Thin-film shape technology is recognized for its core technology to enhance the technology of LCD, PDP, semiconductor manufacturing processes, hard disks and optical disks, and is widely used to form coated thin films of products. In addition, resistance(electron beam filament) technology for heating is used to manufacture filament for ion implants used in semiconductor manufacturing processes. By establishing an electronic beam filament production system and developing seven specifications of electronic beam filament, it is contributing to improving trade dynamics and increasing exports to Japan through localized media of theoretical imports to domestic companies. In this study, CAE analysis was performed after setting electron beam filament specification and development objectives, facilities and fabrication for electron beam filament production, electron beam filament JIG & fixture design and fabrication followed by electron beam filament prototype. Then, the automation and complete inspection equipment of the previously developed electronic beam filament manufacturing facilities was developed and researched to mass-produce them, to analyze and modify prototypes, design and manufacture automation facilities, and finally, to design and manufacture the complete inspection equipment. In this paper, mainly electron beam filament specification analysis and development objectives and CAE analysis were dealted with.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on indoor mobile robot position recognition and driving experiment using QR Code during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on the driving control of indoor mobile robot during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on experimental environments for testbeds during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the driving directions of QR Code-aware movable robots during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the application of QR Code position recognition during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the application of QR Code recognition system during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the speculative navigation using auxiliary encoder during the development of QR Code-aware indoor mobility robots.

본 연구의 목적은 겨울철 약광기 보광 시 줄기 유인 수가 온실 파프리카의 생육, 과실의 품질 및 생산량에 미치는 영향을 구명하는 것이다. 파프리카는 2020년 10월 26일에 m 2당 3.2 주를 정식하였고, 2020년 12월 1일부터 고압나트륨등을 작기 종료일인 2021년 5월 25일까지 하루 16시간의 광주기로 조사 하였다. 줄기 유인 처리는 분지 이후의 생장점이 각각 2, 3개로 유지되도록 유인해 주었다. 초장은 2줄기 유인 처리구에 비해 3줄기 유인 처리구에서 유의적으로 짧았고 마디수 및 엽수는 2줄기 유인 처리구에 비해 3줄기 유인 처리구에서 유의적으 로 증가했다. 엽면적 및 기관별 건물중은 통계적으로 유의한 차이를 보이지 않았다. 과실 생체중 및 건물중은 모든 처리구에서 생육단계에 따라 감소하는 경향을 보였으며, 3줄기 유인 처리구가 2줄기 유인 처리구에 비해 낮은 수치를 보였다. 3줄 기 유인 처리구의 상품과율은 95.4%로 2줄기 유인 처리구의 93.6%에 비해 높았다. 총 수확량은 3줄기 유인 처리구에서 30.2% 높게 나타났다. 결론적으로 온실 파프리카의 3줄기 유인 재배는 적정 수준의 영양생장을 유지함으로써 과실 생산량에 긍정적인 영향을 미쳤다고 할 수 있다. 본 연구 결과는 파프 리카의 생산량 증대를 위한 농가 의사결정에 활용될 수 있을 것으로 사료된다.