• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4191-4211
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• 2019

Software product lines (SPLs) are complex software systems by nature due to their common reference architecture and interdependencies. Therefore, any form of evolution can lead to a more complex situation than a single system. On the other hand, software product lines are developed keeping long-term perspectives in mind, which are expected to have a considerable lifespan and a long-term investment. SPL development organizations need to consider software evolution in a systematic way due to their complexity and size. Addressing new user requirements over time is one of the most crucial factors in the successful implementation SPL. Thus, the addition of new requirements or the rapid context change is common in SPL products. To cope with rapid change several researchers have discussed the evolution of software product lines. However, for the evolution of an SPL, the literature did not present a systematic process that would define activities in such a way that would lead to the rapid evolution of software. Our study aims to provide a requirements-driven process that speeds up the requirements engineering process using social network sites in order to achieve rapid software evolution. We used classification, topic modeling, and sentiment extraction to elicit user requirements. Lastly, we conducted a case study on the smartwatch domain to validate our proposed approach. Our results show that users' opinions can contain useful information which can be used by software SPL organizations to evolve their products. Furthermore, our investigation results demonstrate that machine learning algorithms have the capacity to identify relevant information automatically.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.109-123
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• 2017

The effects of recent climate change on hydrological systems could affect the Winter Olympic Games (WOG) because the event is dependent on suitable snow and ice conditions to support elite-level competitions. We investigate the long-term variability and change in winter total precipitation (P), snowfall water equivalent (SFE), and ratios of SFE to P during the period 1973/74~2015/16 in Gangwon province. The climatological percentages of SFE relative to winter total precipitation were 71%, 28%, and 44% in Daegwallyeong, Chuncheon, and Gangneung, respectively. The winter total P, SFE, and SFE/P has decreased (but not significantly), although significant increases of winter maximum and minimum temperature were detected at a 95% confidence level. Notably, a significant negative trend of SFE/P at Daegwallyeong in February, the month of the WOG, was attributable to a larger decrease in SFE related to the increases in maximum and minimum temperature. Winter wet-day minimum temperatures were warmer than climatological minimum temperatures averaged over the study period. The 20-year return values of daily maximum P and SFE decreased in Yongdong area. Since the SFE/P decrease with increasing temperature, the probability of rainfall rather than snowfall can increase if global warming continues.

• Metals and materials international
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• v.24 no.6
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• pp.1213-1220
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• 2018

The effects of Cr and Fe addition on the mechanical properties of Ti-6Al-4V alloys prepared by direct energy deposition were investigated. As the Cr and Fe concentrations were increased from 0 to 2 mass%, the tensile strength increased because of the fine-grained equiaxed prior ${\beta}$ phase and martensite. An excellent combination of strength and ductility was obtained in these alloys. When the Cr and Fe concentrations were increased to 4 mass%, extremely fine-grained martensitic structures with poor ductility were obtained. In addition, Fe-added Ti-6Al-4V resulted in a partially melted Ti-6Al-4V powder because of the large difference between the melting temperatures of the Fe eutectic phase (Ti-33Fe) and the Ti-6Al-4V powder, which induced the formation of a thick liquid layer surrounding Ti-6Al-4V. The ductility of Fe-added Ti-6Al-4V was thus poorer than that of Cr-added Ti-6Al-4V.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.1-9
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• 2018

Drug repositioning is to discover new uses of drugs. Text mining derives knowledge from unstructured text. We propose a method to predict new drug-disease relationships by taking into account the rate of frequency of genes simultaneously measured in disease-gene and gene-drug. Co-occurrence of drug-gene and gene-disease in the biological literature is counted and calculate the rate of the gene for each drug and disease. Weights of drug-disease relationships are calculated using the average of the rates of genes that are measured and used to measure the accuracy for each disease. In measuring drug-disease relationships, a more accurate identification of relationships was shown by measuring the frequency on a sentence and considering multiple relationships than existing method.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.411-418
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• 2018

With the proliferation of artificial intelligence technology, it is becoming important to obtain, store, and utilize scientific data in research and science sectors. A number of methods for extracting meaningful objects such as graphs and tables from research articles have been proposed to eventually obtain scientific data. Existing extraction methods using heuristic approaches are hardly applicable to electronic documents having heterogeneous manuscript formats because they are designed to work properly for some targeted manuscripts. This paper proposes a prototype of an object extraction system which exploits a recent deep-learning technology so as to overcome the inflexibility of the heuristic approaches. We implemented our trained model, based on the Faster R-CNN algorithm, using the Google TensorFlow Object Detection API and also composed an annotated data set from 100 research articles for training and evaluation. Finally, a performance evaluation shows that the proposed system outperforms a comparator adopting heuristic approaches by 5.2%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.863-869
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• 2018

Due to recent changes in the maritime traffic environment, naval warship accidents are constantly occurring. Especially in 2017, serious loss of life was caused by a US navy destroyer accident. The purpose of this study is to analyze the characteristics of naval warship accident cases and construct an accident scenario by using naval training materials, adjudication of naval warship accidents and US navy destroyer accident reports. Based on the surveyed data, the status of accidents was identified and cases were analyzed. We reproduced 17 accident cases in accordance with accident reproduction procedure and constructed naval warship accident scenarios. As a result of analyzing the CPA, TCPA and PARK model for risk, reproducing 17 naval ship accident cases, collision risk increased on average 5-6 minutes before an accident. The result of this study represents basic data for naval and simulation education materials, contributing to the prevention of marine accidents.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.83-91
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• 2019

These days, virtually every mobile game has a daily quest system. Daily quest is a great tool that can attract game players by providing daily rewards as the player conducts designated missions. However, conducting similar tasks repeatedly has a risk of becoming tedious duties, and maintaining an enjoyable daily quest is critical in enhancing the overall experience of a game. Based on the awareness on the need for academic research on daily quest systems, this study categorized the types of quests systems implemented in the current mobile games, observed how preferred type differs by player's propensity, and analyzed how motivation of a player can be improved using quest types. The results are (1) the staged rewards after each clearance of a task improve a player's motivation, (2) players with high autonomy should be given a freedom to choose their own quests, and (3) players who values their playing skills higher are motivated by providing a feedback on the completion of a task.

• Journal of the HCI Society of Korea
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• v.14 no.1
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• pp.35-43
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• 2019

This study examines how interactivity and usage mode of a chatbot interface affects user experience. Chatbot has rapidly been commercialized in accordance with improvements in artificial intelligence and natural language processing. However, most of the researches have focused on the technical aspect to improve the performance of chatbots, and it is necessary to study user experience on a chatbot interface. In this article, we investigated how 'interactivity' of an interface and the 'usage mode' referring to situations of a user affect the satisfaction, flow, and perceived usefulness of a chatbot for exploring user experience. As the result, first, the higher level of interactivity, the higher user experience. Second, usage mode showed interaction effect with interactivity on flow, although it didn't show the main effect. In specific, when interactivity is high in usage mode, flow was the highest rather than other conditions. Thus, for designing better chatbot interfaces, it should be considered to increase the degree of interactivity, and for users to achieve a goal easily through various functions with high interactivity.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.3
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• pp.177-190
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• 2019

The purpose of this study was to analyze the effects of sewerage facilities through I/I analysis by rainfall by selecting areas where storm overflow diverging chamber is remained due to the non-maintenance drainage equipment when the sewerage system was reconstructed as a separate sewer system. Research has shown that wet weather flow(WWF) increased from 106.2% to 154.8% compared to dry weather flow(DWF) in intercepting sewers, and that the WWF increased from 122.4% to 257.6% in comparison to DWF in storm overflow diverging chamber. As a result, owing to storm overflow diverging chamber of partially separate sewer system with untreated tributary of sewage treatment plant, rainfall-derived infiltration/inflow(RDII) has been analyzed 2.7 times higher than the areas without storm overflow diverging chamber. Meanwhile, infiltration quantity of this study area was relatively higher than that of other study areas. Therefore, it is necessary to reduce infiltration quantity through sewer pipe maintenance nearby river. Drainage equipment maintenance should be performed not to operate storm overflow diverging chamber in order to handle the appropriate sewage treatment plant capacity for rainfall because it is also expected that RDII due to rain will occur after maintenance. In conclusion, it is necessary to recognize aRDII(allowance of rainfall-derived infiltration/inflow) and to be reflected it on sewage treatment plant capacity because aRDII can occur even after maintenance to the complete separate sewer system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.171-178
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• 2019

Korea's shipbuilding industry is in a critical condition due to changes in the domestic and international environment. To overcome this crisis, preemptive development of products and technologies through prediction of new demand for ships is necessary. The goal of this research is to develop an artificial intelligence algorithm based on ship big data in order to predict new demand for ships. We intend to develop a big data analytics platform specialized in predicting ship demand and to utilize the forecast results of new ship demand through data analysis for planning/development of new products. By doing so, the development of sustainable new business models for equipment and equipment manufacturers will create new growth engines for shipyard and shipbuilders. Furthermore, it is expected that shipbuilders will be able to create business cases based on measurable performance, plan market-oriented products and services, and continuously achieve innovation that has high market destructive power.