• Title/Summary/Keyword: Behavior-response performance

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The Possibility of Being an Alternative as Uncontact Concert Format for BTS's Recent Online Concert Called "Bang Bang Con The Live" (BTS '방방콘 The Live'의 비접촉 콘서트로서의 대안 포맷 가능성)

  • Yu, An-Na;Lee, Jong-Oh
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.5
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    • pp.27-35
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    • 2020
  • In 2020, one after another, musicians started to hold non-contact online concerts as the pop music industry began to shrink due to the unprecedented "Covid-19" incident, in seeking for various channels and alternatives. Taking this into account, this study conducted a survey with BTS' "Bang Bang Con The Live" as the subject that was held June 2020 to see if they were qualified as an alternative format for quarantine-focused non-contact concerts. The survey was carried out with the content analysis of online concert videos participated by music experts and by collecting evaluations and alternative suggestions from the audiences. The study showed that the sample performance video well fulfilled the actual feels of offline concert elements (field visualization, face-to-face interaction, and responsive behavior), satisfaction, and convenience as an alternative concert format as an emergency correspondence. However, it was analyzed that there was a serious lack of empathy and realism with fans. Therefore, the study showed the possibility that BTS' "Bangbangcon The Live" will function as an alternative format for non-contact concerts, but suggests that measures such as supplementing digital communication systems and technology devices must be taken to be recognized as a level of settlement in the global music community as well as in Korea.

Running Safety and Ride Comfort Prediction for a Highspeed Railway Bridge Using Deep Learning (딥러닝 기반 고속철도교량의 주행안전성 및 승차감 예측)

  • Minsu, Kim;Sanghyun, Choi
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.35 no.6
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    • pp.375-380
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    • 2022
  • High-speed railway bridges carry a risk of dynamic response amplification due to resonance caused by train loads, and running safety and riding comfort must therefore be reviewed through dynamic analysis in accordance with design codes. The running safety and ride comfort calculation procedure, however, is time consuming and expensive because dynamic analyses must be performed for every 10 km/h interval up to 110% of the design speed, including the critical speed for each train type. In this paper, a deep-learning-based prediction system that can predict the running safety and ride comfort in advance is proposed. The system does not use dynamic analysis but employs a deep learning algorithm. The proposed system is based on a neural network trained on the dynamic analysis results of each train and speed of the railway bridge and can predict the running safety and ride comfort according to input parameters such as train speed and bridge characteristics. To confirm the performance of the proposed system, running safety and riding comfort are predicted for a single span, straight simple beam bridge. Our results confirm that the deck vertical displacement and deck vertical acceleration for calculating running safety and riding comfort can be predicted with high accuracy.

Financial Products Recommendation System Using Customer Behavior Information (고객의 투자상품 선호도를 활용한 금융상품 추천시스템 개발)

  • Hyojoong Kim;SeongBeom Kim;Hee-Woong Kim
    • Information Systems Review
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    • v.25 no.1
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    • pp.111-128
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    • 2023
  • With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

Effect of feeding frequency on reproductive performances and stress responses in gestating sows

  • Sung-Woong Jung;Sungho Do;Jae-Cheol Jang;Jinsu Hong;Geonil Lee;Yoo Yong Kim
    • Journal of Animal Science and Technology
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    • v.66 no.1
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    • pp.135-144
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    • 2024
  • The objective of this study was to investigate the influence of feeding frequency on a sow's reproductive performance and stress response during gestation. A total of twenty multiparous sows (Yorkshire × Landrace) were used in a completely randomized design based on their parity, body weight (BW), and backfat thickness (BFT), and the sows were allotted to two different feeding systems: 1) once daily feeding (OF) and 2) twice daily feeding (TF) in corn-soybean meal based diets. The gestation diet was formulated to contain 3,265 kcal of metabolizable energy (ME) / kg, 12.90% of crude protein (CP), and 0.75 % of total lysine. The lactation diet was formulated to contain 3,265 kcal of ME / kg, 16.80% of CP, and 1.08% of total lysine and provided ad libitum during lactation. In gestation, sow BFT and BF changes were not affected by feeding frequency, but higher BW and BW gain from day 35 to 90 and day 35 to 110 were observed in OF sow (p < 0.10). In lactation, feeding frequency did not influence on BW, BW gain, BFT, BF changes, average daily feed intake, and wean-to-estrus interval. Also, there were no differences in litter size, litter weight and piglet weight in lactating sows. OF sows had higher (p < 0.05; p < 0.10) protein, solid-not-fat, and total solid concentrations in colostrum compared to TF sows, while OF sows had a lower (p < 0.05) lactose concentration in colostrum compared to TF sows. Sows in OF showed significantly lower average daily water consumption (ADWC) from day 35 to 110 of gestation (p < 0.05). While there were no significant differences in stereotypic behaviors and salivary cortisol levels during gestation between treatments, the OF sows showed less time spending on the activity at day 105 (p < 0.05). In conclusion, reduced feeding frequency increased BW gain during gestation, decreased activation time, and changed the colostrum composition. This information may contribute to the understanding of the physiological and behavioral change of gestating sows by manipulating feeding frequency.

Verification of Multi-point Displacement Response Measurement Algorithm Using Image Processing Technique (영상처리기법을 이용한 다중 변위응답 측정 알고리즘의 검증)

  • Kim, Sung-Wan;Kim, Nam-Sik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3A
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    • pp.297-307
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    • 2010
  • Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.

Structural Relationships Among Factors to Adoption of Telehealth Service (원격의료서비스 수용요인의 구조적 관계 실증연구)

  • Kim, Sung-Soo;Ryu, See-Won
    • Asia pacific journal of information systems
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    • v.21 no.3
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    • pp.71-96
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    • 2011
  • Within the traditional medical delivery system, patients residing in medically vulnerable areas, those with body movement difficulties, and nursing facility residents have had limited access to good healthcare services. However, Information and Communication Technology (ICT) provides us with a convenient and useful means of overcoming distance and time constraints. ICT is integrated with biomedical science and technology in a way that offers a new high-quality medical service. As a result, rapid technological advancement is expected to play a pivotal role bringing about innovation in a wide range of medical service areas, such as medical management, testing, diagnosis, and treatment; offering new and improved healthcare services; and effecting dramatic changes in current medical services. The increase in aging population and chronic diseases has caused an increase in medical expenses. In response to the increasing demand for efficient healthcare services, a telehealth service based on ICT is being emphasized on a global level. Telehealth services have been implemented especially in pilot projects and system development and technological research. With the service about to be implemented in earnest, it is necessary to study its overall acceptance by consumers, which is expected to contribute to the development and activation of a variety of services. In this sense, the study aims at positively examining the structural relationship among the acceptance factors for telehealth services based on the Technology Acceptance Model (TAM). Data were collected by showing audiovisual material on telehealth services to online panels and requesting them to respond to a structured questionnaire sheet, which is known as the information acceleration method. Among the 1,165 adult respondents, 608 valid samples were finally chosen, while the remaining were excluded because of incomplete answers or allotted time overrun. In order to test the reliability and validity of the assessment scale items, we carried out reliability and factor analyses, and in order to explore the causal relation among potential variables, we conducted a structural equation modeling analysis using AMOS 7.0 and SPSS 17.0. The research outcomes are as follows. First, service quality, innovativeness of medical technology, and social influence were shown to affect perceived ease of use and perceived usefulness of the telehealth service, which was statistically significant, and the two factors had a positive impact on willingness to accept the telehealth service. In addition, social influence had a direct, significant effect on intention to use, which is paralleled by the TAM used in previous research on technology acceptance. This shows that the research model proposed in the study effectively explains the acceptance of the telehealth service. Second, the research model reveals that information privacy concerns had a insignificant impact on perceived ease of use of the telehealth service. From this, it can be gathered that the concerns over information protection and security are reduced further due to advancements in information technology compared to the initial period in the information technology industry, and thus the improvement in quality of medical services appeared to ensure that information privacy concerns did not act as a prohibiting factor in the acceptance of the telehealth service. Thus, if other factors have an enormous impact on ease of use and usefulness, concerns over these results in the initial period of technology acceptance may become irrelevant. However, it is clear that users' information privacy concerns, as other studies have revealed, is a major factor affecting technology acceptance. Thus, caution must be exercised while interpreting the result, and further study is required on the issue. Numerous information technologies with outstanding performance and innovativeness often attract few consumers. A revised bill for those urgently in need of telehealth services is about to be approved in the national assembly. As telemedicine is implemented between doctors and patients, a wide range of systems that will improve the quality of healthcare services will be designed. In this sense, the study on the consumer acceptance of telehealth services is meaningful and offers strong academic evidence. Based on the implications, it can be expected to contribute to the activation of telehealth services. Further study is needed to assess the acceptance factors for telehealth services, such as motivation to remain healthy, health care involvement, knowledge on health, and control of health-related behavior, in order to develop unique services according to the categorization of customers based on health factors. In addition, further study may focus on various theoretical cognitive behavior models other than the TAM, such as the health belief model.

Modeling of Sensorineural Hearing Loss for the Evaluation of Digital Hearing Aid Algorithms (디지털 보청기 알고리즘 평가를 위한 감음신경성 난청의 모델링)

  • 김동욱;박영철
    • Journal of Biomedical Engineering Research
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    • v.19 no.1
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    • pp.59-68
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    • 1998
  • Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

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Impacts of Increasing Volatility of Profitability on Investment Behavior (수익변동성 확대와 설비투자 위축)

  • LIM, Kyung-Mook
    • KDI Journal of Economic Policy
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    • v.30 no.1
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    • pp.1-31
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    • 2008
  • Various opinions have been suggested to explain the slump in equipment investment, such as increased government regulations, shareholder-oriented management by expanded foreign equity investment, response against M&A threats, conservative investment trends seen after a series of bankruptcy of large conglomerates (amidst crumbling myth of "Too Big to Fail"), and financial restructuring. Some also argued that the increased uncertainty in business environment is mainly responsible for conservative management, though there are few domestic studies made regarding the situation. But, in other countries, including the U.S., studies have shown that more volatility is seen now surrounding stock prices, profitability, and sales growth rate reflecting business performance. Also, there are other studies showing such expanded volatility have led to conservative management by businesses. In this regard, this study reviews the volatility conditions of business performance of Korean companies based on profitability, and then attempts to analyze the impact on investment brought on by increased volatility. Each company's profitability volatility used here is from the standard deviation of companies for the past five years. As a profitability indicator, the ROA (= operating profit/total asset) is used. According to the analysis, profitability volatility has remarkably increased from the mid 3% in 1994 to low 5% in 2005. Profitability volatility of the Korean companies has expanded to a great extent since the financial crisis. The crisis might have served to raise the volatility in the macroeconomic conditions. If increased volatility observed during the economic crisis had gradually declined after the crisis, the situation could be interpreted as a temporary phenomenon, not to be too concerned over. But, this was not the case for Korea. The volatility level, after the crisis, has not dropped back to its pre-crisis level. Hence, in the Korea's case, high volatility cannot be explained by the impact of financial crisis. Not only that, the fact that such expansion is seen in every industrial sector indicates that this phenomenon cannot be explained by the composition change of industries alone. An undergoing study shows that with a rapid spread of globalization, industries fiercely competing with China experience more volatility. Such increased volatility tends to contract investment, and since the crisis the impact of volatility on investment has slightly increased. It is noteworthy that this study only includes a part of 'uncertainty' that could be measured statistically. For instance, the profitability volatility indicator used in this study is unable to reflect all the effects that the tacit reduction of protection by the government or regulations might have made. So, the result here also indicates that other 'uncertain' factors not mentioned in this study may have served to contract investment sentiment. It would be impossible for policies to completely remove uncertainties measured by profitability volatility, but at least it is necessary to put effort to reduce the macroeconomic volatility in the future economic management. Stabilized macroeconomic management may not be enough to diminish all volatility that occurs within each company, but it would make a meaningful contribution in encouraging investment.

Neural Bases of Empathy in Competitive vs. non-Competitive situation (경쟁과 비경쟁 상황에서 공감의 신경학적 기제)

  • Hwang, Su-Young;Yoon, Mi-Sun
    • Korean Journal of Cognitive Science
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    • v.27 no.3
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    • pp.441-467
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    • 2016
  • This fMRI study is aim to investigate effects of competitive environment in cognitive empathic process in human brain. Empathy is known as a crucial factor for human's adaptive behavior in aspects of social cognition and it is almost automatic process, on the other hand competitive situation is psychologically devastated environment to win someone for getting rewards. We hypnotized that reading and understanding of other person's mind are a specific characteristic related to survival evolutionarily, however competition would have an effect on the empathic cognitive process because of mechanisms of competition. To manipulate the competitive atmosphere, one researcher took a role of competitor against participants and they were instructed to get monetary rewards when their performance was better than a competitor. 21 participants(9 males and 12 females) performed to judge the emotional valence of the empathic task consisted of illustrated images with various situation could be experienced in real world as on $1^{st}$ person perspective in both competitive and non-competitive condition, and did same performance with objects stimulus in control condition. In order to examine the competition effects on empathic process,, hemodynamic response were obtained during fMRI session and the imaging data were analyzed to identify brain regions where responses to each condition across the two consecutive runs. Participants' reaction time in competitive condition was faster statistically significant than non-competitive one. Activation for competitive condition increased in the following areas: ACC, mPFC, SMG, thalamus extended caudate and Nacc, parahippocampal gyrus, and for non-competitive condition increased paracingulate gyrus, temporal pole, vmPFC, superior occipital gyrus. As a result of regression analysis using empathic scores as covariance, the rSMG, IFG, fusiform gyrus, thalamus, putamen were correlated with higher empathic levels, and TPJ were correlated with lower empathic scores. We suggest that these observations could mean competitive environment have an effect on neural base of cognitive empathic process.

The Intelligent Determination Model of Audience Emotion for Implementing Personalized Exhibition (개인화 전시 서비스 구현을 위한 지능형 관객 감정 판단 모형)

  • Jung, Min-Kyu;Kim, Jae-Kyeong
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.39-57
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    • 2012
  • Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.