• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.193-202
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• 2017

With the growth of Chinese manufacturing industry and strengthening of manufacturing industry in advanced countries, the competitiveness of Korean manufacturing industry has become weak. Accordingly, it is time when energy for new growth is required very strongly. This research is the basic research to construct a cognitive and emotional information system to support sound design in manufacturing industry, and aims to develop AUI (Auditory User Interface) guideline. To fulfill research aims, this research conducted interviews to persons belonging to the manufacturing industry, and analyzed contexts and major characteristics related with AUI design. In addition, this research conducted survey on 269 persons on user preference on representative function of products. By analyzing survey data, this research examined the most suitable melody method for each sound, and difference in user preference between men and women. Based on beep sound, it performed analysis focusing on the number of sounds, melody types, and code. It also extracted AUI guidelines usable when users of the product into male and female. This research has significance in the sense that it built the basic guide data which can support AUI design in manufacturing industry.

• Information Systems Review
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• v.22 no.2
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• pp.77-99
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• 2020

Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.1-36
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• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.571-580
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• 2011

The purpose of this study was to evaluate the effects of secondary task such as sending text message (STM) and searching navigation (SN) using the variable indicating control of vehicle ((Medial-Lateral Coefficient of Variation, MLCV), (Anterior-Posterior Coefficient of Variation, APCV)) and motion signal (Jerk-Cost function, JC). Participants included 50s taxi drivers; 14 males and 14 females. Participants were instructed to keep a certain distance (30m) from the car ahead with constant speed (80km/hr or 100km/hr). Experiement consisted of driving alone for 1minute and driving with secondary task for 1minute. Both MLCV and APCV were significantly increased during Driving + Sending Text Message(STM) and Driving + Searching Navigation(SN) than Driving only. Also, JC was increased during Driving + STM and Driving + SN than Driving only. In this study, we found that even in the experts group who are taxi driver and have 25 years driving experience, the smoothness of motion is decreased and the control of vehicle is disturbed when they were performing secondary tasks like sending text message or searching navigation.

• Science of Emotion and Sensibility
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• v.15 no.3
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• pp.389-398
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• 2012

Virtual worlds have pursued reality as if they actually exist. In order to evaluate the sense of reality in the computer-simulated worlds, several subjective questionnaires, which include specific independent variables, have been proposed in the literature. However, the questionnaires lack reliability and validity necessary for defining and measuring the virtual realization. Few studies have been conducted to investigate the effect of visual factors on the sense of reality experienced by exposing to a virtual environment. Therefore, this study was aimed at reinvestigating the variables and proposing a more reliable and advisable questionnaire for evaluating the virtual realization, focusing on visual factors. Twenty-one questions were gleaned from the literature and subjective interviews with focused groups. Exploratory factor analysis with oblique rotation was performed on the data obtained from 200 participants(females: 100) after exposing to a virtual character image described in an extreme way. After removing poorly loading items, remained subsets were subjected to confirmatory factor analysis on the data obtained from the same participants. As a result, 3 significant factors were determined to efficiently measure the virtual realization. The determined factors included visual presence(3 subset items), visual immersion(7 subset items), and visual interactivity(4 subset items). The proposed factors were verified by conducting a subjective evaluation in which participants were asked to evaluate a 3D virtual eyeball model based on the visual presence. The results implicated that the measurement method was suitable for evaluating the degree of the virtual realization. The proposed method is expected to reasonably measure the degree of the virtual realization.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.615-627
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• 2012

The market penetration of the smart phones has brought significant changes to the related industries. As the mobile phone market as well as the smart phone application market are growing rapidly, competition among small-size application developers has become severe. However, due to the severe competition and expensive market entry costs, the developers argue that it is necessary to develope the applications from the perspective of the users. However, studies on application development from the users' perspectives are still in the early stages and they have not provided various approaches. Therefore, based on the Open Coding method of Ground Theory, this study collected data on applications review from related communities and blogs of Korean web portal sites, and identified indices which users consider important when they use the applications. In addition, we conduct a comparative analysis between those indices by calculating their frequency of exposure. As a result, a total of 30 sub-categories of indicators such as amusement, controllability, versatility and ease of use appeared to be predominant to users and those lower categories were grouped into five categories; sensibility, design, technology, price, and social skills. The results of this study suggest to the application developers the guidelines of user oriented design and development. It can be used to develop the evaluation tool for application usability.

• Journal of Life Science
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• v.23 no.6
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• pp.804-811
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• 2013

Melanopsin is an opsin-like photopigment found in the small proportion of photosensitive ganglion cells of the retina. It is involved in the regulation of the synchronization of the circadian cycle as well as in the control of pupillary light reflex. The purpose of the present study is to investigate whether melanopsin is also expressed in the other areas of the central visual system outside the retina. We have studied the distribution and morphology of neurons containing melanopsin in the mouse visual cortex with antibody immunocytochemistry. Melanopsin immunoreactivity was mostly present in neuronal soma, but not in nuclei. We found that melanopsin was present in a large subset of neurons within the adult mouse visual cortex with the highest density in layer II/III. In layer I of the visual cortex, melanopsin-immunoreactive (IR) neurons were rarely encountered. In the mouse visual cortex, the majority of the melanopsin-IR neurons consisted of round/oval cells, but was varied in morphology. Vertical fusiform and pyramidal cells were also rarely labeled with the anti-melanopsin antibody. The labeled cells did not show any distinctive distributional pattern. Some melanopsin-IR neurons in mouse visual cortex co-localized with nitricoxide synthase, calbindin and parvalbumin. Our data indicate that melanopsin is located in specific neurons and surprisingly widespread in visual cortex. This finding raises the need of the functional study of melanopsin in central visual areas outside the retina.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.3-12
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• 2009

In this study, by both qualitative and quantitative measurement on the purpose of deriving the sensitive amusement factor. I consider the fear of horror games as "the amused fear" and analyze it, which is based on the play theory by Roger Caillois. On the basis of this, I classified the amusement fear in horror games into the 4 factors. I conducted some positive tests through the player's response in order to verify them. The test is conducted measuring the heart rate of each experimenter by cardiometer while they are playing horror games. By analyzing the video data, I gave a name to the point that the amusement fear factors are expected to influence psychologically and physiologically as the fear point. At this point, I examined if the measured heart rate makes the outstanding difference or not, when compared average heart rate with experimenter's heart rate. In addition, I also examined if there is a statistical correlation of heart rate by attaching player's subjective data through the questionnaire. Consequently, it was statistically turned out that the experimenter's heart rate which is measured rose dramatically than usual, and that there are close correlations among subjective data. I also found out that the amusement fear factor at the relevant point plays a major role in experimenter's psychological and physiological response. In this study, I could prove the horror factor as a meaning of amusement factor using both theoretical method and positive method establishing a standard set that is helpful for further production and planning of the game.