• International Journal of Internet, Broadcasting and Communication
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• 제16권1호
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• pp.307-313
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• 2024

This study explores the integration of Explainable Artificial Intelligence (XAI) and network science in healthcare, focusing on enhancing healthcare data interpretation and improving diagnostic and treatment methods. Key methodologies like Graph Neural Networks, Community Detection, Overlapping Network Models, and Time-Series Network Analysis are examined in depth for their potential in patient health management. The research highlights the transformative role of XAI in making complex AI models transparent and interpretable, essential for accurate, data-driven decision-making in healthcare. Case studies demonstrate the practical application of these methodologies in predicting diseases, understanding drug interactions, and tracking patient health over time. The study concludes with the immense promise of these advancements in healthcare, despite existing challenges, and underscores the need for ongoing research to fully realize the potential of AI in this field.

• 전자통신동향분석
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• 제34권4호
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• pp.15-22
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• 2019

Recent technological advances in three-dimensional (3D) sensing devices and machine learning such as deep leaning has enabled data-driven 3D applications. Research on artificial intelligence has developed for the past few years and 3D deep learning has been introduced. This is the result of the availability of high-quality big data, increases in computing power, and development of new algorithms; before the introduction of 3D deep leaning, the main targets for deep learning were one-dimensional (1D) audio files and two-dimensional (2D) images. The research field of deep leaning has extended from discriminative models such as classification/segmentation/reconstruction models to generative models such as those including style transfer and generation of non-existing data. Unlike 2D learning, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become increasingly popular owing to advances in 3D vision technology, the generation/acquisition of 3D data is still very difficult. Even if 3D data can be acquired, post-processing remains a significant problem. Moreover, it is not easy to directly apply existing network models such as convolution networks owing to the various ways in which 3D data is represented. In this paper, we summarize technological trends in AI-based 3D content generation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3473-3487
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• 2020

In this paper, we present a new approach to creating speech animation with emotional expressions using a small set of example models. To generate realistic facial animation, two example models called key visemes and expressions are used for lip-synchronization and facial expressions, respectively. The key visemes represent lip shapes of phonemes such as vowels and consonants while the key expressions represent basic emotions of a face. Our approach utilizes a text-to-speech (TTS) system to create a phonetic transcript for the speech animation. Based on a phonetic transcript, a sequence of speech animation is synthesized by interpolating the corresponding sequence of key visemes. Using an input parameter vector, the key expressions are blended by a method of scattered data interpolation. During the synthesizing process, an importance-based scheme is introduced to combine both lip-synchronization and facial expressions into one animation sequence in real time (over 120Hz). The proposed approach can be applied to diverse types of digital content and applications that use facial animation with high accuracy (over 90%) in speech recognition.

• 한국시뮬레이션학회논문지
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• 제8권1호
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• pp.113-138
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• 1999

Driven by the explosive expansion and acceptance of the Internet and its multimedia front-end, the Web, a new generation of the modeling and simulation tools have come up with the name of Web-Based Simulation (WBS). Most of WBS libraries inherit its powerful advantages from Java. However, there are cases where explicit specification of models or interface objects is more desirable than the black-box programs. This paper presents an XML-based DEVS (Discrete Event System Specification) markup language for sharing simulation models on the Web. DEVS provides a system-theoretic formalism for the language while XML supports platform-independent data access. This paper focuses on the design of such a language.

• Computers and Concrete
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• 제28권6호
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• pp.605-619
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• 2021

Building Information Modeling (BIM) models are a powerful tool for preserving and using architectural history. Manually creating information models for such a significant number and variety of architectural monuments as Dong drum towers is challenging. The building logic based on "actual measurement construction" was investigated using the metamodel idea, and a metamodel-based automated modeling approach for the wood framework of Dong drum towers was presented utilizing programmable algorithms. Metamodels of fundamental frame kinds were also constructed. Case studies were used to verify the automated modeling's correctness, completeness, and efficiency using metamodel. The results suggest that, compared to manual modeling, automated modeling using metamodel may enhance the model's integrity and correctness by 5-10% while also reducing time efficiency by 10-20%. Metamodel and construction logic offer a novel way to investigate data-driven autonomous information-based modeling.

• 한국분말재료학회지
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• 제31권2호
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• pp.137-145
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• 2024

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

• Wind and Structures
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• 제15권3호
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• pp.247-261
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• 2012

Some numerical investigations are presented concerning the response of a given plate under turbulence driven excitations. Three different input loads are simulated according to the wall pressure distributions derived from the models proposed by Corcos, Efimtsov and Chase, respectively. Modal solutions (finite element based) are used for building the modal stochastic responses in the sub-critical aerodynamic frequency range. The parametric investigations concern two different values of the structural damping and three values of the boundary layer thickness. A final comparison with available experimental data is also discussed. The results demonstrate that the selection of the adequate TBL input model is still the most critical step in order to get a good prediction.

• 한국통신학회논문지
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• 제41권8호
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• pp.928-941
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• 2016

유선 데이터 네트워크(wired data network) 영역에서 가장 많은 에너지를 요구하는 영역은 액세스 네트워크(access network) 영역이다. 오늘날 그린 네트워킹(Green networking)은 유선 데이터 네트워크에서도 통합적인 에너지 관리를 통해 에너지 낭비와 $CO_2$ 배출 감소를 유도하기 위해 주요 관심분야가 되었다. 그러나 유선 액세스 네트워크의 에너지 소모량과 $CO_2$ 배출에 의한 환경적 영향에 대해서는 널리 알려져 있지 않으며, 그에 따른 범용적이고 정량적인 평가 기준도 매우 부족하다. 본 논문에서는 유선 액세스 네트워크의 에너지 소모량을 추정하는 기존의 모델링 기법들의 문제점을 비교 분석하고 하향식(top-down) 접근법을 이용하여 대규모 유선 액세스 네트워크의 에너지 소모량을 추정하는 모델링 기법을 제안한다. 또한 제안 모델로부터 도출된 추정치를 이용하여 액세스 네트워크들이 환경에 미치는 영향도를 산출하는 모델을 제안한다. 그리고 실제 사례를 적용하여 기존 모델과 제안 모델로부터 산출한 추정치와 해당 사례에 대한 기존의 조사와 실측 데이터와 비교 평가 한다.

• 대한원격탐사학회지
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• 제36권4호
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.

• Smart Structures and Systems
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• 제26권4호
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• pp.495-506
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• 2020

Monitoring of complex processes faces several challenges mainly due to the lack of relevant sensory information or insufficient elaborated decision-making strategies. These challenges motivate researchers to adopt complex data processing and analysis in order to improve the process representation. This paper presents the development and implementation of quality monitoring framework based on a model-driven approach using embedded artificial intelligence strategies. In this work, the strategies are applied to the supervision of a microfabrication process aiming at showing the great performance of the framework in a very complex system in the manufacturing sector. The procedure involves two methods for modelling a representative quality variable, such as surface roughness. Firstly, the hybrid incremental modelling strategy is applied. Secondly, a generalized fuzzy clustering c-means method is developed. Finally, a comparative study of the behavior of the two models for predicting a quality indicator, represented by surface roughness of manufactured components, is presented for specific manufacturing process. The manufactured part used in this study is a critical structural aerospace component. In addition, the validation and testing are performed at laboratory and industrial levels, demonstrating proper real-time operation for non-linear processes with relatively fast dynamics. The results of this study are very promising in terms of computational efficiency and transfer of knowledge to manufacturing industry.