• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.56-61
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• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.179-184
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• 2021

Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.671-680
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• 2021

This paper deals with the contents of designing and producing reconnaissance hardware and software, and verifying the functions after being installed on the CanSat platform and ground stations. The main reconnaissance mission is largely composed of two things: terrain search that renders the surrounding terrain in 3D using radar, GPS, and IMU sensors, and real-time detection of major objects through optical camera image analysis. In addition, data analysis efficiency was improved through GUI software to enhance the completeness of the CanSat system. Specifically, software that can check terrain information and object detection information in real time at the ground station was produced, and mission failure was prevented through abnormal packet exception processing and system initialization functions. Communication through LTE and AWS server was used as the main channel, and ZigBee was used as the auxiliary channel. The completed CanSat was tested for air fall using a rocket launch method and a drone mount method. In experimental results, the terrain search and object detection performance was excellent, and all the results were processed in real-time and then successfully displayed on the ground station software.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Korea Science and Art Forum
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• v.21
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• pp.31-43
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• 2015

Information and Communications Technology (ICT) is one of the technologies which represent the core value of the creative economy. It has served as a vehicle connecting the existing industry and corporate infrastructure, developing existing products and services and creating new products and services. In addition to the ICT, new devices including big data, mobile gadgets and wearable products are gaining a great attention sending an expectation for a new market-pioneering. Further, Internet of Things (IoT) is helping solidify the ICT-based social development connecting human-to-human, human-to-things and things-to-things. This means that the manufacturing-based hardware development needs to be achieved simultaneously with software development through convergence. The essential element the convergence between hardware and software is OS, for which world's leading companies such as Google and Apple have launched an intense development recognizing the importance of software. Against this backdrop, the status-quo of the software market has been examined for the study of the present report (Korea Evaluation Institute of Industrial Technology: Professional Design Technology Development Project). As a result, the software platform-based Google's android and Apple's iOS are dominant in the global market and late comers are trying to enter the market through various pathways by releasing web-based OS and similar OS to provide a new paradigm to the market. The present study is aimed at finding the way to utilize a smart content by which anyone can be a developer based on OS responding to such as social change, newly defining a smart content to be universally utilized and analyzing the market to deal with a rapid market change. The study method, scope and details are as follows: Literature investigation, Analysis on the app market according to a smart classification system, Trend analysis on the current content market, Identification of five common trends through comparison among the universal definition of smart content, the status-quo of application represented in the app market and content market situation. In conclusion, the smart content market is independent but is expected to develop in the form of a single organic body being connected each other. Therefore, the further classification system and development focus should be made in a way to see the area from multiple perspectives including a social point of view in terms of the existing technology, culture, business and consumers.

• Cartoon and Animation Studies
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• s.47
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• pp.1-29
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• 2017

360-degree virtual reality has been a technology that has been available for a long time and has been actively promoted worldwide in recent years due to development of devices such as HMD (Head Mounted Display) and development of hardware for controlling and executing images of virtual reality. The production of the 360 degree VR requires a different mode of production than the traditional video production, and the matters to be considered for the user have begun to appear. Since the virtual reality image is aimed at a platform that requires enthusiasm, presence and interaction, it is necessary to have a suitable cinematography. In VR, users can freely enjoy the world created by the director and have the advantage of being able to concentrate on his interests during playing the image. However, the director had to develope and install the device what the observer could concentrate on the narrative progression and images to be delivered. Among the various methods of transmitting images, the director can use the composition of the short. In this paper, we will study how to effectively apply the technique of directing through the composition of this shot to 360 degrees virtual reality. Currently, there are no killer contents that are still dominant in the world, including inside and outside the country. In this situation, the potential of virtual reality is recognized and various images are produced. So the way of production follows the traditional image production method, and the shot composition is the same. However, in the 360 degree virtual reality, the use of the long take or blocking technique of the conventional third person view point is used as the main production configuration, and the limit of the short configuration is felt. In addition, while the viewer can interactively view the 360-degree screen using the HMD tracking, the configuration of the shot and the connection of the shot are absolutely dependent on the director like the existing cinematography. In this study, I tried to study whether the viewer can freely change the cinematography such as the composition of the shot at a user's desired time using the feature of interaction of the VR image. To do this, 3D animation was created using a game tool called Unreal Engine to construct an interactive image. Using visual scripting of Unreal Engine called blueprint, we create a device that distinguishes the true and false condition of a condition with a trigger node, which makes a variety of shorts. Through this, various direction techniques are developed and related research is expected, and it is expected to help the development of 360 degree VR image.

• Cartoon and Animation Studies
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• s.43
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• pp.47-75
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• 2016

This study has analyzed the history of the subcontract animation in Korea that began with Golden Bat of TBC Animation Division in 1966 to 1980s and shed the light on the history of subcontract animation that has been processed over 30 years in Korean animation. For this purpose, through the outlined status of subcontract animation, such as, production company, production status, scale of industry and so forth, the status of the OEM industry then has been checked and it links the solidified background of animation into subcontract production industry with the situation in time for analysis. In addition, on the basis of the foregoing, it is intended to broaden the horizon of the history of animation through the analysis on new search for facilitating the creative animation by overcoming the issues and limits generated by the subcontract animation industry. 1970s was the time that the national objective is to advance heavy-chemical industry and export-led economic growth. From the late 1970s, the animation has been spot lighted as the main-stream export industry through the overseas subcontract orders for animation. Expansion of the subcontract animation production has been influenced from the national policies on public culture, dispersion of color TV, facilitation of video production market and other media changes of the time that led the decline of animation audiences in theaters, and another cause would be in lack of platform of broadcasting companies that avoided the independent animation production for its economic theory. The subcontract animation industry may have the positive evaluation in the aspect of expanding the animation environment, such as, structuring of animation infra, development of new human resources and etc. However, the technology-incentive 'production'-oriented advancement has created distorted structure in advancing the professional human resources due to the absence of 'pre-production' of planning and others as well as the insufficient perception on 'post production (post work)', and it was unable to formulate domestic market by re-investing the capital accumulated for OEM industry into the production of creative animation and it has been assessed as negative aspect. Animation is a cultural and spiritual product of a country. Therefore, the systematic support policy for the facilitation of the creative animation, such as, development of professional human resources, creation of outstanding work, formation of market to make the pre-circulation structure and so forth has to be sought. However, animation is an industry, but there is no perception that it is a cultural industry based on the creativeness, not hardware-oriented manufacturing business. Such a lack of recognition, there was no policies to make the market and facilitate the creative animation by the animation of Korea for this period through the long-term plan and investment for independent work production. Such an attempt is newly begun through diverse searches for protection and advancement of creative animation in Korea after 1990s.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.