• Food Science of Animal Resources
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• v.39 no.2
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• pp.309-323
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• 2019

Fish oil consists of omega-3 fatty acids which play an important role in human health. Its susceptibility to oxidation causes considerable degradation during the processing and storage of food products. Accordingly, encapsulation of this ingredient through freeze drying was studied with the aim of protecting it against environmental conditions. Gum arabic (GA) was used as the wall material for fish oil nanoencapsulation where tween 80 was applied as the emulsifier. A water-in-oil (W/O) emulsion was prepared by sonication, containing 6% fish oil dispersed in aqueous solutions including 20% and 25% total wall material. The emulsion was sonicated at 24 kHz for 120 s. The emulsion was then freeze-dried and the nanocapsules were incorporated into probiotic fermented milk, with the effects of nanocapsules examined on the milk. The results showed that the nanoparticles encapsulated with 25% gum arabic and 4% emulsifier had the highest encapsulation efficiency (EE) (87.17%) and the lowest surface oil (31.66 mg/100 kg). Using nanoencapsulated fish oil in fermented milk significantly (p<0.05) increased the viability of Lactobacillus plantarum as well as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) contents. The fermented milk sample containing fish oil nanoencapsulated with 25% wall material and 4% emulsifier yielded the greatest probiotic bacterial count (8.41 Log CFU/mL) and the lowest peroxide value (0.57 mEq/kg). Moreover, this sample had the highest EPA and DHA contents. Utilizing this nanoencapsulated fish oil did not adversely affect fermented milk overall acceptance. Therefore, it can be used for fortification of low fat probiotic fermented milk.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.154-162
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• 2018

The multiplier circuit is necessary to estimate degradation status of electronic cards in nuclear power plant, but its accuracy is not easy in processing those functions to multiply two input signals. What is important in multiplier circuit is that the multiplication result must be accurate and its linearity must be perfect. We developed and proposed excellent linearity multiplier circuit using operational amplifiers and transistor characteristics, and then proved its validity in this paper. We have made efforts to eliminate nonlinearity components of semiconductors with this circuit in order to ensure excellent linearity of developed multiplier circuit. We conducted multiplication operations through simulation, applying adequate values to each component in order to verify the circuit composed of that method. We showed step-by-step output signals, and then compared the logical analyses and measuring results as simulation results. We confirmed that this method is superior to existing multiplication or linearity.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.223-234
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• 2021

Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.

• The Journal of Advanced Prosthodontics
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• v.14 no.5
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• pp.273-284
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• 2022

PURPOSE. Computer-aided design and manufacturing (CAD-CAM) of implant abutments has been shown to result in surface contamination from site-specific milling and fabrication processes. If not removed, these contaminants can have a potentially adverse effect and may trigger inflammatory responses of the peri-implant tissues. The aim of the present study was to evaluate the bacterial disinfection and cleaning efficacy of ultrasonic reprocessing in approved disinfectants to reduce the microbial load of CAD-CAM abutments. MATERIALS AND METHODS. Four different types of custom implant abutments (total N = 32) with eight specimens in each test group (type I to IV) were CAD-CAM manufactured. In two separate contamination experiments, specimens were contaminated with heparinized sheep blood alone and with heparinized sheep blood and the test bacterium Enterococcus faecium. Abutments in the test group were processed according to a three-stage ultrasonic protocol and assessed qualitatively and quantitatively by determination of residual protein. Ultrasonicated specimens contaminated with sheep blood and E. faecium were additionally eluted and the dilutions were incubated on agar plates for seven days. The determined bacterial counts were expressed as colony-forming units (CFU). RESULTS. Ultrasonic reprocessing resulted in a substantial decrease in residual bacterial protein to less than 80 ㎍ and a reduction in microbiota of more than 7 log levels of CFU for all abutment types, exceeding the effect required for disinfection. CONCLUSION. A three-stage ultrasonic cleaning and disinfection protocol results in effective bacterial decontamination. The procedure is reproducible and complies with the standardized reprocessing and disinfection specifications for one- or two-piece CAD-CAM implant abutments.

• Genomics & Informatics
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• v.21 no.3
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• pp.40.1-40.11
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• 2023

Microbial community profiling using 16S rRNA amplicon sequencing allows for taxonomic characterization of diverse microorganisms. While amplicon sequence variant (ASV) methods are increasingly favored for their fine-grained resolution of sequence variants, they often discard substantial portions of sequencing reads during quality control, particularly in datasets with large number samples. We present a streamlined pipeline that integrates FastP for read trimming, HmmUFOtu for operational taxonomic units (OTU) clustering, Vsearch for chimera checking, and Kraken2 for taxonomic assignment. To assess the pipeline's performance, we reprocessed two published stool datasets of normal Korean populations: one with 890 and the other with 1,462 independent samples. In the first dataset, HmmUFOtu retained 93.2% of over 104 million read pairs after quality trimming, discarding chimeric or unclassifiable reads, while DADA2, a commonly used ASV method, retained only 44.6% of the reads. Nonetheless, both methods yielded qualitatively similar β-diversity plots. For the second dataset, HmmUFOtu retained 89.2% of read pairs, while DADA2 retained a mere 18.4% of the reads. HmmUFOtu, being a closed-reference clustering method, facilitates merging separately processed datasets, with shared OTUs between the two datasets exhibiting a correlation coefficient of 0.92 in total abundance (log scale). While the first two dimensions of the β-diversity plot exhibited a cohesive mixture of the two datasets, the third dimension revealed the presence of a batch effect. Our comparative evaluation of ASV and OTU methods within this streamlined pipeline provides valuable insights into their performance when processing large-scale microbial 16S rRNA amplicon sequencing data. The strengths of HmmUFOtu and its potential for dataset merging are highlighted.

• Journal of Animal Environmental Science
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• v.18 no.3
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• pp.257-266
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

• Korean Journal of Poultry Science
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• v.42 no.4
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• pp.347-352
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• 2015

This study was first conducted to investigate the effect of post-mortem storage time of chicken meat on the quality of chicken breast, and to determine whether the current grading rule that is 'using the chicken meat within 2 day post-mortem (PM)' is appropriate or not at meat processing plants. Different methods such as freshness, lightness ($L^*$), total number of microbes, 2-thiobarbituric acid reactive substances (TBARS), shear force and cooking loss were performed. Forty samples of different PM time (0~4 day) of chicken meat were stored in the refrigerator ($3^{\circ}C$). As a result of comparing the chicken meat of 2 day and 3 day PM, torrymeter value was 6.9 and 7.0, respectively. The other values are also as follows: lightness ($L^*$) 60.22 and 60.51, total number of microbes 4.20 and $4.31log_{10}CFU/g$, TBARS value 0.056 and 0.071 mg MDA/kg, shear force 1.43 and $1.59kg/cm^2$, and cooking loss 17.24 and 15.66%, respectively. As a result, these two groups were not significantly different (P<0.05). TBARS value of the chicken meat of 4 day PM was 0.088 mg MDA/kg which is significantly higher compared to 2~3 day PM (P<0.05). Thus, the result of the study suggests that using the chicken meat within 3 day PM is also possible. If the grading rule that is 'using the chicken meat within 2 day post-mortem (PM)' is changed to 3 day PM, it will allow processing plants and distributors to more flexibly use or distribute chicken meat.

• Microbiology and Biotechnology Letters
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• v.42 no.3
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• pp.267-274
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• 2014

High pressure processing (HPP) is a non-thermal method used to prevent bacterial growth in the food industry. Currently, pasteurization is the most common method in use for most milk processing, but this has the disadvantage that it leads to changes in the milk's nutritional and chemical properties. Therefore, the effects of HPP treatment on the microbiological and chemical properties of milk were investigated in this study. With the treatment of HPP at 600 MPa and $15^{\circ}C$ for 3 min, the quantity of microorganisms and lactic acid bacteria were reduced to the level of 2-3 log CFU/ml, and coliforms were not detected during a storage period of 15 d at $4^{\circ}C$. An analysis of milk proteins, such as ${\alpha}$-casein, ${\beta}$-casein, ${\kappa}$-casein, ${\alpha}$-lactalbumin, ${\beta}$-lactoglobulin by on-chip electorophoresis revealed that the electrophoretic pattern of the proteins from HPP-treated milk was different from that of conventionally treated commercial milk. While the quantities of vitamins and minerals in HPP-treated milk were seen to be comparable to amounts found in raw milk, the enzyme activity of lipase, protease and alkaline phosphatase after HPP treatment was reduced. These results suggest that HPP treatment is a viable method for the control of undesirable microorganisms in milk, allowing for minimal nutritional and chemical changes in the milk during the process.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.16-23
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• 2001

In this paper, we propose the pseudo n-gram language models for speech recognition with middle size vocabulary compared to large vocabulary speech recognition using the statistical n-gram language models. The proposed method is that it is very simple method, which has the standard structure of ARPA and set the word probability arbitrary. The first, the 1-gram sets the word occurrence probability 1 (log likelihood is 0.0). The second, the 2-gram also sets the word occurrence probability 1, which can only connect the word start symbol and WORD, WORD and the word end symbol . Finally, the 3-gram also sets the ward occurrence probability 1, which can only connect the word start symbol , WORD and the word end symbol . To verify the effectiveness of the proposed method, the word recognition experiments are carried out. The preliminary experimental results (off-line) show that the word accuracy has average 97.7% for 452 words uttered by 3 male speakers. The on-line word recognition results show that the word accuracy has average 92.5% for 20 words uttered by 20 male speakers about stock name of 1,500 words. Through experiments, we have verified the effectiveness of the pseudo n-gram language modes for speech recognition.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.407-416
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• 2003

As the usage of database systems dramatically increases and the amount of data pouring into them is massive, the performance administration techniques for using database systems effectively are getting more important. Especially in data warehouses, the performance management is much more significant mainly because of large volume of data and complex queries. The objectives and characteristics of data warehouses are different from those of other operational systems so adequate techniques for performance monitoring and tuning are needed. In this paper we extend functionalities of the DBMax, a performance administration tool for Oracle database systems, to apply it to data warehouse systems. First we analyze requirements based on summary management and ETL functions they are supported for data warehouse performance improvement in Oracle 9i. Then, we design architecture for extending DBMax functionalities and implement it. In specifics, we support SQL tuning by providing details of schema objects for summary management and ETL processes and statistics information. Also we provide new function that advises useful materialized views on workload extracted from DBMax log files and analyze usage of existing materialized views.