• Journal of Korean Society of Environmental Engineers
• /
• v.22 no.1
• /
• pp.121-132
• /
• 2000

This study is to investigate the performance of a new BNR process using predenitrification scheme focusing on nitrogen removal and the possibility of adapting a computer simulation scheme in BNR process development. By using a pre-denitrification basin, higher $COD/NO_3-N$ ratio could be sustained in this BNR process. The results of the investigation showed a SDNR value of 9.04mg/gMv/hr. In the anoxic tank, the average value of SPRR of 6.25mgP/gMv/hr was observed to be very sensitive to SCOD load of influents. By calibrating internal parameters (stoichiometric and kinetic parameters) of the simulation model, the results of simulation for various BNR processes gave good agreement with observed data. The major adjustment was given with three parameters, maximum specific growth rate of heterotrophic biomass, short chain fatty acid (SCFA) limit, and phosphorous release rate. With the series of simulations on varying operational conditions, the simulation by computer program can be a useful tool for process selection, and design and operation of municipal wastewater treatment plant.

• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.7
• /
• pp.951-959
• /
• 2014

The objective of this study was to determine the effects of linseed oil or whole linseed supplementation on performance and milk fatty acid composition of lactating dairy cows. Thirty six Holstein Friesian crossbred lactating dairy cows were blocked by milking days first and then stratified random balanced for milk yields and body weight into three groups of 12 cows each. The treatments consisted of basal ration (53:47; forage:concentrate ratio, on a dry matter [DM] basis, respectively) supplemented with 300 g/d of palm oil as a positive control diet (PO), or supplemented with 300 g/d of linseed oil (LSO), or supplemented with 688 g/d of top-dressed whole linseed (WLS). All cows were received ad libitum grass silage and individually fed according to the treatments. The experiment lasted for 10 weeks including the first 2 weeks as the adjustment period, followed by 8 weeks of measurement period. The results showed that LSO and WLS supplementation had no effects on total dry matter intake, milk yield, milk composition, and live weight change; however, the animals fed WLS had higher crude protein (CP) intake than those fed PO and LSO (p<0.05). To compare with the control diet, dairy cow's diets supplemented with LSO and WLS significantly increased milk concentrations of cis-9,trans-11-conjugated linoleic acid (CLA) (p<0.05) and n-3 fatty acids (FA) (p<0.01), particularly, cis-9,12,15-C18:3, C20:5n-3 and C22:6n-3. Supplementing LSO and WLS induced a reduction of medium chain FA, especially, C12:0-C16:0 FA (p<0.05) while increasing the concentration of milk unsaturated fatty acids (UFA) (p<0.05). Milk FA proportions of n-3 FA remarkably increased whereas the ratio of n-6 to n-3 decreased in the cows supplemented with WLS as compared with those fed the control diet and LSO (p<0.01). In conclusion, supplementing dairy cows' diet based on grass silage with WLS had no effect on milk yield and milk composition; however, trans-9-C18:1, cis-9,trans-11-CLA, n-3 FA and UFA were increased while saturated FA were decreased by WLS supplementation. Therefore, it is recommended that the addition 300 g/d of oil from whole linseed should be used to lactating dairy cows' diets.

• Analytical Science and Technology
• /
• v.17 no.1
• /
• pp.53-59
• /
• 2004

Up to now, methods for the detection of genetic alterations as single strand conformation polymorphism (SSCP) or denaturing gradient gel electrophoresis (DGGE) have been used. It is too labor-intensive and expensive to serve for routine analysis. Moreover, lower in its sensitivity and specificity being also strongly dependent on the experience of the investigater. To improve these problems, we analysed mutation of ${\beta}_2$-adrenergic receptor gene that controls bronchial asthma by denaturing high performance liquid chromatography (DHPLC) according to ion-pair reversed phase chromatography (IP-RPC). We extracted genomic DNA from 80 asthma patients and then amplified DNA using PCR and analysed PCR product by SSCP and DHPLC. As a result, we analysed mutation frequency is 19 (23.75%) on SSCP and 25 (31.25%) on DHPLC in ${\beta}_2$-adrenergic receptor gene. We conclude that DHPLC is a fast and simple screening method rather than SSCP analysis.

• Animal Bioscience
• /
• v.36 no.5
• /
• pp.761-767
• /
• 2023

Objective: The objective of this study was to determine whether dietary supplementation with a functional fatty acid blend (FA) that contains 31.4% butyric acid and 4.99% medium-chain FA improve growth performance, antioxidant capacity, immunity status, and anti-inflammatory ability in weaned piglets. Methods: One hundred and forty-four healthy piglets (Duroc×Landrace×Yorkshire) with an average body weight (BW) of 7.98±3.43 kg were randomly divided into three groups with six replicate pens and eight piglets per pen: Normal control (NC): a corn-soybean basal diet; FA1: a basal diet supplemented with 1,000 mg/kg of a functional FA; FA2: a basal diet supplemented with 2,000 mg/kg of a functional FA. The experiment lasted for 28 d. On d 14 and 28, one piglet in each pen from NC and FA2 groups was randomly selected for antioxidative index and immunoglobulins. On d 28, one piglet in each pen from NC and FA2 groups was randomly selected for intestinal morphology and inflammatory factor. Results: We observed that FA supplementation linearly increased (p<0.05) average daily gain and the final BW. There was higher (p<0.05) catalase on d 14, and immunoglobulin (Ig) A and IgM on d 28 in piglets supplemented with FA2 than in the NC group. Moreover, dietary FA2 reduced (p<0.05) crypt depth of ileum in piglets. The concentrations of tumor necrosis factor-α, interleukin (IL)-1β, IL-8, and IL-10 in jejunum were lower (p<0.05) in the FA2 group compared with the NC group. Conclusion: Therefore, the overall results suggests that the FA may help to improve gut health, antioxidant status, and immune parameters resulting in the improvement of growth performance.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.1
• /
• pp.190-197
• /
• 2010

The ACR (Access Control Router) of WiBro processes location registration of the Correspondent Node and Home Agent as the Correspondent Node moves between ACRs. Therefore, the location update cost is low compared with MIPv6. However, all packets which are sent and received are sent through the ACR, so as the number of mobile nodes that are managed by the ACR increases, the cost of packet delivery also increases. Therefore, the communication state of the ACR domain remains smooth when the ACR which manages the mobile node in the ACR domain has good performance. However, network delays occur unless the ACR performs well, so the role of the ACR is important. In this paper, we analysis performance of the ACR for efficient realization of the WiBro standard. By using the Deny Probability and the Total Profit of ACR performance and apply it to the Random Walk Mobility model as the mobility model.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.4
• /
• pp.27-34
• /
• 2016

In the train system, railway vehicles are connected in a line. Therefore, this feature should be considered in composing network topology in a train system. Besides, inter-car communication should be distinguished from in-car communication. As for the inter-car communication, the hybrid topology was proposed to use rather than the conventional ring, star, daisy-chain, and bus topologies. In the hybrid topology, a number of cars are bound to be a group. Then star topology is used for the communication in a group and daisy-chain topology is used for the communication between groups. Hybrid topology takes the virtue of both star and daisy-chain topologies. Hence it maintains communication speed with reducing the number of connecting cables between cars. Therefore, it is important to choose the number of cars in a group to obtain higher performance. In this paper, we focus on the optimization of hybrid topology for railway cars. We first assume that the size of data and the frequency of data production for each car is identical. We also assume that the importance for the maximum number of cables to connect cars is variable as well as the importance of the communication speed. Separated weights are granted to both importance and we derive the optimum number of cars in a group for various number of cars and weights.

• Nuclear Engineering and Technology
• /
• v.55 no.11
• /
• pp.4057-4065
• /
• 2023

Organic scintillators are widely used for neutron/gamma detection. Pulse shape discrimination algorithms have been commonly used to discriminate the detected radiations. These algorithms have several limits, in particular with plastic scintillator which has lower discrimination ability, compared to liquid scintillator. Recently, machine learning (ML) models have been explored to enhance discrimination performance. Nevertheless, obtaining an accurate ML model or evaluating any discrimination approach requires a reference neutron dataset. The preparation of this is challenging because neutron sources are also gamma-ray emitters. Therefore, this paper proposes a pipeline to prepare clean labeled neutron/gamma datasets acquired by an organic scintillator. The method is mainly based on a Time of Flight setup and Tail-to-Total integral ratio (TTT_ratio) discrimination algorithm. In the presented case, EJ276 plastic scintillator and ²⁵²Cf source were used to implement the acquisition chain. The results showed that this process can identify and remove mislabeled samples in the entire ToF spectrum, including those that contribute to peak values. Furthermore, the process cleans ToF dataset from pile-up events, which can significantly impact experimental results and the conclusions extracted from them.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.29 no.1
• /
• pp.423-428
• /
• 2005

Due to the fast growing rate of the global container trade, every major port is under the pressure of meeting the projected capacity demand. As a result, alternative solutions have been sought for improving capacity and meeting the growing demand for container storage area and terminal capacity. Moreover, material handling process re-engineering is now a critical issue for logistics and supply chain managers of airline, shipping lines, terminal and warehousing enterprises around the world. Therefore, the purpose of this paper is to develop the 3D simulator for executing performance valuation of port transportation systems. The developed 3D simulator system is to measure the effectiveness of the proposed total system and compare it with existing practices. The performance analysis variables are also defined for these comparisons.

• Tribology and Lubricants
• /
• v.22 no.4
• /
• pp.182-189
• /
• 2006

In this paper, the adhesion characteristics between a fused silica without or with an anti-sticking layer and a thermoplastic polymer film used in thermal NIL were investigated experimentally in order to identify the release performance of the anti-sticking layer. The anti-sticking layers were derived from fluoroalkylsilanes, (1H, 1 H, 2H, 2H-perfluorooctyl)trichlorosilane ($F_{13}-OTS$) and (3, 3, 3-trifluoropropyl)trichlorosilane (FPTS), and coated on the silica surface in vapor phase. The commercial polymers, mr-I 7020 and 8020 (micro resist technology, GmbH), for thermal NIL were spin-coated on Si substrate with a rectangular island which was fabricated by conventional microfabrication process to achieve small contact area and easy alignment of flat contact sur- faces. Experimental conditions were similar to the process conditions of thermal NIL. When the polymer film on the island was separated from the silica surface after imprint process, the adhesion force between the silica surface and the polymer film was measured and the surfaces of the silica and the polymer film after the separation were observed. As a result, the anti-sticking layers remarkably reduced the adhesion force and the surface damage of polymer film and the chain length of silane affects the adhesion characteristics. The anti-sticking layers derived from FPTS and $F_{13}-OTS$ reduced the adhesion force per unit area to 38% and 16% of the silica sur-faces without an anti-sticking layer, respectively. The anti-sticking layer derived from $F_{13}-OTS$ was more effective to reduce the adhesion, while both of the anti-sticking layers prevented the surface damages of the polymer film. Finally, it is also found that the adhesion characteristics of mr-I 7020 and mr-I 8020 polymer films were similar with each other.

• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.175-181
• /
• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.