ISE 기반의 임베디드 시스템을 이용한 실시간 수경재배 양액 모니터링 (Real-time Nutrient Monitoring of Hydroponic Solutions Using an Ion-selective Electrode-based Embedded System)
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- 생물환경조절학회지
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- 제29권2호
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- pp.141-152
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- 2020
본 연구는 양액 내 존재하는 다량 영양소의 농도를 실시간으로 측정하기 위해 이온 선택 전극 (ISE) 으로 구성된 임베디드 시스템의 개발을 보여준다. NO3, K 및 Ca 이온을 감지하기위한 PVC ISE, H2PO4를 감지하기위한 코발트 전극, 기준 전극, 샘플 용액이 담기는 챔버, 펌프 및 밸브를 사용하여 측정하는 시스템으로 구성된다. 양액 샘플양 조절과 데이터 수집을 위해서 데이터 Due 보드가 사용되었고, 각각의 샘플 측정 전에, 측정 중 발생하는 드리프트를 최소화시키기 위해 2 점 정규화 방법을 사용하였다. PVC 멤브레인을 기반으로 한 NO3 및 K 전극의 농도 예측 성능은 표준 분석기의 결과와 근접한 일치 (R2 = 0.99) 나타내며 만족스러운 결과를 나타냈다. 하지만, Ca II 이온 투과체 제조된 Ca 전극은 고농도 양액 농도에서 Ca 농도를 55 %로 낮게 측정하였다. 코발트 전극 기반 인산 측정은 반복측정 중에 발생한 코발트 전극의 불안정한 신호로 인해 표준 방법과 비교하여 45 ~ 155 mg / L의 인산 농도 범위에서 24.7 ± 9.26 %의 비교적 높은 오차를 나타냈다. 수경 P 감지의 예측 능력을 향상시키기 위해 코발트 전극의 신호 컨디셔닝에 대한 추가 연구가 필요함으로 판단된다.
본 논문에서는 복합 미생물 배양기의 제어시스템을 제안하였다. 제안하는 제어시스템은 복합 미생물 배양기의 제어부, 통신부, 전원부, 제어시스템 등으로 구성된다. 복합 미생물 배양기의 제어부는 아날로그 신호와 디지털 신호의 변환, LCD 패널을 이용한 디스플레이, 수위센서, 온도센서, pH 농도센서 등과 같은 센서들의 신호 제어를 하도록 설계 및 제작한다. 사용하는 수위센서는 기존 수위센서가 거품과 같은 이물질 등으로 인해 측정이 어려운 문제점을 해결하고자 직진성이 우수한 IR 레이저 방식을 사용하여 정확한 수위 측정이 가능하도록 설계 및 제작한다. 온도센서는 열 저항 원리를 사용하여 측정함으로써, 높은 정확도와 누적 저항 오차가 없도록 설계하여 사용한다. 통신부는 2개의 LAN 포트와 1개의 RS-232 포트로 구성하여 복합 미생물 배양기에서 사용되는 LCD 패널, PCT 패널, 로드셀 컨트롤러 등의 신호를 제어부에 전달할 수 있도록 설계 및 제작한다. 전원부는 제어부와 통신부가 원활하게 동작할 수 있도록 24V, 12V 5V 등 3개의 전압 공급 단자로 구성하여 전원을 공급하도록 설계 및 제작한다. 복합 미생물 배양기의 제어시스템은 PLC를 사용하여 pH 농도센서, 온도센서, 수위센서 등의 센서값과 배양에 사용되는 써큘레이션 펌프, 써큘레이션 밸브, 로터리 펌프와 인버터 로드셀 등의 동작을 제어한다. 제안된 복합 미생물 배양기의 제어시스템의 성능을 평가하기 위하여 공인인증기관에서 실험한 결과는 수위 측정감도의 범위가 -0.41mm~1.59mm로, 물 온도의 변화 폭이 ±0.41℃로 현재 상용으로 판매되는 제품들 성능보다 우수한 성능으로 동작됨이 확인되었다. 따라서, 본 논문에서 제안한 복합 미생물 배양기의 제어시스템의 효용성이 입증되었다.
연구배경: Auto-PEEP 혹은 intrinsic PEEP은 호기말에 폐용적이 전체 호흡기계의 이완 용적으로 돌아오지 않음으로써, 증가된 호흡기계의 탄성반도압만큼 호기말 폐포내압(alveolar pressure) 이양의 값을 보이는 것을 말한다. Auto-PEEP 이 존재하는 만성폐쇄성폐질환 환자에게 externa1 PEEP을 적용하면 환자의 호흡 일을 줄일 수 있어서, 질환의 급성악화시 혹은 기계호흡으로부터의 이탈시 환자의 자발호흡을 보조하기 위한 요법으로 제시되고 있다. 이에 기계호흡중인 환자에서 auto-PEEP의 존재가 호흡 일에 미치는 영향을 알아보고, externa1 PEEP의 사용이 auto- PEEP에 의해 증가된 호흡 일을 줄이는지를 알아보기 위해 본 연구를 시행하였다. 방법: 호흡부전으로 기계호흡을 하고 있는 환자 15명을 대상으로 연구가 이루어 졌으며, 이들 7명에서 auto-PEEP이 관찰되었고(auto-PPEP군) 8명에서 auto-PEEP이 auto-PEEP군). 양군 간의 환자의 호흡역학적 지표의 차이를 조사하였으며, auto-PEEP이 존재하는 환자들에 대해 3cm
The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70