The creation of tools, techniques and methodologies to support the manipulation of large data sets has been receiving special attention of both scientific and industrial communities, in order to discover new ways of d...
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The creation of tools, techniques and methodologies to support the manipulation of large data sets has been receiving special attention of both scientific and industrial communities, in order to discover new ways of dealing with the underlying information, including learning purposes, identification of patterns, decision making support, amongst others. However, making use of computing resources to enhance awareness and understanding of software information and the software itself is still a challenge in software/systems engineering, since it involves the identification of suitable mechanisms, adequate abstractions, and studies on stimulation of the human perceptive and cognitive abilities. This paper presents some of the challenges in this context, based on current trends of software development lifecycle, program comprehension, and software engineering education. At the end, a special focus is given on ongoing research on using and improving current mechanisms for supporting software reuse practices and software comprehension in general.
The recent advances in Grid and Cloud computing make new types of applications possible. At the same time, they require an infrastructure to implement heterogeneous computing resources time and cost-savely. Here, appr...
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The recent advances in Grid and Cloud computing make new types of applications possible. At the same time, they require an infrastructure to implement heterogeneous computing resources time and cost-savely. Here, approaches that utilize design patterns, i.e., proven solutions to existing problems, seem to provide a good approach to enable these kind of applications. In this paper, we investigated which design patterns are already used in the area of Grid computing nowadays. After a brief description of the literature study design, we present our findings which include the discovered design patterns, corresponding categories, and application areas.
In this study, we focused on the interoperability and authentication of medical devices in the context of telemedical systems. A recent standard called the ISO/IEEE 11073 Personal Health Device (X73-PHD) Standards add...
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ISBN:
(纸本)9781424441198
In this study, we focused on the interoperability and authentication of medical devices in the context of telemedical systems. A recent standard called the ISO/IEEE 11073 Personal Health Device (X73-PHD) Standards addresses the device interoperability problem by defining common protocols for agent (medical device) and manager (appliance) interface. The X73-PHD standard however has not addressed security and authentication of medical devices which is important in establishing integrity of a telemedical system. We have designed and implemented a security policy within the X73-PHD standards. The policy will enable device authentication using Asymmetric-Key Cryptography and the RSA algorithm as the digital signature scheme. We used two approaches for performing the digital signatures: direct software implementation and use of embedded security modules (ESM). The two approaches were evaluated and compared in terms of execution time and memory requirement. For the standard 2048-bit RSA, ESM calculates digital signatures only 12% of the total time for the direct implementation. Moreover, analysis shows that ESM offers more security advantage such as secure storage of keys compared to using direct implementation. Interoperability with other systems was verified by testing the system with LNI Healthlink, a manager software that implements the X73-PHD standard. Lastly, security analysis was done and the system's response to common attacks on authentication systems was analyzed and several measures were implemented to protect the system against them.
Condensed matter systems with topological defects in the ground states range from the Abrikosov phases in superconductors, to various blue phases and twist grain boundary phases in liquid crystals, and to phases of sk...
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Condensed matter systems with topological defects in the ground states range from the Abrikosov phases in superconductors, to various blue phases and twist grain boundary phases in liquid crystals, and to phases of skyrmion lattices in chiral ferromagnets and Bose-Einstein condensates. In nematic and chiral nematic liquid crystals, which are true fluids with long-range orientational ordering of constituent molecules, point and line defects spontaneously occur as a result of symmetry-breaking phase transitions or due to flow, but they are unstable, hard to control, and typically annihilate with time. Here we describe the optical generation of two-dimensional crystalline, quasicrystalline, and arbitrary ensembles of particlelike structures manifesting both skyrmionlike and Hopf fibration features—dubbed “torons”—composed of looped double twist cylinders and point defects embedded in a uniform director field. In these two-dimensional lattices, we then introduce various dislocations, defects in positional ordering of the torons. We show that the periodic defect lattices with and without dislocation are light- and voltage-tunable reconfigurable two-dimensional diffraction gratings and can be used to generate various controlled phase singularities in the diffracted laser beams. The results of computer simulations of optical images, diffraction patterns, and phase distributions with optical vortices are in a good agreement with the corresponding experimental findings.
This paper presents a methodology for roughness analysis based on surface characteristics of images obtained from optical and electronic microscopes. Texture analysis has been widely used in different fields, such as ...
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This paper presents a methodology for roughness analysis based on surface characteristics of images obtained from optical and electronic microscopes. Texture analysis has been widely used in different fields, such as medical image analysis, visual interpretation of remote sensing images, image search and industrial quality inspection of manufactured products, which is the focus of this paper. We present a novel method of analysis based on texture characteristics. The Haralick descriptors are used to describe the surface texture and to classify its roughness. The primary roughness standards are evaluated and classified according to several features considering these descriptors. The set of values is the input of a multilayer perceptron artificial neural network. The obtained results show that it can be possible to advance this methodology in order to develop a roughness digital measurement system for the evaluation of surface ending process.
In this work, we present the use of Shannon and Simpson Diversity Indices as texture descriptors for lung nodules in computerized Tomography (CT) images. These indices will be proposed to characterize the nodules into...
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Knowledge Management System (KMS) is one way to organize and documented the knowledge of institution. The purpose of this study is to develop a prototype KMS in organizing and documenting the knowledge in the universi...
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This paper presents an interface that allows a human user to specify a desired path for a mobile robot in a planar workspace with noisy binary inputs that are obtained at low bit-rates through an electroencephalograph...
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ISBN:
(纸本)9781467317375
This paper presents an interface that allows a human user to specify a desired path for a mobile robot in a planar workspace with noisy binary inputs that are obtained at low bit-rates through an electroencephalograph (EEG). We represent desired paths as geodesics with respect to a cost function that is defined so that each path-homotopy class contains exactly one (local) geodesic. We apply max-margin structured learning to recover a cost function that is consistent with observations of human walking paths. We derive an optimal feedback communication protocol to select a local geodesic-equivalently, a path-homotopy class-using a sequence of noisy bits. We validate our approach with experiments that quantify both how well our learned cost function characterizes human walking data and how well human subjects perform with the resulting interface in navigating a simulated robot with EEG.
The low-frequency 1/f noise in graphene transistors has been studied extensively owing to the proposed graphene applications in analog devices and communication systems [1-5]. The studies were motivated by the fact th...
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The low-frequency 1/f noise in graphene transistors has been studied extensively owing to the proposed graphene applications in analog devices and communication systems [1-5]. The studies were motivated by the fact that the low-frequency noise can be up-converted by device nonlinearity and contribute to the phase noise of the system. Similarly, the sensor sensitivity is often limited by the electronic low-frequency noise. Therefore, noise is usually considered as one of the main limiting factors for the device or overall system operation. However, the electronic noise spectrum itself can be used as a sensing parameter increasing the sensor sensitivity and selectivity. Here, we show that vapors of different chemicals produce distinguishably different effects on the low-frequency noise spectra of the graphene-on-Si transistor. Our study showed that some gases change the electrical resistance of pristine graphene devices without changing their low-frequency noise spectra while other gases modify the noise spectra by inducing Lorentzian components with distinctive features. The characteristic corner frequency f C of the Lorentzian noise bulges in graphene devices is different for different chemicals and varies from f C =10 - 20 Hz for tetrahydrofuran to f C =1300 - 1600 Hz for chloroform. We tested the selected set of chemicals vapors on different graphene device samples and alternated different vapors for the same samples. The obtained results indicate that 1/f noise in combination with other sensing parameters can allow one to achieve the selective gas sensing with a single pristine graphene transistor. Our method of gas sensing with graphene does not require graphene surface functionalization or fabrication of an array of the devices with each tuned to a certain chemical. The observation of the Lorentzian components in the vapor-exposed graphene can also help in developing an accurate theoretical description of the noise mechanism in graphene.
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