• Journal of Korea Entertainment Industry Association
• /
• v.15 no.4
• /
• pp.15-29
• /
• 2021

Many countries and companies are pursuing and developing Artificial intelligence as it is the core technology of the 4th industrial revolution. Global IT companies such as Apple, Microsoft, Amazon, Google and Samsung have all released their own AI assistant hardware products, hoping to increase customer loyalty and capture market share. Competition within the industry for AI agent is intense. AI assistant products that command the biggest market shares and customer loyalty have a higher chance of becoming the industry standard. This study analyzed the current status of major overseas and domestic IT companies in the field of artificial intelligence, and suggested future strategic directions for voice UI technology development and user satisfaction. In terms of B2B technology, it is recommended that IT companies use cloud computing to store big data, innovative artificial intelligence technologies and natural language technologies. Offering voice recognition technologies on the cloud enables smaller companies to take advantage of such technologies at considerably less expense. Companies also consider using GPT-3(Generative Pre-trained Transformer 3) an open source artificial intelligence language processing software that can generate very natural human-like interactions and high levels of user satisfaction. There is a need to increase usefulness and usability to enhance user satisfaction. This study has practical and theoretical implications for industry and academia.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.261-282
• /
• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.51-66
• /
• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• KSBB Journal
• /
• v.20 no.4
• /
• pp.253-259
• /
• 2005

This study was accomplished using attached $A^2/O$ process that contains nonsurface-modified and surface-modified polyethylene media inside the Anaerobic/Anoxic, Oxic tank, respectively. We could make the hydrophobic polyethylene media have hydrophilic characteristics by radiating ion beam on the surface of the media. The objectives of this study is to investigate the removal efficiencies of the organics and nitrogen when the step feed ratio of raw wastewater into anaerobic and anoxic tank is changed. In this case, we assumed that the denitrification rate can be improved because the nitrifiers in anoxic tank can perform denitrification using RBDCOD instead of artificial carbon sources (for example, methanol, etc.). The wastewater injection rate into anaerobic/anoxic tank was set up by the ratio of 10 : 0, 9 : 1, 8 : 2, 6 : 4, and the results of BOD removal efficiency showed similar trends with $93.3\%,\;92.6\%,\;92.4\%\;and\;91.6\%$, respectively. But the BOD removal efficiency (utilization of the organics) in the anoxic tank was in the order of 9 : 1 $(84.8\%)$, 10 : 0 $(77.0\%)$, 8 : 2 $(75.3\%)$, and 6 : 4 $(61.1\%)$. The T-N removal efficiency was most high when the ratio is 9 : 1 $(67.4\%)$, and other conditions, 10 : 0, 8 : 2, 6 : 4, showed $61.3(\%),\;60.7\%,\;55.5\%$, respectively; the ratio 6 : 4 was found to be lowest T-N removal efficiency, lower than the ratio 9 : 1 by $12\%$. Though the nitrification rate of the ratio 10 : 0, 9 : 1, and 8 : 2 showed similar levels, the ratio 6 : 4 showed considerable inhibition of nitrification, ammonia was the great portion of the effluent T-N. The advantages of this process is that this process is cost-saving, and non-toxic methods than injecting the artificial carbon source.

• Cartoon and Animation Studies
• /
• s.49
• /
• pp.633-649
• /
• 2017

The purpose of this study is to conceptualize the changing aspects of human freedom of observation and viewing as the visual media evolves from film to 3D stereoscopic film and VR. The purpose of this study is to conceptualize the aspect of freedom and viewing aspect from the viewpoint of genealogy. In addition, I will identify the media aesthetic characteristics of VR and identify the identity and ontology of VR. Media has evolved around the most artificial sense of human being. There is a third visual space called screen at the center of all the reproduction devices centering on visual media such as painting, film, television, and computer. In particular, movies, television, and video screens, which are media that reproduce moving images, pursue perfect fantasy and visual satisfaction while controlling the movement of the audience. A mobilized virtual gaze was secured on the assumption of the floating nature of the so-called viewers. The audience sees a cinematic illusion with a view while seated in a fixed seat in a floating posture. They accept passive, passive, and passively without a doubt the fantasy world beyond the screen. But with the advent of digital paradigm, the evolution of visual media creates a big change in the tradition of reproduction media. 3D stereoscopic film predicted the extinction of the fourth wall, the fourth wall. The audience is no longer sitting in a fixed seat and only staring at the front. The Z-axis appearance of the 3D stereoscopic image reorganizes the space of the story. The viewer's gaze also extends from 'front' to 'top, bottom, left, right' and even 'front and back'. It also transforms the passive audience into an active, interactive, and experiential subject by placing viewers between images. Going one step further, the visual media, which entered the VR era, give freedom to the body of the captive audience. VR secures the possibility of movement of visitors and simultaneously coexists with virtual space and physical space. Therefore, the audience of the VR contents acquires an integrated identity on the premise of participation and movement. It is not a so-called representation but a perfection of the aesthetic system by reconstructing the space of fantasy while inheriting the simulation tradition of the screen.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.33-54
• /
• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Korean Journal of Ecology and Environment
• /
• v.43 no.2
• /
• pp.263-270
• /
• 2010

This is a research on development of water purification equipment called artificial floating island (=AFI) for the stagnant water area which can secure exuberant landscape and water-friendility. The equipment devised in this study is designed to make up the weakness of conventional AFIs and improves the removal efficiency of pollutants using the mixture of media and plants. The air compressor positioned at the inlet releases air with inflow continuously, the water pump at the outlet sprays as a form of fountain with causing a disturbance on stable water column, then, both of them contribute improvement of water quality over a large area. We applied Bio-stone as a media in this system and performed an experiment of pre-efficiency test, and we concluded that the higher pollutants concentration of inflow, the higher removal efficiency we obtained. At the result of lab-scale experiment, in the case of high-concentration inflow, in the removal efficiency of SS is 62.2%, BOD is 50.2%, COD is 55.1%, T-N is 31.6%, T-P is 38.4%. In addition, to evaluate the field application, we set up the facilities in Sin-gal lake located in Yongin-Si Gyeonggi-Do, and researched on the removal efficiency of outflow relative to the inflow. As a result, SS is 53.5%, BOD is 32.8%, COD is 36.9%, T-N is 22.6%, T-N is 33.2%.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.37 no.4
• /
• pp.94-99
• /
• 2009

The purpose of this study was to utilize hydroculture by the vital means of the improvement of indoor relative humidity. This experiment employed a search of the effect of Scindapsus aureus and Syngonium podophyllum that are generalized for hydroculture foliage plant by a difference of volume ratio, pot media and plants species. In the case of Scindapsus aureus, relative humidity was high for growth chamber in which plants presented as opposed to control growth chambers in which there were no plants. Although relative humidity was 25% in control chamber, there was an increase of 40% at a 2% volume ratio, 45% at a 3% volume ratio and 50% at a 5% volume ratio. The relative humidity of Syngonium podophyllum was 40% at a 2% volume ratio, 44% at a 3% volume ratio and 46% at a 5% volume ratio, while the control treatment was 25% relative humidity in hydroculture. Both the control treatment and hydroball pot in a hydroball container were high at first. As time progressed, artificial soil pots in water containers was similar when housed within the control chamber by about 45% relative humidity. Hydroball pots in water container had about 30% relative humidity. Ardisia pusilla of hydroball poIt in hydroball container had about 38% relative humidity.

• Smart Media Journal
• /
• v.7 no.1
• /
• pp.16-23
• /
• 2018

In this paper, we used the Deep Neural Network (DNN) to predict the number of daily spectators of Gwangju - KIA Champions Field in order to provide marketing data for the team and related businesses and for managing the inventories of the facilities in the stadium. In this study, the DNN model, which is based on an artificial neural network (ANN), was used, and four kinds of DNN model were designed along with dropout and batch normalization model to prevent overfitting. Each of four models consists of 10 DNNs, and we added extra models with ensemble model. Each model was evaluated by Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The learning data from the model randomly selected 80% of the collected data from 2008 to 2017, and the other 20% were used as test data. With the result of 100 data selection, model configuration, and learning and prediction, we concluded that the predictive power of the DNN model with ensemble model is the best, and RMSE and MAPE are 15.17% and 14.34% higher, correspondingly, than the prediction value of the multiple linear regression model.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.983-991
• /
• 2019

This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.