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문형철,조인권,임주락,고복래,김대향,황창연,Moon Hyung-Cheol,Cho In-Kwon,Im Ju-Rock,Goh Bok-Rae,Kim Dae-Hyang,Hwang Chang-Yeon 한국응용곤충학회 2006 한국응용곤충학회지 Vol.45 No.1
전북지역 노지 고추 포장에서 총채벌레의 발생소장과 피해 정도를 조사하였다. 고추에 발생하는 총채벌레는 꽃노랑총채벌레와 대만총채벌레이었다. 총채벌레는 5월 5반순 이후 증가하기 시작하여 7월 $2{\sim}4$반순경에 발생이 가장 많았으며 4차례의 발생최성기를 나타냈다. 1차 발생최성기는 6월 4반순, 2차는 7월 2반순, 3차는 8월 3반순, 4차는 9월 4반순이었다. 총채벌레에 의한 고추 피해증상은 과실 끝부분에 부착된 꽃잎 밑에서 총채벌레가 가해함에 따라 이 부위에 검은색의 가해흔이 남게 되며, 고추가 붉게 변해감에 따라 피해부위가 백색으로 되는 것으로 이에 따른 상품가치가 하락되게 된다. 또한 기형과의 발생이 많아지게 되며 과실 꼭지 부분이 총채벌레가 가해함에 따라 거칠게 되는 것으로 조사되었다. 총채벌레에 의한 피해과율은 8월 상순에 임실지역에서 20.8%로 가장 높았으며, 꽃당 발생밀도는 7월 중순에 가장 높았다. Seasonal occurrence of thrips and its damage on fruits were studied at in open field red pepper in Jeonbuk Province. The kind of thrips were Franklinella occidentalis and F. intonsa. The ratio of F. occidentalis was about 30% in periods of survey. Density of thrips increased in late May and showed peak occurrence in early to middle July. The peak occurrence of thrips was appeared at 4 pentad June, 2 pentad July, 3 pentad August, and 4 pentad September. The part of fruit damaged by thrips became discolored and roughed. When turned red, the colors of damaged parts changed from dark brown to yellowish brown. As a result, damage fruits by thrips decreased marketability. The percent of damaged fruits was highest in Imsil at 20.8% in early August. Density of thrips on flowers was highest in middle July.
음성기반 지능형 시스템의 사용자 만족도에 영향을 미치는 인터랙션 설계변수들의 정의 및 분류방안
신종규(Jong Gyu Shin),조인권(In Gwon Jo),임완수(Wan Su Lim),김상호(Sang Ho Kim) 대한인간공학회 2020 大韓人間工學會誌 Vol.39 No.1
Objective: The aim of this study is to identify a few critical design parameters for enhancing user"s satisfaction while interacting with the AI-infused intelligent systems through voice user interface (VUI). Background: The interaction between the user and the AI-infused system is called as Human-AI Interaction (HAII) and supposed to have different features with respect to the human-computer interaction (HCI). It is therefore necessary to establish new criteria for designing and evaluating HAII in the point of user"s satisfaction. Method: This study identified 31 user requirements regarding with HAII from previous studies and organized them into 9 secondary and 3 tertiary level user requirement categories. It was investigated and selected 9 design parameters of VUI that might make differences in user"s satisfaction. The priority of each design parameter was calculated using quality function deployment (QFD) technique. Results: The amount of information, error control, and length of answer were found as the top three critical design parameters among others. They accounted for 51% of the total criticality score. It implies the reliability of information that the AI-infused systems provide during interaction is the most important factor for enhancing user"s satisfaction. Conclusion: This study suggested theoretically nine critical interaction parameters and their priority in designing VUI embedded in AI-infused systems. Application: The result of the study can be used to derive various experimental research models and hypothesis in HAII.
A Study on Identifying Human Factors in Collaboration with the AI-infused Systems
Ismatullaev Ulugbek Vahobjon U,In Gwon Jo(조인권),Sang Ho Kim(김상호) 대한인간공학회 2020 대한인간공학회 학술대회논문집 Vol.2020 No.6
Objective: This paper aims to analyze the human factors in artificial intelligence and discuss the Human-AI collaboration based on previous researches in three major fields such as healthcare, teaching and automated driving. Background: Despite the fact that artificial intelligence is one of the largest and most important inventions of the present, the researches have shown that there are several challenges of using artificial intelligence in the cooperation with human teammates. AI-Infused systems may perform certain operations or tasks faster and more precisely than a person, play chess, drive a car and perform many functions. But, depending on the different type of human factors, users may interact differently with artificial intelligence, and those factors make some challenges in the relationship between human and artificial intelligence. Method: This paper was conducted in three steps: (1) Reviewing previous researches on human factors in three areas; (2) Categorizing human factors in to the table to analyze their importance in adoption to AI infused systems; (3) Identifying the most critical human factors of individuals in three fields in collaboration with artificial intelligence devices to deal with the challenges of AI acceptance to improve teamwork and work efficiency as well as reducing errors mostly caused by human factors for each field. Results: Gender, age and trust in technology are found the most critical factors for each fields, while technology expertise and social influence factors plays important role in adoption AI-Infused systems in Education and Healthcare. Conclusion: It is found that, autonomous driving is most discussed field in terms of use human factors in the interaction with artificial intelligence, while there is still lack of researches about the adoption to AI technologies in education and healthcare based on some differences of human factors such as health, cognitive, work and , physical capabilities. Application: Findings of this study can help for the further studies focusing on identifying the cause of human errors that can be occurred in takeover or handover scenarios in terms of use AI-Infused Systems in healthcare, autonomous driving, and education.