In the classic use of P2P, e.g. file sharing, there is no concern about persistent peer identification, peer and content reputation and content authenticity. Security proposals currently found in technical literature ...
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In the classic use of P2P, e.g. file sharing, there is no concern about persistent peer identification, peer and content reputation and content authenticity. Security proposals currently found in technical literature try to adapt techniques from client-server architecture to P2P environments, which it is not the most appropriate approach. This work proposes applying public keys to identify peers. It allows creating a persistent identification scheme, without losing anonymity, even in a self-managed environment as P2P. Also, it applies digital signature to provide authenticity to the P2P content and to guarantee non-repudiation in the content transfer. In order to provide credibility to the non-certified content and public keys a reputation mechanism is applied. We have developed a prototype to show the benefits of this approach.
Topology control is one of the main techniques that can be used to decrease energy spenditure in wireless sensor networks. Although it has been the subject of much research, less attention has been devoted to study th...
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Topology control is one of the main techniques that can be used to decrease energy spenditure in wireless sensor networks. Although it has been the subject of much research, less attention has been devoted to study the effects of overhearing on topology control, i.e., the effects of the cost implied by nodes hearing transmissions even if these transmissions were not intended to them. In this paper we describe a distributed (localized) algorithm for topology control in wireless sensor networks. Our approach differs from previous work mainly in the sense that it takes the effects of overhearing into consideration and that it might eliminate more communication links from a given connectivity graph, and thus possibly assign lower transmission power to some nodes. This is done by eliminating so-called k-redundant edges, instead of eliminating only two redundant edges. We present the sketch of the proof of properties of the algorithm and simulation results.
Auditory perception is one of the most important functions for robotics applications. Microphone arrays are widely used for auditory perception in which the spatial structure of microphones is usually known. In practi...
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This paper presents a semiautomatic method for the identification of immunohistochemical (IHC) staining in digitized samples. The user trains the system by selecting on a sample image some typical positive stained reg...
The flame-made (5/5) pure ZnO and WO 3 -doped ZnO nanoparticles containing 0.25, 0.50, and 0.75 mol% of WO 3 were successfully synthesized by flame spray pyrolysis (FSP). These materials were studied for NO 2 , CO an...
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The flame-made (5/5) pure ZnO and WO 3 -doped ZnO nanoparticles containing 0.25, 0.50, and 0.75 mol% of WO 3 were successfully synthesized by flame spray pyrolysis (FSP). These materials were studied for NO 2 , CO and H 2 gas sensing at different gas concentrations and operating temperatures ranging from 300-400°C in dry air. The crystalline phase, morphology and size of the nanoparticles were characterized by XRD, BET, TEM, SEM and EDS in order to correlate physical properties with gas sensing performance. The gas-sensing results showed that WO 3 doping significantly enhanced NO 2 gas-sensing performance of ZnO nanoparticles. In addition, 0.5 mol% is found to be an optimal WO 3 concentration which gives the highest sensitivity towards NO 2 .
High computational cost for solving large engineering optimization problems point out the design of parallel optimization algorithms. Population based optimization algorithms provide parallel capabilities that can be ...
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High computational cost for solving large engineering optimization problems point out the design of parallel optimization algorithms. Population based optimization algorithms provide parallel capabilities that can be explored by their implementations done directly in hardware. This paper presents a hardware implementation of particle swarm optimization algorithms using an efficient floating-point arithmetic which performs the computations with high precision. All the architectures are parameterizable by bit-width, allowing the designer to choose the suitable format according to the requirements of the optimization problem. Synthesis and simulation results demonstrate that the proposed architecture achieves satisfactory results obtaining a better performance in therms of elapsed time than conventional software implementations.
A data mining framework has been proposed to estimate intracranial pressure (ICP) non-invasively in our previous work. In the corresponding approach, the feature vector extracted from arterial blood pressure (ABP) and...
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A data mining framework has been proposed to estimate intracranial pressure (ICP) non-invasively in our previous work. In the corresponding approach, the feature vector extracted from arterial blood pressure (ABP) and flow velocity (FV) is translated to the estimated errors by the mapping function for each entry in the database. In this paper, three different mapping function solutions, linear least squares (LLS), truncated singular value decomposition (TSVD) and standard Tikhonov regularization (STR) are systemically tested to compare the possible effects of different solutions on the non-invasive ICP estimation. The conducted comparison demonstrated that the selection of mapping function solution actually influences the estimation. Among the tested three solutions for mapping function, TSVD and STR show better ICP estimation performance with smaller ICP errors than LLS.
Sensor networks are being used in several emerging applications not even imagined some years ago due to advances in sensing, computing, and communication techniques. However, these advances also pose various challenge...
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Sensor networks are being used in several emerging applications not even imagined some years ago due to advances in sensing, computing, and communication techniques. However, these advances also pose various challenges that must be faced. One important challenge is related to the autonomous capability needed to setup and adapt the networks, which decentralizes the control of the network, saving communication and energy resources. Middleware technology helps in addressing this kind of problem, but there is still a need for additional solutions, particularly considering dynamic changes in users' requirements and operation conditions. This paper presents an agent-based framework acting as an integral part of a middleware to support autonomous setup and adaptation of sensor networks. It adds interoperability among heterogeneous nodes in the network, by means of autonomous behavior and reasoning. These features also address the needs for system setup and adaptations in the network, reducing the communication overhead and decentralizing the decision making mechanism. Additionally, preliminary results are also presented.
The focus of this paper is to describe studies on pre-prepared hydrophobic CdSeS(ZnS) quantum dots (QDs) at the air-water interface. Surface pressure-area (π-A) isotherms were extensively studied using QDs capped wit...
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