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핫스팟 접근영역 인식에 기반한 바이너리 코드 역전 기법을 사용한 저전력 IoT MCU 코드 메모리 인터페이스 구조 연구
박대진,Park, Daejin 대한임베디드공학회 2016 대한임베디드공학회논문지 Vol.11 No.2
Microcontrollers (MCUs) for endpoint smart sensor devices of internet-of-thing (IoT) are being implemented as system-on-chip (SoC) with on-chip instruction flash memory, in which user firmware is embedded. MCUs directly fetch binary code-based instructions through bit-line sense amplifier (S/A) integrated with on-chip flash memory. The S/A compares bit cell current with reference current to identify which data are programmed. The S/A in reading '0' (erased) cell data consumes a large sink current, which is greater than off-current for '1' (programmed) cell data. The main motivation of our approach is to reduce the number of accesses of erased cells by binary code level transformation. This paper proposes a built-in write/read path architecture using binary code inversion method based on hot-spot region detection of instruction code access to reduce sensing current in S/A. From the profiling result of instruction access patterns, hot-spot region of an original compiled binary code is conditionally inverted with the proposed bit-inversion techniques. The de-inversion hardware only consumes small logic current instead of analog sink current in S/A and it is integrated with the conventional S/A to restore original binary instructions. The proposed techniques are applied to the fully-custom designed MCU with ARM Cortex-M0$^{TM}$ using 0.18um Magnachip Flash-embedded CMOS process and the benefits in terms of power consumption reduction are evaluated for Dhrystone$^{TM}$ benchmark. The profiling environment of instruction code executions is implemented by extending commercial ARM KEIL$^{TM}$ MDK (MCU Development Kit) with our custom-designed access analyzer.
Predictive Factors for Renal Response in Lupus Nephritis: A Single-center Prospective Cohort Study
박대진,주영빈,방소영,이지영,이혜순,배상철 대한류마티스학회 2022 대한류마티스학회지 Vol.29 No.4
Objective: To identify the predictive factors for renal response in patients with lupus nephritis (LN). Methods: Patients and data were extracted from a prospective systemic lupus erythematosus cohort in Korea, in which clinical data were collected at 0, 3, 6, and 12 months after induction therapy. Treatment response of LN were evaluated as a complete response (CR), partial response (PR), or non-response (NR) at 3, 6, and 12 months, respectively. Predictive factors for CR at 6 months were evaluated using multivariable Poisson regression analysis. Results: A total of 75 patients with LN who underwent biopsy was enrolled. The mean age at diagnosis of LN was 28.9±9.7 years, and 68 (90.7%) were female. The frequencies of classes III, IV, III+V, IV+V, and V were 20.0%, 44.0%, 16.0%, 12.0%, and 8.0%, respectively. Compared to relapsed LN, new-onset LN showed a lower percentage of glomerulosclerosis (45.5% vs. 76.2%, p=0.013). The overall proportions of CR, PR, and NR at 6 and 12 months were 52.0%, 26.7%, 21.3% and 50.7%, 24.0%, 25.3%, respectively. In multivariate analysis, age at enrollment (odds ratio [OR]=1.02, p=0.022), relapsed LN (OR=0.71, p=0.037), anti-Ro antibody (OR=0.67, p=0.014), and class III LN (OR=1.48, p=0.001) were associated with CR at 6 months. Conclusion: In our prospective cohort, class III LN was a good predictive factor for CR at 6 months in patients with LN, whereas younger age, relapsed LN, and anti-Ro antibody were poor predictive factors.