• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.1
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• pp.107-115
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• 2019

This research explores a historical trajectory of the Milwaukee Art Museum from its establishment to the third expansion over the last six decades. After established in 1957 by the architect, Eero Saarinen, this museum underwent three expansions led by three different architects including, David Kahler, Santiago Calatrava, and James Shields. Reasons for expanding the museum were varied. A lack of exhibition space, an absence of visual identity, and path interruption problem within urban contexts were the main factors of a series of expansion. Furthermore, this research points out that there are three issues in the process of the expansion. The first is connection issues between the downtown and the lakefront in which the museum has blocked the public flow. The second, there were controversies on the allocation of the expanded space among the main body of the decision including architects, curators, and stakeholders. The last one is relationships among architects. This is related to each architect's attitude toward the museum. Drawing on historical documents and interviews with the regional architects, I argue that the identity and values of the museum have changed over time through the expansions rather than having the invariable.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.4
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• pp.25-36
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• 2019

Contemporary architecture is showing its deconstruction and departure from modern architecture based on rationality, such as reductionism or virtualism. This means a shift from a mechanistic and ecological world view to an organic and ecological view, from a deterministic reason to a reason for a possible secret static. This study examines the potential of fractals, a scientific theory of complexity that is emerging as a new paradigm in the 21st century, as an appropriate alternative to contemporary complexity architecture. The method and scope of this study were understood and its features were identified through literature and data research and prior study review. Based on the organic nature of fractal geometry, we analyzed the works of contemporary architects(Frank Gehry, Bernard Tschumi, Steven Holl, Zaha Hadid, Rem Koolhaas, Daniel Libeskind, Zvi Hecker, Ito Toyo) and studied the possibility of architectural design using the principle of fractal. As a result, fractal geometry, similar to the patterned order of nature, has an infinite set of organizational functionalities in architecture and can be applied in various aspects of design analysis. Architectural designs based on the fractal theory will require more research and development to realize dynamic design representation using digital computers.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.53-61
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• 2019

Cloud BIM, which incorporates cloud computing technology and BIM technology, is increasingly used in construction. In particular, the recent trend of cloud services in IT field is to provide customized cloud services according to the characteristics of users. These changes are also linked to the cloud BIM, which is emerging in the construction industry. However, cloud BIM researches and commercial technologies that are currently underway do not reflect these trends, and they provide services through generalized management functions in construction projects. In order to solve these problems, a new type of customized cloud BIM service is needed that can provide cloud services by reflecting the characteristics of the project, customization based on the user's work, and providing the knowledge service. Therefore, this study aims to derive the system requirement function that should be preceded for implementing the customized cloud BIM service, and the target project is selected as the medical facility.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.3
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• pp.39-47
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• 2020

This study is preliminary and qualitative research to find out the possibility of using children's architectural work as projective test tools. The features of 21 works from the activity of built-environment education for children was analyzed and compared with MBTI psychological preference types. The key results are as follows: 1) Observation and communication was required to understand and analyze children's architectural works. 2) The results of children's work appeared in various ways, and were classified as indicators according to composition, shape, expression, program, circulation. These indicators also showed the independence of personal expression types regardless of age or gender. 3) The comparison between architectural expressions and MBTI preference types revealed a significant relationship between the indicators. The relationship only appeared in certain indicator pairs. Therefore, it can be said that the built-environment education could be used as a projection test tool to understand the psychological preferences of children. In conclusion, the meanings and limitations of this study and the possibility of future researches were discussed.

• Journal of Genetic Medicine
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• v.17 no.2
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• pp.102-107
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• 2020

We report the case of an infant with a 4q35.1 deletion with 10p duplication. This mutation is rarely reported in the literature and has been found to have variable clinical findings, often including developmental delay. In this case, the condition was detected by chromosomal microarray analysis after initial manifestation of a feeding problem and developmental delay. Minor dysmorphic features with abnormal neurological examination led to further evaluation. The father's chromosome complement was 46, XY, t(4;10)(q35;p12.2). Parental balanced translocation can go unrecognized, because affected individuals are often phenotypically healthy until they have fertility issues such as recurrent miscarriages or children with severe congenital disorders. Genetic diagnoses help to establish a clear family genetic background that permits the development of clear treatment strategies. Prenatal counseling can also help to understand the possible risks associated with pregnancy or future child planning.

• Progress in Medical Physics
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• v.31 no.4
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• pp.153-162
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• 2020

Purpose: We aim to evaluate the accuracy and effectiveness of an automatically converted radiation therapy plan between Radixact machines by comparing the original plan with the transferred plan. Methods: The study involved a total of 20 patients for each randomly selected treatment site who received radiation treatment with Radixact. We set up the cheese phantom (Gammex RMI, Middleton, WI, USA) with an Exradin A1SL ion chamber (Standard Imaging, Madison, WI, USA) and GAFCHROMIC EBT3 film (International Specialty Products, Wayne, NJ, USA) inserted. We used three methods to evaluate an automatically converted radiation therapy plan using the features of the Plan transfer. First, we evaluated and compared Planning target volume (PTV) coverage (homogeneity index, HI; conformity index, CI) and organs at risk (OAR) dose statistics. Second, we compared the absolute dose using an ion chamber. Lastly, we analyzed gamma passing rates using film. Results: Our results showed that the difference in PTV coverage was 1.72% in HI and 0.17% in CI, and majority of the difference in OAR was within 1% across all sites. The difference (%) in absolute dose values was averaging 0.74%. In addition, the gamma passing rate was 99.64% for 3%/3 mm and 97.08% for 2%/2 mm. Conclusions: The Plan transfer function can be reliably used in appropriate situations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.441-450
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• 2022

The introduction of autonomous underwater gliders (AUGs) specifically addresses the reduction of operational costs that were previously prohibited with conventional autonomous underwater vehicles (AUVs) using a "scaling-down" design philosophy by utilizing the characteristics of autonomous drifters to far extend operation duration and coverage. Long-duration, wide-area missions raise the cost and complexity of in-water testing for novel approaches to autonomous mission planning. As a result, a simulator that supports the rapid design, development, and testing of autonomy solutions across a wide range using software-in-the-loop simulation at faster-than-real-time speeds becomes critical. This paper describes a faster-than-real-time AUG simulator that can support high-resolution bathymetry for a wide variety of ocean environments, including ocean currents, various sensors, and vehicle dynamics. On top of the de facto standard ROS-Gazebo framework and open-sourced underwater vehicle simulation packages, features specific to AUGs for ocean mapping are developed. For vehicle dynamics, the next-generation hybrid autonomous underwater gliders (Hybrid-AUGs) operate with both the buoyancy engine and the thrusters to improve navigation for bathymetry mappings, e.g., line trajectory, are is implemented since because it can also describe conventional AUGs without the thrusters. The simulation results are validated with experiments while operating at 120 times faster than the real-time.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.107-121
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• 2022

Coal pillar assessment is of broad importance to underground engineering structure, as the pillar failure can lead to enormous disasters. Because of the highly non-linear correlation between the pillar failure and its influential attributes, conventional forecasting techniques cannot generate accurate outcomes. To approximate the complex behavior of coal pillar, this paper elucidates a new idea to forecast the underground coal pillar stability using combined unsupervised-supervised learning. In order to build a database of the study, a total of 90 patterns of pillar cases were collected from authentic engineering structures. A state-of-the art feature depletion method, t-distribution symmetric neighbor embedding (t-SNE) has been employed to reduce significance of actual data features. Consequently, an unsupervised machine learning technique K-mean clustering was followed to reassign the t-SNE dimensionality reduced data in order to compute the relative class of coal pillar cases. Following that, the reassign dataset was divided into two parts: 70 percent for training dataset and 30 percent for testing dataset, respectively. The accuracy of the predicted data was then examined using support vector classifier (SVC) model performance measures such as precision, recall, and f₁-score. As a result, the proposed model can be employed for properly predicting the pillar failure class in a variety of underground rock engineering projects.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.73-78
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• 2022

The aim of this paper is to investigate the prevalence of Deep Learning in the literature on Fire & Rescue Service. It is found that deep learning techniques are only beginning to benefit the firefighters. The popular areas where deep learning techniques are making an impact are situational awareness, decision making, mental stress, injuries, well-being of the firefighter such as his sudden fall, inability to move and breathlessness, path planning by the firefighters while getting to an fire scene, wayfinding, tracking firefighters, firefighter physical fitness, employment, prediction of firefighter intervention, firefighter operations such as object recognition in smoky areas, firefighter efficacy, smart firefighting using edge computing, firefighting in teams, and firefighter clothing and safety. The techniques that were found applied in firefighting were Deep learning, Traditional K-Means clustering with engineered time and frequency domain features, Convolutional autoencoders, Long Short-Term Memory (LSTM), Deep Neural Networks, Simulation, VR, ANN, Deep Q Learning, Deep learning based on conditional generative adversarial networks, Decision Trees, Kalman Filters, Computational models, Partial Least Squares, Logistic Regression, Random Forest, Edge computing, C5 Decision Tree, Restricted Boltzmann Machine, Reinforcement Learning, and Recurrent LSTM. The literature review is centered on Firefighters/firemen not involved in wildland fires. The focus was also not on the fire itself. It must also be noted that several deep learning techniques such as CNN were mostly used in fire behavior, fire imaging and identification as well. Those papers that deal with fire behavior were also not part of this literature review.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1260-1265
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• 2009

Topographical features in South Korea is characterized that 70% of territory is composed of the mountains that can experience intense rainfall during storms in the summer and autumn. Efficient planning and management of landscape becomes utmost important since the cutting slopes in the mountain areas have been increased due to the limited construction areas for the roadway and residential development. This paper proposed an efficient way of slope management for the landslide risk by developing Web-GIS landslide risk management system. By deploying the Logistic Regression Analysis, the system could increase the prediction accuracy that the landslide disaster might be occurred. High resolution survey technology using GPS and Total-Station could extract the exact position and visual shape of the slopes that accurately describe the slope information. Through the proposed system, the prediction of damage areas from the landslide could also make it easy to efficiently identify the level of landslide risks via web-based user interface. It is expected that the proposed landslide risk management system can support the decision making framework during the identification, prediction, and management of the landslide risks.