This paper presents a pioneering approach for weld bead detection in radiographic images obtained by the Double Wall Double Image (DWDI) technique. Such task constitutes an essential step for several high level proces...
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ISBN:
(纸本)9781467315104
This paper presents a pioneering approach for weld bead detection in radiographic images obtained by the Double Wall Double Image (DWDI) technique. Such task constitutes an essential step for several high level processes, such as fully automatic flaw identification on welded joints. Sets of sample pixels, corresponding to candidate solutions provided by a genetic algorithm (GA), are compared to pre-defined synthetic weld bead and pipe models in an image matching procedure. The fitness of each set (individual) is evaluated based on a linear combination of its genotype (evaluated by a heuristic function) and phenotype. The evolutionary process automatically selects the best individual in the population and, thus, provides information such as position, orientation and dimension of the detected object. The proposed approach successfully detects pipes and weld beads in radiographic images of different complexities, encouraging future works.
We study the secret message capacity of an ergodic block fading wiretap channel with partial channel state information at the transmitter and perfect channel state information at the receivers. We consider that in add...
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We study the secret message capacity of an ergodic block fading wiretap channel with partial channel state information at the transmitter and perfect channel state information at the receivers. We consider that in addition to the statistics of the main and the eavesdropper channel state information (CSI), the sender is provided by the legitimate receiver with a q-bit feedback, at the beginning of each coherence block, through an error-free feedback channel, with capacity q bits. We establish upper and lower bounds on the secrecy capacity. We show that a positive secrecy rate is achievable even when the feedback is at the end of each coherence block and q = 1. We also show that the lower and the upper bounds coincide asymptotically as q → ∞. Finally, asymptotic analysis at high Signal-to-Noise Ratio (SNR) are presented where it is found that the capacity is bounded at high-SNR and present a simple suboptimal scalar quantizer that is capacity achieving, without the need of any numerical optimization, as q → ∞. When applied to Rayleigh fading channels, we show that, at high-SNR, a 4-bit feedback achieves 90% of the secrecy capacity when perfect main CSI is available at the transmitter.
We estimate the amount of free electrons generated by concealed radioactive materials using MCNP code. This simulation results show that the existence of radioactive sources enhances the number of photons and backgrou...
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We estimate the amount of free electrons generated by concealed radioactive materials using MCNP code. This simulation results show that the existence of radioactive sources enhances the number of photons and background free electrons. Those quantities are influenced by density and thickness of container material.
This paper proposed an integration of heart sound and speech for biometrics application .The method the method selects the best fusion and normalization techniques for biometric system. The framework is developed and ...
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This paper proposed an integration of heart sound and speech for biometrics application .The method the method selects the best fusion and normalization techniques for biometric system. The framework is developed and test the verification task. The approach in this paper is biometrics recognition, for example, providing features that can't be easily copied, such as the Mel-Frequency Cepstral Coefficient (MFCC) as a feature vector and vector quantization (VQ) as the matching model algorithm .A simple yet highly reliable method is introduced for biometric applications. Experimental results show that the recognition rate of the Heart sound-speaker verification (HS-SV) provides an average EER of 17.8% while the average EER for the speech speaker verification model (S-SV) is 3.39%. In order to reach a higher security level an alternative to the above approach, which is based on multimodal and a fusion technique, is implemented into the system. The best performance of the work is based on simple-sum score fusion with a pricewise-linear normalization technique which provides an EER of 0.69% while the fusion type Main Rule provide an EER of 1.1%.
This paper considers the problem of the compensation of an unknown dead zone in the input of a plant. A new compensation method is presented based on the estimation of an equivalent input disturbance (EID). Unlike oth...
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In this paper, we proposed optically and graphically coded microdisks that have large coding capacity and small particle size for bioassay. Graphically coded particles generally have large particle size compared with ...
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ISBN:
(纸本)9780979806452
In this paper, we proposed optically and graphically coded microdisks that have large coding capacity and small particle size for bioassay. Graphically coded particles generally have large particle size compared with the conventionally used microbeads. But the large particle size is not suitable for multiplexed bioassay due to a large amount of sample consumption and vigorous mixing. The proposed dual coding method uses optical and graphical codes for minimizing the particle size without reducing the coding capacity. The microdisk has dot patterns for graphical coding and gold layer on the microdisk for optical coding.
This paper introduces a new approach for visualizing multidimentional weather-direction-related time-series data sets called “3D Spring Model”. Spring Model is designed to visualize pattern behind large time-series ...
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ISBN:
(纸本)9781467320269
This paper introduces a new approach for visualizing multidimentional weather-direction-related time-series data sets called “3D Spring Model”. Spring Model is designed to visualize pattern behind large time-series weather data set and to clearify seasonal structure in the data. In addition, it supports visibility of seasonal shift and wind direction anomaly by direct comparison betweem successive spring cycles. The visualization contained three data types: (1) Weather parameter (such as windrun, temperature or rainfall etc.), (2) Wind directions and (3) time. We mapped the color to the model in such the way that it comply with human perception using color gradient. Level-Of-Detail scheme is applied and adjustable resulting different pattern time focus for users. Spring Model is highly self-contained for accumulative long term data. It is interactive, flexible and user-friendly. Spring Model is very well-suited to high computing power visualization environment. At the end of the paper, the observation of weather pattern in Nakhon Si Thammarat, Thailand using Spring Model was proposed as the case study to present the model vast applications.
We derive a semi-analytical expression for the uplink inter-cell interference (ICI) assuming proportional fair scheduling (with a maximum normalized signal-to-noise ratio (SNR) criterion) deployed in the cellular netw...
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We derive a semi-analytical expression for the uplink inter-cell interference (ICI) assuming proportional fair scheduling (with a maximum normalized signal-to-noise ratio (SNR) criterion) deployed in the cellular network. The derived expression can be customized for different models of channel statistics that can capture path loss, shadowing, and fading. Firstly, we derive an expression for the distribution of the locations of the allocated user in a given cell. Then, we derive the distribution and moment generating function of the uplink ICI from one interfering cell. Finally, we determine the moment generating function of the cumulative uplink ICI from all interfering cells. The derived expression is utilized to evaluate important network performance metrics such as outage probability and fairness among users. The accuracy of the derived expressions is verified by comparing the obtained results to Monte Carlo simulations.
In this paper, we propose joint user-and-hop scheduling over dual-hop block-fading broadcast channels in order to exploit multi-user diversity gains and multi-hop diversity gains all together. To achieve this objectiv...
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In this paper, we propose joint user-and-hop scheduling over dual-hop block-fading broadcast channels in order to exploit multi-user diversity gains and multi-hop diversity gains all together. To achieve this objective, the first and second hops are scheduled opportunistically based on the channel state information and as a prerequisite we assume that the relay, which is half-duplex and operates using decode-and-forward, is capable of storing the received packets from the source until the channel condition of the destined user becomes good to be scheduled. We formulate the joint scheduling problem as maximizing the weighted sum of the long term achievable rates by the users under a stability constraint, which means that on the long term the rate received by the relay should equal the rate transmitted by it, in addition to constant or variable power constraints. We show that this problem is equivalent to a single-hop broadcast channel by treating the source as a virtual user with an optimal priority weight that maintains the stability constraint. We show how to obtain the source weight either off-line based on channel statistics or on real-time based on channel measurements. Furthermore, we consider special cases including the maximum sum rate scheduler and the proportional fair scheduler. We demonstrate via numerical results that our proposed joint scheduling scheme enlarges the rate region as compared with a scheme that employs multi-user scheduling alone.
MicroRNAs (miRNAs) are non-coding RNAs with approximately 22 nucleotides (nt) that are derived from precursor molecules. These precursor molecules or pre-miRNAs often fold into stem-loop hairpin structures. However, a...
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MicroRNAs (miRNAs) are non-coding RNAs with approximately 22 nucleotides (nt) that are derived from precursor molecules. These precursor molecules or pre-miRNAs often fold into stem-loop hairpin structures. However, a large number of sequences with pre-miRNA-like hairpins can be found in genomes. It is a challenge to distinguish the real pre-miRNAs from other hairpin sequences with similar stem-loops (referred to as pseudo pre-miRNAs). Several computational methods have been developed to tackle this challenge. In this paper we propose a new method, called MirlD, for identifying and classifying microRNA precursors. We collect 74 features from the sequences and secondary structures of pre-miRNAs; some of these features are taken from our previous studies on non-coding RNA prediction while others were suggested in the literature. We develop a combinatorial feature mining algorithm to identify suitable feature sets. These feature sets are then used to train support vector machines to obtain classification models, based on which classifier ensemble is constructed. Finally we use a boosting algorithm to further enhance the accuracy of the classifier ensemble. Experimental results on a variety of species demonstrate the good performance of the proposed method, and its superiority over existing tools.
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