• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.65-78
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• 2007

This paper proposes a new method of weighted template matching for machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. Template matching is vulnerable to random noises that generate ragged outlines of a pattern when it is binarized. This paper offers a method of chain code trimming in order to remove ragged outlines. The method corrects specific chain codes within the chain codes of the inner and the outer contour of a pattern. The experiment compares confusion matrices of both the template matching and the proposed weighted template matching with chain code trimming. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.31-40
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• 2012

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on Zernike Moment which is robust to rotations of iris patterns. we utilized a selection of Zernike moments for the fast and effective recognition by selecting global optimum moments and local optimum moments for optimal matching of each iris class. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• East Asian Journal of Business Economics (EAJBE)
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• v.9 no.4
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• pp.1-15
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• 2021

Purpose - In a difficult time for a firm, it seems impossible to change circumstances by a firm. Nevertheless, the firm must do whatever it can do by however it can do. Therefore, the purpose of this study is to analyze the effect of HRM practice on organizational effectiveness with the status quo of the firm as a moderator. Based on the result of this study, the managerial implication could be suggested as a contextual response to each status quo of the firm in improving and managing organizational effectiveness by HRM practice. Research design, data, and methodology - This study measured organizational effectiveness with employee satisfaction and organizational commitment. HRM practice includes two HR management areas, HR system, and HR attitude. HR system includes education & training and additional wage welfare. HR attitude includes employee stress and empowerment. As for the status quo of the firm, this study considered three construct; firm feature, strategic feature, environment change feature. This study analyzed 397 employees of 24 company data from the 7th HCCP of KRIVET. Result - Hypothesis 1 through Hypothesis 3 were partially supported. The results of this study suggest that to increase organizational effectiveness(job satisfaction and organizational commitment), employee stress and education & training participation need to be managed. And circumstance of an organization as given the Status Quo of the firm needs to be managed differently like firm size, environment change in demand, and technology. Conclusion - This study suggests best-practice implications based on the result between HRM practice and organizational effectiveness. And also suggest differentiation in management to increase the best-fit in management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.701-720
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• 2023

Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.880-889
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• 2021

Objective: This study aimed to investigate the regional amyloid burden and myocardial deformation using T1 mapping and strain values in patients with cardiac amyloidosis (CA) according to late gadolinium enhancement (LGE) patterns. Materials and Methods: Forty patients with CA were divided into 2 groups per LGE pattern, and 15 healthy subjects were enrolled. Global and regional native T1 and T2 mapping, extracellular volume (ECV), and cardiac magnetic resonance (CMR)-feature tracking strain values were compared in an intergroup and interregional manner. Results: Of the patients with CA, 32 had diffuse global LGE (group 2), and 8 had focal patchy or no LGE (group 1). Global native T1, T2, and ECV were significantly higher in groups 1 and 2 than in the control group (native T1: 1384.4 ms vs. 1466.8 ms vs. 1230.5 ms; T2: 53.8 ms vs. 54.2 ms vs. 48.9 ms; and ECV: 36.9% vs. 51.4% vs. 26.0%, respectively; all, p < 0.001). Basal ECV (53.7%) was significantly higher than the mid and apical ECVs (50.1% and 50.0%, respectively; p < 0.001) in group 2. Basal and mid peak radial strains (PRSs) and peak circumferential strains (PCSs) were significantly lower than the apical PRS and PCS, respectively (PRS, 15.6% vs. 16.7% vs. 26.9%; and PCS, -9.7% vs. -10.9% vs. -15.0%; all, p < 0.001). Basal ECV and basal strain (2-dimensional PRS) in group 2 showed a significant negative correlation (r = -0.623, p < 0.001). Group 1 showed no regional ECV differences (basal, 37.0%; mid, 35.9%; and apical, 38.3%; p = 0.184). Conclusion: Quantitative T1 mapping parameters such as native T1 and ECV may help diagnose early CA. ECV, in particular, can reflect regional differences in the amyloid deposition in patients with advanced CA, and increased basal ECV is related to decreased basal strain. Therefore, quantitative CMR parameters may help diagnose CA and determine its severity in patients with or without LGE.

• The Research Journal of the Costume Culture
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• v.20 no.6
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• pp.923-936
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• 2012

Apparel companies define their target customers to integrate consumers' needs into their product development processes. The sizing standards play a significant role in ready-to-wear garment business. Consumers' body build and sizes are different according to gender, age, and body type. The consumers' morphological feature of the one geographical area has changed with immigration, aging, and lifestyle change. In this study the way of defining body types in the standard garment sizing systems published in USA., UK, Germany, Japan, and Korea were compared. The results of this study show that most of the systems classified the body types by the index value. The chest-waist drop value was used for men's body type classification. Women's body types were defined by hip proportion. The hip-bust drop value was used for it. German and European garment sizing systems provide a wide range of men's body types. US men's garment sizes are developed for very conservative body type. US women's garment sizing system has had clearly defined women's body types. The Misses body types projected in the US garment sizing system had changed as women's waist girth got bigger compared to the past. In 2011 the US Misses sizes were divided into Curvy Misses size and Straight Misses size by the hip-waist drop value. The Curvy Misses sizes have smaller waist girth and larger hip girth than the Straight Misses sizes.

• Journal of Distribution Science
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• v.18 no.4
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• pp.27-37
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• 2020

Purpose: This exploratory research is to give managerial implication to sales personal management. This study focused on antecedents of job satisfaction and organizational commitment specially in HRD programs and system by participation and effect toward job. Research design, data and methodology: This research focuses on relationship analysis among job satisfaction, organizational commitment and HRD programs of logistics and sales personnel in Korea. HRD program consider two parts one is participation and other is effect toward job. And three HRD program is included education & training, system and self-directed Learning. This study used 7th HCCP data from KRIVET and 748 employee data is analyzed. SPSS18 is used and frequency, reliability, correlation and regression analysis are conducted. Results: Result shows that job satisfaction is positively affected by education & training participation, HRD system participation and HRD system effect toward job. Organizational commitment is positively affected by education & training participation, HRD system participation, education & training effect toward job and HRD system effect toward job. However self-directed Learning participation negatively affect organizational commitment. Lastly job satisfaction partially mediates between HRD and organizational commitment. Conclusions: Based on the results, this paper provide implication to academic, practical HRD and suggest feature research.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.5
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• pp.11-17
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• 2016

The purposes of this research are to estimate area of greenable roof and to monitor maintaining of green roofs using World-View 2 images. The contents of this research are development of World-View 2 application technologies for estimation of green roof area and development of monitoring and maintaining of green roofs using World-View 2 images. The available green roof areas in Gwangjin-gu Seoul, a case for this study, were estimated using digital maps and World-View 2 images. The available green roof area is approximately 12.17% ($2,153,700m^2$) of the total area, and the roof vegetation accounts for 0.46% ($80,660m^2$) of the total area. For verification of the extracted roof vegetation, Vworld 3D Desktop map service was applied. The study results may be used as a decision-making tool by the government and local governments in determining the feasibility of green roof projects. In addition, the project implementer may periodically monitor to see whether roof greening has maintained for efficient management of projects, and a vast amount of World-View 2 images may be regularly used before and after the projects to contribute to sharing of satellite images information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.692-710
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• 2013

Conventional interference alignment (IA) for a MIMO interference channel (IFC) requires global and perfect channel state information at transmitter (CSIT) to achieve the optimal degrees of freedom (DoF), which prohibits practical implementation. In order to alleviate the global CSIT requirement caused by the coupled relation among all of IA equations, we propose an IA scheme with a single feedback link of each receiver in a limited feedback environment for a three-user MIMO IFC. The main feature of the proposed scheme is that one of users takes out a fraction of its maximum number of data streams to decouple IA equations for three-user MIMO IFC, which results in a single link feedback structure at each receiver. While for the conventional IA each receiver has to feed back to all transmitters for transmitting the maximum number of data streams. With the assumption of a random codebook, we analyze the upper bound of the average throughput loss caused by quantized channel knowledge as a function of feedback bits. Analytic results show that the proposed scheme outperforms the conventional IA scheme in term of the feedback overhead and the sum rate as well.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.423-430
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• 2017

Recently, data analysis research has been carried out using the deep learning technique in various fields such as image interpretation and/or classification. Various types of algorithms are being developed for many applications. In this paper, we propose a precipitation prediction algorithm based on deep learning with high accuracy in order to take care of the possible severe damage caused by climate change. Since the geographical and seasonal characteristics of Korea are clearly distinct, the meteorological factors have repetitive patterns in a time series. Since the LSTM (Long Short-Term Memory) is a powerful algorithm for consecutive data, it was used to predict precipitation in this study. For the numerical test, we calculated the PWV (Precipitable Water Vapor) based on the tropospheric delay of the GNSS (Global Navigation Satellite System) signals, and then applied the deep learning technique to the precipitation prediction. The GNSS data was processed by scientific software with the troposphere model of Saastamoinen and the Niell mapping function. The RMSE (Root Mean Squared Error) of the precipitation prediction based on LSTM performs better than that of ANN (Artificial Neural Network). By adding GNSS-based PWV as a feature, the over-fitting that is a latent problem of deep learning was prevented considerably as discussed in this study.