• Journal of Microbiology and Biotechnology
• /
• v.21 no.11
• /
• pp.1166-1173
• /
• 2011

Meju is a traditional Korean fermented soy product used as a key element for soy sauce and doenjang. Bacilli with antimicrobial activity were isolated from meju prepared by traditional methods at Sunchang county, Jeollabukdo, Korea. Six isolates were identified as Bacillus amyloliquefaciens by recA gene sequencing and RAPD-PCR. One isolate, B. amyloliquefaciens MJ5-41, showed the strongest fibrinolytic activity. A 27 kDa active fibrinolytic enzyme, AprE5-41, was purified from the culture supernatant of MJ5-41 grown on LB by chromatographic methods. The optimum pH and temperature for purified AprE5-41 were 7.0 and $45^{\circ}C$, respectively. AprE5-41 quickly degraded $A{\alpha}$ and $B{\beta}$ chains but not the ${\gamma}$-chain of fibrinogen. AprE5-41 exhibited the highest specificity for N-succinyl-Ala-Ala-Pro-Phe p-nitroanilide, a known substrate for ${\alpha}$-chymotrypsin, cathepsin G, and subtilisin BPN'. The structural gene, aprE5-41, was cloned by PCR and successfully expressed in B. subtilis.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.3
• /
• pp.74-81
• /
• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

• Journal of Biosystems Engineering
• /
• v.37 no.4
• /
• pp.271-278
• /
• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.577-582
• /
• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based Wheeled Mobile Robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps has a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. Data set between position of WMR and features of lamps are configured. Neural network are composed and teamed with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.10
• /
• pp.118-127
• /
• 2014

DNA data storage refers to any technique for storing massive digital data in base sequence of DNA and has been recognized as the future storage medium recently. This paper presents an information hiding method for DNA data storage that the massive data is hidden in non-coding strand based on DNA steganography. Our method maps the encrypted data to the data base sequence using the numerical mapping table and then hides it in the non-coding strand using the key that consists of the seed and sector length. Therefore, our method can preserve the protein, extract the hidden data without the knowledge of host DNA sequence, and detect the position of mutation error. Experimental results verify that our method has more high data capacity than conventional methods and also detects the positions of mutation errors by the parity bases.

• Journal of Microbiology
• /
• v.43 no.3
• /
• pp.257-259
• /
• 2005

Although automated continuous-monitoring blood culture systems are both rapid and sensitive, false-positive and false-negative results still occur. The objective of this study, then, was to evaluate negative results occurring with BacT/Alert 3D blood culture systems. A total of 1032 samples were cultured with the BacT/Alert 3D automated blood culture system, using both aerobic (BPA) and anaerobic (BPN) media, and 128 of these samples yielded positive results. A total of 904 negative blood samples were then subcultured in $5\%$ sheep blood agar, eosin methylene blue, chocolate agar, and sabouraud-dextrose agar. Organisms growing on these subcultures were subsequently identified using both Vitek32 (bioMerieux, Durham, NC) and conventional methods. Twenty four $(2.6\%)$ of the 904 subcultures grew on the subculture media. The majority $(83.3\%)$ of these were determined to be gram-positive microorganisms. Fourteen $(58.3\%)$ were coagulase-negative staphylococci, two $(8.3\%)$ were Bacillus spp., one $(4.2\%)$ was Staphylococcus aureus, and one $(4.2\%)$ was identified as Enterococcus faecium. Streptococcus pneumoniae and Neisseria spp. were isolated together in two $(8.3\%)$ vials. Gram-negative microorganisms comprised $12.5\%$ of the subcultures, of which two $(8.3\%)$ were found to be Pseudomonas aeruginosa, and one $(4.2\%)$ was Pseudomonas fluorescens. The other isolate $(4.2\%)$ was identified as Candida albicans. We conclude that the subculture of negative results is valuable in the BacT/Alert 3D system, especially in situations in which only one set of blood cultures is taken.

• Journal of KIISE:Software and Applications
• /
• v.28 no.10
• /
• pp.773-784
• /
• 2001

Since documents on the Web are naturally partitioned into may document database, the efficient information retrieval process requires identifying the document database that are most likely to provide relevant documents to the query and then querying the identified document database. We propose a neural net agent approach to such an efficient information retrieval. First, we present a neural net agent that learns about underlying document database using the relevance feedbacks obtained from many retrieval experiences. For a given query, the neural net agent, which is sufficiently trained on the basis of the BPN learning mechanism, discovers the document database associated with the relevant documents and retrieves those documents effectively. In the experiment, we introduce a neural net agent based information retrieval system and evaluate its performance by comparing experimental results to those of the conventional well-known approaches.

• Food Science and Biotechnology
• /
• v.18 no.2
• /
• pp.500-505
• /
• 2009

The fibrinolytic enzyme, subtilisin D5, was purified from the culture supernatant of the isolated Bacillus amyloliquefaciens DJ-5. The molecular weight of subtilisin D5 was estimated to be 30 kDa. Subtilisin D5 was optimally active at pH 10.0 and $45^{\circ}C$. Subtilisin D5 had high degrading activity for the A$\alpha$-chain of human fibrinogen and hydrolyzed the $B{\beta}$-chain slowly, but did not affect the $\gamma$-chain, indicating that it is an $\alpha$-fibrinogenase. Subtilisin D5 was completely inhibited by phenylmethylsulfonyl fluoride, indicating that it belongs to the serine protease. The specific activity (F/C, fibrinolytic/caseinolytic activity) of subtilisin D5 was 2.37 and 3.52 times higher than those of subtilisin BPN' and Carlsberg, respectively. Subtilisin D5 exhibited high specificity for Meo-Suc-Arg-Pro-Tyr-pNA (S-2586), a synthetic chromogenic substrate for chymotrypsin. The first 15 amino acid residues of the N-terminal sequence of subtilisin D5 are AQSVPYGISQIKAPA; this sequence is identical to that of subtilisin NAT and subtilisin E.

• Journal of The Korea Institute of Healthcare Architecture
• /
• v.25 no.3
• /
• pp.75-83
• /
• 2019

Purpose: There are no clear criteria for slip performance in the BF certification process, so the evaluator relies on subjective judgments depending on the field situation. Physical criteria for determining the slip performance of various floor finishes are not clear. C.S.R., the only criterion currently being used to check slip performance, may raise questions about its coverage, feasibility and reliability. Method: For an analysis of domestic standards and status, KS L 1001, KS M 3510, and KS F 2375. External standards are analyzed for ADA Standard, ANSI Standard, and BS EN Standard. Analyze the test methods and evaluation criteria of O-Y-PSM, BPT, and the dynamic slip resistance test used in these criteria. It also presents an improvement plan for the rational presentation of standards. Results: To date, various kinds of test methods and measuring devices of the slip resistance coefficient have been developed, but there are not many ways to trust useful results related to user safety. Reliability and thoroughly verified test methods and criteria should be used to assess the slip performance of the floor. In order to improve the standard for the evaluation of slip performance in Korea, the existing standard should first be raised to the same level as the overseas standard, and the application of the discriminatory standard should be applied considering the characteristics and usage patterns of each space. Implication: Currently, Korean standards propose various test methods, but the proper use of test methods, scope and assessment criteria are not established, so improvement of the comprehensive standard is necessary.

• The Journal of the Korea Contents Association
• /
• v.20 no.12
• /
• pp.301-310
• /
• 2020

The purpose of paper is to find index for building digital database of bike infrastructure statistics by analyzing the existing design standards and manuals. The design standards and guides of both central and local governments which designates the design elements of bikeway were investigated to find the primary index, and then the attribute data of bikeway were grouped into four categories including transportation, geometry, pavement, safety and utility facility, and were analyzed to find the secondary index. A FGI(Focus Group Interview) was conducted with experts in the arena of transportation to collect the opinions on the selected index. It is found that the final twenty four design elements were selected and additional six elements were added. The proposed twenty four index of bikeway design elements are considered to be included when building the digital bikeway register database.