• Journal of the Economic Geographical Society of Korea
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• v.24 no.3
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• pp.259-282
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• 2021

This study analyzes actor networks in regional innovation processes with a focus on actors' activities and finds the determinants of the networks, thereby aiming to provide information useful for regional innovation policy makers. To this end, the study conducted a social network analysis of the national R&D projects data and identified the activities of innovation actors. Finding out the network determinants was QAP analysis. The study suggests three main findings as follows. First, a meaningful difference exists in characteristics of innovation activity by region. Second, the network of innovation actors meaningfully differs from region to region. The centrality of the network was found to be high in universities and businesses in Seoul and Gyeonggi, and in public research institutes in Daejeon. There are regions where all the networks of innovative actors are composed of one component, while some regions are not yet established with the network. Finally, although the networks of innovation actors are influenced by the geographical proximity and the size of the R&D fund, it is notable that the previous continuous relationship forms a strong research network.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.3-14
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• 2013

In this paper, key design issues and considerations for Signal Integrity(SI) and Power Integrity(PI) of a TSV-based 3D IC are introduced. For the signal integrity and power integrity of a TSV-based 3-D IC channel, analytical modeling and analysis results of a TSV-based 3-D channel and power delivery network (PDN) are presented. In addition, various design techniques and solutions which are to improve the electrical performance of a 3-D IC are investigated.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.650-652
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• 2001

The permanent magnet in hybrid step motor is magnetized to the axial direction. Accordingly the 2D analysis method such as 2D finite element method cannot guarantee the analysis accuracy. In this paper, the characteristics of hybrid type step motor are analyzed by using 3D equivalent magnetic circuit network method(3D EMCNM). 3D EMCNM supplements magnetic equivalent circuit by numerical technique using distributive magnetic circuit parameter and 3D EMCNM is used for the accurate and efficient analysis. The validity of the analysis results is confirmed by comparing with the experimental ones.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.37-52
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• 2015

The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.

• Journal of Surface Science and Engineering
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• v.57 no.3
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• pp.214-220
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• 2024

In this study, three-dimensional (3D) networks structure using single-walled carbon nanotubes (SWCNTs) for Si-graphite composite electrode was developed and studied about effects on the electrochemical performances. To investigate the effect of SWCNTs on forming a conductive 3D network structure electrode, zero-dimensional (0D) carbon black and different SWCNTs composition electrode were compared. It was found that SWCNTs formed a conductive network between nano-Si and graphite particles over the entire area without aggregation. The formation of 3D network structure enabled to effective access for lithium ions leading to improve the c-rate performance, and provided cycle stability by alleviating the Si volume expansion from flexibility and buffer space. The results of this study are expected to be applicable to the electrode design for high-capacity lithium-ion batteries.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.15-20
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• 2015

After the US government declared 3D printing technology a next-generation manufacturing technology, there have been many practical studies conducted to expand 3D printing technology to manufacturing technologies, called AMERICA MAKES. In particular, the Keck Center, located at the University of Texas at El Paso, has studied techniques for easily combing the 3D stacking process with space mobility and expanded these techniques to simultaneous staking techniques for multiple materials. Additionally, it developed convergence manufacturing techniques, such as direct inking techniques, in order to produce a module structure that combines electronic circuits and components, such as CUBESET. However, in these studies, it is impossible to develop a unified system using traditional independent through simple sequencing connections. This is because there are many problems in the integration between the stacking modeling of 3D printers and post-machining, such as thermal deformations, the precision accuracy of 3D printers, and independently driven coordinate problems among process systems. Therefore, in this paper, the integration method is suggested, which combines these 3D printers and subsequent machining process systems through an Internet-based cloud. Additionally, the sequential integrated system of a 3D printer, an NC milling machine, machine vision, and direct inking are realized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.444-460
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• 2009

In this paper, we propose an expanded patching technique in order to reduce the server network bandwidth requirements to support true VoD services in VoD Systems. Double Patching, which is a typical multicast technique, ensures that a long patching stream delivers not only essential video data for the current client but also extra video data for future clients. Since the extra data may include useless data, it results in server network bandwidth wastage. In order to prevent a server from transmitting useless data, the proposed patching technique uses a new kind of stream called a linking stream. A linking stream is transmitted to clients that have received short patching streams, and it plays a linking role between a patching stream and a regular stream. The linking stream enables a server to avoid transmitting unnecessary data delivered by a long patching stream in Double Patching, so the server never wastes its network bandwidth. Mathematical analysis shows that the proposed technique requires less server network bandwidth to support true VoD services than Double Patching. Moreover, simulation results show that it has better average service latency and client defection rate compared with Double Patching.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1794-1806
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• 2023

This study presents a method for capturing photographs of users as input and converting them into 2D character animation sprites using a generative adversarial network-based artificial intelligence network. Traditionally, 2D character animations have been created by manually creating an entire sequence of sprite images, which incurs high development costs. To address this issue, this study proposes a technique that combines motion videos and sample 2D images. In the 2D sprite generation process that uses the proposed technique, a sequence of images is extracted from real-life images captured by the user, and these are combined with character images from within the game. Our research aims to leverage cutting-edge deep learning-based image manipulation techniques, such as the GAN-based motion transfer network (impersonator) and background noise removal (U² -Net), to generate a sequence of animation sprites from a single image. The proposed technique enables the creation of diverse animations and motions just one image. By utilizing these advancements, we focus on enhancing productivity in the game and animation industry through improved efficiency and streamlined production processes. By employing state-of-the-art techniques, our research enables the generation of 2D sprite images with various motions, offering significant potential for boosting productivity and creativity in the industry.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.17-24
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• 2014

In this paper, we propose a CMOS FM RX front-end structure with an automatic tunable input matching network and implement it using a 65nm CMOS technology. The proposed FM RX front-end is designed to change the resonance frequency of the input matching network at the low noise amplifier (LNA) according to the channel frequency selected by a phase-locked loop (PLL) for maintaining almost constant sensitivity level when an embedded antenna type with high frequency selectivity characteristic is used for FM receiver. The simulation results of implemented FM front-end show about 38dB of voltage gain, below 2.5dB of noise figure, and -15.5dBm of input referred intercept point (IIP3) respectively, while drawing only 3.5mA from 1.8V supply voltage including an LO buffer.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.170-179
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• 1993

In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.