• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

• Journal of agricultural medicine and community health
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• v.49 no.2
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• pp.121-131
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• 2024

Objective: This study is to design an intervention model for local residents to manage their oral health on their own. By establishing an autonomous participatory network without the intervention of external experts, it is possible to actively practice toothbrushing and use preventive services. Method: This is a case report study, and oral health education was conducted after interviews with 8 members of the Health Plus Village Committee in the N region of Hongcheon-gun and 156 residents of the senior center. Result: To foster oral health guardians in the community and to change behavior by actively sharing information and communicating with residents. It was confirmed that the Health Plus Village Committee was influential in spreading information, means, and interest about toothbrushing practices and preventive dental services to neighbors. Conclusion: In order to implement continuous resident-led oral health projects, resident-led village projects led by the Health Plus Village Committee should be activated through repeated empowerment education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1726-1748
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• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• Journal of Korea Port Economic Association
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• v.24 no.2
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• pp.175-192
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• 2008

Today's individual firms no longer compete as solely autonomous entities, but rather as supply chain. As such the competitive position of a port is not only determined by its internal strengths but also it is also affected by its links in a global supply chin. In other words, port competitiveness is becoming increasingly dependent on external coordination and control of the whole supply chain. The main purpose of this paper is to examine how a port embeds itself into supply chain in order to strengthen its competitive position by focusing on Dubai port case. This paper found that Dubai port used three phases-insertion, integration and dominance-as a strategies for how it can embedded into global supply chain successfully. Dubai's global supply chain strategies give some implications for the further development of the Port of Gwangyang. First, the Port of Gwangyang should fully utilize symbiotic relationship with Gwangyang free Economic Zone. Second, the integration between Korea Container Terminal Authority and GYFEZ can be recommended for fast decision-making and providing a one-stop-service. Finally, Gwangyang should pursue an aggressive supply chain strategy, aims at dominance in the regional port network through port alliance with small and medium ports in neighboring area.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.12
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• pp.1039-1047
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• 2017

This paper presents a test development of a Fly-By-Wireless flight control system for a fixed-wing unmanned aerial vehicle (UAV). Fly-By-Wireless system (FBWLS) refers to a system that uses a wireless network instead of a wired network to connect sensors and actuators with a flight control computer (FCC), reducing considerable amount of wires. FBWLS enables to design a much lighter aircraft along with decreased maintenance time and cost. In this research we developed a Zigbee-based FWBLS UAV in which sensors (GPS and AHRS) are wirelessly connected via a FCC to aileron and elevator servo motors. In order to see the effect of time delay due to wireless signal on the flight stability of the UAV, several flight tests were conducted. From the tests, it was confirmed that the effect is minor by comparing the flight response of the FBWLS with the corresponding Fly-By-Wire system.

• Korean Journal of Organic Agriculture
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• v.14 no.2
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• pp.159-177
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• 2006

Governance systems are basically an autonomous cooperation type among the government, civil society and market, also a new paradigm for efficient and democratic administration of policies. The governance mainly consists of the central operating body, institutions, operating principles and so on. The constituents are the nation(government), civil society(NGO) and market(firm). Institutional conditions are a legitimate base, financial stability and independency. And as a operating principle, governance systems have common goals and issues from a national and social point of view. This governance has been recently emerged due to financial risk of government, diffusion of new liberalism going with the globalization, localization-decentralization, and development of civil society and information-oriented society. We have to grope fur the framework of participatory agri- policy confronting globalization and localization as well as developing our agriculture and rural village. This agri-policy governance should be theoretically focused on policy network or self-organizing network or multi-lateral governance (MLG) based on NPM. Also, it is proper to have connection of nation-central type and civil society-central type. And it is necessary to have a MLG type with local governance corresponding to localization and decentralization. Governance should have the type whose participants have authority and responsibility as well. Basic directions of environmentally friendly agri-policy governance are as follows : first, its purposes are constructing the democratic and efficient framework of participatory environmentally friendly agri-policy based on consensus of all the related groups, embodying environmentally friendly agri-policy adjusted to local field, raising farmer's real interest, and improving their position. Second, its form should have a council or an agreement system, not an advisory or a consultation organ. Thus, public sector(eg. government) and voluntary sector(eg. farmers' organization) jointly execute agricultural policy and are responsible together. Environmentally friendly agri-policy governance is mainly made up of farmers' organization, cooperative and civil society(NGO). And secondary bodies are agribusinesses and academic groups. Government interacts with the main bodies on administrative execution. And environmentally friendly agri-policy governance has MLG type with a central unit, province and county units. Environmentally friendly agri-policy governance has several main functions such as agri-policy partnership, speaking for farmer's rights and interests, investigation and research on domestic and foreign agricultural streams, and etc. Especially, local unit will play roles in activation for regional agriculture, consulting on technique and management, education and training services, services entrusted by government, and so on.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.61-72
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• 2015

The capitalistic resistance movement attempted in most modern art areas was carried out through a complete convergence of the art and skill, which was the new formation of the symbolic boundary. Although this resistance movement was aimed at restoring artisan art through the revival of tbe work of handicraftsmen, it consequently caused the stratification of the art and became a de-artisan art excluding the autonomous labor. Hereupon, this study would focus on Bauhaus which attempted to dismantle the symbolic boundary through the convergence of the technology and art which actively used the condition the great industry brought only as an effort for the restoration of artisan labor, and would examine the actor-network of Bauhaus. Therefore, this study would examine the Bauhaus' artistic trend, the 16C Renaissance art promotion movement, and the 19C art crafts movement in the network-oriented relation, and would analyze the Bauhaus' ideological source which expressed design democracy through the bridging role of and analyze the artisan art and the mechanism that had the new technology fused. Furthermore, the convergence possibility of the 'collaboration spirit' being embodied as a philosophy of the democracy in the design continues with the tremendous influence of the new technology.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.91-102
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• 2019

In autonomous driving systems, the ability to classify pedestrians in images captured by cameras is very important for pedestrian safety. In the past, after extracting features of pedestrians with HOG(Histogram of Oriented Gradients) or SIFT(Scale-Invariant Feature Transform), people classified them using SVM(Support Vector Machine). However, extracting pedestrian characteristics in such a handcrafted manner has many limitations. Therefore, this paper proposes a method to classify pedestrians reliably and effectively using CNN's(Convolutional Neural Network) deep features and transfer learning. We have experimented with both the fixed feature extractor and the fine-tuning methods, which are two representative transfer learning techniques. Particularly, in the fine-tuning method, we have added a new scheme, called M-Fine(Modified Fine-tuning), which divideslayers into transferred parts and non-transferred parts in three different sizes, and adjusts weights only for layers belonging to non-transferred parts. Experiments on INRIA Person data set with five CNN models(VGGNet, DenseNet, Inception V3, Xception, and MobileNet) showed that CNN's deep features perform better than handcrafted features such as HOG and SIFT, and that the accuracy of Xception (threshold = 0.5) isthe highest at 99.61%. MobileNet, which achieved similar performance to Xception and learned 80% fewer parameters, was the best in terms of efficiency. Among the three transfer learning schemes tested above, the performance of the fine-tuning method was the best. The performance of the M-Fine method was comparable to or slightly lower than that of the fine-tuningmethod, but higher than that of the fixed feature extractor method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.84-99
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• 2021

As the micro-mobility market grows, the demand for route guidance, that includes uphill information as well, is increasing. Since the climbing angle depends on the electric motor uesed, it is necessary to establish an uphill road DB according to the threshold standard. Although road alignment information is a very important element in the basic information of the roads, there is no information currently on the longitudinal slope in the road digital map. The High Definition(HD) map which is being built as a preparation for the era of autonomous vehicles has the altitude value, unlike the existing standard node link system. However, the HD map is very insufficient because it has the altitude value only for some sections of the road network. This paper, hence, intends to propose a method to generate the road longitudinal slope using currently available data. We developed a method of computing the longitudinal slope by combining the digital elevation model and the standard link system. After creating an altitude at the road link point divided by 4m based on the Seoul road network, we calculated individual slope per unit distance of the road. After designating a representative slope for each road link, we have extracted the very steep road that cannot be climbed with personal mobility and the slippery roads that cannot be used during heavy snowfall. We additionally described errors in the altitude values due to surrounding terrain and the issues related to the slope calculation method. In the future, we expect that the road longitudinal slope information will be used as basic data that can be used for various convergence analyses.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1047-1056
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• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.