• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.171-187
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• 2022

Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.4
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• pp.257-267
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• 2023

Purpose. The purpose of the study was to fabricate a prototype robotic simulator for dental education, to test whether it could simulate mandibular movements, and to assess the possibility of the stimulator responding to stimuli during dental practice. Materials and methods. A virtual simulator model was developed based on segmentation of the hard tissues using cone-beam computed tomography (CBCT) data. The simulator frame was 3D printed using polylactic acid (PLA) material, and dentiforms and silicone face skin were also inserted. Servo actuators were used to control the movements of the simulator, and the simulator's response to dental stimuli was created by pressure and water level sensors. A water level test was performed to determine the specific threshold of the water level sensor. The mandibular movements and mandibular range of motion of the simulator were tested through computer simulation and the actual model. Results. The prototype robotic simulator consisted of an operational unit, an upper body with an electric device, a head with a temporomandibular joint (TMJ) and dentiforms. The TMJ of the simulator was capable of driving two degrees of freedom, implementing rotational and translational movements. In the water level test, the specific threshold of the water level sensor was 10.35 ml. The mandibular range of motion of the simulator was 50 mm in both computer simulation and the actual model. Conclusion. Although further advancements are still required to improve its efficiency and stability, the upper-body prototype simulator has the potential to be useful in dental practice education.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.