• Journal of Technology Innovation
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• v.24 no.2
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• pp.1-20
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• 2016

This case is to analyze the structure of technology convergence with social network analysis. More specifically, the convergence structure among input technologies mediated with products is analyzed with 2-mode social network analysis. Products are identified in project's goal and coded as the Korea Standard Industrial Classification. The input technologies are coded as the National Science Technology Classification. The subjects were 401 R&D projects applied to '2012 Convergence Technology Development Project for Small and Medium Businesses' promoted by Korea Technology & Information Promotion Agency for Small and Medium Enterprises. IT sectors had the structure of a particular input technology connected to many products, BT sectors also had a few input technology connected to many products but most were connected to specific products. Therefore We have realized that each convergence area had different convergence structure. There were the difference of connectivity centrality between input technologies and input technologies mediated with products. For IT sectors, the embedded S/W were the highest in both cases. For BT sectors, functional cosmetic development and fermentation technology were the highest in input technologies but fermentation technology was not the highest in input technologies mediated with products. This case defines the convergence based on the real projects and the use for managing and planing projects. Therefore, this case was to make a tool to analyze and design technology convergence projects.

• JSTS:Journal of Semiconductor Technology and Science
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• v.3 no.4
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• pp.188-193
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• 2003

This paper describes a novel burst-mode clock and data recovery (CDR) circuit which can be used for 622Mbps burst mode applications. The CDR circuit is basically a phase locked loop (PLL) having two phase detectors (PDs), one for the reference clock and the other for the NRZ data, whose operations are controlled by an external control signal. This CDR was fabricated in a 1-poly 5-metal $0.25{\;}\mu\textrm{m}$ CMOS technology. Jitter generation, burst/continuous mode data receptions were tested. Operational frequency range is 320Mhz~720Mhz and BER is less than 1e-12 for PRBS31 at 622Mhz. For the same data sequence, the extracted clock jitter is less than 8ps rms. Power consumption of 100mW was measured without I/O circuits.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.151-165
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• 1994

Broadband network based on the Asynchronous Transfer Mode(ATM) concept are becoming the target technology for the emerging Broadband Integrated Services Digital Network(B-ISDN). Since B-ISDN is very complex and requites a great amount of investment, optimum design and performance analysis of such systems are very important. Simulation can be widely used to analyze and examine the broadband network behavior. However, for the complicated system like broadband networks it is extremely difficult and time-consuming to develop a complete model for simulation. In this paper, an object-oriented modeling approach for the broadband network simulation is presented for the effective and efficient modeling. Object-oriented approaches can provide a good structuring capability for complicated simulation models and facilitate the development of reusable and extensible simulation models. We have developed an object-oriented model which consists of object model and behavior model. In the object mode., the components of the broadband network and both constant bit rate(CBR) and variable bit rate(VBR) traffic types of call level, burst level, and cell level are modeled as object classes. In the behavior model, the dynamic features for each object class are represented using the state transition diagram. It has been shown by illustration that objectoriented modeling is an effective tool for modeling the complicated B-ISDN.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.1
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• pp.59-67
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• 2012

In this paper, we designed an inter-operation architecture of 10G G-PON(Gigabit passive optical network) network and NGN(Next generation network) architecture. And, we proposed mechanism of dynamic GEM(G-PON encapsulation mode) Port-ID allocation. This is able to solve a problem of 10G G-PON inter-operation. The mechanism of dynamic GEM Port-ID allocation has OMCI(ONT management control and interface) mapping table for IP address and port number. That architecture is able to support per flow QoS(Quality of service) as well as QoS of NGN requirement. So that can improve the resource efficiency of QoS than the existing G-PON architecture.

• 전기의세계
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• v.26 no.1
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• pp.63-70
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• 1977

This paper deals with computer analysis technique of the network having 3-terminal elements whose input and output characteristics are defined by nonuniform spacing function group on the volt-ampere space. Developing the algorithms to obtain the solutions of the network mentioned above by computer, we propose optimization technique, which can solve the normal form equations of the network defined in this paper and which involves mode analysis technique to be able to analyze the case that the function group has negative resistance characteristics.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.679-690
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• 2011

In this paper we consider a local area network (LAN) of dual mode service where one is a token bus and the other is a carrier sense multiple access with a collision detection (CSMA/CD) bus. The objective of the paper is to find the overall cell/packet dropping probability of a dual mode LAN for finite length queue M/G/1(m) traffic. Here, the offered traffic of the LAN is taken to be the equivalent carried traffic of a one-millisecond delay. The concept of a tabular solution for two-dimensional Poisson's traffic of circuit switching is adapted here to find the cell dropping probability of the dual mode packet service. Although the work is done for the traffic of similar bandwidth, it can be extended for the case of a dissimilar bandwidth of a circuit switched network.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• Journal of the Korean Professional Engineers Association
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• v.31 no.1
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• pp.9-16
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• 1998

For the flow facing high1y informationized age, there is a flow from fixed communications connecting fixed places such as offices and homes to mobile communications connecting mobile objets such as automobiles, ships and aircraft. This flow has added to diversifying communications Including data and images. While the axed mode is diversifying information media by digitalization of communications network and computers, the mobile mode has brought higher sophistication of communication modes by a higher degree of electric wave utilization. The following descriptions outlines the mobile communication which is utilizing the electric wave phenomena. In sequence the following items are described: a brief history of mobile communications, the technical object and various kinds of services, propagation of electric wave signal.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.48-54
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• 2020

In this paper, we deal with a liver fibrosis classification problem using ultrasound B-mode images. Commonly representative methods for classifying the stages of liver fibrosis include liver biopsy and diagnosis based on ultrasound images. The overall liver shape and the smoothness and roughness of speckle pattern represented in ultrasound images are used for determining the fibrosis stages. Although the ultrasound image based classification is used frequently as an alternative or complementary method of the invasive biopsy, it also has the limitations that liver fibrosis stage decision depends on the image quality and the doctor's experience. With the rapid development of deep learning algorithms, several studies using deep learning methods have been carried out for automated liver fibrosis classification and showed superior performance of high accuracy. The performance of those deep learning methods depends closely on the amount of datasets. We propose an enhanced U-net architecture to maximize the classification accuracy with limited small amount of image datasets. U-net is well known as a neural network for fast and precise segmentation of medical images. We design it newly for the purpose of classifying liver fibrosis stages. In order to assess the performance of the proposed architecture, numerical experiments are conducted on a total of 118 ultrasound B-mode images acquired from 78 patients with liver fibrosis symptoms of F0~F4 stages. The experimental results support that the performance of the proposed architecture is much better compared to the transfer learning using the pre-trained model of VGGNet.