• Journal of Korea Trade
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• v.26 no.6
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• pp.83-95
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• 2022

Purpose - With the recent spread of COVID-19, U.S. consumers' consumption pattern is changing towards purchasing large-capacity products, as they stay at home longer. Thus, the current research investigates the effects of box shape and component diversity for large-sized products on product evaluation in logistic business. Moreover, this research examines that information-processing fluency mediates the moderating effects of box shape and product components on target evaluations to confirm psychological mechanism for generating this effect. Design/methodology - In order to examine the hypotheses, the current research conducts two online experiments. The 184 participants (Study 1), and 205 participants (Study 2) of U.S. nationality were recruited through Amazon Mechanical Turk. This research analyzes the data by using SPSS 25 and PROCESS macro 4.0. Findings - Study 1 demonstrates that when the height of a box is greater than its width, products with single components promote positive target evaluations, while when the width of box is greater than its height, products with a variety of components lead to positive target evaluations. Study 2 shows that the same results are replicated in other product categories and with different box shape ratios. Moreover, Study 2 also finds that the ease of information processing mediates the interaction effects of box shape and component diversity on U.S. consumers' target evaluations. Originality/value - The current research has originality in that it investigates the effect of box shape and product composition diversity on U.S. consumer product evaluation from the perspective of information-processing theory Moreover, this research has practical implications for global traders who prepare for entering the U.S. market.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.439-441
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• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.595-598
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• 2020

IoU (Intersection over Union) is the most commonly used index in target detection. The core requirement of target detection is what is in the image and where. Based on these two problems, classification training and positional regression training are needed. However, in the process of position regression, the most commonly used method is to obtain the IoU of the predicted bounding box and ground-truth bounding box. Calculating bounding box regression losses should take into account three important geometric measures, namely the overlap area, the distance, and the aspect ratio. Although GIoU (Generalized Intersection over Union) improves the calculation function of image overlap degree, it still can't represent the distance and aspect ratio of the graph well. As a result of technological progress, Bounding-Box is no longer represented by coordinates x,y,w and h of four positions. Therefore, the IoU can be further optimized with the center point and aspect ratio of Bounding-Box.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.1 s.49
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• pp.13-16
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• 2005

For the high-throughput-screening system (HTS) of depigmenting agents using a protein chip, effects of oligonucleotide-inhibitor sequence on the binding of Mitf protein to E box of MC1R was investigated. The sequence of oligonucletide-inhibitor affected the binding of the target DNA to Mitf, depending on the location of the sequence variation in the inhibitor nucleotide. The oligonucletide-inhibitor that changed the CATGTG sequence didn't show enough inhibition of the target DNA to Mitf, whereas significant inhibition was observed when the sequence outside the CATGTG was changed. This result indicated that CATCTG is crucial sequence for the binding of Mitf to I-box which initiates the transcription of pigmenting genes.

• Progress in Medical Physics
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• v.14 no.3
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• pp.167-174
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• 2003

In the radiation treatment planning (RTP) process, especially for stereotactic radiosurgery (SRS), knowing the exact volume and shape and the precise position of a lesion is very important. Sometimes X-ray projection images, such as angiograms, become the best choice for lesion identification. However, while the exact target position can be acquired by bi-projection images, 3D target reconstruction from bi-projection images is considered to be impossible. The aim of this study was to reconstruct the 3D target volume from multiple projection images. It was assumed that we knew the exact target position in advance, and all processes were performed in Target Coordinates, where the origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. The Reconstruction Box was made up of voxels of 3D matrices. Projection images were transformed into 3D in this virtual box using a geometric back-projection method. The resolution and the accuracy of the reconstructed target volume were dependent on the target size. An algorithm was applied to an ellipsoid model and a horseshoe-shaped model. Projection images were created geometrically using C program language, and reconstruction was also performed using C program language and Matlab ver. 6(The Mathwork Inc., USA). For the ellipsoid model, the reconstructed volume was slightly overestimated, but the target shape and position proved to be correct. For the horseshoe-shaped model, reconstructed volume was somewhat different from the original target model, but there was a considerable improvement in determining the target volume.

• BMB Reports
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• v.39 no.6
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• pp.709-716
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• 2006

Mammalian polo-like kinase 1 (Plk1) acts at various stages in early and late mitosis. Plk1 localizes at the centrosome and maintains this position through mitosis. Thereafter Plk1 moves to the kinetochore and midbody region, important sites during chromosome separation and cytokinesis. The catalytic domain of Plk1 is in the N-terminus region, whereas the non-catalytic region in the C-terminus of Plk1 has a conserved motif, named the Polobox. This motif is critical for Plk localization. EGFP proteins fused with the N-terminus and C-terminus of Plk1 localize in the nucleus and centrosomes, respectively. The core sequences of the polo-box (50 amino acids) also localize in Plk1 target organelles. To screen for domain-specific target proteins of Plk1, we constructed an N-terminal domain and a tandem repeat polo-box motif, and used them as templates in a yeast two-hybrid screen. The HeLa cell cDNA library indicated several proteins including the centrosome/kinetochore components or regulators, to be characterized as positive clones. Through in vitro protein binding analyses, we confirmed an interaction between these proteins and Plk1. The data reported from this study indicate that the N- and C- termini of Plk1 may function through recruitment and/or activation of domain-specific target proteins in dividing cells. Additionally, tandem repeats of the conserved core motif of the polo-box are sufficient for targeting and may be useful as a centrosome/kinetochore-specific targeting peptide.

• Radiation Oncology Journal
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• v.31 no.4
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• pp.252-259
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• 2013

Purpose: To report the results of dosimetric comparison between intensity-modulated radiotherapy (IMRT) using Tomotherapy and four-box field conformal radiotherapy (CRT) for pelvic irradiation of locally advanced rectal cancer. Materials and Methods: Twelve patients with locally advanced rectal cancer who received a short course preoperative chemoradiotherapy (25 Gy in 5 fractions) on the pelvis using Tomotherapy, between July 2010 and December 2010, were selected. Using their simulation computed tomography scans, Tomotherapy and four-box field CRT plans with the same dose schedule were evaluated, and dosimetric parameters of the two plans were compared. For the comparison of target coverage, we analyzed the mean dose, $V_{nGy}$, $D_{min}$, $D_{max}$, radical dose homogeneity index (rDHI), and radiation conformity index (RCI). For the comparison of organs at risk (OAR), we analyzed the mean dose. Results: Tomotherapy showed a significantly higher mean target dose than four-box field CRT (p = 0.001). But, $V_{26.25Gy}$ and $V_{27.5Gy}$ were not significantly different between the two modalities. Tomotherapy showed higher $D_{max}$ and lower $D_{min}$. The Tomotherapy plan had a lower rDHI than four-box field CRT (p = 0.000). Tomotherapy showed better RCI than four-box field CRT (p = 0.007). For OAR, the mean irradiated dose was significantly lower in Tomotherapy than four-box field CRT. Conclusion: In locally advanced rectal cancer, Tomotherapy delivers a higher conformal radiation dose to the target and reduces the irradiated dose to OAR than four-box field CRT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2328-2344
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• 2022

2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.189-195
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• 2004

The purpose of this study was to establish the accuracy of the industral photogrammetry system constructed with INCA2 metric camera and V-STARS system on steel box girder measurement under industrial measurement condition. The objective of the measurement was to determine the distances of plane to plane or plane to libs, precise positions of the bolt holes and angles of the plane to plane on the steel box girder using coded targets, tape targets, edge targets and target adapters. The measurement undertaken has shown that industrial photogrammetry method were a very accurate and more importantly were produced quietly to measure the steel box girder.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.761-767
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• 2009

The detection of target echoes in a sonar image is usually difficult since reverberation is originated by the returns reflected around the boundary and volumes. Under the scenario of the target presence around the reverberation, the detection performance of existing algorithms is degraded. Since they have a similar statistical features. But proposed detector gives improvement existing algorithms Under this scenario. In this paper, 4 segmentation contrast box algorithm using maximum contrast value is proposed based on statistical segmentation, which gives better detection performance in the sense of reducing false alarms. The simulations validate the effectiveness of the proposed algorithm.