• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.161-169
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• 2011

There is a consensus in the field of vehicular network security that public key cryptography should be used to secure communications. A certificate revocation list (CRL) should be distributed quickly to all the vehicles in the network to protect them from malicious users and malfunctioning equipment as well as to increase the overall security and safety of vehicular networks. Thus, a major challenge in vehicular networks is how to efficiently distribute CRLs. This paper proposes a CRL distribution method aided by terrestrial digital multimedia broadcasting (T-DMB). By using T-DMB data broadcasting channels as alternative communication channels, the proposed method can broaden the network coverage, achieve real-time delivery, and enhance transmission reliability. Even if roadside units are not deployed or only sparsely deployed, vehicles can obtain recent CRLs from the T-DMB infrastructure. A new transport protocol expert group (TPEG) CRL application was also designed for the purpose of broadcasting CRLs over the T-DMB infrastructure.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.103-108
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• 2008

Art is an ongoing process of experimenting and challenging. The challenge and experiments of the artists encompass both the conceptual process and the expressive process of creating artworks. It is not mandatory to use cutting-edge technologies for interactive performances, since they can be realized by adapting pre-existing technologies. Using previous technologies reduces the difficulties in the production process and makes it easier for the audience to understand the way of participation. In this paper, propose an ARS-server-based control system in which a large audience can participate during a performance to control certain features on stage. This system was first proposed during the 'Ubiplay Workshop and Seminar' hosted by the GSCT, KAIST, and applied to the digital performance 'Syntasia' in June and July, 2007, hosted by the Goyang Culture Foundation.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.1-8
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• 2012

The application of object recognition technology has been increased with a growing need to introduce automated system in industry. However, object transformed by noises and shadows appeared from illumination causes challenge problem in object detection and recognition. In this paper, an illumination invariant object detection using a DoG filter and adaptive threshold is proposed that reduces noises and shadows effects and reserves geometry features of object. And also, rotation invariant object recognition is proposed that has trained with neural network using classes categorized by object type and rotation angle. The simulation has been processed to evaluate feasibility of the proposed method that shows the accuracy of 99.86% and the matching speed of 0.03 seconds on ETRI database, which has 16,848 object images that has obtained in various lighting environment.

• Convergence Security Journal
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• v.24 no.1
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• pp.35-42
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• 2024

Multi-tenancy architecture plays a crucial role in cloud-based services and applications, and data isolation within such environments has emerged as a significant security challenge. This paper investigates various data isolation methods including schema-based isolation, logical isolation, and physical isolation, and compares their respective advantages and disadvantages. It evaluates the practical application and effectiveness of these data isolation methods, proposing security considerations and selection criteria for data isolation in the development of multi-tenant websites. This paper offers important guidance for developers, architects, and system administrators aiming to enhance data security in multi-tenancy environments. It suggests a foundational framework for the design and implementation of efficient and secure multi-tenant websites. Additionally, it provides insights into how the choice of data isolation methods impacts system performance, scalability, maintenance ease, and overall security, exploring ways to improve the security and stability of multi-tenant systems.

• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.531-538
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• 2008

With the dynamic and mobile nature of ad hoc networks, links may fail due to topology changes. So, a major challenge in ad hoc network is dynamically to search paths from a source to destination with an efficient routing method, which is an important issue for delay-sensitive real-time application. The main concerns of graph theory in communications are finding connectivity and searching paths using given nodes. A topology of the nodes in ad hoc networks can be modeled as an adjacency matrix. In this paper, based on this adjacency matrix, we propose new path search algorithms using a sequence of matrix calculation. The proposed algorithms can search paths from a destination to a source using connectivity matrix. Two matrix-based algorithms for two different purposes are proposed. Matrix-Based Backward Path Search(MBBS) algorithm is designed for shortest path discovery and Matrix-Based Backward Multipath Search(MBBMS) algorithm is for multipath search.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.73-84
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• 2019

Machine learning as a service, the so-called MLaaS, has recently attracted much attention in almost all industries and research groups. The main reason for this is that you do not need network servers, storage, or even data scientists, except for the data itself, to build a productive service model. However, machine learning is often very difficult for most developers, especially in traditional science due to the lack of well-structured big data for scientific data. For experiment or application researchers, the results of an experiment are rarely shared with other researchers, so creating big data in specific research areas is also a big challenge. In this paper, we introduce the KISTI-ML platform, a community-based rapid AI model development for scientific data. It is a place where machine learning beginners use their own data to automatically generate code by providing a user-friendly online development environment. Users can share datasets and their Jupyter interactive notebooks among authorized community members, including know-how such as data preprocessing to extract features, hidden network design, and other engineering techniques.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.190-197
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• 2019

The purpose of this study was conducted as a basic data for the formation of a correct job value and to investigate the relationship between lifestyles and their job value in the dental hygiene students. A self-reported questionnaire was completed by 237 dental hygiene students in Seoul city from September 1 to 30, 2018. The data were analyzed by t-test, one way ANOVA, Pearson's correlation. regression analysis. There were lifestyles(3.27), job value(3.77) in subject. The faster birth order, the higher tended to have the internal job value(p<.05). The challenge·adventure, family-oriented lifestyles were were higher in female(p<.05). In order for college students' lifestyles to have a positive meaning on job values, it is necessary to apply job values education, career aptitude tests, and application of individual counseling programs.

• Convergence Security Journal
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• v.20 no.2
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• pp.123-135
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• 2020

Since AlphaGo's Match in 2016, there has been a growing calls for artificial intelligence applications in various industries, and research related to it has been actively conducted. The same is true in the military field, and since there has been no weapon system with artificial intelligence so far, effort to implement it are posing a challenge. Meanwhile, AlphaGo Zero, which beat AlphaGo, showed that artificial intelligence's self-training data-based approach can lead to better results than the knowledge-based approach by humans. Taking this point into consideration, this paper proposes to apply Reinforcement Learning, which is the basis of AlphaGo Zero, to the Shipboard Combat System or Combat Management System. This is how an artificial intelligence application to the Shipboard Combat System or Combat Management System that allows the optimal tactical assist with a constant win rate to be recommended to the user, that is, the commanding officer and operation personnel. To this end, the definition of the combat performance of the system, the design plan for the Shipboard Combat System, the mapping with the real system, and the training system are presented to smoothly apply the current operations.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.123-131
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• 2020

After observing that most tourists plan to complete their visits to multiple cultural heritage sites within one day, we surmised that for many museum visitors, the foremost thought is with regard to the amount of time is to be spent at each location and how they can maximize their enjoyment at a site while still balancing their travel itinerary? Recommendation systems in e-commerce are built on knowledge about the users' previous purchasing history; recommendation systems for museums, on the other hand, do not have an equivalent data source available. Recent solutions have incorporated advanced technologies such as algorithms that rely on social filtering, which builds recommendations from the nearest identified similar user. Our paper proposes a different approach, and involves providing dynamic recommendations that deploy social filtering as well as content-based filtering using term frequency-inverse document frequency. The main challenge is to overcome a cold start, whereby no information is available on new users entering the system, and thus there is no strong background information for generating the recommendation. In these cases, our solution deploys statistical methods to create a recommendation, which can then be used to gather data for future iterations. We are currently running a pilot test at Chao Samphraya national museum and have received positive feedback to date on the implementation.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4491-4501
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• 2016

Verruco-papillary lesions (VPLs) of the oral cavity described in the literature involve a spectrum of conditions including squamous papilloma, verruca vulgaris, focal epithelial hyperplasia, condyloma, proliferative verrucous leukoplakia and verrucous carcinoma. A majority of the VPLs are slow growing, benign in nature and have a viral aetiology. Virus associated benign mucosal outgrowths are not too difficult to diagnose either clinically or by microscopy. Apart from virus-associated lesions, VPLs harboring malignant potential or behaviour such as verrucous carcinoma, proliferative verrucous leukoplakia, oral verrucous hyperplasia (OVH), oral papillary squamous cell carcinoma (PSCC) and oral conventional squamous cell carcinoma with papillary features (CSCC) need to be further clarified for better understanding of their predictable biologic behavior and appropriate treatment. Current understanding of potentially malignant VPLs is perplexing and is primarily attributed to the use of confusing and unsatisfactory terminology. In particular, the condition referred to as oral verrucous hyperplasia (OVH) poses a major diagnostic challenge. OVH represents a histopathological entity whose clinical features are not well recognised and is usually clinically indistinguishable from a verrucous carcinoma and a PSCC or a CSCC. A consensus report published by an expert working group from South Asia as an outcome of the 'First Asian Regional Meeting on the Terminology and Criteria for Verruco-papillary Lesions of the Oral Cavity' held in Kuala Lumpur, Malaysia, recognised the clinical description of these OVH as a new entity named 'Exophytic Verrucous Hyperplasia'. Previously described clinical features of OVH such as the 'blunt' or 'sharp' variants; and the 'mass' or 'plaque' variants can now collectively fall under this newly described entity. This paper discusses in detail the application of the standardized criteria guidelines of 'Exophytic Verrucous Hyperplasia' as published by the expert group which will enable clinicians and pathologists to uniformly interpret their pool of OVH cases and facilitate a better understanding of OVH malignant potential.