• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.291-309
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• 2023

This paper addresses the finite element modeling of functionally graded porous (FGP) beams for free vibration and buckling behaviour cases. The formulated finite element is based on simple and efficient higher order shear deformation theory. The key feature of this formulation is that it deals with Euler-Bernoulli beam theory with only three unknowns without requiring any shear correction factor. In fact, the presented two-noded beam element has three degrees of freedom per node, and the discrete model guarantees the interelement continuity by using both C⁰ and C¹ continuities for the displacement field and its first derivative shape functions, respectively. The weak form of the governing equations is obtained from the Hamilton principle of FGP beams to generate the elementary stiffness, geometric, and mass matrices. By deploying the isoparametric coordinate system, the derived elementary matrices are computed using the Gauss quadrature rule. To overcome the shear-locking phenomenon, the reduced integration technique is used for the shear strain energy. Furthermore, the effect of porosity distribution patterns on the free vibration and buckling behaviours of porous functionally graded beams in various parameters is investigated. The obtained results extend and improve those predicted previously by alternative existing theories, in which significant parameters such as material distribution, geometrical configuration, boundary conditions, and porosity distributions are considered and discussed in detailed numerical comparisons. Determining the impacts of these parameters on natural frequencies and critical buckling loads play an essential role in the manufacturing process of such materials and their related mechanical modeling in aerospace, nuclear, civil, and other structures.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.25-31
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• 2023

The brain-machine interface(BMI) is a next-generation interface that controls the device by decoding brain waves(also called Electroencephalogram, EEG), EEG is a electrical signal of nerve cell generated when the BMI user thinks of a command. The brain-machine interface can be applied to various smart devices, but complex computational process is required to decode the brain wave signal. Therefore, it is difficult to implement a brain-machine interface in an embedded system implemented in the form of an edge device. In this study, we proposed a new type of brain-machine interface system using IoT technology that only measures EEG at the edge device and stores and analyzes EEG data in the cloud computing. This system successfully performed quantitative EEG analysis for the brain-machine interface, and the whole data transmission time also showed a capable level of real-time processing.

• Korean Journal of Environmental Agriculture
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• v.42 no.1
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• pp.14-20
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• 2023

Light is an important factor that influences the growth and development of flowering plants. The present study investigated the effects of in vitro acclimatization to different light colors (white light (WL; control), blue light (BL; 447 nm), green light (GL; 519 nm), and red light (RL; 667 nm)) on the growth of petunia (Petunia hybrida) and of hardening cultivation of plant transferred form in vitro to a greenhouse under sunlight. Compared to the control, the shoot length and leaf width of Petunia increased by 42% and 11.7%, respectively, after acclimatization to BL and the shoot growth increased by 29.3% after acclimatization to RL. The chlorophyll and carotenoid contents after acclimatization to BL and GL were 16.7% and 11.3% higher, respectively, and 14.4% and 11.9% higher, respectively, than those in the control. During greenhouse cultivation, the shoot length increased by 16.7% and 11.3%, respectively, after acclimatization to BL and RL, respectively, and the leaf length and leaf width increased by 14.4% and 11.9%, respectively, after acclimatization to GL. While dry weight of root of GL and BL was not significant difference in vitro, increased by 59.0% and 22.9% ex vitro than that of WL. Thus, acclimatization to BL increased the shoot growth and leaf chlorophyll contents, and acclimatization to GL and RL enhanced shoot and root growth, in petunia.

• Composites Research
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• v.22 no.6
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• pp.1-6
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• 2009

This paper presents an experimental study on the piezoresistive behavior of nanocomposite strain sensors subjected to various loading modes and their capability to detect structural deformations and damages. The electrically conductive nanocomposites were fabricated in the form of a film using various types of thermoplastic polymers and multi-walled carbon nanotubes (MWNTs) at various loadings. In this study, the nanocomposite strain sensors were bonded to a substrate and subjected to tension, flexure, or compression. In tension and flexure, the resistivity change showed dependence on measurement direction, indicating that the sensors can be used for multi-directional strain sensing. In addition, the sensors exhibited a decreasing behavior in resistivity as the compressive load was applied, suggesting that they can be used for pressure sensing. This study demonstrates that the nanocomposite strain sensors can provide a pathway to affordable, effective, and versatile structural health monitoring.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.125-138
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• 2022

Purpose: Failure Mode and Effect Analysis (FMEA) is a widely utilized technique to measure product reliability by identifying potential failure modes. Even though FMEA techniques have been studied, the form of Risk Priority Number (RPN) used to evaluate risk priority in FMEA is still questionable because of its shortcomings. In this study, we suggest common RPN(cRPN) to resolve shortcomings of the traditional RPN and show the extensibility of cRPN. Methods: We suggest cRPN which is based on Cobb-Douglas production function, and represent the various application on weighting risk factors, weighted RPN in a mathematical way, and show the possibility of statistical approach. We also conduct numerical study to examine the difference of the traditional RPN and cRPN as well as the potential application from the analysis on marginal effects of each risk factor. Results: cRPN successfully integrates previously suggested approaches especially on the relative importance of risk factors and weighting RPN. Moreover, we analyze the effect of corrective actions in terms of econometric analysis using cRPN. Since cRPN is rely on the reliable mathematical model, there would be numerous applications using cRPN such as smart factory based on A.I. techniques. Conclusion: We propose a reliable mathematical model of RPN based on Cobb-Douglas production function. Our suggested model, cRPN, resolves various shortcomings such as consideration of the relative importance, the effect of combinations among risk factors. In addition, by adopting a reliable mathematical model, quantitative approaches are expected to be applied using cRPN. We find that cRPN can be utilized to the field of industry because it is able to be applied without modifying the entire systems or the conventional actions.

• Wind and Structures
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• v.36 no.3
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• pp.201-213
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• 2023

In this study, the effect of sea surface temperature (SST) on the distribution of vertical wind speed in the atmospheric boundary layer of coastal areas was analyzed. In general, coastal areas are known to be more susceptible to various meteorological factors than inland areas due to interannual changes in sea surface temperature. Therefore, the purpose of this study is to analyze the relationship between sea surface temperature (ERA5) and wind resource data based on the meteorological mast of Høvsøre, the test bed area of the onshore wind farm in the coastal area of Denmark. In addition, the possibility of coastal disasters caused by abnormal vertical wind shear due to changes in sea surface temperature was also analyzed. According to the analysis of the correlation between the wind resource data at met mast and the sea surface temperature by ERA5, the wind speed from the sea and the vertical wind shear are stronger than from the inland, and are vulnerable to seasonal sea surface temperature fluctuations. In particular, the abnormal vertical wind shear, in which only the lower wind speed was strengthened and appeared in the form of a nose, mainly appeared in winter when the atmosphere was near-neutral or stable, and all occurred when the wind blows from the sea. This phenomenon usually occurred when there was a sudden change in sea surface temperature within a short period of time.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.247-260
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• 2022

This paper investigates plans to expand distribution channels for books by installing a book vending machine at convenience stories for the vitalization of the publishing culture and industry. After establishing the meaning of convenience stories and the concept of a book vending machine, the researcher identified a need for the installation and management of a book vending machine at convenience stories. This plan will promote fairness and transparency in book sales through the convenience store system and push forward outsourcing between the publishing industry and the convenience store industry, the expansion of omnichannel service for consumers, and experiential values for clients to increase their customer satisfaction. The composition of the book vending machine will take the smart library form for its management with a universal design applied to a kiosk program. In the study, the researcher schematized this process and conducted a survey with 310 adults to search for practical management plans for a book vending machine. In the future, more research on the diversification of sales and distribution channels for publications such as the installation of a book vending machine at convenience stores will hopefully contribute to the growing amount of reading per capita and promotion of a reading environment for people according to the vitalization of the publishing culture and industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.496-498
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• 2022

With the prolonged spread of the new coronavirus infection worldwide and the entry of the super-aged society, smart health care, which combines IT technology for senior health care and the health care industry, is emerging as a solution to the aging problem. The development of non-face-to-face care services using Ai is on a global trend, not in some countries, and the form of care services for the elderly using AI artificial intelligence technology is changing rapidly. The convenience of AI-based care services for the elderly is expected to be highlighted, and the technology and market are expected to develop significantly. As the number of single-person households is increasing, the shortage of welfare workers for the elderly is emerging as a social issue. It is presented as a vision to solve long-term social problems such as the labor shortage of elderly care workers as well as the advantages of convenient care services using IT technology. Therefore, we would like to propose the development direction of care services for the elderly as a case study of care services for the elderly and a countermeasure against the super-aging age.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.57 no.2
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• pp.129-136
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• 2024

Lactic acid bacteria (LAB) growth in processed meat products produces slime. In this study, 10 different biofilm-forming LAB, including Leuconostoc mesenteroides, Lacticaseibacillus paracasei, Levilactobacillus brevis, Lactiplantibacillus plantarum, Leuconostoc citreum, Weissella viridescens, and Latilactobacillus sakei, were isolated from various meat products and identified based on 16S rRNA gene analysis. To inhibit biofilm formation by LABs, Eisenia bicycles methanolic extract (EB) and ethyl acetate soluble fraction (EA) were used as antibacterial and antibiofilm agents, respectively. Furthermore, EA and EB were employed to synthesize gold nanoparticles (AuNPs) such as EB-AuNPs and EA-AuNPs, which could serve as antibiofilm agents against the isolated LAB. These findings demonstrate that EA, EB-AuNPs, and EA-AuNPs exhibit significant antibacterial activity against the isolated LAB. Furthermore, EB-AuNPs reduced L. citreum biofilm production, whereas EA-AuNPs inhibited L. mesenteroides and L. brevis biofilm formation. The current results suggest that EB-AuNPs and EA-AuNPs can be used as nanomaterials to inhibit LAB that form biofilms on meat products.