• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.71-84
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• 2021

As part of the recent economic revitalization measures, the national level of encouragement for young people's entrepreneurship continues, and investment in young people's entrepreneurship and support from young people are increasing. Entrepreneurship intention is a direct factor leading to entrepreneurship, and many studies have studied the individual characteristics of entrepreneurs that influence entrepreneurial intention. In the same context, the purpose of this study was to investigate the entrepreneur's passion as a factor affecting entrepreneurial intention, divided into harmony passion and obsessive passion. In addition, the pass to need for achievement, emotion, and subjective norms, which are the individual characteristics of entrepreneurs that influence passion, were verified. To this end, an online survey was conducted for prospective entrepreneurs in universities, and data of 203 persons were collected and structural equations were analyzed. As a result of the analysis, it was found that the need for achievement and positive emotions of preliminary entrepreneurs had a positive (+) effect on the passion for harmony, while the negative emotions and subjective norms were not significant for the passion for harmony. The need for achievement had a negative (-) effect on the obsessive passion, and the positive and negative emotions had a positive (+) effect on the obsessive passion, but the subjective norm was not significant on the obsessive passion. It was confirmed that harmony passion and obsessive passion showed positive (+) effect on entrepreneurial intention. It also confirmed whether harmonious passion and obsessive passion have a mediating effect between need for achievement, positive emotion, negative emotion, and entrepreneurial intention. As a result, it has a mediating effect between need for achievement, positive emotion and entrepreneurial intention, especially need for achievement has a complete mediating effect. Obsessive passion was also confirmed to have a mediating effect in the relationship between positive emotions and intention to start a business.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.172-177
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• 2021

As part of the digital era, a digital twin that simulates the weak part of a product by performing a stress test that reduces the lifespan of some expensive equipment that cannot be done in reality by accurately moving the real world to virtual reality is being actively used in the manufacturing industry. Due to the development of IoT, the digital twin, which accurately collects data collected from the real world and makes it the same in the virtual space, is mutually beneficial through accurate prediction of urban life problems such as traffic, disaster, housing, quarantine, energy, environment, and aging. Based on its action, it is positioned as a necessary tool for smart city construction. Although digital twin is widely applied to the manufacturing field, this study proposes a smart city model suitable for the 4th industrial revolution era by using it to smart cities and increasing citizens' safety, welfare, and convenience through the proposed model. In addition, when a digital twin is applied to a smart city, it is expected that more accurate prediction and analysis will be possible by real-time synchronization between the real and virtual by maintaining realism and immediacy through real-time interaction.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.171-181
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• 2019

In order to confirm whether innovation can be realized through the direction that companies pursue, this study empirically analyzed the relationship between strategic directionality and innovation capacity. Specifically, strategic directionality is divided into customer orientation and technology orientation, and innovation capacity is classified into strategic planning capacity, R&D capacity, and technology commercialization capacity based on previous studies. And the effect of customer and technology orientation on each innovation capacity was analyzed. Data collection was carried out by 368 questionnaires from the workers of manufacturing industry in Gyeongbuk area and the proposed hypotheses were tested by using structural equation. As a result, it was confirmed that technology orientation had significant effects on all three innovation capacities. However, the effect of customer orientation on strategic planning capacity and technical commercialization capacity was accepted, but the relationship with R&D capacity was rejected. These results can provide implications for how to draw innovation from the organizational strategic direction and culture perspectives by explaining the impact of organizational orientation on innovation capacity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.707-725
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• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.365-374
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• 2021

Recently, the high growth rate and advantages of the crowdfunding market have also led to increased participation of brands and companies, and this also applies to fashion business. Risk has been noted to be a key factor in consumer behavior in crowdfunding. With the high-risk context of crowdfunding where supporters inevitably bear to pay full amount of price before receiving the actual products. Factors enhancing or inhibiting perceived risk of crowdfunding need to be explored. The past literature on perceived risk and consumer attitudes in crowdfunding has expanded, but it has rarely covered the context of experience goods such as fashion products. In addition, the platform characteristics in relation to perceived risk should be addressed. The current study attempts to address the effect of the perceived amount of information offered in a fashion crowdfunding project on perceived risk and the intention to participate in the project. For the experiment of this study, a fictitious crowdfunding page for fashion products was set as the stimuli. A total of 240 Korean participants were recruited and their responses were statistically analyzed using SPSS 24.0 software. In the results, the greater the amount of detailed information about the fashion crowdfunding project, the higher the intention to participate the project. The greater the amount of information provided, the lower the perceived risk of consumers. Moreover, the lowered perceived risk affected the intention of participate. Perceived risk has a partial mediation in the relationship between the amount of information and intention to participate. Theoretical and managerial implications are discussed.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.98-105
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• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.513-523
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• 2022

Generally, people act to use Information Technology on the premise of their experience in using various Information Technology. Namely, users perceive Information Technology through their User Experience, and these User Experiences can be said to impact Continuous Use Intention of the Information Technology. Based on this condition, the present study was proceeded to investigate the User Satisfaction's Mediating effect in the relationship between User Experience and Continuous Use Intention of the OTT services. For this purpose, 195 male and female college students' survey data were used for analysis, verified through the SPSS Process Macro. As a result of the analysis, not only the Reliability experience for the OTT services but also the Usability, Convenience, and Pleasurable experiences' User Experiences were verified that Use Satisfaction was Fully Mediating in relation to Continuous Use Intention. This result gives an implication that the importance of User Experience and Use Satisfaction in maintaining customers through continuous use of OTT services are worth noting. Overall, the present study increased the customer utility for OTT services and confirmed the importance of User Experience and Use Satisfaction in order to increase the competitiveness of the company. Also, it proposed a direction for an in-depth future research to develop this study.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.77-89
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• 2022

It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for training in a language environment where resources are scarce. Using the Cross-lingual Post-Training (XPT) method, we analyze the method's efficiency in Korean, which is a low resource language. XPT selectively reuses the English pretrained language model parameters, which is a high resource and uses an adaptation layer to learn the relationship between the two languages. This confirmed that only a small amount of the target language dataset in the relationship extraction shows better performance than the target pretrained language model. In addition, we analyze the characteristics of each model on the Korean language model and the Korean multilingual model disclosed by domestic and foreign researchers and companies.