• 대한가정학회지
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• 제48권10호
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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.

• 한국컴퓨터정보학회논문지
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• 제24권8호
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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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• 제19권5호
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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.

• 한국사회복지학
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• 제49권
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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.

• 정보과학회 논문지
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• 제44권9호
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• pp.992-1004
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• 2017

이미지 품질을 정확히 평가하기 위해 이미지 평가 도구는 인간 시각 시스템을 반영해야 한다. 즉, 이미지의 구조, 색, 명암 비 등 여러 가지 요소들을 고려하여 평가해야 한다. 또한 스마트 폰과 같은 모바일 임베디드 기기의 폭넓은 사용에 따라 빠른 수행 속도를 갖는 것이 중요하다. 본 논문에서는 인간 시각 만족과 빠른 계산속도 달성을 동시에 얻기 위하여 색 유사도, 변화율 유사도, 위상 유사도를 상승적으로 결합하였고 최적화된 이미지 풀링 및 양자화 기반으로 설계하였다. 제안하는 기법은 기존에 존재하는 13개의 기법과 비교하였고 네 가지 검증 도구를 사용하여 성능을 검증하였다. 실험 결과 세 검증 도구에서 가장 우수한 성능을 보였고 한 검증 도구에서 기존 최고 기법인 VSI에 이어 두 번째로 좋은 성능을 보였으며 실행 속도는 VSI에 대해 평균 약 20% 개선된 결과를 얻었다. 또한 기존의 기법들 보다 더 인간 시각 시스템과 제안 기법의 품질 평가 값의 연관성이 크게 존재함을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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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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• 제45권5호
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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.

• 한국정보과학회논문지:정보통신
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• 제30권2호
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• pp.244-251
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• 2003

인터넷과 무선 이동통신 둥이 실생활에 보편화되면서 두 기술을 접목한 WAP(Wireless Application Protocol)[1]이 등장하였고, 다수의 사용자 요구를 동시에 효율적으로 처리하면 서 다양한 무선 단말기로부터 요청을 신속하게 처리할 수 있는 WAP 게이트웨이(WAP gateway)에 대한 연구가 여러 연구 그룹에서 수행되고 있으며, 이에 대한 효율적인 처리가 필수적이다. WAP 스택[2]은 이러한 연구 중의 가장 기본적인 기술이다. 본 논문에서는 Java의 기본적인 서비스인 멀티쓰레드를 이용하고, 컨테이너 유효 리소스의 효율적 관리를 위해 접속 풀링(connection peeling) 기능을 적용하여 WAP container를 구현하며, 우선순위 정책에 기반한 WAP Protocol의 WTP(Wireless Transaction Protocol)[3] 계층 및 UDP(User Datagram Protocol)[4] 계층을 설계하고 구현함으로 우선순위가 높은 트랜잭션들에 대해 기존 시스템보다 신속히 처리할 수 있는 기능을 구현하였고 모의 실험을 통해 그 효율성을 입증하였다.

• 지능정보연구
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• 제12권3호
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• pp.47-65
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• 2006

최근 컨테이너 터미널의 생산성 향상을 위한 자동화가 국내외에서 활발히 이루어지고 있다. 이에 따라 컨테이너 터미널의 개별 장비에 대한 효율적인 운영 방안에 대한 연구가 많이 진척되어 왔다. 하지만 터미널 전체 생산성을 높이기 위해서는 개별 장비의 효율을 높이는 것뿐만 아니라 장비들간의 동기화가 잘 되어야 할 필요가 있다. 본 논문에서는 컨테이너를 쌓아두는 장치장에서 컨테이너를 장치하는 크레인, ATCs(Automated Transfer Crane)와 장치장과 안벽간에 컨테이너를 이송하는 내부트럭, YTs(Yard Truck)의 효율적인 실행 계획을 실시간에 수립할 수 있는 휴리스틱 조합을 제시한다. 이와 함께 컨테이너의 장치 위치 결정을 위한 적합한 장치 전략과 각 작업에 배정할 YT의 적합한 선택 범위에 대해서도 시뮬레이션 실험을 통해 보여준다.

• 농업과학연구
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• 제47권4호
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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.