• The Korean Journal of Ecology
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• v.25 no.4
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• pp.205-211
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• 2002

For landscape ecological management of the isolated forestlands in Incheon city located in the western tip of South Korea, the forest vegetation of Mt. Cheolma was classified phytosciologically and mapped out its spatial distribution at a scale of 1:5,000. Characteristics of forest landscape structures were discussed in terms of the number and size of patches obtained by analy zing vegetation map. Units to manage the forest vegetation were categorized into eighteen communities, seventeen groups, and sixteen subgroups. Landscape elements were classified into five types: secondary vegetation, introduced vegetation for forestry (IVF), introduced vegetation for agriculture (IVA), and other elements. Two hundred and ninety-three forest landscape patches covers 443.3ha, of which IVF accounted for 316.8ha(71.5$\%$), the largest portion, secondary vegetation for 101.2ha(22.8$\%$), IVA for 6.2ha(1.4$\%$), and others for 19.1ha(4.3$\%$). The ratio of natural forest elements of 31.9$\%$ showed that this area was mainly comprised of artificially introduced vegetation, such as Robinia pseudoacacia plantation and Pinus rigida plantation. Forest landscape patches have a mean area of 4.5ha, a density of 66.1/100ha, and a diversity index of 0.87. It was estimated that differentiation of patches recognized in community level would be related to human interference and those in subordinate level to natural processes.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.417-423
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• 2011

Generally, in order to avoid overlap with previous research and to initiate the innovative research, researchers must analyze patent information before research can begin. In this paper, the development of grading criteria using current trends in the wind power generation will be performed by analyzing the following criteria: technology position of major countries, impact factor each countries, patent family size, patent portfolios analysis, patent applied analysis, and analysis of nationality for a patent. This patent information for the wind power generation is expected to be useful in deciding the direction of future research.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.326-329
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• 2017

Most modern computer communications and storage media support encryption technology. Many of the Ping Pong algorithms are stream ciphers that generate random numbers in the LFSR core structure. The LFSR has a structure that guarantees the maximum period of a given size, but it has a linear structure and can be predicted. Therefore, the Ping Pong algorithm has a feature of making the linearity of the LFSR into a nonlinear structure through variable clocks and functions. In this paper, we try to improve the existing linearity by replacing the linear disadvantages of LFSR with logistic maps.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1081-1094
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• 2020

With the recent development of deep learning, most computer vision-related tasks are being solved with deep learning-based network technologies such as CNN and RNN. Computer vision tasks such as object detection or object segmentation use intermediate features extracted from the same backbone such as Resnet or FPN for training and inference for object detection and segmentation. In this paper, an experiment was conducted to find out the compression efficiency and the effect of encoding on task inference performance when the features extracted in the intermediate stage of CNN are encoded. The feature map that combines the features of 256 channels into one image and the original image were encoded in HEVC to compare and analyze the inference performance for object detection and segmentation. Since the intermediate feature map encodes the five levels of feature maps (P2 to P6), the image size and resolution are increased compared to the original image. However, when the degree of compression is weakened, the use of feature maps yields similar or better inference results to the inference performance of the original image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4795-4815
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• 2020

Drone detection can be considered as a specific sort of small object detection, which has always been a challenge because of its small size and few features. For improving the detection rate of drones, we design a Deeper SSD network, which uses large-scale input image and deeper convolutional network to obtain more features that benefit small object classification. At the same time, in order to improve object classification performance, we implemented the up-sampling modules to increase the number of features for the low-level feature map. In addition, in order to improve object location performance, we adopted the down-sampling modules so that the context information can be used by the high-level feature map directly. Our proposed Deeper SSD and its variants are successfully applied to the self-designed drone datasets. Our experiments demonstrate the effectiveness of the Deeper SSD and its variants, which are useful to small drone's detection and recognition. These proposed methods can also detect small and large objects simultaneously.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.1
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• pp.39-46
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• 2022

This study compared the effects of cocopeat and perlite growth media on the storability and quality of sweet pepper fruit stored using modified atmosphere packages (MAP) and carton boxes. The fruits were stored at 8℃ for 35 and 30 days, respectively. Perlite-grown fruits had a significantly lower size at harvest due to the medium's inability to hold plenty of water during the growing stage. Contrary to what is expected for small fruits, the result shows box-stored perlite-grown fruits to have lower weight loss and a longer shelf life than cocopeat-grown fruits, while MAP fruits have indifference. Perlite fruits also had a higher quality in terms of dry matter, soluble solids, and vitamin C, while box-stored fruits had a better visual quality. As expected, respiration and ethylene production rates were high, and fruits had similar after-storage firmness values. Based on the findings, perlite-grown sweet pepper fruits may have a better quality and give preference in a box storage condition.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.337-342
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• 2023

Since the electric vehicle uses an electric motor, problems have arisen as the driver hears the inherent noise of the motor or external noise, which was not a problem in the past, due to the overall lower noise environment than when using an internal combustion engine. Therefore, the purpose of this paper is to reduce the noise and vibration of electric motors for electric vehicles, and recently, to increase the speed of high-power, high-efficiency electric motors in a small size, and to develop low-noise motors, IPM motors are applied to produce 35KW electric motors for electric vehicles. A motor for low noise was designed and implemented. N-T Curve and efficiency map were confirmed as the final result of developing a 35KW low-noise motor for electric vehicles by applying the IPM motor applied in this paper. Based on 3500 rpm, Max Torque [Nm]: 121.15, Max Power [KW]: 44.04, and Max Efficiency [%]: 97.65, showing high efficiency.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.1-11
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• 2023

In this paper, instead of using recurrent neural network, we compare a classification performance of time series imaging algorithms using convolution neural network. There are traditional algorithms that imaging time series data (e.g. GAF(Gramian Angular Field), MTF(Markov Transition Field), RP(Recurrence Plot)) in TSC(Time Series Classification) community. Furthermore, we compare STFT(Short Time Fourier Transform) algorithm that can acquire spectrogram that visualize feature of voice data. We experiment CNN's performance by adjusting hyper parameters of imaging algorithms. When evaluate with GunPoint dataset in UCR archive, STFT(Short-Time Fourier transform) has higher accuracy than other algorithms. GAF has 98~99% accuracy either, but there is a disadvantage that size of image is massive.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2822-2843
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• 2023

All aspects of human life have become increasingly dependent on data in the last few decades. The development of several applications causes an enormous issue on data volume in current years. This information must be safeguarded and kept in safe locations. Massive volumes of data have been safely stored with cloud computing. This technology is developing rapidly because of its immense potentials. As a result, protecting data and the procedures to be handled from attackers has become a top priority in order to maintain its integrity, confidentiality, protection, and privacy. Therefore, it is important to implement the appropriate security measures in order to prevent security breaches and vulnerabilities. An improved version of Modular Encryption Standard (IMES) based on layered modelling of safety mechanisms is the major focus of this paper's research work. Key generation in IMES is done using a logistic map, which estimates the values of the input data. The performance analysis demonstrates that proposed work performs better than commonly used algorithms against cloud security in terms of higher performance and additional qualitative security features. The results prove that the proposed IMES has 0.015s of processing time, where existing models have 0.017s to 0.022s of processing time for a file size of 256KB.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.415-424
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• 2009

As one of the unsupervised learning neural network methods, self-organizing maps(SOM) are applied to various fields. It reduces the dimension of multidimensional data by representing observations on the low dimensional manifold. On the other hand, the minimal spanning tree(MST) of a graph that achieves the most economic subset of edges connecting all components by a single open loop. In this study, we apply the MST technique to SOM with subnodes. We propose SOM's with embedded MST and a distance measure for optimum choice of the size and shape of the map. We demonstrate the method with Fisher's Iris data and a real gene expression data. Simulated data sets are also analyzed to check the validity of the proposed method.