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Wenxiu Zhu,Xinghao Liu,Zhaoguang Yan,Haipu Li 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.11
Considering the frequent detection in environment and the potential threat to human health and ecoenvironment, achieving removal of sulfamerazine (SMZ) from the aquatic environment is of great significance. In this study, the magnetically separable manganese-iron oxides/activated carbon (Mn-Fe3O4/AC) was synthesized by simple co-precipitation method and was used to remove SMZ from solution. Doping manganese oxide could change the specific surface areas of the prepared materials, thus providing more active sites for adsorption and improving the adsorption capacity of Mn-Fe3O4/AC for SMZ (maximum adsorption capacity 146mg g1). The kinetic and thermodynamic study showed that the adsorption of SMZ on Mn-Fe3O4/AC was endothermic and spontaneous, and followed the pseudo-second-order kinetics model and Langmuir model. Efficient removal of SMZ was attributed to varieties of noncovalent interactions between it and Mn-Fe3O4/AC, including electrostatic interactions, hydrogen bonds and - electron donor-acceptor interactions. In addition, SMZ could be degraded by oxidation via redox reactions. After six cycles of use, Mn-Fe3O4/AC still had good adsorption capability.
Exponential Decay Rate of Planar Switched Positive Linear Systems
Wenxiu Zhao,Yuangong Sun 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10
This paper is focused on the estimation of exponential decay rate of planar switched positive linear systems via common linear copositive Lyapunov functions. An exact exponential decay rate for all the state trajectories of the system under arbitrary switching has been given in terms of the minimal eigenvalue of some matrices related to system matrices. Finally, a numerical example illustrates the main result of this paper.
Wenxiu Wang,Shin Saito,Hidetaka Yakabe,Migaku Takahashi 한국자기학회 2013 Journal of Magnetics Vol.18 No.2
This paper shows a new effective approach to measure crystallization temperature of soft magnetic underlayer (SUL) for next generation of heat assisted perpendicular recording media. This approach uses temperature dependent reflectivity, which shows a clear jump when samples are crystallized. To achieve this measurement, an optical system is set up using hot plate and infrared laser. Reflectivity of SUL (Co70Fe30)92Ta₃Zr? shows a clear jump at its amorphous-crystalline transition temperature. Experiment results show this effect is clear in infrared region, and is weak for visible light.
Does Information Disclosed in “Use of Proceeds” from Prospectuses Affect IPO Initial Underpricing?
Tang Wenxiu,Zhou Zhong‐Guo 한국증권학회 2022 Asia-Pacific Journal of Financial Studies Vol.51 No.6
We study the impact of intended use of proceeds disclosed in the section of “Use of Proceeds” in prospectuses on ChiNext IPOs’ initial underpricing. After splitting the entire period into two non-overlapping sub-periods to control for regulatory changes and after controlling for the firm-level characteristics and market conditions, we find that the overall information disclosed from “Use of Proceeds” affects IPO initial underpricing significantly over the two sub-periods. Moreover, the intended use of IPO proceeds in several specific categories affects underpricing too. The proceeds raised for IPO firms’ information platform and research and development over the 2nd sub-period while the proceeds to promote marketing and sales and to expand existing products over the 1st sub-period are significantly and positively related to initial underpricing. The significance changes for the IPOs with the opportunity to change their use of proceeds after IPOs. We explore the causes and effects to explain our findings.
A Novel Data Clustering Algorithm based on Modified Adaptive Particle Swarm Optimization
Ganglong Duan,Wenxiu Hu,Zhiguang Zhang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.3
Fuzzy clustering is a popular unsupervised learning method used in cluster analysis which allows a point in large data sets belongs to two or more clusters. Prior work suggests that Particle Swarm Optimization based approach could be a powerful tool for solving clustering problems. In this paper, we propose a data clustering algorithm based on modified adaptive particle swarm optimization. We choose to use artificial bee colony algorithm combined with PSO technique to modify the traditional clustering methods due to its fast convergence and the presence of adaptive mechanisms based on the evolutionary factor. On the one hand, Particle Swarm Optimization is proven to be an effective and robust technique for fuzzy clustering. On the other hand, the artificial bee colony algorithm has the capability to generate diversity within the swarm when the guide bees are in the exploration mode. Through numerical analysis and experimental simulation, we verify that our algorithm performs much better compared with other state-of-the-art algorithms. Future research schedule is also discussed in the final part.
EXPERIENCE VALUE CO-CREATION IN TOURISM LIVESCAPE: THE ROLE OF INSPIRATION AND ENGAGEMENT
Hongmei Zhang,Wenxiu Wu,Boyang Shu,Yijiang Yang 글로벌지식마케팅경영학회 2023 Global Marketing Conference Vol.2023 No.07
An important segment, tourism e-commerce live streaming (TEcLS) has emerged as a new marketing channel actively embraced by destination marketing organizations (DMO) and tourist firms due to the COVID-19 pandemic. China, Japan, Australia, and many other nations have been selling such tourism products on various platforms. Live e-commerce generates a real-time interactive virtual environment that can be called a livescape. However, many tourism destinations or companies are unaware of the marketing science implications of live streaming and are unsure of their effectiveness or the intricacies of marketing live streaming. Previous research has explored the factors influencing consumer purchase behavior from the product, technology, and live-streamer perspectives, arguing that the advantages of breaking through time and space constraints, strong interactivity, the experience of reality, technological ease of use and usefulness, and celebrity aura encourage online purchases. However, limited investigation has been carried out on the impact of customers’ value-co-creation in livescape when watching tourism live streaming on their purchase intentions considering the key role of engagement. This calls for specific investigation of the phenomenon to facilitate live streaming design and tourism marketing. This study aims to explores the factors influencing consumer purchase intentions in the livescape based on a value co-creation research framework. Compared to traditional e-commerce, livescapes provides the “many-to-many” social presence and an immersive value co-creation platform. Thus, we focus on why and how social presence inspires customer engagement, ultimately leading to purchase intentions. This study finds that, as a crucial marketing tool, the social presence of tourism livescapes can promotes customer engagement, which in turn results in intentions to purchase tourism live-streaming products. Additionally, the mediating role of inspiration (inspired-by and inspired-to) between social presence and customer engagement is examined to reveal the influence mechanism in the tourism context. Finally, this study examines how to create an effective tourism livescape to enhance tourists social presence experience and inspire their engagement, which in turn increases their purchase intention.
Ganglong Duan,Wenxiu Hu,Zhiguang Zhang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.4
With the rapid development of computer science and technology, the data analysis technique has been a hottest research area in the pattern recognition research community. Cluster analysis is an important step in data mining. For clustering, various multi-objective techniques are evolved, which can automatically partition the data. In this paper, we propose a novel multilayer data clustering framework based on feature selection and modified K-Means algorithm. To facilitate the clustering, the proposed algorithm selects a representative feature subset to reduce the dimension of the raw data set. Besides, the selected feature subset has fewer missing values than the raw data set, which may improve the cluster accuracy. Another unique property of the proposed algorithm is the use of partial distance strategy. The experimental analysis and simulation indicate the feasibility and robustness of our method, in the future, we plan to conduct more mathematical analysis to modify our algorithm to achieve better result.