• 제목/요약/키워드: Data-driven approach

검색결과 296건 처리시간 0.027초

Data-driven Adaptive Safety Monitoring Using Virtual Subjects in Medical Cyber-Physical Systems: A Glucose Control Case Study

  • Chen, Sanjian;Sokolsky, Oleg;Weimer, James;Lee, Insup
    • Journal of Computing Science and Engineering
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    • 제10권3호
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    • pp.75-84
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    • 2016
  • Medical cyber-physical systems (MCPS) integrate sensors, actuators, and software to improve patient safety and quality of healthcare. These systems introduce major challenges to safety analysis because the patient's physiology is complex, nonlinear, unobservable, and uncertain. To cope with the challenge that unidentified physiological parameters may exhibit short-term variances in certain clinical scenarios, we propose a novel run-time predictive safety monitoring technique that leverages a maximal model coupled with online training of a computational virtual subject (CVS) set. The proposed monitor predicts safety-critical events at run-time using only clinically available measurements. We apply the technique to a surgical glucose control case study. Evaluation on retrospective real clinical data shows that the algorithm achieves 96% sensitivity with a low average false alarm rate of 0.5 false alarm per surgery.

몽골 창업가들의 창업동기, 자기효능감 및 기업가지향성과 창업성과간의 관계: 성별 차이 (Effects of Mongolian Startup's Motivation, Self-Efficacy and Entrepreneurial Orientation on Performance: gender differences)

  • ;강신형;박상문
    • 아태비즈니스연구
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    • 제13권4호
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    • pp.123-134
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    • 2022
  • Purpose - The purpose of this study is to investigate the effects of entrepreneurial motivation, self-efficacy, and entrepreneurial orientation on the performance of Mongolian entrepreneurs. Design/methodology/approach This study collected data from a survey on 236 entrepreneurs in Mongolia and investigate research hypotheses by empirical analysis. Findings It was found that entrepreneurial motivation (independence, opportunity-driven, achievement motivation) had a positive effect on the startups' performances, and necessity-driven motivation did not have a significant effect on the startups' performances. Entrepreneurial self-efficacy and entrepreneurial orientation had a positive effect on performance of startups. There are differences by gender on the relationships between entrepreneurial motivations and startup performances. Research implications or Originality This paper investigates the effects of entrepreneurial motivation, self-efficacy, and entrepreneurial orientation on the performance of startups in Mongolian.

인공위성 원격 탐사 정보가 자료 기반 모형의 미계측 유역 하천유출 예측성능에 미치는 영향 분석 (Analysis of the Impact of Satellite Remote Sensing Information on the Prediction Performance of Ungauged Basin Stream Flow Using Data-driven Models)

  • 서지유;정하은;원정은;최시중;김상단
    • 한국습지학회지
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    • 제26권2호
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    • pp.147-159
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    • 2024
  • 부족한 하천유출 관측 데이터는 모델 보정 작업을 어렵게 만들어 모델의 성능 향상을 제한한다. 위성 기반 원격탐사 자료는 수문 관련 데이터의 확보에 적극적으로 활용될 수 있으므로 새로운 대안이 될 수 있다. 최근에는 여러 연구를 통하여 기존의 개념적/물리적 모델보다는 인공지능을 이용한 해법이 더 적절하다는 평가를 받고 있다. 본 연구에서는 다양한 순환 신경망들과 의사결정나무 기반 알고리즘들을 결합한 자료 기반 접근 방식을 제안하였다. 또한 인공지능 학습을 위하여 인공위성 원격탐사 정보의 활용성을 조사하였다. 본 연구에서 위성영상은 MODIS와 SMAP의 자료가 사용된다. 공적으로 공개된 25개 유역의 자료를 사용하여 제안된 접근 방식을 검증하였다. 전통적인 지역화 접근법에서 착안하여 모든 유역의 자료를 통합하여 하나의 자료 기반 모델을 학습하는 전략을 채택하였으며, Leave-one-out cross-validation 지역화 설정을 이용하여 하나의 모델이 다양한 유역의 하천유출을 예측함으로써 제안된 접근 방식의 잠재력을 평가하였다. GRU + Light GBM 모델이 대상 유역에 적합한 모델 조합으로 판명되었으며(25개 미계측 유역 일 하천유량 예측 모형효율계수 평균 0.7187) 하천유출이 매우 작은 시기를 제외하면 우수한 미계측 유역의 하천유출 예측 성능을 보여주었다. 인공위성 원격탐사 정보의 영향력은 최대 10% 정도로 파악되었으며, 위성 정보의 추가 적용이 풍수기 또는 평수기보다는 저수기 또는 갈수기의 하천유출 예측에 더 큰 영향을 미쳤다.

다 모델 방식과 모델보상을 통한 잡음환경 음성인식 (A Multi-Model Based Noisy Speech Recognition Using the Model Compensation Method)

  • 정용주;곽성우
    • 대한음성학회지:말소리
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    • 제62호
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    • pp.97-112
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    • 2007
  • The speech recognizer in general operates in noisy acoustical environments. Many research works have been done to cope with the acoustical variations. Among them, the multiple-HMM model approach seems to be quite effective compared with the conventional methods. In this paper, we consider a multiple-model approach combined with the model compensation method and investigate the necessary number of the HMM model sets through noisy speech recognition experiments. By using the data-driven Jacobian adaptation for the model compensation, the multiple-model approach with only a few model sets for each noise type could achieve comparable results with the re-training method.

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Text-driven Speech Animation with Emotion Control

  • Chae, Wonseok;Kim, Yejin
    • 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.

A Comparative Study on Requirements Analysis Techniques using Natural Language Processing and Machine Learning

  • Cho, Byung-Sun;Lee, Seok-Won
    • 한국컴퓨터정보학회논문지
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    • 제25권7호
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    • pp.27-37
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    • 2020
  • 본 연구의 목적은 다양한 도메인에 대한 소프트웨어 요구사항 명세서로부터 수집된 요구사항을 데이터로 활용하여 데이터 중심적 접근법(Data-driven Approach)의 연구를 통해 요구사항을 분류한다. 이 과정에서 기존 요구사항의 특징과 정보를 바탕으로 다양한 자연어처리를 이용한 데이터 전처리와 기계학습 모델을 통해 요구사항을 기능적 요구사항과 비기능적 요구사항으로 분류하고 각 조합의 결과를 제시한다. 그 결과로, 요구사항을 분류하는 과정에서, 자연어처리를 이용한 데이터 전처리에서는 어간 추출과 불용어제거와 같은 토큰의 개수와 종류를 감소하여 데이터의 희소성을 좀 더 밀집형태로 변형하는 데이터 전처리보다는 단어 빈도수와 역문서 빈도수를 기반으로 단어의 가중치를 계산하는 데이터 전처리가 다른 전처리보다 좋은 결과를 도출할 수 있었다. 이를 통해, 모든 단어를 고려하여 가중치 값은 기계학습에서 긍정적인 요인을 볼 수 있고 오히려 문장에서 의미 없는 단어를 제거하는 불용어 제거는 부정적인 요소로 확인할 수 있었다.

와도를 기저로 한 비압축성 점성유동해석 방법 (A Vorticity-Based Method for Incompressible Viscous Flow Analysis)

  • 서정천
    • 한국전산유체공학회지
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    • 제3권1호
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    • pp.11-21
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    • 1998
  • A vorticity-based method for the numerical solution of the two-dimensional incompressible Navier-Stokes equations is presented. The governing equations for vorticity, velocity and pressure variables are expressed in an integro-differential form. The global coupling between the vorticity and the pressure boundary conditions is fully considered in an iterative procedure when numerical schemes are employed. The finite volume method of the second order TVD scheme is implemented to integrate the vorticity transport equation with the dynamic vorticity boundary condition. The velocity field is obtained by using the Biot-Savart integral. The Green's scalar identity is used to solve the total pressure in an integral approach similar to the surface panel methods which have been well established for potential flow analysis. The present formulation is validated by comparison with data from the literature for the two-dimensional cavity flow driven by shear in a square cavity. We take two types of the cavity now: (ⅰ) driven by non-uniform shear on top lid and body forces for which the exact solution exists, and (ⅱ) driven only by uniform shear (of the classical type).

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Quality monitoring of complex manufacturing systems on the basis of model driven approach

  • Castano, Fernando;Haber, Rodolfo E.;Mohammed, Wael M.;Nejman, Miroslaw;Villalonga, Alberto;Lastra, Jose L. Martinez
    • 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.

A Quantitative Approach for Data Visualization in Human Resource Management

  • Bandar Abdullah AlMobark
    • International Journal of Computer Science & Network Security
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    • 제23권2호
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    • pp.133-139
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    • 2023
  • As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a quantitative method for analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

Eulerian-Lagrangian 다상 유동해석법에 의한 피에조인젝터의 니들-노즐유동 상관성 연구 (A Study on Relation of Needle-Nozzle Flow of Piezo-driven Injector by using Eulerian-Lagrangian Multi-phase Method)

  • 이진욱;민경덕
    • 한국자동차공학회논문집
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    • 제18권5호
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    • pp.108-114
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    • 2010
  • The injection nozzle of an electro-hydraulic injector is being opened and closed by movement of a injector's needle which is balanced by pressure at the nozzle seat and at the needle control chamber, at the opposite end of the needle. In this study, the effects of needle movement in a piezo-driven injector on unsteady cavitating flows behavior inside nozzle were investigated by cavitation numerical model based on the Eulerian-Lagrangian approach. Aimed at simulating the 3-D two-phase flow behavior, the three dimensional geometry model along the central cross-section regarding of one injection hole with real design data of a piezo-driven diesel injector has been used to simulate the cavitating flows for injection time by at fully transient simulation with cavitation model. The cavitation model incorporates many of the fundamental physical processes assumed to take place in cavitating flows. The simulations performed were both fully transient and 'pseudo' steady state, even if under steady state boundary conditions. As this research results, we found that it could analyze the effect the pressure drop to the sudden acceleration of fuel, which is due to the fastest response of needle, on the degree of cavitation existed in piezo-driven injector nozzle.