• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.99-109
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• 2021

In recent machine learning studies, in order to consider the quality and completeness of data, derivation of non-functional requirements for data has been proposed from the viewpoint of requirements engineering. In particular, requirements engineers have defined data requirements in machine learning. In this study, data requirements were derived at the data acquisition (DAQ) stage, where data is collected and stored before data preprocessing. Through this, it is possible to express the requirements of all data required in the existing DAQ system, the presence of tasks (functions) satisfying them, and the relationship between the requirements and functions. In addition, it is possible to elicit requirements and to define the relationship, so that a software design document can be produced, and a systematic approach and direction can be established in terms of software design and maintenance. This research using existing DAQ system cases, scenarios and use cases for requirements engineering approach are created, and data requirements for each case are extracted based on them, and the relationship between requirements, functions, and goals is illustrated through goal modeling. Through the research results, it was possible to extract the non-functional requirements of the system, especially the data requirements, from the DAQ system using requirements engineering.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.603-613
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• 2021

As a core policy for achieving the goal of reducing greenhouse gas emissions in the building sector, Korea has enforced the mandatory certification of zero energy buildings for new public buildings from 2020. This study suggests energy-saving technologies and economic factors that building officials can refer to for decision-making on the implementation of zero energy buildings. For this study, the construction cost for the energy item of a building was analyzed by collecting the building energy efficiency level certification data and detailed construction cost statement data from public institutions for the last three years. Based on the building energy efficiency certification data, each energy item of the baseline building was derived, and the energy performance of the zero energy building was derived through repetitive simulations by gradually increasing the energy performance value of the baseline building. By applying the analyzed construction cost, the construction cost for each energy item of the baseline and zero energy buildings was derived. As a result, the lighting equipment contributed up to 10.5% energy savings, and the increase in construction cost of the cooling and heating system was at least 9.1%.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.185-210
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• 2020

The library faced an unexpected crisis of COVID-19, and as a countermeasure strategy, non-face-to-face online service has been reinforced. Therefore, this study attempted to present a plan to overcome the challenges arising from rapidly changing external environment and current crisis. To this end, data search, electronic library, library service, cultural event and open space management status of 288 public libraries serviced as an integrated site were investigated. Based on this, the meaning of online services in the post-COVID-19 era and the implication of it were examined. As a result, first, the increase in the use rate of online data search services with the spread of non-face-to-face culture, second, the expansion of the services of the electronic library, third, the diversification of non-face-to-face, online services, fourth, expansion of online cultural event services, fifth, the diversification of open space services were proposed, sixth, Introduced an artificial intelligence system for unattended loan return based on access and the Seventh, expansion of experiential cultural support services and educational contents through VR, AR and MR. It is deemed necessary for the research on the future direction of the library's non-face-to-face services to be conducted by investigating the current status of online services in various types of libraries and the types and case studies of library services in the era of COVID-19.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.58-64
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• 2021

As the number of registered vehicles increases, traffic congestion will worsen worse, which may act as an inhibitory factor for urban social and economic development. Through accurate traffic flow prediction, various AI techniques have been used to prevent traffic congestion. This paper uses the data from a VDS (Vehicle Detection System) as input variables. This study predicted traffic flow in five levels (free flow, somewhat delayed, delayed, somewhat congested, and congested), rather than predicting traffic flow in two levels (free flow and congested). The Catboost model, which is a machine-learning algorithm, was used in this study. This model predicts traffic flow in five levels and compares and analyzes the accuracy of the prediction with other algorithms. In addition, the preprocessed model that went through RandomizedSerachCv and One-Hot Encoding was compared with the naive one. As a result, the Catboost model without any hyper-parameter showed the highest accuracy of 93%. Overall, the Catboost model analyzes and predicts a large number of categorical traffic data better than any other machine learning and deep learning models, and the initial set parameters are optimized for Catboost.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.63-71
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• 2020

In this paper, we propose a fire detection technology using YOLOv3 and EfficientDet, the most reliable artificial intelligence detection algorithm recently, an alert service that simultaneously transmits four kinds of notifications: text, web, app and e-mail, and an AWS system that links fire detection and notification service. There are two types of our highly accurate fire detection algorithms; the fire detection model based on YOLOv3, which operates locally, used more than 2000 fire data and learned through data augmentation, and the EfficientDet, which operates in the cloud, has conducted transfer learning on the pretrained model. Four types of notification services were established using AWS service and FCM service; in the case of the web, app, and mail, notifications were received immediately after notification transmission, and in the case of the text messaging system through the base station, the delay time was fast enough within one second. We proved the accuracy of our fire detection technology through fire detection experiments using the fire video, and we also measured the time of fire detection and notification service to check detecting time and notification time. Our AI fire detection and notification service system in this paper is expected to be more accurate and faster than past fire detection systems, which will greatly help secure golden time in the event of fire accidents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.568-578
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• 2021

Patents that are research results from industry-university cooperation (IUC) are a source of innovation, and play an important role in economic growth, such as technology transfer and commercialization. For this reason, there are many efforts to revitalize IUC, but in general, company patents are achievements that can be commercialized, rather than research achievements, so not all patents are used for business, even after their creation as the outcome of IUC. Therefore, this research supports the design of measures in which IUC can ultimately be linked to successful utilization of patents by identifying the purposes of IUC, even after it has been successfully promoted, and patents have been filed as a result. To this end, first, the patents registered for industry-academia cooperation in the United States are collected, and second, a predictive model is designed, with unexpired and expired patents predicted using machine learning techniques. The final identified patents are intended to derive available factors in terms of marketability and technicality. This study is expected to help predict the utilization of unexpired and expired patents, and is expected to contribute to setting goals for research results from technical cooperation between corporate and university officials planning early IUC.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.268-278
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• 2021

Technologies that are leading the fourth industrial revolution, such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cyber-physical systems (CPS) are developing and generalizing. The demand to improve productivity, economy, safety, etc., is spreading in various industrial fields by applying these technologies. Digital twins are attracting attention as an important technology trend to meet demands and is one of the top 10 tasks of the Korean version of the New Deal. In this study, papers, magazines, reports, and other literature were searched using Google. In order to investigate the contribution or role of geospatial information in the digital twin application, the definition of a digital twin, we investigated technology trends of domestic and foreign companies; the components of digital twins required in manufacturing, plants, and smart cities; and the core techniques for driving a digital twin. In addition, the contributing contents of geospatial information were summarized by searching for a sentence or word linked between geospatial-related keywords (i.e., Geospatial Information, Geospatial data, Location, Map, and Geodata and Digital Twin). As a result of the survey, Geospatial information is not only providing a role as a medium connecting objects, things, people, processes, data, and products, but also providing reliable decision-making support, linkage fusion, location information provision, and frameworks. It was found that it can contribute to maximizing the value of utilization of digital twins.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.611-618
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• 2020

In this paper, we propose a design and implementation method of speed quiz content that can be driven by a social robot capable of interacting with humans, and a method of developing an intelligent module necessary for implementation. In addition, we propose a method of implementing speed quiz content through the process of constructing a map by arranging and connecting intelligent module blocks. Recently, software education has become mandatory and interest in programming is increasing. However, programming is difficult for students without basic knowledge of programming languages to directly access, and interest in block-type programming platforms suitable for beginners is growing. The block-type programming platform used in this paper is a platform that supports immediate and intuitive programming by supporting interactions between humans and robots. In this paper, the intelligent module implemented for the speed quiz content was used by blocking it within a block-type programming platform. In order to implement the scenario of the speed quiz content proposed in this paper, we implement a total of three image-based artificial intelligence modules. In addition to the intelligent module, various functional blocks were placed to implement the speed quiz content. In this paper, we propose a method of designing a speed quiz content scenario and a method of implementing an intelligent module for speed quiz content.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.67-74
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• 2021

Ground Operations Command (GOC) has studied various methods using artificial intelligence (AI) in order to accomplish ground missions more effectively and to strongly respond to variable strategic situations with advancements in fourth industrial revolution technology. As the result of various literature reviews, PEST-7S-SWOT is considered the most appropriate methodology for promoting strategies and for task development. These procedures consist of three stages. Phase 1 is analysis of external environmental factors from applying PEST procedures. We analyzed external environmental factors to determine opportunities and risk factors. Phase 2 is the analysis of internal environmental factors from applying 7S strategies. We analyzed the current state of an organization to find strengths and weaknesses. Phase 3 is SWOT analysis. It is based on the opportunities and risk factors from Phase 1 and the strength and weakness factors from Phase 2. We derive promotional strategies and tasks through SWOT analysis. In this study, four strategies and 11 tasks were derived for GOC AI systems. Those are promotion of policies and systems, reinforcing organizations, building an AI base, increasing expertise and capabilities, and validating PEST-7S-SWOT methodologies.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.104-112
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• 2021

In this study, emotional analysis was conducted based on the basic attribute data of music and the emotional model in psychology, and the result was applied to the visualization rules in the formative arts. In the existing studies using musical parameter, there were many cases with more practical purposes to classify, search, and recommend music for people. In this study, the focus was on enabling sound data to be used as a material for creating artworks and used for aesthetic expression. In order to study the music visualization as an art form, a method that can include human emotions should be designed, which is the characteristics of the arts itself. Therefore, a well-structured basic classification of musical attributes and a classification system on emotions were provided. Also, through the shape, color, and animation of the visual elements, the visualization of the musical elements was performed by reflecting the subdivided input parameters based on emotions. This study can be used as basic data for artists who explore a field of music visualization, and the analysis method and work results for matching emotion-based music components and visualizations will be the basis for automated visualization by artificial intelligence in the future.