• Women's Health Nursing
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• v.25 no.1
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• pp.99-111
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• 2019

Purpose: To develop nurses' educational needs scale for woman with infertility. Methods: A total of 201 nurses in charge of infertility health services in 4 infertility hospitals and 1 public health center were enrolled for this study. The scale was developed through literature review, in-depth interview, development of preliminary items, verification of content validity, development of secondary items, verification of construct validity, and extraction of final items. Data were analyzed using item analysis, exploratory factor analysis, Pearson's correlation coefficients, and Cronbach's ${\alpha}$. Results: Nurses' educational needs scale for women with infertility consisted of 41 items. Three factors (education for disease and symptom of infertility, supporting and counselling for infertility patients, and education for daily life of infertile patients) explained 63.7% of the total variance. Conclusions: Nurses' educational needs scale for woman with infertility demonstrated acceptable validity and reliability. Its items could be used to assess the level of educational needs for nurses in charge of infertility health services.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.416-422
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• 2021

Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1552-1559
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• 2021

Convolution neural networks (CNNs) show notable performance in image processing and are used as representative core models. CNNs extract and learn features from large amounts of train dataset. In general, it has a structure in which a convolution layer and a fully connected layer are stacked. The core of CNN is the convolution layer. The size of the kernel used for feature extraction and the number that affect the depth of the feature map determine the amount of weight parameters of the CNN that can be learned. These parameters are the main causes of increasing the computational complexity and memory usage of the entire neural network. The most computationally expensive components in CNNs are fully connected and spatial convolution computations. In this paper, we propose a Fourier Convolution Neural Network that performs the operation of the convolution layer in the Fourier domain. We work on modifying and improving the amount of computation by applying the fast fourier transform method. Using the MNIST dataset, the performance was similar to that of the general CNN in terms of accuracy. In terms of operation speed, 7.2% faster operation speed was achieved. An average of 19% faster speed was achieved in experiments using 1024x1024 images and various sizes of kernels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1066-1079
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• 2023

Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.421-422
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• 2020

발 고유 변인 측정 및 데이터의 수집은 소비자의 발 건강을 위한 신발 제작을 위하여 필요하다. 신발의 설계 지표 또한 개정의 필요성이 제시되고 있어 발 고유 변인 측정의 및 데이터 획득에 관한 연구의 필요성이 증대되고 있다. 본 논문에서는 발 형태의 데이터 값을 산출하여 사용자에게 적합한 맞춤형 인솔 및 신발을 제작하고, 신발의 설계 지표를 산출하기 위하여 발 고유 변인의 데이터 값을 자동으로 측정이 가능한 발 고유 변인 산출이 가능한 발 형상 추출 시스템에 대해 서술한다. 이를 위해 사용자의 발 고유 변인 측정을위한 스캐닝 스테이지를 설계 및 제작하고, 3대의 깊이 카메라를 설치하였다. 잡음 및 배경을 제거하기 위해 가우시안 배경 모델링으로 전경 영역을 분리하여 발 점군 데이터를 획득 한 후, Euclidean transformation을 통해 각 점군 데이터를 정합한다. 실험 결과에서는 획득된 발 형상 점군 데이터와 접지면 형상 및 발 변인 추출 결과를 보여준다.

• Journal of The Geomorphological Association of Korea
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• v.26 no.2
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• pp.1-14
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• 2019

This study analyzed the relativity between block stream and talus distributions by employing a likelihood ratio approach. Possible distribution sites for each debris slope landform were extracted by applying a spatial integration model, in which we combined fuzzy set model, Bayesian predictive model, and logistic regression model. Moreover, to verify model performance, a success rate curve was prepared by cross-validation. The results showed that elevation, slope, curvature, topographic wetness index, geology, soil drainage, and soil depth were closely related to the debris slope landform sites. In addition, all spatial integration models displayed an accuracy of over 90%. The accuracy of the distribution potential area map of the block stream was highest in the logistic regression model (93.79%). Eventually, the accuracy of the distribution potential area map of the talus was also highest in the logistic regression model (97.02%). We expect that the present results will provide essential data and propose methodologies to improve the performance of efficient and systematic micro-landform studies. Moreover, our research will potentially help to enhance field research and topographic resource management.

• ALGAE
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• v.38 no.4
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• pp.217-240
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• 2023

Sulfated polysaccharides (SPs) isolated from seaweed have emerged as remarkable bioactive compounds with a wide spectrum of biological activities and have substantial value in the scientific and industrial domains. The current study explores the diverse biological activities of SPs and their relationship with their structures. This aids in an in-depth examination of the multifaceted biological activities of SPs, including anticoagulant, anti-inflammatory, antiviral, antioxidant, and immunomodulatory properties, which underpin their potential health benefits. Furthermore, the current study explores the complicated properties of SPs, with their extraction methodologies and techniques for precise characterization. Elucidation of the commercial significance of SPs derived from brown, red, and green seaweed by highlighting their potential applications has emphasized their importance in human well-being. Further, this review emphasizes the challenges needed to overcome research and industrial innovations for SPs. Collaboration among researchers, industry stakeholders, and regulatory authorities can overcome these challenges and elevate the potential of SPs to revolutionize industries such as pharmaceuticals, cosmeceuticals, food, and biotechnology.

• Journal of Oral Medicine and Pain
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• v.20 no.2
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• pp.429-447
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• 1995

This study was designed to determine the most effective concentration of fluoride and levels of laser irradiation for the remineralization of decayed teeth. After irradiation with a pulsed Nd:YAG laser and the topical application of fluoride, phosphate and fluoride concentration in enamel were measured. And then the changes on surface enamel using an scanning electron microscope were observed. Samples by extraction healthy, permanent, mandibular bovine teeth with no caries were obtained. Among them 371 healthy samples were selected and artificial carious lesions were made. 20 samples were assigned to each experimental group. After irradiation with a pulsed Nd:YAG laser with total energy densities of 10J/$\textrm{cm}^2$, 20J/$\textrm{cm}^2$ for each group. On the teeth, 2% NaF, 1.9% NH4F, 1.6% TiF4 Elmex gel(amine fluoride) and 1.23% APF gel were applied. After pH circulatory procedures, concentrations of fluoride with and Ionalyzer (Orion Research, Model 901, USA) and phosphates with an Uv/V is spectrophotometer (Uvikon 860, Kontrom Co, Switzerland) were measured. By etching the teeth in layers and measuring fluoride concentrations, a profile of fluoride penetration according to depth could be developed. And also the changes on the surface of the enamel using an electron scanning microscope were observed. The comparative analysis yielded the following results : 1. Phosphate concentration was low in all groups compared with the control group except for teeth treated Elmex gel, irradiated with 10J/$\textrm{cm}^2$ and 30J/$\textrm{cm}^2$ energy densities. Teeth treated with APF gel and 30J/$\textrm{cm}^2$ irradiation gad the lowest phosphate concentration. 2. Among all groups, fluoride concentrations in tooth enamel were highest in APF gel and NaF groups irradiated at 30J/$\textrm{cm}^2$. The APF gel group had the highest fluoride concentrations across all energy densities. 3. In the APF gel group, and the NaF group, the greater the energy density of the laser, the higher the fluoride concentrations in the enamel. 4. In all groups, the concentration of fluoride in the enamel by depth tended to decrease with depth. 5. Under the scanning electron microscope, under the condition of irradiation with 20J/$\textrm{cm}^2$, enamel crack was detected for the first time. In the NH4F group, spherical deposits were found on the surface of the enamel, and in the TiF4 group the surface of enamel was covered with an irregular, thin membranous mass in places. In the APF gel and NaF groups irradiated with 10J/$\textrm{cm}^2$, spherical and irregular particles covered the teeth. When these groups were irradiated at 20J/cm2, they were covered with amorphous crystals. These results suggest that one could obtain more effective anticariogenic effects without damage to teeth when less than 20J/$\textrm{cm}^2$ energy densities and APF gel are used.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.502-508
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• 2015

Stereo images have an advantage of calculating depth(distance) values which can not analyze from 2-D images. However, depth information obtained by stereo images has due to following reasons: it can be obtained by computation process; mismatching occurs when stereo matching is processing in occlusion which has an effect on accuracy of calculating depth information. Also, if global method is used for stereo matching, it needs a lot of computation. Therefore, this paper proposes the method obtaining disparity map which can reduce computation time and has higher accuracy than established method. Edge extraction which is image segmentation based on feature is used for improving accuracy and reducing computation time. Color K-Means method which is image segmentation based on color estimates correlation of objects in an image. And it extracts region of interest for applying Loopy Belief Propagation(LBP). For this, disparity map can be compensated by considering correlation of objects in the image. And it can reduce computation time because of calculating region of interest not all pixels. As a result, disparity map has more accurate and the proposed method reduces computation time.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1245-1254
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• 2023

Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.