• Journal of Korean Society of Environmental Engineers
• /
• v.31 no.2
• /
• pp.102-108
• /
• 2009

DO, ORP and pH values measured during SBR operation can provide information about removal reaction of organic contaminants and nutrient materials in the reactor. It is already generalized control strategy to control reaction phase time using their special patterns indicating the end of the removal reactions. However, those informations are limited to point out the end time of oxidative reaction in the aerobic phase or reductive reaction in the anoxic phase without giving quantitative value of influent loading level. In this research, a diagnosis algorithm which can estimate the loading level of carbon and ammonia as high, medium and low was developed using the basic measurements like DO, ORP, and pH. It will be possible to know the level of influent loading rate from those online measurements without experimental analysis.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.32 no.2
• /
• pp.186-191
• /
• 1999

The three speices of miroalgae (Chlorella vulgaris, Dunaliella salina and Porphyridium purpureum) were immobilized in Ca-alginate capsules as a basic study for development of economic cultivation process, and then were cultivated in an air-bubble column bioreactor. Under the batch culture of aerobic conditions, the thickness of the capsule membrane and $CO_2$ supply did not affect the growth of the immobilized microalga, Chlorella vulgaris. Cell concentration of immobilized microalgae in the capsule was higher than those of imobilized microalgae in beads and free cells. The cell concentration of microencapsulated Dunaliella salina was greater about 5 times than that of free cells. Based on these results, it is concluded that the application of microencapsulation technology to the culture of microalgae was an effective method for high-density cultivation.

• Korean Chemical Engineering Research
• /
• v.51 no.4
• /
• pp.470-475
• /
• 2013

Zr-benzendicarboxylate structure, UiO-66 was prepared in 1-L batch scale by using a unique sonochemical-solvothermal combined synthesis method. The produced UiO-66 showed uniform particles of ca. $0.2{\mu}m$ in size with the BET surface area of $1,375m^2/g$ in high product yield (>95%). The UiO-66 showed 198 and 84 mg/g $CO_2$ adsorption capacity at 273 K and 298 K, respectively, with excellent $CO_2$ selectivity ($CO_2:N_2=32:1$) at ambient conditions. The isosteric heat of $CO_2$ adsorption varied from 33 to 25 kJ/mol as the adsorption progressed. The UiO-66 tested for xylene isomer separation in a liquid-phase batch mode confirmed preferential adsorption of the adsorbent for o-xylene over m-, and p-xylene.

• Journal of Life Science
• /
• v.10 no.1
• /
• pp.14-21
• /
• 2000

The experiments were performed using both batch and continuous column reactors. Batch biodegradation studies were performed under aerobic conditions to determine the biodegradable fraction of the natural organic matter (NOM) source. NOM source was evaluated for its biodegradability at three different UV irradiation conditions and compared to its biodegradability without UV irradiation. In continuous experiments, system operating parameters of empty bed contact time (EBCT), recycle ratio, and influent concentration affected the extent of biofiltration in the biofilters. The effluent UV254/DOC ratios fro the biologically active columns were consistently lower than the influent values, which indicated that the dissolved organic carbon (DOC) removed by biodegradation was not a significant part of the UV-absorbable material. The increase in UV254/DOC ratio was caused by the DOC decrease across the biofilter because there was essentially no difference between the feed and effluent UV254 absorbance values over time. The results of this research showed that biofiltration was an effective method for removing the biodegradable fraction of NOM from water supplies.

• Journal of Soil and Groundwater Environment
• /
• v.7 no.1
• /
• pp.25-31
• /
• 2002

This study attempts to elucidate the possibility of treating landfill leachate by steelers' dust/${H_2}{O_2}$ system in a well-mixed batch reactor. Experiments were conducted to investigate the effects of operating variables such as pH, dust and ${H_2}{O_2}$ dosages and ${H_2}{O_2}$ injection method on the treatment efficiency, Contaminant concentrations were identified by TOC (Total Organic Carbon) analyzer. Experimental observations showed the possibility of steelers' dust as a catalytic reagent in the ${H_2}{O_2}$/dust system. The batch experiments showed that the optimal $H_2O$$_2$ and dust dosage, 20g/L dust. 2,000mg/L ${H_2}{O_2}$ removed about 75% of initial TOC concentration (250mg/1) within 60 min. And the TOC removal in the ${H_2}{O_2}$/dust system effectively proceeded only within a limited pH range of 3-4. The stealers' dust-catalyzed oxidative treatment of landfill leachate was more efficient compared with the $FeSO_2$catalyzed system (Fenton oxidation) for the removal rate and the cost.

• Journal of KIISE
• /
• v.42 no.8
• /
• pp.1010-1021
• /
• 2015

Big data systems are widely used to collect large-scale log data, so it is very important for these systems to operate with a high level of performance. However, the current Hadoop-based big data system architecture has a problem in that its performance is low as a result of redundant processing. This paper solves this problem by improving the design of the Hadoop system architecture. The proposed architecture uses the batch-based data collection of the existing architecture in combination with a single processing method. A high level of performance can be achieved by analyzing the collected data directly in memory to avoid redundant processing. The proposed architecture guarantees system expandability, which is an advantage of using the Hadoop architecture. This paper confirms that the proposed architecture is approximately 30% to 35% faster in analyzing and processing data than existing architectures and that it is also extendable.

• Korean Journal of Chemical Engineering
• /
• v.35 no.12
• /
• pp.2384-2393
• /
• 2018

Porous alginate-based hydrogel beads (porous ABH) have been prepared through a facile and sustainable template-assisted method using nano-calcium carbonate and nano-$CaCO_3$ as pore-directing agent for the efficient capture of methylene blue (MB). The materials were characterized by various techniques. The sorption capacities of ABH towards MB were compared with pure sodium alginate (ABH-1:0) in batch and fixed-bed column adsorption studies. The obtained adsorbent (ABH-1:3) has a higher BET surface area and a smaller average pore diameter. The maximum adsorption capacity of ABH-1:3 obtained from Langmuir model was as high as $1,426.0mg\;g^{-1}$. The kinetics strictly followed pseudo-second order rate equation and the adsorption reaction was effectively facilitated, approximately 50 minutes to achieve adsorption equilibrium, which was significantly shorter than that of ABH-1:0. The thermodynamic parameters revealed that the adsorption was spontaneous and exothermic. Thomas model fitted well with the breakthrough curves and could describe the dynamic behavior of the column. More significantly, the uptake capacity of ABH-1:3 was still higher than 75% of the maximum adsorption capacity even after ten cycles, indicating that this novel adsorbent can be a promising adsorptive material for removal of MB from aqueous solution under batch and continuous systems.

• Journal of Microbiology and Biotechnology
• /
• v.31 no.10
• /
• pp.1430-1437
• /
• 2021

Cronobacter sakazakii is an opportunistic pathogenic bacterium found in powdered infant formula and is fatal to neonates. Antibiotic resistance has emerged owing to overuse of antibiotics. Therefore, demand for high-yield bacteriophages as an alternative to antibiotics has increased. Accordingly, we developed a modified mass-production method for bacteriophages by introducing a two-stage self-cycling (TSSC) process, which yielded high-concentration bacteriophage solutions by replenishing the nutritional medium at the beginning of each process, without additional challenge. pH of the culture medium was monitored in real-time during C. sakazakii growth and bacteriophage CS01 propagation, and the changes in various parameters were assessed. The pH of the culture medium dropped to 5.8 when the host bacteria reached the early log phase (OD₅₄₀ = 0.3). After challenge, it decreased to 4.65 and then recovered to 4.94; therefore, we set the optimum pH to challenge the phage at 5.8 and that to harvest the phage at 4.94. We then compared phage production during the TSSC process in jar-type bioreactors and the batch culture process in shaker flasks. In the same volume of LB medium, the concentration of the phage titer solution obtained with the TSSC process was 24 times higher than that obtained with the batch culture process. Moreover, we stably obtained high concentrations of bacteriophage solutions for three cycles with the TSSC process. Overall, this modified TSSC process could simplify large-scale production of bacteriophage CS01 and reduce the unit cost of phage titer solution. These results could contribute to curing infants infected with antibiotic-resistant C. sakazakii.

• Journal of dental hygiene science
• /
• v.20 no.4
• /
• pp.206-212
• /
• 2020

Background: A Teachable Machine is a kind of machine learning web-based tool for general persons. In this paper, the feasibility of Google's Teachable Machine (ver. 2.0) was studied in the diagnosis of the tooth-marked tongue. Methods: For machine learning of tooth-marked tongue diagnosis, a total of 1,250 tongue images were used on Kaggle's web site. Ninety percent of the images were used for the training data set, and the remaining 10% were used for the test data set. Using Google's Teachable Machine (ver. 2.0), machine learning was performed using separated images. To optimize the machine learning parameters, I measured the diagnosis accuracies according to the value of epoch, batch size, and learning rate. After hyper-parameter tuning, the ROC (receiver operating characteristic) analysis method determined the sensitivity (true positive rate, TPR) and specificity (false positive rate, FPR) of the machine learning model to diagnose the tooth-marked tongue. Results: To evaluate the usefulness of the Teachable Machine in clinical application, I used 634 tooth-marked tongue images and 491 no-marked tongue images for machine learning. When the epoch, batch size, and learning rate as hyper-parameters were 75, 0.0001, and 128, respectively, the accuracy of the tooth-marked tongue's diagnosis was best. The accuracies for the tooth-marked tongue and the no-marked tongue were 92.1% and 72.6%, respectively. And, the sensitivity (TPR) and specificity (FPR) were 0.92 and 0.28, respectively. Conclusion: These results are more accurate than Li's experimental results calculated with convolution neural network. Google's Teachable Machines show good performance by hyper-parameters tuning in the diagnosis of the tooth-marked tongue. We confirmed that the tool is useful for several clinical applications.

• Journal of Convergence for Information Technology
• /
• v.11 no.7
• /
• pp.31-38
• /
• 2021

In this paper, in order to obtain the optimization of the RNN model used for sentiment analysis, the correlation of each model was studied by observing the trend of loss and accuracy according to hyperparameter tuning. As a research method, after configuring the hidden layer with LSTM and the embedding layer that are most optimized to process sequential data, the loss and accuracy of each model were measured by tuning the unit, batch-size, and embedding size of the LSTM. As a result of the measurement, the loss was 41.9% and the accuracy was 11.4%, and the trend of the optimization model showed a consistently stable graph, confirming that the tuning of the hyperparameter had a profound effect on the model. In addition, it was confirmed that the decision of the embedding size among the three hyperparameters had the greatest influence on the model. In the future, this research will be continued, and research on an algorithm that allows the model to directly find the optimal hyperparameter will continue.