Wireless Networks - One of the biggest challenges of distributed software defined networks (SDNs) is to create load balancing on controllers to reduce response time. Although recent studies have... 相似文献
Due to its unique artistic value, mosaic ceramics are widely used in construction-related fields. To meet the artist's demand for high-quality mosaic ceramic to create artistic works, it is necessary to meet the needs for efficient screening of mosaic ceramic tiles. Different from the ordinary large-target ceramics, mosaic ceramics exhibit characteristics of small tile sizes, a variety of colors, large demand for quantities, and easy reflection on the surface. Common manual detection methods show problems of low efficiency or accuracy, easy to fatigue, and many others. To solve these problems, this paper proposes a new detection method to identify surface defects of mosaic ceramic tiles and designs a detection system platform to achieve rapid detection. The experiment proves that the detection system has a detection rate of 93.99% for small defects on the surface of mosaic ceramic tiles, and the detection time of a single mosaic ceramic tile is less than 0.06 s. The detection method can quickly and accurately screen out high-quality, defect-free mosaic ceramic tiles, which can effectively improve the quality and artistic value of mosaic ceramic art creation. 相似文献
For the advantages of high-temperature resistance, corrosion resistance and ultra-high hardness, SiCf/SiC composite is becoming a preferred material for manufacturing aero-engine parts. However, the anisotropy and heterogeneity bring great challenges to the processing technology. In this study, a nanosecond pulsed laser is applied to process SiCf/SiC composite, where the influence of the scanning speed and laser scanning direction to the SiC fibers on the morphology of ablated grooves is investigated. The surface characteristics after ablation and the involved chemical reaction of SiCf/SiC are explored. The results show that the increased laser scanning speed, accompanied by the decreasing spot overlap rate, leads to the less accumulation of energy on the material surface, so the ablation effect drops. In addition, for the anisotropy of the SiCf/SiC material, the obtained surface characteristics are closely dependent on the laser scanning direction to the SiC fibers, resulting in different groove morphology. The element composition and phase analysis of the machined surface indicate that the main deposited product is SiO2 and the carbon substance. The results can provide preliminary technical support for controlling the machining quality of ceramic matrix composites. 相似文献
In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.
Sr0.9La0.1TiO3 based textured ceramics (SLTT-S3T) with a texture fraction of 0.81 are successfully fabricated by the reactive template grain growth method, in which Sr0.9La0.1TiO3/20 wt%Ti was used as matrix and 10 wt% plate-like Sr3Ti2O7 template seeds were used as templates. The phase transition, microstructure evolution, and the anisotropic thermoelectric properties of SLTT-S3T ceramics were investigated. The results show that the ceramics are mainly composed of Sr0.9La0.1TiO3 and rutile TiO2 phases. Grains grow with a preferred orientation along (h00). A maximum ZT of 0.26 at 1073 K was achieved in the direction perpendicular to the tape casting direction. The low lattice thermal conductivity of 1.9 W/(m K) at 1073 K was obtained decreased by 34%, 40%, and 38% compared with non-textured, SrTiO3 and Sr0.9La0.1TiO3 ceramics prepared by the same process, can be attributed to the enhanced phonon scattering by the complex multi-scale boundaries and interfaces. This work provides a strategy of microstructural design for thermoelectric oxides to decrease intrinsic lattice thermal conductivity and further regulate thermoelectric properties via texture engineering. 相似文献
In this paper we report on the preparation and laser performance of transparent 3at.% Yb:Sc2O3 ceramics by reactive sintering of commercially available powders under vacuum followed by hot isostatic pressing (HIP). Combinations of different vacuum sintering temperatures (1650 °C and 1750 °C) and different HIP treatments (1700 °C and 1800 °C at 200 MPa) were tested in order to understand how these steps influence the microstructure and thus the optical and lasing properties of the ceramic samples. All the samples showed a good optical quality. The microstructure analysis and the laser tests showed that the vacuum pre-sintering temperature is the key factor determining the quality of the samples and the laser performances. The best values of slope efficiency i.e. ηL = 50 % and output power i.e. Pout = 6.62 W were obtained for the sample pre-sintered under vacuum at 1650 °C and hot isostatically pressed at 1800 °C. 相似文献
Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes. 相似文献
AbstractData mining techniques have been successfully utilized in different applications of significant fields, including medical research. With the wealth of data available within the health-care systems, there is a lack of practical analysis tools to discover hidden relationships and trends in data. The complexity of medical data that is unfavorable for most models is a considerable challenge in prediction. The ability of a model to perform accurately and efficiently in disease diagnosis is extremely significant. Thus, the model must be selected to fit the data better, such that the learning from previous data is most efficient, and the diagnosis of the disease is highly accurate. This work is motivated by the limited number of regression analysis tools for multivariate counts in the literature. We propose two regression models for count data based on flexible distributions, namely, the multinomial Beta-Liouville and multinomial scaled Dirichlet, and evaluated the proposed models in the problem of disease diagnosis. The performance is evaluated based on the accuracy of the prediction which depends on the nature and complexity of the dataset. Our results show the efficiency of the two proposed regression models where the prediction performance of both models is competitive to other previously used regression models for count data and to the best results in the literature. 相似文献