Chung Yuan Christian University

About: Chung Yuan Christian University is a education organization based out in Taoyuan City, Taiwan. It is known for research contribution in the topics: Membrane & Fuzzy logic. The organization has 9819 authors who have published 11623 publications receiving 213139 citations. The organization is also known as: Tiong-gôan-tāi-ha̍k & CYCU.

Functionalized Fe3O4@Silica Core–Shell Nanoparticles as Microalgae Harvester and Catalyst for Biodiesel Production

Abstract: Core-shell Fe3O4@silica magnetic nanoparticles functionalized with a strong base, triazabicyclodecene (TBD), were successfully synthesized for harvesting microalgae and for one-pot microalgae-to-fatty acid methyl ester (FAME, or so-called biodiesel) conversion. Three types of algae oil sources (i.e., dried algae, algae oil, and algae concentrate) were used and the reaction conditions were optimized to achieve the maximum biodiesel yield. The results obtained in this study show that our TBD-functionalized Fe3O4@silica nanoparticles could effectively convert algae oil to biodiesel with a maximum yield of 97.1%. Additionally, TBD-Fe3O4@silica nanoparticles act as an efficient algae harvester because of their adsorption and magnetic properties. The method presented in this study demonstrates the wide scope for the use of covalently functionalized core-shell nanoparticles for the production of liquid transportation fuels from algal biomass.

Multiscenario Underfrequency Load Shedding in a Microgrid Consisting of Intermittent Renewables

Abstract: Underfrequency load shedding maintains the power system in a stable condition when a severe disturbance occurs. The underfrequency relay protects the power system against a blackout when the system frequency declines to predetermined settings. This paper determines the shed load at each stage for the underfrequency relay (81L) in a stand-alone microgrid considering multiple scenarios. In addition, the probabilities of all scenarios are defined based on historical meteorological data and the Markov two-state model. The shed load is minimized and the lowest swing frequency is maximized using the genetic algorithms. Due to many inequality constraints in the studied problem, an efficient tree-encoding chromosome and the penalty functions are presented as well. Moreover, applicability of the proposed method is demonstrated using a microgrid test bed with the gas-turbine, wind-turbine generator, and solar photovoltaic.

A Lossless Compression Method for Medical Image Sequences Using JPEG-LS and Interframe Coding

Abstract: Hospitals and medical centers produce an enormous amount of digital medical images every day, especially in the form of image sequences, which requires considerable storage space. One solution could be the application of lossless compression. Among available methods, JPEG-LS has excellent coding performance. However, it only compresses a single picture with intracoding and does not utilize the interframe correlation among pictures. Therefore, this paper proposes a method that combines the JPEG-LS and an interframe coding with motion vectors to enhance the compression performance of using JPEG-LS alone. Since the interframe correlation between two adjacent images in a medical image sequence is usually not as high as that in a general video image sequence, the interframe coding is activated only when the interframe correlation is high enough. With six capsule endoscope image sequences under test, the proposed method achieves average compression gains of 13.3% and 26.3 % over the methods of using JPEG-LS and JPEG2000 alone, respectively. Similarly, for an MRI image sequence, coding gains of 77.5% and 86.5% are correspondingly obtained.