• Journal of the Korean Home Economics Association
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• v.48 no.10
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• pp.51-64
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• 2010

The purpose of this study was to demonstrate the patterns of income and household expense arrangements within dual-income families. The data was obtained from the F-GENS Korea Panel Survey of Ochanomizu University. The responses were gathered from both married and unmarried people, primarily in Seoul and the metropolitan area, of ages ranging from 25 to 44. The sample for this study was comprised of data from 399 double-income households. Crosstab and multinominal logistic regression models were used to analyze the data. The results were as follows. First, dual-income families choose a pooling system as their income arrangement. Second, variables determining the income arrangement were the husband's age, school attainment, annual average income, and average working hour per day. Third, variables that affected the household expenses arrangement included the husband's level of schooling attained and the husband’s job type. Fourth, the ideology of the economic community effected both the income and household expenses arrangement.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.45-50
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• 2019

Oculus Rift is the most universal VR (virtual Reality) headset for gamers and FPS (First Person Shooting) is the most suitable game genre to play with VR. Using VR can increase the player's sense of reality and make them feel as though they are in direct contact with the enemy while battling. The suggested VR game is a first person game where the player must defend a specific target against the surging enemy all within the time limit. Many objects will need to be used in this method. Object pooling will be used in order to manage all the numerous objects. When an object is repeatedly created and deleted it typically overwhelms the memory. To resolve this issue the game initially summons the object at the beginning of the scene and afterwards only uses the object when needed, lessening the burden on the memory. A ranking system is implemented to keep the game records in order to stimulate a competitive spirit between the players, and the game has received positive response during test play among college students in their 20s.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.688-701
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• 2023

The conventional methods of network intrusion detection system (NIDS) cannot measure the trend of intrusiondetection targets effectively, which lead to low detection accuracy. In this study, a NIDS method which based on a deep neural network in a big-data environment is proposed. Firstly, the entire framework of the NIDS model is constructed in two stages. Feature reduction and anomaly probability output are used at the core of the two stages. Subsequently, a convolutional neural network, which encompasses a down sampling layer and a characteristic extractor consist of a convolution layer, the correlation of inputs is realized by introducing bidirectional long short-term memory. Finally, after the convolution layer, a pooling layer is added to sample the required features according to different sampling rules, which promotes the overall performance of the NIDS model. The proposed NIDS method and three other methods are compared, and it is broken down under the conditions of the two databases through simulation experiments. The results demonstrate that the proposed model is superior to the other three methods of NIDS in two databases, in terms of precision, accuracy, F1- score, and recall, which are 91.64%, 93.35%, 92.25%, and 91.87%, respectively. The proposed algorithm is significant for improving the accuracy of NIDS.

• Korean Journal of Social Welfare
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• v.49
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• pp.343-378
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• 2002

This study examines the organizational performance of human service organizations from the quality output perspective. Using the 2001 evaluation data about 89 community welfare centers in Seoul, this study attempts to identify the levels of the performance of human service organizations in Korea. This study also attempts to identify the factors that predict performance of human service organizations measured in terms of client satisfaction and experts' evaluation about the functioning of each center. Results are as follows: (1) when pooling 866 clients' satisfaction level into satisfaction score about each center, the average of client satisfaction about the centers is 3.42 at 4 points scale. (2) 41.6% of the community welfare centers is evaluated as "highly qualified" in its overall operation and functioning by the professional evaluation team, (3) the employee reward system(+), practice based on the program guideline manual(+), the portion of the government support grant in its budget(-), the overall employee salary level(-), the level of acquirement of program grants from external sources (-) are the predictors in explaining clients' satisfaction level, and (4) the level of professional expertise of the executive director(+), the level of professional supervision of middle managers(+), the employee reward system(+), the program need assessment(+), the level of client information system(+), the portion of government support grant(-), the overall employee salary level(-) are the predictors for "being highly qualified" in its overall operation and function of each center. Through the empirical analysis, this study provides valuable knowledge about organizational performance of community welfare centers from the quality output perspective. Finally, this study discusses implications for more effective and efficient organizational performance of community welfare centers in Korea.

• Journal of KIISE
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• v.44 no.9
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• pp.992-1004
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• 2017

To assess image quality accurately, an image quality assessment (IQA) metric is required to reflect the human visual system (HVS) properly. In other words, the structure, color, and contrast ratio of the image should be evaluated in consideration of various factors. In addition, as mobile embedded devices such as smartphone become popular, a fast computing speed is important. In this paper, the proposed IQA metric combines color similarity, gradient similarity, and phase similarity synergistically to satisfy the HVS and is designed by using optimized pooling and quantization for fast computation. The proposed IQA metric is compared against existing 13 methods using 4 kinds of evaluation methods. The experimental results show that the proposed IQA metric ranks the first on 3 evaluation methods and the first on the remaining method, next to VSI which is the most remarkable IQA metric. Its computing speed is on average about 20% faster than VSI's. In addition, we find that the proposed IQA metric has a bigger amount of correlation with the HVS than existing IQA metrics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Archives of Plastic Surgery
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• v.45 no.5
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• pp.449-457
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• 2018

Background Although previous studies have focused on determining prognostic and causative variables associated with fistula-related complications after head and neck reconstructive surgery, only a few studies have addressed preventive measures. Noting that pooled saliva complicates wound healing and precipitates fistula-related complications, we devised a continuous suction system to remove saliva during early postoperative recovery. Methods A continuous suction system was implemented in 20 patients after head and neck reconstructive surgery between January 2012 and October 2017. This group was compared to a control group of 16 patients at the same institution. The system was placed orally when the lesion was on the anterior side of the retromolar trigone area, and when glossectomy or resection of the mouth floor was performed. When the orohypopharynx and/or larynx were eradicated, the irrigation system was placed in the pharyngeal area. Results The mean follow-up period was $9.2{\pm}2.4$ months. The Hemovac system was applied for an average of 7.5 days. On average, 6.5 days were needed for the net drain output to fall below 10 mL. Complications were analyzed according to their causes and rates. A fistula occurred in two cases in the suction group. Compared to the control group, a significant difference was noted in the surgical site infection rate (P<0.031). Conclusions Clinical observations showed reduced saliva pooling and a reduction in the infection rate. This resulted in improved wound healing through the application of a continuous suction system.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.244-251
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• 2003

As the Internet and wireless mobile communication is being widespread, the WAP (Wireless Application Protocol) that merges these two technologies has emerged. Also, the research of the WAP gateway that enables efficient processing of multiple user demands concurrently and prompt response to requests from various wireless devices has been performed in many working groups. The WAP stack is the most fundamental technology among these researches. In this paper, we implement the WAP container utilizing the JAVA's multithreading and applying to the connection pooling technique to manage the available resource in the container efficiently. Also, we design and implement the WTP(Wireless Transaction Protocol) layer and the UDP(User Datagram Protocol) layer based on the priority Policy. Our design and implementation showed the shorter waiting time than that of the existing FCFS(First-Come, First-Served) system in the transaction layer and its efficiency was proved through simulation.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.47-65
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• 2006

These days, the number of automated container terminals is increasing to encourage the productivity of the container terminal inside and outside of the country. So far, there have been a lot of researches on the operating one type of equipments in a container terminal. However, there is still room for further improvement as none of equipment works itself but cooperate each other to finish a job, which means synchronization among the equipments is necessary. Among lots of equipments in a terminal, this paper concerns with the operation of ATCs (Automated Transfer Crane) and YTs (Yard Truck). The purpose of this paper is to find the efficient heuristic methods for operating ATCs and YTs that can set up a schedule in a real time. Moreover, using simulation this paper shows the efficient stacking strategy to decide the location of containers to be put and the proper selection range of YTs.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1109-1122
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• 2020

The aim of this study was to develop a marbling classification and prediction model using small parts of sirloin images based on a deep learning algorithm, namely, a convolutional neural network (CNN). Samples were purchased from a commercial slaughterhouse in Korea, images for each grade were acquired, and the total images (n = 500) were assigned according to their grade number: 1++, 1+, 1, and both 2 & 3. The image acquisition system consists of a DSLR camera with a polarization filter to remove diffusive reflectance and two light sources (55 W). To correct the distorted original images, a radial correction algorithm was implemented. Color images of sirloins of Hanwoo (mixed with feeder cattle, steer, and calf) were divided and sub-images with image sizes of 161 × 161 were made to train the marbling prediction model. In this study, the convolutional neural network (CNN) has four convolution layers and yields prediction results in accordance with marbling grades (1++, 1+, 1, and 2&3). Every single layer uses a rectified linear unit (ReLU) function as an activation function and max-pooling is used for extracting the edge between fat and muscle and reducing the variance of the data. Prediction accuracy was measured using an accuracy and kappa coefficient from a confusion matrix. We summed the prediction of sub-images and determined the total average prediction accuracy. Training accuracy was 100% and the test accuracy was 86%, indicating comparably good performance using the CNN. This study provides classification potential for predicting the marbling grade using color images and a convolutional neural network algorithm.