• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.2
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• pp.122-128
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• 2010

To meet the NOx limit without a penalty of fuel consumption, urea-SCR system is currently regarded as promising NOx reduction technology for diesel engines. SCR system has to achieve maximal NOx conversion in combination with minimal $NH_3$ slip. In this study, the performance characteristics of urea-SCR system with open loop control were assessed in the European Transient Cycle(ETC) for heavy duty diesel engine. The SCR inlet temperaure varied in the range of 200 to $340^{\circ}C$ in the ETC cycle. Open loop control calculated the urea flow rate based on the NOx and NSR map which gave for each combination of SCR inlet temperature and space velocity the normalized $NH_3$ to NOx stoichiometric ratio which resulted in a steady-state $NH_3$ slip of 20ppm. During the ETC cycle, the open loop control with the optimized NSR offset achieved NOx reduction of 80% while keeping the average $NH_3$ slip below 10ppm and maximum 20ppm. It was also found that NOx sensor was cross-sensitive to $NH_3$ and a control strategy for cross-sensitivity compensation was required in order to use a NOx sensor as feedback device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1881-1900
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• 2014

Since 802.11 wireless LANs are so widely used, it has become common for numerous access points (APs) to overlap in a region, where most of those APs are managed individually without any coordinated control. This pattern of wireless LAN usage is called the private OBSS (Overlapping Basic Service Set) environment in this paper. Due to frame collisions across BSSs, each BSS in the private OBSS environment suffers severe performance degradation. This study approaches the problem from the perspective of congestion control rather than noise or collision resolution. The retry limit, one of the 802.11 attributes, could be used for traffic control in conjunction with TCP. Reducing the retry limit causes early discard of a frame, and it has a similar effect of random early drops at a router, well known in the research area of congestion control. It makes the shared link less crowded with frames, and then the benefit of fewer collisions surpasses the penalty of less strict error recovery. As a result, the network-wide performance improves and so does the performance of each BSS eventually. Reducing the retry limit also has positive effects of merging TCP ACKs and reducing HOL-like blocking time at the AP. Extensive experiments have validated the idea that in the OBSS environment, reducing the retry limit provides better performance, which is contrary to the common wisdom. Since our strategy is basically to sacrifice error recovery for congestion control, it could yield side-effects in an environment where the cost of error recovery is high. Therefore, to be useful in general network and traffic environments, adaptability is required. To prove the feasibility of the adaptive scheme, a simple method to dynamically adjust the value of the retry limit has been proposed. Experiments have shown that this approach could provide comparable performance in unfriendly environments.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.