Economic Consequences Of IFRS Adoption In Korea: A Literature Review

We provide a comprehensive review of academic research on the economic consequences of International Financial Reporting Standards (IFRS) adoption in Korea. We review 18 empirical studies on the economic consequences of IFRS adoption in Korea and classify them into six areas: (a) earnings quality, (b) comparability of financial statements, (c) value relevance, (d) analysts’ behavior, (e) information asymmetry, and (f) cost of capital and firm value. Our review suggests that IFRS adoption in Korea has generally afforded positive economic consequences. The limitations of the existing studies are discussed and various directions for future research are suggested

Evaluation of Protective Efficacy of Respiratory Syncytial Virus Vaccine against A and B Subgroup Human Isolates in Korea

Human respiratory syncytial virus (HRSV) is a significant cause of upper and lower respiratory tract illness mainly in infants and young children worldwide. HRSV is divided into two subgroups, HRSV-A and HRSV-B, based on sequence variation within the G gene. Despite its importance as a respiratory pathogen, there is currently no safe and effective vaccine for HRSV. In this study, we have detected and identified the HRSV by RT-PCR from nasopharyngeal aspirates of Korean pediatric patients. Interestingly, all HRSV-B isolates exhibited unique deletion of 6 nucleotides and duplication of 60 nucleotides in the G gene. We successfully amplified two isolates (‘KR/A/09-8’ belonging to HRSV-A and ‘KR/B/10-12’ to HRSV-B) on large-scale, and evaluated the cross-protective efficacy of our recombinant adenovirus-based HRSV vaccine candidate, rAd/3xG, by challenging the immunized mice with these isolates. The single intranasal immunization with rAd/3xG protected the mice completely from KR/A/09-8 infection and partially from KR/B/10-12 infection. Our study contributes to the understanding of the genetic characteristics and distribution of subgroups in the seasonal HRSV epidemics in Korea and, for the first time, to the evaluation of the cross-protective efficacy of RSV vaccine against HRSV-A and -B field-isolates

Effect of shared decision-making education on physicians’ perceptions and practices of end-of-life care in Korea

Background Evidence of the ethical appropriateness and clinical benefits of shared decision-making (SDM) are accumulating. This study aimed to not only identify physicians’ perspectives on SDM, and practices related to end-of-life care in particular, but also to gauge the effect of SDM education on physicians in Korea. Methods A 14-item questionnaire survey using a modified Delphi process was delivered to nephrologists and internal medicine trainees at 17 university hospitals. Results A total of 309 physicians completed the survey. Although respondents reported that 69.9% of their practical decisions were made using SDM, 59.9% reported that it is not being applied appropriately. Only 12.3% of respondents had received education on SDM as part of their training. The main obstacles to appropriate SDM were identified as lack of time (46.0%), educational materials and tools (29.4%), and education on SDM (24.3%). Although only a few respondents had received training on SDM, the proportion of those who thought they were using SDM appropriately in actual practice was high; the proportion of those who chose lack of time and education as factors that hindered the proper application of SDM was low. Conclusion The majority of respondents believed that SDM was not being implemented properly in Korea, despite its use in actual practice. To improve the effectiveness of SDM in the Korean medical system, appropriate training programs and supplemental policies that guarantee sufficient application time are required

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Calibration of time synchronization error in GPS/SDINS hybrid navigation

In this study, we analyzed the effect of a constant transmission delay that occurs in delivering measurements from a global positioning system receiver to a Kalman filter for an aided strapdown inertial navigation system and propose an efficient delay calibration algorithm. A new error model for the circular trajectories is derived to show that all the currently computed navigation variables converge not to the current true variables but to the neighborhood of the past true variables at the instant the delayed measurements were actually sampled. In order to eliminate the undesirable delay effects given various combinations of receivers and strapdown inertial measurement units, a simple delay calibration algorithm is proposed. The proposed algorithm is enabled by the vehicle's controlled maneuver, and advantageously requires no modification in onboard hardware. Keywords: GPS, SDINS, Calibration, Delay, Error model. 1

The Stability Analysis of the Adaptive Fading Extended Kalman Filter Using the Innovation Covariance

The well-known conventional Kalman filter gives the optimal solution but to do so, it requires an accurate system model and exact stochastic information. However, in a number of practical situations, the system model and the stochastic information are incomplete. The Kalman filter with incomplete information may be degraded or even diverged. To solve this problem, a new adaptive fading filter using a forgetting factor has recently been proposed by Kim and co-authors. This paper analyzes the stability of the adaptive fading extended Kalman filter (AFEKF), which is a nonlinear filter form of the adaptive fading filter. The stability analysis of the AFEKF is based on the analysis result of Reif and co-authors for the EKF. From the analysis results, this paper shows the upper bounded condition of the error covariance for the filter stability and the bounded value of the estimation error

The Stability Analysis of the Adaptive Fading Extended Kalman Filter

The well-known conventional Kalman filter gives the optimal solution but requires an accurate system model and exact stochastic information. Thus, the Kalman filter with incomplete information may be degraded or even diverged. In a number of practical situations, the system model and the stochastic information are incomplete. To solve this problem, a new adaptive fading Kalman filter (AFKF) using the forgetting factor has recently been proposed. This paper extends the AFKF to nonlinear system models to obtain an adaptive fading extended Kalman filter (AFEKF). The forgetting factor is generated from the ratio between the calculated innovation covariance and the estimated innovation covariance. Based on the analysis result of Reif for the EKF, the stability of the AFEKF is also analyzed.GNSS Receiver Technology BK21 Team in Konkuk Universit