• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2444-2452
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• 2022

The field-programmable gate array (FPGA) is gaining popularity in industrial automation such as nuclear power plant instrumentation and control (I&C) systems due to the benefits of having non-existence of operating system, minimum software errors, and minimum common reason failures. Separate functions can be processed individually and in parallel on the same integrated circuit using FPGAs in comparison to the conventional microprocessor-based systems used in any plant operations. The use of FPGAs offers the potential to minimize complexity and the accompanying difficulty of securing regulatory approval, as well as provide superior protection against obsolescence. Wireless sensor networks (WSNs) are a new technology for acquiring and processing plant data wirelessly in which sensor nodes are configured for real-time signal processing, data acquisition, and monitoring. ZigBee (IEEE 802.15.4) is an open worldwide standard for minimum power, low-cost machine-to-machine (M2M), and internet of things (IoT) enabled wireless network communication. It is always a challenge to follow the specific topology when different Zigbee nodes are placed in a large network such as a plant. The research article focuses on the hardware chip design of different topological structures supported by ZigBee that can be used for monitoring and controlling the different operations of the plant and evaluates the performance in Vitex-5 FPGA hardware. The research work presents a strategy for configuring FPGA with ZigBee sensor nodes when communicating in a large area such as an industrial plant for real-time monitoring.

• Steel and Composite Structures
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• v.51 no.4
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• World Technopolis Review
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• v.5 no.2
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• pp.108-118
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• 2016

There are very few studies on governance structure for the collaboration between HEIs and science and technology parks until today. Major activities between science parks and HEIs are R&D activities, collaborative researches, technology transfer, space provision for BIs and Technology BIs in the science parks, provision of technical, legal and financial services for start-ups and venture firms. Governance structure for the collaboration of high education institutes with science and technology parks is the handling of complexity and management of dynamic flows of collaboration between two groups. Three models on the governance structure for the collaboration are suggested in this study. The first model is a governance structure that links R&D system such as universities, public research institutes and private research institutes with industrial production cluster such as a group of companies and industrial parks. The second model is a governance structure that has four layers of hierarchy. This hierarchical governance model is composed of four levels of organizations such as central government, three actors, one center for collaboration and many individual research performers. The third model is a governance structure that networks all the stakeholders horizontally. Under this structure, governance is conducted by the network members with no separate and unique governance entity.

• Korean Journal of Child Studies
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• v.31 no.2
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• pp.277-290
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• 2010

This study reviewed elementary school teachers' opinions on the integrated curriculum in terms of the 2007 curriculum draft revision, as well as surveying their requests in regards to the 2009 curriculum draft revision. This study was conducted by means of questionnaires with 183 elementary school teachers. Most agreed that a theme-based-integrated curriculum was better than studying separate subjects, but most also argued that it takes considerable time reorganize and implement the integrated curriculum. Successful implementation also requires further teachers' training and their cooperation. The theme-based texts have already been in use from 2009 for first and second grades. Teachers prefer training courses which focus on the integration of the subjects, understanding the nature of each subject and sharing ideas and tips. Such training can assist in identifying the gaps between the curriculum plans and real classroom applications. Furthermore it can present clear guidelines to help ensure that the curriculum is organized effectively and well managed. Networks of specialized personnel or programs were also found to be very good resources both in and out of school.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4B
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• pp.224-231
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• 2008

EPONs are a low cost, high speed solution to the bottleneck problem of broadband access networks. To support point-to-point and shared LAN emulation, EPONs use the multi-point control protocol (MPCP), which uses logical link identification (LLID) for frame tagging and filtering between the OLT and ONUs. In this paper, ONU-based multicast or multiple shared LAN emulation is used for IPTV channel package delivery services. Using ONU-based VLAN services, EPONs can support separate and secure connections between providers and subscribers in a simple manner. Also, IPTV channel packages can be delivered through EPONs by implementing ONU-based VLAN and IGMP snooping mechanisms. By showing fast channel zapping time of proposed architecture, I show that EPONs is suitable for IPTV channel package delivery service.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.1
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• pp.25-32
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• 2016

This study deals with the light environments and weather conditions affecting to the night illuminance over the Korean peninsula. The experiment was executed to analyze the effects on the illuminance at separate sites(Gyeryong and Pilseung) considering the different light environments. The analysis was applied to illuminance measurement from the lightmeter, which was developed for the IYA(International Year of Astronomy) 2009, in order to observe the illuminance of areal networks. The weather observations, such as the cloud cover and visibility, were used to understand the quantitative influence of the illuminance to the selected sites. The results show that the illuminance measurements are significantly different from data of the operational illuminance prediction model which simply applies extinction effect for the illuminance. It shows that these differences are caused by the light environments and weather conditions for each site. Therefore, it can be confirmed that the night illuminance is the output of interaction with the characteristics of light for luminous sources.

• Geomechanics and Engineering
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• v.13 no.2
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• pp.237-254
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• 2017

Estimation of slope stability is a very important task in geotechnical engineering. However, its estimation using conventional and soft computing methods has several drawbacks. Use of conventional limit equilibrium methods for the evaluation of slope stability is very tedious and time consuming, while the use of soft computing approaches like Artificial Neural Networks and Fuzzy Logic are black box approaches. Multiple Regression (MR) analysis provides an alternative to conventional and soft computing methods, for the evaluation of slope stability. MR models provide a simplified equation, which can be used to calculate critical factor of safety of slopes without adopting any iterative procedure, thereby reducing the time and complexity involved in the evaluation of slope stability. In the present study, a multiple regression model has been developed and tested its accuracy in the estimation of slope stability using real field data. Here, two separate multiple regression models have been developed for dry and wet slopes. Further, the accuracy of these developed models have been compared and validated with respect to conventional limit equilibrium methods in terms of Mean Square Error (MSE) & Coefficient of determination ($R^2$). As the developed MR models here are not based on any region specific data and covers wide range of parametric variations, they can be directly applied to any real slopes.

• Convergence Security Journal
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• v.14 no.2
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• pp.25-33
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• 2014

With the development of information and communication, public institutions and enterprises utilize the business continuity using the Internet and Intranet. In this environment, public institutions and enterprises is to be introduced the number of solutions and appliances equipment to protect the risk of leakage of inside information. However, this is also the perfect external network connection is not enough to prevent leakage of information. To overcome these separate internal and external networks are needed. In this paper, we constructed the physical and logical network separation is applied to the network using the virtualization and thus the network configuration and network technical review of the various schemes were proposed for the separation.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.134-143
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• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4701-4719
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• 2015

A Mobile Ad hoc Network (MANET) consists of mobile nodes which co-operate to forward each other's packets without the presence of any centralized authority. Due to this lack of centralized monitoring authority, MANETs have become vulnerable to various kinds of routing misbehaviour. Sometimes, nodes exhibit non-cooperating behaviour for conserving their own resources and exploiting others' by relaying their traffic. A node may even drop packets of other nodes in the guise of forwarding them. This paper proposes an efficient Reputation and Collaboration technique through route-request for handling such misbehaving nodes. It lays emphasis not only on direct observation but also considers the opinion of other nodes about misbehaving nodes in the network. Unlike existing schemes which generate separate messages for spreading second-hand information in the network, nodes purvey their opinion through route-request packet. Simulation studies reveal that the proposed scheme significantly improves the network performance by efficiently handling the misbehaving nodes in the network.