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Zagreb, Croatia

Kornaros G.,Technological Educational Institute of Crete | Harteros K.,Technological Educational Institute of Crete | Astrinaki M.,Technological Educational Institute of Crete | Christoforakis I.,Technological Educational Institute of Crete | And 2 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013

Hardware virtualization is a major challenge in embedded virtualization. The key to improving resource utilization in a virtualized system is to allow maximum possible resource access operations to perform natively with minimal intervention by the virtual machine monitor, while at the same time ensuring protected operation among different virtual machines' address space. An innovative I/O Memory Management Unit component (IOMMU) is architected to enable mapping of virtual addresses from multiple devices to the correct VM's physical memory locations, offering enhanced protection, scatter-gather functions on distributed memory organizations, high performance supported by a configurable TLB and an integrated lightweight hardware monitoring unit to facilitate dynamic system optimizations. This new IOMMU is designed in a modular way supporting address translation along with protection and security extensions. The principal objective is to ensure device isolation by safely mapping a device to a particular guest without risking the integrity of other guests. Additionally, the IOMMU is designed to provide an increased level of security in scenarios without virtualization; with the aid of the IOMMU, the operating system is able to protect itself from malicious device drivers by limiting a device's memory accesses and managing the permissions of peripheral devices. © 2013 SPIE. Source

Polat O.M.,Microelectronics | Ozkazanc Y.,Hacettepe University
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013

In blind scene analysis, the aim is to obtain information about background and targets without any prior information. Blind methods can be considered as pre-processing steps for scene understanding. By means of blind signal separation methodologies, anomalies can be detected and these anomalies can be exploited for target detection. There are many imaging sensor systems which uses different properties of the emittance or the reflectance characteristics of the scene components. Spectral reflectance properties are related to the material composition and these multispectral characteristics can be exploited for detection, identification and classification of the scene components. As the light scattered from the scene elements shows polarization, polarized measurements can be used as extra features. Multispectral and polarimetric images of a scene provide information to some level and this information can be used to get further information on the scene and to facilitate detection. In this study, spectral and polarimetric images of a scene are analyzed via Canonical Correlation Analysis (CCA) which is a powerful multivariate statistical methodology. Multispectral and polarimetric data (spectro-polarimetric data) are treated as two different sets. Canonical variants obtained by CCA give different scene components such as background elements and some man-made objects. The linear relationship of the polarimetric and multispectral data of the same scene is also obtained by CCA. © 2013 SPIE. Source

Polat O.M.,Microelectronics | Ozkazanc Y.,Hacettepe University
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013

In hyperspectral data analysis, blind separation of the target and background can be considered as a pre-processing step in the target detection process. Blind Source Separation (BSS) techniques can be used when there is no prior information on the scene for image understanding. Previously, Principal Component Analysis and Independent Component Analysis methods are used as blind techniques for the analysis of hyperspectral data. In this study, we propose a blind analysis methodology based on Canonical Correlation Analysis (CCA) for the analysis of hyperspectral data sets. CCA is a multivariate method of analysis for the exploration of the data structures which extremize the correlations between two data sets. The hyperspectral data analyzed in this study is the HyMap sensor data which is available in the Target Detection Blind Test website. We produce two data sets out of the HyMap data cube which are later subjected to CCA. In the creation of these data sets, two different approaches are used. In first case, the HyMap data cube is simply divided into two sub-cubes by simple spectral separation. As another approach, the second data cube is derived from the HyMap data by a spatial filtering. In both cases, two data sets are analyzed via CCA and canonical variates of these data sets are obtained. The scene components are obtained from images expressed by the canonical variates obtained via CCA. The CCA methodology and its use as a blind analysis tools is presented on the HyMap data. © 2013 SPIE. Source

Dogan I.O.,Microelectronics | Yazicioglu Y.,Middle East Technical University
Journal of Computational and Theoretical Nanoscience | Year: 2014

Recent investigations in nanotechnology show that carbon nanotubes have significant mechanical, electrical and optical properties. Interactions between those are also promising in both research and industrial fields. Those unique characteristics are mainly due to the atomistic structure of carbon nanotubes. In this paper, the structural effects of vacant atoms on single walled carbon nanotubes are investigated using matrix stiffness method. In order to use this technique, a linkage between structural mechanics and molecular mechanics is established. A code has been developed to construct the single walled carbon nanotubes with the desired chirality, extracting the vacant atoms with the corresponding atomic bonds between the neighbor nodes and calculating the effect of these vacancies on their vibrational properties. In order to investigate the effect of those vacant nodes, large number of simulations has been carried out with randomly positioned vacant atoms. Also, consecutive vacant nodes have been positioned in order to investigate their effect on the structural properties through the length of a single walled carbon nanotubes. Effects of vacancies on Young's modulus have also been investigated. It is concluded that any amount of vacant atoms have substantial effect on modal frequencies and modulus of elasticity. Chirality and the amount/position of the vacancies are the main parameters determining the structural properties. Copyright © 2014 American Scientific Publishers All rights reserved. Source

Baric A.,Microelectronics
MIPRO 2012 - 35th International Convention on Information and Communication Technology, Electronics and Microelectronics - Proceedings | Year: 2012

High-gain charge pumps use MOS switches to rearrange the topology of the circuit in the adjacent half periods of the clock signals, which enables the charge pump circuit to achieve high output voltage. The MOS switches must be adequately controlled to enable fast charge transfer while turned "on" and to prevent leakage current while in the "off" state. This paper presents the limitations of the Cascode Voltage Switch Logic (CVSL) circuit as a control circuit for MOS switches. The operation of the CVSL driver is discussed and the negative effects of the capacitive load associated with the CVSL output node are analyzed. © 2012 MIPRO. Source

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