• STI Policy Review
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• v.9 no.1
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• pp.133-157
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• 2018

The divide between the "digital" economy and the traditional "physical" economy is outdated. In fact, we are in a transition to a singular economy. This paper classifies economic objects (including actors) as either physical or virtual and argues that due to emerging technologies, these objects are interacting with each other in both physical and increasingly digital spheres in tandem. This paper recognizes the elemental difference between atoms and bytes but argues that physical and digital economic activities are becoming inseparably intertwined. Furthermore, arbitrarily dividing the economy into two categories - one "physical" and the other "digital" - distorts the overall view of the actual execution of economic activity. A wide range of innovations emerging concurrently is fueling the transition to a singular economy. Often referred to as the elements of the Fourth Industrial Revolution (4IR), four emerging technological areas are reviewed here: distributed ledger technology, artificial intelligence/machine learning/data sciences, biometrics and remote sensor technologies, and access infrastructure (universal internet access/electricity/cloud computing). The financial services sector is presented as a case study for the potential impact of these 4IR technologies and the blurring physical/digital line. To reach the potential of these innovations and a truly singular economy, it requires the concurrent development of social, organizational, and regulatory innovations, though they lag in terms of technological progress thus far.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.11-20
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.330-330
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• 2022

우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.1
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• pp.1-13
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• 1986

The purpose of this study is to investigate the effect of temperature control by a shade tree and the lawn area. In this investigation, we find out that artificial-lawn, concerte, and exposed soil are more higher temperature than covered with plant materials. The results of the measurement may to summerized as follows; 1) Low-temperature effects of zoysia japonica is more controlled by condition of growth than leaf length of grass. Surface temperature make 0.7$^{\circ}C$ difference between long grass (15cm), and short grass (5cm), but make 5$^{\circ}C$ difference between good growth grass (230/10$\textrm{cm}^2$) and bad growth grass (80/10$\textrm{cm}^2$). 2) The surface temperature of the lawn area is 40.5$^{\circ}C$ lower on a maxinum than that of the artificial lawn (July 28, 1985). During the day of summer, shade area under the shade tree is 0.9$^{\circ}C$ lower then lawn area surface temperature, 6.9$^{\circ}C$ lower than bad growth lawn, 10.3$^{\circ}C$ lower than exposed soil, and 18$^{\circ}C$ lower than concrete surface temperature. 3) Natural irrigation effect on the surface temperature fluctuation. But this effect is changed by compositions of ground materials and time-lapse. 4) Sunny day is more effective than cloud day. 5) In summer season, surface temperature make a difference compare to temperature of 0.5-1.5m height from ground : Surface temperature is 3.4$^{\circ}C$ lower at the lawn area (11 a.m.), 4.2$^{\circ}C$ lower at the shade area the shade tree, 12.7$^{\circ}C$ higher at the concrete area (3p.m.), 38.8$^{\circ}C$ higher at the artificial lawn (2p.m.) 6) According to compositions of ground materials and season have specific vertical temperature distribution curve. 7) In summer season, temperature distribution of 0.5-1.5m hight at the shade tree is 4.8-5.7$^{\circ}C$ lower than concrete area (noon-3p.m.)

• Journal of The Geomorphological Association of Korea
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• v.19 no.2
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• pp.69-79
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• 2012

The aim of this study is to analyze the mid-term changes of beach and dune morphology at Sohwang beach, Korea using by Total Station. Measurements executed 4 times during two year. Based on ArcInfo as point cloud obtained through precise measurement data by Total Station, alteration of beach and dune was analyzed at DEM, of which cell size is about 1m. Since these artificial constructions have influenced current systems of this region, the large-scale sand movements above mentioned have occurred around the jetty and the sea-wall. There occurred sedimentation in the north of the Jetty and erosion in the south of the Jetty, which is installed at the central part of object area. The direction of recent topographic development does not coincide with that of wind, and, rather, topographic changes occurred mainly at beaches and dunes due to the transformation of coastal water flow caused by artificial structure nearby. If precise measurement is conducted periodically, and long term monitoring is carried out by installing equipment measuring movement pattern of sediment around artificial structure, cause of topographic change around the object area could be discovered.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.944-951
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• 2018

Artificial icing test and wind tunnel test can be performed to reduce the development period when a rotorcraft is required operation under icing situations. Artificial icing test of the KUH(Korean Utility Helicopter) was performed in advance to verify anti-icing and de-icing performance before natural icing test. Although high-precision sensor, the CCP(Cloud Combination Probe) is used to measure icing test condition parameters such as LWC(Liquid Water Content) and MVD(Median Volume Diameter), the measured values need to be verified in various methods due to the possibility of uncertainties which are the test atmosphere environment, sensor errors, and etc. The calculated LWC from the ice thickness cumulated on the fuselage of the KUH is compared to the measured value by CCP, and the results show the effective indirect method to check the test conditions.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.368-376
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• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.9-15
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• 2021

With the recent development of 5G and artificial intelligence technologies, it is interested in AIOT technology to collect, process, and analyze information in cloud edge environments. AIIoT technology is being applied to various smart environments, but research is needed to perform fast response processing through accurate analysis of collected information. In this paper, we propose a technique to minimize bandwidth and processing time by blocking the connection processing between AIOT information through fast processing and accurate analysis/forecasting of information collected in the smart environment. The proposed technique generates seeds for data indexes on AIOT devices by multipointing information collected by blockchain, and blocks them along with collection information to deliver them to the data center. At this time, we deploy Deep Neural Network (DNN) models between cloud and AIOT devices to reduce network overhead. Furthermore, server/data centers have improved the accuracy of inaccurate AIIoT information through the analysis and predicted results delivered to minimize latency. Furthermore, the proposed technique minimizes data latency by allowing it to be partitioned into a layered multilayer network because it groups it into blockchain by applying weights to AIOT information.