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Reliable Localization for Wireless Sensor Networks in Complex Environments
Xiaolei Liu,Yongji Ren,Xuguang Xin,Liping Zhang,Jixiang Chen 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.10
Although localization has been widely studied for Wireless Sensor Networks (WSNs), the complex environments and the large network scale pose severe challenges and make it necessary to develop new reliable localization algorithms. In this paper, we propose a novel Multi-Hop Localization Algorithm for large-scale WSNs in complex environments. This work is based on the consideration that the localization process would encounter several kinds of adverse factors with different nature at the same time (e.g. anisotropic network characteristics, ranging uncertainty, link quality of multihop paths, etc.), which lead to obvious degradation of localization performance. Unlike most of the existing schemes, we transform the localization problem in complex environments into a hybrid constraint satisfaction problem (CSP) which is composed of three different kinds of constraints, i.e. spatial constraint, network situation constraint, and confidence constraint. Set-membership approach and interval analysis method have been utilized to deal with the CSP and determine the positions of sensor nodes. Simulation results show that our scheme is an effective and efficient approach to localization in large-scale WSNs.
The Method of Finding Potentially Churning Customers Based on Social Networks
Wanqiu Huang,Xuguang Jia,Fen Tian,Yu Zhang,Zhe Zhou 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.11
Customer churn analysis has become an important focus of corporate marketing. It will be a great help to profitability if there is a method can find losing customers in time. In the paper, a method based on RFM and Cross-correlation model is proposed. Firstly, the customer’s value is calculated by RFM. Secondly, the typical losing curves of customer value are matched via cross-correlation. And finally, integrated with social network analysis (SNA) and community detection, the group of potential losing customers are revealed. The effectiveness of the presented method has been proven in a dataset of retail sales records.
Xiaona Huang,Hao Zhang,Xuguang Wang,Xiutian Yang,Rongzhuang Lin,Fan Zhang,Ying Liu,Kun Xu,Chao Zhou,Pixin Wang 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.127 No.-
During cementing construction, H2S gas leak from micro-cracks of cement ring or cementing interface,seriously damaging wellbore integrity and shortening the life of wells. Therefore, microcrack selfhealingcement technology is of great significance for oil wells to maintain the durability of cement ringsand adapt to complex underground environments. Herein, acrylamide (AM), acrylonitrile (AN) and Nvinylformamide(NVF) were used as functional monomers, and laponite was added to prepareLaponite-poly(acrylamide-acrylonitrile-n-vinylformamide) nanocomposite hydrogel (L-PMAN) withexcellent mechanical strength as micro-crack repair agent for gas-triggered cementing cement sheath. Considering the difference of chemical environment in the process of wellbore cement slurry sealingand subsequent micro-fracture plugging, different structural units were selected to design amphotericstructure. The construction of zwitterionic structure makes it exhibit excellent swelling behavior in saltsolution while maintaining 80% of the original mechanical strength. More importantly, after adding LPMANpowder,cement stone (C1) can achieve good repair of microcracks under the trigger of H2S within3 days, and the maximum gas breakthrough pressure can reach 2.5 MPa, indicating the great potentials ofthe L-PMAN for plugging microcracks in cement sheath.
Affection-enhanced Personalized Question Recommendation in Online Learning
Mingzi Chen,Xin Wei,Xuguang Zhang,Lei Ye 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.12
With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students’ affection into traditional CDM by employing the non-compensatory bi-dimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students’ responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.
Kim, Soo-Jin,Soo, Chia,Zhang, Xinli,Zhang, Xuguang,Kim, Sung Ha,Kang Ting Korean Academy of Oral Biology and the UCLA Dental 1998 International Journal of Oral Biology Vol.23 No.4
Fetal rat skin undergoes transition from scarless fetal to adult-type repair with scarring between day 16 and day 18 of gestation (term=21 days). TGF-β family has been implicated in this ontogenetic transition. Specifically, TGF-β1 and -β2 promote scarring while TGF-β3 may reduce scarring. However, little is knowm about the endogenous mRNA expression of TGF-β ligands, TGF-β masking protein (TGF-β-MP), or potential modulators during skin development. The aim of this study was to analyze the endogenous mRNA expression of TGF-1,2,3 ligands. TGF-β-MP, fibromodulin and decorin, as a function of gestation age in fetal rat skin. Fetal dorsal skin from gestation days 14.5, 16.5, 18.5, and 21.5 was harvested and frozen in liquid nitrogen. Total RNA from each time point was isolated and relative mRNA quantitation was performed using reverse trancription-polymerase chain reaction (RT-PCR). Correct PCR products were confirmed by probing with an internal oligonucleotide. Densitometric values were normalized to GAPDH control and calculated for induction relative to term fetal skin. Our results indicate that: 1) TGF-βligands were not significantly up-regulated as a function of gestation age 2) two TGF-β activity modulators. TGF-β-MP and fibromodulin were significantly down-regulated late in gestation 3) decorin was significantly up-regulated. In conclusion, our data suggest that fetal skin may have different TGF-β modulator profiles compared to adult-type skin.
Lulu Guo,Shushu Zhao,Guimao Yang,Lifeng Gao,Yanhong Wu,Xuguang Zhang 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.126 No.-
Perovskite oxide semiconductors have attracted tremendous interest in gas sensing due to their promisingproperties of tunable active sites, excellent catalytic ability and good structural stability. Nevertheless, the rapid synthesis of perovskite oxides and controlled regulation of their surface oxygenvacancies remains a great challenge. Herein, we report a novel metal–organic frameworks (MOFs) selftemplatestrategy for the rapid and large-scale preparation of LaFeO3 nanoparticles (MLaFeO3) withabundant oxygen vacancies. Benefit from the introduction of oxygen vacancies, the resultantMLaFeO3 gas sensor exhibit excellent formaldehyde (HCHO) sensing performance at a low operatingtemperature of 160 C, including high sensitivity (Rg/Ra = 8.9 @ 100 ppm), fast response/recovery rate(53 s/32 s), low detection limit (1 ppm) and excellent selectivity. Comprehensive density functional theory(DFT) calculation and spectral characterizations reveal that oxygen vacancies play a vital role in promotingthe adsorption and activation of O2 and HCHO molecules, and accelerate the chemical reaction onthe sensing materials surface. Most importantly, it proves the promising application of MLaFeO3 sensorin food safety assessment. This work not only provides a simple strategy for constructing oxygen vacanciesenriched LaFeO3, but also demonstrates the application potential of LaFeO3-based gas sensors in thefield of formaldehyde detection.