Kim, Haelee;Cho, Dong-hyun;Lee, Sanghoon;Park, Chanhwi;Lim, Ha Kyeong;Kim, Geonwoo;Kwak, Minwoo;Lee, Changhyun;Kim, Shinhyung;Koo, Inhoi;Lee, Daewoo
Journal of the Korean Society for Aeronautical & Space Sciences
/
v.50
no.2
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pp.137-146
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2022
AIS(Automatic Identification System) is a device that automatically transmits and receives ship information and is mounted on the ship. AIS information of ships near the coast can be received on the ground, but when going out to sea more than 50 nautical miles, communication with the ground is cut off. To solve this problem, ship information can be transmitted to the ground through an AIS satellite equipped with an AIS receiver. There is no case of AIS satellite development in Korea yet, and many domestic shipping companies are using overseas AIS services. PNUSAT-1 is a 1U+ CubeSat, developed by Pusan National University, and it is equipped with an AIS receiver for monitoring of ships and transmitting ship information to the ground. Since the mission data of PNUSAT-1 is in text format, the data size is not large. In consideration of this, communication equipment, low-precision sensors, and actuators were selected. In this paper, system preliminary design of PNUSAT-1 was performed, requirements for mission performance, operation scenario and mode design, hardware and software selection, and preliminary design of each subsystem were performed.
Since the first 12 ones were designated in 1969, 228 places have been designated as tourism sites, and about 70 percent of them were designated before the 2000s. It shows that changes in most of tourism sites are needed in terms of physical, functional and environmental aspects. However, there are still not enough academic progress and policy consideration regarding the decline of tourism sites and the regeneration of them. This study aims to find the causes of decline and the factors to activate in tourism sites, to draw important conditions to recover the attractiveness of tourism sites in decline from the comprehensive analysis of causes and factors, and to apply the conditions to a real case in severely declining stage. According to the findings, the conditions for recovery could be restructured into four categories: 'The upgrade of hardware such as facilities in tourism site', 'the development of software such as contents and programs', 'the reinforcement of local capacity and institutional grounds' and 'the expansion of functions and the building of networks with various external stakeholders such as expert groups, related enterprises, talented individuals and so forth.
Park, Hyune-Jun;Lee, Sang-Min;Song, Chang-Heon;Cho, Jung-Woo;Oh, Joo-Young
Tunnel and Underground Space
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v.32
no.5
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pp.298-311
/
2022
Some problems, such as aging workers, a decreased population due to a low birth rate, and shortage of skilled workers, are rising in construction sites. Therefore research for smart construction technology that can be improved for productivity, safety, and quality has been recently developed with government support by replacing traditional construction technology with advanced digital technology. In particular, the motor grader that mainly performs road surface flattening is a construction machine that requires the application of automation technology for repetitive construction. It is predicted that the construction period will be shortened if the construction automation technology such as trajectory tracking, automation work, and remote control technology is applied. In this study, we introduce the hardware and software architecture of the smart motor grader to apply unmanned and automation technology and then analyze the traditional earthwork method of the motor grader. We suggested the application plans for the path pattern and blade control method of the smart motor grader based on this. In addition, we verified the performance of waypoint-based path-following depending on scenarios and the blade control's performance through tests.
Seung Ryeon Kim ;Duk Geun Yoon ;Sun Jin Oh ;Eui Hyuk Lee;Sa Won Min ;Hyun Su Oh ;Eun Hee Kim
Journal of the Korea Society for Simulation
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v.32
no.3
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pp.23-31
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2023
Software development involves a series of stages, including requirements analysis, design, implementation, unit testing, and integration testing, similar to those used in the system engineering process. This study utilized MathWorks' model-based design platform to develop multi-function radar software and evaluated its feasibility and efficiency. Because the development of conventional radar software is performed by a unit algorithm rather than in an integrated form, it requires additional efforts to manage the integrated software, such as requirement analysis and integrated testing. The mode-based platform applied in this paper provides an integrated development environment for requirements analysis and allocation, algorithm development through simulation, automatic code generation for deployment, and integrated requirements testing, and result management. With the platform, we developed multi-level models of the multi-function radar software, verified them using test harnesses, managed requirements, and transformed them into hardware deployable language using the auto code generation tool. We expect this Model-based integrated development to reduce errors from miscommunication or other human factors and save on the development schedule and cost.
Dong-Hoon Yoo;Young-Chan Lee;Do-Sam Kim;Kwang-Ho Lee
Journal of Korean Society of Coastal and Ocean Engineers
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v.35
no.4
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pp.75-83
/
2023
Apart from implementing hardware solutions like raising the crest freeboard of coastal structures to efficiently counter wave-overtopping, there is a simultaneous requirement for software-driven disaster mitigation strategies. These tactics involve the swift and accurate dissemination of wave-overtopping information to the inland regions of coastal zones, enabling the regulation of evacuation procedures and movement. In this study, a method was proposed to estimate wave-overtopping by utilizing the temporal variation of wave heights exceeding the structure's crown level, with the aim of developing an on-site wave measurement system for providing wave-overtopping information in the field. Laboratory model experiments were conducted on vertical seawall structures to measure wave-overtopping volumes and wave runup heights under different wave conditions and structural freeboard variations. By assuming that the velocity of water inundation on the top of the structure during wave-overtopping events is equivalent to the long-wave velocity, an overtopping discharge coefficient was introduced. This coefficient was utilized to estimate the rate of wave-overtopping based on the temporal changes in wave runup heights measured at the top of the structure. Upon reasonably calculating the overtopping discharge coefficient, it was verified that the estimation of wave-overtopping could be achieved solely based on the wave runup heights.
The impact of competition on pricing has been studied in the context of counterfactual merger analyses where expected optimal prices in a hypothetical monopoly are compared with observed prices in an oligopolistic market. Such analyses would typically assume static decision making by consumers and firms and thus have been applied mostly to data obtained from consumer packed goods such as cereal and soft drinks. However such static modeling approach is not suitable when decision makers are forward looking. When it comes to the markets for durable products with indirect network effects, consumer purchase decisions and firm pricing decisions are inherently dynamic as they take into account future states when making purchase and pricing decisions. Researchers need to take into account the dynamic aspects of decision making both in the consumer side and in the supplier side for such markets. Firms in a two-sided market typically subsidize one side of the market to exploit the indirect network effect. Such pricing behaviors would be more prevalent in competitive markets where firms would try to win over the battle for standard. While such qualitative expectation on the relationship between pricing behaviors and competitive structures could be easily formed, little empirical studies have measured the extent to which the distinct pricing structure in two-sided markets depends on the competitive structure of the market. This paper develops an empirical model to measure the impact of competition on optimal pricing of durable products under indirect network effects. In order to measure the impact of exogenously determined competition among firms on pricing, we compare the equilibrium prices in the observed oligopoly market to those in a hypothetical monopoly market. In computing the equilibrium prices, we account for the forward looking behaviors of consumers and supplier. We first estimate a demand function that accounts for consumers' forward-looking behaviors and indirect network effects. And then, for the supply side, the pricing equation is obtained as an outcome of the Markov Perfect Nash Equilibrium in pricing. In doing so, we utilize numerical dynamic programming techniques. We apply our model to a data set obtained from the U.S. video game console market. The video game console market is considered a prototypical case of two-sided markets in which the platform typically subsidizes one side of market to expand the installed base anticipating larger revenues in the other side of market resulting from the expanded installed base. The data consist of monthly observations of price, hardware unit sales and the number of compatible software titles for Sony PlayStation and Nintendo 64 from September 1996 to August 2002. Sony PlayStation was released to the market a year before Nintendo 64 was launched. We compute the expected equilibrium price path for Nintendo 64 and Playstation for both oligopoly and for monopoly. Our analysis reveals that the price level differs significantly between two competition structures. The merged monopoly is expected to set prices higher by 14.8% for Sony PlayStation and 21.8% for Nintendo 64 on average than the independent firms in an oligopoly would do. And such removal of competition would result in a reduction in consumer value by 43.1%. Higher prices are expected for the hypothetical monopoly because the merged firm does not need to engage in the battle for industry standard. This result is attributed to the distinct property of a two-sided market that competing firms tend to set low prices particularly at the initial period to attract consumers at the introductory stage and to reinforce their own networks and eventually finally to dominate the market.
Chul-Soo Ye;Young-Man Ahn;Tae-Woong Baek;Kyung-Tae Kim
Korean Journal of Remote Sensing
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v.39
no.5_4
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pp.1111-1123
/
2023
In recent times, semantic image segmentation methods using deep learning models have been widely used for monitoring changes in surface attributes using remote sensing imagery. To enhance the performance of various UNet-based deep learning models, including the prominent UNet model, it is imperative to have a sufficiently large training dataset. However, enlarging the training dataset not only escalates the hardware requirements for processing but also significantly increases the time required for training. To address these issues, transfer learning is used as an effective approach, enabling performance improvement of models even in the absence of massive training datasets. In this paper we present three transfer learning models, UNet-ResNet50, UNet-VGG19, and CBAM-DRUNet-VGG19, which are combined with the representative pretrained models of VGG19 model and ResNet50 model. We applied these models to building extraction tasks and analyzed the accuracy improvements resulting from the application of transfer learning. Considering the substantial impact of learning rate on the performance of deep learning models, we also analyzed performance variations of each model based on different learning rate settings. We employed three datasets, namely Kompsat-3A dataset, WHU dataset, and INRIA dataset for evaluating the performance of building extraction results. The average accuracy improvements for the three dataset types, in comparison to the UNet model, were 5.1% for the UNet-ResNet50 model, while both UNet-VGG19 and CBAM-DRUNet-VGG19 models achieved a 7.2% improvement.
Black box cryptography is a cryptographic scheme based on a hardware encryption device, operating under the assumption that the device and the user can be trusted. However, with the increasing use of cryptographic algorithms on unreliable open platforms, the threats to black box cryptography systems have become even more significant. As a consequence, white box cryptography have been proposed to securely operate cryptographic algorithms on open platforms by hiding encryption keys during the encryption process, making it difficult for attackers to extract the keys. However, unlike traditional cryptography, white box-based encryption lacks established specifications, making challenging verify its structural security. To promote the safer utilization of white box cryptography, CHES organizes The WhibOx Contest periodically, which conducts safety analyses of various white box cryptographic techniques. Among these, the Differential Computation Analysis (DCA) attack proposed by Bos in 2016 is widely utilized in safety analyses and represents a powerful attack technique against robust white box block ciphers. Therefore, this paper analyzes the research trends in white box block ciphers and provides a summary of DCA attacks and relevant countermeasures. adhering to the format of a research paper.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.16
no.6
/
pp.489-498
/
2023
Advancements in hardware performance and computing technology have facilitated the progress of climate prediction models to address climate change. The Korea Meteorological Administration employs the GloSea6 model with supercomputer technology for operational use. Various universities and research institutions utilize the Low-GloSea6 model, a low-resolution coupled model, on small to medium-scale servers for weather research. This paper presents an analysis using Intel VTune Profiler on Low-GloSea6 to facilitate smooth weather research on small to medium-scale servers. The tri_sor_dp_dp function of the atmospheric model, taking 1125.987 seconds of CPU time, is identified as a hotspot. Nonlinear regression models, a machine learning technique, are applied and compared to existing functions conducting numerical operations. The K-Nearest Neighbors regression model exhibits superior performance with MAE of 1.3637e-08 and SMAPE of 123.2707%. Additionally, the Light Gradient Boosting Machine regression model demonstrates the best performance with an RMSE of 2.8453e-08. Therefore, it is confirmed that applying a nonlinear regression model to the tri_sor_dp_dp function during the execution of Low-GloSea6 could be a viable alternative.
In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.
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