A Study on GPS Data Tracking Method for KOMPSAT Spacecraft Orbit Control

The Global Positioning System (GPS) is becoming more attractive navigation means for LEO spacecraft due to the data accuracy and convenience for utilization. The anomalies such as serious variations of Dilution-Of-Precision (DOP), loss of infrequent 3-dimensional position fix, and deterioration of instantaneous accuracy of position and velocity data could be observed, which have not been appeared during the ground testing. It may cause lots of difficulty for the processing of the orbit control algorithm using the GPS data. In this paper, the characteristics of the GPS data were analyzed according to the configuration of GPS receiver such as position fix algorithm and mask angle using GPS navigation data obtained from the first Korea Multi-Purpose Satellite (KOMPSAT). The problem in orbit tracking using GPS data, including the infrequent deterioration of the accuracy, and an efficient algorithm for its countermeasures has also been introduced. The reliability and efficiency of the modified algorithm were verified by analyzing the effect of the results between algorithm simulation using KOMPSAT flight data and ground simulator

Transcriptome Atlas by Long-Read RNA Sequencing: Contribution to a Reference Transcriptome

The recent emergence of long-read transcriptome sequencing has helped improve the overall accuracy of gene prediction compared with that by short-read RNA-Seq. In addition, the technology can offer a more comprehensive view of functional genomics in uncharacterized species with an efficient full-length unigene build and high-precision gene annotation, thus being efficient in developing transcriptome data resources from useful genetic pools. Hence, I will review the applications of long-read RNA isoform sequencing, including the relative merits of the technology, the improvement of the accuracy in gene prediction and gene annotation, and the full-length unigene builds in a new genome; the limitations of the technology will be also discussed. The review will be valuable in collecting data resources for functional genomic studies

Excess cost of non-remission among outpatients with major depressive disorder

Background: The purpose of this study was to assess the economic benefit of achieving remission among outpatients with major depressive disorder (MDD) who are currently employed in Korea. Methods: Cross-sectional observational study. A total of 337 outpatients with MDD with paid jobs were recruited from 14 psychiatric clinics in Korea and were then divided into three groups as follows: new visit group (n = 128), remitted group (n = 100) and non-remitted group (n = 109). The 17-item Hamilton Depression Rating Scale (HAM-D) was used to decide whether a patient should be assigned to the remitted or non-remitted group. Direct medical and non-medical costs were measured via interview with the subjects. The World Health Organization Health and Work Performance Questionnaire (HPQ) were applied in order to measure the lost productive time (LPT) and related productivity costs. Results: The three groups did not show a significant difference in direct medical cost. However, the difference between the remitted group and non-remitted group was statistically significant (25.49 ± 52.99 vs. 44.79 ± 126.55, χ2 = 12.99, p = 0.0015). The remitted group demonstrated a significant improvement in productivity (particularly presenteeism) when compared with the new visit group (Z = −3.29, p = 0.001). Although the non-remitted group received treatment at psychiatric clinics similar to the remitted group, it lost 33 more working hours per month, which is compatible to $332 per month. Conclusion: These results suggest the economic importance of achieving remission in treating depression

Localized Dielectric Loss Heating in Dielectrophoresis Devices

Temperature increases during dielectrophoresis (DEP) can affect the response of biological entities, and ignoring the effect can result in misleading analysis. The heating mechanism of a DEP device is typically considered to be the result of Joule heating and is overlooked without an appropriate analysis. Our experiment and analysis indicate that the heating mechanism is due to the dielectric loss (Debye relaxation). A temperature increase between interdigitated electrodes (IDEs) has been measured with an integrated micro temperature sensor between IDEs to be as high as 70 °C at 1.5 MHz with a 30 Vpp applied voltage to our ultra-low thermal mass DEP device. Analytical and numerical analysis of the power dissipation due to the dielectric loss are in good agreement with the experiment data

Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

We propose a symmetric graph convolutional autoencoder which produces a low-dimensional latent representation from a graph. In contrast to the existing graph autoencoders with asymmetric decoder parts, the proposed autoencoder has a newly designed decoder which builds a completely symmetric autoencoder form. For the reconstruction of node features, the decoder is designed based on Laplacian sharpening as the counterpart of Laplacian smoothing of the encoder, which allows utilizing the graph structure in the whole processes of the proposed autoencoder architecture. In order to prevent the numerical instability of the network caused by the Laplacian sharpening introduction, we further propose a new numerically stable form of the Laplacian sharpening by incorporating the signed graphs. In addition, a new cost function which finds a latent representation and a latent affinity matrix simultaneously is devised to boost the performance of image clustering tasks. The experimental results on clustering, link prediction and visualization tasks strongly support that the proposed model is stable and outperforms various state-of-the-art algorithms.Comment: 10 pages, 3 figures, ICCV 2019 accepte