The design and analysis of some algorithms for the implementation of supervisors corresponding to centralized systems using Petri networks is approached in this article. Starting from the basis of supervised control, ...
详细信息
The design and analysis of some algorithms for the implementation of supervisors corresponding to centralized systems using Petri networks is approached in this article. Starting from the basis of supervised control, namely, monitoring and controlling of discrete event systems via a central controller (supervisor), the paper proposes a method for supervised control using Petri net type models based on parallel composition of subsystems. To illustrate and validate the proposed method, a flexible manufacturing system based on a transport system with seven nodes is used.
Aim of this paper is to present a radio communication system that can be easily integrated in an emergency communication network, which is able to relay analog and digital data. Implementation of a multiprocessor radi...
详细信息
Aim of this paper is to present a radio communication system that can be easily integrated in an emergency communication network, which is able to relay analog and digital data. Implementation of a multiprocessor radio network controller, based on the FPGA technology, is the main goal of this project. This configuration allows a multiple possibilities of communication: APRS data transmission and analogue (voice) communication.
The paper investigates single-link fault localization in all-optical networks in a line topology in which a single monitoring node (MN) can localize shared risk link group (SRLG) faults by inspecting the optical burst...
详细信息
The paper investigates single-link fault localization in all-optical networks in a line topology in which a single monitoring node (MN) can localize shared risk link group (SRLG) faults by inspecting the optical bursts traversing through it. We investigate relevant problems in the proposed fault monitoring approach, including m-trail allocation, burst launching time scheduling, and node switch fabric configuration, where constructions are developed to derive optimal solutions and are further examined in numerical experiments.
Extended power laws and inhomogeneous connections are structural patterns often found in empirical networks. Mechanisms based on the formation of triads are able to explain the power law behavior of the degree distrib...
详细信息
ISBN:
(纸本)9781479932757
Extended power laws and inhomogeneous connections are structural patterns often found in empirical networks. Mechanisms based on the formation of triads are able to explain the power law behavior of the degree distribution of such networks. The proposed model introduces a two-step mechanism of attachment and triad formation that illustrates how preferential linkage plays an important role in shaping the inhomogeneity of connections and the division of the network into groups of nodes (i.e., the growth of community structures). In particular, we identify conditions under which the scaling exponent of the power law correlates to a widely-used modularity measure of non-overlapping communities. Our analytical results characterize the asymptotic behavior of both the scaling exponent and the modularity, as a function of the strength with which nodes with similar characteristics tend to link to each other.
Voice disorders are non-trivial when it comes to their early detection. Symptoms range from slight hoarseness to complete loss of voice, and may seriously impact personal and professional life. To date, we are still l...
详细信息
Voice disorders are non-trivial when it comes to their early detection. Symptoms range from slight hoarseness to complete loss of voice, and may seriously impact personal and professional life. To date, we are still largely missing reliable data to help us better understand and screen voice pathologies. In this paper, we present an ambulatory voice monitoring system using surface electromyography (sEMG) and a robust algorithm for pattern recognition of vocal gestures. The system, which can process up to four sEMG channels simultaneously, also can store large amounts of data (up to 13 hours of continuous use) and in the future will be used to analyze on-the-fly various patterns of sEMG activation in the search for maladaptive laryngeal activity that may lead to voice disorders. In the preliminary results presented here, our pattern recognition algorithm (Hierarchical GUSSS) detected six different sEMG patterns of activation, and it achieved 90% accuracy.
This work is an extension of our previous attempt to construct a spatial representation of 21 initial consonants in Thai by partitioning them into homogeneous clusters based on empirical measures of confusability and ...
详细信息
This work is an extension of our previous attempt to construct a spatial representation of 21 initial consonants in Thai by partitioning them into homogeneous clusters based on empirical measures of confusability and distance among phonemes. The measures were taken from perceptual identification performance of 28 listeners (seven full subjects) when stimuli were presented in noise. In present study, two methods of clustering, namely Multidimensional scaling analysis and k-means clustering were employed, yielding six different classifications and four perceptually relevant categories: intra-cluster short distance, intra-cluster long distance, inter-cluster short distance, and inter-cluster long distance. Another set of perceptual experiment (eight listeners; two full subjects) was carried out to verify the predictions. The findings reveal that the derived perceptual clusters and defined categories fit relatively well with the listeners' performance. Distinctive feature systems in phonological theory appear to provide some basis for the clustering of phonemes.
Multichannel microscopy has emerged as a technique for imaging multiple targets (molecules, protein distributions, etc.) simultaneously. Discovering the relative changes in these targets (i.e. distribution of differen...
详细信息
Multichannel microscopy has emerged as a technique for imaging multiple targets (molecules, protein distributions, etc.) simultaneously. Discovering the relative changes in these targets (i.e. distribution of different proteins) is fundamental for understanding cell structure and function. We describe a new method for quantifying and visualizing relationships between multiple targets, from a set of segmented multichannel cells. The method is based on combining the canonical correlation analysis technique with a framework for analyzing images based on the concept of optimal mass transportation. We apply the method towards understanding chromatin distribution in cancer nuclei as a function of nuclear envelope shape. We also show that sub cellular distribution of mitochondria can be used to predict the sub cellular localization of actin fibers in yeast cells. Finally, we also describe the application of the method towards understanding relationships between nuclear and cellular shapes in 2D HeLa cells. We believe that the method could serve as a general tool for mining relationships between different sub cellular protein/molecule distributions as well as organelle shapes.
In this paper comparison of the two innovative signal processing methods for analysis of both EEG and EMG biomedical signals is in short presented. The reason for that is caused by the fact, that nowadays the broad an...
详细信息
In this paper comparison of the two innovative signal processing methods for analysis of both EEG and EMG biomedical signals is in short presented. The reason for that is caused by the fact, that nowadays the broad analysis of various biomedical signals is extremely popular. The first method presented in this paper relies on kernel density estimators application. Implementation of such method enables construction of densitograms for the examined bio-signals. One of the biggest advantages of this method is that it allows to obtain statistically filtered signals, which results in making the whole signal processing task significantly quicker. The second method described in this paper is based on basic mathematical operations only. Despite its simplicity the whole process can be implemented on almost any hardware platform, including those with very limited computational capabilities. Also it makes the task quick. In accordance with the conducted experiments - the method is also efficient and as it can also be implemented on embedded platform and the algorithm can be rewritten in any programming language, the potential application of this method is wide.
Recent research suggests DNA repeats play critical roles in cellular regulatory functions and disease development. Also, repeat variability among different species, or the same species, is an important indicator for t...
详细信息
Recent research suggests DNA repeats play critical roles in cellular regulatory functions and disease development. Also, repeat variability among different species, or the same species, is an important indicator for the development of specific phenotypes. Similarities in repetitive sequences among different species have been shown to indicate deeply conserved functions. Patterns such as ultra conserved elements (UCEs), tandem repeats, and palindromes have been of interest. Researchers utilize various computational approaches to aid in the identification of each of these types of patterns. The challenge associated with identifying repeats across a collection of genomes arises from the amount of data stored within DNA. The human genome alone consists of more than 3.1 billion base pairs, and intermediate data generated by alignment- and hash-based approaches are substantial. This sort of all-against-all analysis on a large collection of genomic sequence data often requires data to be reprocessed when new genomes are collected. To handle data of this scale, we utilize the Hadoop Distributed File System running on a cluster of 11 relatively inexpensive nodes, each containing a quad-core commodity processor. Furthermore, to alleviate redundant computation, intermediate data are organized in HBase, allowing us to incrementally process new genomic data without having to reprocess existing genomes. Our approach lends a cost-effective, flexible, robust, and scalable solution to the challenge of identifying various types of repetitive sequences across a collection of genomes. In this study, we benchmark our method using a collection of 6 genomes, summing to an approximate total of 14.2 billion base pairs. Three case studies are presented, demonstrating a 10.4 times speedup over previous state-of-the-art approaches and linear scalability.
In this paper, a multiresolution approach is proposed for texture characterization of breast tumors in dynamic contrast-enhanced magnetic resonance images. The decomposition scheme represented by the stationary wavele...
详细信息
In this paper, a multiresolution approach is proposed for texture characterization of breast tumors in dynamic contrast-enhanced magnetic resonance images. The decomposition scheme represented by the stationary wavelet transform (SWT) is investigated in terms of its' ability to discriminate between malignant and benign tumors. The mean and entropy of the detail subimages produced for the specific decomposition scheme are used as texture features. The extracted features are subsequently provided into a linear classifier in a leave-one-out cross-validation setting. The experimental results for the proposed features exhibit high performance, when compared to the existing approaches, with the classification accuracy approaching 0.91.
暂无评论