Inflation Targeting in an Emerging Market: the Case of Korea

To evaluate the effectiveness of targeting monetary policy strategies in a small open economy, we develop a dynamic optimizing model calibrated to recent Korean data. We then explore the consequences of alternative specifications of the loss function for society and the central bank, with particular focus on exchange rate volatility. Policy simulations include variations on inflation targeting, nominal income growth targeting and exchange rate targeting. Our results indicate that inflation targeting remains the most preferred policy regime, even when an explicit motive for exchange rate smoothing is introduced. In this case, the optimal inflation targeting and nominal income growth targeting policies are characterized by a “conservative” central bank that places greater weight on both the primary target variable and on the exchange rate than in society’s objective function. However, the optimal policy reacts to changes in degree of exchange rate pass-though in a non-linear fashion, complicating the robustness of inflation targeting recommendations for emerging markets.Korean economy, inflation targeting, optimal monetary policy, small open economy

The Performance of Targeting Monetary Policies in a Small Open Economy

This paper examines the performance of targeting monetary policies in a dynamic optimizing model. Towards this end I develop a small open economy version of the New Keynesian model and calibrate it to the recent Korean data. By modeling the central bank as an optimizing agent with explicit weights on different components of the objective function, I explore the consequences of alternative specifications of the central bank's objectives. Policy simulations include variations on inflation targeting, nominal income growth targeting and exchange rate targeting. Simulation results suggest that inflation targeting is preferable to nominal income growth and exchange rate pegging in smoothing out fluctuations in inflation and the output-gap

A globally exponentially stable position observer for interior permanent magnet synchronous motors

The design of a position observer for the interior permanent magnet synchronous motor is a challenging problem that, in spite of many research efforts, remained open for a long time. In this paper we present the first globally exponentially convergent solution to it, assuming that the saliency is not too large. As expected in all observer tasks, a persistency of excitation condition is imposed. Conditions on the operation of the motor, under which it is verified, are given. In particular, it is shown that at rotor standstill---when the system is not observable---it is possible to inject a probing signal to enforce the persistent excitation condition. {The high performance of the proposed observer, in standstill and high speed regions, is verified by extensive series of test-runs on an experimental setup

Sensorless Control of Surface-Mount Permanent-Magnet Synchronous Motors Based on a Nonlinear Observer

International audienceA nonlinear observer for surface-mount permanent-magnet synchronous motors (SPMSMs) was recently proposed by Ortega et al.(LSS, Gif-sur-Yvette Cedex, France, LSS Internal Rep., Jan. 2009). The nonlinear observer generates the position estimate hat(theta) via the estimates of sin theta and cos theta. In contrast to Luenberger-type observers, it does not require speed information, thus eliminating the complexity associated with speed estimation errors. Further, it is simple to implement. In this study, the nonlinear observer performance is verified experimentally. To obtain speed estimates from the position information, a proportional-integral (PI) tracking controller speed estimator was utilized. The results are good with and without loads, above 10 r/min

DiffFace: Diffusion-based Face Swapping with Facial Guidance

In this paper, we propose a diffusion-based face swapping framework for the first time, called DiffFace, composed of training ID conditional DDPM, sampling with facial guidance, and a target-preserving blending. In specific, in the training process, the ID conditional DDPM is trained to generate face images with the desired identity. In the sampling process, we use the off-the-shelf facial expert models to make the model transfer source identity while preserving target attributes faithfully. During this process, to preserve the background of the target image and obtain the desired face swapping result, we additionally propose a target-preserving blending strategy. It helps our model to keep the attributes of the target face from noise while transferring the source facial identity. In addition, without any re-training, our model can flexibly apply additional facial guidance and adaptively control the ID-attributes trade-off to achieve the desired results. To the best of our knowledge, this is the first approach that applies the diffusion model in face swapping task. Compared with previous GAN-based approaches, by taking advantage of the diffusion model for the face swapping task, DiffFace achieves better benefits such as training stability, high fidelity, diversity of the samples, and controllability. Extensive experiments show that our DiffFace is comparable or superior to the state-of-the-art methods on several standard face swapping benchmarks.Comment: Project Page: https://hxngiee.github.io/DiffFac

Anti-inflammatory function of arctiin by inhibiting COX-2 expression via NF-κB pathways

<p>Abstract</p> <p>Background</p> <p>Arctiin, isolated from <it>Forsythia suspensa </it>has been reported to have anti-inflammatory, anti-oxidant, antibacterial, and antiviral effects <it>in vitro</it>. However, there has been a lack of studies regarding its effects on immunological activity. The aim of this study is to investigate the anti-inflammatory potential and possible mechanisms of arctiin in LPS-induced macrophages.</p> <p>Methods</p> <p>We investigated the mRNA and protein levels of proinflammatory cytokines through RT-PCR and western blot analysis, followed by a FACS analysis for surface molecule changes.</p> <p>Results</p> <p>Arctiin dose dependently decreased the production of NO and proinflammatory cytokines such as IL-1β, IL-6, TNF-α, and PGE₂, and it reduced the gene and protein levels as determined by RT-PCR and western blot analysis, respectively. The expression of co-stimulatory molecules such as B7-1 and B7-2 were also inhibited by arctiin. Furthermore, the activation of the nuclear transcription factor, NF-κB in macrophages was inhibited by arctiin.</p> <p>Conclusion</p> <p>Taken together these results provide evidence of the bioactivity of arctiin in inflammatory diseases and suggest that arctiin may exert anti-inflammatory effect by inhibiting the pro-inflammatory mediators through the inactivation of NF-kB.</p

Human Capital Formation and Saving-Investment Dynamics

This paper explores the dynamics of saving, investment and the trade balance in a two-country version of human capital growth model. As observed in the post-war G7 data, the model economy generates a high saving-investment correlation, together with a countercyclical trade balance. The persistent movement of investment, sustained by the accumulation of human capital, turns out to play a key role in producing the realistic cyclical properties of the model economy

Online Overshoot Suppression Method for EV Propulsion Motor Considering Cross-Coupled Inductance

The effects of cross-coupled inductance are significant in high power density motors. It is observed here that the cross-coupled inductance causes current and voltage overshoots in the high-speed region. As the required voltage exceeds the voltage limit, the system becomes unstable. Here, the current dynamics are analyzed with a reduced model that incorporates a cross-coupled inductance, L-qd. Further, it is shown that L-qd makes an uncanceled zero in the current transfer function, which invokes the overshoot. It can be compensated with an estimate (L) over cap (qd). However, it is not easy to obtain correct estimates of L-qd in a wide current range. In this paper, an online overshoot suppression algorithm is proposed by using a high-pass filter. The simulation and experimental results provide some evidence for the effectiveness of the proposed algorithm. Finally, it is shown experimentally that the proposed algorithm cured the vehicle hunting problem after tapping off the gas pedal in a high-speed operation.11Nsciescopu