• Wind and Structures
• /
• v.36 no.2
• /
• pp.75-90
• /
• 2023

Turbulent wind flow over hilly terrains has been extensively investigated in the scientific literature and main findings have been included in technical standards. In particular, turbulent wind flow over nominally two-dimensional hills is often adopted as a benchmark to investigate wind turbine siting, estimate wind loading, and dispersion of particles transported by the wind, such as atmospheric pollutants, wind-driven rain, windblown snow. Windblown sand transport affects human-built structures and natural ecosystems in sandy desert and coastal regions, such as transport infrastructures and coastal sand dunes. Windblown sand transport taking place around any kind of obstacle is rarely in equilibrium conditions. As a result, the modelling of windblown sand transport over complex orographies is fundamental, even if seldomly investigated. In this study, the authors present a wind-sand tunnel test campaign carried out on a nominally two-dimensional sinusoidal hill. A first test is carried out on a flat sand fetch without any obstacle to assess sand transport in open field conditions. Then, a second test is carried out on the hill model to assess the sand flux overcoming the hill and the morphodynamic evolution of the sand sedimenting over its upwind slope. Finally, obtained results are condensed into a dimensionless parameter describing its sedimentation capability and compared with values resulting from other nominally two-dimensional obstacles from the literature.

• Smart Structures and Systems
• /
• v.31 no.2
• /
• pp.183-197
• /
• 2023

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

• Microbiology and Biotechnology Letters
• /
• v.51 no.1
• /
• pp.69-82
• /
• 2023

Nitrilases are a hydrolase group of enzymes that catalyzes nitrile compounds and produce industrially important organic acids. The current objective is to optimize nitrilase production using statistical methods assisted with artificial intelligence (AI) tool from novel nitrile degrading isolate. A nitrile hydrolyzing bacteria Bacillus subtilis AGAB-2 (GenBank Ascension number- MW857547) was isolated from industrial effluent waste through an enrichment culture technique. The culture conditions were optimized by creating an orthogonal design with 7 variables to investigate the effect of the significant factors on nitrilase activity. On the basis of obtained data, an AI-driven support vector machine was used for the fitted regression, which yielded new sets of predicted responses with zero mean error and reduced root mean square error. The results of the above global optimization were regarded as the theoretical optimal function conditions. Nitrilase activity of 9832 ± 15.3 U/ml was obtained under optimized conditions, which is a 5.3-fold increase in compared to unoptimized (1822 ± 18.42 U/ml). The statistical optimization method involving Plackett Burman Design and Response surface methodology in combination with an AI tool created a better response prediction model with a significant improvement in enzyme production.

• Annual Conference of KIPS
• /
• 2010.11a
• /
• pp.287-290
• /
• 2010

오늘날 모바일 시장을 중심으로 다양한 플랫폼이 등장하면서 모바일 어플리케이션 개발 시 여러 플랫폼을 고려해야 하는 부담이 증대되고 있다. 이러한 상황에서 Model-Driven Development(MDD) 는 멀티플랫폼에 대응하는 어플리케이션 개발의 효율성을 높여줄 수 있다. 하지만 이 기법을 이용하는 대다수의 연구 결과들은 해당 방법론을 통해 생성된 결과물의 질을 객관적으로 평가할 수 없고, 이 때문에 해당 방법론의 성능 평가가 힘들다. 본 연구에서는 대상 플랫폼들이 제공하는 API 를 분석한 결과에 근거하여 공통 요소를 추출하고 이를 이용하여 MDD 기반으로 개발을 진행할 수 있는 개발 프로세스를 소개하고, 이를 통해 생성된 소스 코드의 기능적 유사도 및 코드 생성률과 기능적 유사도를 평가할 수 있는 방법을 제안한다. 이 방법은 코드를 AST 로 바꾸고 API 맵핑 테이블에 근거하여 동일한 키워드로 변환하고 유사도를 측정하여 설계 시 의도한 기능이 얼마나 잘 코드로 생성되었는 지 평가할 수 있는 방법이다. 본 연구에서는 이 방법을 이용하여 생성된 코드의 기능적 유사도와 코드 생성률을 측정하였다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.175-175
• /
• 2023

Detection and monitoring of wildfires are essential for limiting their harmful effects on ecosystems, human lives, and property. In this research, we propose a novel method running in the Google Earth Engine platform for identifying and characterizing burnt regions using a hybrid of Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (multispectral photography) images. The 2022 Uljin wildfire, the severest event in South Korean history, is the primary area of our investigation. Given its documented success in remote sensing and land cover categorization applications, we select the Random Forest (RF) method as our primary classifier. Next, we evaluate the performance of our model using multiple accuracy measures, including overall accuracy (OA), Kappa coefficient, and area under the curve (AUC). The proposed method shows the accuracy and resilience of wildfire identification compared to traditional methods that depend on survey data. These results have significant implications for the development of efficient and dependable wildfire monitoring systems and add to our knowledge of how machine learning and remote sensing-based approaches may be combined to improve environmental monitoring and management applications.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.47 no.4
• /
• pp.666-683
• /
• 2023

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.

• Advances in nano research
• /
• v.15 no.2
• /
• pp.175-189
• /
• 2023

The under-evaluation structure includes a functionally graded porous (FGP) core which is confined by two piezoelectric carbon nanotubes reinforced composite (CNTRC) layers. The whole structure rests on the Pasternak foundation. Using quasi-3D hyperbolic shear deformation theory, governing equations of a sandwich plate are driven. Moreover, face sheets are subjected to the electric field and the whole model is under thermal loading. The properties of all layers alter continuously along with thickness direction due to the CNTs and pores distributions. By conducting the current study, the results emerged in detail to assess the effects of different parameters on buckling of structure. As instance, it is revealed that highest and lowest critical buckling load and consequently stiffness, is due to the V-A and A-V CNTs dispersion type, respectively. Furthermore, it is revealed that by porosity coefficient enhancement, critical buckling load and consequently, stiffness reduces dramatically. Current paper results can be used in various high-tech industries as aerospace factories.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.4
• /
• pp.24-33
• /
• 1996

PLCs are vital components of modern automation systems, which have penetrated into almost every industry. Many industries have a demand for facilitation of PLC programming. In this study, a programning system for sequential control is developed on a personal computer. This programming system consists of two main parts, a GRAFCET editor and a GRAFCET compiler. The GRAFCET editor enables us to model an actual sequential process by a GRAFCET diagram. This GRAFCET editor is developed by the menu-driven method based on specific menus and graphic symbols. The GRAFCET compiler consists of two parts, a GRAFCET parser and a code generator. The possible errors in a drawn GRAFCET diagram are first checked by the GRAFCET parser which generates finally an intermediate code from a verified CRAFCET diagram. Then the intermediate code is converted into a control code of an actual sequential controller by the code generator. To show the usefulness of this programming system, this system is applied to a pneumatically controlled handling robot. For this robot, a Z-80 microprocessor is used as the actual sequential controller.

• Nuclear Engineering and Technology
• /
• v.54 no.12
• /
• pp.4759-4775
• /
• 2022

The RVACS is a versatile and robust safety system driven by two natural circulations: in-vessel coolant and ex-vessel air. To observe interaction between the two natural circulations, SINCRO-IT facility was designed with two different similarity laws simultaneously. Bo' based similarity law was employed for the in-vessel, while Ishii's similarity law for the ex-vessel excluding the radiation. Compared to the prototype, the sodium and air system, SINCRO-IT was designed with Wood's metal and air, having 1:4 of the length reduction, and 1.68:1 of the time scale ratio. For the steady state, RV temperature limit was violated at 0.8% of the decay heat, while the sodium boiling was predicted at 1.3%. It showed good accordance with the system code, TRACE. For an arbitrary re-criticality scenario with RVACS solitary operation, sodium boiling was predicted at 25,100 s after power increase from 1.0 to 2.0%, while the system code showed 30,300. Maximum temperature discrepancy between the experiments and system code was 4.2%. The design and methodology were validated by the system code TRACE in terms of the convection, and simultaneously, the system code was validated against the simulating experiments SINCRO-IT. The validated RVACS model could be imported to further accident analysis.

• Educational Technology International
• /
• v.24 no.2
• /
• pp.169-202
• /
• 2023

This study aims to develop instructional design strategies included in educational programs that can effectively improve the educational data literacy of pre-service teachers. We used the design and development model proposed by Richey and Klein and investigated its internal and external validity. Internal validity assessment involved the input of five experts who evaluated the initial instructional strategies. We conducted an educational data literacy education program with 29 pre-service teachers from Korean colleges and graduate schools for external validity. The effectiveness of the program was verified by the Wilcoxon Rank Sum Test, which revealed a meaningful statistical difference between Wilcoxon Rank Sum Test post-scores after the four weeks of online classes. Therefore, this study developed instructional strategies followed by the steps of data-based decision-making: the final instructional strategies encompass 21 strategies, categorized for implementation before, during, and after classes, accompanied by 38 detailed guidelines. This approach bears notable significance as it encapsulates actionable and effective instructional strategies thoughtfully tailored to the unique circumstances and educational setting of the field, as well as the specific characteristics and requirements of the learners.