• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.99-111
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• 2021

The connected farm that agricultural land, agricultural machinery and farmer are connected with an IoT gateway is in the commercialization stage. That has increased productivity, efficiency and profitability by intimate information exchange among those. In order to develop the educational program of intelligent agricultural machinery and the agricultural machinery safety education performance indicator, this study analyzed patent trends of agricultural machine with unmanned technology used in agriculture and efficiency technology applied advanced technologies such as ICT, robots and artificial intelligence. We investigated and analyzed patent trends in agricultural machinery of Korea, the USA and Japan as well as the countries in Europe. The United States is an advanced country in the field of unmanned technology and efficiency technology used in agriculture. Agricultural automation technology in Korea is insufficient compared to developed countries, which means rapid technological development is needed. In the sub-fields of field automation technology, path generation and following technology and working machine control technology through environmental awareness have activated.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.273-282
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• 2022

Testing approaches for configurable software product lines differs significantly from a single software testing, as it requires consideration of common parts used by all member products of a product line and variable parts shared by some or a single product. Test coverage is a measure of the adequacy of testing performed. Test coverage measurements are important to evaluate the adequacy of testing at the software product line level, as there can be hundreds of member products produced from configurable software product lines. This paper proposes a method for measuring code coverage at the product line level in configurable software product lines. The proposed method tests the member products of a product line after hierarchizing member products based on the inclusion relationship of the selected features, and quantifies SPL(Software Product Line) test coverage by synthesizing the test coverage of each product. As a result of applying the proposed method to 11 configurable software product line cases, we confirmed that the proposed method could quantitatively visualize how thoroughly the SPL testing was performed to help verify the adequacy of the SPL testing. In addition, we could check whether the newly performed testing for a member product covers the newly added code parts of a feature.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.21-33
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• 2022

This paper is to suggest the secure secret sharing system in order to outstandingly reduce the damage caused by the leakage of the corporate secret. This research system is suggested as efficient P2P distributed system kept from the centrally controlled server scheme. Even the bitcoin circulation system is also based on P2P distribution scheme recenly. This research has designed the secure circulation of the secret shares produced by Threshold Shamir Secret Sharing scheme instead of the shares specified in the torrent file using the simple, highly scalable and fast transferring torrent P2P distribution structure and its protocol. In addition, this research has studied to apply both Shamir Threshold Secret Sharing scheme and the securely strong multiple user authentication based on Collaborative Threshold Autentication scheme. The secure transmission of secret data is protected as using the efficient symmetric encryption with the session secret key which is safely exchanged by the public key encryption. Also it is safer against the leakage because the secret key is effectively alive only for short lifetime like a session. Especially the characteristics of this proposed system is effectively to apply the threshold secret sharing scheme into efficient torrent P2P distributed system without modifying its architecture of the torrent system. In addition, this system guaranttes the confidentiality in distributing the secret file using the efficient symmetric encryption scheme, which the session key is securely exchanged using the public key encryption scheme. In this system, the devices to be taken out can be dynamically registered as an user. This scalability allows to apply the confidentiality and the authentication even to dynamically registerred users.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.227-237
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• 2022

The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1889-1900
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• 2022

Roads are an essential factor in the physical functioning of modern society. The spatial information of the road has much longer update cycle than the traffic situation information, and it is necessary to generate the information faster and more accurately than now. In this study, as a way to achieve that goal, the Pan-sharpening technique was applied to satellite images of Kompsat 3 and 3A to improve spatial resolution. Then, the data were used for road extraction using the semantic segmentation technique, which has been actively researched recently. The acquired Kompsat 3/3A pan-sharpened images were trained by putting it into a U-Net based segmentation model along with Massachusetts road data, and the applicability of the images were evaluated. As a result of training and verification, it was found that the model prediction performance was maintained as long as certain conditions were maintained for the input image. Therefore, it is expected that the possibility of utilizing satellite images such as Kompsat satellite will be even higher if rich training data are constructed by applying a method that minimizes the impact of surrounding environmental conditions affecting models such as shadows and surface conditions.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.1-10
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• 2022

Defense fields widely operate unmanned systems to lower vulnerability and enhance combat effectiveness. In the navy, swarm unmanned surface vehicles(USVs) form a cluster within communication range, share situational awareness information among the USVs, and cooperate with them to conduct military missions. This paper proposes an interface system, i.e., Interface Adapter System(IAS), to achieve inter-USV and intra-USV interoperability. We focus on the mission planning subsystem(MPS) for interoperability, which is the core subsystem of the USV to decide courses of action such as automatic path generation and weapon assignments. The central role of the proposed system is to exchange interface data between MPSs and other subsystems in real-time. To this end, we analyzed the operational requirements of the MPS and identified interface messages. Then we developed the IAS using the distributed real-time middleware. As experiments, we conducted several integration tests at swarm USVs simulation environment and measured delay time and loss ratio of interface messages. We expect that the proposed IAS successfully provides bridge roles between the mission planning system and other subsystems.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.

• Journal of Naturopathy
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• v.10 no.2
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• pp.77-85
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• 2021

Background: It is necessary to verify the resilience of the newly improved Kneipp psychotherapy. Purpose: This study assesses whether Kneipp Lebensordnung psychotherapy; KnLP program improves resilience. Methods: The KnLP program, including salutogenesis, logotherapy, meditation, and resilience training, is reorganized in consideration of Korean culture and sentiments. It was conducted 4 times for 25 adults (once a week, 3 hours a time), and data, KRQ-53 (Korean Resilience Quotient-53) measured intervention, before, and after was compared and analyzed. Results: The data for 9 adults were selected to draw reliable analysis, and it concluded that participants' KRQ-53 mean score increased by 14.66 from 191.56 to 206.22 during and after the program. The score increase by factor in resilience training is 5.89 points for self-regulation skills, 4.89 points for in interpersonal skills, and 3.89 points for positive capacity. Conclusions: KnL program improves participants' resilience skill (p<.05), and especially in self-regulation skill. Subsequent studies with more participants are required to achieve statistically significant and generalized results in the future.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.794-807
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• 2022

Although registration of dogs is mandatory according to the revision of the Animal Protection Act, the registration rate is low due to the inconvenience of the current registration method. In this paper, a performance improvement study was conducted on the dog face recognition technology, which is being reviewed as a new registration method. Through deep learning learning, an embedding vector for facial recognition of a dog was created and a method for identifying each dog individual was experimented. We built a dog image dataset for deep learning learning and experimented with InceptionNet and ResNet-50 as backbone networks. It was learned by the triplet loss method, and the experiments were divided into face verification and face recognition. In the ResNet-50-based model, it was possible to obtain the best facial verification performance of 93.46%, and in the face recognition test, the highest performance of 91.44% was obtained in rank-5, respectively. The experimental methods and results presented in this paper can be used in various fields, such as checking whether a dog is registered or not, and checking an object at a dog access facility.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.3
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• pp.293-299
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• 2022

Recently, various stakeholder are interested in microplastic to cause pollution of the marine's ecosystem and effort to conduct study of product's life cycle to reduce pollution of marine's ecosystem. The micorplastic refer to materials of the nano- to micro- sized units and it can be classified into primary and secondary. The primary microplastic mean the manufactured for use in the specific field such as the microbead of the cosmetic or cleanser. also, secondary mean the unintentionally generated during use of the product such as the textile crumb by the doing the laundry. Tire and Road Wear Particles(TRWPs) are also defined as secondary microplastic. Typically, TRWPs are created by friction between the tread compound's rubber of the tire and the surface of the road du ring the driving cars. Most of the generated TRWPs exist on the roadside and some of them were carried to marine by the rainwater. In this study, we perform the quantitative analysis of the TRWPs existed in fine dust at the roadside. So, we collected the dust from the roadside in Chungcheongnam-do's C site with a movement of 1,300 cars per the hour. The collected samples were separated according to size and density. And shape analysis was performed using the Scanning Electron Microscope(SEM). We were possible to discover a lot of TRWPs at the fine dust of the 100 ± 20 ㎛. And we analysis it u sing the Thermo Gravimetric Analysis(TGA) and Gas Chromatography/Mass Spectrometer(GC/MS) for the quantitative components from the tire. As a result, it was confirmed that TRWPs generated from the roadside fine dust were included the 0.21 %, and the tire and road components in the generated TRWPs consisted of the 3:7 ratio.