• International Journal of Precision Engineering and Manufacturing
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• v.4 no.2
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• pp.49-56
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• 2003

As semi-solid forging (SSF) is compared with conventional casting such as gravity die-casting and squeeze casting, the product without inner defects can be obtained from semi-solid forming and globular microstructure as well. Generally, SSF consists of reheating, forging, and ejecting processes. In the reheating process, the materials are heated up to the temperature between the solidus and liquidus line at which the materials exists in the form of liquid-solid mixture. The process variables such as reheating time, reheating temperature, reheating holding time, and induction heating power has large effect on the quality of the reheated billets. It is difficult to consider all the variables at the same time for predicting the quality. In this paper, Taguchi method, regression analysis and neural network were applied to analyze the relationship between processing conditions and solid fraction. A356 alloy was used for the present study, and the learning data were extracted from the reheating experiments. Results by neural network were in good agreement with those by experiment. Polynominal regression analysis was formulated using the test data from neural network. Optimum processing condition was calculated to minimize the grain size and solid fraction standard deviation or to maximize the specimen temperature average. Discussion is given about reheating process of row material and results are presented with regard to accurate process variables fur proper solid fraction, specimen temperature and grain size.

• Advances in concrete construction
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• v.3 no.2
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• pp.91-102
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• 2015

In this paper, the load-deflection analysis of the Carbon Fiber Reinforced Polymer (CFRP) strengthened Reinforced Concrete (RC) slab using Recurrent Neural Network (RNN) is investigated. Six reinforced concrete slabs having dimension $1800{\times}400{\times}120mm$ with similar steel bar of 2T10 and strengthened using different length and width of CFRP were tested and compared with similar samples without CFRP. The experimental load-deflection results were normalized and then uploaded in MATLAB software. Loading, CFRP length and width were as neurons in input layer and mid-span deflection was as neuron in output layer. The network was generated using feed-forward network and a internal nonlinear condition space model to memorize the input data while training process. From 122 load-deflection data, 111 data utilized for network generation and 11 data for the network testing. The results of model on the testing stage showed that the generated RNN predicted the load-deflection analysis of the slabs in acceptable technique with a correlation of determination of 0.99. The ratio between predicted deflection by RNN and experimental output was in the range of 0.99 to 1.11.

• Journal of the Korean Society for information Management
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• v.26 no.2
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• pp.195-210
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• 2009

This study explores knowledge structures of science and technology disciplines using a cocitation analysis of journal subject categories with the publication data of a science & technology oriented university in Korea. References cited in the articles published by the faculty of the university were analyzed to produce MDS maps and network centralities. For the whole university research domain, six clusters were created including clusters of Biology related subjects, Medicine related subjects, Chemistry plus Engineering subjects, and multidisciplinary sciences plus other subjects of multidisciplinary nature. It was found that subjects of multidisciplinary nature and Biology related subjects function as central nodes in knowledge communication network in science and technology. Same analysis procedure was applied to two natural science disciplines and another two engineering disciplines to present knowledge structures of the departmental research domains.

• Journal of the Korean Institute of Gas
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• v.5 no.2 s.14
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• pp.43-51
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• 2001

ln this study, a natural gas pipeline network model was established using STONER. First a map of natural gas pipeline network was drawn on STONER and then the length and diameter of the pipe were inputted. And as the specific gravity of gas flowing in the pipeline which is the value of natural gas was inputted. Finally in order to decide the pipeline variables and gas temperature, through the verification with observed real data, the possible error was minimized. For the verification, the pipeline variables and gas temperature were assumed and the pipeline network analysis was accomplished with real demand data. The square deviation of analysed pressure from observed pressure was calculated and the minimum case was selected for the optimum pipeline variables and gas temperature. Thus a proper natural gas pipeline network model for real network was established.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.33-47
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• 2020

In recent years, due to the demand for operating efficiency and cost reduction of industrial facilities, remote access via the Internet is expanding. the control network accelerates from network separation to network connection due to the development of IIoT (Industrial Internet of Things) technology. Transition of control network is a new opportunity, but concerns about cybersecurity are also growing. Therefore, manufacturers must reflect security compliance and standards in consideration of the Internet connection environment, and enterprises must newly recognize the connection area of the control network as a security management target. In this study, the core target of the control system security threat is defined as the network boundary, and issues regarding the security architecture configuration for the boundary and the role & responsibility of the working organization are covered. Enterprises do not integrate the design organization with the operation organization after go-live, and are not consistently reflecting security considerations from design to operation. At this point, the expansion of the control network is a big transition that calls for the establishment of a responsible organization and reinforcement of the role of the network boundary area where there is a concern about lack of management. Thus, through the organization of the facility network and the analysis of the roles between each organization, an static perspective and difference in perception were derived. In addition, standards and guidelines required for reinforcing network boundary security were studied to address essential operational standards that required the Internet connection of the control network. This study will help establish a network boundary management system that should be considered at the enterprise level in the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.279-288
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• 2017

The Material Transportation Capability Analysis Method in North Korea includes adversary's activities such as destruction of bridge which is one kind of choke points in the road network and surprise attack against resupply march unit. Also, the amount of damage on choke points in the road network and repair time depending on repair unit commitment must be reflected. In this study, a scenario encompassing plausible resupply transportation circumstances while counterattacking into NK will be established. Then, based on such scenario, a simulation model will be established and the result of simulation will be compared to the results of numeric example which has been used in the ROK Army. We demonstrate, through a certain Corps operation area, that the Scenario-based Simulation Model results predict the performance of resupply operation very well. Therefore, it makes sustainment planners and commanders do activities which is suitable for battlefield and should be used in the real situation. It is also a stochastic model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4604-4623
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• 2014

Authentication mechanisms coupled with strong encryption techniques are used for network security purposes; however, given sufficient time, well-equipped intruders are successful for compromising system security. The authentication protocols often fail when they are analysed critically. Formal approaches have emerged to analyse protocol failures. In this study, Communicating Sequential Processes (CSP) which is an abstract language designed especially for the description of communication patterns is employed. Rank functions are also used for verification and analysis which are helpful to establish that some critical information is not available to the intruder. In order to establish this, by assigning a value or rank to each critical information, it is shown that all the critical information that can be generated within the network have a particular characterizing property. This paper presents an application of rank functions approach to an authentication protocol that combines delaying the decryption process with timed authentication while keys are dynamically renewed under pseudo-secure situations. The analysis and verification of authentication properties and results are presented and discussed.

• Animal cells and systems
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• v.16 no.2
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• pp.121-126
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• 2012

In this study, a neural network (NN) modeling approach has been used to predict the mechanical and geometrical behaviors of mouse embryo cells. Two NN models have been implemented. In the first NN model dimple depth (w), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were used as inputs of the model while indentation force (f) was considered as output. In the second NN model, indentation force (f), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were considered as inputs of the model and dimple depth was predicted as the output of the model. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. Experimental data deduced by Fl$\ddot{u}$ckiger (2004) were collected to obtain training and test data for the NN. The results of these investigations show that the correlation values of the test and training data sets are between 0.9988 and 1.0000, and are in good agreement with the experimental observations.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.177-186
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• 2022

A network QoS model for the joint integrated C4I structure was proposed for the integration of network infrastructure and network operations(NetOps) for NCOE. Detailed QoS requirements process of the joint integrated C4I systems are needs in the Multi-Domain Operation Environment(MDOE). A process is proposed for identifying QoS requirements and establishing in the MDOE using JMT(Joint Mission Thread) reference architecture and solution architecture. Mission analysis identify JCOAs(Joint Critical Operational Activities) and related activities based on JMT & System architecture's OVs, and Information analysis identify QoS attributes using System architecture's SVs. Identifying QoS attributes will be registered at PPS Registry by pre-regulated process, and will be set-up by NetOps. MDOE QoS requirement Process will support efficiently MUM-T and smart defense platform users under the future uncertain battlefield circumstances.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3571-3584
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• 2024

Reactor core transient calculation is very important for the reactor safety analysis, in which the kernel is neutron kinetics calculation by simulating the variation of neutron density or thermal power over time. Compared with the point kinetics method, the time-space neutron kinetics calculation can provide accurate variation of neutron density in both space and time domain. But it consumes a lot of resources. It is necessary to develop a surrogate model that can quickly obtain the temporal and spatial variation information of neutron density or power with acceptable calculation accuracy. This paper uses the time-varying characteristics of power to construct a time function, parameterizes the time-varying characteristics which contains the information about the spatial change of power. Thereby, the amount of targets to predict in the space domain is compressed. A surrogate method using the machine learning is proposed in this paper. In the construction of a neural network, the input is processed by a convolutional layer, followed by a fully connected layer or a deconvolution layer. For the problem of time sequence disturbance, a structure combining convolutional neural network and recurrent neural network is used. It is verified in the tests of a series of 1D, 2D and 3D reactor models. The predicted values obtained using the constructed neural network models in these tests are in good agreement with the reference values, showing the powerful potential of the surrogate models.