• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

• Annual Conference of KIPS
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• 2023.11a
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• pp.1010-1011
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• 2023

코로나19 팬데믹 이후 배달 앱 사용량이 증가에 따라 배달 오토바이 수가 급증하면서 이와 관련 사고 또한 급격히 증가하는 추세를 보이고 있다. 특히 청각 장애인들은 도로에서 이러한 종류의 사고 위험에 더욱 노출되어 있으며, 이 문제를 해결하기 위해 구글 앱 인벤터를 사용하여 도로에서 오토바이 소리를 인식하는 인공지능 학습 모델을 개발하였다. 개발된 어플리케이션은 도로에서 오토바이 소리를 감지하고 사용자에게 진동과 사진으로 알림을 보냄으로써 사고를 예방에 기여할 수 있다.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.957-976
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• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.7-13
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• 2023

In this paper, Depression is a mental disorder characterized by a lack of enthusiasm and feelings of sadness, which significantly impairs daily functioning. In 2018, there was an increase in book sales in the essay genre, particularly the popularity of "healing essays." This trend is seen as challenging the negative image and prejudices associated with depression. In 2021, a significant rise in the proportion of 20-year-old patients with depression is attributed to factors like job-related stress, interpersonal issues, and financial burdens. Additionally, there is a strong correlation between depression and suicidal thoughts, particularly among individuals who have experienced feelings of depression. Despite the increasing prevalence of depression among young adults, research in this area is lacking. To address this gap, statistical tools such as logistic regression and chi-squared tests are employed. The analysis reveals various independent variables associated with feelings of depression, shedding light on the relationships between these factors.

• Korean Journal of Environment and Ecology
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• v.25 no.5
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• pp.717-724
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• 2011

The objectives of this study were to analyze environment in the forest and growth characteristics for investigating the characteristics of Robinia pseudoacacia distribution in a Pinus thunbergii forest at the coast. As a result of analyzing inhibitory factors of Robinia pseudoacacia distribution in a Pinus thunbergii forest at the coast, it is considered that the salt level included in a sea wind is supposed to be the primary factor of the slow growth for Robinia pseudoacacia since brown leaves, wilting and early leaf fall have appeared in the 0m spot from the artificial dune which has the high salt level. However, the soil properties and light environment hardly have a effect on the growth of Robinia pseudoacacia because there is no difference among planting places. Also, the growth ring of the horizontal root in 2year individuals 0.1~0.2m away from the dune have been formed for 1 year only as a consequence of analyzing growth rings of Robinia pseudoacacia growing on the coast. It can be infered that the nourishment of the horizontal root from individuals growing on the coast have been provided for the first 1 year only. It is estimated that, in case of the nearby areas on the coast, it is not enough to provided nourishment to the horizontal root due to obstructing the growth of new individuals by a sea wind, so the growth of the horizontal root would be hampered. Therefore, it is considered that impedient Robinia pseudoacacia distribution in a Pinus thunbergii forest at the coast is caused by making no growth of new horizontal roots and newborn individuals.

• Korean Journal of Ichthyology
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• v.33 no.4
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• pp.287-296
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• 2021

This study was conducted to investigate the species composition collected by fyke net and characteristics of the Erythroculter erythropterus population in the Asan Lake and Chungju Lake from June to September, 2021. The collected fish in Asan lake were identified as 4,977 individuals of 13 species from a total of six families and in Chungju lake were identified as 2,436 individuals of 18 species from a total of eight families. The dominant species in Asan lake, both the individuals and biomass were E. erythropterus with 4,470 (89.8%) and 498,424g (84.5%). The dominant species in Chungju lake, both the individuals and biomass were E. erythropterus with 1,327 (54.5%) and 301,818 g (77.5%). The results of the community analysis showed that a dominant index value of Asan lake was 0.93, higher than 0.71 of Chungju lake, and a diversity, evenness, and richness index value of Chungju lake were higher than of Asan lake. The frequency distribution of the total length analysis of the E. erythropterus population showed the appearance rate of 1~2 year olds was high in Asan lake, and the appearance rate of more than 2 years old were high in Chungju lake. The length-weight analysis of E. erythropterus in Asan Lake and Chungju Lake showed a regression coefficient b of 3.06 and 3.04, a condition factor (K) of 0.000128 and 0.000051 with a positive slope. This study could be served as baseline data for assessing habitat characteristics based on the species composition of fishes, and identifying health conditions of E. erythropterus in Asan Lake and Chungju Lake, artificial lakes.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Aquaculture
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• v.18 no.1
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• pp.13-18
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• 2005

This study was to investigate the effects of water temperature and food on the mass seed production of larval parrot fish, Oplegnathus fasciatus. Growth of the larvae reared at heated water temperature ($25.3^{\circ}C$) was significantly higher than that of the larvae reared at natural water temperature ($20.5^{\circ}C$). In addition, survival rate of the larvae at heated and natural sea water temperature were $24.0\%$ and $12.3\%$, respectively (P<0.05). Growth and survival rate of the larvae fed mixed diets of Nannochloropsis oculata, rotifer (Brachionus rotundiformis). Artemia nauplii, Tigriopus japonicus and artificial diets were significantly higher than that of the larvae fed only either rotifer or artificial diets (P<0.05). The average survival rate and total length of the larvae reared for 50 days after hatching were $22.5\%$ and 62.0$\pm$4.0 mm, respectively. Amount of consumed rotifers at one time feeding by a larva was rapidly increased with growth from 10.3 individuals per larva 5 day old to 65.5 individuals per larva 20 day old.

• Korean Journal of Environmental Biology
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• v.27 no.4
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• pp.375-383
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• 2009

The aims of this study were wintering individuals, usage of foraging sites, potential food availability, daily activity and disturbance factors of White-naped Cranes Grus vipio on the wintering site, Han-river estuary, Goyang and Gimpo city, Korea. We want to provide basic data to conserve the cranes. Maxium population was identified 162 individuals at the middle of February in the river side and mud flat of this study area. Spring migration for breeding was started at the first week of March and finished for two weeks later. White-naped Cranes were used four feeding sites in winter; agricultural area in Hongdopyong, Yihwa-dong, Pyong-dong and Songpo-dong. Expected carrying capacity (ECC) was 334 days (121~909 days). White-naped Cranes departed from roosting site to feeding site at every morning for foraging. If they were disturbed by some factors at feeding sites, they moved to mud flat in the Han river to forage and take a rest. Daily activity was consisted of six category; feeding, alert, locomotion, preening, comfort, social and other behaviors. Feeding was the highest portion among behaviors in the wintering area. Feeding, alert, locomotion and preening in daily activities significantly differed among feeding sites. We watched total 348 times of disturbances in the wintering sites. Artificial disturbances were vehicles, humans, bicycles and motorcycles. Natural disturbances were noises, animals and others. Disturbances in all wintering sites were highest in Yihwa-dong (134 times) and followed by Hongdopyong (109 times), Songpo-dong (64 times) and then Pyong-dong (44 times). And artificial disturbances (228 times) were more than natural disturbances (120 times). Especially, vehicle was one of the most checked factor in the wintering area.