• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.1
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• pp.13-20
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• 1991

This paper describes the fish-density dependence of the mean backscattering strength with aggregations of encaged, free-swimming fish of known density in relation to the experimental verification of echo-integration technique for estimating the density of fish shoals. In this experiment, various numbers of gold crussian, Carassius burgeri burgeri, with a mean length of 18.5cm and a mean weight of 205.9g, were introduced into a net cage of approximately 0.76m super(3). During the backscattering measurements. the cage was suspended on the sound axis of the 50kHz transducer having a beam width of 33 degrees at -3dB downpoints. The volume backscattering strengths from fish aggregations were measured as a function of fish density. Data acquisition, processing and analysis were performed by means of the microcomputer-based sonar-echo processor including a FFT analyzer. The calibration of echo-sounder system was carried out at field with a steel ball bearing of 38mm in diameter having the target strength of -40.8dB. The dorsal-aspect target strengths on anesthetized specimens of gold crussian used in the cage experiment were measured and compared with the target strength predicted by the fish density-echo energy relationship for aggregations of free-swimming gold crussian in the cage. The results obtained can be summarized as follows: 1. The target strengths in the dorsal aspect on anesthetized specimens of gold crussian, with the mean length of 19.1cm and the mean weight of 210.5g, varied from -40.9dB to -44.8dB with a mean of -42.6dB. This mean target strength did not differ significantly from that predicted by the regression of echo energy on fish density of free-swimming gold crussian in the cage. It suggests that the target-strength measurements on anesthetized fish was valid and can be representative for live, free-swimming fish. 2. The relationship between mean backscattering strength(, dB) and distribution density of gold $crussian(\rho, $ fish/m super(3)) was expressed by the following equation; =-41.9+11 $Log(\rho)$ with a correlation coefficient of 0.97. This result support the existence of a linear relationship between fish density and echo energy, but suggest that this line has steeper slope than the regression by the theory of estimating the density of fish schools.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.6
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• pp.596-602
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• 2006

The effects of resin additives and inorganic compounds addition on the thermal decomposition of low density polyethylene(LDPE) resin have been studied in a thermal analyzer(TGA, DSC) and a small batch reactor. The silica-alumina type compounds tested were kaolinite, bentonite, perlite, diatomaceous earth, activated clay and clay. The resin additives were antiforgging-agent and longevity-agent. As the results of TGA experiments, addition of antifogging-agent, longevity-agent and clay increased the temperature of the maximum reaction rate($T_{max}$). The silica-alumina type inorganic materials increased the pyrolysis reraction rate in the order of activated clay, diatomaceous earth, bentonite, perlites, and kaolinite. In the DSC experiments, addition of antifogging-agent and clay decreased the heat of fusion and the heat of pyrolysis reaction. Bentonite decreased 20% of the heat of fusion and 25% of the heat of pyrolysis reaction. In the batch system experiments, the mixing of clay retarded the initial producing rate of fuel oil, but increased the yield of fuel oil. Addition of bentonite increased the yield of fuel oil from LDPE resin. Mixing of antifogging-agent and longevity-agent produced the fuel oil having lower carbon number. The amounts of the carbon number below 12 in fuel oil decreased with adding the clay. That below 23 in fuel oil increased with mixing of bentonite, perlite, kaolinite, and activated clay. But the mixing of diatomaceous earth did not affect the carbon contents of fuel oil from pure LDPE resin. In the silica-alumina type inorganic material used in this experiments, bentonite was the most effective from the pyrolysis heat, yields, and the characteristics of fuel oil.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Korean Chemical Engineering Research
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• v.53 no.6
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• pp.783-791
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• 2015

A fluidized-bed reactor with an inside diameter of 0.1 m and a height of 1.2 m was used to study the effect of steam and catalyst additions to air-blown biomass gasification on the production of producer gas. The equipment consisted of a fluidized bed reactor, a fuel supply system, a cyclone, a condenser, two receivers, steam generator and gas analyzer. Silica sand with a mean particle diameter of $380{\mu}m$ was used as a bed material and calcined dolomite ($356{\mu}m$), which is effective in tar reduction and producer gas purification, was used as the catalyst. Both of Korea wood pellet (KWP) and a pellet form of EFB (empty fruit bunch) which is the byproduct of Southeast Asia palm oil extraction were examined as biomass feeds. In all the experiments, the feeding rates were 50 g/min for EFB and 38 g/min for KWP, respectively at the reaction temperature of $800^{\circ}C$ and an ER (equivalence ratio) of 0.25. The mixing ratio (0~100 wt%) of catalyst was applied to the bed material. Air or an air-steam mixture was used as the injection gas. The SBR (steam to biomass ratio) was 0.3. The composition, tar content, and lower heating value of the generated producer gas were measured. The addition of calcined dolomite decreased tar content in the producer gas with maximum reduction of 67.3 wt%. The addition of calcined dolomite in the air gasification reduced lower heating value of the producer gas. However The addition of calcined dolomite in the air-steam gasification slightly increased its lower heating value.

• Korean Journal of Food Science and Technology
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• v.49 no.3
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• pp.304-310
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• 2017

The aim of this study was to compare the physicochemical properties of domestic and imported commercial plain wheat flour and dough. Four types of domestic wheat flour (DW; DW1-4) were compared to four types of imported wheat flour (IW; IW1-4). DWs exhibited lower moisture content, lightness (L), and whiteness, and higher protein content, redness (a), and yellowness (b), than those exhibited by IWs. Solvent retention capacity of DWs and IWs was similar; however, DWs showed higher gluten performance index. Pasting properties, analyzed by rapid visco analyzer (RVA), were similar for DW1, DW2, and IWs; however, DW3 and DW4 showed different RVA patterns. Considering that DW3 and DW4 were organic wheat flour, possible incorporation of damaged kernel might increase amylase activities resulting in decreased peak viscosity. Dough resistance (108.4-159.9 g) and extensibility (11.8-16.7 mm) of IWs were higher than those of DWs (78.0-118.7 g, 8.7-12.5 mm, respectively).

• Tuberculosis and Respiratory Diseases
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• v.66 no.3
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• pp.178-185
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• 2009

Background: Epigallocatechin-3-gallate (EGCG) is the major catechin in green tea, and has shown antiproliferative, antiangiogenic, antimetastatic and cell cycle pertubation activity in various tumor models. Hypoxia can be induced because angiogenesis is insufficient for highly proliferating cancer. Hypoxia-inducible factor-1$\alpha$ (HIF-1$\alpha$) and its downstream target, vascular endothelial growth factor (VEGF), are important for angiogenesis, tumor growth and metastasis. The aim of this study was to determine how hypoxia could cause changes in the cellular phenomena and microenvironment in a non-small cell culture system and to examine the effects of EGCG on a HIF-1$\alpha$ and VEGF in A549 cell line. Methods: A549 cells, a non-small cell lung cancer cell line, were cultured with DMEM and 10% fetal bovine serum. A decrease in oxygen tension was induced using a hypoxia microchamber and a $CO_2-N_2$ gas mixture. Gas analysis and a MTT assay were performed. The A549 cells were treated with EGCG (0, 12.5, 25, 50 ${\mu}mol/L$), and then examined by real-time-PCR analysis of HIF-1$\alpha$, VEGF, and $\beta$-actin mRNA. Results: Hypoxia reduced the proliferation of A549 cells from normoxic conditions. EGCG inhibited HIF-1$\alpha$ transcription in A549 cells in a dose-dependent manner. Compared to HIF-1$\alpha$, VEGF was not inhibited by EGCG. Conclusion: HIF-1$\alpha$ can be inhibited by EGCG. This suggests that targeting HIF-1$\alpha$ with a EGCG treatment may have therapeutic potential in non-small cell lung cancers.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.271-280
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• 2020

This study compared soil CO₂ efflux rates after fertilization, in Pinus densiflora and Quercus variabilis stands. Compound fertilizers were applied to the forest floor in March 2016, following a one-year calibration period (from March 2015 to February 2016). In situ soil CO₂ efflux rates were measured every month during the two-year study periods, using an infrared gas analyzer with a closed chamber system. Mean annual soil CO₂ efflux rates were higher following fertilizer application in the P. densiflora and Q. variabilis stands (P. densiflora: 2.180 μmol m^-2 s^-1; Q. variabilis: 1.977 μmol m^-2 s^-1) as compared with the rates measured during the calibration period (P. densiflora: 1.620 μmol m^-2 s^-1; Q. variabilis: 1.557 μmol m^-2 s^-1). The mean annual soil CO₂ efflux rates in the unfertilized treatments of both stands were not significantly different between the two-year study periods. The Q₁₀ values of fertilized treatments in Q. variabilis stands were higher in the fertilization period (3.41) than in the calibration period (3.14), whereas the Q₁₀ values in P. densiflora stands did not change between the fertilization and calibration periods. The Q₁₀ values of unfertilized treatments in the Q. variabilis stands were lower during the 2016-2017 period (3.69), than in the 2015-2016 period (3.85), whereas the Q₁₀ values in P. densiflora stands were higher during the 2016-2017 period (3.65), than in the 2015-2016 period (3.15). These results indicate that the increase in soil CO₂ efflux rates in P. densiflora stands could be more sensitive to fertilization compared with the rates in Q. variabilis stands.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.30 no.2
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• pp.181-187
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• 2004

Preparations of mesoporous materials using various templates and their applicability have been intensively investigated for many years. We studied on synthesizing mesoporous Ti02 with pores in which sensitive compounds having weak physico-chemical properties such as thermal or UV irradiation and low solubility in solvent are trapped. Prior to trapping OMC in the pores of mesoporous titania, OMC was nano-emulsified in O/W system using Lecithin. Thereafter the OMC was trapped in the pores of mesoporous titania using sol-gel method. Main focus of this work is to prepare OMC-trapped mesoporous titania and to trace the stability and solubility of nano-emulsified OMC in the pores of mesoporous titania, and compared with that of mesoporous silica. OMC-trapped mesoporous Inorganic-Organic hybrid titania showed higher factors in sun protecting and a skin penetration phenomenon was reduced.

• Economic and Environmental Geology
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• v.25 no.4
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• pp.397-416
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• 1992

In the present study, three clay deposits, named the Seongsan, Ogmaesan and Haenam deposits, were investigated. The altered zones are recognized in the hydrothermally altered rocks of the clay deposits from the center of the alteration to the margin: Kaolin, Kaolin-Quartz, Quartz, Sericite and Chlorite zones in the Seongsan deposits; Quartz zone, Alunite zone, Kaolin zone, Sericite zone and Chlorite zone in the Ogmaesan deposits; Quartz zone, Pyrophyllite zone, Sericite zone and Chlorite zone in the Haenam deposits. These zones can be grouped into two types of alteration: Acidic alteration such as Pyrophyllite zone, Alunite zone, Quartz zone, Kaolin zone, Kaolin-Quartz zone and a part of Sericite zone; Propylitic alteration such as Chlorite zone and a part of Sericite zone. All clay deposits belong to high-sulfidation (acid-sulfate) system. The rocks of the acidic alterations are composed of pyrophyllite, alunite, kaolin minerals, sericite, quartz and pyrite. On the basis of bulk chemical compositions, it was found that some components such as $SiO_2$, $TiO_2$, $Fe_2O_3$, FeO, MgO, CaO, $K_2O$ and $Na_2O$ were mobilized considerably from the original rocks. The mobility of these major elements is related to, and controls, mineral assemblages in each altered zone. Polytypes of sericite are determined as $2M_1$ and 1M by X-ray diffraction method. The amount of $2M_1$ is nearly equal to that of 1M in the Seongsan deposits whereas $2M_1$ is less and higher than that of 1M in the Ogmaesan and the Haenam deposits. These facts indicate that formation temperature of sericite is relatively high in the Haenam deposits, moderate in the Seongsan deposits, and low in the Ogmaesan deposits. The ratios of Na/(K+Na) for alunite in the Ogmaesan deposits determined by electron microprobe analyzer (EPMA) are higher than those in the Seongsan deposits. Thus, the alunite of the Ogmaesan deposits must have been formed from the solutions with relatively high aqueous Na/(K+Na) ratios and low pH at a high temperature rather than that of the Seongsan deposits. From all data, it is clarified that alunite is hypogene in origin, and has been formed by oxidation of hydrogen sulfide in the steam-heated environment, and that alunite has been produced by the spectacular solfataric alteration observed at the surface of some present-day hydrothermal systems.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.