• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.1-13
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• 2006

In this paper, we introduce a novel key management scheme that is based on the key pre-distribution but provides the key re-distribution method, in order to manage keys for message encryption and authentication of lower-layer sensor nodes on hierarchical mobile sensor networks. The characteristics of our key management are as follows: First, the role of key management is distributed to aggregator nodes as well as a sink node, to overcome the weakness of centralized management. Second, a sink node generates keys using regression model, thus it stores only the information for calculating the keys using the key information received from nodes, but does not store the relationship between a node and a key, and the keys themselves. As the disadvantage of existing key pre-distributions, they do not support the key re-distribution after the deployment of nodes, and it is hard to extend the key information in the case that sensor nodes in the network enlarge. Thirdly, our mechanism provides the resilience to node capture(${\lambda}$-security), also provided by the existing key pre-distributions, and fourth offers the key freshness through key re-distribution, key distribution to mobile nodes, and scalability to make up for the weak points in the existing key pre-distributions. Fifth, our mechanism does not fix the relationship between a node and a key, thus supports the anonymity and untraceability of mobile nodes. Lastly, we compare ours with existing mechanisms, and verify our performance through the overhead analysis of communication, computation, and memory.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.2
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• pp.23-36
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• 2005

The main obstacle hindering the wide deployment of identity-based cryptosystem is that the entity responsible for creating the private key has too much power. As a result, private keys are no longer private. One obvious solution to this problem is to apply the threshold technique. However, this increases the authentication computation, and communication cost during the key issuing phase. In this paper, we propose a new effi ient model for issuing multiple private keys in identity-based encryption schemes based on the Weil pairing that also alleviates the key escrow problem. In our system, the private key of a user is divided into two components, KGK (Key Description Key) and KUD(Key Usage Desscriptor), which are issued separately by different parties. The KGK is issued in a threshold manner by KIC (Key Issuing Center), whereas the KW is issued by a single authority called KUM (Key Usage Manager). Changing KW results in a different private key. As a result, a user can efficiently obtain a new private key by interacting with KUM. We can also adapt Gentry's time-slot based private key revocation approach to our scheme more efficiently than others. We also show the security of the system and its efficiency by analyzing the existing systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.115-131
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• 2022

Carbon dioxide (CO₂) emissions from the transportation sector in South Korea accounts for 16.5% of all CO₂ emissions, and road transportation accounts for 96.5% of this sector's emissions in South Korea. Hence, constant research is being carried out on methods to reduce CO₂ emissions from this sector. With the emerging use of smart crossings, attempts to monitor individual vehicles are increasing. Moreover, the potential commercial deployment of autonomous vehicles increases the possibility of obtaining individual vehicle data. As such, CO₂ emission research was conducted at five signalized intersections in the Gangnam District, Seoul, using data such as vehicle type, speed, acceleration, etc., obtained from image detectors located at each intersection. The collected data were then applied to the MOtor Vehicle Emission Simulator (MOVES)-Matrix model-which was developed to obtain second-by-second vehicle activity data and analyze daily CO₂ emissions from the studied intersections. After analyzing two large and three small intersections, the results indicated that 3.1 metric tons of CO₂ were emitted per day at each intersection. This study reveals a new possibility of analyzing CO₂ emissions using actual individual vehicle data using an improved analysis model. This study also emphasizes the importance of more accurate CO₂ emission analyses.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.997-1008
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• 2023

Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

• Cartoon and Animation Studies
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• s.40
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• pp.55-81
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• 2015

Animation as a public visuals media have been expanding increasingly its social and cultural influences beyond the ages and nations on the basis of global consumption. However, animation increases the negative impact in modern popular culture, and in regard to this, 'the recovery of ethics' should be considered in a reflexive and educational perspectives for the social role of animation. Thus, the research addresses the animation films of Brigham Young University students which contain a ethical values and receive attention by New York Times, etc. as a successful educational model. To do this, firstly, literature has reviewed by focusing on the negative impact of animation, 1) violence, 2) excessive sensationalism, 3) confusion of cultural identity, 4) gender discrimination, and 5) distorted view of history. Secondly, the education system of animation course at Brigham Young University will be analysed. Thirdly, based on this, the case study will be conducted by focusing on the 13 animation films of students to reveal the characteristics of the way of film direction. Through this research, firstly, most of animation films are comic genre, consisting of children and animal characters, family-friendly and lyrical story style and deployment of coincidental and allegoric incident. Thirdly, the religious spirit and multidisciplinary methods of education in Brigham Young University has influenced to the ethical expression and technical perfection in animation filmmaking. In the light of this, the research and suggests the new paradigm is for the practical disciplines of animation in the restoration of the ethical perspective and explores how the animation production adopts the moral significance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1040-1047
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• 2015

This study is investigated for M2M Communication Network Standard based on 3GPP. The environment of M2M communication, we can predict the new mobile service that gathering, handling, controlling, transferring of the data for Intelligence, so that we can consider new direction for a lot of subject of study development issue. This study is shown three types of M2M network structure and four types of use cases on 3GPP International Standard. In Addition, we can introduce the future M2M communication network model, it can be propagate the industry and academic cooperation with 3GPP standards. The suggestion develops multiple applications and multiple devices for industry and academic. With the deployment of network provider, this environment support our current communication market that the standard devices of M2M network and service requirement. We are suggest this study for grasp the initial market with the intellectual property right (IPR) based on International Standards. In the future, we wish the success that grap the initial market or initial academic study with helpful issue.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.421-426
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• 2010

Due to the ease of deployment and the extended coverage, wireless mesh networks (WMNs) are gaining popularity and research focus. For example, the routing protocols that enhance the throughput on the WMNs and the link quality measurement schemes are among the popular research topics. However, most of these works assume that the locations of the mesh routers are predetermined. Since the operators in an Indoor mesh network can determine the locations of the mesh routers by themselves, it is essential to the WMN performance for the mesh routers to be initially placed by considering the performance issues. In this paper, we propose a mesh router placement scheme based on genetic algorithms by considering the characteristics of WMNs such as interference and topology. There have been many related works that solve similar problems such as base station placement in cellular networks and gateway node selection in WMNs. However, none of them actually considers the interference to the mesh clients from non-associated mesh routers in determining the locations of the mesh routers. By simulations, we show that the proposed scheme improves the performance by 30-40% compared to the random selection scheme.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.6
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• pp.1-12
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• 2017

This paper is brought to asses the training effect of KS-QFD boot camp for the companies in the early growth stage. In particular, the focus of research falls on measuring transfer intension of the participants from the early stage companies older than three years old, motivating effect of applying knowledges acquired from KS-QFD training camp into their real business case. KS-QFD program is presented to help company in the early stage companies over three years old of boosting up their sales volume more than 5 times than now for the next 18 months by this training. The training program of KS-QFD is ultimately to design more practical and helpful program to real business and spread out. The research establish model by setting the learner readiness and perceived content validity by doing training design as independent variables, self-efficacy of learner as mediating variable, and transfer intension as dependant variable. Research results shows the following outcomes. First, learner readiness does not have directly effect on transfer intension under keeping statistical significance. But as the parameter of self-efficacy, it has perfect mediating effect. Second, research proves that perceived content validity have directly impact on learning transfer intension of mediating by self-efficacy partially. This research contributes on proving that learning by doing KS-QFD boot camp enable the participants to build up their self-efficacy and lead to enhance transfer intension. In more steps, the research validates that KS-QFD training camp have delivered very practical and helpful on-site knowledge to the participants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.110-119
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• 2018

Blockchain technology has been highly evaluated for its contracts (contracts for sale, real estate contracts) because of its excellent security, including integrity and non-repudiation. In a blockchain, these contract services can be developed using a technology called a smart contract, and several blockchain platforms provide a programming language for developing smart contracts. Bitcoin and Ethereum, typical blockchain platforms, provide the Bitcoin Scripts and Solidity languages. Using these programming languages, we can develop the smart contract, a digital contract that can be processed dynamically. Smart contracts are being developed in a variety of areas, but studies of designs based on a blockchain are insufficient. In this paper, we propose a meta-model and a static/dynamic design method based on Unified Modeling Language (UML) for smart contracts based on Ethereum. We propose a method for static design attributes and functions of smart contracts, and propose a technique for designing structures among contracts. Dynamic design proposes a technique for designing deployment, function calls, and synchronization among smart contracts, accounts, and blocks within a blockchain. Experiments verify the validity of the design method by applying the static/dynamic design method through real estate contracts.