• Journal of the Korean Geotechnical Society
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• v.38 no.6
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• pp.5-16
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• 2022

In the case of domestic seismic design, deformation of structures and ground is reviewed through undrained condition analysis and applied to design and maintenance. However, when the ground undergoes dissipation after liquefaction due to a dynamic load such as an earthquake, additional displacement occurs and greater damage occurs. Therefore, it is necessary to additionally analyze the drained conditions, It is necessary to grasp the exact ground behavior such as calculating and reviewing the amount of subsidence of the ground that has undergone the loss process after an earthquake and apply it to design and maintenance together. Therefore, in this study, numerical analysis was performed assuming undrained and drained conditions by dividing pure sandy soil into loose soil with Dr=30% and high-density soil with Dr=70%. In particular, when a dynamic load such as an earthquake is applied, considering the drained conditions of the ground, the settlement amount and the pore water pressure ratio of loose and dense ground are compared, This study focused on comparative analysis of settlement amount and pore water pressure ratio in the process of ground loss after an earthquake. As a result, the amount of subsidence during the dissipation process was 30 to 60 times greater than that of the earthquake.

• The Korean Journal of Emergency Medical Services
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• v.26 no.2
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• pp.97-111
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• 2022

Purpose: Automated External Defibrillator (AED) usage in out-of-hospital cardiac arrests (OHCAs) improves the survival of patients. In Singapore, public AEDs are protected by locked boxes with a 'break glass' mechanism to deter theft. Community responders have sustained injuries while breaking glass to retrieve AEDs. This unprecedented study aimed to elucidate the factors influencing successful retrieval of an AED and to document the prevalence of injuries. Methods: A survey was created and distributed. Participants were required to have responded to an OHCA in the past 12 months. Comparison tests were performed with the Fischer-Freeman-Halton Exact test or Pearson chi square test at 5% significance levels, and with multiple logistic regression with a logit link function. Results: Eighty-eight participants were eligible. The success of retrieving an AED was found not to be impacted by occupation, age, gender or time. Participants who responded to an OHCA because of activation by the myResponder App were more likely to retrieve an AED successfully. (AOR 11.111, 95% CI: 2.141-58.824) Conclusion: Use of the myResponder mobile application is associated with the greater success of retrieving an AED. Successful retrieval of an AED is not impacted by time, gender, age, or the occupation of the responder. Community responders in Singapore remain motivated to respond to Cardiac Arrests despite risk of injury.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.185-191
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• 2022

This paper proposed a division algorithm of performance complexity $O{\frac{n(n+1)}{2}}$ for a change-making problem(CMP) in which polynomial time algorithms are not known as NP-hard problem. CMP seeks to minimize the sum of the x_j number of coins exchanged when a given amount of money C is exchanged for c_j,j=1,2,⋯,n coins. Known polynomial algorithms for CMPs are greedy algorithms(GA), divide-and-conquer (DC), and dynamic programming(DP). The optimal solution can be obtained by DP of O(nC), and in general, when given C>2ⁿ, the performance complexity tends to increase exponentially, so it cannot be called a polynomial algorithm. This paper proposes a simple algorithm that calculates quotient by dividing upper triangular matrices and main diagonal for k×n matrices in which only j columns are placed in descending order of c_j of n for c_j ≤ C and i rows are placed k excluding all the dividers in c_j. The application of the proposed algorithm to 39 benchmarking experimental data of various types showed that the optimal solution could be obtained quickly and accurately with only a calculator.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.42-49
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• 2023

Poor indoor acoustic environments negatively affect occupants. Previous research has shown that indoor acoustic environments affect not only task performance and job satisfaction of the occupants, but also their health and well-being. This study aimed for evaluating indoor acoustic environments of open-plan offices located in public buildings in Korea. It also aimed to review the matters that need to be considered in order to improve occupants' acoustic comfort. Indoor noise levels were measured in 13 sites; the measurements were conducted for five consecutive working days from Monday to Friday. The noise levels were evaluated based on the levels recommended by the ISO and the EU ALDREN project. The study found that most of the indoor noise levels measured in the sampled sites during the working hours met the ISO standard. In the case of the levels under unoccupied conditions at night, those at three sites did not meet the recommendation of the ALDREN. In addition, some characteristics of the sites had significant effects on the noise level. Since the exact acoustic performance of the building envelope could not be identified, future research is needed for investigating the relationship between accurate building performance and indoor acoustic environments.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.367-374
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• 2022

This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.

• Journal of the Korean earth science society
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• v.44 no.2
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• pp.148-160
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• 2023

The Pliny Letter, the first historical record of volcanic eruptions and disasters on Earth, was studied to better understand the Vesuvius' eruption patterns in 79 AD. The two-day eruption, which began at 1 a.m. on August 24th 79 AD, produced large amounts of volcanic ash and pumice, which were carried by the wind and fell on nearby cities. Furthermore, during the eruption, fast-moving pyroclastic flows flowed down the volcano's sides, and several phenomena such as earthquakes and tsunamis occurred. Cities near Mount Vesuvius were buried and destroyed by volcanic ash and pyroclastic flows. Previous studies were collected, analyzed, and investigated and the scope of damage was chosen from Pompeii, Herculaneum, Stabiae, and Oplontis. The sedimentary stratigraphy and thickness vary according to location and distance from Vesuvius in each region. Within the depositional layers, the remains of residents who died during the eruption were also discovered, and 1,150 remains have been discovered in Pompeii, 306 in Herculaneum, 111 in Stabiae, and 54 in Oplontis, but the exact number of people who killed is unknown. The eruption that exhibited the pattern seen in AD 79 was named the Plinian eruption after Pliny and classified as a new type of eruption as a result of Pliny's detailed description of the eruption.

• Journal of Life Science
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• v.33 no.5
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• pp.429-435
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• 2023

Epidemiological studies suggest that maternal infection, maternal stress, and environmental risk factors during pregnancy increase the risk of brain development abnormalities associated with cognitive impairment in the offspring and increase susceptibility to schizophrenia and autism spectrum disorder. Several animal models have demonstrated that maternal immune activation (MIA) is sufficient to induce abnormal brain development and behavioral defects in the fetus. When polyinosine:polycytodylic acid (poly I:C) or lipopolysaccharide (LPS), which is commonly used in maternal immune activation animal models, was introduced into a pregnant dam, an increase in pro-inflammatory cytokines and microglial activity was observed in the offspring's brain. Microglia are brain-resident immune cells that play a mediating role in the central nervous system, and they are responsible for various functions, such as phagocytosis, synapse formation and branching, and angiogenesis. Several studies have reported that microglia are activated in MIA offspring and influence offspring behavior through interactions with various cytokines. In addition, it has been reported that they play an important role in brain circuits through interactions with neurons and astrocytes. However, there is controversy concerning whether microglia are essential to brain development or lead to behavioral defects, and the exact mechanism remains unknown. Therefore, for the potential diagnosis and treatment of brain developmental disorders, a functional study of microglia should be conducted using MIA animal models.

• Journal of Korean Foot and Ankle Society
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• v.27 no.2
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• pp.49-54
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• 2023

Purpose: The present study examined the effectiveness of the preoperative ischemia-modified albumin (IMA) levels in predicting the healing period of amputation wounds in patients with diabetes mellitus following a non-traumatic below-knee amputation (BKA). Materials and Methods: This study enrolled 41 diabetic foot ulcer patients who underwent BKA at the authors' hospital diabetic foot center from April 2016 to April 2022. Among the 41 patients, 29 (70.7%) were male and 12 (29.3%) were female. Their mean age was 64.54±11.38 years (41~81 years). The mean follow-up period was 19.48±5.56 weeks (14~48 weeks) after BKA. The patients were divided into two groups (high IMA group and normal IMA group), which evaluated the healing period, wound dehiscence, and revision operation rate using a Fisher's exact test and Mann-Whitney U test. Three orthopedic surgeons performed stump wound evaluation, and they were evaluated as healing when all sutures were fused without oozing. Results: Thirty patients (73.2%) (group A) showed a high level of IMA (median: 91.2 U/mL), and 11 (26.8%) patients (group B) showed a normal range of IMA (median: 82.7 U/mL). In group A, the median period for wound healing took 1.4 weeks longer, which was significant (p=0.001). No statistical relationship was observed between wound dehiscence, revision operation rate, and IMA value. There was no correlation between the other risk factors (estimated glomerular filtration rate, HbA1c) and the wound healing period. Conclusion: Although there was a limitation in using IMA as the sole factor to predict the healing period of amputation wounds in patients after BKA, this study revealed a significant positive correlation between IMA and the period of stump healing after BKA. Therefore, the preoperative IMA levels may help predict the period of stump healing after BKA.

• Journal of Platform Technology
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• v.10 no.4
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• pp.47-55
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• 2022

Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1249-1249
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• 2022

The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.