• Journal of the Microelectronics and Packaging Society
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• v.19 no.2
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• pp.7-15
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• 2012

Semiconductor packages are increasingly moving toward miniaturization, lighter and multi-functions for mobile application, which requires highly integrated multi-stack package. To meet the industrial demand, the package and silicon chip become thinner, and ultra-thin packages will show serious reliability problems such as warpage, crack and other failures. These problems are mainly caused by the mismatch of various package materials and geometric dimensions. In this study we perform the numerical analysis of the warpage deformation and thermal stress of 4-layer stacked FBGA package after EMC molding and reflow process, respectively. After EMC molding and reflow process, the package exhibits the different warpage characteristics due to the temperature-dependent material properties. Key material properties which affect the warpage of package are investigated such as the elastic moduli and CTEs of EMC and PCB. It is found that CTE of EMC material is the dominant factor which controls the warpage. The results of RSM optimization of the material properties demonstrate that warpage can be reduced by $28{\mu}m$. As the silicon die becomes thinner, the maximum stress of each die is increased. In particular, the stress of the top die is substantially increased at the outer edge of the die. This stress concentration will lead to the failure of the package. Therefore, proper selection of package material and structural design are essential for the ultra-thin die packages.

• Journal of Life Science
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• v.23 no.2
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• pp.290-298
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• 2013

The genus Mycobacterium includes crucial animal and human pathogens such as Mycobacterium tuberculosis, Mycobacterium leprae, and Mycobacterium bovis. Although it is important to understand the genetic basis for their virulence and persistence in host, genetic analysis in mycobacteria was hampered by a lack of sufficient genetic tools. Therefore, many functional vectors as molecular genetic tools have been designed for understanding mycobacterial biology, and the application of these tools to mycobacteria has accelerated the study of mechanisms involved in virulence and gene expression. To overcome the pre-existing problems in genetic manipulation of mycobacteria, this paper reports new vector systems as effective genetic tools in Mycobacterium smegmatis. Three vectors were developed; pKOTs is a suicide vector for mutagenesis containing a temperature-sensitive replication origin (TSRO) and the sacB gene encoding levansucrase as a counterselectable marker. pMV306lacZ is an integrative lacZ transcriptional fusion vector that can be inserted into chromosomal DNA by site-specific recombination. pTnMod-OKmTs is a minitransposon vector harboring the TSRO that can be used in random mutagenesis. It was demonstrated in this study that these vectors effectively worked in M. smegmatis. The vector systems reported here are expected to successfully applicable to future research of mycobacterial molecular genetics.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.637-647
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• 2019

The detection of crop stress is an important issue for the accurate assessment of yield decline. The photochemical reflectance index (PRI) was developed as a remotely sensed indicator of light use efficiency (LUE). The PRI has been tested in crop stress detection and a number of studies demonstrated the feasibility of using it. However, only few studies have focused on the use of PRI from remote sensing imagery. The monitoring of PRI using drone and satellite is made difficult by the low spectral resolution image captures. In order to estimate PRI from multispectral sensor, we propose a band fusion method using adjacent bands. The method is applied to the drone-based hyperspectral and multispectral imagery and estimated PRI explain 79% of the original PRI. And time series analyses showed that two PRI data (drone-based and SRS sensor) had very similar temporal variations. From these results, PRI from multispectral imagery using band fusion can be used as a new method for evaluation of crop stress.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.3
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• pp.83-90
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• 2019

In this paper, Mg-doped AlN epilayers for power semiconductor devices are grown by mixed-source hydride vapor phase epitaxy. Magnesium is used as p-type dopant material in the grown AlN epilayer. The AlN epilayers on the GaN-templated sapphire substrate and GaN-templated-patterned sapphire substrate (PSS), respectively, as the base substrates for device application, were selectively grown. The surface and the crystal structures of the AlN epilayers were investigated by field emission scanning electron microscopy (FE-SEM) and high-resolution-X-ray diffraction (HR-XRD). From the X-ray photoelectron spectroscopy (XPS) and Raman spectra results, the p-type AlN epilayers grown by using the mixed-source HVPE method could be applied to power devices.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.239-250
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• 2021

When considering the introduction of a new technology, it is important to accurately grasp and selectively apply the technical characteristics related to the technology in order to fully utilize the advantages of the technology. In this study, the technical characteristics of high relative importance were analyzed in order to increase the efficiency of new application of blockchain technology by companies. The technical characteristics of the blockchain identified through previous research were reclassified from the perspective of the system hierarchy, and sub-factors of the technical characteristics were derived. In addition, a questionnaire survey on the relative importance of technical characteristics was conducted for internal experts and SI experts using the Analytical Hierarchy Process (AHP) technique. As a result of the analysis, respondents evaluated data protection as the most important factor in the threat of hacking related to security. In addition, it was different that the comparison results of the importance of the technical characteristics between the experts in the company and the SI experts and the priority of the technical characteristics between the expert groups by industry. It is expected that the results of this study will be usefully utilized when using blockchain technology in enterprises in line with the upcoming changes of the 4th industrial revolution. An empirical analysis of the internal and external factors required for adoption of blockchain technology by industry and the effect of technology introduction will be a meaningful study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.177-185
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• 2022

A method of restoring the occluded area was proposed by referring to images taken with the same types of sensors on high-resolution optical satellite images through deep learning. For the natural continuity of the simulated image with the occlusion region and the surrounding image while maintaining the pixel distribution of the original image as much as possible in the patch segmentation image, CycleGAN (Cycle Generative Adversarial Network) method with ConvNeXt block applied was used to analyze three experimental regions. In addition, We compared the experimental results of a training patch size of 512*512 pixels and a 1024*1024 pixel size that was doubled. As a result of experimenting with three regions with different characteristics,the ConvNeXt CycleGAN methodology showed an improved R² value compared to the existing CycleGAN-applied image and histogram matching image. For the experiment by patch size used for training, an R² value of about 0.98 was generated for a patch of 1024*1024 pixels. Furthermore, As a result of comparing the pixel distribution for each image band, the simulation result trained with a large patch size showed a more similar histogram distribution to the original image. Therefore, by using ConvNeXt CycleGAN, which is more advanced than the image applied with the existing CycleGAN method and the histogram-matching image, it is possible to derive simulation results similar to the original image and perform a successful simulation.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.133-145
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• 2022

Compared to the continuously increasing dog population and industry size in Korea, systematic analysis of related data and research on breed classification methods are very insufficient. In this paper, an automatic breed classification method is proposed using deep learning technology for 14 major dog breeds domestically raised. To do this, dog images are collected for deep learning training and a dataset is built, and a breed classification algorithm is created by performing transfer learning based on VGG-16 and Resnet-34 as backbone networks. In order to check the transfer learning effect of the two models on dog images, we compared the use of pre-trained weights and the experiment of updating the weights. When fine tuning was performed based on VGG-16 backbone network, in the final model, the accuracy of Top 1 was about 89% and that of Top 3 was about 94%, respectively. The domestic dog breed classification method and data construction proposed in this paper have the potential to be used for various application purposes, such as classification of abandoned and lost dog breeds in animal protection centers or utilization in pet-feed industry.

• Journal of Industrial Convergence
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• v.22 no.7
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• pp.1-13
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• 2024

Among e-government services, the intelligent CCTV control platform is a screening control service that utilizes artificial intelligence to display major objects such as people, cars, etc. to control personnel when they appear on CCTV. The operation of an intelligent CCTV control platform is expected to improve the quality of life of citizens by enabling rapid response in the event of an emergency and increasing the resolution of complaints. In this study, the benefits of the intelligent CCTV control platform, a non-market good, were estimated by applying the contingent valuation method (CVM), a choice experiment technique, to estimate the average willingness to pay per household and calculate the social benefits. As a result of the analysis, the average willingness to pay per household was estimated to be KRW 6,908 per year, and the economic benefits for the country as a whole were estimated to be about KRW 150.4 billion per year. This study is of academic significance as it extends the application of CVM to the field of intelligent e-Government services. The Intelligent CCTV control platforms is being actively discussed, this study has practical implications in that the benefits were estimated in monetary value.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.167-177
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• 2022

In order to obtain satellite image products using the image transmitted to the ground station after capturing the satellite images, many image pre/post-processing steps are involved. During the pre/post-processing, when converting from level 1R images to level 1G images, geometric correction is essential. An interpolation method necessary for geometric correction is inevitably used, and the quality of the level 1G images is determined according to the accuracy of the interpolation method. Also, it is crucial to speed up the interpolation algorithm by the level processor. In this paper, we proposed a lightweight CNN-based interpolation method required for geometric correction when converting from level 1R to level 1G. The proposed method doubles the resolution of satellite images and constructs a deep learning network with a lightweight deep convolutional neural network for fast processing speed. In addition, a feature map fusion method capable of improving the image quality of multispectral (MS) bands using panchromatic (PAN) band information was proposed. The images obtained through the proposed interpolation method improved by about 0.4 dB for the PAN image and about 4.9 dB for the MS image in the quantitative peak signal-to-noise ratio (PSNR) index compared to the existing deep learning-based interpolation methods. In addition, it was confirmed that the time required to acquire an image that is twice the resolution of the 36,500×36,500 input image based on the PAN image size is improved by about 1.6 times compared to the existing deep learning-based interpolation method.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.29-42
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• 2016

Remote sensing allows acquisition of information across a large area without contacting objects, and has thus been rapidly developed by application to different areas. Thus, with the development of remote sensing, satellites are able to rapidly advance in terms of their image resolution. As a result, satellites that use remote sensing have been applied to conduct research across many areas of the world. However, while research on remote sensing is being implemented across various areas, research on data processing is presently insufficient; that is, as satellite resources are further developed, data processing continues to lag behind. Accordingly, this paper discusses plans to maximize the performance of satellite image processing by utilizing the CUDA(Compute Unified Device Architecture) Library of NVIDIA, a parallel processing technique. The discussion in this paper proceeds as follows. First, standard KOMPSAT(Korea Multi-Purpose Satellite) images of various sizes are subdivided into five types. NDVI(Normalized Difference Vegetation Index) is implemented to the subdivided images. Next, ArcMap and the two techniques, each based on CPU or GPU, are used to implement NDVI. The histograms of each image are then compared after each implementation to analyze the different processing speeds when using CPU and GPU. The results indicate that both the CPU version and GPU version images are equal with the ArcMap images, and after the histogram comparison, the NDVI code was correctly implemented. In terms of the processing speed, GPU showed 5 times faster results than CPU. Accordingly, this research shows that a parallel processing technique using CUDA Library can enhance the data processing speed of satellites images, and that this data processing benefits from multiple advanced remote sensing techniques as compared to a simple pixel computation like NDVI.