• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.5-14
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• 2024

PHC piles demonstrate superior resistance to compression and bending moments, and their factory-based production enhances quality assurance and management processes. Despite these advantages that have resulted in widespread use in civil engineering and construction projects, the design process frequently relies on empirical formulas or N-values to estimate the soil-pile friction, which is crucial for bearing capacity, and this reliance underscores a significant lack of experimental validation. In addition, environmental factors, e.g., the pH levels in groundwater and the effects of seawater, are commonly not considered. Thus, this study investigates the influence of vibrating machine foundations on PHC pile models in consideration of the effects of varying pH conditions. Concrete model piles were subjected to a one-month conditioning period in different pH environments (acidic, neutral, and alkaline) and under the influence of seawater. Subsequent repeated direct shear tests were performed on the pile-soil interface, and the disturbed state concept was employed to derive parameters that effectively quantify the dynamic behavior of this interface. The results revealed a descending order of shear stress in neutral, acidic, and alkaline conditions, with the pH-influenced samples exhibiting a more pronounced reduction in shear stress than those affected by seawater.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.749-758
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• 2004

In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.

• Journal of the Korean Society of Food Culture
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• v.21 no.6
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• pp.653-660
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• 2006

Some quality characteristics of tofu prepared with cuttlefish ink were investigated to study the effects of various of coagulants. Each concentration of coagulant was determined as 0.2% of GDL, 0.3# of $MgCl_2$, 1%^ of $CaCl_2$, 1.5% of $CaSO_4$ and 0.6% D-gluconic acid calcium by pre-experiment. Also, the optimum concentration of added cuttlefish ink was chosen as 3%(diluted in twenty times). The yield of inky tofu prepared with GDL as coagulant was the highest. According to prepared with $MgCl_2$ was the highest. The result of microstructure was examined by SEM, the particles of inky tofu coagulated with GDL and D-gluconic acid calcium were small and uniformity. In overall acceptability of sensory properties, inky tofu coagulated with GDL was the highest in score. In the color of inky tofu, L value and a value were the highest coagulated with GDL, but that coagulated with $CaCl_2$ had the highest b value. In the texture properties of inky tofu, hardness, gumminess and brittleness were the highest coagulated with D-gluconic acid calcium. A positive correlation was observed between the pH of tofu whey and acidity. Sensory properties of roasted nutty flavor, hardness, cohesiveness and springiness were positively correlated with the acceptability.

• Korean journal of food and cookery science
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• v.22 no.6 s.96
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• pp.774-782
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• 2006

Flavor components in fresh Codonopsis lanceolata cultivated on a wild hill were detected by headspace sampling(HSS) method and GC-MS equipped with a VB-5(5% phenylmethyl polysiloxane) column. The 167 volatile compounds that were detected, consisted of 28 terpenes and terpene alcohols, 34 hydrocarbon, 31 alcohols, 13 aldehydes and ketones, 25 esters, 6 acids, 10 ethers and 20 miscellaneous components. The ten major volatile flavor components, comprising about 58% of the total, were dl-limonene (10.2%), ${\alpha}$-guaiene (9.0%), 2,2,6-trimethyl-octane (8.6%), hexadecane (8.0%), isolongifolan-8-ol (4.2%), 2,4,4-trimethyl-1,3-pentanediol diisobutyrate (4.1%), ${\beta}$-selinene (3.9%), 2,2,3-trimethylnonane (3.6%), 3-methyl-5-propyl-nonane (3.1%), and ledene (3.1%). The unique aroma of fresh Codonopsis lanceolata described by sensory evaluation was green, earthy, camphoraceous and aldehydic. The components attributed to green or camphoraceous flavor such as 1-hexanol, 2-methylhexan-3-ol, 3-hexen-1-ol, cis-3-hexenyl butyrate, ethylhexanol, hexyl acetate, trans-2-hexen-1-ol, camphor, longiborneol and menthol were not included in the ten or twenty major volatile components which had the largest peak area in descending order. We concluded that the intensity of green and camphoraceous flavor might be used as an indicator of the freshness of Codonopsis lanceolata.

• Journal of the Korean Wood Science and Technology
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• v.37 no.6
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• pp.505-516
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• 2009

The effects of wood species, particle size of wood flours and coupling treatment on the mechanical properties of wood plastic composites (WPC) are investigated in this study. Chemical components of wood flour from 3 different wood species were analyzed by the chemical analysis. Wood flours of 40~60 mesh and 80~100 mesh were manufactured from Larix (Larix kaempferi Lamb.), Quercus (Quercus accutisima Carr.), and Maackia (Maackia amuresis Rupr. et Maxim). The wood flours were reinforced into polypropylene (PP) by melt compounding and injection molding, then tensile, flexural, and impact strength properties were analyzed. The order of alpha-cellulose content in wood is Quercus (43.6%), Maackia (41.3%) and Larix (36.2%). The order of lignin content in wood is Larix (31.6%), Maackia (24.7%), and Quercus accutisima (24.4%). The content of extractives in wood is in the order of Larix (8.5%), Maackia (4.4%), and Quercus accutisima (3.9%). As the content of alpha-cellulose increases and the lignin and extractives decreases, tensile and flexural strengths of the WPC increase. At the same loading level of wood flours, the smaller particle size (80~100 mesh) of wood flours showed highly improved tensile and flexural strengths, compared to the larger one (40~60 mesh). The impact strength of the WPC was not significantly affected by the wood species, but the wood flours of larger particle size showed better impact strengths. The addition of maleated polypropylene (MAPP) provided the highly improved tensile, flexural and impact strengths. Morphological analysis shows improved interfacial bonding with MAPP treatment for the composites.

• Journal of the korean academy of Pediatric Dentistry
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• v.44 no.3
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• pp.335-340
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• 2017

Composite resin becomes an essential material in pediatric dentistry. However, incremental filling of composite resin to minimize the polymerization shrinkage takes time. To reduce the polymerization shrinkage, clinicians and researchers have focused on bulk-filling materials. Bulk-base composite resin is newly introduced as bulk-filling composite resin. The purpose of this study was to evaluate microhardness profile of bulk-base composite resin according to the depth of cure. A high flow bulk-base material and a low flow bulk-base material were used for experimental group, and a conventional composite resin was used for control group. Each group consist of 20 specimens, $3.5{\times}3.5{\times}5.0mm$ mold was used to make specimen. Specimens were sectioned at the 2 mm and the 3 mm depth with milling machine. Microhardness profile was measured at the surface, 2 mm depth, 3 mm depth, and 4 mm depth. Microhardness of control group showed statistically significant difference (p < 0.05) according to the polymerization depth. In contrast, experimental group showed no statistically significant difference, except between 0 mm and 4 mm at HFB, 0 mm and 2 mm, 0 mm and 3 mm at MFB. At the surface and the 2 mm depth, the control group showed higher microhardness than the experimental groups (p < 0.05). However, at the 4 mm depth, the experimental groups showed significantly higher microhardness (p < 0.05). The results from this study, the bulk-base composite resin showed higher microhardness at the 4 mm and lower microhardness at the surface and the 2 mm depth. Therefore, if bulk-base resin overcomes the mechanical weakness, it could be considered using in pediatric dentistry.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.101-113
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• 2021

In this paper, we introduce a speaker overlap system and look at the process of converting the existed system on the specific framework of artificial intelligence. Speaker overlap is when two or more speakers speak at the same time during a conversation, and can lead to performance degradation in the fields of speech recognition or speaker recognition, and a lot of research is being conducted because it can prevent performance degradation. Recently, as application of artificial intelligence is increasing, there is a demand for switching between artificial intelligence frameworks. However, when switching frameworks, performance degradation is observed due to the unique characteristics of each framework, making it difficult to switch frameworks. In this paper, the process of converting the speaker overlap detection system based on the Keras framework to the pytorch-based system is explained and considers components. As a result of the framework switching, the pytorch-based system showed better performance than the existing Keras-based speaker overlap detection system, so it can be said that it is valuable as a fundamental study on systematic framework conversion.

• Korean journal of food and cookery science
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• v.16 no.6
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• pp.593-601
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• 2000

Seven domestic wheat cultivars, Suwon 261, Suwon 265, Eunpa, Kobun, Alchan, Olgru, and Kumgang, and a standard wheat, ASW(Australian Standard White Wheat), were compared in noodle-making properties. The ash contents of domestic wheats and flours were 0.1-0.3% higher than that of ASW. Therefore, domestic wheats required the control of ash contents during milling process. The protein contents which suggest the flour gluten content were 10.32, 11.3, and 9.57% in Suwon 261, Suwon 265, and Kumgang cultivars, respectively. Valorimeter values of Eunpa, Olgru, and Kumgang which indicate the dough formation time and stability were similar to that of ASW. Resistance rate of domestic wheats was lower than that of ASW. Maximum viscosity in Amylograph for Eunpa, Olgru, and Kumgang were in the range of 500-800BU, which were suitable for making noodles. Increase in weight and volume of Olgru noodle was negatively correlated with protein content. Turbidity was not positively correlated with weight and volume increase, but domestic cultivars except Suwon 265 and Eunpa showed a similar turbidity with ASW. The mechanical properties of wet and dry noodles were evaluated by TPA test before and after cooking. Springiness and cohesiveness of wet noodles increased by cooking, and the domestic cultivars showed higher values than ASW. Springiness and cohesiveness of dry noodle were not increased by cooking in any cultivars. Gumminess, chewiness and hardness of domestic wheat cultivars showed higher values than that of ASW. In the tensile test, wet noodles showed no difference between domestic cultivars and ASW. But dry noodles of domestic wheat cultivars showed higher values than ASW. In the color test for lightness, redness and yellowness, there were no differences between flour and dough of domestic wheat cultivars and ASW. In the sensory evaluation, Kumgang wheat cultivar was the most preferred among the wet and dry noodles of other domestic wheat cultivars and ASW. These results suggested Kumgang wheat cultivar to be a practical wheat variety for noodle-making.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.3
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• pp.145-152
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• 2016

The objective of this study was to evaluate the mechanical quality of cultivars that could potentially be used to processed cooked rice. Proximate composition, amylose content, cooking quality, and the Toyo value, were higher in Jungsaenggold than in the other cultivars. The results showed that the crude protein contents of the rice cultivars were between 4.60 and 6.59%. The amylose content was the highest in the Haedam cultivar (21.36%), but was the lowest in the Jungsaenggold cultivar (17.11%). Cooking quality was the highest in the Haiami and Jungsaenggold cultivar. Texture analyzer test showed that Ilpum had the lowest hardness and highest stickiness. Significant differences in the palatability characteristics (Toyo results for glossiness quality) of the rice flour were recorded using a Toyo Meter Analyzer. Ilpum, Samkwang, Haiami and Jungsaenggold had low amylose contents and the highest Toyo values. Thus, the results of this study suggested that Jungsaenggold can be effectively used to produce processed cooked rice.