• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.1-10
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• 2022

The purpose of this study was to investigate how the characteristics of mobile-based financial platforms have an impact on the intention to use loan service users. In addition, it was attempted to investigate whether usefulness and ease of use had a mediating effect in the relationship between each characteristic of the mobile financial platform on the intention to use the loan service. Data collection was conducted from March 1 to April 30, 2022, and 200 people participated in the study. Analysis methods were frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, hierarchical multiple regression analysis, and three-step mediation regression analysis. The research results are as follows. First, the influence of user factors, technical factors, and environmental factors of a financial platform on the intention to use a mobile loan service was found to be ubiquity in user factors, reliability in technical factors, and facilitation conditions in environmental factors. Second, in the relationship between convenience and intention to use user factors, usefulness had a completely mediating effect. Third, in the relationship between reliability of technical factors and intention to use, usefulness showed a partial mediating effect. Fourth, in the relationship between the social impact of environmental factors and facilitation conditions and intention to use, the usefulness showed a partial mediating effect. Fifth, ease of use showed a completely mediating effect in the relationship between convenience and intention of use of user factors. Sixth, in the relationship between reliability of technical factors and intention to use, ease of use showed a partial mediating effect. Seventh, in the relationship between the social impact of environmental factors and intention to use, ease of use showed a partial mediating effect, and in the relationship between facilitation conditions and intention to use, ease of use showed a fully mediating effect. Through this study, we tried to present basic data on the determinants of the user's acceptable intention to use the mobile loan service.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Korea Science and Art Forum
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• v.27
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• pp.277-288
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• 2017

The number of science museums in Korea has expanded quantitatively from 72 in 2008 to 128 in 2016. This study started with the fact that the government puts a lot of budget into building a science museum, but there are more than one quarter of science museums with less than 50 spectators per day and many inefficient institutions. The number of visitors is an important factor in improving the efficiency of the science museum operation. The purpose of this study is to analyze the relation between the service quality of the science museum and the customer satisfaction and the intention to revisit and to find out what kind of effort should be concentrated in the science museum to attract more visitors. Questionnaires were written in the exhibition, education, and culture fields of the Gwacheon National Science Museum. The results were derived by frequency analysis, reliability analysis, factor analysis, and multiple regression analysis. The results and contents of the study are as follows. First, in the field of exhibition, the quality of exhibition facilities was expected to affect customer satisfaction and intention to return, but did not have a meaningful relationship. Second, the education sector has been found to affect customer satisfaction and return intention in all aspects of service quality (operation and contents, instructors, educational facilities and environment). Third, in the field of culture (event), the quality of the cultural program influences the visitor satisfaction, but it does not affect the intention to revisit. The science museum can provide satisfaction to visitors by combining activities such as science and arts. Despite the limitations, it is necessary to make efforts to improve the visitor satisfaction and revisit by proceeding with the convergence research on the entire National Science Museum in the future.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• 한국벤처창업학회:학술대회논문집
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• 2009.10a
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• pp.265-288
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• 2009

The study has found that the main reasons affecting to the mature conjugal relations of middle-aged persons are closely related with sede factors brought about after marriage. Comparatively the factors before marriage have more or less weak power on the conjugal relations. They are mature relations wp between husbands and wives, stable and enough incede, and religious activities, which have deep relations with the satisfactory conjugal relations. C. G. Jung divided the whole life span as self-assuredness period in the first half and self-convergence period in the second half. The first is the period when one does his or her best to get external and physical self. On the contrary, the second is the middle-aged period one finds his or her meaning of life in the religious, philosophical, intuitional, and spiritual world, which lead life into harmony and integration. Therefore if one overcomes some psychological crisis related with middle-aged development he or she can enjoy happy senescence(old age). The study has suggested through literature investigation the definition of middle age and the developmental traits of middle age, and the relations between religions and conjugal relations of middle-aged husbands and wives. Futhermore, it has analyzed the theories which religions have close relations with the life satisfaction of middle-aged conjugal relations. In order to give an analysis the influence of the variable of religious activities and religious maturity, with the degree of conjugal satisfaction, 400 middle age are selected as the object of the study whose ages are ranging from 35 years to 60 years, and who reside in Seoul or near Seoul. They were asked to fill out the questionnaires asking about religious activities, religious maturity, and the conjugal satisfaction from March 25th to April 30th, 2009. The results of the survey have been statistically processed and analyzed. First, the higher religious maturity gives positive influence on the general religious activities including public service, human relations, and spiritual stability. That is, this result indicates that the individual, spiritual, and formal religious activities give to a degree influence on the religious maturity. Second, the maturity of religious life resulting from religious activities has a causation with the satisfaction of conjugal life. In more details, religious activities has a positive influence on the satisfaction of conjugal life(T=31.36, p<.001) In more details, religious activities has a positive influence on the religious maturity(T=31.36, p<.001), and religious activities has a positive influence on the satisfaction of conjugal life(T=33.81, p<.001), and the religious maturity has a positive influence on the satisfaction of conjugal life(T=28.64, p<.001) Third, as we analyze the main effects which religious activities and the religious maturity could give influence on the satisfaction of conjugal life, it is found that both religious activities(F=15.95, p<.001) and the religious maturity(F=23.94, p<.001) give a positive influence on the satisfaction of conjugal life. In conclusion, it is sure that religious activities and the religious maturity have a close relations with the satisfaction of conjugal life. Therefore it can be said that religious activities at the protestant religion, buddhism, and catholic religion can give an important influence on the satisfaction of middle-aged conjugal life.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.