• The KIPS Transactions:PartD
• /
• v.17D no.2
• /
• pp.147-156
• /
• 2010

Conformance testing for embedded software is to check whether software was correctly implemented according to software specification or not. In conformance testing, test scenarios must be extracted to cover every test cases of software. In a general way, test scenarios simply focus on testing all functions at least one time. But, test scenarios are necessary to consider efficiency of test execution. In this paper, we propose a test scenario extraction method by considering function's execution time and waiting time for user interaction. A test model is a graph model which is generated from state machine diagram and test cases in software specification. The test model is augmented by describing test execution time and user interaction information. Based on the test model, test scenarios are extracted by a modified Dijkstra's algorithm. Our test scenario approach can reduce testing time and improve test automation.

• Korean Journal of Agricultural Science
• /
• v.44 no.3
• /
• pp.451-461
• /
• 2017

Korean agriculture has recently focused on the 6th dimension of industrialization, which includes the functions of healing and care. The green care and healing business is one of the most representative models, satisfying modern consumers' needs for care or healing in rural agricultural environments. Many studies have shown physical and social benefits from green care and healing, but studies regarding economic performance are rarely found. The present study aimed to analyze the economic feasibility of different green care and healing farm complexes proposed in recent domestic research, with various possible combinations of business scenarios. The results show that most of the scenarios are economically feasible as B/C (benefit-cost ratio) and IRR (internal rate of return) are 1.19 and 8.53%, respectively, under scenario 1. This study also performed a break-even analysis for providing more flexible decision-making information. Overall, scenario 1 from green care and healing site and scenario 4 from green care and healing cluster are found to be superior to the other scenarios in terms of B/C and IRR. The scenarios in this study reflect the domestic farms or complexes which have similar functions of care or healing. Therefore, the results of this study provide information on practical policies and business implications in making decisions on the specific size and operational patterns when adopting green care and healing complexes by central or local governments and private sectors in the future.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.268-272
• /
• 2010

The research presented here represents a collaborative effort with the SFWMD on developing scenarios for future climate for the SFWMD area. The project focuses on developing methodology for simulating precipitation representing both natural quasi-oscillatory modes of variability in these climate variables and also the secular trends projected by the IPCC scenarios that are publicly available. This study specifically provides the results for precipitation modeling. The starting point for the modeling was the work of Tebaldi et al that is considered one of the benchmarks for bias correction and model combination in this context. This model was extended in the framework of a Hierarchical Bayesian Model (HBM) to formally and simultaneously consider biases between the models and observations over the historical period and trends in the observations and models out to the end of the 21st century in line with the different ensemble model simulations from the IPCC scenarios. The low frequency variability is modeled using the previously developed Wavelet Autoregressive Model (WARM), with a correction to preserve the variance associated with the full series from the HBM projections. The assumption here is that there is no useful information in the IPCC models as to the change in the low frequency variability of the regional, seasonal precipitation. This assumption is based on a preliminary analysis of these models historical and future output. Thus, preserving the low frequency structure from the historical series into the future emerges as a pragmatic goal. We find that there are significant biases between the observations and the base case scenarios for precipitation. The biases vary across models, and are shrunk using posterior maximum likelihood to allow some models to depart from the central tendency while allowing others to cluster and reduce biases by averaging. The projected changes in the future precipitation are small compared to the bias between model base run and observations and also relative to the inter-annual and decadal variability in the precipitation.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.7
• /
• pp.1568-1574
• /
• 2009

One of the most difficult problems in user requirement engineering is the communication gap that exists between different end-users, stakeholders, and software engineers. Since scenarios allow different stakeholders to describe and review the problem in their own language instead of some abstract model, they are also a solution to the problem. We propose a progressive, iterative and interleaved process of using scenario at different requirement engineering stages including elicitation, analysis and validation. This process model has been applied to our TRES System. In our proposed system, we combine prototype, scenarios and use cases in a single and comprehensive framework to avoid most of the shortcomings in other tools. Our system is an XML-based system for scenario-driven requirement engineering. Within the TRES system, scenarios are stories capture information about users and their tasks, including the context of use. In our TRES system, scenarios are stored in XML-based database and described using XML notation.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.519-519
• /
• 2016

Upper Chenab Canal (UCC) is a non-perennial canal in Punjab Province of Pakistan which provides irrigation water only in summer season. Winter and summer are two distinct cropping season with an average rainfall of about 161 mm and 700 mm respectively. Wheat-rice is common crop rotation being followed in the UCC command area. During winter season, groundwater and rainfall are the main sources of irrigation while canal and ground water is used to fulfil the crop water requirements (CWR) during summer. The objective of current study is to estimate how the irrigation water requirements (IWR) of the two crops are going to change under different conditions of temperature and rainfall. For this purpose, 12 different climatic scenarios were designed by combining the assumptions of three levels of temperature increase under dry, normal and wet conditions of rainfall. Weather records of 13 years (2000-2012) were obtained from PMD (Pakistan Meteorological Department) and CROPWAT model was used to simulate the IWR of the crops under normal and scenarios based climatic conditions. Both crops showed a maximum increase in CWR for temperature rise of $+2^{\circ}C$ i.e. 8.69% and 6% as compared to average. Maximum increment (4.1% and 17.51% respectively) in IWR for both wheat and rice was recorded when temperature rise of $+2^{\circ}C$ is coupled with dry rainfall conditions. March & April during winter and August & September during summer were the months with maximum irrigation requirements. Analysis also showed that no irrigation is needed for rice crop during May and June because of enough rainfall in this area.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.8
• /
• pp.121-129
• /
• 2013

As more than 80 percent of tasks within corporations are performed through information systems, they have become large in scale and complicated, which make the range of the system users diverse and specialized. and as recent corporate strategies focus on the real-time environment in businesses, the organizational structure within companies tend to show frequent changes. In order to ensure the business continuity in this environment, the most important aspect is to prevent incompleteness of business by narrowing the gap of understanding of business process between the system users and the maintenance managers. In order to address this problem, this study suggests a modeling method that utilizes business scenarios reflecting actual business rules and procedures which ultimately transforms the optimized and standardized form of business scenarios into the actual software maintenance activities. This modeling method improves reusability and usability through the repeated feedback mechanism for modified software by leading to gradual fine-grained process. The feasibility of this is to be proven by applying the modeling method to the real business environment.

• Journal of the Society of Disaster Information
• /
• v.16 no.4
• /
• pp.784-795
• /
• 2020

Purpose: This study intends to review the risk assessment procedures specified in the corporate disaster management standard. Method: The requirements for each stage of risk assessment stipulated in the corporate disaster management standard were identified, the case of application of the organization'A' and the partner companies were reviewed, and the risk assessment procedure in line with the requirements was reviewed. Result: It was reviewed that it was necessary to clearly define the method and procedure for deriving risk scenarios, which are the requirements of the corporate disaster management standard, and to introduce a standardized procedure for deriving risk scenarios. Conclusion: A method of deriving risk scenarios was implemented by applying the STPA technique based on the system theory for power generation fuel supply and demand, and it was suggested that the STPA technique be reflected in corporate disaster management standards as a risk scenario derivation technique for the establishment of a disaster reduction activity plan.

• Journal of Climate Change Research
• /
• v.7 no.3
• /
• pp.257-268
• /
• 2016

Both economic growth and industrial structure have great influence on energy consumption and GHG emissions. This study analyzed long-term scenarios for GHG emissions projections considering economic growth and industry value added change. In consideration of 3 GDP and 3 industry value added outlook, total 9 scenarios were set; 'Assembly Industry Baseline(AI)', 'Assembly KEIT industry(AK)', 'Assembly Advanced Country industry(AA)', 'KDI Industry Baseline(KI)', 'KDI KEIT industry(KK)', 'KDI Advanced Country industry(KA)', 'OECD Industry Baseline(OI)', 'OECD KEIT industry(OK)', and 'OECD Advanced Country industry(OA)' scenarios. In consideration of the GDP increase rate and industry value added outlook, it is estimated that AI scenario's GHG emissions would be 777 million tons of $CO_2eq$ in 2030. On the other hand, in the case of OA scenario, GHG emissions would be 560.2 million tons of $CO_2eq$ in 2030. Differences between AI scenario's and OA scenario's were 216.8 million tons of $CO_2eq$. It can be identified by that GDP and industry value added change have great influence on GHG emissions. In view of the fact that Korea's amount of GHG emission reduction targets in 2030 were 218.6 million tons of $CO_2eq$ that the result of this research could give us valuable insight.

• Wind and Structures
• /
• v.35 no.6
• /
• pp.405-418
• /
• 2022

The aerodynamic behaviour of a CRH high-speed train under three infrastructure scenarios (flat ground, embankment, and viaduct) in the presence of a crosswind was simulated using a 1/8th scaled train model with three cars and the IDDES framework. The time-averaged and instantaneous flow field around the model were examined. The employed numerical algorithm was verified through a wind tunnel test, and the grid and timestep resolution analyses were conducted to ensure the reliability of the data. It was noted that the flow around the rail line was different under different infrastructure scenarios, especially in the case of the embankment, which degraded the aerodynamic performance of the train under the crosswind. The flow around the train on the flat ground and viaduct was different, although the aerodynamic performance of the train was similar in both cases. Moreover, the viaduct accidents were noted to have the most critical consequences, thereby requiring the most attention. The aerodynamic performance of the train on the windward track of the embankment under the crosswind was worse than that of the train on the leeward track. But for the other two infrastructure scenarios, the aerodynamic performance of the train on the windward track is relatively dangerous, which is mainly caused by the head car. These observations suggest that the aerodynamic behaviour of the train on an embankment under a crosswind must be carefully considered and that certain wind protection measures must be adopted around rail lines in windy areas.

• Journal of Korean Society on Water Environment
• /
• v.40 no.3
• /
• pp.121-129
• /
• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.