• Title/Summary/Keyword: Evaluation models

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Young Rabbit Model for Pathophysiologic Study of Acute Lung Injury in Early Childhood (유아기 급성폐손상 병태생리 연구를 위한 어린 토끼 실험모델)

  • 권영민;최석철;박종원;김양원;이양행;황윤호;조광현
    • Journal of Chest Surgery
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    • v.36 no.8
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    • pp.545-558
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    • 2003
  • Adult respiratory distress syndrome (ARDS) is of particular interest because of its severity of the associated lung injury and its high mortality. However, the pathophysiologies of ARDS in infant and childhood groups are still not well clarified inspite of many previous investigations. To investigate the time course of pathophysiology of ARDS in infant and childhood groups, this study was designed with experimental endotoxin-induced ARDS model using young rabbits (8 week-old). Material and Method: Rabbits were divided into the control group (n=8) and the endotoxin-treated group (n=32). The endotoxin group was subdivided into 4 groups by the sampling times as 3, 6, 12 and 24 hr-groups (G- $E_{3,6,12,24,}$ each n=8). The experimental ARDS was made by a bolus injection of endotoxin (Escherichia coli serotype 055 : B5, 0.50 mg/kg) via rabbit ear vein. For evaluation of the hematologic and inflammatory markers, and superoxide dismutase (SOD) concentrations, the blood samples were taken from the heart. The bronchoalveolar lavage fluid (BALF) were obtained for analysis of the leukocytes and protein concentration. With biopsy of the lung, histopathologic changes of the lung were also evaluated. Result: In the endotoxin groups, significant leukopenia (owing to pancytopenia) occurred in 3 and 6-hr groups, which was followed by significant leukocytosis (owing to neutrophilia) in the 12 and 24-hr groups (p<0.05). Serum levels of tumor necrosis factor-$\alpha$ (TNF-$\alpha$) and interleukin-1 $\beta$ (IL-1 $\beta$) in the endotoxin groups were higher than those of control group (p<0.05). Serum levels of superoxide dismutase (SOD) of G- $E_{3}$ and G- $E_{6}$ were higher than those of control group, whereas those of G- $E_{12}$ were lower than those of control groups (p<0.05). Total leukocyte counts and protein con-centrations in BALF were significantly elevated in the endotoxin groups compared to the control group (p < 0.05). The hemorrhagic pattern of BALF showed occurred in the endotoxin groups. The endotoxin groups (in G- $E_{6}$) had severe infiltration of inflammatory cells (lymphocyte and monocyte) in the pulmonary interstitium and parenchyma, migrations of neutrophil and eosinophil into alveolar spaces and interstitial widening, which are the evidences of acute lung injury. In the endotoxin groups, there were significant positive correlations between the BALF findings and the immunologic markers (TNF-$\alpha$, IL-1$\beta$, SOD) (p<0.05). Conclusion: Severe acute lung injury occurred in all the endotoxin-treated rabbits. The pathophysiologic findings were so progressive until 6-hr by time dependant pattern, and then recovered slowly, Variable hematologic, immuno-logic, and pathologic factors were well correlated in the development and progression of endoxin-induced lung injury. The pathophysiologic responses were sensitive and rapid in young rabbit Young rabbit seemed to be a useful experimental animal model for infant and childhood groups.roups.

Studies of the Effects of Acupuncture Stimulation at Huatuo Jiaji(EX B2) Points on Axonal Regeneration of Injured Sciatic Nerve in the Rats (화타협척혈 침자극에 의한 손상 말초신경의 재생효과에 관한 연구)

  • Kim, Dae-Feel;Park, Young-Hoi;Keum, Dong-Ho
    • Journal of Korean Medicine Rehabilitation
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    • v.18 no.4
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    • pp.39-61
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    • 2008
  • Objectives : The present study was performed to investigate whether acupuncture stimulation in the rats affected regeneration properties of the injured sciatic nerve. A differential effect of acupuncture stimulation on the one point near the spinal nerve root controlling sciatic nerve activity and the other point in the peripheral area subordinated by injured nerve was compared. Materials and Methods: Rat sciatic nerves were injured by crush, and the effects on axonal regeneration on injured sciatic nerves were evaluated by acupuncture stimulation at two different regions. In proximal acupuncture stimulation group, acupuncture stimulation was performed on Huatuo Jiaji(EX B2) points located from L5 to S1 vertebral levels to stimulate the nearest spinal nerve root that innervates sciatic nerves. In distal acupuncture stimulation group, acupuncture stimulation was performed on Zusanli(ST 36) and Weizhong(BL 40) points to stimulate at peripheral area dominated by injured sciatic nerves. Acupuncture stimulation was given every other days for 1 or 2 weeks. Sciatic nerve tissues collected from acupuncture stimulation experimental groups, injury control group, and intact animal group were used for protein analysis by Western blotting or Hoechst nuclear staining. To determine axonal regeneration, Dil fluorescence dye was injected into the sciatic nerve 0.5 cm distal to the injury site in individual animal groups and Dil-labeled cells by retrograde tracing were measured in the DRG at lumbar 5 or in the spinal cord. DRG sensory neurons prepared from individual animal groups were used to measure the extent of neurite outgrowth and for immunofluorescence staining with anti-GAP-43 antibody. Results : Animal groups given proximal or distal acupuncture stimulation showed upregulation of GAP-43 and Cdc2 protein levels in the sciatic nerve at 7 days after injury. Cdk2 protein levels were strongly induced by nerve injury, but did not show changes by acupuncture stimulation. Phospho-Erk1/2 protein levels were elevated by acupuncture stimulation above those present in the injury control animals. These increase in regeneration-associated protein levels appeared to be related with increase cell proliferation in the injured sciatic nerves. Hoechst 33258 staining of sciatic nerve tissue to visualize nuclei of individual cells showed increased Schwann cell number in the distal portion of the injured nerve 7 and 14 days after injury and further increases by acupuncture stimulation particularly at the proximal position. Measurement of axonal regeneration by retrograde tracing showed significantly increased Dil-labeled cells in proximal acupuncture stimulation group compared to distal acupuncture stimulation group and injury control group. Finally, an evaluation of axonal regeneration by retrograde tracing showed increased number of Dil labeled cells in the DRG at lumbar 5 or in the ventral horn of the spinal cord at lower thoracic level at 7 days after nerve injury. Conclusions : The present data show that the proximal acupuncture stimulation at Huatuo Jiaji(EX B2) points governing injured sciatic nerves was more effective for axonal regeneration than the distal acupuncture stimulation. Further studies on functional recovery or associated molecular mechanisms should be critical for developing animal models and clinical applications.

Electronic Word-of-Mouth in B2C Virtual Communities: An Empirical Study from CTrip.com (B2C허의사구중적전자구비(B2C虚拟社区中的电子口碑): 관우휴정려유망적실증연구(关于携程旅游网的实证研究))

  • Li, Guoxin;Elliot, Statia;Choi, Chris
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.262-268
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    • 2010
  • Virtual communities (VCs) have developed rapidly, with more and more people participating in them to exchange information and opinions. A virtual community is a group of people who may or may not meet one another face to face, and who exchange words and ideas through the mediation of computer bulletin boards and networks. A business-to-consumer virtual community (B2CVC) is a commercial group that creates a trustworthy environment intended to motivate consumers to be more willing to buy from an online store. B2CVCs create a social atmosphere through information contribution such as recommendations, reviews, and ratings of buyers and sellers. Although the importance of B2CVCs has been recognized, few studies have been conducted to examine members' word-of-mouth behavior within these communities. This study proposes a model of involvement, statistics, trust, "stickiness," and word-of-mouth in a B2CVC and explores the relationships among these elements based on empirical data. The objectives are threefold: (i) to empirically test a B2CVC model that integrates measures of beliefs, attitudes, and behaviors; (ii) to better understand the nature of these relationships, specifically through word-of-mouth as a measure of revenue generation; and (iii) to better understand the role of stickiness of B2CVC in CRM marketing. The model incorporates three key elements concerning community members: (i) their beliefs, measured in terms of their involvement assessment; (ii) their attitudes, measured in terms of their satisfaction and trust; and, (iii) their behavior, measured in terms of site stickiness and their word-of-mouth. Involvement is considered the motivation for consumers to participate in a virtual community. For B2CVC members, information searching and posting have been proposed as the main purpose for their involvement. Satisfaction has been reviewed as an important indicator of a member's overall community evaluation, and conceptualized by different levels of member interactions with their VC. The formation and expansion of a VC depends on the willingness of members to share information and services. Researchers have found that trust is a core component facilitating the anonymous interaction in VCs and e-commerce, and therefore trust-building in VCs has been a common research topic. It is clear that the success of a B2CVC depends on the stickiness of its members to enhance purchasing potential. Opinions communicated and information exchanged between members may represent a type of written word-of-mouth. Therefore, word-of-mouth is one of the primary factors driving the diffusion of B2CVCs across the Internet. Figure 1 presents the research model and hypotheses. The model was tested through the implementation of an online survey of CTrip Travel VC members. A total of 243 collected questionnaires was reduced to 204 usable questionnaires through an empirical process of data cleaning. The study's hypotheses examined the extent to which involvement, satisfaction, and trust influence B2CVC stickiness and members' word-of-mouth. Structural Equation Modeling tested the hypotheses in the analysis, and the structural model fit indices were within accepted thresholds: ${\chi}^2^$/df was 2.76, NFI was .904, IFI was .931, CFI was .930, and RMSEA was .017. Results indicated that involvement has a significant influence on satisfaction (p<0.001, ${\beta}$=0.809). The proportion of variance in satisfaction explained by members' involvement was over half (adjusted $R^2$=0.654), reflecting a strong association. The effect of involvement on trust was also statistically significant (p<0.001, ${\beta}$=0.751), with 57 percent of the variance in trust explained by involvement (adjusted $R^2$=0.563). When the construct "stickiness" was treated as a dependent variable, the proportion of variance explained by the variables of trust and satisfaction was relatively low (adjusted $R^2$=0.331). Satisfaction did have a significant influence on stickiness, with ${\beta}$=0.514. However, unexpectedly, the influence of trust was not even significant (p=0.231, t=1.197), rejecting that proposed hypothesis. The importance of stickiness in the model was more significant because of its effect on e-WOM with ${\beta}$=0.920 (p<0.001). Here, the measures of Stickiness explain over eighty of the variance in e-WOM (Adjusted $R^2$=0.846). Overall, the results of the study supported the hypothesized relationships between members' involvement in a B2CVC and their satisfaction with and trust of it. However, trust, as a traditional measure in behavioral models, has no significant influence on stickiness in the B2CVC environment. This study contributes to the growing body of literature on B2CVCs, specifically addressing gaps in the academic research by integrating measures of beliefs, attitudes, and behaviors in one model. The results provide additional insights to behavioral factors in a B2CVC environment, helping to sort out relationships between traditional measures and relatively new measures. For practitioners, the identification of factors, such as member involvement, that strongly influence B2CVC member satisfaction can help focus technological resources in key areas. Global e-marketers can develop marketing strategies directly targeting B2CVC members. In the global tourism business, they can target Chinese members of a B2CVC by providing special discounts for active community members or developing early adopter programs to encourage stickiness in the community. Future studies are called for, and more sophisticated modeling, to expand the measurement of B2CVC member behavior and to conduct experiments across industries, communities, and cultures.

A Study on the Differences of Information Diffusion Based on the Type of Media and Information (매체와 정보유형에 따른 정보확산 차이에 대한 연구)

  • Lee, Sang-Gun;Kim, Jin-Hwa;Baek, Heon;Lee, Eui-Bang
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.133-146
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    • 2013
  • While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.

An Empirical Study on Motivation Factors and Reward Structure for User's Createve Contents Generation: Focusing on the Mediating Effect of Commitment (창의적인 UCC 제작에 영향을 미치는 동기 및 보상 체계에 대한 연구: 몰입에 매개 효과를 중심으로)

  • Kim, Jin-Woo;Yang, Seung-Hwa;Lim, Seong-Taek;Lee, In-Seong
    • Asia pacific journal of information systems
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    • v.20 no.1
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    • pp.141-170
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    • 2010
  • User created content (UCC) is created and shared by common users on line. From the user's perspective, the increase of UCCs has led to an expansion of alternative means of communications, while from the business perspective UCCs have formed an environment in which an abundant amount of new contents can be produced. Despite outward quantitative growth, however, many aspects of UCCs do not meet the expectations of general users in terms of quality, and this can be observed through pirated contents and user-copied contents. The purpose of this research is to investigate effective methods for fostering production of creative user-generated content. This study proposes two core elements, namely, reward and motivation, which are believed to enhance content creativity as well as the mediating factor and users' committement, which will be effective for bridging the increasing motivation and content creativity. Based on this perspective, this research takes an in-depth look at issues related to constructing the dimensions of reward and motivation in UCC services for creative content product, which are identified in three phases. First, three dimensions of rewards have been proposed: task dimension, social dimension, and organizational dimention. The task dimension rewards are related to the inherent characteristics of a task such as writing blog articles and pasting photos. Four concrete ways of providing task-related rewards in UCC environments are suggested in this study, which include skill variety, task significance, task identity, and autonomy. The social dimensioni rewards are related to the connected relationships among users. The organizational dimension consists of monetary payoff and recognition from others. Second, the two types of motivations are suggested to be affected by the diverse rewards schemes: intrinsic motivation and extrinsic motivation. Intrinsic motivation occurs when people create new UCC contents for its' own sake, whereas extrinsic motivation occurs when people create new contents for other purposes such as fame and money. Third, commitments are suggested to work as important mediating variables between motivation and content creativity. We believe commitments are especially important in online environments because they have been found to exert stronger impacts on the Internet users than other relevant factors do. Two types of commitments are suggested in this study: emotional commitment and continuity commitment. Finally, content creativity is proposed as the final dependent variable in this study. We provide a systematic method to measure the creativity of UCC content based on the prior studies in creativity measurement. The method includes expert evaluation of blog pages posted by the Internet users. In order to test the theoretical model of our study, 133 active blog users were recruited to participate in a group discussion as well as a survey. They were asked to fill out a questionnaire on their commitment, motivation and rewards of creating UCC contents. At the same time, their creativity was measured by independent experts using Torrance Tests of Creative Thinking. Finally, two independent users visited the study participants' blog pages and evaluated their content creativity using the Creative Products Semantic Scale. All the data were compiled and analyzed through structural equation modeling. We first conducted a confirmatory factor analysis to validate the measurement model of our research. It was found that measures used in our study satisfied the requirement of reliability, convergent validity as well as discriminant validity. Given the fact that our measurement model is valid and reliable, we proceeded to conduct a structural model analysis. The results indicated that all the variables in our model had higher than necessary explanatory powers in terms of R-square values. The study results identified several important reward shemes. First of all, skill variety, task importance, task identity, and automony were all found to have significant influences on the intrinsic motivation of creating UCC contents. Also, the relationship with other users was found to have strong influences upon both intrinsic and extrinsic motivation. Finally, the opportunity to get recognition for their UCC work was found to have a significant impact on the extrinsic motivation of UCC users. However, different from our expectation, monetary compensation was found not to have a significant impact on the extrinsic motivation. It was also found that commitment was an important mediating factor in UCC environment between motivation and content creativity. A more fully mediating model was found to have the highest explanation power compared to no-mediation or partially mediated models. This paper ends with implications of the study results. First, from the theoretical perspective this study proposes and empirically validates the commitment as an important mediating factor between motivation and content creativity. This result reflects the characteristics of online environment in which the UCC creation activities occur voluntarily. Second, from the practical perspective this study proposes several concrete reward factors that are germane to the UCC environment, and their effectiveness to the content creativity is estimated. In addition to the quantitive results of relative importance of the reward factrs, this study also proposes concrete ways to provide the rewards in the UCC environment based on the FGI data that are collected after our participants finish asnwering survey questions. Finally, from the methodological perspective, this study suggests and implements a way to measure the UCC content creativity independently from the content generators' creativity, which can be used later by future research on UCC creativity. In sum, this study proposes and validates important reward features and their relations to the motivation, commitment, and the content creativity in UCC environment, which is believed to be one of the most important factors for the success of UCC and Web 2.0. As such, this study can provide significant theoretical as well as practical bases for fostering creativity in UCC contents.

Development of New Variables Affecting Movie Success and Prediction of Weekly Box Office Using Them Based on Machine Learning (영화 흥행에 영향을 미치는 새로운 변수 개발과 이를 이용한 머신러닝 기반의 주간 박스오피스 예측)

  • Song, Junga;Choi, Keunho;Kim, Gunwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.67-83
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    • 2018
  • The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)

  • Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.163-177
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    • 2019
  • As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.