42 research outputs found
Implementation of Accelerometer Sensor Module and Fall Detection Monitoring System based on Wireless Sensor Network
Performance evaluation of a motor-imagery-based EEG-Brain computer interface using a combined cue with heterogeneous training data in BCI-Naive subjects
Development of Formation Flying CubeSats and Operation Systems for the CANYVAL-C Mission: Launch and Lessons Learned
The CubeSat Astronomy NASA and Yonsei using Virtual telescope ALignment for Coronagraph (CANYVAL-C) is a technology demonstration mission that shows the concept of a virtual space telescope using two CubeSats in formation flying. The final goal of the mission is to obtain several images of the solar corona during an artificial solar eclipse created by the two CubeSats, Timon (1U CubeSat) and Pumbaa (2U CubeSat). To implement this mission, two CubeSats in formation flying and a ground segment have been developed. The CubeSats were constructed mainly with commercial off the shelf components, sharing the bus architecture. The payload of each CubeSat is a visible camera and an occulter to block the light from the photosphere of the Sun. The occulter is composed of tape measures and a black-colored polyimide film; the system size is smaller than 0.5U (10 Ă 10 Ă 5 cm3) while it stowed and enlarged to 0.75 Ă 0.75 m2 after spreading the film. The 3D-printed propulsion system is smaller than 0.5U and facilitates accurate positioning maneuvers of Pumbaa. The on-board computer has multi-task processing capabilities and a space-saving configuration which is integrated with the GNSS receiver and the UHF transceiver. The core technology for the mission implementation is the precise formation flying guidance, navigation, and control system with a cold-gas propulsion system and an inter-satellite link system. The specification of each CubeSat system was evaluated using numerical simulations and ground testing. To operate CubeSats, the ground segment was constructed with some components, including the UHF ground station (UGS), flight dynamics system (FDS), mission analysis and planning system (MAPS), and spacecraft operation system (SOS). Each component works under the environment of an integrated graphic user interface. In particular, the UGS handles the RF communication, data storage, and instrument control for tracking CubeSats. The FDS processes the navigation data to precisely estimate absolute position and velocity. Then, the MAPS determines the allowable mission schedule and parameter set for implementing maneuvers of each CubeSat. Using the MAPS, feasibility of the mission operation canbe ensured through numerical simulations based on the solutions from the FDS. Finally, the SOS is the interface system between each component, processing telemetry and generating telecommand. The CubeSats were launched on March 22, 2021, by Soyuz-2.1a with a Fregat stage
Bioinformatics services for analyzing massive genomic datasets
The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating down-stream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/. ?? 2020, Korea Genome Organization
Coupling between flexible ship and liquid sloshing using potential flow analysis
The significant increase in demand for Liquefied Natural Gas (LNG) and the economic aspects of its transportation resulted in increases in the number and size of LNG carriers. One of the design issues for LNG carriers is the sloshing phenomenon because containment systems widely used nowadays have no internal structures. Furthermore, because the weights of ship and cargo are comparable and ship operators want more flexible operations allowing partial fillings in tanks, the coupling effect between ship motions and sloshing requires further investigation, including the effect of ship distortion.The previous study on coupling between rigid body and sloshing shows good agreement between methods of prediction and measurements[1,2]. Hence, in this paper the potential flow approach adopted for the coupling effect between rigid body ship motion and sloshing is extended to flexible ship-partially filled tank system, using the de-singularised Rankine source method. In this case, the global deflection of the flexible ship is used for application of the body boundary condition on the partially filled tank. The aim of this paper is to investigate the influence of hull flexibility on the hydrodynamic forces and moments associated with liquid sloshing and vice versa, as well as the dynamic characteristics (e.g. resonance frequencies) of the whole system. As there are no experimental results available, the method is validated by comparing hydrodynamic forces from sloshing obtained using rigid and flexible body approaches. The coupling effect between flexible ship and sloshing in partially filled tanks is investigated for an idealized LNG Carrier in beam regular waves, considering different partial filling scenarios
Coupling between flexible ship and liquid sloshing using potential flow analysis
EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Effect of Heat Treatments on the Properties of Two Long-grain Rice Cultivars During Storage
During storage, the milling and physicochemical properties and eating quality of rice change, which is generally termed `aging\u27. Aged rice is preferred by processors, and there are attempts to develop accelerated aging process using various heat sources. In this study, the effects of various heat treatments and their influence on the milling, pasting, thermal, and cooking properties of two long-grain rice cultivars during storage were investigated using a full-factorial experimental design. Two long-grain rice cultivars, Wells and XP723, was treated with 8 different heat treatments including one control and stored at room temperature for 180 days. Heat treatments included 2 levels of UV irradiation, 2 levels of autoclaving and 3 levels of convection oven. The heat treatments significantly influenced head rice yield and thermal properties. The surface lipid content and cooked rice hardness and stickiness were impacted by cultivars, heat treatments and storage with different extent showing 3-way interactions. Severe autoclaving resulted in different protein composition from the other treatments. Peak pasting viscosity significantly increased at the first 3 months and gradually leveled off regardless of cultivar and heat treatments. Leached solid contents were decreased gradually during storage. Autoclaving (especially severe autoclaving) samples showed more distinct characteristics on HRY, leached solids and cooking properties. Although different heat treatments had different impacts on their properties, the results show that the various heat treatments employed in this
study slightly accelerated rice aging by stabilizing rice properties during storage
Classification of BMI control commands from rat's neural signals using extreme learning machine
<p>Abstract</p> <p>A recently developed machine learning algorithm referred to as Extreme Learning Machine (ELM) was used to classify machine control commands out of time series of spike trains of ensembles of CA1 hippocampus neurons (n = 34) of a rat, which was performing a target-to-goal task on a two-dimensional space through a brain-machine interface system. Performance of ELM was analyzed in terms of training time and classification accuracy. The results showed that some processes such as class code prefix, redundancy code suffix and smoothing effect of the classifiers' outputs could improve the accuracy of classification of robot control commands for a brain-machine interface system.</p