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Who Beats Plowshares into Swords? Determinants of Commitment to Ceasefire Agreements
Junghyun Lim,Geunwook Lee 한국국제정치학회 2015 The Korean Journal of International Studies Vol.13 No.3
Although ceasefire agreements end wars, they are not left unthreatened. A number of ceasefire agreements have been threatened or violated in various ways. A ceasefire agreement collapses when at least one adversary fails to comply with the agreement it previously accepted and resumes military conflict against its old enemy. Why do some states break ceasefire agreements while others carry them out? Under what conditions are states less likely to commit to ceasefire agreements? Previous studies on the commitment problem identify regime type, relative capability, and power shift as important variables that affect the ability of states to commit to agreements. Accordingly, this paper examines whether those variables have a significant effect on states` commitment to ceasefire agreement. To test the effects of those variables, I build a data set using MIDB, COW, NMC, and Polity IV data. To test the effects of those variables, a dataset was constructed using MIDB, COW NMC, and Polity IV data. A key finding of this paper is that democracies are no more likely to commit to agreements than democracies, while relative power and power shifts have statistically significant effects on commitment to agreements. This paper suggests that democratic advantage on commitment does not exist, at least with regard to ceasefire agreements.
울산광역시 아황산가스(SO<sub>2</sub>)의 최적관측소 평가방법
임정현 ( Junghyun Lim ),윤상후 ( Sanghoo Yoon ) 한국환경과학회 2017 한국환경과학회지 Vol.26 No.9
Manufacturing and technology industries produce large amounts of air pollutants. Ulsan Metropolitan City, South Korea, is well-known for its large industrial complexes; in particular, the concentration of SO<sub>2</sub> here is the highest in the country. We assessed SO<sub>2</sub> monitoring sites based on conditional and joint entropy, because this is a common method for determining an optimal air monitoring network. Monthly SO<sub>2</sub> concentrations from 12 air monitoring sites were collected, and the distribution of spatial locations was determined by kriging. Mean absolute error, Root Mean Squared Error (RMSE), bias and correlation coefficients were employed to evaluate the considered algorithms. An optimal air monitoring network for Ulsan was suggested based on the improvement of RMSE.