• Land and Housing Review
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• v.15 no.1
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• pp.147-156
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• 2024

This study aims to reduce CO₂ generated during the manufacturing process by using limestone (CaCO₃), a carbonate mineral used in the production of cement clinker, as a decarbonated raw material that does not contain CO₂. Among various industrial by-products, we attempted to use cement paste attached to waste concrete. In general, limestone for cement must have a CaCO₃ content of at least 80% (CaO, 44% or more) to ensure the quality of cement clinker. However, the CaO content of waste concrete fine powder is about 20% on average, so in order to use it as a cement clinker raw material, the CaO content must be increased to more than 35%. Therefore, by using the difference in hardness of the mineral composition of waste concrete fine powder to selectively crush CaO type minerals with relatively low hardness, classify and sieve, the CaO content can be increased by more than 35%. Accordingly, in this study, we experimentally and statistically reviewed and analyzed the optimal conditions for efficiently separating CaO and SiO₂ and other components by selectively pulverizing minerals containing relatively low CaO through a grinding process. As a result of the optimal grinding conditions experiment, it was found that the optimal conditions were a grinding time of less than 5 minutes, a type of material to be crushed of 30 mm, and an amount of material to be crushed of 1.0 or more. However, it is judged that it is necessary to review pulverized materials of mixed particle sizes rather than pulverized products of single particle size.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.30 no.2
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• pp.101-106
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• 2024

Current cold chain logistics relying on organic or eutectic materials within the 2~8℃ range as secondary fluids often face limitations in heat storage capacity, necessitating high energy consumption and large volume capacity. An effective approach to address this challenge is by incorporating polymers to enhance the heat storage capacity of eutectic materials. In this study, we investigated the impact of polyethylene glycols (PEGs) on phase change materials using Fourier transform infrared spectroscopy (FT-IR), differential scanning calorimeter (DSC), analyses of endothermic and exothermic phase change processes, and an accelerated thermal cycling test. Our findings indicate that the introduction of PEGs into the phase change materials can lead to improvements in latent heat, thermal conductivity, and 2~8℃ retention time. This enhancement is attributed to the high latent heat and thermal conductivity of the polymer, along with its ability to inhibit crystal formation in the eutectic mixture.

• Clinical and Experimental Reproductive Medicine
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• v.35 no.2
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• pp.99-110
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• 2008

Objectives: Preimplantation genetic diagnosis (PGD) has become an assisted reproductive technique for couples carrying genetic conditions that may affect their offspring. Osteogenesis imperfecta (OI) is an autosomal dominant disorder of connective tissue characterized by bone fragility and low bone mass. At least 95% of cases are caused by dominant mutations in the COL1A1 or COL1A2. In this study, we report on our experience clinical outcomes with 5 PGD cycles for OI in two couples. Methods: Before clinical PGD, we assessed the amplification rate and allele drop-out (ADO) rate of alkaline lysis and nested PCR protocol using heterozygous patient's single lymphocytes in the pre-clinical diagnostic tests for OI. We performed 5 cycles of PGD for OI by nested PCR for the causative mutation loci, COL1A1 c.2452G>A and c.3226G>A, in case 1 and case 2, respectively. The PCR products were analyzed by agarose gel electrophoresis, restriction fragment length polymorphism (RFLP) analysis with HaeIII restriction enzyme in the case 1 and direct DNA sequencing. Results: We confirmed the causative mutation loci, COL1A1 c.2452G>A in case 1 and c.3226G>A in case 2. In the pre-clinical tests, the amplification rate was 94.2% and ADO rate was 22.5% in case 1, while 98.1% and 1.9% in case 2, respectively. In case 1, a total of 34 embryos were analyzed and 31 embryos (91.2%) were successfully diagnosed in 3 PGD cycles. Eight out of 19 embryos diagnosed as unaffected embryos were transferred in all 3 cycles, and in the third cycle, pregnancy was achieved and a healthy baby was delivered without any complications in July, 2005. In case 2, all 19 embryos (100.0%) were successfully diagnosed and 4 out of 11 unaffected embryos were transferred in 2 cycles. Pregnancy was achieved in the second cycle and the healthy baby was delivered in March, 2008. The causative locus was confirmed as a normal by amniocentesis and postnatal diagnosis. Conclusions: To our knowledge, these two cases are the first successful PGD for OI in Korea. Our experience provides a further demonstration that PGD is a reliable and effective clinical techniques and a useful option for many couples with a high risk of transmitting a genetic disease.

• Journal of Life Science
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• v.28 no.7
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• pp.835-840
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• 2018

Quantitative determination of the protein expression levels is one of the most important parts in assessment of the safety of foods derived from genetically modified (GM) crops. Overexpression of AtCYP78A7, a gene encoding cytochrome P450 protein, has been reported to improve tolerance to abiotic stress, such as drought and salt stress, in transgenic rice (Oryza sativa L.). In the present study, an enzyme-linked immunosorbent assay (ELISA) kit for diagnosing AtCYP78A7 protein including AtCYP78A7-specific monoclonal antibody was developed. GST-AtCYP78A7 recombinant protein was induced and purified by affinity column. Four monoclonal antibodies (mAb 6A7, mAb 4C2, mAb 11H6, and mAb 7E8) against recombinant protein were also produced and biotinylated with avidin-HRP. After pairing test using GST-AtCYP78A7 protein and lysate of rice samples, mAb 4C2 and mAb 7E8 were selected as a capture antibody and a detecting antibody, respectively, for ELISA kit. Product test using rice samples indicated that percentages of detected protein in total protein were greater than 0.1% in AtCYP78A7-overexpressing transgenic rice (Line 10B-5 and 18A-4), whereas those in negative control non-transgenic rice (Ilpum and Hwayoung) were less than 0.1%. The ELISA kit developed in this study can be useful for the rapid detection and safety assessment of transgenic rice overexpressing AtCYP78A7.

• Journal of the Korean Magnetics Society
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• v.15 no.6
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• pp.315-319
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• 2005

To obtain low switching field ($H_{SW}$) we introduced amorphous ferromagnetic $Co_{70.5}Fe_{4,5}Si_{15}B_{10}$ single and synthetic antiferromagnet (SAF) free layers in magnetic tunnel junctions (MTJs). The switching characteristics for MTJs with structures $Si/SiO_2/Ta$ 45/Ru 9.5/IrMn 10/CoFe 7/AlOx/CoFeSiB 7 or CoFeSiB (t)/Ru 1.0/CoFeSiB (7-t)/Ru 60 (in nm) were investigated and compared to MTJs with $Co_{75}Fe_{25}$ and $Ni_{80}Fe_{20}$ free layers. CoFeSiB showed a lower saturation magnetization of $560 emu/cm^3$ and a higher anisotropy constant of $2800\;erg/cm^3$ than CoFe and NiFe, respectively. An exchange coupling energy ($J_{ex}$) of $-0.003erg/cm^2$ was observed by inserting a 1.0 nm Ru layer in between CoFeSiB layers. In the CoFeSiB single and SAF free layer MTJs, it was frond that the size dependence of the $H_{SW}$ originated from the lower $J_{ex}$ experimentally and by micromagnetic simulation based on the Landau-Lisfschitz-Gilbert equation. The CoFeSiB SAF structures showed lower $H_{SW}$ than that of NiFe, CoFe and CoFeSiB single structures. The CoFeSiB SAF structures were proved to be beneficial far the switching characteristics such as reducing the coercivity and increasing the sensitivity in micrometer to submicrometer-sized elements.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.15-22
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• 2002

Transportation project appraisal should be precise in order to increase the social welfare and efficiency, and it has been evaluated by only a single criterion analysis such as benefit/cost analysis. However, this method cannot assess some qualitative items, and cannot get a proper solution for the clash of interests among various groups. Therefore, the multi-criteria analysis, which can control these problems, is needed, and then Saaty has developed one of these methods, AHP(Analytic Hierarchy Process) method. In AHP, the project is evaluated through weighted score of the criteria and the alternatives, which is surveyed by a questionnaire of specialists. It is based on some strict suppositions such as reciprocal comparison, homogeneity, expectation, independence relationship between multi-criteria, but supposing that each criterion has independence relation with others is too difficult in two reasons. First, in real situation, there cannot be perfect independence relationship between standards. Second, individuals, even though they are specialists of that area, do not feel the degree of independence relation as same as others. This paper develops a modified AHP method for solving this dependence relationship between multi-criteria. First of all. in this method, the degree of dependence relationship between multi-criteria that the specialist feels is surveyed and included to the weighted score of multi-criteria This study supposes three methods to implement this idea. The first model products the degree of dependence relationship in the first step for calculating the weighted score, and the others adjust the result of weighted score from the basic AHP method to the dependence relationship. One of the second methods distributes the cross weighted score to each standard by constant ratio, and the other splits them using Fuzzy measure such as Bel and Pl. Finally, in order to validate these methods, this paper applies them to evaluate the alternatives which can control public resentments against Korean rail path in a city area.

• Pediatric Infection and Vaccine
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• v.15 no.1
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• pp.45-51
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• 2008

Purpose : Better understanding of the epidemiology of Streptococcus pneumoniae affects preventive and therapeutic strategies for children with otitis media. This study was undertaken to examine the prevalence of pneumococcal serotypes causing otitis media in children. Methods : Pneumococcal isolates obtained from the ear discharge of children with otitis media between January 2001 and December 2006 were characterized by serotyping and antibiotic susceptibility testing. Results : There were 54 pneumococcal isolates from 54 children with otitis media. The median age of patients was 13 months, and the proportion of children <5 years old was 81%. The predominant serotypes, in order of decreasing frequency, were 19A (44%), 19F(28%), 6B (7%), 6A (4%), 9V (4%), and 1 (4%); 23 isolates (43%) belonged to types included in the heptavalent pneumococcal conjugate vaccine (PCV7). The proportion of serotype 19A and 19F accounted for 72% of overall pneumococcal isolates, which accounted for 84% of pneumococcal isolates from otorrhea of children <5 years old (vs 20% in children ${\geq}5$ years old, P<0.001). All serotypes isolated from 3 vaccinees of PCV7 were 19A. There was no significant diminution in otitis media caused by pneumococcal vaccine serotypes after the introduction of PCV7. The frequency of nonsusceptibility to penicillin, erythromycin, and trimethoprim-sulfamethoxazole was higher in serotype 19A than in other non-vaccine serotypes, respectively. The frequency of multiple drug resistance was 96% in serotype 19A, compared with 29% in other non-vaccine serotypes (P=0.001). Conclusion : 19A was the most common pneumococcal serotype causing otitis media and represented a large proportion of strains with multiple drug resistance in children younger than 5 years of age.

• Journal of the Korean Chemical Society
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• v.47 no.6
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• pp.614-618
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• 2003

$Sr_2Ru_{1-x}Cu_xO_{4-y}(0.0{\le}x{\le}0.5)$ compounds were prepared using a conventional solid state reaction. Based on the Rietveld refinements of X-ray diffraction results, it is revealed that $Sr_2Ru_{1-x}Cu_xO_{4-y}$ compounds are the single phases with K2NiF4 type tetragonal system in the range of 0=x=0.3, while the mixed phases of$Sr_2RuO_4$ and $Sr_2CuO_3$ in the range of $0.4{\le}x{\le}0.5$. By means of X-ray photoelectron spectroscopy, the valence states of Ru and Cu in $Sr_2Ru_{1-x}Cu_xO_{4-y}$, have been confirmed to 4+ and 2+, respectively. The bond length difference between $Ru-O_1 ({\times}4)\;and\;Ru-O_2 ({\times}2)\;in\;RuO_6$ octahedron is gradually decreased with increasing Cu content in $Sr_2Ru_{1-x}Cu_xO_{4-y}$, which results in the lower c/a ratio. So, it might be assured that the variation of local symmetry of $RuO_6$ octahedron is very closely related to the transporting property of $Sr_2Ru_{1-x}Cu_xO_{4-y}$ compounds. The behavior of resistivity discloses that the metallic property in $Sr_2RuO_4$ changes into the semiconducting one in proportion to the Cu content in $Sr_2Ru_{1-x}Cu_xO_{4-y}$.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.501-512
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• 2023

This study aimed to assess and determine the optimal model for predicting the full bloom date of 'Fuji' apples across South Korea. We evaluated the performance of four distinct models: the Development Rate Model (DVR)1, DVR2, the Chill Days (CD) model, and a sequentially integrated approach that combined the Dynamic model (DM) and the Growing Degree Hours (GDH) model. The full bloom dates and air temperatures were collected over a three-year period from six orchards located in the major apple production regions of South Korea: Pocheon, Hwaseong, Geochang, Cheongsong, Gunwi, and Chungju. Among these models, the one that combined DM for calculating chilling accumulation and the GDH model for estimating heat accumulation in sequence demonstrated the most accurate predictive performance, in contrast to the CD model that exhibited the lowest predictive precision. Furthermore, the DVR1 model exhibited an underestimation error at orchard located in Hwaseong. It projected a faster progression of the full bloom dates than the actual observations. This area is characterized by minimal diurnal temperature ranges, where the daily minimum temperature is high and the daily maximum temperature is relatively low. Therefore, to achieve a comprehensive prediction of the blooming date of 'Fuji' apples across South Korea, it is recommended to integrate a DM model for calculating the necessary chilling accumulation to break dormancy with a GDH model for estimating the requisite heat accumulation for flowering after dormancy release. This results in a combined DM+GDH model recognized as the most effective approach. However, further data collection and evaluation from different regions are needed to further refine its accuracy and applicability.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.