Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation.
Korea's defense industry has been fostered as a protection industry in which the government directly controls prices, quantities, and costs for the past 40 years, and it is deepening into a low-efficiency industrial structure. By implementing the Defense Industry Building Act in 2021, the government is creating a healthy ecosystem for the defense industry and strengthening its global competitiveness. In this study, based on KPC's Productivity Management System (PMS), a diagnostic model of defense companies that has been implemented since 2013, on-site diagnosis was performed from 4 to 28 days depending on the size of the company, and data was collected based on the results. For the effect of innovation capability on productivity performance, the causal relationship was analyzed through structural equation model path analysis. As a result, it suggests that defense materials suppliers should focus on which core processes to innovate and strengthen and improve their innovation capabilities.
대한민국의 항공산업 대표 기업인 한국항공우주산업의 최근 9년간의 성장과정을 경영진단모델(Productivity Management System)와 연계하여 경영진단과 OJT(On Job Training)를 수행하였고 표준경영시스템(Disciplinary system)에서 변화대응시 스템(Agile system)으로 성장하는 과정의 사례연구를 통한 기업의 경영시스템 고도화 과정과 지속 가능한 성장의 경영시스템 기반 확보에 관한 사례를 통한 실증연구 방향을 제시하고자 한다.
In this paper, we propose dead pixel detection and compensation method using nonlinear estimator for infrared camera. Infrared camera has dead pixel that is abnormal output values due to complex factors such as manufacturing process, electronic parts and so on. Dead pixels are able to affect detecting a small target. So, It needs detection and Compensation process. However, after Compensation, some dead pixels are remained and detected by the human. They are soft dead pixel. The key idea of this proposed method, detecting soft dead pixels, is that design a nonlinear estimator using image data characteristics. This propose is able to not only detect soft dead pixels but also pixel Compensation that reflects infrared camera output characteristics well.