• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.85-96
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• 2017

In this paper, a 2~18 GHz wideband 6-port network is designed and fabricated to extend the measurement frequency bandwidth of noise parameter measurement method using 6-port network. In order to design a broadband 6-port network, a wilkinson power divider and a directional coupler with wideband characteristics are designed. The wilkinson power divider is designed as a three-section structure to achieve wideband characteristics. The direction coupler is designed as a three-section structure and slot-coupled structure using multi-layer substrate to obtain wideband characteristics. A wideband 6-port network is designed and fabricated combining the designed power divider and coupler. The measured results of the fabricated 6-port network for the 2~18 GHz band show characteristics applicable to the noise parameter measurement method.

• KNOM Review
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• v.23 no.2
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• pp.1-10
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• 2020

Network Function Virtualization (NFV) is a key technology of 5G networks that has the advantage of enabling building and operating networks flexibly. However, NFV can complicate network management because it creates numerous virtual resources that should be managed. In NFV environments, service function chaining (SFC) composed of virtual network functions (VNFs) is widely used to apply a series of network functions to traffic. Therefore, it is required to dynamically allocate the right amount of computing resources or instances to SFC for meeting service requirements. In this paper, we propose Deep Q-Networks (DQN)-based auto-scaling to operate the appropriate number of VNF instances in SFC. The proposed approach not only resizes the number of VNF instances in SFC composed of multi-tier architecture but also selects a tier to be scaled in response to dynamic traffic forwarding through SFC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.253-258
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• 2010

The causal network represents the knowledge related to the dependency relationship between all attributes. If the causal network is available, the dependency relationship can be employed to estimate the missing values for improving the estimation performance. However, the previous method had a limitation in that it did not consider the bidirectional characteristic of the causal network. The proposed method considers the bidirectional characteristic by applying prior and posterior conditions, so that it outperforms the previous method.

• Korean Management Science Review
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• v.9 no.1
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• pp.17-30
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• 1992

This paper is organized as follows. Section 2 illustrates several applications of neural networks. Section 3 presents the theoretical aspects of the major neural network paradigms as well as the structure of the back -propagation network used in the study. Section 4 describes the experiment including data analysis, modeling, and the performance criteria followed by the detailed discussion of the experimental results. Future research avenues including advantages and limitations of neural network are presented in the last section.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.183-186
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• 2003

Customer profitability recognition is easier with CRM enabling technologies and the strategy of firing unprofitable customers prevails in the market. However, in the digital and Internet age, network externality is becoming more important. Therefore, the concern over firing unprofitable customers has increased. Our research is intended to develop strategic guidance for customer selection when firms implement CRM in the market with network externality.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.354-357
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• 2001

Optical transport has been sucessfully developed as a fast information transfer since 1970s, and a WDM system, based on the wavelength division multiplexing technique, was implemented to the backbone network. The WDM technique is able to improve its data traffic by utilizing its optical fiber efficiently, and is suitable for an easy network operation and management. Therefore, trend for DWDM, which is known to be one of DWM system being currently used, and the direction for optical network development will be investigated in this study.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.1-19
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• 1994

A generalized network problem is a special class of linear programming problem whose coefficient matrix contains at most two nonzero elements per column. A generalized network problem with 0-1 flow restrictions is called an integer generalized network(IGN) problem. In this paper, we presented a branch and bound algorithm for the IGN that uses network relaxation. To improve the procedure, we develop various strategies, each of which employs different node selection criterion and/or branching variable selection criterion. We test these solution strategies and compare their efficiencies with LINDO on 70 randomly generated problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.239-244
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• 1998

The environment of the access network service market is characterized by uncertain demand and various competing alternative technologies. In Korea, despite the introduction of competition, dominant Public Network Operator(PNO) still leads the market. Therefore, the decision of PNO has a great impact on the access network evolution. In this paper, we propose an model which aims to reduce risks and both investment and operating costs, to cope with the uncertain demand and technology evolution. We expect this model to provide a tool analyze risks and evaluate various strategies on the network evolution.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.1
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• pp.117-133
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• 1990

This paper is concerned with determining a minisum location with jockeying for a server on a probabilistic network in which each customer type enters the network system permitting with jockeying through a specified node and a nonpreemptive service policy is in effect. An algorithm to locate a single Fixed Priority Queue Median with Jockeying (FPQMJ) on acyclic networks is developed by using the Generalized Benders' Decomposition technique. The results are then extended to a general network.