A novel application of the wavelet transform in retrieving the separate signals from overlapping chromatographic peaks and quantitative determination of the components in the overlapping ...chromatograms is described. The signals can be very easily separated by decomposing an overlapping chromatographic peak into localized contributions according to their frequency, and quantitative calculation can be done by studying the contributions of higher frequency. Overlapping peaks of two- and three-component mixtures were investigated by the method, and the results show excellent correlations between peak areas of the retrieved signals and the concentrations for all of the components.
Component number in overlapping multicomponent chromatogram was determined by a novel method—wavelet transform. Because of the characteristic of the double localization in time and frequency domain, ...the wavelet transform can decompose an overlapping chromatogram into contributions of different frequency. Among these contributions, there will be contributions which will represent the resolved chromatographic signals because their frequency is higher than the overlapping signal and lower than the high frequency noise. Therefore, the component number of an overlapping chromatogram can be determined by the number of peaks in the resolved chromatogram. Simulated data sets and a seriously overlapping 5-component chromatogram were investigated by the method. It was proved that the wavelet transform is a very easy and convenient method for detecting the component number in overlapping multicomponent chromatograms.
Research on 3D CAD Model Retrieval Algorithm Based on Global and Local Similarity Ma, Weifang; Wang, Peiyan; Cai, Dongfeng ...
2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS),
2019-Oct.
Conference Proceeding
Content-based 3D CAD model retrieval takes a 3D CAD model as input and finds other models with the same or similar structure. This paper proposes a two-stage retrieval method that can take into ...account the global and local similarity of CAD models. In the first stage, the CAD model formation candidate modles with high global matching degree with the query model is selected, and the TF-IMF (Term Frequency-Inverse Model Frequency) vector method is proposed to describe the global surface line distribution of the 3D CAD model. In the second stage, on the basis of the global similarity, the models which are locally similar with the query models are further filtered, and the attribute adjacency graphs between models are calculated by ACO (ant colony optimization) algorithm. Experimental results show that the proposed method achieves better retrieval performance than the maximum clique method based on the attribute adjacency graph (NDCG), which is 90.68%, and has higher retrieval efficiency.
Mobile edge caching provides a feasible solution to alleviate the heavy traffic through Device-to-Device (D2D) communication in cellular networks. By integrating the storage capacity of mobile user ...terminals (UT) and small base stations (SBS), we propose COPO, a COntext aware and POsterior caching scheme, instead of the traditional prior-caching scheme, which assigns contents in advance and then evaluates the system performance. COPO first defines a placement incidence matrix and uses the hit rate metric to study posterior-caching model, and then analyzes the copies of contents derived from the global initial allocation. After that, it places contents and their copies in appropriate nodes with a heuristic algorithm. Consecutively, numerical results are presented to compare the COPO with other caching schemes and show its efficiency and effectiveness.
Concept acquisition is an important part of domain ontology construction, and how to accomplish assistant concept acquisition becomes a research focus. In this paper, a character-based CRF model is ...adopted to obtain the set of candidate terms, and we propose an active learning algorithm to select a concept from the set of candidate terms for the user and use the stochastic gradient descent algorithm for training the weight of concepts. The experiment results show that this algorithm can effectively assist user acquire domain concepts, when the set of correct terms identified by the CRF model is used as candidate concepts, the value of MAP reaches 0.9335.
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