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Jun Cheng,Zongbo Yang,Junhu Zhou,Kefa Cen 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.2
Residence time of flue gas bubbles with different solution velocities and the influence of NOX and SO2 from flue gas on pH values of culture solutions were analyzed based on large-scale raceway reactors. Microalgal growth and CO2 fixation rates were also investigated with different gas flow rates. Bubble residence time was ~1.1 s when the solution velocity was 20 cm/s. The NOX and SO2 effects on microalgal growth were negligible, although 66% NOX and 95% SO2 were captured by the microalgal solution. Microalgal biomass productivity increased from 10.3 to 14.1 g/m2/d when flue gas flow rate increased from 20 to 50m3/h. CO2 fixation and microalgae biomass productivity increased further from 26.3 to 31.9 g/m2/d and from 14.1 to 17.1 g/m2/d, respectively, upon increase of flue gas flow rate from 50 to 150m3/h.
Jun Cheng,Bo Wang,Park, Ju H.,Wei Kang IET 2017 IET CONTROL THEORY AND APPLICATIONS Vol.11 No.12
<P>This study investigates the sampled-data reliable control for a class of Takagi-Sugeno (T-S) fuzzy semi-Markovian jump system (FSMJS). The system under consideration involves semi-Markov stochastic process that is described by the property of cumulative distribution function. To relax the difficulty of finding upper bounds in sample-and-hold behaviour of the FSMJS, a novel method named mismatched membership function is presented. Sufficient conditions that can guarantee the T-S FSMJS to be stochastically stable are given. More precisely, the reliable sampled-data controller is designed in terms of linear matrix inequalities. Finally, the validity of the presented approach is demonstrated by a controller design for a single-link robot arm model.</P>
Jun Cheng,Jian‑hua Zhao,Dengzhi Zheng,Ke He,Yu Guo 대한금속·재료학회 2021 METALS AND MATERIALS International Vol.27 No.3
The galvanized-Q235/AZ91D bimetallic material was achieved via solid–liquid compound casting, and the effect of theheat treatment at 250 °C for 3 h on the microstructure and mechanical properties of the galvanized-Q235/AZ91D bimetallicmaterial were investigated. The interface zone in the galvanized-Q235/AZ91D was composed of three different layers whichwere the FeAl3+ α-Mg, (α-Mg + MgZn), and α-Mg + (α-Mg + MgZn) from the galvanized-Q235 to AZ91D, successively. After the heat treatment, the (α-Mg + MgZn) eutectic structure was transformed into Al5Mg11Zn4to promote the microhardnessfrom 139.2 HV to reach 298.8 HV. In addition, the α-Mg and (α-Mg + Mg12Al17) eutectic structure in AZ91D wereseparately transformed into (α-Mg + Al5Mg11Zn4) and Al5Mg11Zn4resulting in the increasement of microhardness, from59.5 to 173.4 HV and 294.2 HV, respectively. Moreover, the interfacial shear strength was changed from 11.23 to 24.63 MPadue to the formation of Al5Mg11Zn4and the vanishment of MgZn.
Finite-time Boundness of H∞ Filtering for Switching Discrete-Time Systems
Jun Cheng,Hong Zhu,Shouming Zhong,Yu-Ping Zhang 제어·로봇·시스템학회 2012 International Journal of Control, Automation, and Vol.10 No.6
For switched discrete-time systems, switching behavior always affect the finite-time stability property, which was neglected by most previous research. This paper investigated the problem of finite-time boundness of H∞ filtering for switched discrete-time systems. Sufficient conditions which can ensure finite-time bounded and H∞ filtering finite-time boundness under arbitrary switching are derived. Based on the results of finite-time boundness and stochastic character, the closed-loop system trajectory stays within a prescribed bound. An example is given to illustrate the efficiency of the proposed method.
JunCheng Guo,YiJun Yang,Min Guo,XiaoDan Wang,Yang Juan,YunSuo Gao,LinQiu Fu,XiangLing Jiang,LinMei Fu,Tao Huang 대한신경정신의학회 2018 PSYCHIATRY INVESTIGATION Vol.15 No.4
Objective-To investigate the correlations of four genetic single nucleotide polymorphisms (SNPs) of brain-derived neurotrophic factor (BDNF) with posttraumatic stress disorder (PTSD). Methods-A total of 300 patients with sporadic PTSD and 150 healthy subjects (the control group) were selected according to the diagnostic criteria of PTSD (DSM-IV), and the genotypes of the BDNF SNPs G-712A, C270T, rs6265, and rs7103411 were detected by polymerase chain reaction and direct DNA sequencing to determine intergroup differences in the genotypes and allele frequencies; the pvalues were corrected with the permutation test. Results-The genotypes and allele frequencies of the SNPs G-712A, rs6265, and rs7103411 of BDNF showed no significant intergroup differences (p>0.05). However, the genotype and allele frequencies of C270T showed significant differences between the PTSD group and the control group (p<0.05). Conclusion-The SNP C270T of BDNF may be associated with PTSD. Individuals carrying the polymorphic T allele of C270T may be more likely to suffer from PTSD.
Venture Capital Backing and Issuance of Seasoned Equity Offerings: Evidence from China
Juncheng Li,Songling Yang,Hemei Li,Qiuyue Zhang,Qianqian Shi 한국증권학회 2020 Asia-Pacific Journal of Financial Studies Vol.49 No.6
We analyze how venture capital (VC) affects the timing of seasoned equity offering (SEO) issuance and the post-SEO performance of Chinese companies during the 2006–2018 period. Empirical analysis confirms that VC “accelerates” SEO issuance because of greater financing demands. Thus, VC-backed firms prefer to issue their first SEOs earlier than non-VC-backed firms. Moreover, quick SEOs promoted by venture capitalists are more underpriced because of information asymmetry.
Juncheng Liu,Guodong Zhang 한국물리학회 2008 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.53 No.5
The thermal stress field of CdZnTe single crystals grown with the vertical Bridgman method was simulated with the thermal elastic finite-element model. The effects of the growth parameters, the furnace temperature gradient, the crucible descending velocity, and the thickness of the graphite lm plating on the quartz crucible inner wall, on the thermal stress field were investigated. The stress at the crystal's edge is much larger than that at the crystal's center, and the stress at the crystal's bottom is larger than that at the crystal's top. Them aximum stress 'σmax'appearsat the location where the crystal adhere to the crucible's inner wall. When the furnace's temperature gradient was increased from 5 K/cm to 20 K/cm, the stress in the crystal increased a great deal. If no graphite lm was plated on the crucible's inner wall, the stress at the crystal's l edge increased several times while the stress at the crystal's center increased only a little. On the contrary, when the thickness of the graphite film was increased from 250 μm to 500 μm, up to a pure graphite crucible, the stress at the crystal's edge decreased a little, while the stress at the crystal's center decreased a lot. In the range of the 0.5 ∽ 3 mm/h, the crucible's descending velocity had little effect on the stress.
Evaluating the bond strength of FRP in concrete samples using machine learning methods
Juncheng Gao,Mohammadreza Koopialipoor,Danial Jahed Armaghani,Aria Ghabussi,Shahrizan Baharom,Armin Morasaei,Ali Shariati,Majid Khorami,Jian Zhou 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.26 No.4
In recent years, the use of Fiber Reinforced Polymers (FRPs) as one of the most common ways to increase the strength of concrete samples, has been introduced. Evaluation of the final strength of these specimens is performed with different experimental methods. In this research, due to the variety of models, the low accuracy and impact of different parameters, the use of new intelligence methods is considered. Therefore, using artificial intelligent-based models, a new solution for evaluating the bond strength of FRP is presented in this paper. 150 experimental samples were collected from previous studies, and then two new hybrid models of Imperialist Competitive Algorithm (ICA)-Artificial Neural Network (ANN) and Artificial Bee Colony (ABC)-ANN were developed. These models were evaluated using different performance indices and then, a comparison was made between the developed models. The results showed that the ICA-ANN model's ability to predict the bond strength of FRP is higher than the ABC-ANN model. Finally, to demonstrate the capabilities of this new model, a comparison was made between the five experimental models and the results were presented for all data. This comparison showed that the new model could offer better performance. It is concluded that the proposed hybrid models can be utilized in the field of this study as a suitable substitute for empirical models.
A novel multi-objective service composition architecture for blockchain-based cloud manufacturing
Tong Juncheng,Zhao Bo,An Yang 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.1
In recent years, many core technologies of Industry 4.0 have advanced significantly, particularly the integration of big data technology and cloud manufacturing (CMfg). The decentralization and traceability features of blockchain technology (BCT) provide an effective solution to provide trusted resource service in CMfg. Service composition is a core issue of CMfg to increase the value of digital assets. However, existing research on service composition based on BCT suffers from both the blockchain proof-of-work (PoW) mechanism and the service composition problem need to consume large computational overheads, as well as the blockchain fork problem affecting the system’s reliability, which reduces the usefulness of these schemes. To solve these problems, this paper proposes a novel multi-objective service composition architecture for blockchain-based CMfg (MOSC-BBCM). In MOSC-BBCM, first, a blockchain-chained storage structure is designed for the actual manufacturing cloud service constraint and scale dynamic changes, which can fully use the historical service information and accelerate the search for high-quality solutions. Second, to reduce the squandered computing resources in the PoW, a mining mechanism based on multi-objective service composition and optimal selection is proposed, where miners competitively solve a nondeterminate polynomial-hard problem to replace the mathematical puzzle. Finally, an incentive mechanism based on the environment selection method is proposed, which can avoid the fork problem while distributing on a labor basis. The effectiveness of the proposed MOSC-BBCM is verified in simulated numerical experiments of CMfg, which shows that the architecture provides a flexible and configurable scheme for blockchain-based CMfg with high availability.
An Improved Eclat Algorithm for Mining Association Rules Based on Increased Search Strategy
Zhiyong Ma,Juncheng Yang,Taixia Zhang,Fan Liu 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.5
Although Eclat algorithm is an efficient algorithm for mining association rules, there are some disadvantages which limit the efficient of Eclat. In this paper, we proposed an improved Eclat algorithm called Eclat_growth which is based on the increased search strategy. There are three main steps in the Eclat_growth algorithm. First, it scans the database and stores it into a table using vertical data format. Then, it builds an increased two-dimensional pattern tree and the TID_sets of itemsets in the vertical data format table are added into the pattern tree row by row. New frequent itemsets are generated by combining the new added item data with the existing frequent itemsets in the pattern tree. Finally, all frequent itemsets can be found by picking up all nodes of the pattern tree. In the process of generating new frequent itemsets, the prior knowledge is used to fully clip the candidate itemsets. In the process of generating an intersection of two itemsets and calculating the support degree, we proposed a new method called BSRI (Boolean array setting and retrieval by indexes of transactions) to reduce the run time. By comparing Eclat_growth with Eclat, Eclat-diffsets, Eclat-opt and hEclat, it is indicated that Eclat_growth has the highest performance in mining associating rules from various databases.