• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.319-329
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• 2021

This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.173-180
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• 2021

Non Orthogonal Multiple Access (NOMA) is a technology to guarantee the explosively increased Quality of Service(QoS) of users in 5G networks. NOMA can remove the frequent orthogonality in Orthogonal Multiple Access (OMA) while allocating the power differentially to classify user signals. NOMA can guarantee higher communication speed than OMA. However, the NOMA has one disadvantage; it consumes a more energy power when the distance increases. To solve this problem, relay nodes are employed to implement the cooperative NOMA control idea. In a cooperative NOMA network, relay node participations for cooperative communications are essential. In this paper, a new bandwidth allocation scheme is proposed for cooperative NOMA platform. By employing the idea of Vickrey-Clarke-Groves (VCG) mechanism, the proposed scheme can effectively prevent selfishly actions of relay nodes in the cooperative NOMA network. Especially, base stations can pay incentives to relay nodes as much as the contributes of relay nodes. Therefore, the proposed scheme can control the selfish behavior of relay nodes to improve the overall system performance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.459-466
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• 2021

The present study was conducted to propose future research directions for weed management by examining the current trends of research on weed occurrence according to cropping systems. The cropping systems are developed for the efficient use of arable land, and the weed flora changes according to the management practices of a given cropping system. In particular, weed occurrence can be reduced by altering the soil environment. In addition, cultivation methods, such as tillage, affect the weed seed bank in the soil, thus altering the pattern of weed occurrence. Here, we propose three weed management practices according to the cropping system. First, it is necessary to develop a model that can classify weed species by analyzing young seedlings and can predict the flora in the field. Second, it is important to manage the cropping system history and establish a database of agricultural information, which can be linked to meteorological and geographic data. Third, it is critical to estimate the weed occurrence and soil seed bank dynamics, based on which a cropping system platform and digitalization technology can be developed. In the future, the prediction of weed occurrence and control according to the cropping system will contribute to sustainable agriculture by reducing the use of herbicides and solving the problems of resistant weeds.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.233-244
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• 2022

One of the most noteworthy topics in recent corporate management is ESG(Environmental, Social, Governance). Although there are many companies that have declared ESG management, KT has declared full-fledged ESG management in 2021 and is sharing its sustainable management strategy with stakeholders. In addition, KT is strengthening ESG management by issuing ESG bonds for the first time in the domestic ICT industry. At a time when the information technology industry became more important due to COVID-19, this study attempted to examine KT's ESG management goals and strategies by dividing them into environmental, social, and governance areas. KT was aiming to achieve environmental integrity through 'environmental management', 'green competence', 'energy resources', and 'eco-friendly projects' in the environmental field. In addition, in the social field, genuine creating social value was pursued through 'social contribution', 'co-growth', and 'human rights management'. Finally, in the governance area, it was aiming for a transparent corporate management system to pursue economic reliability through 'ethics and compliance' and 'risk management'. In particular, KT was promoting its own ESG management by promoting strategies to solve environmental and social problems using AI and BigData technologies based on the characteristics of a digital platform company. This study aims to derive implications for ESG strategy establishment and ESG management development direction through KT's ESG management case in relation to ESG management, which has emerged as a hot topic.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.193-201
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• 2022

5-HMF(5-Hydroxymethylfurfural) and LA(levulinic acid) derived from biomass are green platform chemicals, which have a wide of potential applications as biofules and biochemicals. In this study, the kinetics of LA formation from glucose decomposition with various concentration of sulfuric acid at different temperature was investigated. The experiments were performed in a broad temperature (140-200 ℃), using H₂SO₄ (1-3 wt%) as the catalyst. Glucose solution was made by dissolving 1 g of glucose in 10 ml of H₂SO₄ solution. The reactions rates increased with temperature and the activation energy showed a similar tendency to previous reported values. Reaction time for maximum concentration of 5-HMF decreased as the temperature increased. Furthermore, the decomposition of 5-HMF was fast as the acid concentration increased. Reaction time to reach maximum concentration of levulinic acid was reduced as the acid concentration increased. Continuing to raise the temperature decreased the maximum concentration of levulinic acid and increased the amount of humins. On the basis of results, kinetic parameters help to understand mechanism of LA and 5-HMF. In addition, this study provides useful information to achieve high concentration of LA and 5-HMF from biomass.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.51-58
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• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.31-40
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• 2023

Various policies and services are being implemented in Korea and other countries, such as the expansion of convenience facilities for mobility support, the provision of special means of transportation, and the establishment of public transportation route plans and fare policies based on data and AI-based movement pattern analysis to ensure the mobility rights of the weak in transportation. However, A research is still needed to improve service convenience in order to more conveniently use the desired means of transportation in a necessary situation from the viewpoint of the transportation vulnerable. This study examines the policies and services for the promotion of mobility for the transportation disadvantaged, and presents a MyData-based service model for mobility support for the transportation disadvantaged. In the proposed service model, the transportation-disabled person can freely choose and use the means of transportation according to individual circumstances, and receive the same transportation welfare voucher benefits provided by the state or government. The proposed service model defines the MyData platform that supports the safe collection and use of personal data, the authentication of traffic welfare recipients based on MyData, and the payment function for fee settlement after using the service as key components. In this research, the service satisfaction from the user's point of view was investigated by implementing the proposed service model and providing a demonstration service for the transportation vulnerable in Daejeon.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.129-140
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• 2021

The next generation mBcN should be built to cooperate with the wireless network to support hyper-speed and hyper-connectivity. In this paper, we propose a network architecture for the cooperation mBcN and 5G commercial network and architecture of the cooperative security gateway required for the cooperation. The proposed cooperative security gateway is between gNB and UPF to support LBO, SFC, and security. Our analysis shows that the proposed architecture has several advantages. First of all, user equipment connected with the mBcN can be easily connected through the 5G commercial radio network to the mBcN. Second, the military application traffic can be transmitted to mBcN without going through the 5G core network, reducing the end-to-end transmission delay without causing the traffic load on the 5G core network. In addition, the security level of the military application can effectively be maintained because the user equipment can be connected to the cooperative security gateway, and the traffic generated by the user equipment is transmitted to the mBcN without going through the 5G core network. Finally, we demonstrate that LBO, SFC, and security modules are essential functions of the proposed gateway in the 5G test-bed environment.