• Horticultural Science & Technology
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• v.33 no.1
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• pp.114-123
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• 2015

Plants can respond and adapt to cold stress through regulation of gene expression in various biochemical and physiological processes. Cold stress triggers decreased rates of metabolism, modification of cell walls, and loss of membrane function. Hence, this study was conducted to construct coexpression networks for time-based expression pattern analysis of genes related to cold stress in Chinese cabbage (Brassica rapa ssp. pekinensis). B. rapa cold stress networks were constructed with 2,030 nodes, 20,235 edges, and 34 connected components. The analysis suggests that similar genes responding to cold stress may also regulate development of Chinese cabbage. Using this network model, it is surmised that cold tolerance is strongly related to activation of chitinase antifreeze proteins by WRKY transcription factors and salicylic acid signaling, and to regulation of stomatal movement and starch metabolic processes for systemic acquired resistance in Chinese cabbage. Moreover, within 48 h, cold stress triggered transition from vegetative to reproductive phase and meristematic phase transition. In this study, we demonstrated that this network model could be used to precisely predict the functions of cold resistance genes in Chinese cabbage.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.235-243
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• 2021

River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.33-45
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• 2020

This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.45-51
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• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.89-104
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• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• Journal of Life Science
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• v.30 no.1
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• pp.45-57
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• 2020

The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules' functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules'(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.918-927
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• 2004

WCDMA system is 3rd generation wireless mobile system specified by 3GPP. In WCDMA downlink, two power control schemes are operated. One is inner loop power control operated in every slot. Another is outer loop power control based on one frame time. Base station (BS) can estimate proper transmission power by these two power control schemes. However, because each MS's transmission power makes a severe effect on BS's performance, BS cannot give excessive transmission power to the specific user. 3GPP defined Power Control Dynamic Range (PCDR) to guarantee proper BS's performance. In this paper, we propose Adaptive PCDR algorithm. By APCDR algorithm, Radio Network Controller (RNC) can estimate each MS's current state using received signal to interference ratio (SIR). APCDR algorithm changes MS's maximum code channel power based on frame. By proposed scheme, each MS can reduce wireless channel effect and endure outages in cell edge. Therefore, each MS can obtain better QoS. Simulation result indicate that APCDR algorithm show more attractive output than fixed PCDR algorithm.

• Management & Information Systems Review
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• v.34 no.5
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• pp.295-312
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• 2015

Companies are recently emphasizing social capital that is formed by the network and trust among organization members to secure continuous competitive edge. Social capital induces the members' adaptation and immersion through the interactions with multidimensional factors within an organization, and contributes to increasing an organization's performance by causing cooperative behaviors as a passage of communications and participation. This study analyzed the influence of social capital and organizational support recognition formed in an organization on the turnover intention, and examined the moderating effect of organizational support recognition in the relationship between social capital and turnover intention. To achieve the purpose, this research conducted a survey on small and medium sized manufacturing companies in Busan and Gyeongnam and performed an empirical analysis using hierarchical regression analysis. According to the empirical analysis, the structural and relational dimensions of social capital had a negative (-) influence on the turnover intention. Especially, the relational dimension had a huge influence on the turnover intention, showing that it is important to form trust among an organization's members through their interactions. Second, organizational support recognition also had a negative (-) influence on the turnover intention, demonstrating that attention and complete support at an organizational dimension were needed for individual members. Third, organizational support recognition appeared to mediate the relationship between social capital and the turnover intention. The higher the organizational support recognition was, the lower the negative (-) influence of the relational dimension of social capital on the turnover intention was. Based on these results, this paper discussed the theoretical and practical implications of this research as well as future assignments.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.153-165
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• 2018

There must be a balanced development of both conglomerates and small and mid-sized companies in order to secure constant economic growth and competitive edge of South Korea. Accordingly, high expectations are being placed on win-win growth and joint overseas expansion of conglomerates and small and mid-sized companies. This study seeks efficient ways to promote joint overseas expansion of major retailers and small and mid-sized companies considering the distinctiveness of home shopping by conducting interviews about joint overseas expansion of home shopping companies and small and mid-sized consumer goods companies in South Korea. To do this, interviews were conducted with three home shopping companies and three consumer goods SMEs operating in overseas markets. The results are as follows. Home shopping companies contribute to opening up overseas markets for small and mid-sized consumer goods companies, and allows them to make use of business and marketing competencies that they lack. Home shopping companies also produce visual materials or provide language translations, and help draw up documents for customs clearance in trading. They also form market development teams and provide information about the overseas markets. However, since the actual benefits from joint overseas expansion are minor for home shopping companies, there is a need for a strategy for win-win growth of both parties in the long run. To this end, it is necessary to provide substantial benefits to encourage joint overseas expansion. Ultimately, balanced development between home shopping companies and small- and medium-sized consumer goods companies should be promoted.