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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Changes of ICP waveform morphology are characterized with different patients' states like hypertension, hydrocephalus and traumatic brain injury etc. Morphological clustering and analysis of ICP pulse (MOCAIP) app...
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Changes of ICP waveform morphology are characterized with different patients' states like hypertension, hydrocephalus and traumatic brain injury etc. Morphological clustering and analysis of ICP pulse (MOCAIP) approach is recently developed to extract ICP morphology feature, in which hierarchical clustering is used to extract the dominated pulse. In this paper, we evaluate the feasibility of using principle component analysis (PCA) and independent component analysis (ICA) to extract dominated pulse. The comparative study among clustering, PCA and ICP based approaches shows that PCA approach may be an alternative of clustering approach to extract dominated pulse in a faster fashion when dataset is of large size.
In Recent years, secure communications have become a important subject of research. The new service for wireless and wired networks is to provide confidentiality, authentication, authorization and data integrity. Secu...
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The Transmission Control Protocol - TCP has been widely researched in many different networking technologies such as wireless, optical, satellite, sensor, and wired since it is the most used protocol on the Internet. ...
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The Transmission Control Protocol - TCP has been widely researched in many different networking technologies such as wireless, optical, satellite, sensor, and wired since it is the most used protocol on the Internet. In Wireless mesh networks, this protocol still has challenges due to its origin and implementations for wired networks. This paper proposes an adaptation on the congestion control mechanism using information from the network layer to improve TCP performance through the vertical calibration across layer technique. The result is the Cross Layer Mesh - Transmission Control Protocol (CLM-TCP). To show the efficiency of the proposal, simulations in the NS-2 were carried out.
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