• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.969-976
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• 2020

Urban Air Mobility is attracting attention as a future innovation industry around the world, and leading industries are considering the application of composite materials for structural robustness and lightening in the designing and manufacturing new concept eVTOL aircraft. To apply composite materials to the new concept of eVTO aircraft, this paper was analyzed about composite material qualification system of FAA & EASA and institutionalized by Korea Government, including the procedures and methods, the organization to carry out the material verification for domestic conditions. The domestic composite material qualification system will not only make it easier for manufacturers of eVTOL aircraft with a new concept to apply composite materials to domestic aircraft through pre-material qualification, but also reduce the burden of material qualification within the period of type certification. In addition, domestic manufacturers of composite materials with qualified material quality and performance will be easy to enter for domestic aircraft applications and composite material manufacturers with experience in applying to aircraft will have a positive impact on overseas exports. This system will be able to promote the development eVTOL aircraft industry of a new concept and enhance international credibility of made aircraft in Korea.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.235-244
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• 2022

In this study, a class operation case of an engineering design project targeting a golf ball dispenser, a commercial product, was presented. The project was carried out according to the systematic engineering design approach suggested by Kim Jong-won and W. Beitz. This method broadly divides engineering design into four stages: 'product planning → conceptual design → basic design → detailed design'. In particular, the conceptual design stage is divided into 'functional structure diagram → detailed working principle exploration → various design alternatives creation → optimal design selection'. In the conceptual design, the input/output of the golf ball dispenser was defined and a functional structure diagram was prepared for it. Through this process, it was possible to subdivide the functions of the product and to easily explore the working principle for each. The searched working principles are devised as various design alternatives by various combinations, and for each proposal, the advantages and disadvantages were compared with each other to derive the optimal design alternative. In the basic design, the prototype layout was completed through failure mode analysis and the actual prototype was manufactured using it. Through the entire process, students participating in the class will be able to design commercial products in a systematic way and experience manufacturing prototypes within the department of mechanical engineering curriculum.

• Annual Conference of KIPS
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• 2011.04a
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• pp.576-579
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• 2011

Wireless sensor network are widely all over different fields. Because of its distinguished characteristics, we must take account of the factor of energy consumed when designing routing protocol. Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors sends data from the CH (Cluster Head) and then to the BS (Base Station). BCDCP works well in a smallscale network however is not preferred in a large scale network since it uses much energy for long distance wireless communication. TBRP can be used for large scale network, but it weakness lies on the fact that the nodedry out of energy easily since it uses multi-hops transmission data to the Base Station. Here, we proposed a routing protocol. A Cluster Based Energy Efficient Tree Routing Protocol (CETRP) in Wireless Sensor Networks (WSNs) to prolong network life time through the balanced energy consumption. CETRP selects Cluster Head of cluster tree shape and uses maximum two hops data transmission to the Cluster Head in every level. We show CETRP outperforms BCDCP and TBRP with several experiments.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.207-212
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• 2023

Near-infrared (NIR) absorbing dyes have been applied to various applications such as optical filters, biotechnology, energy storage and conversion, coating additive, and traditionally information-storage materials. Because image sensors used in cellphones and digital cameras have sensitivity in the NIR region, the NIR cut-off filter is essential to achieving more clear images. As energy storage and conversion have been important, diverse NIR absorbing materials have been developed to extend the absorption region to the NIR region, and NIR absorbing materials-based research has proceeded to improve device performances. Adding NIR-absorbing dye with a photo-thermal effect to a self-healable coating system has been attractive for future mobility technology, and more effective self-healing properties have been reported. In this report, the chemical structures of representative NIR-absorbing dyes and state of the art research based on NIR-absorbing dyes are introduced.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.641-653
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• 2023

As climate change and urbanization are causing unprecedented natural disasters in urban areas, it is crucial to have urban flood predictions with high fidelity and accuracy. However, conventional physically- and deep learning-based urban flood modeling methods have limitations that require a lot of computer resources or data for high-resolution flooding analysis. In this study, we propose and implement a method for improving the spatial resolution of urban flood analysis using a deep learning based super-resolution technique. The proposed approach converts low-resolution flood maps by physically based modeling into the high-resolution using a super-resolution deep learning model trained by high-resolution modeling data. When applied to two cases of retrospective flood analysis at part of City of Portland, Oregon, U.S., the results of the 4-m resolution physical simulation were successfully converted into 1-m resolution flood maps through super-resolution. High structural similarity between the super-solution image and the high-resolution original was found. The results show promising image quality loss within an acceptable limit of 22.80 dB (PSNR) and 0.73 (SSIM). The proposed super-resolution method can provide efficient model training with a limited number of flood scenarios, significantly reducing data acquisition efforts and computational costs.

• Food Science and Preservation
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• v.31 no.1
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• pp.126-137
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• 2024

In this study, zinc oxide nanoparticles (ZnONPs) were synthesized using three distinct zinc salts: zinc acetate, zinc chloride, and zinc nitrate. These ZnONPs were subsequently utilized in the fabrication of carrageenan-ZnONPs (Car-ZnONPs) composite films. The study assessed influence of the various ZnONPs on the morphological, water vapor barrier, color, optical, and antimicrobial properties of the Car-ZnONPs composite films. The surface morphology and UV-blocking attributes of the composite films were affected by the type of ZnONPs used, but their surface color, transparency, and chemical structure remained unaltered. The composite film's thickness and elongation at break (EB) significantly increased, while the tensile strength significantly decreased. In contrast, film's elastic modulus (EM) and water vapor permeability coefficient (WVP) showed no significant difference. All the composite films with added ZnONPs demonstrated potent antibacterial activity against Escherichia coli O157:H7 and Listeria monocytogenes . Among the carrageenan-based composite films, Car-ZnONPs^ZC showed the highest antibacterial and UV-blocking properties, and its elongation at break was significantly higher than that of the pure carrageenan films. This suggests that ZnONPs composite films have the potential to be used as an active packaging film, preserve the safety of the packaged food and extend shelf life.

• Phonetics and Speech Sciences
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• v.16 no.1
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• pp.67-76
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• 2024

Recent advances in text-to-speech (TTS) technology have significantly improved the quality of synthesized speech, reaching a level where it can closely imitate natural human speech. Especially, TTS models offering various voice characteristics and personalized speech, are widely utilized in fields such as artificial intelligence (AI) tutors, advertising, and video dubbing. Accordingly, in this paper, we propose a one-shot multi-speaker TTS system that can ensure acoustic diversity and synthesize personalized voice by generating speech using unseen target speakers' utterances. The proposed model integrates a speaker encoder into a TTS model consisting of the FastSpeech2 acoustic model and the HiFi-GAN vocoder. The speaker encoder, based on the pre-trained RawNet3, extracts speaker-specific voice features. Furthermore, the proposed approach not only includes an English one-shot multi-speaker TTS but also introduces a Korean one-shot multi-speaker TTS. We evaluate naturalness and speaker similarity of the generated speech using objective and subjective metrics. In the subjective evaluation, the proposed Korean one-shot multi-speaker TTS obtained naturalness mean opinion score (NMOS) of 3.36 and similarity MOS (SMOS) of 3.16. The objective evaluation of the proposed English and Korean one-shot multi-speaker TTS showed a prediction MOS (P-MOS) of 2.54 and 3.74, respectively. These results indicate that the performance of our proposed model is improved over the baseline models in terms of both naturalness and speaker similarity.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of the Korea Institute of Building Construction
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• v.9 no.4
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• pp.63-73
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• 2009

Recently, the use of lightweight panels in building structures has been increasing. Of the various lightweight panel types, styrofoam sandwich panels are inexpensive and are excellent in terms of their insulation capacity and their constructability. However, sandwich panels that include organic material are quite vulnerable to fire, and thus can numerous casualties in the event of a fire due to the lack of time to vacate and their emission of poisonous gas. On the other hand, lightweight foamed concrete is excellent, both in terms of its insulation ability and its fire resistance, due to its Inner pores. The properties of lightweight concrete is influenced by foaming agent type. Accordingly, this study investigates the insulation properties by foaming agent type, to evaluate the possibility of using light-weight foamed concrete instead of styrene foam. Our research found thatnon-heating zone temperature of lightweight foamed concrete using AP (Aluminum Powder) and FP (animal protein foaming agent) are lower than that of light-weight foamed concrete using AES (alkyl ether lactic acid ester). Lightweight foamed concrete using AES and FP satisfied fire performance requirements of two hours at a foam ratio 50, 100. Lightweight foamed concrete using AP satisfied fire performance requirements of two hours at AP ratio 0.1, 0.15. The insulation properties were better in closed pore foamed concrete by made AP, FP than with open pore foamed concrete made using AES.

• Journal of Korean Society of Steel Construction
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• v.20 no.5
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• pp.633-644
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• 2008

The structural framework design uses high-strength bolts and welding in column splices. However, for the column under high compression, the number of the required high-strength bolts can be excessive and the increase of welding results in difficulty of quality inspection, the transformation of the structural steels, and the increase of erection time. According to the AISC criteria, when columns have bearing plates, or they are finished to bear at splices, there shall be sufficient connections to hold all parts securely in place. The Korean standard sets the maximum 25% of the load as criteria. Using direct contact makes it possible to transfer all compressive force through it. The objective of this study is to examine the generally applied stress path mechanism of welded or bolted columns and to verify the bending moment and compression transfer mechanism of the column splice according to metal touch precision. For this study,22 specimens of various geometric shapes were constructed according to the change in the variables for each column splice type, which includes the splice method, gap width, gap axis, presence or absence of splice material, and connector type. The results show that the application of each splice can be improved through the examination of the stress path mechanism upon metal contact. Moreover, the revision of the relative local code on direct contact needs to be reviewed properly for the economics and efficiency of the splices.