• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.46-55
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• 2016

This work proposes a 13b 100MS/s 45nm CMOS ADC with a high dynamic performance for IF-domain high-speed signal processing systems based on a four-step pipeline architecture to optimize operating specifications. The SHA employs a wideband high-speed sampling network properly to process high-frequency input signals exceeding a sampling frequency. The SHA and MDACs adopt a two-stage amplifier with a gain-boosting technique to obtain the required high DC gain and the wide signal-swing range, while the amplifier and bias circuits use the same unit-size devices repeatedly to minimize device mismatch. Furthermore, a separate analog power supply voltage for on-chip current and voltage references minimizes performance degradation caused by the undesired noise and interference from adjacent functional blocks during high-speed operation. The proposed ADC occupies an active die area of $0.70mm^2$, based on various process-insensitive layout techniques to minimize the physical process imperfection effects. The prototype ADC in a 45nm CMOS demonstrates a measured DNL and INL within 0.77LSB and 1.57LSB, with a maximum SNDR and SFDR of 64.2dB and 78.4dB at 100MS/s, respectively. The ADC is implemented with long-channel devices rather than minimum channel-length devices available in this CMOS technology to process a wide input range of $2.0V_{PP}$ for the required system and to obtain a high dynamic performance at IF-domain input signal bands. The ADC consumes 425.0mW with a single analog voltage of 2.5V and two digital voltages of 2.5V and 1.1V.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.25-28
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• 2019

Purpose In patients with unusual kidney position after $^{99m}Tc-DTPA$ renal dynamic imaging study, the GFR(Glomerular Filtration Rate) values are significantly different according to the depth of the kidney. Thus, we tried to compare the difference of the GFR values between the depth measurement methods and in-vitro test. 30 adult patients who were subjected to renal study. 27 patients were in usual position and 3 patients were in unusual. $555{\pm}37MBq$ of $^{99m}Tc-DTPA$ was administrated to all patients. GE infinia gamma camera was used. GFR values were obtained in-vivo(gates method) and in-vitro(blood). The kidney depth in-vivo was calculated by three methods(tonnensen, manual, taylor). In-vitro, GFR was performed by blood test. Differences in the mean values of GFR and correlation between depth and GFR values were evaluated using the SPSS 12.0 statistical program. The GFR values for 27 patients with kidney in the usual position are as follows(1.tonnensen 2.manual 3.taylor 4.invitro); $69.3{\pm}4.2$, $88.2{\pm}5.6$, $77.8{\pm}4.3$, $82.2{\pm}5.8ml/min$. The three unusual cases are as follows, first(congenital renal anomaly): 66.4, 101.24, 69.07, 94.8 ml/min. second(transplantation kidney): 12.22, 29.99, 19.36, 23.5 ml/min. third(horseshoe kidney): 37.37, 93.54, 35.9, 92.5 ml/min. There was a difference between tonnensen and manual in the usual position of the kidney(p<0.05). There was no significant difference between the other methods. However, there was a significant difference in case of the unusual position of the kidneys. Correlation analysis between both kidney depth and GFR value shows person correlation as follows; Rt kidney: 0.298, Lt kidney: 0.322. When compared with the GFR values in-vitro test, it was useful to calculate the GFR value by measuring the kidney depth using a manual formula in the unusual position of the kidneys. GFR values and kidney depth were significantly related.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.261-268
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• 2021

Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

• Microbiology and Biotechnology Letters
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• v.48 no.4
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• pp.525-532
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• 2020

A continuous fermentation process was carried out to enhance hyaluronic acid (HA) production using Streptococcus zooepidemicus cells. During the 1st stage continuous operation from 8 h with a dilution rate of 0.029/h (D1), HA was produced in the range of 7.5-10 g/l. During the 2nd stage from 44 h with a dilution rate of 0.036/h (D2), HA production (8.28 g/l) was initially reduced to a small extent due to increase of dilution rate from D1 to D2, and then a new pseudo-steady state was formed within a few hours with a concurrent small variations of HA production. The HA amount produced during the latter part of the 2nd stage was stably maintained in the range of 8.28-9.48 g/l, about 4.7% less amount compared to the 1st stage. Due to 24% increase of dilution rate from D1 to D2, however, maximum volumetric productivity (DP) amounting to 0.341 g/l/h was obtained at 96 h during the 2nd stage. This maximum productivity obtained from the continuous culture turned out only a small increase (3%) as compared to the corresponding batch fermentation. However, it should be noted that, in the case of batch process, one run typically consists of serial stages of growth culture plus one final production culture. This implies that, if the continuous fermentation that practically needs no dead time necessary for the multi-stage growth cultures is run for longer period, the total amount of the accumulated HA would be far greater than the amount obtained from the corresponding batch culture performed for the identical period.

• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.

• Resources Recycling
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• v.31 no.4
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• pp.56-65
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• 2022

Copper is one of the non-ferrous metals used in the electrical/electronic manufacturing industries due to its superior properties particularly the high conductivity and less resistivity. The effluent generated from the surface finishing process of these industries contains higher copper content which gets discharged in to water bodies directly or indirectly. This causes severe environmental pollution and also results in loss of an important valuable metal. To overcome this issue, continuous R & D activities are going on across the globe in adsorption area with the purpose of finding an efficient, low cost and ecofriendly adsorbent. In view of the above, present investigation was made to compare the performance of a plant root (Datura root powder) as a bio-adsorbent to that of the synthetic one (Tulsion T-42) for copper adsorption from such effluent. Experiments were carried out in batch studies to optimize parameters such as adsorbent dose, contact time, pH, feed concentration, etc. Results of the batch experiments indicate that 0.2 g of Datura root powder and 0.1 g of Tulsion T-42 showed 95% copper adsorption from an initial feed/solution of 100 ppm Cu at pH 4 in contact time of 15 and 30 min, respectively. Adsorption data for both the adsorbents were fitted well to the Freundlich isotherm. Experimental results were also validated with the kinetic model, which showed that the adsorption of copper followed pseudo-second order rate expression for the both adsorbents. Overall result demonstrates that the bio-adsorbent tested has a potential applicability for metal recovery from the waste solutions/effluents of metal finishing units. In view of the requirements of commercial viability and minimal environmental damage there from, Datura root powder being an effective material for metal uptake, may prove to be a feasible adsorbent for copper recovery after the necessary scale-up studies.

• The Journal of Korean Society for Radiation Therapy
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• v.34
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• pp.51-60
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• 2022

Objectives: The purpose is to evaluate dosimetric performance and delivery efficiency of VMAT with Halcyon LINAC for double target spine SBRT Materials and Methods: 12 patients with spine oligometastases were retrospectively studied. Single-isocenter spine SBRT plans was established using Halcyon® with Dual Layer MLC and Truebeam® with High Definition MLC. All patients' plans were created in Eclipse TPS through the identical conditions and optimization. C.I, H.I, G.I (Gradient Index), maximal and volumetric doses to spinal cord and low dose area were evaluated for comparison of both plans. Also, total MU and BOT(Beam On Time) were evaluated. Results: Halcyon plans was no Statistical differences in C.I and H.I. However, the average of G.I was 4.64 for Halcyon, which decreased to 5.5% compared to Truebeam (P<0.001). Halcyon plans demonstrated statistically significant reduced G.I. The average of 50% and 25% isodose volume was 487.56 cc (-3.82%, P<0.001), 1859.45 cc (-4.75%, P<0.001) in Halcyon, respectively. Significantly reduced low dose spill were observed in Halcyon plans. In the evaluation of the spinal cord, the average of Dmean and V10 of Halcyon plans in the sample group with an overlap volume of less than 1 cc was 6.802 Gy (-3.504%, P=0.067), 5.766±1.683 cc (-8.199%, P=0.002), respectively. Halcyon plans demonstrated statistically significant reduced D_mean and V10. For delivery efficiency, MU and BOT(maximum dose rate for each machine), on average, increased in Halcyon plans. However, the average of BOT(800MU/min for each machine) was 648.33 sec for Halcyon (-1.74%, P<0.001). Conclusion: Halcyon plan for double-target spine SBRT demonstrated advantages in the low dose area with a steep dose gradient, while having dosimetrically equivalent target dose distribution and spinal cord protective effect. As a result, Halcyon LINAC produced a dosimetrically improved plan for double-target spine SBRT.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Korean Journal of Food Science and Technology
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• v.48 no.2
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• pp.133-141
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• 2016

The physicochemical properties, antioxidant capacities, and sensory optimization of taro (Colocasia esculenta) under different aging conditions were investigated to develop black taro. Black taro was processed in three steps (steaming: $95{\pm}3^{\circ}C$ for 1 h; aging: 85, 90, $95^{\circ}C$ for 20, 40, and 60 h; drying: $60^{\circ}C$ for 24 h) and ground into a powder for all experiments. Black taro showed an increased crude fiber content and browning index compared to raw taro. Calcium oxalate contents, reducing sugar contents, moisture contents, and lightness values were decreased during the processing of taro. Improvements in total polyphenol content and antioxidant activity (DPPH, ABTS, FRAP) were observed in the black taro samples aged at higher temperature. Response surface methodology was used for sensory optimization, and the optimum aging conditions with the highest acceptance values were found to be $88.73^{\circ}C$ for 39.50 h for taste, and $88.82^{\circ}C$ for 42.60 h for overall acceptance.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.