• Land and Housing Review
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• v.13 no.3
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• pp.107-113
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• 2022

With increasing airtight building construction aimed at reducing energy consumption, indoor relative humidity is increasing which can lead to condensation and moisture damage in multi-family residential buildings. This has led to increased implementation of mechanical ventilation to control indoor moisture. However mechanical ventilation systems consume additional energy and generate noise. As this leads to occupant discomfort, it is necessary to select a ventilation system that addresses the energy and noise issues. This research measured the ventilation performance, energy consumption, and noise level of mechanical ventilation devices in multi-family residential buildings. TOPSIS, a multi-criteria decision making technique was used to determine appropriate ventilation strategies in addition to occupant ventilation system operation preference.

• Composites Research
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• v.36 no.1
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• pp.32-36
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• 2023

Recently, as global environmental issues for sustainable development, such as carbon neutrality, have emerged, disposal methods of glass fiber composites, a material of existing wind turbines, have become a problem. To solve this problem, in this study, 30kW wind turbine blades were manufactured using flax fiber-based composites, which are eco-friendly natural fiber composites that can replace existing glass fiber composites, and their suitability was evaluated. First, mechanical strength tests were conducted to verify the feasibility of using eco-friendly natural flax fiber composites as a wind turbine blade material, and as a result, better strength were confirmed compared to previous studies on the properties of flax fiber composites. In addition, the suitability was confirmed through a static strength performance evaluation test to measure the static strength of the flax fiber composite blade using the manufactured 30kW class flax fiber composite blade.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.88-88
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• 2023

지난 100년 동안 전 지구의 기상 이변이 꾸준히 증가하고 있다. 기후 변화는 도시 홍수 피해에 큰 영향을 끼치는데 급속한 도시화와 이상 기후로 인한 돌발 강우 패턴의 증가는 도시 침수의 취약성을 가중시킨다. 또한 급격한 도시 발전으로 인한 도심지의 불투수율 또한 꾸준히 증가하였다. 특히 2022년 8월 8일에 강남역과 도림천 일대에 내린 기록적인 강우는 기후 변화를 실감하게 하는 사회적 이슈가 되었으며 도심지 미래 수방 대책 변화를 상기시키는 계기가 되었다. 이로 인한 재해 피해에 최소화하기 위해 미래 기후 변화를 고려한 도심지의 새로운 방재 목표강우량 설정이 필요하다. 하지만 전 지구 모형(GCM)의 기후 변화 시나리오는 일 단위(Daily) 상세화 자료를 보편적으로 사용하고 있다. 하지만 이는 단기 강우 자료를 필요로 하는 도시 홍수 모의에서 제대로 활용할 수 없는 한계를 가지고 있다. 따라서 본 연구는 2019년에 발간된 IPCC 6차 평가 보고서(AR6)가 제안하는 SSP(Shared Socioeconomic Pathways, 공통사회경제경로) 시나리오를 기반하여 상세화된 일 단위(Daily) 강우 데이터를 비모수적 통계 기법을 사용하여 시간 단위(Hourly)로 상세화하였다. 또한 지속 시간별 연 최대치 강우를 추출하여 빈도 해석을 통해 도시 유역의 미래 확률 강우량을 제시하였으며, 서울시 상습적인 침수 취약 지역인 도림천 유역에 강우-유출 모형(XP-SWMM)을 사용하여 미래전망 기후 자료인 SSP2-4.5와 SSP5-8.5에 따른 미래 확률 강우 침수 모의를 실시하였다. 본 연구의 결과는 최신 기후 변화 시나리오를 고려한 서울시 방재 성능 목표 강우량 산정에 활용 가능할 것으로 사료되며 미래 강우량 침수 모의를 통해 침수 취약 구역인 도림천 일대 홍수피해의 근거 자료가 되는 것에 의의를 둔다. 또한 치수 분야에서 기후 변화를 고려하기 위해서는 기후 변화 시나리오에 따른 시간 단위 자료의 상세화가 필요함을 시사한다.

• Smart Media Journal
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• v.11 no.9
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• pp.64-74
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• 2022

A number of studies related to underwater robots are being conducted to utilize marine resources. However, unlike ordinary drones, underwater robots have a problem that it is not easy to locate because the medium is water, not air. The monitoring and positioning program of underwater robots, an existing study for identifying underwater locations, has difficulty in locating and monitoring in small spaces because it aims to be utilized in large spaces. Therefore, in this paper, we propose a three-dimensional positioning program for continuous monitoring and command delivery in small spaces. The proposed program consists of a multi-dimensional positioning monitoring function and a ability to control the path of travel through a three-dimensional screen so that the depth of the underwater robot can be identified. Through the performance evaluation, a robot underwater could be monitored and verified from various angles with a 3D screen, and an error within the assumed range was verified as the difference between the set path and the actual position is within 6.44 m on average.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.102-110
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• 2017

Current word sense disambiguation techniques employ various machine learning-based methods. Various approaches have been proposed to address this problem, including the knowledge base approach. This approach defines the sense of an ambiguous word in accordance with knowledge base information with no training corpus. In unsupervised learning techniques that use a knowledge base approach, graph-based and similarity-based methods have been the main research areas. The graph-based method has the advantage of constructing a semantic graph that delineates all paths between different senses that an ambiguous word may have. However, unnecessary semantic paths may be introduced, thereby increasing the risk of errors. To solve this problem and construct a fine-grained graph, in this paper, we propose a model that iteratively constructs the graph while eliminating unnecessary nodes and edges, i.e., senses and semantic paths. The hybrid similarity estimation model was applied to estimate a more accurate sense in the constructed semantic graph. Because the proposed model uses BabelNet, a multilingual lexical knowledge base, the model is not limited to a specific language.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.501-508
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• 2023

Addressing urban noise problems, this study develops eco-friendly, inorganic sound-absorbing panels, overcoming the limitations of traditional PMMA and cement-based panels. These conventional panels pose safety risks due to flammability and environmental concerns due to carbon emissions. Utilizing industrial waste, the research comprises two phases: initial tests for physical and performance characteristics (fluidity, density, compressive strength, sound absorption) and subsequent development of optimized panel mixtures. This approach aims to replace existing panels with sustainable, effective alternatives, significantly contributing to safer, environmentally responsible urban infrastructure. The findings of this study have implications for the sound panel market, offering novel solutions for noise control while aligning with environmental and safety standards.

• Annual Conference of KIPS
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• 2008.05a
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• pp.826-829
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• 2008

모바일 환경에서는 모바일 기기의 제한된 에너지를 효율적으로 사용하는 것이 요구된다. 특히 모바일 Peer-to-Peer(P2P) 시스템에서 모바일 기기가 피어로서 저장된 에너지를 모두 소모하면 더 이상파일 탐색 등과 같은 작업에 참여할 수 없게 된다. 또한 에너지가 없는 피어가 증가하게 되면 파일탐색 실패율이 증가하게 되고, 결국 파일탐색이 불가능하게 된다. 슈퍼피어(super peer)를 기반으로 한 계층적 P2P 시스템은 기존 단일 계층 P2P 시스템보다 더 적은 양의 메시지로 파일탐색을 가능하게 해준다. 하지만 하나의 슈퍼피어가 관리하는 서브피어(sub-peer)가 많을 경우, 서브피어의 관리 비용과 파일 탐색 요청의 증가로 슈퍼피어의 에너지 소모 비율이 크게 증가하게 되며, 이로 인해 네트워크 참여 시간이 줄어들게 된다. 이는 전체 네트워크 유지시간 감소에 영향을 미친다. 본 논문은 무선 통신 기반의 모바일 환경에서 슈퍼피어를 기반으로 한 계층적 P2P 시스템을 기반으로, 슈퍼피어가 관리하는 서브피어들의 수를 제한하고, 만약 일정한 수를 초과하였을 경우, 초과한 슈퍼피어의 서브피어들 중에서 새로운 슈퍼피어를 선정하고, 기존 슈퍼피어로부터 일부 서브피어들을 분배하여 관리하게 하는 시스템을 제안하였다. 실험을 통해 성능을 평가 하였으며, 실험 결과 파일 탐색 요청을 위한 네트워크 유지시간이 더 오래 지속됨을 확인하였다.

• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.1043-1054
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• 2023

Amidst the rapid growth of the vegan cosmetics market, consumer orientation towards environmental and ethical values has been intensifying. However, research on this subject remains limited. This study delves into the relationship between consumer value perception, environmental motivations, and perceived barriers influencing the purchase intentions of vegan cosmetics. Conducting a PLS-SEM analysis on a sample of 300 women with experience using vegan cosmetics, it was discerned that monetary value, social value, brand value, emotional value, quality value, and environmental knowledge play significant roles in influencing purchase intentions. The moderating effect analysis highlighted image barriers and value barriers as crucial factors. Through Importance-Performance Map Analysis, emotional value emerged as a pivotal element in strategizing to strengthen the purchasing intentions for vegan cosmetics. This research contributes both theoretically and practically to enhancing the competitive edge of the vegan cosmetics market and promoting sustainable consumption behavior.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.707-724
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• 2024

Recently, Golang has been gaining attention in programming language rankings each year due to its cross-compilation capabilities and high code productivity. However, malware developers have also been increasingly using it to distribute malware such as ransomware and backdoors. Interestingly, Golang, being an open-source language, frequently changes the important values and configuration order of a crucial structure called Pclntab, which includes essential values for recovering deleted symbols whenever a new version is released. While frequent structural changes may not be an issue from a developer's perspective aiming for better code readability and productivity, it poses challenges in cybersecurity, as new versions with modified structures can be exploited in malware development. Therefore, this paper proposes GoAsap, a detection and analysis system for Golang executables targeting the new versions, and validates the performance of the proposed system by comparing and evaluating it against six existing binary analysis tools.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.367-372
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• 2024

Although developmental disabilities account for a relatively low number of the total number of disabilities, they are generally classified as severe disabilities considering the degree of disability. If these developmental disorders are discovered early, adaptability and early treatment efficiency can be improved, but most parents do not detect any signs from their children or miss the right time for treatment. In this paper, we conducted development of the developmental disorder diagnosis algorithm that can recognize hand-flapping, one of the early unusual behaviors of developmental disorders, for parents and early childhood care workers who cannot recognize signs of early developmental disorders based on specific behavioral characteristics as a pilot study. It was confirmed that the recognition area and fingers were accurately recognized, and the number of hand flapping was accurately counted. It is expected that research on algorithms that can diagnose various behavioral patterns will continue to be conducted and expanded all through algorithms advancement and expansion of functional performance using big data.