• Membrane Journal
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• v.32 no.2
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• pp.116-125
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• 2022

In this experiment, an α-Al₂O₃ ceramic hollow fiber was used as a support, and a hydrogen membrane plated with Pd and Pd-Ag was manufactured through electroless plating. The Pd-Ag membrane was annealed at 500℃ for 10 h to form an alloy of Pd and Ag. It was confirmed that it became a Pd-Ag alloy through EDS (Energy Dispersive X-ray Spectroscopy) analysis. Also, the thickness of the Pd, Pd-Ag plating layer was measured to be about 8.98 and 9.29 ㎛ through SEM (Scanning Electron Microscope) analysis respectively. Hydrogen permeation experiment was performed using the H₂ gas and mixed gas (H₂ and N₂) in the range of 350~450℃ and 1-4 bar using the prepared hydrogen membrane. Under the H₂ gas condition, the Pd and Pd-Ag membrane has a flux of up to 21.85 and 13.76 mL/cm²·min and also separation factors of 1216 and 361 were obtained in the mixed gas at 450℃ and 4 bar conditions respectively.

• Journal of the Korean GEO-environmental Society
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• v.23 no.9
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• pp.17-23
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• 2022

Using cement as a road subbase is economical, easily modified and supplemented and has excellent road pavement quality control. In addition, cement adheres well to sandy soils without adhesion, and it plays a role of permanently preserving adhesion in viscous soils with adhesion, so it can be widely applied as stable treatment with the advantages of increased strength, reduced compressibility. and improved durability. However, while cement is excellent in terms of strength for a road subbase, the material properties mean that it is difficult to maintain and reinforce when cracks or fractures occur due to dry shrinkage, and the pH increases in the ground due to hexavalent chromium eluting from cement. which can cause environmental problems such as groundwater contamination. Therefore, this study evaluates the usability of alternatives in the road base layer such as environmentally cementitious stabilizer and on-site soil generated from the site. We intend to reduce the environmental damage and evaluate the durability. To evaluate the applicability of the site, Environmental stability test and freeze-thaw test and wetting-drying test was conducted to evaluate the strength characteristics of alternative materials on the road through the limited performance evaluation of environmentally cementitious stabilizer. The test ranges were set at mixing ratios of 10%, 20%, and 30% and ages of three days, and 28 days old to evaluate the early strength and reference strength according to the mixing ratio of the environmentally cementitious stabilizer.

• Korean Journal of Optics and Photonics
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• v.33 no.1
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• pp.28-34
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• 2022

We study through computational simulation the focal performance of an infrared (IR) Fresnel lens, composed of a multilayer-graphene zone plate formed under a graphene electrode. Here the Fermi level E_F of the patterned multilayer graphene is adjusted by the overlying graphene electrode. The Fresnel lens effect, with respect to the reflectance contrast between the graphene electrode and the 8-layer graphene zone plate placed on a glass substrate, has been analyzed over a broad wavelength range from 4 to 30 ㎛. As the optimal wavelength of 8 ㎛ (considering the reflectance and the reflectance-contrast ratio) is incident upon the Fresnel lens with a focal length of 240 ㎛, the focal intensity is enhanced by a factor of 4.3 as the E_F of multilayer graphene increases from 0.4 eV to 1.6 eV, and is improved by a factor of 5.8 as the number of graphene layers increases from two to eight. As a result, an all-graphene-based IR Fresnel zone-plate lens, exhibiting multifocal function (240 ㎛ and 360 ㎛) according to the selected E_F, is proposed as an ultrathin lens platform.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.1-7
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• 2022

Recently, satellites equipped with high-performance electronics have required higher power consumption because of the advancement of satellite missions. For this reason, the size of the solar panel is gradually increasing to meet the required power budget. Increasing the size and weight of the solar panel is one of the factors that induce the elastic vibration of the flexible solar panel during the highly agile maneuvering of the satellite or the mode of vibration coupling to the satellite or the mode of vibration coupling to the micro-jitter from the on-board appendages. Previously, an additional damper system was applied to reduce the elastic vibration of the solar panel, but the increase in size and mass of system was inevitable. In this study, to overcome the abovementioned limitations, we proposed a high -damping yoke structure consisting of a superplastic SMA(Shape Memory Alloy) laminating a thin FR4 layer with viscoelastic tape on both sides. Therefore, this advantage contributes to system simplicity by reducing vibrations with small volume and mass without additional system. The effectiveness of the proposed superelastic SMA multilayer solar panel yoke was validated through free vibration testing and temperature testing using a solar panel dummy.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.221-232
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• 2023

This paper presents a novel convolutional neural network (CNN)-based approach for predicting bolt clamping force in the early bolt loosening state of bolted structures. The approach entails tightening eight bolts with different clamping forces and generating frequency responses, which are then used to create a similarity map. This map quantifies the magnitude and shape similarity between the frequency responses and the initial model in a fully fastened state. Krylov subspace-based model order reduction is employed to efficiently handle the large amount of frequency response data. The CNN model incorporates a regression output layer to predict the clamping forces of the bolts. Its performance is evaluated by training the network by using various amounts of training data and convolutional layers. The input data for the model are derived from the magnitude and shape similarity map obtained from the frequency responses. The results demonstrate the diagnostic potential and effectiveness of the proposed approach in detecting early bolt loosening. Accurate bolt clamping force predictions in the early loosening state can thus be achieved by utilizing the frequency response data and CNN model. The findings afford valuable insights into the application of CNNs for assessing the integrity of bolted structures.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.363-373
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• 2023

Forest biomass surveys are regularly conducted to assess and manage forests as carbon sinks. LiDAR (Light Detection and Ranging), a remote sensing technology, has attracted considerable attention, as it allows for objective acquisition of forest structure information with minimal labor. In this study, we propose a method for estimating overstory and understory biomass in forest stands using backpack laser scanning (BPLS) and unmanned aerial vehicle laser scanning (UAV-LS), and assessed its accuracy. For overstory biomass, we analyzed the accuracy of BPLS and UAV-LS in estimating diameter at breast height (DBH) and tree height. For understory biomass, we developed a multiple regression model for estimating understory biomass using the best combination of vertical structure metrics extracted from the BPLS data. The results indicated that BPLS provided accurate estimations of DBH (R² =0.92), but underestimated tree height (R² =0.63, bias=-5.56 m), whereas UAV-LS showed strong performance in estimating tree height (R² =0.91). For understory biomass, metrics representing the mean height of the points and the point density of the fourth layer were selected to develop the model. The cross-validation result of the understory biomass estimation model showed a coefficient of determination of 0.68. The study findings suggest that the proposed overstory and understory biomass survey methods using BPLS and UAV-LS can effectively replace traditional biomass survey methods.

• Composites Research
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• v.36 no.4
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• pp.270-274
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• 2023

The stacking configuration of fiber-reinforced polymer (FRP) composites, achieved via the filament winding process, exhibits distinct variations compared to conventional FRP composite stacking arrangements. Consequently, it becomes challenging to ascertain the influence of mechanical properties based on the typical stacking structures. Thus, it becomes imperative to enhance the mechanical behavior and optimize the interleaved structures to improve overall performance. Therefore, this study aims to investigate the impact of incorporating amorphous halloysite nanotubes (A-HNTs) within different layers of five unique layer arrangements on the low-velocity impact properties of interleaved carbon fiber-reinforced polymer (CFRP) structures. The low-velocity impact characteristics of the laminate were validated using a drop weight impact test, wherein the resulting impact damage modes and extent of damage were compared and evaluated under microscopic analysis. Each interleaved structure laminate according to whether nanoparticles are added was compared at impact energies of 10 J and 15 J. In the case of 10 J, the absorption energy showed a similar tendency in each structure. However, at 15 J, the absorption energy varies from structure to structure. Among them, a structure in which nanoparticles are not added exhibits the highest absorption energy. Additionally, various impact fracture modes were observed in each structure through optical microscopy.