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Cong Feng,Zhaojun Yang,Chuanhai Chen,Jinyan Guo,Hailong Tian,Fanning Meng 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.6
Accuracy retention is an important performance index of CNC machine tools. At present, research on the evaluation of machining accuracy retention of CNC machine tools mainly focuses on accuracy value of a fixed time point or different time periods, but studies on the fluctuation degree of degradation trajectory related to time change are limited. Extracting simple and effective degradation characteristics of machining accuracy and then evaluating machining accuracy retention considering fluctuation of degradation trajectory are necessary. The volume error model of CNC machine tools is established on the basis of multibody system theory in this study. Three-dimensional volume error vector is transformed into one-dimensional machining accuracy degradation by calculating offset distance between spatial error and origin points. Degradation data obtained via regular measurement and calculation are used to establish the complete degradation trajectory model of the CNC machine tools machining accuracy using radial basis function interpolation method according to the fluctuation degree of degradation trajectory, and concepts of average degradation rate and average degradation amount are defined. Lastly, examples showed that these two indicators can intuitively reflect fluctuation degree of machining accuracy degradation of CNC machine tools and effectively and quantitatively evaluate accuracy retention of CNC machine tools. The quantitative evaluation method of accuracy retention of CNC machine tools defined in this study considers the fluctuation degree of accuracy degradation trajectory. The quantitative evaluation index of accuracy retention demonstrates satisfactory engineering application because it can reflect not only the accuracy change of a single machine tool but also accurately compare the accuracy retention between different machine tools.
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Power and QoS Aware Multi-level Resource Coordination and Scheduling in Virtualized Servers
Congfeng Jiang,Jingling Mao,Dongyang Ou,Yumei Wang,Xindong You,Jilin Zhang,Jian Wan 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.11
Modern cloud data centers are virtualized for resource multiplexing and services consolidations. Virtual machines (VMs) residing in the same server cluster share the same hardware resources and power supply while they may have different QoS requirements for their services and applications. Moreover, the power consumption of the server cluster is highly dynamic since different virtual machines have different workloads due to different services requests. Cluster level power and QoS coordination is crucial for data center level energy efficiency coordination as well as high quality service provisioning. In this paper we propose the power and QoS aware multi-level resource coordination and scheduling in virtualized servers, i.e., the cluster-level power control layer, the VMs resource allocation layer, and the QoS optimization layer. This three-level controlling framework schedules and allocates hardware resource for QoS guarantee and cluster level power management. We use dynamic frequency scaling for QoS mitigating when power budget changes. The experiment results show that the proposed multi-level coordinated control architecture consumes 5.36% and 6.96% less power for web servers and computing intensive virtual machines, respectively while it can guarantee the response time of web server and execution time of computing tasks no more than those without the proposed controlling approach.
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A Dual-Reduct Approach to Generate Core Rules
Lv Hanfei,Jiang Congfeng 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.9
In this paper, we propose a Dual-Reduct method to generate core rules from original data sets for decision making. We rank the rules by rule usefulness after the step of first reduct. Then we take the useful rules as condition attribute and construct another new decision table. After the step of second reduct we generate core rules from the new constructed decision table. In our approach the generation process is straightforward and objective. At the same time, our approach can significantly reduce the number of rules comparing to the traditional generation approach because we adopt rule usefulness as a measure of core rules. We also provide theoretical proofs and deductions. Our approach is proved to be feasible and effective in a production security system.
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Prison Identification Technology Research Based on Iris Image Recognition
Lv Hanfei,Jiang Congfeng 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.9
In this paper we study one prison identification method based on iris image recognition to meet the real-time identification requirements for prison management. The identification method for online real-time acquisition personnel iris image using pre-processing algorithm to improve the quality of image for subsequent feature extraction. Moreover, we use the coarse-to-fine approach to precisely extract the iris information. We combine the edge extraction method and the connected domain characteristics of multistage de-noising method to locate the inner and outer boundary. Finally we use image multiple features template matching method to recognize the iris information. The experimental results show that the proposed algorithm can correctly identify the iris image quickly. It can meet the requirements of the prison site management.
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One Hybrid Feature Set Filtering Localization Approach for Iris Recognition
Lv Hanfei,Jiang Congfeng 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.7
In this paper we propose one hybrid feature set filtering localization approach (HFSFLA) for iris recognition. Our HFSFLA method is different from the traditional iris localization method. Firstly we combine the advantages of both linear filtering method and non-linear filtering method, which can not only remove the noise and unwanted area but also keep the useful edge information of the iris image. Secondly, we propose feature set filtering localization to locate the iris precisely. Finally, we adopt one template matching method based on hamming distance deviation to recognize the iris information. Comparison experiments between the traditional localization method and the proposed HFSFLA are conducted on three iris databases. The experimental results show that the equal error rate and the correct recognition rate of the HFSFLA are better than those of the traditional localization method consistently in all iris data sets. And HFSFLA has high correct localization rate in the all three iris databases. It is a robust and rapid localization method.
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