• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.62-70
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• 2000

In usual language models(LMs), the probability has been estimated by selecting highly frequent words from a large text side database. However, in case of adopting LMs in a specific task, it is unnecessary to using the general method; constructing it from a large size tent, considering the various kinds of cost. In this paper, we propose a construction method of LMs using a small size text database in order to be used in specific tasks. The proposed method is efficient in increasing the low frequent words by applying same sentences iteratively, for it will robust the occurrence probability of words as well. We carried out continuous speech recognition(CSR) experiments on 200 sentences uttered by 3 speakers using LMs by iterative teaming(IL) in a air flight reservation task. The results indicated that the performance of CSR, using an IL applied LMs, shows an 20.4% increased recognition accuracy compared to those without it. This system, using the IL method, also shows an average of 13.4% higher recognition accuracy than the previous one, which uses context-free grammar(CFG), implying the effectiveness of it.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.242-247
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• 2004

Conventional keyword spotting systems use the connected word recognition network consisted by keyword models and filler models in keyword spotting. This is why the system can not construct the language models of word appearance effectively for detecting keywords in large vocabulary continuous speech recognition system with large text data. In this paper to solve this problem, we propose a keyword spotting system using pseudo N-gram language model for detecting key-words and investigate the performance of the system upon the changes of the frequencies of appearances of both keywords and filler models. As the results, when the Unigram probability of keywords and filler models were set to 0.2, 0.8, the experimental results showed that CA (Correctly Accept for In-Vocabulary) and CR (Correctly Reject for Out-Of-Vocabulary) were 91.1% and 91.7% respectively, which means that our proposed system can get 14% of improved average CA-CR performance than conventional methods in ERR (Error Reduction Rate).

• Applied Chemistry for Engineering
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• v.7 no.6
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• pp.1096-1104
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• 1996

In order to synthesize a new antibacterial and antitumor agents, we have prepared new analogues pteroic acid(13a, 13b), which means C-9 position of pteroic acid has been replaced by norfloxacin(8) or ciprofloxacin(9) and amino group of C-2 position by $CH_3$. These derivatives were synthesized coupling at N-4 piperazine of norfloxacin and ciprofloxacin with 2-amino-3-cyano-5-chloromethylpyrazine(20) provided 1-alkyl(ethyl, cyclopropyl)-6-fluoro-1,4-dihydro-4-oxo-7-[[4-N-(2-amino-3-cyanopyrazin-5-yl)methyl]piperazin-1-yl]-3-quinoline-carboxylic acid(12a, 12b). It was then cyclized with acetamidine. HCI to obtain new analogues of C-2 desaminomethylpteroic acid(13a, 13b) in yield of 76.2% and 82.8 % respectively. These compounds were tested in vitro on antibacterial activity against Gram-positive and Gram-negative bacteria including Pseudomonas aeruginosa ATCC9027. In general, these synthesized compounds(13a, 13b) showed less potent activities than those of norfloxacin.

• Informatization Policy
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• v.26 no.4
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• pp.85-106
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• 2019

Recently, there have been increasing cases of collective petitions filed in the electronic petitions system. However, there is no efficient management system, raising concerns on side effects such as increased administrative workload and mass production of social conflicts. Aimed at suggesting a methodology for estimating electronic collective petitions using anomaly detection and corpus linguistics-based content analysis, this study conducted the followings: i) a theoretical review of the concept of collective petitions, ii) estimation of electronic collective petitions using anomaly detection based on nonparametric unsupervised learning, iii) a content similarity analysis on petitions using n-gram cosine angle distance, and iv) a case study on the Voice of Citizens of Changwon City, through which the utility of the proposed methodology, policy implications and future tasks were reviewed.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.267-273
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• 2016

Creation and Sharing of information which is structured data as well as various unstructured data. makes progress actively through the spread of mobile. Recently, Big Data extracts the semantic information from SNS and data mining is one of the big data technique. Especially, the general emotion analysis that expresses the collective intelligence of the masses is utilized using large and a variety of materials. In this paper, we propose the emotion prediction system architecture which extracts the significant keywords from social network paragraphs using n-gram and Korean morphological analyzer, and predicts the emotion using SVM and these extracted emotion features. The proposed system showed 82.25% more improved recall rate in average than previous systems and it will help extract the semantic keyword using morphological analysis.

• Journal of the Korean Chemical Society
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• v.54 no.5
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• pp.506-514
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• 2010

A new series of ligands N-[(benzoylamino)-thioxomethyl]-amino acid (HL) were synthesized by reaction of benzoylisothiocyanate with various amino acids namely aspartic acid [BATA] (1), glutamic acid [BATG] (2), methionine [BATM] (3), leucine [BATL] (4), and tryptophan [BATT] (5). The ligands were characterized by elemental analysis, IR and NMR spectra. Some transition metal complexes ($ML_2$) for these ligands (6-8) were prepared; [M=Cu(II), Co(II), or Ni(II)], and characterized by elemental analysis, IR and $^1H$ NMR spectra. Antibacterial study showed that all the ligands have no antibacterial activity, whereas ($ML_2$) complexes; [M = Cu(II), Co(II), or Ni(II)] have antibacterial activity towards (Gram -ive) Escherichia (NCTC5933) and (Gram +ive) Staphylococcus (NCTC6571) and have no toxicity on (BALB/C) Albino mice.

• Convergence Security Journal
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• v.22 no.5
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• pp.145-154
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• 2022

Recently, the widespread proliferation and high sophistication of botnets are having serious consequences not only for enterprises and users, but also for cyber warfare between countries. Therefore, research to detect botnets is steadily progressing. However, the DGA-based botnet has a high detection rate with the existing signature and statistics-based technology, but also has a high limit in the false positive rate. Therefore, in this paper, we propose a detection model using text-based n-gram to detect DGA-based botnets. Through the proposed model, the detection rate, which is the limit of the existing detection technology, can be increased and the false positive rate can also be minimized. Through experiments on large-scale domain datasets and normal domains used in various DGA botnets, it was confirmed that the performance was superior to that of the existing model. It was confirmed that the false positive rate of the proposed model is less than 2 to 4%, and the overall detection accuracy and F1 score are both 97.5%. As such, it is expected that the detection and response capabilities of DGA-based botnets will be improved through the model proposed in this paper.

• Journal of Korean Academy of Nursing
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• v.9 no.2
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• pp.17-26
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• 1979

This research is to prevent the infection of maternity in the hospital by examining the microbes contaminations in maternity through airbone microbes and those who are engaged in the ward of O.B. ＆ G.Y. and to furnish the basic data available to hospital management. The bacterial growth of airbone microbes contaminations in nosocomial air and who thor the nasal cavity of passers by (doctors, nurses, parturient women) who went to the ward of O.B. ＆ G.Y. contaminated or not were examined in“E”Univ. Hospital from July to August, 1979 by using thioglycollate broths and agar plates. The following results were obtained: 1. The average colony number of airborne microbes revealed as follows the pediatric ward (36 colonies), the internal ward (33 colonies), the ward of O.B. ＆ G.Y. (30 colonies), the ward of surgery (24 colonies), delivery-waiting room (11 colonies), and the delivery room (3 colonies). 2. The bacterial growth beforenoon differed from that of afternoon. Namely, the latter (24 colonies) was higher than the former (21 colonies). 3. The type of strains isolated from the air of the ward revealed staphylococci (82%), Gram negative bacilli (18%), fungi (17%), Gram positive diplococci (13%), and Bacillus subtilis (2.8%). 4. The strains isolated in the delivery-waiting room revealed staphylococci (66.7%), Gram negative bacilli (33.6%), and revealed staphylococci (75%), Gram positive diplococci (8.3%), and fungi (8.3%), in delivery room. 5. Most of strains isolated in the ward of O.B. & G.Y. revealed staphylococci (100.0%), Gram positive diplococci (8.3%), and Gram negative bacilli (6.7%). 6. The strain isolated in the surgical ward revealed staphylococci (91.7%), fungi (33.3%), Gram positive diplococci (25%), Gram negative bacilli (25%) and Bacillus subtilis (8.3%). 7. The strain isolated in the pediatric ward revealed staphylococci (75%), fungi (25%), Gram positive diplococci (8.3%), Bacillus subtilis (8.3%), and Gram negative bacilli (8.3%). 8. The strain isolated in the internal ward revealed staphylococci (91.7%), fungi (33.3%), Gram positive diplococci (25%), and negative bacilli (16.7%). The strains isolated from the nasal cavity of those doctors and nurses who and enaged in the ward of O.B. & G.Y. revealed staphylococci (80%), Bacillus subtilis (10%), and Gram negative bacilli (10%), from doctors and Gram positive diplococci (10%), instead of Gram negative bacilli (10％), from nurses. 10. The strain isolated from nasal cavity of parturient women on admission revealed staphylococci (90%), and Gram negative bacilli (10%), but after admission revealed staphylococci (70％), Gram positive diplococci (10%), and Gram negative bacilli (10%). 11. Of the total 91 staphylococci isolated from the air of the ward, the Coagulase pastive was 36 (39.6%), and the negative 55 (60.4%), As a result of the coagulase experiment of the staphylococci isolated from the nasal cavity of those who are engaged in the ward of O.B. ＆ G.Y. all were revealed as negative that belonged to non-pathogenic. 12. Consequence of the biochemic examination of the gram negative bacilli isolated from the air of the ward the aerobacter aerogens revealed was (16.7%) E-coli 5％ in the nasal cavity of those came and went to the of O.B. ＆ G.Y. and Aerobacter aerogens 7.5%.

• Membrane and Water Treatment
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• v.9 no.3
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• pp.195-203
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• 2018

N-acetylcysteine (NAC) has been widely used as an initial mucolytic agent and is generally used as an antioxidant to help alleviate various inflammatory symptoms. NAC reduces bacterial extracellular polymeric substances (EPS) production, bacterial adhesion to the surface and strength of mature biofilm. The efficacy has been shown to inhibit proliferation of gram-positive and gram-negative bacteria. In membrane bioreactor (MBR) processes, which contain a variety of gram negative bacteria, biofilm formation has become a serious problem in stable operation. In this study, use of NAC as an inhibitor of biofilm contamination was investigated using the center for disease control (CDC) reactors with MBR sludge. Biomass reduction was confirmed with CLSM images of membrane surfaces by addition of NAC, which was more efficient as the concentration of NAC was increased to 1.5 mg/mL. NAC addition also showed decreases in EPS concentrations of the preformed biofilm, indicating that NAC was able to degrade EPS in the mature biofilm. NAC addition was also effective to inhibit biofilm formation by MBR sludge, which consisted of various microorganisms in consortia.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.724-729
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• 2011

Information retrieval is a method to search the needed data by users. Generally, when a user searches some data in the large scale data set like the internet, ranking-based search is widely used because it is not easy to find the exactly needed data at once. In this paper, we propose a novel ranking-based search method based on sequence and adjacency relationship of user query by the help of TF-IDF and n-gram. As a result, it was possible to find the needed data more accurately with 73% accuracy in more than 19,000 data set.