Hardware Implementation of Two-level Scheduling Algorithm in μC/OS-II

Guangwu Zhang,Yan Li,Yidong Chen,Huaiguo Dong,Huanhuan Chi,Min Shi,Junfeng Gao 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.4

Aiming at the problem that μC/OS-II does not support round-robin scheduling of the same priority task, a two-level hybrid task scheduling strategy was proposed. In the first level, by putting the task priority as criterion for task scheduling, a preemptive scheduling of different priority task was implemented. And in the second level, adopting time slice circulars scheduling strategy, round-robin scheduling of same priority task was implemented. The waiting list of tasks was designed by on-chip registers of FPGA and the ready list of tasks was designed by RAM of FPGA, and to implement time slice circulars scheduling, hardware circuit for finding successor of task was designed. The system adopted VHDL, and simulated by the software ISE10.1. The simulation results show that the hardware implementation of the system is well-worked.

Maximal United Utility Degree Model for Fund Distributing in Higher School

Zhang, Xingfang,Meng, Guangwu Korean Institute of Industrial Engineers 2013 Industrial Engineeering & Management Systems Vol.12 No.1

The paper discusses the problem of how to allocate the fund to a large number of individuals in a higher school so as to bring a higher utility return based on the theory of uncertain set. Suppose that experts can assign each invested individual a corresponding nondecreasing membership function on a close interval I according to its actual level and developmental foreground. The membership degree at the fund $x{\in}I$ is called utility degree from fund x, and product (minimum) of utility degrees of distributed funds for all invested individuals is called united utility degree from the fund. Based on the above concepts, we present an uncertain optimization model, called Maximal United Utility Degree (or Maximal Membership Degree) model for fund distribution. Furthermore, we use nondecreasing polygonal functions defined on close intervals to structure a mathematical maximal united utility degree model. Finally, we design a genetic algorithm to solve these models.

RETCAM: An Efficient TCAM Compression Model for Flow Table of OpenFlow

Chaoqin Zhang,Penghao Sun,Guangwu Hu,Liang Zhu 한국통신학회 2020 Journal of communications and networks Vol.22 No.6

OpenFlow is a widely adopted dataplane protocol insoftware-defined networking (SDN). However, the expansion ofsupported match fields in OpenFlow brings additional pressure tothe storage space of ternary content addressable memory (TCAM)in physical device, since the arbitrary wildcard support in thematch field of OpenFlow relies heavily on TCAM for looking-upspeed. In this paper, a mathematical model aiming at the storagespace reduction of the flow table in TCAM is presented, which isnamed as RETCAM. RETCAM analyzes the relationships amongall the match fields and then categorize the redundancy amongdifferent fields into three types. Based on the three redundancytypes, three compression algorithms named as inter-field merge,field mapping and intra-field compression are presented. The outcomes of each compression algorithm are flow entries with smallerbit-width which is sent to TCAM for flow matching. In this way, theflexibility of OpenFlow is not harmed, thus maintaining the function integrity of the original flow table. Simulation at the end showsthat RETCAM saves almost about 60% of TCAM space for a givenflow table with no damage to the function integrity of OpenFlow,and the compression performance stands stable with the increaseof flow table size.

Maximal United Utility Degree Model for Fund Distributing in Higher School

Xingfang Zhang,Guangwu Meng 대한산업공학회 2013 Industrial Engineeering & Management Systems Vol.12 No.1

The paper discusses the problem of how to allocate the fund to a large number of individuals in a higher school so as to bring a higher utility return based on the theory of uncertain set. Suppose that experts can assign each invested individual a corresponding nondecreasing membership function on a close interval I according to its actual level and developmental foreground. The membership degree at the fund x ∈ I is called utility degree from fund x, and product (minimum) of utility degrees of distributed funds for all invested individuals is called united utility degree from the fund. Based on the above concepts, we present an uncertain optimization model, called Maximal United Utility Degree (or Maximal Membership Degree) model for fund distribution. Furthermore, we use nondecreasing polygonal functions defined on close intervals to structure a mathematical maximal united utility degree model. Finally, we design a genetic algorithm to solve these models.

Mechanical behaviour of partially encased composite columns confined by CFRP under axial compression

Jiongfeng Liang,Guangwu Zhang,Jianbao Wang,Minghua Hu 국제구조공학회 2019 Steel and Composite Structures, An International J Vol.31 No.2

This paper presents the results of an experimental study to investigate the mechanical behavior of partially encased composite columns confined by CFRP under axial compression. The results show that the failure of the partially encased composite columns confined by CFRP occurred due to rupture of the CFRP followed by local buckling of the steel flanges. External wrapping of CFRP effectively delayed the local buckling of the steel flanges. The load carrying capacity of the column increased with the application of CFRP sheet. And the enhancement effect of the column was increased with the number of CFRP layer.

Improvement of SVM Image Reconstruction Algorithm in ECT System

Li Yan,Song Haifeng,Zhang Guangwu,Chen Deyun,Wang Zhao,Cui Peng 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.3

Due to the problem of low imaging accuracy and slow imaging speed when applying SVM image reconstruction algorithm in ECT system to dealing with a large amount of sample data set, the method of combining feature dimension reduction with SVM algorithm is proposed. This method classifies the sample data by using the way of clustering and extracts the feature parameter, finds out the connection between each sample and the feature, and deals the sample data with dimension reduction, thus finally getting the high-quality training sample. Then it trains the simplified sample data by applying SVM algorithm and obtains decision function, then the decision function is used to predict and image. The experimental results of image reconstruction show that this method greatly reduces the running time and improves the accuracy of imaging compared to using the SVM algorithm alone.

Effect of crumb rubber on compressive behaviour of CRCFST stub columns

Dawei Liu,Jiongfeng Liang,Guangwu Zhang,Jianbao Wang 사단법인 한국계산역학회 2020 Computers and Concrete, An International Journal Vol.25 No.3

This paper investigates the effect of crumb rubber (CR) on compressive behaviour of crumb rubber concrete filled steel tube (CRCFST) stub columns. Therefore, experiments on 16 stub columns subjected to axial loading are carried out. The results show that the failure modes of CRCFST stub columns with different CR replacement ratios and CR size are similar, manifested the buckling of the outer steel tube. The axial bearing capacity and stiffness both decrease with an increase in CR replacement ratio, and with decreasing CR size.

Research and Application of NSSN Neural Network in Electrical Capacitance Tomography Image Reconstruction

Daoyang Yu,Yan Li,Yuehua Li,Guangwu Zhang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.9

Levonorgestrel-releasing intrauterine system-based therapies for early- stage endometrial cancer: a systematic review and meta-analysis

Hongyi Wei,Ningning Pan,Wen Zhang,Guangwu Xiong,Wenping Guo,Zhe Dong,Caihong Ma 대한부인종양학회 2023 Journal of Gynecologic Oncology Vol.34 No.2

Objective: To conduct a systematic review and meta-analysis of studies evaluating the oncological and fertility outcomes of early-stage endometrial cancer (EC) treated with the levonorgestrel-releasing intrauterine system (LIUS)-based regimens. Methods: The Meta-analyses Of Observational Studies in Epidemiology statement for meta-analyses was followed. Searches were conducted on MEDLINE, Embase, PubMed, Preprints, and the Cochrane Central Register of Controlled Trials from January 1990 to August 4, 2022. The Joanna Briggs Institute Critical Appraisal Checklist was used for quality assessment. The primary endpoint was the complete response (CR) rate and the secondary endpoints were relapse, pregnancy, and live birth rate. Results: A total of 25 studies (821 women) were included. The CR rate of LIUS-based regimens was 63.4% (95% confidence interval [CI]=52.3%–73.2%), with 29.6% (95% CI=23.3%–36.8%) of cases experiencing recurrence during follow-up. In sensitivity analyses, patients younger than 45 years of age with a body mass index <30 kg/m2 who were treated with LIUS-based regimens achieved a high CR rate of 84.6% (95% CI=80.3%–88.1%) over a median follow-up of more than 24 months. Overall pregnancy and live birth rates were 37.9% (95% CI=24.1%–53.9%) and 39.3% (95% CI=24.0%–57.0%), respectively. No statistical differences were apparent in CR or relapse rates among the LIUS+GnRH agonist, LIUS+oral progesterone, or hysteroscopic resection followed by LIUS subgroups. Conclusion: LIUS-based therapies are viable for the conservative management of early-stage endometrioid EC on CR and fertility outcome.

Practical Preparation of Carbon Black/Carbon Nitride Compounds and Their Photocatalytic Performance

Shaozheng Hu,Haoying Wang,Fei Wang,Jin Bai,Lei Zhang,Xiaoxue Kang,GuangWu 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.10

Here we report a carbon-black-modified g-C3N4 nanocomposite prepared by a convenient method and its photocatalytic performance, which was compared with other carbon-material-, carbon nanotube (CNT)-, C60-, and graphene (GR)-modified g-C3N4 nanocomposites. X-ray diffraction, N2 adsorption, UV–vis spectroscopy, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy, and photoluminescence were used to characterize the prepared composite material. The results reveal that incorporating g-C3N4 with carbon materials decreases the bandgap and the electron–hole recombination rate of the prepared catalysts. No significant difference was observed in the structural and optical properties among these four series of carbon-material-modified g-C3N4 nanocomposites. Carbon-based materials cannot act as visible-light sensitizers but they can facilitate the separation and transport of photogenerated carriers. These composites obey a tentative reaction mechanism similar to rhodamine B (RhB) photocatalytic degradation. Carbon-black-modified g-C3N4 exhibits comparable activity and stability as those of GR-modified g-C3N4 , which is better than the modification by C60 and CNTs. Compared to CNTs, GR, and C60 , carbon black is a cheap and effective carbon source with excellent photocatalytic performance for the preparation of carbon material/g-C3N4 nanocomposites.