• 동의생리병리학회지
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• 제34권4호
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• pp.159-169
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• 2020

Shanghanlun (Treatise on Cold Damage Diseases) is the oldest document in the literature on clinical records of Traditional Asian medicine (TAM), on which TAM theories about symptoms-herbs relationships are based. In this study, we aim to quantitatively explore the relationships between symptoms and herbs in Shanghanlun. The text in Shanghanlun was converted into structured data. Using the structured data, Term Frequency - Inverse Document Frequency (TF-IDF) scores of symptoms and herbs were calculated from each chapter to derive the major symptoms and herbs in each chapter. To understand the structure of the entire document, principal component analysis (PCA) was performed for the 6-dimensional chapter space. Bipartite network analysis was conducted focusing on Jaccard scores between symptoms and herbs and eigenvector centralities of nodes. TF-IDF scores showed the characteristics of each chapter through major symptoms and herbs. Principal components drawn by PCA suggested the entire structure of Shanghanlun. The network analysis revealed a 'multi herbs - multi symptoms' relationship. Common symptoms and herbs were drawn from high eigenvector centralities of their nodes, while specific symptoms and herbs were drawn from low centralities. Symptoms expected to be treated by herbs were derived, respectively. Using measurable metrics, we conducted a computational study on patterns of Shanghanlun. Quantitative researches on TAM theories will contribute to improving the clarity of TAM theories.

• 한국인터넷방송통신학회논문지
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• 제21권4호
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• pp.1-8
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• 2021

전세계 수많은 사용자들이 특정 실시간 가상 환경을 공유하는 MMOG(Massive Multi-player On-line Game)를 지원하고자 본 논문에서 P2P(Peer-to-Peer)와 클라우드 컴퓨팅의 기술적 장점을 결합하는 기법을 제시한다. 본 논문에서 제시된 클라우드 컴퓨팅 기반의 P2P 시스템은 사용자 수가 급증할 경우에도 사용자 자원을 기반 구조에 추가함으로써 준수한 수준의 확장성을 제공할 수 있다. 또한 이 시스템은 사용자들의 처리 능력을 활용함으로써 클라우드에 있는 서버의 부하 즉 상당한 컴퓨팅 능력과 통신량을 절감할 수 있다. 본 논문에서 MMOG의 확장성을 위한 클라우드 컴퓨팅 기반의 P2P 시스템의 개념과 기본적 구조가 기술된다. 대규모 사용자 집단에 대한 경제적 비용과 서비스 품질의 규모를 고려하는 이 구조가 실현되기 위해서는 효율적이고 효과적인 자원의 공급과 부하의 배분이 반드시 필요하다. 시뮬레이션 결과 제시된 P2P 시스템은 동시에 실행되는 사용자들의 수가 증가할 때 클라우드와 사용자 제공 자원의 양을 제어함으로써 사용자들의 충분한 대역폭을 활용하는 반면 서버의 대역폭을 감소시킬 수 있는 것으로 나타났다.

• 한국전자통신학회논문지
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• 제16권6호
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• pp.1081-1088
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• 2021

현대 무선통신 시스템은 대규모의 안테나 요소가 장착된 메시브 배열 안테나를 사용하여 다수의 사용자에게 원활한 통신 서비스를 지원하기 위해 빔형성 기술을 활용한다. 신뢰도 높은 빔형성 기술은 안테나로 입사되는 신호에 대한 도래각(Angle-of-Arrival : AOA) 정보가 필수적으로 요구되는데, 일반적으로 도래각 정보는 고분해 성능을 가지는 MUSIC(: Multiple Signal Classification)과 같은 도래각 추정 알고리즘을 통해 추정된다. MUSIC 알고리즘은 우수한 추정성능을 갖지만, 메시브 배열 안테나 사용 시 알고리즘의 급격한 복잡도 증가로 인해 실시간 도래각 추정이 어렵다. 이와 같은 문제점을 개선하기 위해, 본 논문은 안테나 요소 ON/OFF 기능을 가지는 FMCCA(: Flexible Massive Concentric Circular Array) 안테나 기반의 캐스케이드 도래각 추정 알고리즘을 제안한다. 제안된 캐스케이드 AOA 추정 알고리즘은 전체 안테나 요소 중 일부 안테나 요소를 사용하는 CAPON 알고리즘과 전체 안테나 요소를 사용하는 Beamspace MUSIC 알고리즘으로 구성되며, 다양한 시나리오를 가정한 컴퓨터 시뮬레이션을 통해 알고리즘의 도래각 추정 성능을 검증한다.

• 한국정보전자통신기술학회논문지
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• 제14권6호
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• pp.445-451
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• 2021

최근 코로나19 확산과 피해가 늘어나는 가운데 감염을 차단하기 위해 가장 중요한 것은 감염자를 조기에 찾아내는 것이다. 지난 반세기 전에 등장한 그룹검사(group testing)가 최근 코로나19 진단 방법으로써 활용 가능하며 매우 효율적인 방법으로 자리 잡고 있다. 본 논문에서는 기존의 그룹검사 알고리즘들의 동작원리를 살펴본다. 그리고 압축센싱(compressed sensing)에서 제안한 희소 신호 복원 방법을 개선하여 그룹검사의 해법으로 제시한다. 압축센싱과 그룹검사는 연산 방법에서 차이가 있지만 희소 신호를 찾는다는 점에서 유사하다. 시뮬레이션 결과를 통해 제안하는 희소 신호 복원 방법의 성능 우수성을 보여준다. 주목할 점은 모든 결함 샘플을 정확히 찾고자 하는 그룹검사 시스템에서는 제안하는 방법이 다른 알고리즘보다 월등한 성능 향상을 보여준 것이다. 또한 결함 샘플 수가 적을 때보다는 많을 때 그 성능이 크게 개선된다.

• Membrane and Water Treatment
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• 제13권5호
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• pp.235-243
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• 2022

The paper presents the effect of operating temperatures and flow rates on the distillate flux that can be obtained from a hydrophobic membrane having the characteristics: pore size of 0.15 ㎛; thickness of 130 ㎛; and 85% porosity. That membrane in the present investigation could be the direct contact (DCMD) or the air-gap membrane distillation (AGMD). To model numerically the membrane distillation processes, the two-dimensional computational fluid dynamic (CFD) is used for the DCMD and AGMD cases here. In this work, DCMD and AGMD models have been validated with the experimental data using different flows (Parallel and Counter-current flows) in non-steady-state situations. A good agreement is obtained between the present results and those of the experimental data in the literature. The new approach in the present numerical modeling has allowed examining effects of the nature of materials (Polyvinylidene fluoride (PVDF) polymers, copolymers, and blends) used on thermal properties. Moreover, the effect of the area surface of the membrane (0.021 to 3.15 ㎡) is investigated to explore both the laminar and the turbulent flow regimes. The obtained results found that copolymer P(VDF-TrFE) (80/20) is more effective than the other materials of membrane distillation (MD). The mass flux and thermal efficiency reach 193.5 (g/㎡s), and 83.29 % using turbulent flow and an effective area of 3.1 ㎡, respectively. The increase of feed inlet temperatures and its flow rate, with the reduction of cold temperatures and its flow rate are very effective for increasing distillate water flow in MD applications.

• Smart Structures and Systems
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• 제28권6호
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• pp.745-760
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• 2021

Dynamic buckling of structure is one of the failure modes that needs to be considered since it may result in catastrophic failure of the structure in a short period of time. For a thin fiber-reinforced polymer (FRP) plate under compression, buckling is an inherent hazard which will be intensified by the existence of defects like holes, cracks, and delamination. On the other hand, the growth of the delamination is another prime concern for thin FRP plates. In the current paper, reinforcing the plates against buckling is realized by using SMA wires in the form of stitches. A numerical framework is proposed to simulate the dynamic instability emphasizing the effect of the SMA stitches in suppressing delamination growth. The suggested algorithm is more accurate than the other methods when considering the transformation point of the SMA wires and the modeling of the cohesive zone using simple and yet reliable technique. The computational design of the method by producing the line by line orders leads to a simple algorithm for simulating the super-elastic behavior. The Lagoudas constitutive model of the SMA material is implemented in the form of user material subroutines (VUMAT). The normal bilinear spring model is used to reproduce the cohesive zone behavior. The nonlinear finite element formulation is programmed into FORTRAN using the Newmark-beta numerical time-integration approach. The obtained results are compared with the results obtained by the finite element method using ABAQUS/Explicit solver. The obtained results by the proposed algorithm and those by ABAQUS are in good agreement.

• Wind and Structures
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• 제34권5호
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• pp.407-419
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• 2022

Many factors should be considered by architects and designers for designing a tall building. Wind load is one of these important factors that govern the design of tall building structures and can become a serious challenge when buildings tend to be built very tall and slender. On the other hand, through the initial stages of a design process, choosing the design geometry greatly affects the wind-induced forces on a tall building. With this respect, geometric shapes with 3-fold rotational symmetry are one of the applied plan shapes in tall buildings. This study, therefore, aims to investigate the aerodynamic characteristics of 8 different geometrical shapes using Computational Fluid Dynamics (CFD) by measuring the drag and lift forces. A case study approach was conducted in which different building shape models have the same total gross area and the same height of 300 meters. The simulation was an incompressible transient flow that ran 1700 timesteps (85 seconds on the real-time scale). The results show a great difference between wind-induced force performance of buildings with different plan shapes. Generally, it is stated that the shapes with the same area, but with smaller perimeters, are better choices for reducing the drag force on buildings. Applying the lift force, the results show that the buildings with plan shapes that have rounded corners act better in crosswind flow while, those with sharp corners induce larger forces in the same direction. This study delivers more analytical understanding of building shapes and their behavior against the wind force through the parametric modelling.

• Steel and Composite Structures
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• 제44권2호
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• pp.241-254
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• 2022

The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.

• 한국소프트웨어감정평가학회 논문지
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• 제16권2호
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• pp.53-62
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• 2020

IoT 환경의 최종 사용자 도메인에서 점점 더 많은 수의 지능형 M2M(Machine-to-Machine Communication) 장치가 애플리케이션 서비스를 생성하고 공유하기 위한 자원을 제공한다. 따라서 기존의 중앙집중식 서비스 제공자의 역할을 P2P 환경의 최종 사용자에게 이전하여 신뢰를 관리하는 것은 매우 유용할 수 있다. 그러나 최종 사용자가 독립적으로 서비스를 제공하거나 소비하는 비중앙집중식 M2M 컴퓨팅 환경에서는 상호간의 신뢰 구축이 가장 중요한 요인이 된다. 오작동하는 서비스를 구축하려는 악의적인 사용자들이 IoT와 같은 M2M 컴퓨팅 환경에서 보안문제를 야기할 수 있기 때문이다. 본 논문에서는 M2M 애플리케이션 서비스의 신뢰 평가를 위한 통합적인 분석과 접근방식을 제공하고, M2M 커뮤니티의 사용자들 사이의 신뢰도를 보장할 수 있는 최적화된 신뢰 평가 모델을 제시한다.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.334-342
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• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.