• 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.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.185-190
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• 1995

Conventional alarm system has many difficulties in the operator's identifying the plant status during special situations such as design basis accidents. To solve the shortcomings, an on-line alarm annunciator system, called dynamic alarm console (DAC), was developed. In the DAC, a signal is generated as alarm by the use of an adaptive setpoint check strategy based on operating mode, and time delay technique is used not to generate nuisance alarms. After alarm generation, if activated alarm is a level precursor alarm or a consequencial alarm, it would be suppressed, and the residual alarms go through dynamic prioritization which provide the alarms with pertinent priorities to the current operating mode. Dynamic prioritization is achieved by going through the system- and mode-oriented prioritization. The DAC has the alarm hierarchical structure based on the physical and functional importance of alarms. Therefore the operator can perceive alarm impacts on the safety or performance of the plant with the alarm propagation from equipment level to plant functional level. In order to provide the operator with the most possible cause of the event and quick cognition of the plant status even without recognizing the individual alarms, reactor trip status tree (RTST) was developed. The DAC and the RTST have been simulated with on-line data obtained from the full-scope simulator for several abnormal cases. The results indicated that the system can provide the operator with useful and compact information fur the earlier termination and mitigation of an abnormal state.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.295-304
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• 2014

Communication infrastructure supports wide variety of mobile services such as photo and file sharing, location tracking, social network services and instant messaging. However, instances like power-loss and natural disasters disrupt these communication infrastructures unable to render support to these mobile services. Delay-tolerant networks (DTNs) offer a solution to these problems at hand. By utilizing mobility and opportunistic contacts among mobile devices, a plausible communication network can be establish and enable support to mobile applications. This paper presents an energy-efficient, reliable message delivery routing scheme with message prioritization rules for DTN. It uses the context information of nodes (mobile devices) such as the contact history (location and time of contact), speed/velocity, moving direction to determine the best forwarders among nodes in the network. The remaining energy of the nodes is also used to determine the message types a node can deliver successfully. The simulation results show that proposed approach outperforms Epidemic and Prophet routing schemes in terms of delivery ratio, overhead ratio, delivered messages per types and remaining energy.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.181-181
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• 2017

Low impact development (LID) practices has become important to mitigate the damage from natural disasters in urban areas. Thereby many hydrological simulation models can simulate the hydrological impact of LID practices. However, commonly used models are not able to provide specific information to most users such as where LIDs should be placed and what kind of LID should be designed. In this study, a decision support system which can be used with the EPA's SWMM was developed for the determination of LID types and locations of LID practices, named Water Management Prioritization Module (WMPM), was applied to a urbanized university campus. Eight sub-catchments were selected as feasible candidate areas for the planning of LID practices. Pre-designated infiltration trenches and permeable pavements were applied to each selected sub-catchments, followed by peak and total runoffs comparison between before/after planning of LIDs. Moreover, TOPSIS, one of a multi-criteria decision analysis method was used in the procedure of selecting target sub-catchment areas and final prioritization of LID types and locations. As a result, sub-catchments S4 with permeable pavements and S16 with infiltration trenches has shown the most decrease in total and peak runoffs, respectively. Therefore, WMPM was found to be effective in determining the best alternative among various scenarios generated and simulated.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.129-137
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• 2010

In this paper, we propose a packet prioritization scheme using preamble signal and backoff time which is designed to provide a differentiated channel occupation with a packet priority in wireless sensor networks. This scheme aims at enabling QoS such as fast delivery of high priority packets by reducing their backoff time as well as thus securing higher channel occupation. We expect that it could also improve the channel utilization of the entire network by avoiding unnecessary channel contention. For the purpose, we add new features of multiple queue and preamble modification to the TinyOS based B-MAC. This scheme achieves 82-88% reduction in delivery time of high priority packets, thus it enables realtime support for urgent applications.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.1-10
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• 2019

Research classification of software modules was done to validate the approaches proposed for addressing limitations in existing classification approaches. The objective of this study was to replicate the experiments of a recently published research study and re-evaluate its results. The reason to repeat the experiment(s) and re-evaluate the results was to verify the approach to identify the faulty and non-faulty modules applied in the original study for the prioritization of test cases. As a methodology, we conducted this study to re-evaluate the results of the study. The results showed that binary logistic regression analysis remains helpful for researchers for predictions, as it provides an overall prediction of accuracy in percentage. Our study shows a prediction accuracy of 92.9% for the PureMVC Java open source program, while the original study showed an 82% prediction accuracy for the same Java program classes. It is believed by the authors that future research can refine the criteria used to classify classes of web systems written in various programming languages based on the results of this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1607-1614
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• 2016

Because required weapon systems in the planning stage exceed the extent of defense budget, we should consider the priorities of them in the programming and budget stage. The purpose of this paper is to find out the factors that affect the prioritization of required weapon systems limited by budget. For this purpose, we analyse statistically major 20 defense projects launched in 2014. We derived the reasons for prioritization through the pairwise comparisons and also extracted six representative factors through the Exploratory Factor Analysis(EFA). The KMO was 0.779 and the total variance explained was 79.59%, Cronbach's Alpha was above 0.7 which means EFA was appropriate to accept. The significance of this paper is that influencing factors on prioritization was derived by the comparisons using the present weapon systems and people in charge of defense acquisition. The factors can be utilized in AHP or Delphi to determine the priority and ultimately contribute to rational judgement for the military strategy objectives within the limited resources.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.115-127
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• 2021

With the development of science and technology around the world, the realm of cyberspace, following land, sea, air, and space, is also recognized as a battlefield area. Accordingly, it is necessary to design and establish various elements such as definitions, systems, procedures, and plans for not only physical operations in land, sea, air, and space but also cyber operations in cyberspace. In this research, the importance of cyber targets that can be considered when prioritizing the list of cyber targets selected through intermediate target development in the target development and prioritization stage of targeting processing of cyber operations was selected as a factor to be considered. We propose a method to calculate the score for the cyber target and use it as a part of the cyber target prioritization score. Accordingly, in the cyber target prioritization process, the cyber target importance category is set, and the cyber target importance concept and reference item are derived. We propose a TIR (Target Importance Rank) algorithm that synthesizes parameters such as Event Prioritization Framework based on PageRank algorithm for score calculation and synthesis for each derived standard item. And, by constructing the Stuxnet case-based network topology and scenario data, a cyber target importance score is derived with the proposed algorithm, and the cyber target is prioritized to verify the proposed algorithm.

• Proceedings of the Korea Water Resources Association Conference
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• 2003.05a
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• pp.493-496
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• 2003

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