• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1716-1722
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• 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes bacteria foraging algorithm based optimal learning fuzzy-neural network (BA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by bacteria foraging algorithm. The learning algorithm of the BA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, bacteria foraging algorithm is used for tuning of membership functions of the proposed model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.75-80
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• 2017

In this paper, we describe the effect of the regularization method and the network with identity mapping on the performance of the activation functions in deep convolutional neural networks. The activation functions act as nonlinear transformation. In early convolutional neural networks, a sigmoid function was used. To overcome the problem of the existing activation functions such as gradient vanishing, various activation functions were developed such as ReLU, Leaky ReLU, parametric ReLU, and ELU. To solve the overfitting problem, regularization methods such as dropout and batch normalization were developed on the sidelines of the activation functions. Additionally, data augmentation is usually applied to deep learning to avoid overfitting. The activation functions mentioned above have different characteristics, but the new regularization method and the network with identity mapping were validated only using ReLU. Therefore, we have experimentally shown the effect of the regularization method and the network with identity mapping on the performance of the activation functions. Through this analysis, we have presented the tendency of the performance of activation functions according to regularization and identity mapping. These results will reduce the number of training trials to find the best activation function.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.176-182
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• 2021

This paper evaluates and compares the performance of the Deep Nerual Network (DNN)-based speech enhancement models according to various loss functions. We used a complex network that can consider the phase information of speech as a baseline model. As the loss function, we consider two types of basic loss functions; the Mean Squared Error (MSE) and the Scale-Invariant Source-to-Noise Ratio (SI-SNR), and two types of perceptual-based loss functions, including the Perceptual Metric for Speech Quality Evaluation (PMSQE) and the Log Mel Spectra (LMS). The performance comparison was performed through objective evaluation and listening tests with outputs obtained using various combinations of the loss functions. Test results show that when a perceptual-based loss function was combined with MSE or SI-SNR, the overall performance is improved, and the perceptual-based loss functions, even exhibiting lower objective scores showed better performance in the listening test.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.666-674
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• 2013

This paper studied about the design and implementation of tactical communication network simulator in order to obtain tactical communication network parameter, such as link capacity and routing plan, and a number of exceptional cases that may occur during actual deployment by conducting simulation of a large-scale tactical communication networks. This tactical communication network simulator provides equipment models and link models of commercial OPNET simulator for tactical communication network. In addition, 6 types of simulation scenario writings convenience functions and traffic generation models that may occur in situations of tactical communication network environment were implemented in order to enhance user friendliness. By taking advantages of SITL(System-In-The-Loop) function of OPNET, the tactical communication network simulator allows users to perform interoperability test between M&S models and actual equipment in operating simulation of tactical communication network, which is run on software. In order to confirm the functions and performance of the simulator, small-scale of tactical communication network was configured to make sure interoperability between SITL-based equipment and a large-scale tactical communication network was simulated and checked how to cope with traffic generated for each network node. As the results, we were able to confirm that the simulator is operated properly.

• Korean Journal of Social Welfare
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• v.61 no.4
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• pp.61-84
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• 2009

This study is to analyze the nature of mentoring network of single mothers with dependent children and to show the mentoring network effect on mentoring function and empowerment applying social network approach. 439 single mothers with dependent children in Busan and Gyeongsangnam-do have been surveyed about mentoring network properties. The results are 1. The mentoring relationships between single mothers have been shown in various size and relationship characters. The out-degree of Their network is low, the range is narrow, and the tie-strength is weak. 2. When the effect of mentoring network characteristics on mentoring function has been analyzed, in career functions, the range of network and the strength of relationships are represented as significant variables among the mentoring network characteristics, in psychosocial functions, the size of network and the strength of relationships are shown as significant variables, and the inverted-U-shaped relationship according to the size of network has not been revealed. In role modeling function only the size of network is represented as a significant variable. 3. The direct effect of mentoring network of single mothers with dependent children has not been much on empowerment and the career related function among mentoring functions has been revealed as the variable, which affect on empowerment. Based on these results the suggestions and implementations are mentioned in this paper.

• ETRI Journal
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• v.39 no.4
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• pp.525-534
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• 2017

A hardware-acceleration architecture that separates virtual network functions (VNFs) and network control (called HSN) is proposed to solve the mismatch between the simple flow steering requirements and strong packet processing abilities of software-defined networking (SDN) forwarding elements (FEs) in SDN/network function virtualization (NFV) architecture, while improving the efficiency of NFV infrastructure and the performance of network-intensive functions. HSN makes full use of FEs and accelerates VNFs through two mechanisms: (1) separation of traffic steering and packet processing in the FEs; (2) separation of SDN and NFV control in the FEs. Our HSN prototype, built on NetFPGA-10G, demonstrates that the processing performance can be greatly improved with only a small modification of the traditional SDN/NFV architecture.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.31-38
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• 2023

In the current Internet system, there are many problems using anonymity of the network communication such as personal information leaks and crimes using the Internet system. This is why TCP/IP protocol used in Internet system does not have the user identification information on the communication data, and it is difficult to supervise the user performing the above acts immediately. As a study for solving the above problem, there is the study of Policy Based Network Management (PBNM). This is the scheme for managing a whole Local Area Network (LAN) through communication control for every user. In this PBNM, two types of schemes exist. As one scheme, we have studied theoretically about the Destination Addressing Control System (DACS) Scheme with affinity with existing internet. By applying this DACS Scheme to Internet system management, we will realize the policy-based Internet system management. In this paper, required functions in the PBNM Scheme for multiple domains as cyber physical system that utilizes data science and AI is examined.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.737-744
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• 2010

A Social Network Service(SNS) is the best attracting internet business model and serviced in the several countries. The Facebook is the most popular SNS in a foreign country and the Cyworld is most popular one in Korea. In this paper, after investing and analyzing the existing Social Network Services, I present a new OpenU Social Network Service based on Web 2.0 concepts. This is a next generation internet platform which can be communicated with real-time chatting and share d data and talked during seeing data by collaboration functions OpenU's main characteristics and functions by screen design and implementations are explained. And also OpenU's excellence by comparing with other SNSs system is presented.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.21-25
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• 1999

Planning support systems(PSS) add more advanced spatial analysis functions than Geographic information systems(GIS) and intertemporal functions to the functions of spatial decision support systems(SDSS). This paper reports the continuing development of a PSS providing a framework that facilitates urban planners and civil engineers in conducting coherent deliberations about planning, design and operation & maintenance(O&M) of water-distribution networks for urban growth management. The PSS using dynamic optimization model, modeling-to-generate-alternatives, value engineering(VE) and life-cycle cost(LCC) can generate network alternatives in consideration of initial cost and O&H cost. Users can define alternatives by the direct manipulation of networks or by the manipulation of parameters in the models. The water-distribution network analysis model evaluates the performance of the user-defined alternatives. The PSS can be extended to include the functions of generating sewer network alternatives, combining water-distribution and sewer networks, eventually the function of planning, design and O&H of housing sites. Capacity expansion by the dynamic water-distribution network optimization model using MINLP includes three advantages over capacity expansion using optimal control theory(Kim and Hopkins 1996): 1) finds expansion alternatives including future capacity expansion times, sizes, locations, and pipe types of a water-distribution network provided, 2) has the capabilities to do the capacity expansion of each link spatially and intertemporally, and 3) requires less interaction between models. The modeling using MINLP is limited in addressing the relationship between cost, price, and demand, which the optimal control approach can consider. Strictly speaking, the construction and O&M costs of water-distribution networks influence the price charged for the served water, which in turn influence the. This limitation can be justified in rather small area because price per unit water in the area must be same as that of neighboring area, i.e., the price is determined administratively. Planners and engineers can put emphasis on capacity expansion without consideration of the relationship between cost, price, and demand.