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Articles 1 - 6 of 6
Full-Text Articles in Computer Engineering
Theoretical Explanation Of Bernstein Polynomials' Efficiency: They Are Optimal Combination Of Optimal Endpoint-Related Functions, Jaime Nava, Vladik Kreinovich
Theoretical Explanation Of Bernstein Polynomials' Efficiency: They Are Optimal Combination Of Optimal Endpoint-Related Functions, Jaime Nava, Vladik Kreinovich
Departmental Technical Reports (CS)
In many applications of interval computations, it turned out to be beneficial to represent polynomials on a given interval [x-, x+] as linear combinations of Bernstein polynomials (x- x - )k * (x+ - x)n-k. In this paper, we provide a theoretical explanation for this empirical success: namely, we show that under reasonable optimality criteria, Bernstein polynomials can be uniquely determined from the requirement that they are optimal combinations of optimal polynomials corresponding to the interval's endpoints.
A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal., Sarah M. Asio
A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal., Sarah M. Asio
Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research
The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To …
Multi-Channel Peer-To-Peer Streaming Systems As Resource Allocation Problems, Miao Wang
Multi-Channel Peer-To-Peer Streaming Systems As Resource Allocation Problems, Miao Wang
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
In the past few years, the Internet has witnessed the success of Peer-to-Peer (P2P) streaming technology, which has attracted millions of users. More recently, commercial P2P streaming systems have begun to support multiple channels and a user in such systems is allowed to watch more than one channel at a time. We refer to such systems as multi-channel P2P streaming systems. In this dissertation, we focus on designing multi-channel P2P streaming systems with the goal of providing optimal streaming quality for all channels, termed as system-wide optimal streaming quality. Specifically, we design the systems from the perspective of how to …
Natural Gas As Petroleum Fuel Substitution: Analysis Of Supply-Demand Projections, Infrastructures, Investments And End-User Prices, Abdul Qoyum Tjandranegara, Arsegianto Arsegianto, Widodo Wahyu Purwanto
Natural Gas As Petroleum Fuel Substitution: Analysis Of Supply-Demand Projections, Infrastructures, Investments And End-User Prices, Abdul Qoyum Tjandranegara, Arsegianto Arsegianto, Widodo Wahyu Purwanto
Makara Journal of Technology
The petroleum fuels (PF) subsidy has long burdens the government spending, and discourages less expensive energy usage such as natural gas (NG). Exporting NG and importing the more expensive PF products cause financial losses to Indonesia. The lack of NG infrastructure is the main hurdle in maximizing domestic NG usage and so does the perception of its high investment costs burdening government spending and pushing the NG transportation cost up. This study calculates the required NG infrastructure and its investments for several levels of PF substitutions up to 2030. To balance the NG demands, the supply from each field and …
Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea
Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea
Open Access Theses & Dissertations
The main contribution of this dissertation is the development of a method to train a Support Vector Regression (SVR) model for the large-scale case where the number of training samples supersedes the computational resources. The proposed scheme consists of posing the SVR problem entirely as a Linear Programming (LP) problem and on the development of a sequential optimization method based on variables decomposition, constraints decomposition, and the use of primal-dual interior point methods. Experimental results demonstrate that the proposed approach has comparable performance with other SV-based classifiers. Particularly, experiments demonstrate that as the problem size increases, the sparser the solution …
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …