• Journal of The Korea Institute of Healthcare Architecture
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• v.28 no.3
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• pp.7-16
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• 2022

Purpose: This study aims to establish the basic directions of the modular airborne infection isolation(AII) ward. Considering a specific function and purposed use as a modular AII ward, it is a chance to derive an address of current modular technology by overview the limitation and improvement of the existing modular architecture. Methods: In addition to the literature analysis on the configuration system of mobile hospitals, research cases on the operational effectiveness of the domestic and foreign mobile construction systems are analyzed. Results: In order to meet the various and strict space guidelines of the AII ward and a chance to improve limitations of uniformed existing modulars, AII modular the negative pressurized care setting should be minimized a structural restriction for reflecting its system on a architectural plan. For this unique requirements, it could be possible to apply various space boxes called infill box which needs to secure a large-scale space. So, a rahmen structure system could be adaptable for this purpose. A dead space between beams of the rahmen structure is to be used for MEP installation. Partial separation, dismantling, and repair should be possible by separating the MEP and infill box from the structure. The infill box must keep 3.5m width under the current Road Traffic Act. Implications: It is necessary to utilize and develop an improved construction method that can reduce the problems of existing steel modular and PC modular.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Journal of Korean Port Research
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• v.9 no.2
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• pp.9-24
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• 1995

The intensification of the competition among container terminals has led to important affect such as, decision making or aggressive intervention of customers for terminal operation. Therefore, in case of developed ports, the large transition of port operation is composed of the press of terminal customer than decision making of terminal manager. Overall port tariffs for using terminal is made out by the conference of terminal customers than the supreme headquarters of terminal operation, and the related investment of terminal has been made according to requisition or proposal of customers. Therefore, among decision making problems that shippers, shipping companies, and freight forwarder among decision making problems that shippers, shipping companies, and freight forwarder face, the choice of the container terminal is one of the most important problems. So, the decision making of the users seems to have a significant impact on the competitive power of container terminals. The main objective of this study is to design port marketing strategy for strengthening the competitive power of container terminals. The results of this study were found as follows: Firstly, port authority should establish user-oriented operation policy of terminal as the means of activating the opinion window, using terminal monitoring system(TMS). Secondly, terminal planning and development of government should be made to minimize the lead time, to induce the civil capital and to utilize the economies of scale. Thirdly, port authority needs to endeavor to analyze the information of competing foreign terminals as well to promote the concentrated marketing for the terminal on the users, to train the expert and to develop the new port charge system. Fourthly, to improve the competitive power of the container terminal, Port Authority should optimize the subsystems related to port marketing, far more these systems should be joined organically to work effectively. Finally, port authority system should be introduced, Namely, port should have the enterprise inclination as well s the public inclination.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.142-142
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• 2023

Humans inevitably and continuously produce wastewater in daily life worldwide. To decrease the degradation of river water bodies and aquatic ecosystem therein, humans have built systems at different scales to collect, drain, and treat household-produced wastewater. Particularly, municipal wastewater treatment plants (WWTPs) with centralized controls have played a key role in reducing loads of nutrients in domestic wastewater for the last few decades. Notwithstanding such contributions, impaired rivers regarding water quality and habitat integrity still exist at the whole river basin scale. It is highly attributable to the absence of dilution capacity of receiving streams and/or the accumulation of the pollutant loads along flow paths. To improve the perspective for individual WWTPs assessment, the first crucial step is to achieve systematic understanding on spatial distribution characteristics of all WWTPs together in a given river basin. By taking the initiative, our former study showed spatial hierarchical distributions of WWTPs in three large urbanized river basins in Germany. In this study, we uncover how municipal WWTPs in the contiguous United States are distributed along river networks in a give river basin. The extended spatial scope allows to deal with wide ranges in geomorphological attributes, hydro-climatic conditions, and socio-economic status. Furthermore, we identify the relation of the findings with multiple factors related to human activities, such as the spatial distribution of human settlements, the degree of economy development, and the fraction of communities served by WWTPs. Generalizable patterns found in this study are expected to contribute to establishing viable management plans for recent water-environmental challenges caused by WWTP-discharges to river water bodies.

• Journal of the Korean Geotechnical Society
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• v.23 no.5
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• pp.53-62
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• 2007

Recently, for the stabilization estimation of structures, many automatic measuring instruments with expensiveness and high accuracy have been developed and utilized. However, the existing manual measuring systems are almost impossible to measure the real-time for the whole surface of large-scale structures and an automatic measuring system has disadvantages with demanding enormous expense. In this study, 3D digital visual monitoring system was developed by using digital photogrammetry technique. To confirm application of developed system, it was applied to the measurement of the wall displacement of concrete surface and displacement measurement of reinforced-soil wall block. Then, the result of the test was compared with measuring value of total station. Based on the results of the comparison, the application of visual monitoring system was evaluated. The results show that the developed visual monitoring system could be available in displacement measure of structures.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.191-199
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• 2009

The integrated medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. Because of the large-scale medical institutions and their cooperating organizations are operating the integrated medical information systems, they can share medical images and diagnosis information. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image analysis system is necessary. In this paper, the proposed relationship method analyzes medical images for features generation. Under this method, the medical images have been segmented into several objects. The medical image features have been extracted from each segmented image. Then, extracted features were applied to the Relationship Method for medical image analysis. Several experimental results that show the effectiveness of the proposed method are also presented.

• Journal of Electrochemical Science and Technology
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• v.14 no.2
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• pp.152-161
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• 2023

Vanadium redox flow batteries (VRFBs) have been considered one of promising power sources for large scale energy storage systems (ESS) because of their excellent cycle performance and good safety. However, VRFBs still have a few challenging issues, such as poor Coulombic efficiency due to vanadium crossover between catholyte and anolyte, although recent efforts have shown promise in electrochemical performance. Herein, the vanadium complexes with various glyme ligands have been examined as active materials to suppress vanadium crossover between catholyte and anolyte, thus improving the Coulombic efficiency of VRFBs. The conventional Nafion membrane has a channel size of ca. 10 Å, whereas vanadium cation species are small compared to the Nafion membrane channel. For this reason, vanadium cations can permeate through the Nafion membrane, resulting in significant vanadium crossover during cycling, although the Nafion membrane is a kind of ion-selective membrane. In this regard, various glyme additives, such as 1,2-dimethoxyethane (monoglyme), diethylene glycol dimethyl ether (diglyme), and tetraethylene glycol dimethyl ether (tetraglyme) have been examined as complexing agents for vanadium cations to increase the size of vanadium-ligand complexes in electrolytes. Since the size of vanadium-glyme complexes is proportional to the chain length of glymes, the vanadium permeability of the Nafion membrane decreases with increasing the chain length of glymes. As a result, the vanadium complexes with tetraglyme shows the excellent electrochemical performance of VRFBs, such as stable capacity retention (90.4% after 100 cycles) and high Coulombic efficiency (98.2% over 100 cycles).

• Smart Structures and Systems
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• v.32 no.1
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• pp.1-7
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• 2023

In modal analysis, the mode shape reflects the vibration characteristics of the structure, and thus it is widely performed for finite element model updating and structural health monitoring. Generally, the acceleration-based mode shape is suitable to express the characteristics of structures for the translational vibration; however, it is difficult to represent the rotational mode at boundary conditions. A tilt sensor and gyroscope capable of measuring rotational mode are used to analyze the overall behavior of the structure, but extracting its mode shape is the major challenge under the small vibration always. Herein, we conducted a feasibility study on a multi-mode shape estimating approach utilizing a single physical quantity signal. The basic concept of the proposed method is to receive multi-metric dynamic responses from two sensors and obtain mode shapes through bridge loading test with relatively large deformation. In addition, the linear transformation matrix for estimating two mode shapes is derived, and the mode shape based on the gyro sensor data is obtained by acceleration response using ambient vibration. Because the structure's behavior with respect to translational and rotational mode can be confirmed, the proposed method can obtain the total response of the structure considering boundary conditions. To verify the feasibility of the proposed method, we pre-measured dynamic data acquired from five accelerometers and five gyro sensors in a lab-scale test considering bridge structures, and obtained a linear transformation matrix for estimating the multi-mode shapes. In addition, the mode shapes for two physical quantities could be extracted by using only the acceleration data. Finally, the mode shapes estimated by the proposed method were compared with the mode shapes obtained from the two sensors. This study confirmed the applicability of the multi-mode shape estimation approach for accurate damage assessment using multi-dimensional mode shapes of bridge structures, and can be used to evaluate the behavior of structures under ambient vibration.

• Smart Structures and Systems
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• v.31 no.3
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.