• Journal of the East Asian Society of Dietary Life
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• v.12 no.2
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• pp.91-99
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• 2002

This study was carried out to develop a diabetic-oriented convenience flood using 7 medicinal plants (Schisandra chinensis, Coix lachryma-jobi, Dioscorea batatas, Ophipogon japonicus, Lyicium chinense, Houttuynia cordata, Polygonatum sibiricum) and chicken. Portion size was 310g, total calorie was 551.6 kcal and carbohydrate, lipid and protein were consisted of 53.0%, 20.9% and 26.1%, respectively. Calcium, zinc and iron content were 268.9mg, 5.4mg and 6.1mg, respectively. Crude fiber content was 22.9g. In sensory evaluation, the scores of taste, color, texture and overall acceptability were higher than normal diabetic meal. Hypoglycemic effect of the device meal for diabetic persons was excellent compared to that of normal diabetic meal. The above results indicate that the 7 medicinal plants can be used as functional ingredients fur diabetic-oriented convenience flood industry. Also, device meal can be used as ready-prepared food for weight control.

• Culinary science and hospitality research
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• v.21 no.4
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• pp.16-28
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• 2015

The purpose of this study, as a part of developing a new french dressing, was to present the best conditions to make improved kiwi dressing, suitable for the tastes of modern people, the processing and cooking methods of different ratios of green kiwi and gold kiwi have been sought to develop a new type of dressing, then its antioxidant have been defined, and used for producing kiwi dressing. Each 150g of different Kiwi purees, made based on the most preferable combinations from the pre-test were used for kiwi dressing, and thereafter its quality characteristics, and physical properties were investigated, as well as a sensory test was conducted. The highest viscosity of kiwi dressing was test sample GD2, and in general that of combining both types of kiwis were higher than that of either single kiwi. The sugar content was decreased by changing the Gold kiwi portion(p<0.05). The chromaticity in general increased with increases in the Gold kiwi portion, and a-value(brightness) and b-value(redness) of sample GD1 were the highest by -2.75 and 17.50(p<0.05). From the acceptability test, the highest overall acceptability was the dressing sample combining Gold kiwi and Green kiwi at a ratio of 1:1. Based on the study results, it is expected that the dressing, made of kiwi puree, mixing Green kiwi and Gold kiwi by 1:1 ratio, and adding 130g of edible oil, 50g of onion, 40g of sugar, and 5g of salt, would improve the quality and overall acceptability of the dressing.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.57-66
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• 2007

Natural gases generally consist of mainly $^{12}C$ and about 1.1% of $^{13}C$. It is well known that a stable carbon isotope, $^{13}C$, has been widely used for the applications of medical, pharmaceutical, and agricultural tracers. As a result, the development of the separation and concentrating technology of $^{13}C$ can cause of high value-added products and the possibility of the generation of new carbon materials, In general, there are two kinds of approaches to obtain a stable $^{13}C$ isotope by the separation of cryogenic distillation. One is to obtain a concentrated $^{13}CH_4$ isotope from natural gas. Another approach is to get concentrated $^{13}CO$ by distillation followed by a chemical reaction of $CH_4$ and $H_2O$. In this study, rigorous process simulations of the cryogenic distillation have been performed and analyzed for the concentrated separation of $^{13}C$ isotopes from LNG and NG by using commercial process simulator. Due to the very small differences of relative volatilities and separabilities of $^{12}C$ and $^{13}C$, the process design and operation of effective separation and concentration of $^{13}C$ need special strategies and feasibility studies. Utilization of vapor pressure data to acentric factor in SRK equation of state and optimized process conditions have been able to predict for the effective of the separation yield and concentration of $^{13}C$ for the cryogenic distillation. The various operation strategies for both batch and continuous cryogenic distillation are also studied and suggested for the basic design of the process. Development of this study can provide a tool for the effective design and operation of the cryogenic separation of $^{13}C$.

• Investigative Magnetic Resonance Imaging
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• v.14 no.2
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• pp.103-114
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• 2010

Purpose : To generate a Korean specific brain template, especially in patients with Alzheimer's disease (AD) by optimizing the voxel-based analysis. Materials and Methods : Three-dimensional T1-weighted images were obtained from 123 subjects who were 43 cognitively normal subjects and patients with 44 mild cognitive impairment (MCI) and 36 AD. The template and the corresponding aprior maps were created by using the matched pairs approach with considering differences of age, gender and differential diagnosis (DDX). We measured several characteristics in both our and the MNI templates, including in the ventricle size. Also, the fractions of gray matter and white matter voxels normalized by the total intracranial were evaluated. Results : The high resolution template and the corresponding aprior maps of gray matter, white matter (WM) and CSF were created with the voxel-size of $1{\times}1{\times}1\;mm$. Mean distance measures and the ventricle sizes differed between two templates. Our brain template had less gray matter and white matter areas than the MNI template. There were volume differences more in gray matter than in white matter. Conclusion : Gray matter and/or white matter integrity studies in populations of Korean elderly and patients with AD are needed to investigate with this template.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.2
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• pp.111-116
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• 2020

This study was conducted to determine the maintenance energy requirements of growing goats in order to establish an appropriate energy benefit system, to reduce feed costs and improve livestock productivity of goat farmers, and to present basic data for detailed specifications afterwards. This experiment was conducted as a group specification test for a total of 3 months, with 32 goats of three months age and conducted by four treatments with different energy levels (T1: NRC+0%, T2: NRC+10%, T3: NRC+20%, and T4: NRC+30%). The average daily gain was the highest in the treated with NRC + 10% of the energy level of the experimental diet, and the feed conversion ratio was in the range of 6.3 g to 7.3 g in the group feeding experiment. Although there was no significant difference in digestibility between treatments, the digestibility of dry matter, crude protein, and crude fat was higher in T2 treated with NRC + 10% than the other treatments. Through the regression equation of the values of MEI and ADG obtained through the experiment (Y=0.5439X+111.51, R²=0.712), the maintenance energy requirement of the goat in the growing period was estimated to be 111.51 kcal/kgBW^0.75.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.469-478
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• 2001

In the virtual memory system, page replacement policy exerts a great influence on the performance of demand paging. There are LRU(Least Recently Used) and LFU (Least Frequently Used) as the typical replacement policies. The LRU policy performs effectively in many cases and adapts well to the changing workloads compared to other policies. It however cannot distinguish well between frequently and infrequently referenced pages. The LFU policy requires that the page with the smallest reference count be replaced. Though it considers all the references in the past, it cannot discriminate between references that occurred far back in the past and the more recent ones. Thus, it cannot adapt well to the changing workload. In this paper, we first analyze memory reference patterns of eight applications. The patterns show that the recently referenced pages or the frequently referenced pages are accessed continuously as the case may be. So it is rather hard to optimize page replacement scheme by using just one of the LRU or LFU policy. This paper makes an attempt to combine the advantages of the two policies and proposes a new page replacement policy. In the proposed policy, paging list is divided into two lists (LRU and LFU lists). By keeping the two lists in recency and reference frequency order respectively, we try to restrain the highly referenced pages in the past from being replaced by the LRU policy. Results from trace-driven simulations show that there exists points on the spectrum at which the proposed policy performs better than the previously known policies for the workloads we considered. Especially, we can see that our policy outperforms the existing ones in such applications that have reference patterns of re-accessing the frequently referenced pages in the past after some time.

• Journal of Life Science
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• v.21 no.2
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• pp.309-315
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• 2011

Rice syrup meal (RSM) was enzymatically hydrolyzed using eight commercial proteases (Protamex, Neutrase, Flavourzyme, Alcalase, Protease M, Protease N, Protease A, Molsin F) for 4 hr at optimum pH and temperature. Proteolytic hydrolysates were examined in supernatant and precipitate using Lowry protein assay, semimicro Kjeldahl method and gravimetric method using weight difference before and after enzymatic hydrolysis. Although RSM contains a high amount of protein (71.2%), only a very small amount of protein was hydrolyzed. Two proteases (Protease M and Protease N) were found to be the most effective in the hydrolysis of RSM protein. In Lowry method, 57.5 and 59.0 mg protein/g RSM were hydrolyzed after Protease M and Protease N treatments, respectively. In gravimetric method, 80.0 and 85.4 mg protein/g RSM were hydrolyzed after Protease M and Protease N treatments. In Kjeldahl method, 67.43 and 70.43 mg protein/g RSM were hydrolyzed after Protamex and Protease N treatments, respectively. For synergistic effect, two or three effective commercial proteases (Protease M, Protease N and Protease A) were applied to RSM at one time. The highest hydrolysis of RSM protein was observed in both Lowry protein assay (80.3 mg protein/g RSM) and gravimetric methods (153.2 mg protein/g RSM) when three commercial proteases were applied at one time, suggesting the synergistic effect of those proteases.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• 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.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.61-77
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• 2019

If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.