• Journal of Digital Convergence
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• v.3 no.2
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• pp.23-37
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• 2005

On the situation cooperating with business partners on the supply chain, systematic decision making process is a critical issue for them. The two major issues of purchasing strategy such as selecting vendors and managing them are important part of their overall business activities. This study mainly focus on the former issue of the vendor selection. Through the empirical study, analytical hierarchy process (AHP) method was applied to select vendors among supplier vendors based on four selection criteria such as the level of quality, product on management ability, delivery, and price. The results of study showed the main criteria of vender selection was the ability of quality management. The vender selected based on AHP and the current selection method was different, but implicitly projected the dilemma situation between quality and price which occurs in decision making process of real life.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.235-240
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• 2013

Cloud systems are popular computing environment because they can provide easy access to computing resources for users as well as efficient use of resources for companies. The resources of cloud computing are heterogeneous and jobs have various characteristics. One such issue is effective job scheduling. Scheduling in the cloud system may be defined as a multiple criteria decision model. To address this issue, this paper proposes a priority-based two-step job scheduling algorithm. On the first level, jobs are classified based on preference. Resources are dedicated to a job if a deadline failure would cause severe results or critical business losses. In case of only minor discomfort or slight functional impairment, the job is scheduled using a best effort approach. On the second level, jobs are allocated to adequate resources through their priorities that are calculated by the analytic hierarchic process model. We then analyze the proposed algorithm and make a scheduling example to confirm its efficiency.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.196-203
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• 2019

We have reviewed the potential impact of blockchain technology on the music industry by analyzing the views of academia and the industry experts. The music industry had rapid changes from the physical market to the digital market in the past decades. The consumers download and stream music online and mobile during the digital dominant market. While streaming music has been recently growing at a fast rate, fair distribution of revenue to the artists continues to be an issue. Some industry experts believe that the issue of fair distribution of revenue to the artist may be resolved using blockchain technology, while some are skeptical about the application or the duration of impact. The blockchain may enhance speedier payment using smart contracts, provide additional revenue and promote the music if excellent fan support is achieved. The positive impact on the music industry may only be possible if there are detailed consideration of the industry and careful understanding of the customers.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.92-98
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• 2024

The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.402-412
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• 2017

The convergence of broadcasting and telecommunication technologies is a key issue of the ubiquitous networks. So this paper offers the convergence of integrated telecommunication networks and broadcasting system, Advanced Terrestrial Digital Multimedia Broadcasting (AT-DMB), and the interconnection of them via the Media Independent Information Server/Service (MIIS). Then, this paper proposes the fast wakeup and connection mechanism with concepts for improving QoS and energy efficiency simultaneously. In the proposed convergence network, our mechanism places the key on the minimization of both the incoming service delay destined to a turned-off interface by using the broadcasting network and the additional energy consumption. This paper further evaluates the performance of proposed mechanism through the numerical and experimental analysis and has confirmed the decrease of both service delay and energy consumption.

• ETRI Journal
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• v.30 no.5
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• pp.653-662
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• 2008

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti-collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation-2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti-collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6152-6168
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• 2017

Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy.

• Journal of Ocean Engineering and Technology
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• v.33 no.2
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• pp.178-188
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• 2019

When burying underwater cables using robots, heading control is one of the key functions for the robots to improve task efficiency. This paper addresses the heading control issue for URI-T, an ROV for underwater construction tasks, including the burial and maintenance of cables or small diameter pipelines. Through modeling and identifying the heading motion of URI-T, the dynamic characteristics and input limitation are analyzed. Based on the identification results, a PD type controller with appropriate input treatment is designed for the heading control of URI-T. The performance of the heading controller was verified in water tank experiments. The field applicability of the proposed controller was also evaluated through the sea trial of URI-T at the East Sea, with a water depth of 500 m.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.125-134
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• 2022

Recently, there are an increased the number of reports on the misuse or malicious use of an UAS. Thus, many researchers are studying on defense schemes for UAS by developing or improving C-UAS sensor technology. However, the wrong placement of sensors may lead to a defense failure since the proper placement of sensors is critical for UAS defense. In this study, a multi-object optimization model for C-UAS sensor placement in an air base is proposed. To address the issue, we define two objective functions: the intersection ratio of interested area and the minimum detection range and try to find the optimized placement of sensors that maximizes the two functions. C-UAS placement model is designed using a NSGA-II algorithm, and through experiments and analyses the possibility of its optimization is verified.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.528-529
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• 2023

Due to vast points and irregular structure, labeling full points in large-scale point clouds is highly tedious and time-consuming. To resolve this issue, we propose a novel point-based transformer network in weakly-supervised semantic segmentation, which only needs 0.1% point annotations. Our network introduces general local features, representing global factors from different neighborhoods based on their order positions. Then, we share query point weights to local features through point attention to reinforce impacts, which are essential in determining sparse point labels. Geometric encoding is introduced to balance query point impact and remind point position during training. As a result, one point in specific local areas can obtain global features from corresponding ones in other neighborhoods and reinforce from its query points. Experimental results on benchmark large-scale point clouds demonstrate our proposed network's state-of-the-art performance.