C4I system is an integrated battlefield information system that automates the five elements of command, control, communications, computers, and information to efficiently manage the battlefield. C4I systems play an important role in collecting and analyzing enemy positions, situations, and operational results to ensure that all services have the same picture in real time and optimize command decisions and mission orders. However, the current C4I has limitations whenever a new weapon system is introduced, as it only provides battlefield visualization in a single area focusing on the battlefield situation for each military service. In a future battlefield that expands not only to land, sea, and air domains but also to cyber and space domains, improved command and control decisions will be possible if organic data from various weapon systems is gathered to quickly visualize the battlefield situation desired by the user. In this study, the visualization technology applicable to the future C4I system is divided into map area, situation map area, and display area. The technological implementation of this future C4I system is based on various data and communication means such as 5G networks, and is expected to enable hyper-connected battlefield visualization that utilizes a variety of high-quality information to enable realistic and efficient battlefield situation awareness.
The Journal of the Convergence on Culture Technology
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v.10
no.1
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pp.227-233
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2024
Korea achieved its highest ever defense export performance in 2022. Defense exports are the most effective way to promote the defense industry by exporting Korea's weapons to foreign countries. In addition, to continuously supply excellent weapon systems, a solid defense industry must be established. So defense industry exports are an important issue at the national level, the Korea government is actively supporting policies for the Presidential office as a control tower. In particular, the topic of entry into the defense industry export big4 is being raised in Korea. As an innovative defense export promotion plan, this paper presents a strategic plan of joint research and development that export customized to the needs of purchasing countries and securing cutting-edge technology that can possess world-class weapon systems. In other words, in order to secure cutting-edge technology, the military must break away from existing methods and boldly select cutting-edge technology, provide sufficient budget support, and grant autonomy to development agencies. A rapid acquisition system must also be introduced so that this technology can be applied to advanced weapons in a timely manner. Export joint research and development is intended to promote flexible technology transfer excluding ultra-sensitive core technologies and to form strategic partnerships, taking into account the purchasing country's willingness to possess cutting-edge technology. Through this, we have helped Korea's defense industry exports enter the world's big4 through groundbreaking new strategy.
Journal of the Korea institute for structural maintenance and inspection
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v.28
no.4
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pp.55-61
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2024
Recently, the number of aging concrete structures is steadily increasing. This is because many of these structures are reaching their expected lifespan. Such structures require accurate inspections and persistent maintenance. Otherwise, their original functions and performance may degrade, potentially leading to safety accidents. Therefore, research on objective inspection technologies using deep learning and computer vision is actively being conducted. High-resolution images can accurately observe not only micro cracks but also spalling and exposed rebar, and deep learning enables automated detection. High detection performance in deep learning is only guaranteed with diverse and numerous training datasets. However, surface damage to concrete is not commonly captured in images, resulting in a lack of training data. To overcome this limitation, this study proposed a method for generating concrete surface damage images, including cracks, spalling, and exposed rebar, using stable diffusion. This method synthesizes new damage images by paired text and image data. For this purpose, a training dataset of 678 images was secured, and fine-tuning was performed through low-rank adaptation. The quality of the generated images was compared according to three base models of stable diffusion. As a result, a method to synthesize the most diverse and high-quality concrete damage images was developed. This research is expected to address the issue of data scarcity and contribute to improving the accuracy of deep learning-based damage detection algorithms in the future.
Hong hwan Ahn;Han Sol Lim;Seung Kyun Ra;Bong Gyou Lee
Journal of Internet Computing and Services
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v.25
no.3
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pp.71-81
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2024
In response to the COVID-19 pandemic, the global airport industry is actively introducing 4th Industrial Revolution technology-based systems for quarantine and passenger safety, and test bed construction and prior verification using airport infrastructure and resources are actively being conducted. Analysis of recent cases shows that despite the changing travel patterns of airport users and the diversification of airport service demands, most testbeds construction studies are still focused on suppliers, and task prioritization is also determined by decision makers. There is a tendency to rely on subjective judgment. In order to find practical ways to become a first mover that leads innovation in the aviation industry, this study selected tasks and derived priorities to build testbeds from a service perspective that reflects various customer service needs and changes. Research results using the AHP analysis method resulted in priorities in the order of access transportation and parking services (29.2%), security screening services (23.4%), and departure services (21.8%), and these analysis results were tested in the airport industry. It shows that innovation in testbeds construction is an important factor. In particular, the establishment of smart parking and UAM transportation testbeds not only helps strengthen airports as centers of technological innovation, but also promotes cooperation with companies, research institutes, and governments, and provides an environment for testing and developing new technologies and services. It can be a foundation for what can be done. The results and implications produced through this study can serve as useful guidelines for domestic and foreign airport practitioners to build testbeds and establish strategies.
The Journal of the Convergence on Culture Technology
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v.10
no.4
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pp.645-661
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2024
Today, the development of new technologies due to the 4th industrial revolution requires work performance methods such as non-face-to-face collaboration. In response to this, various VR collaboration tools are emerging, but VR collaboration tools for brainstorming, which are used in collaboration or design development work, are not provided. Therefore, despite the advantages and possibilities of VR for non-face-to-face collaboration, there are limitations in practical use. Accordingly, the development of VR collaboration tools in a digitalized work environment is necessary, and research on UI design development for this is required. The purpose of this study is to propose a VR collaboration tool prototype by developing an interaction UI design that applies user hand behavior elements that appear during collaboration sessions through user research. This study was a qualitative study. The research method was to conduct user research through observation and in-depth interviews, and as a result of analyzing the data obtained from this, five types of user hand behavior elements were derived. In this study, an interaction UI design was developed that reflects hand gestures as behavioral elements. And using Unity and the Oculus Integration SDK Kit, we created a prototype VR collaboration tool that can be used without a controller. As a result of conducting a user evaluation of the prototype produced in this study, it was found that users had difficulty making hand gestures accurately, and it was possible to find areas for improvement in UI design. It is expected that this study will help develop interaction UI design for VR collaboration tools that can increase work efficiency.
Recent advances in large-scale data processing technologies such as big data, cloud computing, and artificial intelligence have increased the demand for high-performance storage devices in data centers and enterprise environments. In particular, the fast data response speed of storage devices is a key factor that determines the overall system performance. Solid state drives (SSDs) based on the Non-Volatile Memory Express (NVMe) interface are gaining traction, but new bottlenecks are emerging in the process of handling large data input and output requests from multiple hosts simultaneously. SSDs typically process host requests by sequentially stacking them in an internal queue. When long transfer length requests are processed first, shorter requests wait longer, increasing the average response time. To solve this problem, data transfer timeout and data partitioning methods have been proposed, but they do not provide a fundamental solution. In this paper, we propose a dual queue based scheduling scheme (DQBS), which manages the data transfer order based on the request order in one queue and the transfer length in the other queue. Then, the request time and transmission length are comprehensively considered to determine the efficient data transmission order. This enables the balanced processing of long and short requests, thus reducing the overall average response time. The simulation results show that the proposed method outperforms the existing sequential processing method. This study presents a scheduling technique that maximizes data transfer efficiency in a high-performance SSD environment, which is expected to contribute to the development of next-generation high-performance storage systems
Bridge lanterns are installed on bridges or piers to signal the presence of these structures on navigational routes and navigable waters, and they fall under the category of light wave signals in Aids to Navigation. In Korea, medium to large bridges installed over major rivers and seas are equipped with bridge lanterns, which are necessary for routes frequented by ships and require periodic inspections on a monthly or multi-month basis. However, most bridge lanterns are mounted externally on bridge railings as fixed or manual rotary supports, posing a high risk of fatal falls during inspections. Furthermore, high -traffic bridges demand quick maintenance works due to complaints about traffic disruption, thus increasing work hazards. Consequently, this study introduced a tailored automatic bridge lantern support concept based on different types of bridge lantern installations, aiming for safe and rapid inspections. Additionally, the study sought to achieve full automation of the bridge lighting system by integrating it with a management program for monitoring and controlling bridge lanterns, utilizing both wired and wireless communication technologies. These findings provide foundational design data for new and refurbished bridges that will be installed in the future.
Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used
. Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.
Journal of the Korean Institute of Landscape Architecture
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v.39
no.5
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pp.119-126
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2011
The standard unit manpower and material in landscape architectural construction was consist of a standard and universal work classification. However, these constructional methods have created a number of problems in utilizing and responding on a variety of recently-developed working methods such as new constructional skills and technologies. This research decided that presenting the amendments of work classification of a standard unit manpower and material in landscape architectural construction was very important, and investigated those work classifications which required these new amendments. First of all, assessment items were selected through the literature reviews and a preliminary survey. Then, these assessment items were surveyed to the total of 60 professional landscape architecture field. The results of this study were as follows; First, the utilization level of the a standard unit manpower and material in landscape architectural construction was highest in the area of work classification of planting unit manpower and material. Second, the work classifications that needed to be added were recognized as leveling the ground construction, landscape structure construction, paving construction, water facilities construction, and outdoor facilities construction. Third, in the field of the a standard unit manpower and material in landscape architectural construction, 66.7% of the respondents replied that some amendments were necessary, and those amendments needed work classifications were identified as work classification of planting unit manpower and material was gigantic plant, topiary tree, temporary planting, exchange dead tree, etc. In the area of digging out was gigantic plant and plastic tree were recognized. The survey respondents also answered that, in keeping and management work classifications some amendments in pruning waste were necessary, and in the fields of rubble masonry work classifications some improvements were required in rubble aperture planting unit manpower and material and sodding and herbaceous sowing was a realistic lawn size unit manpower and material was needed. Based on the results explained above, this study suggests that amendments for a standard unit manpower and material in landscape architectural construction are necessary, especially in the areas of planting size and quality of work classifications unit manpower and material and in the unit manpower and material that affects the quality of lands caping constructions.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.13
no.1
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pp.61-72
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2018
In a rapidly changing environment, such as globalization, technology-based startups are attracting attention as a new growth engine that creates jobs and added value and promotes national competitiveness. At present, countries around the world recognize the development of technology-based start-up companies as a major policy task and strive to make policy efforts to revitalize start-ups and strengthen innovation capabilities of companies. Especially, in order to secure superiority in the fierce market competition, it is becoming more and more important for the growth and development of technological start-up companies that pioneer new markets and energize the economy based on original and innovative technologies. Therefore, it is necessary to study systematically and plan for survival and growth of technology start-up companies. The purpose of this study is to investigate the entrepreneurial spirit of Innovation, Entrepreneurship, Risk Sensibility and Technology Innovation Capacity, R&D ability, Technology Accumulation Capacity, Technology Innovation System, The results of this study are as follows. the effects of marketing ability on technical performance and financial performance are examined. First, the CEO 's entrepreneurial spirit has an effect on the technical performance and financial performance of the management performance. Second, the technology accumulation ability and the R & D capability have a positive effect on the technical performance. Finally, it was found that the ability to commercialize the technology commercialization capacity affects both technical performance and financial performance. The policy implications that can be gained through this are as follows. First, by strengthening cooperation between universities and research institutes, related technology entrepreneurship education programs should be upgraded so that technology entrepreneurs or preliminary entrepreneurs can capture business opportunities and secure market price competitiveness. Secondly, R & D for the purpose of start-up should be developed and marketable technology should be developed and linked to direct start-up. Third, it is necessary to activate the program to match the company with the honorary retirement manpower of large enterprises and SMEs, which have more experience in field experience than the founders.
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