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Jie LIU Linlin QIN Jing GAO Aidong ZHANG
Ontology mapping is important in many areas, such as information integration, semantic web and knowledge management. Thus the effectiveness of ontology mapping needs to be further studied. This paper puts forward a mapping method between different ontology concepts in the same field. Firstly, the algorithms of calculating four individual similarities (the similarities of concept name, property, instance and structure) between two concepts are proposed. The algorithm features of four individual similarities are as follows: a new WordNet-based method is used to compute semantic similarity between concept names; property similarity algorithm is used to form property similarity matrix between concepts, then the matrix will be processed into a numerical similarity; a new vector space model algorithm is proposed to compute the individual similarity of instance; structure parameters are added to structure similarity calculation, structure parameters include the number of properties, instances, sub-concepts, and the hierarchy depth of two concepts. Then similarity of each of ontology concept pairs is represented by a vector. Finally, Support Vector Machine (SVM) is used to accomplish mapping discovery by training and learning the similarity vectors. In this algorithm, Harmony and reliability are used as the weights of the four individual similarities, which increases the accuracy and reliability of the algorithm. Experiments achieve good results and the results show that the proposed method outperforms many other methods of similarity-based algorithms.
Chuang ZHU Jie LIU Xiao Feng HUANG Guo Qing XIANG
This paper reports a high-quality hardware-friendly integer motion estimation (IME) scheme. According to different characteristics of CTU content, the proposed method adopts different adaptive multi-resolution strategies coupled with accurate full-PU modes IME at the finest level. Besides, by using motion vector derivation, IME for the second reference frame is simplified and hardware resource is saved greatly through processing element (PE) sharing. It is shown that the proposed architecture can support the real-time processing of 4K-UHD @60fps, while the BD-rate is just increased by 0.53%.
A novel element is proposed for manipulating two orthogonally-polarized electromagnetic waves, resulting in a polarization-reconfigurable flat transmitarray. This element consists of four identical metallic patterns, including a square frame loaded with short stubs and an internal crossed dipole, which are printed on the two sides of three identical flat dielectric slabs, with no air gap among them. With a linearly-polarized (LP) feeder, the flat transmitarray can transform the LP incident wave into a circular, horizontal or vertical polarization wave in a convenient way. By rotating the LP feeder so that the polarization angle is 0°, 45°, 90° or 135°, the waves of linear horizontal, right-handed circular, linear vertical or left-handed circular polarization can be obtained alternately. Simulations and experiments are conducted to validate the performance. The measured axial ratio bandwidths for RHCP and LHCP transmitarrays are about 7.1% and 5.1%, respectively, the 3dB gain bandwidths are 16.19% and 22.4%, and the peak gains are 25.56dBi and 24.2dBi, respectively.
Jie LIU Zhuochen XIE Huijie LIU Zhengmin ZHANG
In this paper, a new non-uniform weight-updating scheme for adaptive digital beamforming (DBF) is proposed. The unique feature of the letter is that the effective working range of the beamformer is extended and the computational complexity is reduced by introducing the robust DBF based on worst-case performance optimization. The robust parameter for each weight updating is chosen by analyzing the changing rate of the Direction of Arrival (DOA) of desired signal in LEO satellite communication. Simulation results demonstrate the improved performance of the new Non-Uniform Weight-Updating Beamformer (NUWUB).
In this letter, a novel and highly efficient haze removal algorithm is proposed for haze removal from only a single input image. The proposed algorithm is built on the atmospheric scattering model. Firstly, global atmospheric light is estimated and coarse atmospheric veil is inferred based on statistics of dark channel prior. Secondly, the coarser atmospheric veil is refined by using a fast Tri-Gaussian filter based on human retina property. To avoid halo artefacts, we then redefine the scene albedo. Finally, the haze-free image is derived by inverting the atmospheric scattering model. Results on some challenging foggy images demonstrate that the proposed method can not only improve the contrast and visibility of the restored image but also expedite the process.
Zijie LIU Can CHEN Yi CHENG Maomao JI Jinrong ZOU Dengyin ZHANG
Common schedulers for long-term running services that perform task-level optimization fail to accommodate short-living batch processing (BP) jobs. Thus, many efficient job-level scheduling strategies are proposed for BP jobs. However, the existing scheduling strategies perform time-consuming objective optimization which yields non-negligible scheduling delay. Moreover, they tend to assign BP jobs in a centralized manner to reduce monetary cost and synchronization overhead, which can easily cause resource contention due to the task co-location. To address these problems, this paper proposes TEBAS, a time-efficient balance-aware scheduling strategy, which spreads all tasks of a BP job into the cluster according to the resource specifications of a single task based on the observation that computing tasks of a BP job commonly possess similar features. The experimental results show the effectiveness of TEBAS in terms of scheduling efficiency and load balancing performance.
Wen-Yin HUANG Jia-Jie LIU Jou-Ming CHANG Ro-Yu WU
An n-dimensional folded hypercube, denoted by FQn, is an enhanced n-dimensional hypercube with one extra link between nodes that have the furthest Hamming distance. Let FFv (respectively, FFe) denote the set of faulty nodes (respectively, faulty links) in FQn. Under the assumption that every fault-free node in FQn is incident to at least two fault-free links, Hsieh et al. (Inform. Process. Lett. 110 (2009) pp.41-53) showed that if |FFv|+|FFe| ≤ 2n-4 for n ≥ 3, then FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv|. In this paper, we show that, under the same conditional fault model, FQn with n ≥ 5 can tolerate more faulty elements and provides the same lower bound of the length of a longest fault-free cycle, i.e., FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv| if |FFv|+|FFe| ≤ 2n-3 for n ≥ 5.
This Letter focuses on deep learning-based monkeys' head swing counting problem. Nowadays, there are very few papers on monkey detection, and even fewer papers on monkeys' head swing counting. This research tries to fill in the gap and try to calculate the head swing frequency of monkeys through deep learning, where we further extend the traditional target detection algorithm. After analyzing object detection results, we localize the monkey's actions over a period. This Letter analyzes the task of counting monkeys' head swings, and proposes the standard that accurately describes a monkey's head swing. Under the guidance of this standard, the monkeys' head swing counting accuracy in 50 test videos reaches 94.23%.