• Journal of Powder Materials
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• v.24 no.3
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• pp.202-209
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• 2017

A cold-work tool steel powder is used to fabricate 3-dimensional objects by selective laser melting using a high-pressure gas atomization process. The spherical powder particles form continuous carbide networks among the austenite matrix and its decomposition products. The carbides comprise Nb-rich MC and Mo-rich $M_2C$. In the SLM process, the process parameters such as the laser power (90 W), layer thickness ($25{\mu}m$), and hatch spacing ($80{\mu}m$) are kept fixed, while the scan speed is changed from 50 mm/s to 4000 mm/s. At a low scan speed of 50 mm/s, spherical cavities develop due to over melting, while they are substantially reduced on increasing the speed to 2000 mm/s. The carbide network spacing decreases with increasing speed. At an excessively high speed of 4000 mm/s, long and irregularly shaped cavities are developed due to incomplete melting. The influence of the scan pattern is examined, for which $1{\times}1 mm^2$ blocks constituting a processing layer are irradiated in a random sequence. This island-type pattern exhibits the same effect as that of a low scan speed. Post processing of an object using hot isostatic pressing leads to a great reduction in the porosity but causes coarsening of the microstructure.

• Korean Journal of Veterinary Service
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• v.29 no.3
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• pp.277-285
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• 2006

Plasmids are covalently closed circular molecules of DNA that are stably inherited and replicate somewhat independently of the bacterial chromosome. Genes carried on plasmids can mediate a wide variety of important functions, including antibiotics (R plasmids) and heavy metals resistance, toxins production, cell penetration, iron chelation, complement resistance, and metabolic characteristics such as sucrose and lactose fermentation. Fifty strains of lactobacilli were isolated from 26 staters and 29 fermented milk products. They were classified 27 strains as Lactobacillus paracasei subsp paracasei, 11 stains as Lactococcus lactis subsp cremoris, 6 strains as L delbrueckii subsp lactis, 4 strains as L acidophius, and 2 strains as L delbrueckii subsp bulgaricus. All of these strains were examined for drug resistance and transferability of R plasmids. All of the isolates were sensitive to Am, C, CF, E, NB, P, T, and Te. But resistant to SXT 94% (47 strains), K 66% (33 strains), S 56% (28 strains), ENR 50% (25 strains), NOR 38% (19 strains) CIP 38% (19 strains), GM 16% (8 strains), and N 14% (7 strains), in order. And 32 different resistant patterns were found. The most frequently encountered patterns were CIP-ENR-K-NOR-S-SXT (5 strains). In vitro R plasmids transfer experiment, 57 antibiotic resistant strains which were not transfer to the recipient 2 Escherichia coli strains by conjugation, These results indicate that Lactobacillus in internal trade market' stater recognize R factor but transmissible R plasmid is not existed.

• Journal of Distribution Research
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• v.16 no.4
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• pp.1-27
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• 2011

Introduction: Sales of private labels(PU have been growing m recent years. Globally, PLs have already achieved 20% share, although between 25 and 50% share in most of the European markets(AC. Nielson, 2005). These products are aimed to have comparable quality and prices as national brand(NB) products and have been continuously eroding manufacturer's national brand market share. Stores have also started introducing premium PLs that are of higher-quality and more reasonably priced compared to NBs. Worldwide, many retailers already have a multiple-tier private label architecture. Consumers as a consequence are now able to have a more diverse brand choice in store than ever before. Since premium PLs are priced higher than regular PLs and even, in some cases, above NBs, stores can expect to generate higher profits. Brand extensions and private label have been extensively studied in the marketing field. However, less attention has been paid to the private label extension. Therefore, this research focuses on private label extension using the Multi-Attribute Attitude Model(Fishbein and Ajzen, 1975). Especially there are few studies that consider the hierarchical effect of the PL's two parent brands: store brand and the original PL. We assume that the attitude toward each of the two parent brands affects the attitude towards the extended PL. The influence from each parent brand toward extended PL will vary according to the perceived fit between each parent brand and the extended PL. This research focuses on how these two parent brands act as reference points to one another in the consumers' choice consideration. Specifically we seek to understand how store image and attitude towards original PL affect consumer perceptions of extended premium PL. How consumers perceive extended premium PLs could provide strategic suggestions for retailer managers with specific suggestions on whether it is more effective: to position extended premium PL similarly or dissimilarly to original PL especially on the quality dimension and congruency with store image. There is an extensive body of research on branding and brand extensions (e.g. Aaker and Keller, 1990) and more recently on PLs(e.g. Kumar and Steenkamp, 2007). However there are no studies to date that look at the upgrading and influence of original PLs and attitude towards store on the premium PL extension. This research wishes to make a contribution to this gap using the perceived fit difference between parent brands and extended premium PL as the context. In order to meet the above objectives, we investigate which factors heighten consumers' positive attitude toward premium PL extension. Research Model and Hypotheses: When considering the attitude towards the premium PL extension, we expect four factors to have an influence: attitude towards store; attitude towards original PL; perceived congruity between the store image and the premium PL; perceived similarity between the original PL and the premium PL. We expect that all these factors have an influence on consumer attitude towards premium PL extension. Figure 1 gives the research model and hypotheses. Method: Data were collected by an intercept survey conducted on consumers at discount stores. 403 survey responses were attained (total 59.8% female, across all age ranges). Respondents were asked to respond to a series of Questions measured on 7 point likert-type scales. The survey consisted of Questions that measured: the trust towards store and the original PL; the satisfaction towards store and the original PL; the attitudes towards store, the original PL, and the extended premium PL; the perceived similarity of the original PL and the extended premium PL; the perceived congruity between the store image and the extended premium PL. Product images with specific explanations of the features of premium PL, regular PL and NB we reused as the stimuli for the Question response. We developed scales to measure the research constructs. Cronbach's alphaw as measured each construct with the reliability for all constructs exceeding the .70 standard(Nunnally, 1978). Results: To test the hypotheses, path analysis was conducted using LISREL 8.30. The path analysis for verification of the model produced satisfactory results. The validity index shows acceptable results(${\chi}^2=427.00$(P=0.00), GFI= .90, AGFI= .87, NFI= .91, RMSEA= .062, RMR= .047). With the increasing retailer use of premium PLBs, the intention of this research was to examine how consumers use original PL and store image as reference points as to the attitude towards premium PL extension. Results(see table 1 & 2) show that the attitude of each parent brand (attitudes toward store and original pL) influences the attitude towards extended PL and their perceived fit moderates these influences. Attitude toward the extended PL was influenced by the relative level of perceived fit. Discussion of results and future direction: These results suggest that the future strategy for the PL extension needs to consider that positive parent brand attitude is more strongly associated with the attitude toward PL extensions. Specifically, to improve attitude towards PL extension, building and maintaining positive attitude towards original PL is necessary. Positioning premium PL congruently to store image is also important for positive attitude. In order to improve this research, the following alternatives should also be considered. To improve the research model's predictive power, more diverse products should be included in study. Other attributes of product should also be included such as design, brand name since we only considered trust and satisfaction as factors to build consumer attitudes.

• Journal of Food Hygiene and Safety
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• v.22 no.1
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• pp.45-51
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• 2007

The Collected 70 samples from 5 sandwich shops were analysed for the pathogenic bacteria such as Escherichia coli O157:H7, Salmonella spp., Listeria monocytogenes, and Staphylococcus aureus. As a result of Listeria monocytogenes and Saphylococcus aureus were detected in 1 sample, 11 samples, respectively. However, Escherichia coli O157:H7 and Salmonella spp. were not detected in anywhere. The antibiotics test of isolated bacteria was pelformed by the disk diffusion method from NCCLS. The resistance rate of Listeria monocytogenes isolates was confirmed 38.5% to 10 species such as Am, B, P, and Va for antibiotics of 26 species. MRSA was determinated 4 strains in S. aureus isolates. The resistance pattern of Staphylococcus aureus isolates were confirmed 36.4% to P Am OX B K E CXM, 18.2% to P Am B K E CXM B, 9.1% to P Am B K, 27.3% to P Am B, and 9.1% to Te B Nb. Therefore, continuous surveillance and monitoring for antibiotic resistance strains are demanded for prevention of increases in multiple antibiotic resistance strains.

• Proceedings of the Korean Fiber Society Conference
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• 1990.06b
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• pp.36-37
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• 1990

In the past, facile dissolution of cellulose has been hampered by the lack of suitable nondegrading solvents. Recently, this problem has been solved in our laboratory by the discovery of an inexpensive, convenient solvent system, that is the mixture of $NH_3\;and\;NH_4SCN$, for cellulose. Also, the $cellulose/NH_3/NH_4SCN$ solution system has been found to form the anisotropic, i.e., liquid crystalline phase. It is believed that both the cholesterio and the nematic phase occur. This finding has prompted extensive on-going researoh on the formation of the liquid crystalline phase from an inexpensive natural source such as cellulose since the nematic phase is envisioned as an excellent precursor sources for products with desirable properties, for example, high modulus and high strength. This interest naturally leads to a desire to understand the theological properties of the nematic phase so that the transformation of the nematic phase to the solid state with desirable properties can be efficiently accomplished, ;From this point of view, the theological behavior of the $cellulose/NH3_/NH_4SCN$ system has been studied as a function of shear rate and shear stress over a wide range of solvent compositions, cellulose concentration, centrifugation and urea contents, Results indicate that the viscosity decreases with increasing shear rate. A marked shear thinning behavior and a quasi-Newtonian behavior were observed in the low shear rate region and in the high shear rate region, respectively for all solvent compositions. The $cellulose/NH_3/NH_4SCN$ solution system only exhibited the viscosity increase with increasing cellulose concentration and failed to show the viscosity drop generally observed at the point of incipience of liquid crystal formation, This may be due to the gel-like nature of the solution by the association of the rodlike molecules into bundles which may serve as crosslinking points giving the cellulose solution a network structure. Also, simply hydrogen bonding may be so restrictive of molecular mobility that a viscosity drop is blocked. In addition to the above results, yield stress and thixotropy were also observed in the $cellulose/NH_3/NB_4SCN$ solution system which are characteristics of liquid crystal and gel, The results of the effect of centrifugation on viscosity show that viscosity decreases by the application of centrifugation. This may be explained by the change of the piled polydomain structure to the dispersed polydomain structure due to the pressure gradient generated during centrifugation.ation.

• The Journal of the Petrological Society of Korea
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• v.17 no.1
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• pp.16-35
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• 2008

We study metamorphism of metasedimetary rocks and origin and evolution of leucogranite form Samcheok area, northeastern Yeongnam massif, South Korea. Metamorphic rocks in this area are composed of metasedimentary migmatite, biotite granitic gneiss and leucogranite. Metasedimentary rocks, which refer to major element feature of siliclastic sediment, are divided into two metamorphic zones based on mineral assemblages, garnet and sillimanite zones. According to petrogenetic grid of mineral assemblages, metamorhpic P-T conditions are $740{\sim}800^{\circ}C$ at $4.8{\sim}5.8\;kbar$ in the garnet zone and $640-760^{\circ}C$ at 2.5-4.5kbar in sillimanite zone. The leucogranite (Imwon leucogranite) is peraluminous granite which has high alumina index (A/CNK=1.31-1.93) and positive discriminant factor value (DF > 0). Thus, leucogranite is S-type granite generated from metasedimentary rocks. Major and trace element diagram ($R_1-R_2$ diagram and Rb vs. Y+Nb etc.) show collisional environment such as syn-collisional or volcanic arc granite. Because Rb/sr ratio (1.8-22.9) of leucogranites is higher than Sr/Ba ratio (0.21-0.79), leucogranite would be derived from muscovite dehydrate melting in metasedimentary rocks. Leucogranites have lower concentration of LREE and Eu and similar that of HREE relative to metasedimentary rocks. To examine difference of REEs between leucogranites and metasedimentary rocks, we perform modeling using volume percentage of a leucogranite and a metasedimenatry rock from study area and REE data of minerals from rhyolite (Nash and Crecraft, 1985) and melanosome of migmatite (Bea et al., 1994). Resultants of modeling indicate that LREE and HREE are controlled by monazites and garnet, respectively, although zircon is estimated HREE dominant in some leucogranite without garnet. Because there are many inclusions of accessary phases such as monazite and zircon in biotites from metasedimentary rocks. leucogranitic magma was mainly derived from muscovite-breakdown in metasedimenary rocks. Leucogranites can be subdivided into two types in compliance with Eu anomaly of chondrite nomalized REE pattern; the one of negative Eu anomaly is type I and the other is type II. Leucogranites have lower Eu concetnrations than that of metasedimenary rocks and similar that of both type. REE modeling suggest that this difference of Eu value is due to that of components of feldspars in both leucogranite and metasedimentary rock. The tendency of major ($K_2O$ and $Na_2O$) and face elements (Eu, Rb, Sr and Ba) of leucogranites also indicate that source magma of these two types was developed by anatexis experienced strong fractionation of alkali-feldspar. Conclusionally, leucogranites in this area are products of melts which was generated by muscovite-breakdown of metasedimenary rock in environment of continetal collision during high temperature/pressure metamorphism and then was fractionated and crystallized after extraction from source rock.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.