• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• The Journal of Fisheries Business Administration
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• v.39 no.2
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• pp.81-108
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• 2008

Since the declaration made by UN Convention on the Law of the Sea on EEZs, The open seas of Northeast Asia, considerd as a convention area, needed new agreements in conformity with the changes brought by the introduction of the Exclusive Economic Zone(EEZ) system. The Contracting Parties of these agreements set up their own EEZs, which extend certain ranges from their baselines, Fishing in the other party's EEZ is done based on mutual agreements, which take into account traditional fishing activity in the zones. Seperate fishries management systems, in accordance with the relevant legal status of the waters, are applied to individual overlapping areas: Middle Zone in the Bast Sea and the waters south of jeju Island, Interim Measure Zone in the Yellow Sea and East China Sea, and the Transitional Zone in the Yellow Sea. They decided to conclude fisheries agreements as the provisional agreement under Article 74(3) of the UN Convention before the delimitations of the EEZs to avoid the territorial disputes. China and Japan concluded the Fishries Agreement in the November 1997, allowing each coastal State 52 mile EEZ. it was followed by Korea and Japan in September 1998, reaching a final compromise. And also Korea and China came to a satisfactary settlement in November 1998. Fisheries agreements have been established between the three North-east Asian States, the agreement are all bilateral. That implies inefficient resource management on the overlapping waters of the three states, especially on the East China Sea. The Korea-Japan Fisheries Agreement and the China-Japan Fishery Agreement worked as governing rules in the North-east Asian seas before the establishment of EEZs (Exclusive Economic Zones). However the conclusion of the bilateral fishery agreements, Korea China and Japan have developed EEZs, and these three countries have competed for the exploitation of fisheries resources. Therefore, the issue of fisheries resource management was no longer a single countries' problem and emerged as a common issue facing these three countries. In recognition of the above-mentioned problem, it is needed for the construction of cooperative System fishery management in the North-east Asian seas. Therefore, cooperative measures should be establishied. The final goal of the construction of fisheries management cooperative system is to establish sustainable fisheries in the North-east Asian seas. However, there is a big difference in fisheries management tools, fishing gear, exploitation rate of species, etc. This implies that a careful approach should be taken in order to achieve the cooperative fisheries management among Korea, China and Japan. conclusionly, the Governments of Korea, China and Japan should complement three bilateral agreemens, and which they prepares to 'Fisheries Resource Restore Program' Between Korea, China and Japan in the adjacent waters south of Jeju Island.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.

• Korean Journal of Heritage: History & Science
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• v.57 no.3
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• pp.162-182
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• 2024

Since the adoption of the World Heritage Convention, sites associated with dark histories have been inscribed as World Heritage sites over the past fifty years. However, in 2018, the review of nomination dossiers for these sites was temporarily suspended to prevent additional discomfort or the conflicts these inscriptions might cause. Despite concerns raised by experts about nominations of these sites, the increasing demands from State Parties led to the adoption of the Guiding Principles for the Preparation of Nominations Concerning Sites of Memory Associated with Recent Conflicts. These Guiding Principles have made it possible to inscribe such sites as World Heritage sites. The Guiding Principles play a crucial role in outlining the nature and criteria for inscription, the components required in the nomination dossier, and mechanisms for notifying a contestation in cases of differing interpretations of the site. Their primary aim is to minimize further conflicts that may arise from the inscription of sites of memory. They affirm that such sites can contribute to achieving the objectives of the World Heritage Convention and represent a significant step in addressing heritage interpretation in the World Heritage system. The amendment of the Operational Guidelines to incorporate a contestation mechanism has arguably established a more transparent and open inscription process. However, the Guiding Principles also have limitations. Among the ten criteria set by the World Heritage Convention, sites related to conflicts or dark histories can use Criterion (vi). This criterion focuses on the site's outstanding universal value linked to historical events or associations, regardless of physical evidence. If a State Party chooses not to use Criterion (vi), the application of the Guiding Principles cannot be expected. Furthermore, while the Guiding Principles require a heritage interpretation strategy in the nomination dossier, the lack of detailed guidance may confuse nominating countries. Sites of memory associated with recent conflicts are not just places that need protection and remembrance due to their association with dark histories. They have also evolved to become spaces for reconciliation and healing. The inscription of these sites as World Heritage sites is not just a recognition of their historical significance, but also a platform for discussing the impact of past conflicts on modern society. It opens up a dialogue on how current generations can address these issues. With the adoption of the Guiding Principles, we hope that inscribed sites will not only promote reconciliation and healing but also serve as a starting point for addressing present and future challenges.

• The Korean Literature and Arts
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• v.27
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• pp.273-321
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• 2018

The purpose of this study is to explore the characteristics and meaning of the Korean American women's poetry in New York area. New York area poetry has been led by women poets from the very beginning of the paragraph. In this paper, set the starting point of "New York Literature" in 1991, and classified the poets who had started their activities in the past as a first generation, and poets who have been active since then, as second generation. The characteristics and meaning of women's poetry were examined by focusing on Kwak Sang-hee, Kim Jung-ki, Kim Song-hee, and Choi Jeong-ja in the first generation, Jo Seong-Ja, and Shin Ji-hye, An Young-ae, Bok Young-mi in the second generation. On the one hand, they share a common sentiment of immigrant women, while on the other they show a slightly different world recognition and identity for each poet. The characteristics of women's poetry in New York area are as follows: ① they express the nostalgia for their experience and home in a strange space, ② that they reveal their identity as a mother and a poet, ③ they show the experience of labor and other consciousness, and ④ shows the changing identity through Nomadistic thought and de-territorialization. Although the content of the prototypes of female poets differ slightly depending on the motive and timing of immigration, in the early days of immigration, mainly the nostalgia for their hometowns and the consciousness of the Gentiles have become a poetic theme, and the alienation ceremony, And as time passes it shows consciousness as a settler who regards America as their second hometown. In the 1990s, most of the first-generation women poets have been harsh with the process of adaptation and settlement, revealing the nostalgia for their hometowns. Jo Seong-Ja and Shin Ji-hye, who are doing their work in the 1990s as a settlement stage, are adapting easily to American society compared to their predecessors. They also show that they are able to overcome ethnicity and race, It shows the open vision and identity to overcome. If the first generation of immigrant women has been leading the flow of New York poetry since the liberation, it is meaningful that second generation of women's poetry can be used as a measure of future change and development of New York poetry.