• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.423-433
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• 1996

This study was conducted to predict the drafts of various tillage tools with a model tool and a neural network. Drafts of tillage tools were measured and a time lagged recurrent neural network was developed. The neural network had a structure to predict dynamic draft, having a function of one step ahead prediction . The results showed the model tool draft had linear relations with high coefficient of determinations to the drafts of the tillage tools. Also, the drafts of tillage tools were successfully predicted by the developed neural network.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.257-265
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• 2021

Home networking and its security issues are directly related. Previous studies have shown that home-network and understanding the security of it is a problem for non-technical users. The existing network management tools or ISP adapter tools are far too technical and difficult to be understood by ordinary home-network users. Its interface is not non-technical user-directed and does not address the home user's needs in securing their network. This paper presents an interactive security monitoring tool, which emphasizes support features for home-network users. The tool combines an interactive visual appearance with a persuasive approach that supports sustainability. It is not only an easy-to-use tool for all categories of home-network users but also acts as a monitoring feature for the user to secure their home-network.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.79-85
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• 2007

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.349-352
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• 2001

In this paper, the design of WDM network using the traffic estimation modeling is implemented. Because of the lack of data of real traffic volumes, the information of statistic data is used. Using the modeling results, the WDM channels are assinged for each node, and the network is simulated using OPNET simulation tools. Here, we investigate the shortest routing scheme using OPNET simulation tools. As a result the realistic WDM network design for Korea topology is proposed.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.52-59
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• 2008

The accuracy of the machine tools is degraded because of thermal error of structure due to thermal variation. To improve the accuracy of a machine tools, measurement and prediction of thermal error is very important. The main part of thermal source is spindle due to high speed with friction. The thermal error of spindle is very important because it is over 10% in total thermals errors. In this paper, the suitable thermal error prediction technology for machine tools with open architecture controller is developed and implemented to machine tools. Two thermal error prediction technologies, neural network and multi-linear regression, are investigated in several methods. The multi-linear regression method is more effective for implementation to CNC. The developed thermal error prediction technology is implemented on the internal function of CNC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3571-3587
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• 2021

For accurately analysing and forecasting the social networks of China's political, economic and social power elites, it is necessary to develop a database that collates their information. The development of such a database involves three stages: data definition, data collection and data quality maintenance. The present study recommends distinctive solutions in overcoming the challenges that occur in existing comparable databases. We used organizational and event factors to identify the Chinese power elites to be included in the database, and used their memberships, social relations and interactions in combination with flows data collection methodologies to determine the associations between them. The system can be used to determine the optimal relationship path (i.e., the shortest path) to reach a target elite and to identify of the most important power elite in a social network (e.g., degree, closeness and eigenvector centrality) or a community (e.g., a clique or a cluster). We have used three social network analysis tools (i.e., R, UCINET and NetMiner) in order to find the important nodes in the network. We compared the results of centrality rankings of each tool. We found that all three tools are providing slightly different results of centrality. This is because different tools use different algorithms and even within the same tool there are various libraries which provide the same functionality (i.e., ggraph, igraph and sna in R that provide the different function to calculate centrality). As there are chances that the results may not be the same (i.e. centrality rankings indicating the most important nodes can be varied), we recommend a comparison test using different tools to get accurate results.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.323-327
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• 2006

During the past decades in South Korea, there have been several projects to reduce water demand and save water for paddy irrigation system by automation. This is called as intensive water management system by telemetering of paddy ponding depth and canal water level and telecontrol of water supply facilities. This study suggests a method of constructing topology-based irrigation network system using GIS tools. For the network modeling, a typical agricultural watershed included reservoirs, irrigation and drainage canals, pumping stations was selected. ArcHydro tools composed of edge, junction, waterbody and watershed were used to construct hydro-network. ArcHydro Model was then designed and the network was successfully built using the HydroID. Visualization using ArcHydro tools could display table property of each object. ArcHydro Model was linked to Agricultural Water Demamd and Supply Estimation System (AWDS) which developed by Korea Rural Community and Agriculture Corporation (KRC) to extract information of the study area. And menu of supply facilities information, demand analysis and supply analysis constructed for information acquisition and visualization of acquired informations.

• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.67-72
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• 2000

A dynamic draft model is necessary to analyze mechanics of tillage and to design optimal tillage tools. In order to deal with draft dynamics, a neural network paradigm was applied to develop dynamic draft models. For the development of the models, three kinds of tillage tools were used to measure drafts in the soil bin and a time lagged recurrent neural network was developed. The neural network had a structure to predict dynamic draft, having a function of one-step-ahead prediction. A procedure for network prediction model identification was established. The results show promising modeling of the dynamic drafts with developed neural network.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.162-173
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• 2021

The Honeypot is the mechanism that is made to learn more about the attackers like knowing about the method and pattern of attack and is also used to obtain very useful info about all intrusive activities. Honeypots usually categorized according to the interaction's level as (high, medium, low) interaction. The main purpose which is used as honey production and honey research. This paper includes a detailed study of two honeypot tools. The different honey pot findings are put in in this paper to illustrate how honey is working in a real environment and even how it reacts when undesirable interest obtain in this network, and these tools are used to improve the concept of security, protection and confidentiality within or outside the organization to avoid attacks, vulnerabilities and breaches.

• Molecules and Cells
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• v.45 no.2
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• pp.76-83
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• 2022

Neurons-on-a-Chip technology has been developed to provide diverse in vitro neuro-tools to study neuritogenesis, synaptogensis, axon guidance, and network dynamics. The two core enabling technologies are soft-lithography and microelectrode array technology. Soft lithography technology made it possible to fabricate microstamps and microfluidic channel devices with a simple replica molding method in a biological laboratory and innovatively reduced the turn-around time from assay design to chip fabrication, facilitating various experimental designs. To control nerve cell behaviors at the single cell level via chemical cues, surface biofunctionalization methods and micropatterning techniques were developed. Microelectrode chip technology, which provides a functional readout by measuring the electrophysiological signals from individual neurons, has become a popular platform to investigate neural information processing in networks. Due to these key advances, it is possible to study the relationship between the network structure and functions, and they have opened a new era of neurobiology and will become standard tools in the near future.