• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.35-46
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• 2023

A model test is performed to measure the sloshing impact pressure in the liquid tank. A preprocessing is performed to learn the model test results applied with various environmental conditions. In this study, we propose a method for generating data similar to the total pressure data using Generative Adversarial Networks. In addition, after approximating the generated result to the three parameter Weibull distribution, the difference of the three parameters was compared through the RMSE and SMAPE calculation results. As a result, the distribution of the generated data showed similar results to the total pressure data distribution.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• Journal of Advanced Navigation Technology
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• v.26 no.1
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• pp.1-8
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• 2022

Telemetry system is a system that measures and transmits status information in the aircraft to the ground. The data received from the ground is information for monitoring the state of the aircraft, and can be checked and analyzed in real time through the test program. Data processing test system for telemetry currently in operation is built to transmit data using wired communication and perform test. As smart devices become popular due to the continuous development of information and communication technology, wireless communication networks are becoming important, and technologies for improving performance are steadily being developed. In this paper, we suggests and builds data processing ground test system for telemetry using wireless communication(Wi-Fi) that can be checked through smart devices such as tablets, in order to break away from the existing method and apply future-oriented technology. Finally, the suggested test system performance was proved by testing in various environments by linking test equipment and test program.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.19-26
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• 2011

Relay-assisted multiple input multiple output (MIMO) technique has become a promising candidate for next generation broadband wireless communications. In this paper, we propose maximum ratio combining (MRC) minimum mean-square-error (MMSE) equalization for single carrier-frequency domain equalizer (SC-FDE) in amplify-and-forward (AF) relaying networks. The performance of SC-FDE system can be improved considerably by achieving both the diversity gain and the MMSE equalization gain when the signals from source-destination (S->D) and source-relay-destination (S->R->D) are combined and equalized by means of the MMSE criteria. We find the weighting coefficients of MRC combining and the tap coefficients of MMSE equalizer for SC-FDE in AF relaying networks. Simulation results show that the proposed relay-based system considerably outperforms the conventional SC-FDE system.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.1
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• pp.1-18
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• 2013

The elements that determine the success of development projects on goats and the prerequisites for ensuring this are discussed in the context of the bewildering diversity of goat genetic resources, production systems, multifunctionality, and opportunities for responding to constraints for productivity enhancement. Key determinants for the success of pro-poor projects are the imperatives of realistic project design, resolution of priorities and positive impacts to increase investments and spur agricultural growth, and appropriate policy. Throughout the developing world, there exist 97% of the total world population of 921 million goats across all agroecological zones (AEZs), including 570 breeds and 64% share of the breeds. They occupy a very important biological and socioeconomic niche in farming systems making significant multifunctional contributions especially to food, nutrition and financial security, stability of farm households, and survival of the poor in the rural areas. Definitions are given of successful and failed projects. The analyses highlighted in successful projects the value of strong participatory efforts with farmers and climate change. Climate change effects on goats are inevitable and are mediated through heat stress, type of AEZ, water availability, quantity and quality of the available feed resources and type of production system. Within the prevailing production systems, improved integrated tree crops - ruminant systems are underestimated and are an important pathway to enhance C sequestration. Key development strategies and opportunities for research and development (R and D) are enormous, and include inter alia defining a policy framework, resolution of priority constraints using systems perspectives and community-based participatory activities, application of yield-enhancing technologies, intensification, scaling up, and impacts. The priority for development concerns the rainfed areas with large concentrations of ruminants in which goats, with a capacity to cope with heat tolerance, can be the entry point for development. Networks and networking are very important for the diffusion of information and can add value to R and D. Well formulated projects with clear priority setting and participatory R and D ensure success and the realisation of food security, improved livelihoods and self-reliance in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1320-1329
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• 2022

Currently, advanced national research network groups are continuously conducting R&D for the requirement to provide SDN/NFV-based network automation and intelligence technology for R&E users. In addition, the requirement for providing large-scale data transmission with the high performance networking facility, compared to general network environments, is gradually increasing in the advanced national research networks. Accordingly, in this paper, we propose an open API-based virtual network provisioning automation platform for large data transmission researched and developed to respond to the networking requirements of the national research network and present the implementation results. The platform includes the KREONET-S VDN system that provides SDN-based network virtualization technology, and the Kubernetes system that provides container-oriented server virtualization technology, and the Globus Online, a high-performance data transmission system. In this paper, the environment configurations, the system implemetation results for the interworking between the heterogeneous systems, and the automated virtual network provisioning implementation results are presented.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.179-184
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• 2022

The accurate wing flexure model is required to improve the transfer alignment performance of guided weapon system mounted on a wing of fighter aircraft or armed helicopter. In order to solve this problem, mechanical or stochastical modeling methods have been studying, but modeling accuracy is too low to be applied to weapon systems. The deep learning techniques that have been studying recently are suitable for nonlinear. However, operating fighter aircraft for deep-learning modeling to secure a large amount of data is practically difficult. In this paper, it was used to generate amount of flexure data samples that are similar to the actual flexure data. And it was confirmed that generated data is similar to the actual data by utilizing "measures of similarity" which measures how much alike the two data objects are.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.17-26
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• 2013

ISO/IEC 29157 originally developed in the Republic of Korea and is based on commercially available PicoCast v1.0. ISO/IEC JTC1 SC6 was registered by the international standard on May 2010. A single platform for a variety of applications and media formats to support development objectives were. ISO/IEC 29157 based wireless networks, ie, Pico-net to master node periodically transmit sync signal is synchronized to the number of slave nodes have the communications structure. Pico-net also supports a variety of network topologies and direct communication between nodes(single-hop communication) and QoS is guaranteed. But Pico-net network structure has the following problems. Loss of communication problems due to mobile nodes, resulting in limitations of node mobility and wireless network operation range of conventional wireless networks operating range less than 1/4 was reduced to the problem. In this paper, a possible solution to the problems mentioned is proposed, using multi-hop communication technology and sync signal transmission technology between nodes.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.1-26
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• 2016

The period after the PhD has a huge impact on the careers of researcher from a researcher lifecycle perspective. This is a turning point which student receives guidance from professor and become an independent researcher. Furthermore, they learn to develop ideas for independent research, apply for grants and manage a project; they also form expert networks in related filed and publish papers to share their findings. This study focuses on the period between earning doctoral degree and being employed as a stable position in university. This study starts from a research questions that asks which factors of postdoctoral experience affect research output. In this study, the paper performance, especially co-authorship of paper, of postdoctoral researchers was investigated. The cumulative advantage theory and Matthew effect were employed to shed a light on this research question. The empirical work is based on the Survey & Analysis of National R&D program in Korea conducted by Korea Institute of S&T Evaluation and Planning (KISTEP). The correlations between the research output and characteristics of postdoctoral experience were verified. These results are expected to contribute as new empirical evidences on investigating knowledge transfer activities of new PhDs.