On a note of the Smarandache power function

For any positive integer n, the Smarandache power function SP(n) is defined as the smallest positive integer m such that njmm, where m and n have the same prime divisors

Performance of MIMO with Circular Antenna Array Using Correlation Matrix

Spatial correlation is one of the impairment practical Multiple-Input Multiple-Output (MIMO) wireless communication systems have to be coped with. Capacity increases promised by MIMO systems mostly depend on the spatial correlation properties of the radio channels. This paper investigates the connection between these properties and the channel capacity. By investigating the channel capacity using the correlation matrix for a circular array, we prove that, for circular array, decrease in the radius is equivalent to decrease in signal to noise ratio (SNR)

Measurements of Coherent Synchrotron Radiation and its Impact on the LCLS Electron Beam

In order to reach the high peak current required for an x-ray FEL, two separate magnetic dipole chicanes are used in the LCLS accelerator to compress the electron bunch length in stages. In these bunch compressors, coherent synchrotron radiation (CSR) can be emitted-induced either by a short electron bunch, or by any longitudinal density modulation that may be on the bunch. We present measurements, simulations, and analysis of (1) the CSR-induced energy loss, (2) the related transverse emittance growth, and (3) the microbunching-induced CSR directly observed at optical wavelengths

Cell segmentation and classification via unsupervised shape ranking

As histology patterns vary depending on different tissue types, it is typically necessary to adapt and optimize segmentation algorithms to these tissue type-specific applications. Here we present an unsupervised method that utilizes cell shape cues to achieve this task-specific optimization by introducing a shape ranking function. The proposed algorithm is part of our Layers™ toolkit for image and data analysis for multiplexed immunohistopathology images. To the best of our knowledge, this is the first time that this type of methodology is proposed for segmentation and ranking in cell tissue samples. Our new cell ranking scheme takes into account both shape and scale information and provides information about the quality of the segmentation. First, we introduce cell-shape descriptor that can effectively discriminate the cell-type's morphology. Secondly, we formulate a hierarchical-segmentation as a dynamic optimization problem, where cells are subdivided if they improve a segmentation quality criteria. Third, we propose a numerically efficient algorithm to solve this dynamic optimization problem. Our approach is generic, since we don't assume any particular cell morphology and can be applied to different segmentation problems. We show results in segmenting and ranking thousands of cells from multiplexing images and we compare our method with well established segmentation techniques, obtaining very encouraging results. © 2013 IEEE

Cell segmentation and classification via unsupervised shape ranking

As histology patterns vary depending on different tissue types, it is typically necessary to adapt and optimize segmentation algorithms to these tissue type-specific applications. Here we present an unsupervised method that utilizes cell shape cues to achieve this task-specific optimization by introducing a shape ranking function. The proposed algorithm is part of our Layers™ toolkit for image and data analysis for multiplexed immunohistopathology images. To the best of our knowledge, this is the first time that this type of methodology is proposed for segmentation and ranking in cell tissue samples. Our new cell ranking scheme takes into account both shape and scale information and provides information about the quality of the segmentation. First, we introduce cell-shape descriptor that can effectively discriminate the cell-type's morphology. Secondly, we formulate a hierarchical-segmentation as a dynamic optimization problem, where cells are subdivided if they improve a segmentation quality criteria. Third, we propose a numerically efficient algorithm to solve this dynamic optimization problem. Our approach is generic, since we don't assume any particular cell morphology and can be applied to different segmentation problems. We show results in segmenting and ranking thousands of cells from multiplexing images and we compare our method with well established segmentation techniques, obtaining very encouraging results. © 2013 IEEE

Scalable social tie strength measuring

202103 bcrcAccepted ManuscriptSelf-fundedPublishe

Path View Algorithm for Transportation Networks: The Dynamic Reordering Approach

this paper thus focus on providing solutions to the centralized route guidance problem. The underlying principle we explore is to precompute the path vie

A Semi-Materialized View Approach for Route Guidance in Intelligent Vehicle Highway Systems

Efficient path computation necessary for route guidance has been identified as one of the key requirements for Intelligent Vehicle Highway Systems (IVHS) applications. While the current IVHS literature has focused on the application of search algorithms (typically, heuristic A* algorithms) to provide for compute-on-demand path finding, we propose a semi-materialized path view approach that pre-computes optimal paths. Advantages of our approach include (1) route computation is very efficient and no longer dependent on the number of route requests and (2) the storage overhead is less than for the full enumeration of all possible paths. In this paper, we present algorithms for incrementally updating the encoded path view structure in response to weight changes on the traffic links of the underlying network, e.g., a slower link traversal time, a congestion, etc. Our algorithms are designed to operate correctly on cyclic graphs --- given that IVHS maps typically correspond to highly interco..