce networks, and obtained acceptable results in these applications. This model consists of computational units called cells and each cell has one or more learning automata. In each stage, each automaton chooses an action from its actions set and applies it to the environment. Each cell has some neighboring cells that constitute its local environment. The local rule... 

Worldwide interoperability for Microwave Access (WiMAX) is one of the most dominant cell-based broadband wireless metropolitan access technologies. Packet scheduling algorithm specifies the packet transmission order. In WiMAX standard, packet scheduling algorithm is not defined and its efficient design is left for developers and researchers. The existing researches in the scope of uplink packet scheduling, which is the most challenging packet scheduling scheme, consider only one cell. However the uplink available resources might not be enough when there are many packets that should be scheduled. To solve this problem, we propose an algorithm that uses the load balancing mechanisms that are... 

Nowadays wireless technology is widespread all over the world, because of extensive and successful application of low cost, low power, multifunctional tiny sensor nodes that can be grouped to make up of a wireless sensor network (WSN). Some of Wireless sensor network technologies include Zigbee, EnOcean, Personal area network, Ultra-Wideband and Bluetooth which this thesis focuses on the last one. Scalability, mobility, reliability and energy efficiency are some of the requirements and challenges of WSNs, which among them reliability and reducing energy consumption are two important objectives in wireless sensor networks. Since each sensor node has limited energy to consume, overcoming the... 

Nowadays, multi-agent systems as part of the distributed artificial intelligence play an important role in modeling and solving complex industrial and commercial problems. They have distinguishing characteristics such as distributiveness (spatial, temporal, semantic, or functional distribution), robustness, parallel processing, etc. One of the capabilities that can be added to this system is the learning capability. It can help the system to adapt itself to the new environment. This paper proposed a method for the problem of credit assignment in multi-agent domain. Solving the multi-agent credit assignment problem, one can expect individual learning for a single agent in systems of... 

Text classification is one if the widest and most important applications in data mining. Because of the huge number of features in these applications, a method for dimensionality reduction is needed before applying the classification algorithm. Various number of methods for dimensionality reduction and feature selection are proposed. Feature selection based on feature ranking has received much attention by researchers. The major reasons are their scalability, ease of use, and fast computation. Feature ranking methods are divided to different categories and use different measures for scoring features. Recently ensemble methods have entered the field of ranking, and achieved more accuracy... 

Classification is one of the most important problems in machine learning area. Reliable and successful classification is essential for diagnosing patients for further treatment. In many applications such as bioinformatics unlabeled data is abundant and available. However labeling data is much more difficult and expensive to obtain. This dissertation presents a novel transductive approach for the development of robust microarray data classification. The transduction problem is to estimate the value of classification function at the given points in the working set. This contrasts with the standard inductive learning problem of estimating the classification method at all possible values and... 

One of the standing problems in Molecular Biology and Bioinformatics is uncovering signaling pathways. Discovering the causes of many cancer-like diseases and developing better treatments for them, requires a better understanding of the behavior of cellular processes. Understanding signaling pathways can help to realize cellular processes. Due to the fast increase of possible signaling pathways when the number of components increases, the problem seems to have an inherent complexity. One of the recent methods for generating data relating to such networks is RNA interference technique. In this thesis we use data which are provided by this method. We propose two methods to infer signaling... 

Mobile ad hoc networks (MANETs) are networks which consist entirely of mobile nodes, placed together in ad hoc manner, i.e. with minimal prior planning. In these networks, all nodes have routing capabilities and forward data packets for other nodes. Nodes can enter or leave the network at any time and may also be mobile. Hence, the network topology changes frequently. There are lots of challenges in these networks, which make routing to be a hard task. These challenges arise from the dynamic and unplanned nature of these networks such as unreliability of wireless communication, limited resources available in terms of bandwidth, processing capacity, network size, and etc. Due to these... 

Wireless sensor networks have a wide range of applications in the world. In most of the applications, collected data is not usable without the knowledge about the localization of events. There are two approaches to specifying the location of a sensor: using hardware solutions such as GPS, which is an expensive solution, and using the localization algorithm. Therefore, localization has an important role in sensor networks. Most of the current localization algorithms are non-adaptive and proposed for fixed wireless sensor networks. Recently, adaptive localization algorithms have been considered because of their simple implementation, fast result and low computation overhead for each node. In... 

As part of the definition of concept drift as an online learning task, concepts change or drift as time goes by. Consequently, these changes have to be monitored and their implication for learning should be recognized. An example of concept drift detection is needed for spam filtering problem. An effective spam filter must be able to handle various changes, including changes in the user’s criteria for filtering spam, changes in message topics, and changes caused by the people sending spam messages. In this thesis, spam detection system has been considered in which emails are given sequentially and learns them one by one. As we mentioned, the purpose of this thesis is detecting spam emails....