• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.68-76
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• 2018

Target prioritization is necessary for a multifunction radar(MFR) to track an important target and manage the resources of the radar platform efficiently. In this paper, we consider an artificial neural network(ANN) model that calculates the priority of the target. Furthermore, we propose a neural network learning algorithm based on the steepest descent method, which is more suitable for target prioritization by combining the conventional gradient descent method. Several simulation results show that the proposed scheme is much more superior to the traditional neural network model from analyzing the training data accuracy and the output priority relevance of the test scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.515-524
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• 2014

In this paper, The investment prioritization model was investigated for keeping the service level of mooring facilities more than the target level of management with a limited budget in the right time. Network level prioritization criteria of the national scale was developed to take into criteria index and quantitative evaluation, management authority's opinion. Delphi method was conducted maintenance exports of mooring facilities over twice for verifying the validity and adequacy. In order to improve the objectivity of criteria, the criteria for evaluating the utilization of port facilities is presented form yearly facility traffic/facility's length, the result of the analysis of facility traffic data. The investment prioritization criteria of mooring facilities is expected to be utilized for more efficient and national budget distribution applied to the maintenance budget plan of nationwide.

• 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 Institute of Military Science and Technology
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• v.22 no.4
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• pp.555-566
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• 2019

In order to prepare for the future warfare environment, which requires a faster operational tempo, it is necessary to utilize the fourth industrial revolution technology in the field of military operations. This study propose a methodology, 'machine learning based dynamic targeting', which can contribute to reduce required man-hour for dynamic targeting. Specifically, a decision tree algorithm is considered to apply to dynamic targeting process. The algorithm learns target prioritization patterns from JIPTL(Joint Integrated Prioritized Target List) which is the result of the deliberate targeting, and then learned algorithm rapidly(almost real-time) determines priorities for new targets that occur during ATO(Air Tasking Order) execution. An experiment is performed with artificially generated data to demonstrate the applicability of the methodology.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.198-206
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• 2013

This paper presents the improvement of tracking performance using fuzzy inference system based task prioritizations for multi-function radars. The presented technique calculates elemental priorities using track information of a target and obtain the total priority from fuzzy inference system of each fuzzy set's membership function. In this paper, we proposed the task prioritization algorithms based on fuzzy inference system, and evaluated the tracking performance on multi-function radar scenario using it. As a result, we confirmed that excellent performance could be achieved when using the proposed algorithm.

• Information Systems Review
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• v.8 no.1
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• pp.25-41
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• 2006

This paper is about how to drive a Business Process Management(BPM) implementation project from selecting a target process to BPM deployment. For guidance of BPM implementation, LG CNS BPM Methodology and enPAM(Entrue Process Assessment Model) were used. This paper focuses on the methodology of process selection and presents a case study from the telecommunication industry. The enPAM consists of three major criteria in determining process priority for BPM system deployment: business impact, BPM adequateness and implementation feasibility. These three criteria can be easily modified for other telecommunication business just as we did to suit this telecom case. Moreover, it could provide useful ideas to companies that consider introducing a BPM solution for process management. Although we propose a comprehensive design methodology for selecting a proper target business process for BPM implementation, more work is still needed to extend the results for rigorous and practical method.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.433-446
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• 2009

Pharmaceuticals in the aquatic environment are trace contaminants of growing importance in environmental health due to their physiologically active nature. Pharmaceuticals could affect non-target species and might eventually damage sustainability of susceptible populations in the ecosystem. Potentials for health consequences among susceptible human population cannot be ruled out since long-term exposure to cocktails of pharmaceuticals, which might be present in drinking water, is possible. Selection of antibiotic resistant microorganisms is of another concern. In order to understand, and if needed, to properly address the environmental health issues of pharmaceutical residues, knowledge gaps need to be filled. Knowledge gaps exist in many important areas such as prioritization of target pharmaceuticals for further risk studies, occurrence patterns in different environments, chronic toxicities, and toxicities of pharmaceutical mixtures. Appropriate treatment technologies for drinking water and wastewater could be developed when they are deemed necessary. One of the simplest, yet most efficient measures that could be undertaken is to implement a return program for unused or expired drugs. In addition, implementation of environmental risk assessment frameworks for pharmaceuticals would make it possible to efficiently manage potential environmental health problems associated with pharmaceutical residues in the environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3885-3906
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• 2020

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.

• Journal of Distribution Science
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• v.20 no.2
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• pp.19-29
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• 2022

Purpose: Understanding the distribution channel is a foundational element of successful hotel revenue management. This study aims to assess hotel distribution network partnerships and develops a model that can be utilized to ensure hoteliers are not becoming increasingly reliant on a single channel, optimize their market exposure, and maximize their portion of the overall worth of the network. Research design, data and methodology: This study utilizes a grounded theory approach to form a theoretical model by analyzing and examining the current practice of hotel distribution management through interviews with 15 stakeholders in Indonesia, such as hoteliers, online travel agents, wholesalers, and connectivity managers. Results: Based on data analysis, we describe hotel distribution elements, revenue team, managed channels, and channel prioritization for a different type of hotel. Finally, we propose a distribution channel model that comprises hotel teams, customer types, indirect channels, and direct channels. Conclusions: The model contributes to the literature by exploring the options of distribution channels for various hotel types to support hotel revenue management practice. By utilizing our model, practitioners can have a complete picture regarding the strategic choice of the channel by considering their hotel capacity and market target.