• Journal of Microbiology and Biotechnology
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• v.32 no.10
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• pp.1325-1334
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• 2022

Global warming has accelerated in recent decades due to the continuous consumption of petroleum-based fuels. Cyanobacteria-derived biofuels are a promising carbon-neutral alternative to fossil fuels that may help achieve a cleaner environment. Here, we propose an effective strategy based on the large-scale cultivation of a newly isolated cyanobacterial strain to produce phycobiliprotein and biodiesel, thus demonstrating the potential commercial applicability of the isolated microalgal strain. A native cyanobacterium was isolated from Goryeong, Korea, and identified as Pseudanabaena mucicola GO0704 through 16s RNA analysis. The potential exploitation of P. mucicola GO0704 was explored by analyzing several parameters for mixotrophic culture, and optimal growth was achieved through the addition of sodium acetate (1 g/l) to the BG-11 medium. Next, the cultures were scaled up to a stirred-tank bioreactor in mixotrophic conditions to maximize the productivity of biomass and metabolites. The biomass, phycobiliprotein, and fatty acids concentrations in sodium acetate-treated cells were enhanced, and the highest biodiesel productivity (8.1 mg/l/d) was achieved at 96 h. Finally, the properties of the fuel derived from P. mucicola GO0704 were estimated with converted biodiesels according to the composition of fatty acids. Most of the characteristics of the final product, except for the cloud point, were compliant with international biodiesel standards [ASTM 6761 (US) and EN 14214 (Europe)].

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.33-40
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• 2022

With the recent increase in the development of military drones, they are adopted and used as the combat system of battalion level or higher. However, it is difficult to use drones that can be used in battles below the platoon level due to the current conditions for the formation of units in the Korean military. In this paper, therefore, we developed a program drones equipped with a thermal imaging camera and LiDAR sensor for reconnaissance and exploration that can be applied in battles below the platoon level. Using these drones, we studied the possibility and feasibility of drones for small-scale combats that can find hidden enemies, search for an appropriate detour through image processing and conduct reconnaissance and search for battlefields, hiding and cover-up through image processing. In addition to the purpose of using the proposed drone to search for an enemies lying in ambush in the battlefield, it can be used as a function to check the optimal movement path when a combat unit is moving, or as a function to check the optimal place for cover-up or hiding. In particular, it is possible to check another route other than the route recommended by the program because the features of the terrain can be checked from various viewpoints through 3D modeling. We verified the possiblity of flying by designing and assembling in a form of adding LiDAR and thermal imaging camera module to a drone assembled based on racing drone parts, which are open source hardware, and developed autonomous flight and search functions which can be used even by non-professional drone operators based on open source software, and then installed them to verify their feasibility.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.71-78
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• 2022

This paper proposes an algorithm for 3D object detection by processing point cloud data of 3D LiDAR. Unlike 2D LiDAR, 3D LiDAR-based data was too vast and difficult to process in three dimensions. This paper introduces various studies based on 3D LiDAR and describes 3D LiDAR data processing. In this study, we propose a method of processing data of 3D LiDAR using clustering techniques for object detection and design an algorithm that fuses with cameras for clear and accurate 3D object detection. In addition, we study models for clustering 3D LiDAR-based data and study hyperparameter values according to models. When clustering 3D LiDAR-based data, the DBSCAN algorithm showed the most accurate results, and the hyperparameter values of DBSCAN were compared and analyzed. This study will be helpful for object detection research using 3D LiDAR in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.715-725
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• 2022

With the development of digital technology related to mobile, cloud, IoT, even traditional businesses have began to develop strategies for digital transformation. This is regarded as a very important part for business sustainability. However, many of these attempts are being conducted from the management point of view, and there has been little research on user experience design for digital transformation. In this study, Starbucks, which started a offline store business and expanded its experience with online services, was selected as a representative case and user research was conducted on it. Through an usability evaluation and post-task interviews of the Starbucks mobile application users, we discovered important issues of user experience to consider when transforming and expanding services online from offline. Based on the findings, the considersations for designing online user experience were discussed and proposed. These are expected to contribute to the process of researching and implementing digital transformation.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.803-813
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• 2022

In this study, we improved the water-based condensation particle counter in Atmospheric Research Aircraft NARA and investigated the condensation particle number concentration over the Korean peninsula. Pump and set point information were changed to improve the instrument used by aircraft for observation. Ground-based observational result showed that the error between two instruments, which are water-based condensation particle counter and butanol-based condensation particle counter, was 4.7%. Aerial observational result revealed that the number concentration before improvement indicate large variation with unstable condition, whereas the number concentration after improvement indicate a reasonable variation. After improvement, the number concentration was 706±499 particle/cm³ in the West Sea and 257±80 particle/cm³ in Gangwon-do, and these are similar to the concentration range reported in previous studies. Notably, this is the first attempt to use aerial observation with water-based condensation particle counter to investigate condensation particle number concentration.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.113-119
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• 2023

In this paper, we propose an optimization of a pose estimation deep learning model for recognition of abnormal behavior in unmanned stores using radio frequencies. The radio frequency use millimeter wave in the 30 GHz to 300 GHz band. Due to the short wavelength and strong straightness, it is a frequency with less grayness and less interference due to radio absorption on the object. A millimeter wave radar is used to solve the problem of personal information infringement that may occur in conventional CCTV image-based pose estimation. Deep learning-based pose estimation models generally use convolution neural networks. The convolution neural network is a combination of convolution layers and pooling layers of different types, and there are many cases of convolution filter size, number, and convolution operations, and more cases of combining components. Therefore, it is difficult to find the structure and components of the optimal posture estimation model for input data. Compared with conventional millimeter wave-based posture estimation studies, it is possible to explore the structure and components of the optimal posture estimation model for input data using genetic algorithms, and the performance of optimizing the proposed posture estimation model is excellent. Data are collected for actual unmanned stores, and point cloud data and three-dimensional keypoint information of Kinect Azure are collected using millimeter wave radar for collapse and property damage occurring in unmanned stores. As a result of the experiment, it was confirmed that the error was moored compared to the conventional posture estimation model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.3
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• pp.245-259
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• 2023

The purpose of this paper is to examine the most recent tunnel scanning systems to obtain insights for the development of non-contact mobile inspection system. Tunnel scanning systems are mostly being developed by adapting two main technologies, namely laser scanning and image scanning systems. Laser scanning system has the advantage of accurately recreating the geometric characteristics of tunnel linings from point cloud. On the other hand, image scanning system employs computer vision to effortlessly identify damage, such as fine cracks and leaks on the tunnel lining surface. The analysis suggests that image scanning system is more suitable for detecting damage on tunnel linings. A camera-based tunnel scanning system under development should include components such as lighting, data storage, power supply, and image-capturing controller synchronized with vehicle speed.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.95-101
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• 2023

Colmap is one of the innovative artificial intelligence technologies, highly effective as a tool in 3D reconstruction tasks. Moreover, it excels at constructing intricate 3D models by utilizing images and corresponding metadata. Colmap generates 3D models by merging 2D images, camera position data, depth information, and so on. Through this, it achieves detailed and precise 3D reconstructions, inclusive of objects from the real world. Additionally, Colmap provides rapid processing by leveraging GPUs, allowing for efficient operation even within large data sets. In this paper, we have presented a method of collecting 2D images of traditional Korean towers and reconstructing them into 3D models using Colmap. This study applied this technology in the restoration process of traditional stone towers in South Korea. As a result, we confirmed the potential applicability of Colmap in the field of cultural heritage restoration.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1075-1084
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• 2022

The use of Hi-Tech in cultural heritage preservation and the promotion of cultural heritage values in general, particularly artifacts, opens new opportunities for attracting tourists while also posing a challenge due to the need to reward high-quality excursions to visitors historical and cultural values. Building Information Modeling (BIM) and Hi-Tech in new building management have been widely adopted in the construction industry; however, Historic Building Information Modeling (HBIM) is an exciting challenge in 3D modeling and building management. For those reasons, the Scan-to-HBIM approach involves generating an HBIM model for existing buildings from the point cloud data collected by Terrestrial 3D Laser Scanner integrated with Virtual Reality (VR), Augmented Reality (AR), contributes to spatial historic sites simulation for virtual experiences. Therefore, this study aims to (1) generate the application of Virtual Reality, Augmented Reality to Historic Building Information Modeling - based workflows in a case study which is a monument in the city; (2) evaluate the application of these technologies to improve awareness of visitors related to the promotion of historical values by surveying the experience before and after using this application. The findings shed light on the barriers that prevent users from utilizing technologies and problem-solving solutions. According to the survey results, after experiencing virtual tours through applications and video explanations, participant's perception of the case study improved. When combined with emerging Hi-Tech and immersive interactive games, the Historic Building Information Modeling helps increase information transmission to improve visitor awareness and promote heritage values.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.110-122
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• 2023

Over the last few decades, various innovative technologies have emerged that have significantly contributed to making life easier for humans. Various information and communication technologies (ITCs) have emerged as a result of the global technological revolution, including big data, IoT, 4G and 5G networks, cloud computing, mobile computing, and artificial intelligence. These technologies have been adopted in urban planning and development, which gave rise to the concept of smart cities in the 1990s. A smart city is a type of city that uses ITCs to exchange and share information to enhance the quality of services for its citizens. With the global population increasing at unprecedented levels, cities are overwhelmed with a myriad of challenges, such as the energy crisis, environmental pollution, sanitation and sewage challenges, and water quality issues, and therefore, have become a convergence point of economic, social, and environmental risks. The concept of a smart city is a multidisciplinary, unified approach that has been adopted by governments and municipalities worldwide to overcome these challenges. Though challenging, this transformation is essential for cities with differing technological and social features, which all have the potential to determine the success or failure of the digital transformation of cities into smart cities. In recent years, researchers, businesses, and the government have all turned their attention to the emerging field of smart cities. Accordingly, this paper aims to represent a thorough understanding of the movement toward smart cities. The key themes identified are smart city definitions and concepts, smart city dimensions, and smart city architecture of different layers. Furthermore, this article discusses the challenges and some examples of smart cities.