• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.100-109
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• 2019

Maintainability indicates the extent to which maintenance can be done easily and quickly. The consideration of maintainability is crucial to reduce the operation and support costs of weapon systems, but if the maintainability is evaluated after the prototype production is done and necessitates design changes, it may increase the cost and delay the schedule. The evaluation should verify whether maintenance work can be performed, and support the designers in developing a design to improve maintainability. In previous studies, the maintainability index was calculated using the graph theory at the early design phase, but evaluation accuracy appeared to be limited. Analyzing the methods of evaluating the maintainability using fuzzy logic and 3D modeling indicate that the design of a system with good maintainability should be done in an integrated manner during the whole system life cycle. This paper proposes a method to evaluate maintainability using SysML-based modeling and simulation technique and fuzzy logic. The physical design structure with maintainability attributes was modeled using SysML 'bdd' diagram, and the maintainability was represented by an AHP matrix for maintainability attributes. We then calculated the maintainability using AHP-based weighting calculation and fuzzy logic through the use of SysML 'par' diagram that incorporated MATLAB. The proposed maintainability model can be managed efficiently and consistently, and the state of system design and maintainability can be analyzed quantitatively, thereby improving design by early identifying the items with low maintainability.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.97-106
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• 2008

Quality of Protection(QoP) provides a standard that can evaluate networks offering protection. Also, QoP estimates stability of the system by quantifying intensity of the security. Security should be established based on the circumstance which applied to appropriate level, and this should chose a security policy which fit to propose of network because it is not always proportioned that between stability of security mechanism which is used at network and performance which has to be supported by system. With evolving wireless networks, a variety of security services are defined for providing secure wireless network services. In this paper, we propose a new QoP model which makes up for weak points of existing QoP model to choose an appropriate security policy for wireless network. Proposed new QoP model use objectively organized HVM by Flow-based Abnormal Traffic Detection Algorithm for constructing Utility function and relative weight for constructing Total reward function.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.417-428
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• 2005

Today, IT organizations perform projects with vision related to marketing and financial profit. The objective of realizing the vision is to improve the project performing ability in terms of QCD. Organizations have made a lot of efforts to achieve this objective through process improvement. Large companies such as IBM, Ford, and GE have made over $80\%$ of success through business process re-engineering using information technology instead of business improvement effect by computers. It is important to collect, analyze and manage the data on performed projects to achieve the objective, but quantitative measurement is difficult as software is invisible and the effect and efficiency caused by process change are not visibly identified. Therefore, it is not easy to extract the strategy of improvement. This paper measures and analyzes the project performance, focusing on organizations' external effectiveness and internal efficiency (Qualify, Delivery, Cycle time, and Waste). Based on the measured project performance scores, an OT (Opportunity Tree) model was designed for optimizing the project performance. The process of design is as follows. First, meta data are derived from projects and analyzed by quantitative GQM(Goal-Question-Metric) questionnaire. Then, the project performance model is designed with the data obtained from the quantitative GQM questionnaire and organization's performance score for each area is calculated. The value is revised by integrating the measured scores by area vision weights from all stakeholders (CEO, middle-class managers, developer, investor, and custom). Through this, routes for improvement are presented and an optimized improvement method is suggested. Existing methods to improve software process have been highly effective in division of processes' but somewhat unsatisfactory in structural function to develop and systemically manage strategies by applying the processes to Projects. The proposed OT model provides a solution to this problem. The OT model is useful to provide an optimal improvement method in line with organization's goals and can reduce risks which may occur in the course of improving process if it is applied with proposed methods. In addition, satisfaction about the improvement strategy can be improved by obtaining input about vision weight from all stakeholders through the qualitative questionnaire and by reflecting it to the calculation. The OT is also useful to optimize the expansion of market and financial performance by controlling the ability of Quality, Delivery, Cycle time, and Waste.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.316-328
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• 2021

In this study, the leaf Na content prediction model for spring potato was established using 400-1000 nm hyperspectral sensor to develop the multispectral sensor for the salinity monitoring in reclaimed land. The irrigation conditions were standard, drought, and salinity (2, 4, 8 dS/m), and the irrigation amount was calculated based on the amount of evaporation. The leaves' Na contents were measured 1st and 2nd weeks after starting irrigation in the vegetative, tuber formative, and tuber growing periods, respectively. The reflectance of the leaves was converted from 5 nm to 10 nm, 25 nm, and 50 nm of FWHM (full width at half maximum) based on the 10 nm wavelength intervals. Using the variance importance in projections of partial least square regression(PLSR-VIP), ten band ratios were selected as the variables to predict salinity damage levels with Na content of spring potato leaves. The MLR(Multiple linear regression) models were estimated by removing the band ratios one by one in the order of the lowest weight among the ten band ratios. The performance of models was compared by not only R2, MAPE but also the number of band ratios, optimal FWHM to develop the compact multispectral sensor. It was an advantage to use 25 nm of FWHM to predict the amount of Na in leaves for spring potatoes during the 1st and 2nd weeks vegetative and tuber formative periods and 2 weeks tuber growing periods. The selected bandpass filters were 15 bands and mainly in red and red-edge regions such as 430/440, 490/500, 500/510, 550/560, 570/580, 590/600, 640/650, 650/660, 670/680, 680/690, 690/700, 700/710, 710/720, 720/730, 730/740 nm.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.225-236
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• 1994

Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set［2］. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.6
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• pp.253-260
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• 2015

When we buy items in online stores, it is common to face recommended items that meet our interest. These recommendation system help users not only to find out related items, but also find new things that may interest users. Recommendation system has been widely studied and various models has been suggested such as, collaborative filtering and content-based filtering. Though collaborative filtering shows good performance for predicting users preference, there are some conditions where collaborative filtering cannot be applied. Sparsity in user data causes problems in comparing users. Systems which are newly starting or companies having small number of users are also hard to apply collaborative filtering. Content-based filtering should be used to support this conditions, but content-based filtering has some drawbacks and weakness which are tendency of recommending similar items, and keeping history of a user makes recommendation simple and not able to follow up users preference changes. To overcome this drawbacks and limitations, we suggest weighted window assisted user history based recommendation system, which captures user's purchase patterns and applies them to window weight adjustment. The system is capable of following current preference of a user, removing useless recommendation and suggesting items which cannot be simply found by users. To examine the performance under user and data sparsity environment, we applied data from start-up trading company. Through the experiments, we evaluate the operation of the proposed recommendation system.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.5
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• pp.141-150
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• 2014

In recent years, because of the development of ubiquitous technology in healthcare research is actively progress. Especially, healthcare service area is change to home for the elderly or patients from hospital. The technology to identify residents in a home is crucial for smart home application services. However, existing researches for resident identification have several problems. In this case, residents are needed to attach of various sensors on their body. Also relating private life, it is difficult to apply to resident's environment. In this paper, we used constraint-free sensor and unconscious sensor to solve these problems and we limited using of sensor and indoor environment in the way of working economical price systems. The way of multi-resident identification using only these limited sensors, we selected elements of personal identifications and suggested the methods in giving the weight to apply these elements to systems. And we designed the SABA mechanism to tract their location and identify the residents. It mechanism can distinguish residents through the sensors located each space and can finally identify them by using the records of their behaviors occurred before. And we applied the mechanism designed for applications to approve this location tracking system. We verified to the location tracking system performance according to the scenario.