• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.279-280
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• 2023

Due to the deterioration of infrastructure, the importance of maintenance is continuously increasing. Therefore, an integrated maintenance method for various facilities is required. In this study, a maintenance priority determination method for integrated maintenance of roads and pipe network facilities was developed. It is possible to analyze attribute information by using GIS data of roads and pipe networks, and shape information can be used. This information is derived as quantitative figures for determining maintenance priorities. In the future, it is expected that facility maintenance can be further advanced in connection with maintenance method and quantity information for each facility.

• Journal of the Korean Geotechnical Society
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• v.38 no.12
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• pp.79-89
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• 2022

Every summer in our country, an accident occurs, in which the retaining wall on a steep slope collapses due to torrential rain. According to the data on the results of steep slope risk assessment in 2019, over 780 retaining walls are below grade C; therefore, preparing for countermeasures is urgent. However, due to the limited budget for the repair and reinforcement of these retaining walls, it is necessary to discuss the investment prioritization. In this study, a prioritization method was proposed at the network and project levels along with the review of the revised criteria of disaster risk assessment in the steep slope retaining wall, and an application research in the network level was conducted for six retaining walls. Moreover, it is proposed that the priority index was determined by using the actual cost for repair and reinforcement in determination of the project level prioritization.

• Land and Housing Review
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• v.2 no.2
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• pp.171-182
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• 2011

Current state of population, the existing roads, and the function of roads and highways of North Korea have been reviewed in this paper. In addition, the 'Five by five' road network has proposed for North-South and East-West directions to be connected with the road network of South Korea, China, and Asian Highways. Furthermore, the evaluation criteria and weighted values have suggested to determine the investment priority of highway based on the survey results from expert group members using AHP analysis method. Throughout the analysis, the ranking of the investment priority has been decided for the North-South axis and East-West axis. The second North-South axis (Geasung-Pyungyang-Anju-China) has been ranked as the first priority for the North-South axis followed by the fifth North-South axis as the second, the first axis as the third, the third axis as the fourth and the fourth axis as the last priority. For the East-West axis, the second East-West axis(Nampo-Pyungyang-Wonsan) has been ranked as the first priority followed by the first axis as the second, the third axis as the third, the fourth axis as the fourth and the fifth East-West axis as the last priority.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.561-565
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• 2010

Many methods have been researched to prolong sensor network lifetime using mobile technologies. In the mobile sink research, there are the track based methods and the anchor points based methods as representative operation methods for mobile sinks. However, the existing methods decrease Quality of Service (QoS) and lead the routing hotspot in the vicinity of the mobile sink. The reason is that they use static mobile paths that are not concerned about the network environments such as the query position and the data priority. In this paper, we propose the novel mobile sink operation method that solves the problems of the existing methods. In our method, the probing priority of the mobile sink is determined with the data priorities for increasing the QoS and the mobile features are used for reducing the routing hotspot. The experimental results show that the proposed method reduces query response time and improves network lifetime over the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1252-1260
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• 2017

As digital communication technology evolves, the diversity of maritime communication methods has benn increasing due to the emergence of new maritime communication technologies such as digital very high frequency (VHF) communication systems and LTE-M as well as traditional conventional maritime communication systems. At sea, all maritime communication methods may be available, but only some communication methods may be available depending on the location. In this paper, we propose a multi-band network selection (MNS) system that can provide seamless maritime communication service by switching to an optimal communication band among available communication systems, depending on network environment and user requirements. The proposed MNS system in the middleware layer is designed to be able to interface with two types of digital VHF communication systems that satisfy Annex 1 and Annex 4 of ITU-R M. 1842-1, LTE, and high frequency (HF) communication systems. We assign priority to each communication band, and design an optimal communication band determination algorithm based on this priority.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.7
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• pp.650-664
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• 2000

NOW(Network of Workstations) is considered as a platform for running parallel programs by many people. One of the fundamental problems that must be addressed to achieve good performance for parallel programs on NOW is the determination of efficient job scheduling policies. Currently most research on NOW assumes that all the workstations in the NOW have the same processing power. In this paper we consider a NOW in which workstations may have different computing power. We introduce 10 classes of space sharing-based scheduling policies that can be applied to the NOW with heterogeneous computing power. We compare the performance of these scheduling policies by using the simulator which accepts synthetically generated sequential and parallel workloads and generates the response time and waiting time of parallel jobs as performance indices of various scheduling strategies. Through the experiments the case when a parallel program is partitioned heterogeneously in proportion to the computing power of workstations is shown to have better performance than when a parallel program is partitioned into parallel processes of the same size. When the owner returns to the workstation which is executing a parallel process, the policy which just lowers the priority of the parallel process shows better performance than the one which migrates the parallel process to a new idle workstation. Among the policies which use heterogeneous partitioning and process priority lowering, the adaptive policy performed best across the wide range of inter-arrival time of parallel programs but when the load imbalance among parallel processes becomes very high, the modified adaptive policy performed better.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1167-1175
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• 2022

In this study, management index method has been developed to estimate the level of deterioration, applied to Cheongju city, and compared with the previous estimation methods of deterioration level of water distribution system. From the results, distribution systems of Yullyang, Naedeok1 and Yongam2 are found to be seriously deteriorated. And it was also found that probability of pipe breakage was estimated as 3.21%, 4.64% which is highest level at the steel pipe of 200 mm and 300 mm diameter. It was found that risk degree was estimated as 0.2609, 0.2644 by using management index method in Naedeok1 which is the most dangerous distribution system in the city. It was also found that results of risk analysis by management index method have been similar with the results of safety analysis by reliability method and indirect estimation method of deterioration level. Therefore, newly developed management index method can be applied and may be useful to the estimation of deterioration level for the future maintenance and management of water distribution system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.