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在工业软件的用户生产现场测试中,可能由于操作风险、用户生产限制等约束而导致测试不充分,针对实践中的难点提出新的现场测试过程及其测试数据生成方法。定义了测试拆分子集及相关属性概念,根据现场因素设计的测试拆分子集提高了现场测试可主动性;综合现场因素设计拆分方案,采用针对性的辅助管理程序引导每个测试拆分子集的现场测试的实施;通过对生产现场的历史数据的处理建立针对各测试拆分子集的测试准备数据库,以搜索测试准备数据库的结果为依据并结合现场因素设计现场主动测试的输入数据,并说明了实践中的综合实施过程。通过石化生产优化控制系统的现场测试的实际案例,说明了这种方法能够在预防风险的前提下显著提高现场测试的充分性和测试效率。 相似文献
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Previous studies of tablet personal computers have concentrated on their use in education and healthcare. The current study focused instead on personal usage, investigating how satisfied users are with their own tablets after having used them in their daily lives. The objective was to identify the major features for tablets and to investigate how form factors affect the preference of functions by performing a comparison of iPad1 and Galaxy Tab. Also, gender and ethnicity were analyzed to determine whether they influence satisfaction with the devices. For e‐mail and web browsing functions, users’ ratings showed more satisfaction with the iPad1 since it has a larger display; for the e‐book reader function, users indicated higher satisfaction with the Galaxy Tab. Male users evaluated their devices by the function itself, whereas female users were mainly concerned with aesthetic aspects. Koreans indicated that they were less satisfied with their tablets than were other ethnic groups. 相似文献
95.
Chao Chen Wen Ji Seungmin Rho Bo-Wei Chen Yiqiang Chen 《Multimedia Tools and Applications》2016,75(22):14507-14524
Mobile video quality assessment plays an essential role in multimedia systems and services. In the case of scalable video coding, which enables dynamic adaptation based on terminal capabilities and heterogeneous network, variable resolution is one of the most prominent types of video distortions. In this paper, we propose a new hybrid spatial and temporal distortion metric for evaluating video streaming quality with variable spatio-temporal resolution. The key idea is to project video sequence into feature domain and calculate the distortion of content information from the projected principal component matrix and its eigenvectors. This metric can measures the degree of content information degradation especially in spatio-temporal resolution scalable video. The performance of the proposed metric is evaluated and compared to some state-of-the-art quality evaluation metrics in the literature. Our results show that the proposed metric achieves good correlations with the subjective evaluations of the EPFL scale video database. 相似文献
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Dae Kyung Kim Ji Yeon Hyun Sung Chul Kim Han Sung Kim Sei Young Lee 《Microfluidics and nanofluidics》2016,20(5):75
Micro-/nanoparticle-based systems are regarded as one of the possible candidates due to the engineerability and multifunctionality to maximize the accumulation of the nano-/microparticle-based drug delivery system on the target. Recent advances in nanotechnology enable the fabrication of diverse particle shapes from simple spherical particles to more complex shapes. The particle dynamics in blood flow and endocytosis characteristics of non-spherical particles change as the non-sphericity effect increases. We used a numerical approach to investigate the particle dynamics in linear shear flow near a wall. We examined the dynamics of slender cylindrical particles with aspect ratio γ = 5.0 in terms of particle trajectory, velocity, and force variation for different Stokes numbers over time. We identified the rotating inertia of particle near a wall as the source of inertial migration toward the wall. The drift velocity of slender cylindrical particles is comparable to that of discoidal particles. We discuss the possibilities and limitations of using slender cylindrical particles as a drug delivery system. 相似文献
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Meiyu Huang Yiqiang Chen Bo-Wei Chen Junfa Liu Seungmin Rho Wen Ji 《Peer-to-Peer Networking and Applications》2016,9(5):864-875
With the proliferation of healthcare data, the cloud mining technology for E-health services and applications has become a hot research topic. While on the other hand, these rapidly evolving cloud mining technologies and their deployment in healthcare systems also pose potential threats to patient’s data privacy. In order to solve the privacy problem in the cloud mining technique, this paper proposes a semi-supervised privacy-preserving clustering algorithm. By employing a small amount of supervised information, the method first learns a Large Margin Nearest Cluster metric using convex optimization. Then according to the trained metric, the method imposes multiplicative perturbation on the original data, which can change the distribution shape of the original data and thus protect the privacy information as well as ensuring high data usability. The experimental results on the brain fiber dataset provided by the 2009 PBC demonstrated that the proposed method could not only protect data privacy towards secure attacks, but improve the clustering purity. 相似文献
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