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On the Worst Case Data Sets for Order Statistics
Full text linkIn this work, we consider the selection algorithms for the order statistics problems. A general partition based selection algorithm can be made to go quadratic by constructing input on the fly in response to the sequence of items compared. We develop an extremely simple class for constructing the worst case data set for the partition based selection algorithm. The general method works against any implementation of partition based selection algorithm that satisfies certain very mild and realistic assumptions. Computational results ascertain that the techniques developed are not only of theoretical interest, but also may actually lead to the worst case data sets for general partition based selection algorithms
The influence of the expansion of the smart mobile phones on the insurance industry
Full text linkDevelopment in the area of smart mobile phones is still accelerating. The expansion of smart mobile phones will bring new challenges and tasks to almost all industry areas. One of them will be the insurance industry. The clients will ask for new insurance products according to their actual personal needs and surroundings that could be effect by using smart mobile phones. In this article we try to predict such business opportunities in the new kind of insurance products development and its application. We focus on both the business and the risk model because these changes will cause a massive movement in the way of premium calculation
Modeling Complex Systems by Functional Subsystems Representation and Thermostatted-KTAP Methods
Full text linkIn the last two decades the mathematical modeling of real-world complex systems has received much attention. These systems are composed by a high number of interacting entities which are able to express a specific strategy. In order to reduce complexity, the whole system is decomposed in different subsystems that are sets of heterogeneous entities having the ability of expressing the same function. The microscopic interactions among the functional subsystems generate the emerging behaviors that are typical of the complex systems. This paper is concerned with suitable developments of the methods of mathematical kinetic theory for active particles for the modeling of complex systems splitted in functional subsystems and constrained to maintain constant some macroscopic quantities
A Projected Gradient Method for a High-order Model in Image Restoration Problems
Full text linkBased on the augmented Lagrangian strategy, we propose a projected gradient method for solving the high-order model in image restoration problems. Based on the Berm`udez and Moreno (BM) algorithm, the convergence of the proposed method is proved. We also give the relationship that the semi-implicit gradient descent method can be deduced from the projected gradient method. Some numerical experiments are arranged to demonstrate the efficiency of the proposed method for restoring the gray-level and color images
Improved DFT-based Channel Estimation in OFDM Systems Based on Phase Compensation
Full text linkBased on frequency domain pilot channel estimation is a typical technology of channel estimation in OFDM system. In most cases, the pilot configuration of the system can’t start from the first subcarrier, which will have an effect on channel estimation values at the pilot, especially in the algorithm of channel estimation based on DFT interpolation which will largely degrade the performance of the algorithm. The study analyses and deduces in detail phase offsets and the compensation technology under the condition of noninteger multiple of the multipath delay and non-integer multiple of the number of pilot. The simulation results show that the proposed phase compensation technology can effectively improve the performance of the channel estimation
Semi-supervised Ultrasound Image Segmentation Based on Direction Energy and Texture Intensity
Full text linkFor the ultrasound images accurate segmentation problem, this paper proposes a novel SVM semi-supervised segmentation method based on major features in curvelet domain. Firstly, ultrasound images were decomposed into different directions and frequencies in the curvelet domain, then the cauchy model was used to simulate curvelet coefficients distribution, thus the main distribution of the curvelet coefficients were extracted to reduce the algorithm time complexity; Secondly after curvelet inverse transform we designed texture analysis method to distinguish texture intensity of every blocks among each sub-bands, then elected maximum K numbers energy sub-bands accroding to the strong texture characteristic, followly extracted features such as: angular second moment, contrast, correlation, entropy, variance, mean, adverse moments, etc from these maximum energy sub-bands, thereby calculating data amount was reduced and algorithm real-time performance was improved; Finally we designed semi-supervised SVM classifier and took the expert manual tagging map as reference standards, compared with the results of moment method and active contour model, experimental data show that our algorithm for ultrasound images pathological region segmentation has better accuracy and effectiveness
Research of cryptosystems resistance on cascade codes to nonalgebraic decoding attacks
Full text linkCryptosystems of theoretical resistance, construction of which is based on using algebraic block codes (code-theoretic schemes) are considered. Resistance of cascade code-theoretic schemes to hacking by an opponent with the help of the method of permutable decoding is researched
On Sarhan-Balakrishnan Bivariate Distribution
Full text linkRecently Sarhan and Balakrishnan (Journal of Multivariate Analysis, 98, 1508 - 1527, 2007) introduced a new singular bivariate distribution using generalized exponential and exponential distributions. They discussed several interesting properties of this new distribution. Sarhan-Balakrishnan did not discuss any estimation procedure of the unknown parameters. In Sarhan-Balakrishnan model, there is no scale parameter. Unfortunately without the presence of any scale parameter, it is difficult to use it for any data analysis purposes. We introduce a scale parameter in the model and it becomes a four-parameter bivariate model. The usual maximum likelihood calculation involves a four dimensional optimization problem. We discuss the maximum likelihood estimation of the unknown parameters using EM algorithm, and it involves only a one-dimensional optimization calculation at each M-step of the EM algorithm. One data analysis has been performed for illustrative purposes. The performance of the EM algorithm is very satisfactory