• Applied Chemistry for Engineering
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• v.32 no.4
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• pp.461-466
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• 2021

In this article, a portable and cost-effective voltammetric biosensor with nanoparticles was developed for the measurements of heterogeneous nuclear ribonucleoprotein A1 protein (hnRNP A1) biomarker which can potentially be used for lung cancer diagnosis. Gold nanoparticles were first electrodeposited onto screen printed carbon electrode (SPCE) followed by immobilizing a single stranded DNA aptamer specific to hnRNP A1 onto the electrode surface. Ethanolamine was also used when immobilizing DNA aptamer on the surface to prevent signals from non-specific adsorption events. Sequential injection of hnRNP A1 biomarker and anti-hnRNP A1 conjugated with alkaline phosphatase (ALP) onto the aptamer chip surface allows to form the sandwich complex of DNA aptamer/hnRNP A1/ALP-anti-hnRNP A1 on the electrode surface which further reacted with 4-aminophenyl phosphate (APP). The electrocatalytic reaction of the enzyme, ALP, and the substrate, APP, resulting in the oxidative current response changes at -0.05 and -0.17 V (vs. Ag/AgCl) against the hnRNP A1 concentration was measured using cyclic and differential pulse voltammetry, respectively. The Au nanoparticles-integrated voltammetric biosensor was applied to analyze human normal serum solutions possibly suggesting potential applicability for lung cancer diagnosis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.1-10
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• 2021

In this study, a circular pipe can be installed by suction pressure for construction on soft ground with a low-water level. A series of laboratory-scale model tests were conducted in sandy ground to comprehend the suction pressure of the circular pipe in low-water levels. For repeated tests on saturated sandy soil, a container was mounted with three vibration generators on the floor. A repetitive vibration was applied using the vibration system for ground compaction. In the model tests, different diameters and thicknesses on saturated sandy soil with a water depth were considered. The result showed that the suction pressure increased with increasing penetration depth of the circular pipe. Moreover, the suction pressure required to penetrate the pipe decreased with increasing diameter. In the low-water level, the total suction pressure measured at the top lid increased because additional suction pressure is required to lift the water column. On the other hand, this led to a decrease in suction pressure to penetrate the circular pipe because the weight of the water column is applied as a dead load. Therefore, it is necessary to consider the water level to design the required suction pressure accurately.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.22-31
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• 2021

Surface image velocimetry (SIV) is a noncontact velocimetry technique based on images. Recently, studies have been conducted on surface velocity measurements using drones to measure a wide range of velocities and discharges. However, when measuring the surface velocity using a drone, reference points must be included in the image for image correction and the calculation of the ground sample distance, which limits the flight altitude and shooting area of the drone. A technique for calculating the surface velocity that does not require reference points must be developed to maximize spatial freedom, which is the advantage of velocity measurements using drone images. In this study, a technique for calculating the surface velocity that uses only the drone position and the specifications of the drone-mounted camera, without reference points, was developed. To verify the developed surface velocity calculation technique, surface velocities were calculated at the Andong River Experiment Center and then measured with a FlowTracker. The surface velocities measured by conventional SIV using reference points and those calculated by the developed SIV method without reference points were compared. The results confirmed an average difference of approximately 4.70% from the velocity obtained by the conventional SIV and approximately 4.60% from the velocity measured by FlowTracker. The proposed technique can accurately measure the surface velocity using a drone regardless of the flight altitude, shooting area, and analysis area.

• Journal of the Korean Geotechnical Society
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• v.23 no.12
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• pp.61-73
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• 2007

As a part of Load and Resistance Factor Design(LRFD) code development in Korea, in this paper an intensive reliability analysis was performed to evaluate reliability levels of the two static bearing capacity methods for driven steel pipe piles adopted in Korean Standards for Structure Foundations by the representative reliability methods of First Order Reliability Method(FORM) and Monte Carlo Simulation(MCS). The resistance bias factors for the two static design methods were evaluated by comparing the representative measured bearing capacities with the design values. In determination of the representative bearing capacities of driven steel pipe piles, the 58 data sets of static load tests and soil property tests were collected and analyzed. The static bearing capacity formula and the Meyerhof method using N values were applied to the calculation of the expected design bearing capacity of the piles. The two representative reliability methods(FORM, MCS) based computer programs were developed to facilitate the reliability analysis in this study. Mean Value First Order Second Moment(MVFOSM) approach that provides a simple closed-form solution and two advanced methods of FORM and MCS were used to conduct the intensive reliability analysis using the resistance bias factor statistics obtained, and the results were then compared. In addition, a parametric study was conducted to identify the sensibility and the influence of the random variables on the reliability analysis under consideration.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.147-160
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• 2008

This paper presents the results of full-scale loading tests performed on 54 passive anchors and 4 group anchored footings grouted to various lengths at several sites in Korea. The test results, the failure mechanisms as well as uplift capacities of rock anchors depend mostly on rock type and quality, embedded fixed length, properties of the discontinuities, and the strength of rebar. Anchors in poor quality rocks generally fail along the grout/rock interfaces when their depths are very shallow (a fixed length of less than 1 m). However, even in such poor rocks, we can induce a more favorable mode of rock pull-up failure by increasing the fixed length of the anchors. On the other hand, anchors in good quality rocks show rock pull-up failures with high uplift resistance even when they are embedded at a shallow depth. Laboratory test results revealed that a form of progressive failure usually occurs starting near the upper surface of the grout, and then progresses downward. The ultimate tendon-grout bond strength was measured from $18{\sim}25%$ of unconfined compressive strength of grout. One of the important findings from these tests is that the measured strains along the corrosion protection sheath were so small that practically the reduction of bond strength by the presence of sheath would be negligible. Based on test results, the main parameters governing the uplift capacity of the rock anchor system were determined. By evaluation of the ultimate uplift capacity of anchor foundations in a wide range of in situ rock masses, rock classification suitable for a transmission tower foundation was developed. Finally, a very simple and economical design procedure is proposed for rock anchor foundations subjected to uplift tensile loads.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.123-138
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• 2022

In order to improve ScienceON as a customized portal for MZ generation, this study investigated the characteristics of MZ generation's use of information portals and the demand for ScienceON to derive ways to improve ScienceON. To this end, a survey was conducted on Generation MZ who had experience using ScienceON, and the direction of improvement of ScienceON was derived. The ScienceON improvement plan proposed in this study is as follows. First, it is necessary to derive a plan to be familiar with the MZ generation for the MZ generation seeking familiarity and convenience. Second, it is necessary to improve the portal, such as arranging intuitive menus and providing convenient information, and various ways such as improving design and UI and reorganizing functions provided by ScienceON are needed. Third, it is necessary to promote the spread of Science ON by providing content through various platforms such as SNS and YouTube. In the future, as interest in the MZ generation continues to increase, analysis studies on the characteristics and demand of the MZ generation are expected to increase. Therefore, this study can be used as basic data for research on MZ generation, and it is expected that it can be used as a reference for the demand for information search and services of MZ generation.

• Korean Journal of Ecology and Environment
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• v.56 no.2
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• pp.161-171
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• 2023

The medium-large cladoceran species Simocephalus spp. predominantly occur in habitats with developed aquatic vegetation. Accordingly, due to Simocephalus' high contribution to zooplankton community biomass in the lake's littoral zone and wetland habitats, estimating their biomass is important to understand the matter cycling based on biological interactions within the aquatic food web. In this study, we reviewed the length-weight regression equations used previously to estimate Simocephalus biomass, directly measured S. serrulatus' body specification (length, width and area) and their biomass(dry weight) using instruments such as a microscopic digital camera and a microscale, and performed regression analysis between each other. When S. serrulatus biomass was estimated using the equation (Kawabata and Urabe, 1998) presented in 『Biomonitoring Survey and Assessment Manual』, Korea, errors between estimates and measures were relatively large compared to the S. serrulatus species-specific biomass estimate equation developed by Lemke and Benke (2003). In addition, both equations showed not only increasing trends in error (estimate-measure) with increasing S. serrulatus' body length, but also in error variance among similar-sized individuals. The results of regression analysis with dry weight by body specifications indicated that the most appropriate equation for estimating the biomass of S. serrulatus was derived from the width-dry weight exponential regression equation (R²=0.9555). The review and development study of such species-specific biomass estimation equations for zooplankton can be used as a tool to understand their role and function in aquatic ecosystem food webs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.119-130
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• 2009

Seismic fragility curves of a structure represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity such as peak ground acceleration (PGA), spectral acceleration ($S_a$) and spectral displacement ($S_d$). So those are very essential to evaluate the structural seismic performance and seismic risk. The purpose of this paper is to develop seismic fragility curves for PSC box girder bridges. In order to construct numerical fragility curve of bridge structure using nonlinear time history analysis, a set of ground motions corresponding to design spectrum are artificially generated. Assuming a lognormal distribution, the fragility curve is estimated by using the methodology proposed by Shinozuka et al. PGA is simple and generally used parameter in fragility curve as ground motion intensity. However, the PGA has not good relationship with the inelastic structural behavior. So, $S_a$ and $S_d$ with more direct relationship for structural damage are used in fragility analysis as more useful intensity measures instead of PGA. The numerical fragility curves based on nonlinear time history analysis are compared with those obtained from simple method suggested in HAZUS program.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.91-98
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• 2024

With the advancement of ICT (Information and Communication Technology), searching for judgments through the internet has become increasingly convenient. However, predicting sentencing based on judgments remains a challenging task for individuals. This is because sentencing involves a complex process of applying aggravating and mitigating factors within the framework of legal provisions, and it often depends on the subjective judgment of the judge. Therefore, this research aimed to develop a model for predicting sentencing using artificial intelligence by focusing on structuring the data from judgments, making it suitable for AI applications. Through theoretical and statistical analysis of previous studies, we identified variables with high explanatory power for predicting sentencing. Additionally, by analyzing 50 legal judgments related to serious crimes that are publicly available, we presented a framework for extracting essential information from judgments. This framework encompasses basic case information, sentencing details, reasons for sentencing, the reasons for the determination of the sentence, as well as information about offenders, victims, and accomplices evident within the specific content of the judgments. This research is expected to contribute to the development of artificial intelligence technologies in the field of law in the future.

• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.