• Title/Summary/Keyword: Feature compensation

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A study of the preconsonantal vowel shortening in Chinese

  • Yun, Ilsung
    • Phonetics and Speech Sciences
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    • v.10 no.4
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    • pp.39-44
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    • 2018
  • This study aimed to examine whether preconsonantal vowel shortening, which occurs in many languages, exists in Chinese. To this end, we compared 15 pairs of Chinese bi-syllabic words with intervocalic unaspirated/aspirated stops. The results revealed that (1) the effect of the feature aspiration of the following stop on the preceding vowel (V1) was neither significant nor consistent though V1 tends to be a little longer before an unaspirated stop; (2) the following unaspirated stop closure (C) was similar to or longer than its aspirated cognate; (3) the durational sum of V1 and C was longer when the stop is unaspirated, and V1 and C had no compensatory relationship; (4) Voice Onset Time (VOT) was significantly longer when the stop is aspirated than unaspirated; (5) the vowel (V2) following VOT was significantly longer when the stop is unaspirated, so the differentials in VOT were partially compensated; (6) despite the partial compensation, the sum of VOT and V2 was longer when the stop is aspirated; (7) words with an intervocalic aspirated stop were longer than those with its unaspirated cognate. It is concluded that while VOT is the most important factor for deciding the timing structure of Chinese words with intervocalic stops, closure duration is crucial for Korean and many other languages.

Real-Time Face Recognition Based on Subspace and LVQ Classifier (부분공간과 LVQ 분류기에 기반한 실시간 얼굴 인식)

  • Kwon, Oh-Ryun;Min, Kyong-Pil;Chun, Jun-Chul
    • Journal of Internet Computing and Services
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    • v.8 no.3
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    • pp.19-32
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    • 2007
  • This paper present a new face recognition method based on LVQ neural net to construct a real time face recognition system. The previous researches which used PCA, LDA combined neural net usually need much time in training neural net. The supervised LVQ neural net needs much less time in training and can maximize the separability between the classes. In this paper, the proposed method transforms the input face image by PCA and LDA sequentially into low-dimension feature vectors and recognizes the face through LVQ neural net. In order to make the system robust to external light variation, light compensation is performed on the detected face by max-min normalization method as preprocessing. PCA and LDA transformations are applied to the normalized face image to produce low-level feature vectors of the image. In order to determine the initial centers of LVQ and speed up the convergency of the LVQ neural net, the K-Means clustering algorithm is adopted. Subsequently, the class representative vectors can be produced by LVQ2 training using initial center vectors. The face recognition is achieved by using the euclidean distance measure between the center vector of classes and the feature vector of input image. From the experiments, we can prove that the proposed method is more effective in the recognition ratio for the cases of still images from ORL database and sequential images rather than using conventional PCA of a hybrid method with PCA and LDA.

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A Study on the Security Service to a Duty Satisfaction and an Organization (경호원의 직무만족과 조직몰입에 관한 연구)

  • Park, Jun-Seok;Jung, Sung-Sook
    • Korean Security Journal
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    • no.10
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    • pp.127-147
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    • 2005
  • This study (research) has been done on the job, job-satisfaction and job dedication of body guards from many sectors in Korea. This research is focused on the relationship of job, job-satisfaction and job-dedication in diverse aspects in order to build up a detailed theory, As a result, teams of body guard can enhance their systematic efficiency through the theory. Therefore in this chapter, it will re-examine the result of this research and discuss about the theoretical and practical aspect of the result. This study(research) will be the outset(start) for the organizational behavior study of the body guards in Korea. Especially, this research tries to distinguish the duty aspect and the general feature of the body guards, satisfaction along with the level of dedication. Therefore it will give the persons concerning the bodyguards many theoretical and practical points to consider. But there is a limitation as crossing research that in this research we didn't research in compensation for all internal body guards and accomplishment of research has achieved in a short-time. Though it will be necessary to accomplish in henceforth research, if at all possible, in compensation for all body guards and much more diverse security service classification, also for a long time extended vertical research.

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Normalization of Face Images Subject to Directional Illumination using Linear Model (선형모델을 이용한 방향성 조명하의 얼굴영상 정규화)

  • 고재필;김은주;변혜란
    • Journal of KIISE:Software and Applications
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    • v.31 no.1
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    • pp.54-60
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    • 2004
  • Face recognition is one of the problems to be solved by appearance based matching technique. However, the appearance of face image is very sensitive to variation in illumination. One of the easiest ways for better performance is to collect more training samples acquired under variable lightings but it is not practical in real world. ]:n object recognition, it is desirable to focus on feature extraction or normalization technique rather than focus on classifier. This paper presents a simple approach to normalization of faces subject to directional illumination. This is one of the significant issues that cause error in the face recognition process. The proposed method, ICR(illumination Compensation based on Multiple Linear Regression), is to find the plane that best fits the intensity distribution of the face image using the multiple linear regression, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experimental results show a significant improvement of the recognition accuracy.

A Study on the Improvement of Geometric Quality of KOMPSAT-3/3A Imagery Using Planetscope Imagery (Planetscope 영상을 이용한 KOMPSAT-3/3A 영상의 기하품질 향상 방안 연구)

  • Jung, Minyoung;Kang, Wonbin;Song, Ahram;Kim, Yongil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.4
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    • pp.327-343
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    • 2020
  • This study proposes a method to improve the geometric quality of KOMPSAT (Korea Multi-Purpose Satellite)-3/3A Level 1R imagery, particularly for efficient disaster damage analysis. The proposed method applies a novel grid-based SIFT (Scale Invariant Feature Transform) method to the Planetscope ortho-imagery, which solves the inherent limitations in acquiring appropriate optical satellite imagery over disaster areas, and the KOMPSAT-3/3A imagery to extract GCPs (Ground Control Points) required for the RPC (Rational Polynomial Coefficient) bias compensation. In order to validate its effectiveness, the proposed method was applied to the KOMPSAT-3 multispectral image of Gangnueng which includes the April 2019 wildfire, and the KOMPSAT-3A image of Daejeon, which was additionally selected in consideration of the diverse land cover types. The proposed method improved the geometric quality of KOMPSAT-3/3A images by reducing the positioning errors(RMSE: Root Mean Square Error) of the two images from 6.62 pixels to 1.25 pixels for KOMPSAT-3, and from 7.03 pixels to 1.66 pixels for KOMPSAT-3A. Through a visual comparison of the post-disaster KOMPSAT-3 ortho-image of Gangneung and the pre-disaster Planetscope ortho-image, the result showed appropriate geometric quality for wildfire damage analysis. This paper demonstrated the possibility of using Planetscope ortho-images as an alternative to obtain the GCPs for geometric calibration. Furthermore, the proposed method can be applied to various KOMPSAT-3/3A research studies where Planetscope ortho-images can be provided.

Fire Severity Mapping Using a Single Post-Fire Landsat 7 ETM+ Imagery (단일 시기의 Landsat 7 ETM+ 영상을 이용한 산불피해지도 작성)

  • 원강영;임정호
    • Korean Journal of Remote Sensing
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    • v.17 no.1
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    • pp.85-97
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    • 2001
  • The KT(Kauth-Thomas) and IHS(Intensity-Hue-Saturation) transformation techniques were introduced and compared to investigate fire-scarred areas with single post-fire Landsat 7 ETM+ image. This study consists of two parts. First, using only geometrically corrected imagery, it was examined whether or not the different level of fire-damaged areas could be detected by simple slicing method within the image enhanced by the IHS transform. As a result, since the spectral distribution of each class on each IHS component was overlaid, the simple slicing method did not seem appropriate for the delineation of the areas of the different level of fire severity. Second, the image rectified by both radiometrically and topographically was enhanced by the KT transformation and the IHS transformation, respectively. Then, the images were classified by the maximum likelihood method. The cross-validation was performed for the compensation of relatively small set of ground truth data. The results showed that KT transformation produced better accuracy than IHS transformation. In addition, the KT feature spaces and the spectral distribution of IHS components were analyzed on the graph. This study has shown that, as for the detection of the different level of fire severity, the KT transformation reflects the ground physical conditions better than the IHS transformation.

Study on the Market Segmentation of inpatients (입원환자 시장세분화에 관한 연구)

  • Lee, Eun-Whan
    • Korea Journal of Hospital Management
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    • v.17 no.2
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    • pp.21-33
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    • 2012
  • Purpose : This study aims to suggest application of patients DB to hospital marketing by performing market segmentation and selecting target market. Consequently help to establish suited strategy of marketing. Method : 14,072 patients hospitalized in a University Medical Center were recruited into this study. In order to classify the customer groups, cluster analysis was used with RFM(Recency, Frequency, Monetary) model, and 1-way ANOVA verified the differences among groups. And then, sociodemographical status, healthcare utilization and diagnosis(ICD-10) of each group were compared to draw a marketing strategy. Results : Four groups were classified through clustering analysis, and'high use and high profit' and'low use and high profit' groups were selected as a target market. The features of target market were as follows, the female proportion was high; used a private room; hospitalized through the emergency room; had operation; length of stay was long; had many comorbidity and cooperative treatment. There was difference in each feature of target market: as for the'high use and high profit' group, many patients were diagnosed with 'certain infectious and parasitic diseases'; and as for the'low use and high profit'group, the proportion of patients who purchased'industrial accident compensation insurance'and'auto insurance'was relatively high; many patients were diagnosed with'Injury, poisoning and certain other consequences of external causes'. Conclusion : It is needed to establish'positioning' strategy by monitoring and communicating with'high use and high profit' group. And for the case of'low use and high profit' group, it is necessary to make a follow-up management and lead them to have a medical check-up.

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A Real-Time Embedded Speech Recognition System

  • Nam, Sang-Yep;Lee, Chun-Woo;Lee, Sang-Won;Park, In-Jung
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.690-693
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    • 2002
  • According to the growth of communication biz, embedded market rapidly developing in domestic and overseas. Embedded system can be used in various way such as wire and wireless communication equipment or information products. There are lots of developing performance applying speech recognition to embedded system, for instance, PDA, PCS, CDMA-2000 or IMT-2000. This study implement minimum memory of speech recognition engine and DB for apply real time embedded system. The implement measure of speech recognition equipment to fit on embedded system is like following. At first, DC element is removed from Input voice and then a compensation of high frequency was achieved by pre-emphasis with coefficients value, 0.97 and constitute division data as same size as 256 sample by lapped shift method. Through by Levinson - Durbin Algorithm, these data can get linear predictive coefficient and again, using Cepstrum - Transformer attain feature vectors. During HMM training, We used Baum-Welch reestimation Algorithm for each words training and can get the recognition result from executed likelihood method on each words. The used speech data is using 40 speech command data and 10 digits extracted form each 15 of male and female speaker spoken menu control command of Embedded system. Since, in many times, ARM CPU is adopted in embedded system, it's peformed porting the speech recognition engine on ARM core evaluation board. And do the recognition test with select set 1 and set 3 parameter that has good recognition rate on commander and no digit after the several tests using by 5 proposal recognition parameter sets. The recognition engine of recognition rate shows 95%, speech commander recognizer shows 96% and digits recognizer shows 94%.

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Improve Stability of Military Infrared Image and Implement Zynq SoC (군사용 적외선 영상의 안정화 성능 개선 및 Zynq SoC 구현)

  • Choi, Hyun;Kim, Young-Min;Kang, Seok-Hoon;Cho, Joong-Hwee
    • IEMEK Journal of Embedded Systems and Applications
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    • v.13 no.1
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    • pp.17-24
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    • 2018
  • Military camera equipment has a problem that observability is inferior due to various shaking factors. In this paper, we propose an image stabilization algorithm considering performance and execution time to solve this problem and implemented it in Zynq SoC. We stabilized both the simple shaking in the fixed observation position and the sudden shaking in the moving observation position. The feature of the input image is extracted by the Sobel edge algorithm, the subblock with the large edge data is selected, and the motion vector, which is the compensation reference, is calculated through template matching using the 3-step search algorithm of the region of interest. In addition, the proposed algorithm can distinguish the shaking caused by the simple shaking and the movement by using the Kalman filter, and the stabilized image can be obtained by minimizing the loss of image information. To demonstrate the effectiveness of the proposed algorithm, experiments on various images were performed. In comparison, PSNR is improved in the range of 2.6725~3.1629 (dB) and image loss is reduced from 41% to 15%. On the other hand, we implemented the hardware-software integrated design using HLS of Xilinx SDSoC tool and confirmed that it operates at 32 fps on the Zynq board, and realized SoC that operates with real-time processing.

Study of Hero-storytelling Model in Console Games (게임에서의 '영웅 스토리텔링' 모델화 연구)

  • Choi Young-Mee;Bae Ju-Young
    • The Journal of the Korea Contents Association
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    • v.6 no.4
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    • pp.109-116
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    • 2006
  • This study is to present 'game-storytelling' is based on 'hero-storytelling' and to transform the basic pattern which is extracted from 'heroic-storytelling' so that it can be applied to 'game-storytelling'. 'Game-storytelling' has the similar foundation as 'heroic storytelling'. It begins with an extraordinary birth, introduction to the strange world, exploration, adventure, birth of a hero and finally return of a hero. The most distinctive feature of stages is the conquest of outer and internal limitation. Each stage goes through the process of compensation and outer, internal acknowledgements. These processes are the structural core of game storytelling. Generally, stage 1 to 5 includes background stories, stage 6 to 9 are the progress of game, and stage 10 to 12 are the transformation of game with rules and genre.

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