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Semarang, Indonesia

Diponegoro University is a public university located in Semarang, Central Java, Indonesia. Founded in 1957 as a private university by the Semarang University Foundation, it is a pioneer of higher learning institutions in Indonesia and the first and oldest education corporation in Central Java. It is a member of IDGHE in Indonesia. Wikipedia.


Sudarno U.,Karlsruhe Institute of Technology | Sudarno U.,Diponegoro University | Winter J.,Karlsruhe Institute of Technology | Gallert C.,Karlsruhe Institute of Technology
Bioresource Technology | Year: 2011

Nitrification under changing salinities (0-9%), temperatures (6-50°C), ammonia (0-5gNL -1) and nitrite concentrations (0-0.4gNL -1) was investigated in fixed-bed reactors. For all conditions ammonia oxidation rates (AOR) were lower than nitrite oxidation rates (NOR). AORs and NORs increased from 12.5 to 40°C and were very low at 6°C and almost zero at 50°C. No recovery of nitrification was obtained after incubation at 50°C, whereas nitrification was restorable after incubation at 6°C. Ammonia concentrations of 5gNL -1 or nitrite concentrations up to 0.125gNL -1 decreased AOR to almost zero. AORs and NORs recovered if ammonia or nitrite was removed. At concentrations of 1 and 5gNL -1 ammonia AOR and NOR were inhibited by 50%, whereas 27mgN/L nitrite inhibited AOR by 50%. © 2011 Elsevier Ltd. Source


Caesarendra W.,Pukyong National University | Widodo A.,Diponegoro University | Yang B.-S.,Pukyong National University
Mechanical Systems and Signal Processing | Year: 2010

Degradation parameter or deviation parameter from normal to failure condition of machine part or system is needed as an object of prediction in prognostics method. This study proposes the combination between relevance vector machine (RVM) and logistic regression (LR) in order to assess the failure degradation and prediction from incipient failure until final failure occurred. LR is used to estimate failure degradation of bearing based on run-to-failure datasets and the results are then regarded as target vectors of failure probability. RVM is selected as intelligent system then trained by using run-to-failure bearing data and target vectors of failure probability estimated by LR. After the training process, RVM is employed to predict failure probability of individual units of machine component. The performance of the proposed method is validated by applying the system to predict failure time of individual bearing based on simulation and experimental data. The result shows the plausibility and effectiveness of the proposed method, which can be considered as the machine degradation assessment model. © 2009 Elsevier Ltd. All rights reserved. Source


Hadiyanto,Diponegoro University
International Food Research Journal | Year: 2013

Bread product quality is highly dependent to the baking process. A model for the development of product quality of bread products has been calibrated by experiments at a fixed baking temperature of 200°C and in combination with 100 W of microwave powers. The parameters in this model were estimated in sequence procedures: heat and mass transfer, then product transformations and finally product quality parameters. The results showed that there was an agreement between the calibrated model and the experimental data. Furthermore, the microwave input contributed significantly to the internal product properties but not for the surface properties as crispness and color. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. © 2008 IFRJ. Source


Widodo A.,Diponegoro University | Yang B.-S.,Pukyong National University
Expert Systems with Applications | Year: 2011

Condition monitoring (CM) of machines health or industrial components and systems that can detect, classify and predict the impending faults is critical in reducing operating and maintenance cost. Many papers have reported the valuable models and methods of prognostic systems. However, it was rarely found the papers deal with censored data, which was common in machine condition monitoring practice. This work deals with development of machine degradation assessment system that utilizes censored and complete data collected from CM routine. Relevance vector machine (RVM) is selected as intelligent system then trained by input data obtained from run-to-failure bearing data and target vectors of survival probability estimated by Kaplan-Meier (KM) and probability density function estimators. After validation process, RVM is employed to predict survival probability of individual unit of machine component. The plausibility of the proposed method is shown by applying the proposed method to bearing degradation data in predicting survival probability of individual unit. © 2010 Elsevier Ltd. All rights reserved. Source


to validate the effect of plain kefir on immune responses of hyperglycemia wistar rats induced by Streptozotocin. the randomized pretest - posttest control group study design was conducted in male hyperglycemia Wistar rats induced by streptozotocin (STZ). Rats were randomized into four groups: (1) STZ-induced group were given insulin treatment 0.76 UI/200 g bw, (2) STZ-induced group and treated with plain kefir 3.6 cc/200 g bw/day for 30 days, (3) STZ-induced group as control, (4) normal animal group as a negative control. Blood glucose was measured from whole blood that was taken 0.1 ml from retroorbitalis vein by microhematocrit on day 1 (pretest) and day 30 (post test) by enzymatic methods. Immune responses (cytokines IL1, IL6, IL10, TNF) were measured by ELISA. Data were analyzed by one way Anova, Mann Whitney test and Duncan with significant level of p<0.05. plain kefir supplementation 3.6 cc/day affect blood glucose, proinflamatory cytokines (IL1, IL6, TNF) and antiinflamatory cytokine (IL10). Statistical analysis showed decrease of glucose -111.00±44.23 ml (p<0.001) and proinflamatory cytokines IL1 about -18.62±23.59 and IL6 -3.21±7.57 mU/mL (p<0.001), respectively compared to the control groups. TNF decreased 1.65±4.62 mU/mL, but not significant (p>0.05), except for controls group. In addition, antiinflammatory (IL10) showed also increase about 15.11±2.16 (p<0.05), except for the control. plain kefir supplementation significantly decreased blood glucose, level of cytokines (IL1, IL6) and lowered TNF level. On the contrary, the level of IL10 is increased compare to control groups. Source

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