• Journal of Korea Trade
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• v.27 no.3
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• pp.147-160
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• 2023

Purpose - This paper aims to investigate the competitiveness and complementarity of the agricultural products trade between Korea and Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) countries. The study evaluates the opportunities and challenges that Korea's agricultural sector faces after joining the CPTPP, and suggests strategies to deepen cooperation and expand Korea's agricultural products trade. Design/methodology - To achieve these objectives, we analyze the trade competition and cooperation relationship between Korea and CPTPP countries in the agricultural products trade. This study uses data from Chapters HS1-24 in UN Comtrade from 2012 to 2022, and applies the indices of revealed comparative advantage, export similarity, and trade complementarity to examine the trade dynamics. Furthermore, we use an Autoregressive Integrated Moving Average (ARIMA) model to predict the agricultural products trade complementarity index between Korea and CPTPP countries from 2022 to 2031. Findings - The findings of our analysis reveal that Korea's agricultural products trade competitiveness is weak compared to that of CPTPP countries, and Korea's agricultural products are at a competitive disadvantage. On the whole, the similarity index of agricultural products trade exports between Korea and CPTPP countries is low, the structure of agricultural products export is quite different, and trade competition is relatively moderate. The trade complementarity index between Korea and CPTPP countries is generally high, with strong complementarity and a large space for cooperation and development. The ARIMA model shows that in the next ten years, although the agricultural products trade complementarity index fluctuates, but is generally high, there will still be a complementarity advantage in the future. Originality/value - This study is the first attempt to investigate the competitiveness and complementarity of the agricultural products trade between Korea and CPTPP countries. We also introduce an ARIMA model to forecast and analyze the future agricultural products trade complementarity index. Our study provides new perspectives and solutions for the future development of Korea's agricultural products trade after joining the CPTPP.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.333-333
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• 2006

We synthesized two novel polynorbornene derivatives, chiral poly(norbornene acid methyl ester) (C-PNME) and racemic poly(norbornene acid n-butyl ester) (R-PNME), which are potential low dielectric constant materials for applications in advanced microelectronic and display devices. Thin films of these polymers deposited on substrates were investigated by structural analyses using synchrotron grazing incidence X-ray scattering, specular reflectivity and ellipsometry. These analyses provided important information on the structure, electron density gradient across film thickness, chain orientation, refractive index and thermal expansion of the polymers in substrate-supported thin films. The structural characteristics and properties of the thin films were first dependent on the polymer chain' tacticity and further influenced by film thickness and thermal annealing.

• Korean Journal of Optics and Photonics
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• v.15 no.2
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• pp.171-176
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• 2004

A light deflector integrated laser diode(LD) was fabricated and the characteristics of LD and ourput beam deflection as a function of deflector injection current were measured. To integrate the deflector with LD, a passive waveguide was integrated with the LD and a triangular-type light deflector was fabricated on the upper clad of the passive waveguide section. Light deflection from the fabricated light deflector is controlled by the effective refractive index variation induced by carrier injection. To characterize the effect of the deflector injection current, threshold current, slope efficiency, and output beam spectrum were measured as a function of deflector injection current. From these measured data, the increment in the threshold current and the decrement of the slope efficiency were observed. However, the output beam spectrum was not affected by the deflector. The Beam Propagation Method(BPM) was used to simulate the proposed device and the light deflection was measured by the far-field pattern of the output beam as a function of the deflector injection current. In the fabricated deflector integrated LD, the deflection angle of 1.9$^{\circ}$ at the injection current of 15 ㎃ was obtained.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.32-32
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• 2018

Flora investigations in Korea have been conducted by many researchers for diverse purposes. Accumulated flora investigation data has not been utilized efficiently because there is no accessible database for comparison. To overcome this shortcoming, we constructed web-based database of flora investigation, named as the Integrated Korean Flora Database (IKFD; http://www.floradb.net/intro.php). Until now, 284 flora references (263 papers, 14 reports and books, and 7 unpublished papers written in between 1962 and 2017) were digitalized into the database. From 134,711 records, 4,301 species belonging to 228 families and 1,079 genera were identified via mapping with two major Korean plant species lists. Polygon areas originated from references were used for distribution of plant species, identifying precise distribution area. It will be a better index to show plant ecological characteristics. Collected micro-climate data provided by Korea Meteorology Administration were also integrated in IFKD for understanding correlation between distribution of plants and micro-climate. Cold hardiness zone which has been utilized for classifying climate zones. 12 out of 26 zones identified based on micro-climate data in Korea were mapped with distribution of plants. More than half species were appeared in zone 6a, 6b, 7a, and 7b. Taken together with these results, IKFD will be a fundamental platform for understanding plants in Korea flora investigation as well as a new standard for classifying distribution of plants. Moreover, Biodiversity Observation Database (BODB; http://www.biodiversitydb.info/intro.php) which integrates plant distribution data was also integrated for further studies.

• Journal of IKEEE
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• v.24 no.2
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• pp.409-418
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• 2020

In this paper, an integrated optical, evanescent-wave biosensor utilizing a multimode interferometer based on a Si₃N₄ rib-optical waveguide consisting of the Si/SiO₂/Si₃N₄/SiO₂ stacked structure was described. The theoretical background of the multimode interferometer was reviewed, and the structure and design process were presented through numerical computational analysis. We analyzed how the dimension (length, width) of the multimode interferometer affected the sensor performance. It has been confirmed through computational analysis that the changes in the refractive index of an analyte greatly affect the mode pattern formation position and output optical power of a multimode interferometer, and proved that this principle could be applied to integrated-optic biosensor.

• Korean Journal of Optics and Photonics
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• v.19 no.3
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• pp.224-228
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• 2008

A highly sensitive integrated photonic temperature sensor was proposed and developed incorporating a polymeric microring resonator. The change in the ambient temperature was estimated by observing the shift in the resonant wavelength of the resonator induced via the thermooptic effect. For the purpose of enhancing its sensitivity, the sensor was built by implementing a polymeric resonator exhibiting a high thermooptic coefficient on a silicon substrate with a small coefficient of thermal expansion. For the range of from $20^{\circ}C$ to $30^{\circ}C$ near the room temperature, the fabricated sensor yielded a sensitivity of as high as 165 ${\pm}/^{\circ}C$ and a resolution of better than $0.1^{\circ}C$. And its performance was found to be hardly affected by the variation in the refractive index of the target analyte, which was applied to the surface of the sensor. It is hence expected that the sensor could be integrated with other refractormetric optical sensors, thereby compensating for the fatal error caused by the change in the ambient temperature.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.1
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• pp.1-17
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• 2020

Three-dimensional microscopic approaches in histopathology display multiplex properties that present puzzling questions for specimens as related to their comprehensive volumetric information. This information includes spatial distribution of molecules, three-dimensional co-localization, structural formation and whole data set that cannot be determined by two-dimensional section slides due to the inevitable loss of spatial information. Advancement of optical instruments such as two-photon microscopy and high performance objectives with motorized correction collars have narrowed the gap between optical theories and the actual reality of deep tissue imaging. However, the benefits gained by a prolonged working distance, two-photon laser and optimized beam alignment are inevitably diminished because of the light scattering phenomenon that is deeply related to the refractive index mismatch between each cellular component and the surrounding medium. From the first approaches with simple crude refractive index matching techniques to the recent cutting-edge integrated tissue clearing methods, an achievement of transparency without morphological denaturation and eradication of natural and fixation-induced nonspecific autofluorescence out of real signal are key factors to determine the perfection of tissue clearing and the immunofluorescent staining for high contrast images. When performing integrated laboratory workflow of tissue for processing frozen and formalin-fixed tissues, clear lipid-exchanged acrylamide-hybridized rigid imaging/immunostaining/in situ hybridization-compatible tissue hydrogel (CLARITY), an equipment-based tissue clearing method, is compatible with routine procedures in a histopathology laboratory.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.21-26
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• 2008

A multi-geophysical surveys were carried out at Hwasan caldera which is located in Euisung Sub-basin. In order to overcome the limitation of the previous studies, dense gravity data and magnetotelluric (MT) data were obtained and integrated. In this study, the independent inversion models from gravity and MT method were integrated using a correlation and classification approaches to map geologic structure. The results of integration analysis indicated followings; 1) pyroclastic rocks around the central area of Hwasan caldera have lower density and resistivity when compared with those of neighborhood regions and are extended to around 1 km in depth, 2) the high resistivity and density intrusive igneous rocks are imaged around the ring fault boundary, and 3) the basement structure, which has low resistivity and high density, 5 km deep inferred by integration analysis. Also, for integration analysis, we suggested Structure Index method. This method is analyzed using Type Angle and Type Intensity, which are calculated by the spatial correlation of the physical properties. In this study, we can perform the integration analysis effectively using Structure Index method.

• Safety and Health at Work
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• v.15 no.1
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• pp.66-72
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• 2024

Background: This study examines the relationship between functional disability and work ability in workers affected by low back pain (LBP) through an analysis of correlations between the Oswestry Disability Index (ODI) and Work Ability Index (WAI). The role of personal and work factors on functional disability/work ability levels has also been studied. LBP is the most common musculoskeletal problem and a major disabling health problem worldwide. Its etiology is multifactorial. Multidisciplinary approaches may help reduce the burden of pain and disability and improve job continuity and reintegration at work. Methods: A cohort of 264 patients affected by LBP from an Italian outpatient clinic were included in a clinical diagnostic/therapeutic trial aiming at rehabilitation and return to work through an integrated investigation protocol. Data were collected during the first medical examination using anamnestic and clinical tools. The final sample is composed of 252 patients, 57.1% man, 44.0 % blue collars, 46.4% with the high school degree, 45.6% married. Results: WAI and ODI reported a negative and fair correlation (r = -0.454; p = .000). Workers with acute LBP symptoms have a higher probability of severe disability than those with chronic LBP symptoms. White collars without depressive symptoms reported higher work ability - even in chronic disability conditions-than those with depressive symptoms. Conclusion: The study found that ODI and WAI have a convergent validity and this suggests that the two tools measure capture distinctive aspects of disability related to personal, environmental, and occupational characteristics. The most important and modifiable prognostic factors found for ODI and WAI were depressive symptoms, workday absence, and intensity of back pain. The study also found a mild association between age and ODI. The study's findings highlight the importance of using a multidisciplinary approach to manage and prevent disability due to LBP.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.