• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.4
• /
• pp.80-87
• /
• 2015

Memristor is a new kind of memory device whose resistance varies depending upon applied charge and whose previous resistance state is preserved even when its power is off. Ordinary memristor has a nonlinear programming characteristics about time when a constant voltage is applied. For the easiness of programming, it is desirable that resistance is programmed linearly about time. We had proposed previously a memristor bridge configuration with which weight can be programmed nicely in positive, negative or zero. In memristor bridge circuit, two memristors are connected in series with different polarity. Memristors are complementary each other and it follows that the memristance variation is linear with respect to time. In this paper, the linearization effect of weight programming of memristor bridge synapse is investigated and verified about both $TiO_2$ memristor from HP and a nonlinear memristor with a window function. Memristor bridge circuit would be helpful to conduct synaptic weight programming.

• Journal of Aerospace System Engineering
• /
• v.16 no.6
• /
• pp.54-63
• /
• 2022

Recently, electric propulsion aircraft with various propeller mounting positions have been under construction. The position of the propeller relative to the wing can significantly affect the aerodynamic performance of the aircraft. Placing the propeller in front of the wing produces a complex swirl flow behind or around the propeller. The up/downwash induced by the swirl flow can alter the wing's local effective angle of attack, causing a change in the aerodynamic load distribution across the wing's spanwise direction. This study investigated the influence of the distance between a propeller and a wing on the aerodynamic loads on the wing. The swirl flow generated by the propeller was modelled using an actuator disk theory, and the wing's aerodynamics were analysed with the VSPAERO tool. Results of the study were compared to wind tunnel test data and established that both axial and spanwise distance between the propeller and the wing positively affect the wing's lift-to-drag ratio. Specifically, it was observed that the lift-to-drag ratio increases when the propeller is positioned higher than the wing.

• Science of Emotion and Sensibility
• /
• v.25 no.3
• /
• pp.15-32
• /
• 2022

This study seeks to clarify the mechanisms of anthropomorphism and positive user experience. This study adopts the "computers are social actors" (CASA) paradigm to verify the causal relationship between social response and anthropomorphism and correctly explicate this paradigm. The intimacy-forming and anthropomorphizing effects of deep self-disclosure in interpersonal relationships were replicated in relationships between humans and conversational agents to induce both social response and anthropomorphism. Then, the mediating effect of intimacy on the anthropomorphizing effect of deep self-disclosure was explored with psychological models that revealed the causal relationships between social connections, including intimacy and anthropomorphism. Furthermore, we explored how intimacy and anthropomorphism trigger positive user experiences. The results demonstrated that the deeper the self-disclosure depth was, the more intimate and humanly the agent was perceived and the more positive the user experience was. In addition, the effect of self-disclosure depth on anthropomorphism and positive user experience was completely mediated by intimacy. This means that when using a computer with interpersonal characteristics, people anthropomorphize it and have a positive experience because people react socially to objects with social cues. This study bridges the gap between the CASA paradigm and anthropomorphism research, suggesting the possibility of psychological explanations for the principle of human-computer interactions. In addition, it explicates the mechanism of anthropomorphism and positive user experience, emphasizing the importance of social response-that is, intimacy.

• Information Systems Review
• /
• v.20 no.4
• /
• pp.1-23
• /
• 2018

A smart phone has been widely spread around world and makes people enjoy online shopping in any time and any place. Recently it also changes the distribution environment. O2O (Online-to-Offline) service becomes new normal due to its convenience of ease shopping of product and services. O2O service market shows steady and steep growth, It is reported that, however, 80% of the businesses has been discontinued within the first year because of unstable business models, customer dissatisfaction and distrust of service. Therefore, it is very important research issue to find out influential factors promoting continuous usage intention of O2O service. Previous study shows that it only considers online characteristics and lack of analysis about offline characteristics and social impact factors. The purpose of this paper is to find out continuous usage intention factors of O2O services by literature review, case analysis, and empirical test. A comprehensive research model and related hypothesis are developed and tested by using a structural equation, Survey was carried out among users who have used O2O service including payment service for at least once. Finally 611 samples are selected out of total 813 surveys. The result shows that the model is theoretically proved and 12 out of 17 hypotheses are accepted. The contribution of this paper is that it provides a new theoretical research model about continuous usage intention factors as well as practical guidelines about promoting continuous usage and growth strategies of O2O service.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.6
• /
• pp.1619-1637
• /
• 2016

With wide distribution of smart phones and development of mobile network, social network service (SNS) is displaying remarkable growth rates. Users build new social relations by sharing their interests, which brings surging growth to the SNS based on the combination between the strength of expanding the place for communication and distribution of smart phones featured with easy portability. This study is designed to understand impact factors of SNS on users in Korea and to conduct empirical research on casual relationship between the factors above and the factors affecting personal information behavior through the privacy protection and self-efficacy. In order to accomplish the objective above, the study presented a research model applied with key variables of the Health Belief Model (HBM) predicting behaviors capable of recognizing and preventing individual diseases in the field of health communication. To perform empirical verification on the research model of this study, a survey was conducted upon college students at N university located in Chungcheongnam-do and K university in rural area, who have experiences using the SNS. Through this survey, a total of 186 samples were collected, and path analysis was performed in order to analyze the relationship between the factors. Based on the findings from the survey, first, variables Perceived probability, Perceived severity, Perceived impairment of the HBM, key factors of personal information protection behavior on the SNS, were found to exhibit negative relationship with self-efficacy, and Perceived probability, Perceived benefit, Perceived impairment were found to exhibit negative relationship with privacy protection. But the above, Perceived severity showed positive relationship with privacy protection, and Perceived benefit and self-efficacy also displayed positive relationship. Second, although self-efficacy, a parameter, showed positive relationship with privacy protection, it demonstrated negative relationship with personal information protection behavior. Lastly, privacy protection exhibited positive relationship with personal information protection behavior. By presenting theoretical model reflected with characteristics of prevention based on these findings above unlike previous studies on personal information protection using technologies threatening personal information, this study is to provide theoretical and operational foundation capable of offering explanations how to predict personal information protection behavior on the SNS in the future.

• Journal of Life Science
• /
• v.31 no.8
• /
• pp.710-718
• /
• 2021

Placenta-derived mesenchymal stem cells (PD-MSCs) are promising candidates for cell-based therapy in regenerative medicine. The migration and homing potential of PD-MSCs to injured sites is a critical property of MSC engraftment. MicroRNAs (miRNAs) have recently been shown to regulate the critical functions of MSCs, such as proliferation, survival, and migration. The objective of the present study was to identify the miRNA and target genes involved in PD-MSCs homing in a bile duct ligation (BDL) rat model. We selected candidate miRNAs targeting genes for PD-MSCs homing based on microarray analysis. PD-MSC engraftment in BDL-injured rat liver was identified by immunofluorescence assay and human-specific Alu gene expression by quantitative real-time polymerase chain reaction (qRT-PCR) one week after transplantation. Compared with migrated naïve PD-MSCs under hypoxic and normoxic conditions (Hyp/Nor), the transplanted group with PD-MSCs (Tx) showed distinct differences in miRNA expressions in BDL-injured rat liver. We also validated the miRNAs and their target genes for PD-MSCs homing. The expressions of integrin α4 (ITGA4) and integrin α5 (ITGA5) target genes for miR-199a-5p and miR-148a-3p were significantly upregulated in the Tx group (p<0.05). In addition, integrin β1 (ITGB1) and integrin β8 (ITGB8) were upregulated by suppressing miR-183-5p and miR-145-5p, respectively. These results demonstrated that PD-MSCs regulate miRNA expression related to the integrin family for their homing effects on the BDL-injured rat liver. The findings further suggest that miRNA-mediated regulation of the integrin family contributes to the therapeutic efficacy of PD-MSCs in the rat hepatic fibrosis model by BDL.

• Knowledge Management Research
• /
• v.22 no.2
• /
• pp.119-144
• /
• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_3
• /
• pp.1009-1029
• /
• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Digital Convergence
• /
• v.16 no.3
• /
• pp.249-259
• /
• 2018

This research had intended to find out regarding the present influences of the Smart Work on the intention to use continuously with the staff members working in the small- and medium-sized enterprises as the subject. And, finally, it had intended to find out about the Smart Work environments of the IT corporations and the non-IT corporations. For this research, the questionnaire survey data were collected from the staff members working at the small- and medium-sized enterprises. Through the questionnaire survey data that were collected, an empirical analysis was carried out. And, through the reliability analysis, the feasibility analysis, the discriminatory feasibility analysis, and the inspection of the degree of suitableness of the structural equation model, finally, the research model was verified and, finally, a difference analysis of the IT corporations and the non-IT corporations was carried out. Regarding the results of the analysis of the research, it appeared that the factors of the job efficiency and the job autonomy of the special characteristics of the job had the positive influences on the usefulness and the job satisfaction, which were the parameters and which were perceived. And it appeared that the time flexibility of the job form could not have any influences on the usefulness and the job satisfaction, which were the parameters and which were perceived. And it appeared that the spatial flexibility had the influences on the job satisfaction only. The perceived usefulness, which was a parameter, had the positive influences on the job satisfaction and the intention to use continuously. And, finally, the job satisfaction had the positive influences on the intention to use continuously. And it appeared that there were the differences, too, between the IT corporations and the non-IT corporations. It is thought that, through the results of this research and through the Smart Work environment, the positive influences on the workers and the organizations could be induced and that a better working environment than previously can be provided to the workers to fit the special characteristics of the corporations.

• Journal of Internet Computing and Services
• /
• v.21 no.4
• /
• pp.17-23
• /
• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.