• Smart Media Journal
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• v.12 no.1
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• pp.77-91
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• 2023

Interaction methods and technologies for mutual exploration based on user behavior are evolving variously. Especially, in recent years, with the development of a wide range of sensors, they have developed from contact to non-contact methods. However, developers' senseless definitions of the interaction methods have made the exploration process quite complicated, which rather creates the hassle of users needing to learn the interaction guide defined by the developers before experiencing the exhibition contents. In this context, in order to make visitors smoothly communicate with exhibition contents, a preliminary study on easy interaction for users of various ages is needed, and in particular, research on improving the usability of user interaction is also essential when developing non-contact exhibition contents. So, in this study, a method to reduce the confusion between developers and users was sought by researching non-contact interaction that could be universally interacted with in the field of exhibition contents and proposing behavior designs. First, based on the narrative structure of cultural resources, existing studies were reviewed and the points of interactions as cultural contents were derived. Then the most efficient search process was selected among non-contact behaviors based on hand gestures that allow users to naturally guess and learn interaction methods. Furthermore, on the basis of the meaning of non-linear narrative-based interaction and the analysis results of spatial behavior elements, affordance behavior with high learning effect and efficiency was derived. Through this research process, an action that helps users to understand non-contact interaction naturally in the process of exploring exhibition-type cultural contents and to utilize non-contact interaction in the process of immersion in exhibition contents is proposed as a final model.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.817-823
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• 2023

Manufacturing plants face the challenge of reducing energy use in response to climate change. Reducing energy consumption can be seen as one of the most important issues, such as reducing production costs and improving efficiency. Among manufacturing industries, the increase in energy consumption in the food industry is gradually increasing along with the improvement of the standard of living and the increase in population. In order to save energy in food processing plants, it is important to identify and analyze energy consumption characteristics in energy-consuming processes. Prior to this, it is necessary to monitor and analyze existing energy consumption to derive reduction measures. In this study, a small and medium-sized food processing plant producing processed meat products was used as a case study to identify and analyze the energy consumption structure at typical cycle/stage level of the batch heating process. From this, we tried to establish realistic and quantitative goals that can be obtained under individual process operating conditions. The results of this study will be used as basic data for the development of diffusion and pervasive energy saving FEMS technology for common core processes of food factories of small and medium-sized enterprises in the future.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.21-29
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• 2023

In this paper, we propose an AI-based system for automatically classifying industry and occupation codes in the population census. The accurate classification of industry and occupation codes is crucial for informing policy decisions, allocating resources, and conducting research. However, this task has traditionally been performed by human coders, which is time-consuming, resource-intensive, and prone to errors. Our system represents a significant improvement over the existing rule-based system used by the statistics agency, which relies on user-entered data for code classification. In this paper, we trained and evaluated several models, and developed an ensemble model that achieved an 86.76% match accuracy in industry and 81.84% in occupation, outperforming the best individual model. Additionally, we propose process improvement work based on the classification probability results of the model. Our proposed method utilizes an ensemble model that combines transfer learning techniques with pre-trained models. In this paper, we demonstrate the potential for AI-based systems to improve the accuracy and efficiency of population census data classification. By automating this process with AI, we can achieve more accurate and consistent results while reducing the workload on agency staff.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.275-283
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• 2006

Recently, there are increasing needs to provide sufficient information on road signs for expanding cities and traffic networks. Improving efficiency of direction guidance information from road signs not only requires criteria for but also systematic approach to selecting place names that appear on road sings. As such, this paper looks at road direction information from existing road signs that leads to Suwon and investigates whether the current system of road sings provides efficient, systematic and continuous direction information for road users to easily reach their destination. In this paper, Suwon's city hall is set up as the final destination, which is linked from five other cities, Euiwang, Ansan, Hwaseong, Osan and Yongin. The paper attempts to find out whether there is continuity and suitable number of road signs for direction information by analyzing the road signs between these 5 cities and Suwon with respect to direction, direction advance notice and direction guidance. It is found that road users cannot easily find the needed information on their destination from the existing road signs and that continuity of selected place names that systematically appear on road signs is insufficiency. That is to say, the findings of the paper are that while it is easy for road users to find place names that are classified under land marks or the first-class selection of place names on road signs, it is difficult to obtain information from road signs on place names that are grouped under the second or third class. In addition, direction guidance on road signs is problematic, because the appearance frequency of road signs is not adequate and the continuity of road signs is not effective. Moreover, there is insufficient information on local direction guidance for immediate destinations on road signs with respect to turning left or right or going straight. Hence road signs in urban area need systematic improvement to find easily some destination.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.399-408
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• 2009

The major changes in construction environment are that construction project is bigger and more complicated and the power of construction market changes from the supplier to the client or the user. Especially public construction enterprises have advanced to introduce the value engineering (VE) which is one of the cost management based on the owner's leading at the design phase for economical efficiency and quality improvement. According to the these efforts, the implementation of VE was legislated in the revised Construction Technology Management Act in 2000, governmental agencies, local autonomies, and construction public enterprises universally has taken the VE into consideration. In this circumstance, the scope that VE construction applied at 50 billion won projects from 2003 has been extended to 10 billion won projects in 2006. Therefore, the VE construction will be activated in the future. The cost savings and function improvement, which are the purpose of VE are not only construction public enterprises, but also every public client supported from government's budget or owned by the government. Therefore, the purpose of this study is to propose the improved process and performance index of VE for governmental agencies, local autonomies, and construction public enterprises which want to introduce or improve the VE process. This research also suggested the To-be design-phased VE process model. In addition, it suggested the To-be model of design management reflected the To-be design-phased VE process model, which is eliminated two problems reflected for the performance improvement of the As-is model of design management.

• 한국노년학
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• v.39 no.2
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• pp.213-229
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• 2019

The purpose of this study was to examine various factors influencing the needs of Seoul's newly implemented outreach community services for older adults, and to suggest the direction of the outreach community health services in Seoul. A multi-level regression was conducted using data collected by face-to-face interviews from 1,000 individuals aged 65 and 70 in 17 districts, where participated in the Seoul's outreach community services. The results demonstrated that socioeconomic status (higher income and living alone), health status (having multiple chronic conditions and depression, lower health literacy), limited experience of the outreach community services, and low government trust at the individual level were associated with higher unmet need for the community outreach services. In addition, shorter participation period of the outreach services and financial independency at the district level were associated with higher unmet need for the services. The findings from this study implies the need for improving the quality of services by focusing on vulnerable groups such as individuals with lower income and worse health status. In addition, the outreach community health services may need to target individuals aged 66 to increasing efficiency of the services through utilizing results of life-cycle health checkup by the National Health Insurance Corporation.

• Asia Marketing Journal
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• v.15 no.3
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• pp.79-95
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• 2013

New product innovation is a process of embodying new knowledge in a product and technology licensing is getting popular as a means to innovations and introduction of new product to the market in today's competitive global market environment. Incumbents often rely on technology licensing to access new product opportunities created by other firms. Prior research has examined various aspects of technology licensing agreements such as specific contract terms of licensing agreements, e.g., distribution of control rights, exclusivity of licensing agreements, cross-licensing, and the scope of licensing agreements. This study aims to provide answers to an important, but under-researched question: why do some incumbents initiate more licensing agreement for exploratory learning while others do it for exploitative learning along the innovation process? We attempt to extend our knowledge of licensing agreements from an organizational learning perspective. Technology licensing as a specific form of interfirm linkages can be initiated with different learning objectives along the process of new product innovation. The exploratory stages of the innovation process such as discovery or research stages involve extensive searches to create new knowledge or capabilities, whereas the exploitative stages of the innovation process such as application or test stages near the commercialization are more focused on developing specific applications or improving their efficiency or reliability. Thus, different stages of the innovation process generate different types of learning and the resulting technological resources. We examine when incumbents as licensees initiate more licensing agreements for exploratory learning objectives and when more for exploitative learning objectives, focusing on two factors that may influence a firm's formation of exploratory and exploitative licensing agreements: 1) its past radical and incremental innovation experience and 2) its internal investments in R&D and marketing. We develop and test our hypotheses regarding the relationship between a firm's radical and incremental new product experience, R&D investment intensity and marketing investment intensity, and the likelihood of engaging in exploratory and exploitive licensing agreements. Using data collected from various secondary sources (Recap database, Compustat database, and FDA website), we analyzed technology licensing agreements initiated in the biotechnology and pharmaceutical industries from 1988 to 2011. The results of this study show that incumbents initiate exploratory rather than exploitative licensing agreements when they have more radical innovation experience and when they invest in R&D activities more intensively; in contrast, they initiate exploitative rather than exploratory licensing agreements when they have more incremental innovation experience and when they invest in marketing activities more intensively. The findings of this study contribute to the licensing and interfirm cooperation studies. First, this study lays a foundation to understand the organizational learning aspect of technology licensing agreements. Second, this study sheds lights on how a firm's internal investments in R&D and marketing are linked to its tendency to initiate licensing agreements along the innovation process. Finally, the findings of this study provide important insight to managers regarding which technologies to gain via licensing agreements. This study suggests that firms need to consider their internal investments in R&D and marketing as well as their past innovation experiences when they initiate licensing agreements along the process of new product innovation.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.523-528
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• 2023

The applicability as a material to improve solar cell performance was reviewed by synthesizing a phosphor that emits red wavelengths by a liquid synthesis method using a metal salt aqueous solution and a polymer medium as a starting material. An aqueous solution was prepared using nitrate of metals such as Ca, Zn, Al, and Eu, and a precursor impregnated with starch, a natural polymer, was sintered to synthesize CaZnAlO:Eu phosphor powder. The surface structure and composition analysis of the synthesized CaZnAlO:Eu phosphor powder were analyzed by scanning electron microscope(SEM) and energy-dispersed X-ray spectroscopy(EDS). The crystal structure of CaZnAlO:Eu phosphor particles was analyzed by an X-ray diffraction analyzer (XRD). As a result of measuring the photoluminescence(PL) characteristics of the phosphor, it was confirmed that a red phosphor with a light emitting wavelength of 650-780nm was successfully synthesized. According to SEM and EDS analysis, the synthesized Ca₁₄Zn₆Al_9.93O₃₅:Eu³⁺_0.07 phosphor powder has a uniform particle size, and Eu ions used as an activator are present. The synthesized CZA:Eu³⁺ phosphor can be used as a material that can increase the light absorption efficiency of the solar cell by converting ultraviolet or visible light down conversion into a wavelength in the near-infrared region.