INVESTIGATION OF MICRO-BLOGGING MARKETING STRATEGY OF FASHION BRAND : VIA BIG DATA AND MACHINE LEARNING METHODOLOGY

Ruirui Zhang,Shan Xue,Leslie Davis Burns 글로벌지식마케팅경영학회 2014 Global Marketing Conference Vol.2014 No.2

In this paper, researchers investigated current fashion brands’ social media micro-blogging marketing strategy and consumers’ word of mouth reactions. More than 5,000 of the micro-blogs posted by fashion brands and 143,000 of customers’ comments were analysed in this study. Researchers firstly investigated the overall micro-blogging marketing structure for each fashion brand and compared them. Then researchers identified the type of expression pattern of each fashion brand currently in the micro-blogging context, negative or positive sentiments. Researchers found that fashion brands are using different micro-blogging marketing strategies. Forever21 used 61% micro-blogs for customer communication. H&M posted very diverse micro-blogs content to their official account. Their main micro-blogs were used for new product promotion (43%) and brand’s live event broadcasting (33%). Luxury brands, such as Burberry, more than 52% of micro-blogs posted last year were used for new product promotion and 36% of their micro-blogs contents included celebrities’ images of wearing Burberry product. Chanel used 60% of their micro-blogs to broadcast and introduce their brand events. There was no sale information posted on Chanel and Burberry’s micro-blogs account. Through sentiment analysis, researchers also found the brands have very positive electronic word of mouth (e-WOM). Particular, luxury fashion brands are having better e-WOM than fast fashion brands.

A TBM Cutter Life Prediction Method Based on Rock Mass Classification

Ruirui Wang,Yaxu Wang,Jianbin Li,Liujie Jing,Guangzu Zhao,Lichao Nie 대한토목학회 2020 KSCE Journal of Civil Engineering Vol.24 No.9

Cutter life is an important economical index for tunnel boring machines (TBM) excavation, and its prediction is widely concerned. This paper introduces a method for predicting cutter life on the basis of statistics and regression. Traditional researches only evaluate the average mileage or time interval of each cutter change. Differently, the proposed method can accurately predict the mileage position of each cutter relatively, on the premise of knowing the installment radius of each cutter and the rock properties along the tunnel. In this procedure, the influence of the rock classification and rock properties of each cutter passing area on their passing distance is obtained by linear regression. For proposing and verifying the prediction method, totally 1,200 records of cutter changing caused by normal cutter wear are collected from the 4th Section of Water Supply Project from Songhua River. Among them, randomly selected 920 samples are used to determine the regression coefficients involved in the method. The method is verified by the rest 280 samples, and a reliable predicted result is obtained (MAPE = 27%, and R2 = 0.69).

A Convenient Method to Prepare Novel Rare Earth Metal Ce-Doped Carbon Nitride with Enhanced Photocatalytic Activity Under Visible Light

Ruirui Jin,Shaozheng Hu,Jianzhou Gui,Dan Liu 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.1

Graphitic carbon nitride (g-C3N4) doped with the rare earth metal Ce was prepared by a simple method using melamine and Ce(SO4)2쨌4H2O as precursors. X-ray diffraction (XRD), UV-vis spectroscopy, Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), photoluminescence (PL) spectroscopy, and X-ray photoelectron spectroscopy (XPS) were used to characterize the prepared catalysts. The results indicate that the introduction of Ce inhibits the crystal growth of g-C3N4, decreases the bandgap energy, and increases the separation efficiency of photogenerated electrons and holes. The activities of Ce-doped g-C3N4 catalysts were tested in the photocatalytic degradation of rhodamine B (RhB) under visible light. The rate constant of Ce-doped g-C3N4 is 2.1횞 that of neat g-C3N4. A possible mechanism is proposed.

Fabricating patterned microstructures by embedded droplet printing on immiscible deformable surfaces

Ruirui Zhang,Lehua Qi,Hongcheng Lian,Jun Luo 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.105 No.-

The deposition of droplets inside the deformable surfaces has attracted researchers for decades due to itsapplication in direct-writing microporous polymer architectures, printing embedded flexible wires, patterningfunctional nanoparticles, etc. Herein, a patterned microstructure method based on droplets,named as the embedded droplet printing (EDP), is proposed. The experiments were conducted at aWeber number of 5.49–17.7 to explore the impact outcome, spreading laws and embedded morphologyof the droplets. The rebound of droplets impacting the viscous surface was suppressed under appropriateconditions. The spreading factor of the droplet impacting on the high viscous surface followed the powerlaw d*/ t a. However, the exponent a was observed to be in the range 0.042–0.031, much smaller than thereported values (0.1–1), which could be explained by the Oh number. The diameters of droplets wrappedwith viscous PDMS were only about 1/6th as compared to the spreading on the surface of PDMS precuredfor 30 min. In particular, a domain map was plotted in which patterns of solid bracts, plates and coffeerings were printed. Overall, EDP is a promising candidate to tailor the size, depth and morphology of dropletsfor preparing the patterned microstructures inside the soft materials.

Direct printing of surface-embedded stretchable graphene patterns with strong adhesion on viscous substrates

Ruirui Zhang,Lehua Qi,Hongcheng Lian,Jun Luo 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.109 No.-

The graphene patterns with piezoresistance behaviors, originating from the structural deformation andband-structure shift under strain, represent an attractive characteristic for developing the small strain(<10%) sensors for wearable devices. However, the insufficient adhesion between the patterns and substrateshas significantly limited their utility and reliability. Here, the surface-embedded graphene patternswere directly deposited on polydimethylsiloxane (PDMS) surfaces without hydrophilic treatmentvia the embedded droplet printing (EDP). The viscous PDMS films instead of the solid ones were usedas substrates, and the graphene patterns were partly embedded onto the viscous PDMS surfaces. Toassess the adhesion performance, a series of tests were performed. In the bending and tensile tests,the patterns strongly adhered to the PDMS films. Further, the patterns had a favorable increase in resistancein the tensile strain range of 0–3.5%. The resistance of the surface-embedded graphene patternsexhibited a negligible change for over 3 min in the ultrasonic bath. Finally, the relative resistance R/R0remained constant after the first two adhesion tests using a 3M tape. The surface-embedded graphenepatterns exhibited a strong adhesion to the flexible/stretchable substrates, indicating the application prospectin the field of flexible devices.

Sequential Prediction of the TBM Tunnelling Attitude Based on Long-Short Term Memory with Mechanical Movement Principle

Ruirui Wang,Yuhang Xiao,Qian Guo,Hai Wang,Lingli Zhang,Yaodong Ni 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.2

TBM tunnelling attitude controlling is a significant issue for guaranteeing the tunnel fitting the expected tunnel axis, with directly influence the tunnel quality. The key to solve the problem is to establish the relationship between the tunnelling attitude and the controlling parameters and to predict the tunnelling attitude accordingly. For this, this paper introduced a TBM tunnelling attitude predicting method. In detail, using Long-Short Term Memory (LSTM), the initial tunnelling attitude and the controlling parameters of each later ring are taken as input, while the tunnelling attitude of each later rings are regarded as the output, and the relationship between the input and output is established. Meanwhile, for avoid the over-fitting and error accumulation risk of LSTM, the theoretical relationship between the input and output is also built based on the TBM mechanical movement principle, and it is also involved into the LSTM-based relationship as constraints. The proposed method is verified by the field data collected from the 6th Section of the Qingdao Metro Project, and the results reveal that the proposed LSTM-based method is accurate and acceptable.

An Intrusion Detection Method Based on Changes of Antibody Concentration in Immune Response

Ruirui Zhang,Xin Xiao 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.1

Although the research of immune-based anomaly detection technology has made some progress, there are stillsome defects which have not been solved, such as the loophole problem which leads to low detection rate andhigh false alarm rate, the exponential relationship between training cost of mature detectors and size of selfantigens. This paper proposed an intrusion detection method based on changes of antibody concentration inimmune response to improve and solve existing problems of immune based anomaly detection technology. Themethod introduces blood relative and blood family to classify antibodies and antigens and simulate correlationsbetween antibodies and antigens. Then, the method establishes dynamic evolution models of antigens andantibodies in intrusion detection. In addition, the method determines concentration changes of antibodies inthe immune system drawing the experience of cloud model, and divides the risk levels to guide immuneresponses. Experimental results show that the method has better detection performance and adaptability thantraditional methods.

Study of Danger-Theory-Based Intrusion Detection Technology in Virtual Machines of Cloud Computing Environment

( Ruirui Zhang ),( Xin Xiao ) 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.1

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted IVMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply IVMIDS to the cloud computing platform.

Genomics and expression analysis of DHHC-cysteine-rich domain S-acyl transferase protein family in apple

Ruirui Xu,Yuemin Zhang,Meihong Sun,Xiuyan Zhao,Nan Xu,Xiaocui Luo 한국유전학회 2016 Genes & Genomics Vol.38 No.8

S-acylation is one of a group of lipid modifications that occurs on eukaryotic proteins, mediated by DHHC-CRD-containing proteins, which plays an important role in regulating the membrane association, trafficking and function of target proteins. Although genome-wide identification of PAT family has been carried out in yeast, mice, humans and Arabidopsis, little is known about apple PAT genes. In this study, a total of 33 putative apple PAT proteins, containing DHHC-CRD by domain analysis, have been identified, and were classified into three groups according to the phylogenetic analysis of PAT proteins in apple and Arabidopsis. More complex TMDs in the most MdPATs revealed the PM location of the gene family. Gene structure, gene chromosomal location and paralogs analysis of MdPAT genes within the apple genome demonstrated that tandem and segmental duplications, as well as whole genome duplications, have likely contributed to the expansion and evolution of the PAT gene family in apple. According to the microarray and expressed sequence tag (ESTs) analysis, the different expression patterns indicate that they may play different roles during fruit development and rootstock-scion interactions process. Moreover, PATs were performed expression profile analyses in different tissues, indicating that the PATs are involved in various aspects of physiological and developmental processes of apple. To our knowledge, this is the first report of a genome-wide analysis of the apple PAT gene family, and this genomic analysis of apple DHHCCRD PAT genes provides the first step towards a functional study of this gene family in apple.

INVESTIGATION OF MICRO-BLOGGING MARKETING STRATEGY OF FASHION BRAND: VIA BIG DATA AND MACHINE LEARNING METHODOLOGY

Ruirui Zhang,Shan Xue,Leslie Davis Burns 글로벌지식마케팅경영학회 2014 Global Marketing Conference Vol.2014 No.7

In this paper, researchers investigated current fashion brands’ social media micro-blogging marketing strategy and consumers’ word of mouth reactions. More than 5,000 of the micro-blogs posted by fashion brands and 143,000 of customers’ comments were analysed in this study. Researchers firstly investigated the overall micro-blogging marketing structure for each fashion brand and compared them. Then researchers identified the type of expression pattern of each fashion brand currently in the micro-blogging context, negative or positive sentiments. Researchers found that fashion brands are using different micro-blogging marketing strategies. Forever21 used 61% micro-blogs for customer communication. H&M posted very diverse micro-blogs content to their official account. Their main micro-blogs were used for new product promotion (43%) and brand’s live event broadcasting (33%). Luxury brands, such as Burberry, more than 52% of micro-blogs posted last year were used for new product promotion and 36% of their micro-blogs contents included celebrities’ images of wearing Burberry product. Chanel used 60% of their micro-blogs to broadcast and introduce their brand events. There was no sale information posted on Chanel and Burberry’s micro-blogs account. Through sentiment analysis, researchers also found the brands have very positive electronic word of mouth (e-WOM). Particular, luxury fashion brands are having better e-WOM than fast fashion brands.