• Journal of Wetlands Research
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• v.23 no.4
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• pp.307-316
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• 2021

Due to rapidly increased urbanization, impervious area has been extended and concerns about urban flooding has been increased as well. A lot of effort has been made to restore the urban water circulation. Low Impact Development (LID) technology that consist of retention, infiltration, and evapotranspiration has begun to attract attention to simulate the hydrologic phenomenon before and after development. Many researches on the technique is being actively conducted. In this study, the effect on reducing runoff in urban catchment was analyzed and evaluated by applying LID techniques using SWMM and six scenarios. A SWMM-LID model was built for the Gasan 1 rainwater pumping station basin, and Green Roof and Permeable Pavement were selected as LID techniques to be applied. As a result, the reduction effect of the permeable pavement was larger than green roof. In the future, the results could be used to design a LID facility using the characteristics of the watershed, and other urban water resource factors such as river and groundwater levels that affect each other should be considered, so that the entire system can be considered.

• Journal of Conservation Science
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• v.37 no.5
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• pp.536-544
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• 2021

In the present study, safe management and value improvement of bamboo sunblind, which is an item of cultural heritage, were performed by adopting stable conservation treatment methods. The bamboo sunblind used in the present study was excavated from No. 1 catchment site in Baesanseongji, Busan. It was determined that the main material used to make the sunblind was bamboo, and herbal plants were used to weave the bamboo using lacquer as an adhesive agent. All contaminants and soil adhered to the sunblind was removed. Thereafter, the sunblind, which was recovered in the form of blocks, was washed separately after fixing it to a temporary plaster frame and to avoid the blocks from breaking during washing. Then, polyethylene glycol (PEG) impregnation was utilized for the reinforcement treatment. Based on the preliminary test results, the shape of the sunblind was fixed using a stainless-steel frame to prevent physical damage that may occur during the drying process. Thereafter, the bamboo sunblind was vacuum freeze-dried. PEG 20% (in ethyl alcohol) was applied as a surface treatment agent for stabilization the sunblind. After the surface treatment, the bamboo sunblind were joined together to fit the maximum width, and the rectangular shape of the sunblind was restored-as best as possible-while filling in the missing parts by maximizing the use of unknown members such as in the disturbed layers below bamboo sunblind surface. The conservation treatment was completed by fixing the bamboo sunblind into the fabricated frame.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.3
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• pp.233-240
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• 2021

Evaluation of the resected margins of the frozen section during breast-conserving surgery can determine the presence of cancer cells in a short time and have a significant impact on the scope of surgery and the prognosis of the patient. However, breast tissue is composed of adipose tissue, which affects the accuracy of the test. In this study, a new method was applied to the resected surface of the frozen section in which wiping the surface of the frozen section block with alcohol was expected to expose the parenchyma to the surface as the adipose tissue would melt momentarily. Indeed, of the total of 98 cases, 37 cases showed a better exposure ratio of the parenchyma in the improved frozen section test than in the previous frozen section test. Of the 37 cases with increased visibility of parenchymal sections obtained by this method, two cases of ductal carcinoma in situ (DCIS) were detected. Although there are limitations such as turnaround time (TAT), the diagnostic accuracy of histopathologic examination of the frozen section may improve through this method and may have a direct impact on patient safety, and should therefore be researched further.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.25-32
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• 2019

The purpose of this study is to investigate how to make a proper investment in ICO in the market. Previously, companies used to borrow money from banks or to obtain investments from venture capital (VC) and angel investors, but now ICOs are used as a new type of funding and financing model. The ICO sells the tokens or coins created on the blockchain openly online to raise the necessary funds, and provides the market value by paying the tokens or coins as much as the investment amount. According to this study, the limitations of the ICO market are (1) difficulties in evaluating the company, (2) uncertainties in investments, (3) lack of legal safeguards, and (4) measures to secure corporate stability after recruitment. At present, there is no way to cope with this systematically since the ICO is not protected in the legal framework. Nevertheless, we investigated the ways to make proper investment in the existing ICO market. In investing in ICO, investors should (1) consider investment methods and profitability, and (2) verify and judge investment fraud through various channels (ex. Homepage, composition team profile, etc.) and make investments based on this. This study will contribute to the formation of a healthy ICO market by understanding the newly emerged ICO market and studying the considerations when investing in it, thereby contributing to the right investor training and reducing the mass production of consumer damages caused by fraud. The limitation of this study is that the domestic ICO has not yet been examined in the legal framework, so further research is needed when policy changes occur in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.667-675
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• 2021

The purpose of this study is as follows: First, to analyze the spatial structure of Jeju by analyzing the rate of parking demand and supply; Second, to determine the parking service imbalance between regions; and third, to elucidate the causes of this spatial structural parking service imbalance and provide effective measures. Due to the rapid population and tourism growth, Jeju is suffering from traffic congestion and serious parking problems. For this, the ways to efficiently utilize the existing parking spaces were identified through spatial structure analysis based on the parking demand and supply in the Jeju area. As short-term policy, the following changes were proposed: switching to small-scale eup or myeon blocks of parking space, use of shared parking system, and repairing side streets in residential areas. As mid-to-long-term policy, it is linked to other means of transportation as follows: parking demand management policy through modal share by reorganizing public transportation routes or expanding traffic facilities; securing park-and-ride lots; and different parking pricing for different time periods. To implement these policies, each area of the public sector, private sector, and private-public partnership should develop the bond of sympathy by areas and participants.

• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.21-30
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• 2021

The existing construction industry is classified into industries with low productivity compared to other industries. In order to solve the decline in productivity in the construction industry, the world is focusing on off-site construction (OSC), which is about 40% more productive than existing construction methods. This high productivity is possible because the three stages of production, transport to the site, and site assembly are consistently maintained in a continuous flow. This study conducted a functional survey through literature review, preliminary field survey, questionnaire, and expert interview. The surveyed function were classified into five categories: convenience, flexibility, manageability, communication, and safety, and the functional characteristics of flexibility, manageability, and communication were high. Because of the change according to the construction progress, the production schedule of the factory, and the variety of transportation time required. Finally, A functional block diagram was developed based on the 15 functions corresponding with an average score of 4 or more in the surveyed function score result. If the OSC transport system is established through this study, It can contribute to a successful construction OSC project and increase productivity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.65-84
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• 2021

The purpose of this study was to develop and evaluate the Home Economics(HE) Flipped Problem-Based Learning(FPBL) education plans focusing on 'food selection and storage' unit for middle school students. The results of this study are as follows. First, middle school students who participated in the class had mainly experienced lecture-style classes previously, but they preferred group activity classes to lecture-style classes. Their 'preferred on-line class tools' was 'Miricanvas', and the 'helpful on-line class tools for learning' was 'Tinkerbell'. Second, the HE FPBL education plan was designed and developed to conduct block time classes, twice a week for 3 weeks by applying the '13 stages of FPBL'. The main topic of the class is "food selection and storage that protects health and the environment". The practical and unstructured problems in the FPBL was to participate in the 'Food Selection and Storage to Protect Health and Environment' mission development contest of a TV entertainment program. Learning materials(stepping video, reading materials, activity sheets, and evaluation tools for process-based evaluation) were developed. The 206 senior students at a middle school in Haeundae-gu, Busan, took the class for three weeks and evaluated it as a good class that helps them learn, is satisfactory, interesting, and suitable, leads to class participation, and is differentiated from other teaching methods.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.3-16
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• 2008

A Wireless Sensor Network (WSN for short) is a wireless network consisting of distributed small devices which are called sensor nodes or motes. Recently, there has been an extensive research on WSN and also on its security. For secure storage and secure transmission of the sensed information, sensor nodes should be equipped with cryptographic algorithms. Moreover, these algorithms should be efficiently implemented since sensor nodes are highly resource-constrained devices. There are already some existing algorithms applicable to sensor nodes, including public key ciphers such as TinyECC and standard block ciphers such as AES. Stream ciphers, however, are still to be analyzed, since they were only recently standardized in the eSTREAM project. In this paper, we implement over the MicaZ platform nine software-based stream ciphers out of the ten in the second and final phases of the eSTREAM project, and we evaluate their performance. Especially, we apply several optimization techniques to six ciphers including SOSEMANUK, Salsa20 and Rabbit, which have survived after the final phase of the eSTREAM project. We also present the implementation results of hardware-oriented stream ciphers and AES-CFB fur reference. According to our experiment, the encryption speeds of these software-based stream ciphers are in the range of 31-406Kbps, thus most of these ciphers are fairly acceptable fur sensor nodes. In particular, the survivors, SOSEMANUK, Salsa20 and Rabbit, show the throughputs of 406Kbps, 176Kbps and 121Kbps using 70KB, 14KB and 22KB of ROM and 2811B, 799B and 755B of RAM, respectively. From the viewpoint of encryption speed, the performances of these ciphers are much better than that of the software-based AES, which shows the speed of 106Kbps.