Sharif Digital Repository

Simulation has numerous applications, for instance in training. Training for different types of surgery with the use of simulation is very common today. During the surgery, the surgeon tears and cuts fine tissues. Modeling this process has always been one of the most challenging areas in the field of simulation design. Triangular meshing, especially Delaunay triangulation is often used to simulate a twodimensional surface. Now, if we want to simulate the process of cutting that surface, we need to modify the mesh in a real-time manner and simulate the cutting process by adding, removing, or changing the vertices, edges and triangles. therefore, to re-design the mesh according to the cut, we... 

Matching points is an important issue in the world of algorithms and has attracted the attention of many researchers with its wide applications. In recent years, researchers have proposed various issues in the field of matching points and looked at it from different perspectives. In recent years, this issue, like other issues, entered the online world and tried to be investigated online. In this thesis, we examine some examples of models of this problem that are projected on the plane and online and try to find a way to solve them or introduce a lower bound for them  

We study a class of optimization network problems on pairs of structures. In particular, given n pairs of points P = f(p1; q1); (p2; q2); : : : ; (pn; qn)g, in the plane or in general metric space, the goal is to color points of each pair, one red and the other blue, so as a given cost function on the red points and blue points is optimized. The cost functions studied previously are MST, TSP, and matching. In this work, we consider a new cost function; i.e., the diameter of each colored point set, and present efficient algorithms to solve the problem according to some objective functions  

The edge coloring problem is one of the most fundamental problems in graph theory. In this problem, the task is to assign colors to edges so that no two incident edges have the same color. Although finding an optimal edge coloring is NP-hard, Vizing’s theorem asserts that ∆+1 colors are always sufficient, denoting the maximum degree in the graph by ∆.Due to significant increase in the volume of data, for most problems, storing the whole data is not possible. This had led to emergence of new models of processing data such as data streaming model. In semi-streaming model the input graph is represented as a stream of edges, and the storage space of an algorithm is bounded by O(n. polylog n). So... 

Network optimization problems are fundamental and widely used in computer sci- ence. One of the recent researches in this field has focused on network stabilization, which is posed as follows: in a network with 2n servers, each server has an identical twin with exactly the same contents. The goal is to partition these 2n servers into two networks such that no server is in the same network as its twin, and the objective cost function in these two networks is optimized. This stabilization method ensures that if one network experiences problems, the other can continue to operate independently. This type of network stabilization was first proposed by Arkin et al. in 2017, and recently, some... 

In today's world, where data volumes are rapidly increasing, the implementation of algorithms in distributed or parallel manners has become a common strategy for improving processing speed by leveraging multiple computing nodes. However, due to the heterogeneity in the computational power of these nodes, the overall performance of such algorithms is often dictated by the slowest machines. To overcome this limitation, novel approaches based on task repetition, computational load balancing, intelligent data distribution and polynomial-based coding have been proposed. These methods enable the final result to be obtained by collecting responses from only a subset of the machines, rather than... 

Clustering is a fundamental problem for data analysis, and it has a lot of variants. In this thesis we focused on the k-center problem, which is one of the most popular and well-studied variants of clustering. In this problem we are given a metric set of points called X, and a parameter k ⩽ |X|. Our goal is to find a set of k centers in X, minimizing the maximum distance of any point of X from its closest center. This thesis has worked on a version of the problem that is harder to solve. we have an extra parameter called z, which represents the maximum number of points that there is no need to be clustered, and we refer to them as outliers. The growth of data that needs to be processed makes... 

Since the amount of data is increasing, it is important to reduce the size of components and circuits. For instance, bus routing problem, rectangle scape problem, and minimizing number of layers are important problems in printed circuit boards. Rectangle scape problem can be used as an estimation for minimizing number of layers problem. To minimize number of layers in this problem, we are given some axis-parallel rectangles inside a axis-parallel rectangular region. The objective is to extend one of the four boundaries of each rectangle in a certain direction such that all rectangles can be placed without any conflict in minimum number of layers. In this thesis, we analyze a common greedy... 

In this research, we investigate shape fitting problems in high dimensional streams and we provide lower bounds for the problems of minimum enclosing spherical shell and minimum enclosing cylindrical shell in streaming model. We will prove that no streaming algorithm can approximate these problems with constant factor with storage sub-exponential in dimension. More precisely, we will prove that every streaming algorithm that can solve these problems with storage sub-exponential in dimension, does not have an approximation factor better than√28 d1/3, where d is dimension of the input points. This is the first lower bound that has been proved for these two problems in high dimensional streams  

In this thesis, we study the coloring problem in interval graphs within a relaxed variant of the online model. In this variant, vertices are introduced one by one and must be colored immediately, without any knowledge of the remaining portion of the graph. Our goal is to minimize the number of colors used, while ensuring that adjacent vertices always have distinct colors. This relaxed variant deviates from the traditional online model by allowing a limited number of previously colored vertices to be recolored. The number of recolorings per update is called the recourse budget. Our primary contribution is the design of three algorithms: one for unit interval graphs and two for general... 

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... 

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... 

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... 

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... 

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... 

Traditional classification techniques of machine learning assume that data have stationary distributions. This assumption for recent challenges where tremendous amount of data are generated at unprecedented rates with evolving patterns, is not true anymore. Classification of data streams has become an important area of machine learning, as the number of applications facing these challenges increases. Examples of such data streams applications include text streams, surveillance video streams, credit card fraud detection, market basket analysis, information filtering, computer security, etc. An appropriate method for such problems should adapt to drifting concepts by revising and refining the... 

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... 

Concept drift is a challenging problem in the context of data stream processing. As a result of increasing applications of data streams, including network intrusion detection, weather forecasting, and detection of unconventional behavior in financial transactions; numerous studies have been conducted in the field of concept drift detection. In order to solve the problem of concept drift detection, an ideal method should be able to quickly and correctly identify a variety of changes, adapt quickly to new concepts, in the presence of limitations of memory and processing power. In this thesis, a new explicit concept drift detection method based on ensemble classifiers has been proposed for data... 

The rapid growth of broadband wireless access (BWA) has increased the demand of new  application  such  as  VoIP,  video  conferencing,  online  gaming  each  of  which  has  different requirement for quality of service. Due to limited bandwidth provided for these networks,  one  of  the  most  important  issues  is  how  effective  we  manage  bandwidth  in  order to support requests. The quality of service is an important indicator of the effective management  of  bandwidth.  Using  mechanisms  of  call  admission  control is  a  commonly  accepted method for balance between quality of service and increase of utilization resource  in  cellular  mobile  networks.  In  fact, ...