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드라이브 스루의 서비스 품질이 만족과 행동의도에 미치는 영향:패스트 푸드점을 중심으로
김동범 (사)한국조리학회 2020 한국조리학회지 Vol.26 No.10
The purpose of this study is to investigate the effect of service quality (physical environment quality, interaction quality, outcome quality) on satisfaction and behavioral intention for consumers using drive- thru services. Data was collected from consumers who have used the drive-thru service of fast food restaurants (McDonald’s, Burger king, Lotteria, Kfc) within the last three months. The survey period was from August 1, 2020 to August 20, and a total of 257 questionnaires were collected through online research company. Data analysis was performed using SPSS 22.0 and AMOS 22.0 for demographic analysis, descriptive statistics analysis, reliability analysis, confirmatory factor analysis, correlation matrix analysis and structural equation modeling. The results of this study are as follows. First, the physical environmental quality had a positive (+) effect on satisfaction. Second, interaction quality had a positive (+) effect on satisfaction. Third, outcome quality had a positive (+) effect on satisfaction. Fourth, satisfaction had a positive (+) effect on behavioral intention. Through this study, the service quality, satisfaction, and behavioral intentions of consumers who have used the drive-thru service of fast food restaurants are presented from multiple perspectives. Also implications and limitations through the results of this study were mentioned.
불확정 표적 모델에 대한 순환 신경망 기반 칼만 필터 설계
김동범,정대교,임재혁,민사원,문준 한국군사과학기술학회 2023 한국군사과학기술학회지 Vol.26 No.1
For various target tracking applications, it is well known that the Kalman filter is the optimal estimator(in the minimum mean-square sense) to predict and estimate the state(position and/or velocity) of linear dynamical systems driven by Gaussian stochastic noise. In the case of nonlinear systems, Extended Kalman filter(EKF) and/or Unscented Kalman filter(UKF) are widely used, which can be viewed as approximations of the(linear) Kalman filter in the sense of the conditional expectation. However, to implement EKF and UKF, the exact dynamical model information and the statistical information of noise are still required. In this paper, we propose the recurrent neural-network based Kalman filter, where its Kalman gain is obtained via the proposed GRU-LSTM based neural-network framework that does not need the precise model information as well as the noise covariance information. By the proposed neural-network based Kalman filter, the state estimation performance is enhanced in terms of the tracking error, which is verified through various linear and nonlinear tracking problems with incomplete model and statistical covariance information.
김동범,추연근,조해용,Kim, Dongbum,Qiu, Yuangen,Cho, Hae-Yong 대한용접접합학회 2015 대한용접·접합학회지 Vol.33 No.3
Self-piercing riveting is an joining method of advanced high strength steels (AHSS) and other dissimilar materials. It has attracted considerable interest from the automotive industry. The SPR has become an interesting alternative joining technique for difficult to weld materials such as steels and aluminium alloys. In this paper, self-piercing rivet and anvil for SPR were designed for the joining conditions with AHSS and aluminium alloy. Various conditions of SPR were simulated for the design of rivets and anvils. The simulated results were in good agreement with experimental ones. As a result, over HV500 rivet is desirable to joint SPFC780 AHSS and aluminum alloy.
국방획득체계에서의 지속적 기술 최신화 전략 : 기술의 진부화 장벽을 넘어
김동범,김호성 한국방위산업학회 2023 韓國防衛産業學會誌 Vol.30 No.2
무기체계 획득에 있어 장기적인 프로세스는 급속히 변화하는 기술 환경과 미래 전장 환경의 요구를 맞추는 데 중대한 어려움을 초래한다. 최첨단 기술을 획득 단계에서 통합하더라도, 긴 획득 과정을 통해 전력화 단계에 도달하는 시점에는 해당 기술이 이미 진부화된 상태에 이르게 된다. 더욱이, 기술의 최신화 없이 장기간 운용 유지 단계를 유지하면 변화하는 전장 환경에 대응하는 것에 한계에 봉착하게 된다. 본 연구는 기술 퇴화 방지를 위한 미국의 국방획득 혁신 사례와 국내의 국방획득사례를 분석하여, 기존의 무기체계 획득제도 아래에서 기술 진부화를 극복하고 최신 기술을 통합할 수 있는 방안을 제시하여최신 기술을 통합한 무기체계를 획득하는데 필요한 해결책을 제시한다. 첫째, 최신 기술을 통합할 수 있는 대상 기술에 중점을 둔 모듈화 설계의 필요성을 제시한다. 둘째, 최신화 대상 기술을 식별하기 위한 '피드포워드(Feedforward)' 기술 발전 예측 모델을 제안한다. 이 개념은 체계공학(SE)의 각 단계에 통합되어 무기획득이 이루어져야 한다. 본 연구에서 제시한 두 가지 발전 전략은 현재 우리의 무기획득체계에서 겪고 있는 기술 진부화의 문제를 극복하고 무기체계 개발에 적용되고 있는 기술을 보다 최신화 된 것을 받아들일 수 있을 방안이 될 것이다. The protracted processes in defense acquisition systems present significant challenges in adapting to the rapidly changing technological environment and the evolving needs of future battlefields. Even when cutting-edge technologies are integrated at the acquisition stage, they often reach obsolescence by the time the system becomes operational, owing to the lengthy acquisition procedures. Moreover, maintaining a system for an extended period without upgrading technology renders it ineffective in responding to changing battlefield conditions. This research attempts to identify solutions for integrating up-to-date technologies and overcoming technological obsolescence within the existing weapons acquisition system, a necessary step for acquiring weapons systems equipped with the latest technology. Through an analysis of the United States' innovative defense acquisition practices aimed at preventing technological obsolescence, and an examination of domestic defense acquisition cases, this study first emphasizes the need for modular design focused on target technologies capable of incorporating the most recent advancements. Secondly, it proposes a 'Feedforward' predictive model for identifying technologies prone to upgrades. Ultimately, this study develops a model that integrates these elements at each stage of systems engineering (SE). It offers a way to overcome the challenges of technological obsolescence and align the defense acquisition process with the pace of modern technological progress