Experimental Evaluation and Prediction Algorithm Suggestion for Determining SOC of Lithium Polymer Battery in a Parallel Hybrid Electric Vehicle

The necessity of hybrid vehicles and electric vehicles is widely known for reasons such as fossil fuel depletion, climate change, emission norms mandated by regulations, and so on. Expansion of the hybrid vehicle market is a realistic way to respond to fuel efficiency regulations. Hybrid electric vehicles are continuously challenged to meet cross-attribute performance while minimizing energy usage and component cost in a highly competitive automotive market. Current optimization strategy for a parallel hybrid requires much computational time and relies heavily on the drive cycle to accurately represent driving conditions in the future. With increasing application of the lithium-ion battery technology in the automotive industry, development processes and validation methods for the battery management system (BMS) have attracted attention. The purpose of this study is to propose an algorithm to analyze charging characteristics and improve accuracy for determining state of charge (SOC), the equivalent of a fuel gauge for the battery pack, during the regenerative braking period of a TMED type parallel hybrid electric vehicle

Stroscope: Multi-Scale Visualization of Irregularly Measured Time-Series Data

For irregularly measured time-series data, the measurement frequency or interval is as crucial information as measurements are. A well-known time-series visualization such as the line graph is good at showing an overall temporal pattern of change; however, it is not so effective in revealing the measurement frequency/interval while likely giving illusory confidence in values between measurements. In contrast, the bar graph is more effective in showing the frequency/interval, but less effective in showing an overall pattern than the line graph. We integrate the line graph and bar graph in a unified visualization model, called a ripple graph, to take the benefits of both of them with enhanced graphical integrity. Based on the ripple graph, we implemented an interactive time-series data visualization tool, called Stroscope, which facilitates multi-scale visualizations by providing users with a graphical widget to interactively control the integrated visualization model. We evaluated the visualization model (i.e., the ripple graph) through a controlled user study and Stroscope through long-term case studies with neurologists exploring large blood pressure measurement data of stroke patients. Results from our evaluations demonstrate that the ripple graph outperforms existing time-series visualizations, and that Stroscope has the efficacy and potential as an effective visual analysis tool for (irregularly) measured time-series data.N

Design of LSM-tree-based Key-value SSDs with Bounded Tails

Key-value store based on a log-structured merge-tree (LSM-tree) is preferable to hash-based key-value store, because an LSM-tree can support a wider variety of operations and show better performance, especially for writes. However, LSM-tree is difficult to implement in the resource constrained environment of a key-value SSD (KV-SSD), and, consequently, KV-SSDs typically use hash-based schemes. We present PinK, a design and implementation of an LSM-tree-based KV-SSD, which compared to a hash-based KV-SSD, reduces 99th percentile tail latency by 73%, improves average read latency by 42%, and shows 37% higher throughput. The key idea in improving the performance of an LSM-tree in a resource constrained environment is to avoid the use of Bloom filters and instead, use a small amount of DRAM to keep/pin the top levels of the LSM-tree. We also find that PinK is able to provide a flexible design space for a wide range of KV workloads by leveraging the read-write tradeoff in LSM-trees. © 2021 Association for Computing Machinery.1

PinK: High-speed In-storage Key-value Store with Bounded Tails

Key-value store based on a log-structured merge-tree (LSM-tree) is preferable to hash-based KV store because an LSM-tree can support a wider variety of operations and show better performance, especially for writes. However, LSM-tree is difficult to implement in the resource constrained environment of a key-value SSD (KV-SSD) and consequently, KV-SSDs typically use hash-based schemes. We present PinK, a design and implementation of an LSM-tree-based KV-SSD, which compared to a hash-based KV-SSD, reduces 99th percentile tail latency by 73%, improves average read latency by 42% and shows 37% higher throughput. The key idea in improving the performance of an LSM-tree in a resource constrained environment is to avoid the use of Bloom filters and instead, use a small amount of DRAM to keep/pin the top levels of the LSM-tree. Copyright © Proc. of the 2020 USENIX Annual Technical Conference, ATC 2020. All rights reserved

Analysis of Wireless Power Transfer system design on active silicon interposer for low voltage applications in 3D-IC

In this study, a Wireless Power Transfer (WPT) system design on active silicon (Si) interposer for low voltage applications in 3D-IC is proposed. The proposed WPT system includes magnetically coupled coils, a full-bridge rectifier, and a voltage regulator. In order to validate the proposed system, we first design all of the system components. First, we design a three dimensional helix-type transmitter (Tx) coil with the size of 1.6 mm by 1.6 mm on PCB, and a spiral-type receiver (Rx) coil using 3 μm top metal CMOS process with the size of 1.5 mm by 1.5 mm on Si-interposer. Second, a CMOS full-bridge rectifier is designed on the active Si-interposer to convert the AC voltage received from the Tx coil to DC voltage, which will then be fed to the input of the voltage regulator. Third, we design a voltage regulator to deliver 1.5 V DC voltage supply to multiple low voltage devices in 3D-IC. Power transfer efficiency of the coil system, full-bridge rectifier including a filtering capacitor, and voltage regulator is calculated to be 55 %, 69.5 %, and 71 %, respectively from circuit simulations. The simulated whole system efficiency is found to be 27 %

Prophylactic Effects of Bee Venom Phospholipase A2 in Lipopolysaccharide-Induced Pregnancy Loss

Spontaneous abortion represents a common form of embryonic loss caused by early pregnancy failure. In the present study, we investigated the prophylactic effects of bee venom phospholipase A2 (bvPLA2), a regulatory T cell (Treg) inducer, on a lipopolysaccharide (LPS)-induced abortion mouse model. Fetal loss, including viable implants, the fetal resorption rate, and the fetal weight, were measured after LPS and bvPLA2 treatment. The levels of serum and tissue inflammatory cytokines were determined. To investigate the involvement of the Treg population in bvPLA2-mediated protection against fetal loss, the effect of Treg depletion was evaluated following bvPLA2 and LPS treatment. The results clearly revealed that bvPLA2 can prevent fetal loss accompanied by growth restriction in the remaining viable fetus. When the LPS-induced abortion mice were treated with bvPLA2, Treg cells were significantly increased compared with those in the non-pregnant, PBS, and LPS groups. After LPS injection, the levels of proinflammatory cytokines were markedly increased compared with those in the PBS mouse group, while bvPLA2 treatment showed significantly decreased TNF-α and IFN-γ expression compared with that in the LPS group. The protective effects of bvPLA2 treatment were not detected in Treg-depleted abortion-prone mice. These findings suggest that bvPLA2 has protective effects in the LPS-induced abortion mouse model by regulating Treg populations

Automated extraction of Biomarker information from pathology reports

Abstract Background Pathology reports are written in free-text form, which precludes efficient data gathering. We aimed to overcome this limitation and design an automated system for extracting biomarker profiles from accumulated pathology reports. Methods We designed a new data model for representing biomarker knowledge. The automated system parses immunohistochemistry reports based on a “slide paragraph” unit defined as a set of immunohistochemistry findings obtained for the same tissue slide. Pathology reports are parsed using context-free grammar for immunohistochemistry, and using a tree-like structure for surgical pathology. The performance of the approach was validated on manually annotated pathology reports of 100 randomly selected patients managed at Seoul National University Hospital. Results High F-scores were obtained for parsing biomarker name and corresponding test results (0.999 and 0.998, respectively) from the immunohistochemistry reports, compared to relatively poor performance for parsing surgical pathology findings. However, applying the proposed approach to our single-center dataset revealed information on 221 unique biomarkers, which represents a richer result than biomarker profiles obtained based on the published literature. Owing to the data representation model, the proposed approach can associate biomarker profiles extracted from an immunohistochemistry report with corresponding pathology findings listed in one or more surgical pathology reports. Term variations are resolved by normalization to corresponding preferred terms determined by expanded dictionary look-up and text similarity-based search. Conclusions Our proposed approach for biomarker data extraction addresses key limitations regarding data representation and can handle reports prepared in the clinical setting, which often contain incomplete sentences, typographical errors, and inconsistent formatting

Effect of rhubarb (Rheum spp.) root on in vitro and in vivo ruminal methane production and a bacterial community analysis based on 16S rRNA sequence

The objective of this study was to evaluate the anti-methanogenic effect of rhubarb (Rheum spp.) on in vitro and in vivo. Rhubarb root powder was tested at different concentrations (0, 0.33, 0.67, and 1.33 g/L) in vitro, and all incubations were carried out in triplicate two runs on separate days. Concentrations of 0.67 and 1.33 g/L rhubarb significantly (P < 0.05) reduced methane production and the acetate propionate ratio compared with those of the control, without adverse effects on total volatile fatty acids and total gas production. In the second in vivo trial, four Hanwoo (Korean native) steers (live body weight 556 ± 46 kg) with a ruminal cannula were housed individually in metabolic stalls and fed a basal diet twice daily in equal amounts at 0900 and 2100 hours. The before rhubarb treatment (before treatment) duration was 24 days for all steers; 14 days were used for diet adaptation and 10 days were used for gas samples collected 1, 2, and 3 hours after the morning feeding on days 3, 5, 7, and 9. We used three syringe needles passed through the ruminal cannula stopper at different time points. Thereafter, mesh bag containing 90g sliced rhubarb root was placed in the rumen of each steer for 14 days 4, 7, 10, 12, and 13. The results showed a significant (P < 0.05) decrease in methane concentration from the rhubarb-treated steers. Furthermore, 16s RNA sequencing after treatment showed an increase in the numbers of Prevotella and decreases in Ruminococcus and Methanobrevibacter. In conclusion, rhubarb had an anti-methanogenic effect in vitro and in vivo, and the increase in the number of Prevotella shifted ruminal fermentation toward propionate production.OAIID:RECH_ACHV_DSTSH_NO:A201619510RECH_ACHV_FG:RR00200003ADJUST_YN:EMP_ID:A079567CITE_RATE:FILENAME:GGAA-abstract(2016).PNGDEPT_NM:국제농업기술학과EMAIL:[email protected]_YN:FILEURL:https://srnd.snu.ac.kr/eXrepEIR/fws/file/58590475-3aa4-4645-8899-8d345fab8b7a/linkCONFIRM:

Legislative Documents

Also, variously referred to as: House bills; House documents; House legislative documents; legislative documents; General Court documents