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Real Time Environmental Classification Algorithm Using Neural Network for Hearing Aids (인공 신경망을 이용한 보청기용 실시간 환경분류 알고리즘)

  • Seo, Sangwan;Yook, Sunhyun;Nam, Kyoung Won;Han, Jonghee;Kwon, See Youn;Hong, Sung Hwa;Kim, Dongwook;Lee, Sangmin;Jang, Dong Pyo;Kim, In Young
    • Journal of Biomedical Engineering Research
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    • v.34 no.1
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    • pp.8-13
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    • 2013
  • Persons with sensorineural hearing impairment have troubles in hearing at noisy environments because of their deteriorated hearing levels and low-spectral resolution of the auditory system and therefore, they use hearing aids to compensate weakened hearing abilities. Various algorithms for hearing loss compensation and environmental noise reduction have been implemented in the hearing aid; however, the performance of these algorithms vary in accordance with external sound situations and therefore, it is important to tune the operation of the hearing aid appropriately in accordance with a wide variety of sound situations. In this study, a sound classification algorithm that can be applied to the hearing aid was suggested. The proposed algorithm can classify the different types of speech situations into four categories: 1) speech-only, 2) noise-only, 3) speech-in-noise, and 4) music-only. The proposed classification algorithm consists of two sub-parts: a feature extractor and a speech situation classifier. The former extracts seven characteristic features - short time energy and zero crossing rate in the time domain; spectral centroid, spectral flux and spectral roll-off in the frequency domain; mel frequency cepstral coefficients and power values of mel bands - from the recent input signals of two microphones, and the latter classifies the current speech situation. The experimental results showed that the proposed algorithm could classify the kinds of speech situations with an accuracy of over 94.4%. Based on these results, we believe that the proposed algorithm can be applied to the hearing aid to improve speech intelligibility in noisy environments.

Understanding the Selective Attention and Animation Induction Device According to the Visual Capture of Audience (관객의 시각포획현상에 따른 선택적 주의집중과 애니메이션 유도장치의 이해)

  • Lee, Jong-Han
    • Cartoon and Animation Studies
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    • s.41
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    • pp.133-152
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    • 2015
  • Some artists and scientists in physics and animation originating from research on its form of expression thanks to the rapid development of the example in the late 20th century image production technology integrating existing media feature, perform a re-creation and pop culture content has been recognized as a key factor. animation of the modern emphasis is also commercial and artistic activities as show whether the artist can not be excluded that also target audience. The audience does not want only to receive offers simply 'seeing' and 'hearing' in the animation requires a more indirect mental met. the other side, the director should lead the audience to immerse myself in work as intended mystification induce the world. where a conflict occurs between the audience and the director and The director needs to have its troubleshooting point to 'Technology of the communication'. Which is reduced to 'How will tell,' is technology communication technologies that are abbreviated representations of animation director is accessible to the audience and it is a close relationship between the psychological aspect of audience. Because, the audience is reproduced in a limited space, but he called on the board of directors and the same time the screen, the audience located at reception and the director located at provide. It is given. led force is given to the director. for this reason, The director needs to pay attention to the psychological aspect of audience this can be explained based on psychoanalytic theory. In this paper, "How can you lie to the audience and the director is the same line?" put down logic that is the animation audience under the logic that takes place visually capture phenomenon "selective attention" and sub-concept of "goal-directed selection' and 'stimulus-driven capturel' for theory of psychology. also, Induction device to elicit selective attention of the audience accordingly, let's consider whether and how they apply in animation.

An effect of laser irradiation on periodontal pocket tissue (레이저 조사가 치주낭 조직에 미치는 영향)

  • Han, Kyeong-Yoon;Kim, Sang-Mok;Kim, Byung-Ock;Kim, Hyun-Sub;Lim, Kee-Jung
    • Journal of Periodontal and Implant Science
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    • v.26 no.2
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    • pp.511-521
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    • 1996
  • Periodontal pocket is one of the most frequently developed clinical feature on the teeth with periodontal disease. In order to determine the gingival curettage effect of intrapocket irradiation of a pulsed Nd : YAG laser on periodontally involved teeth, bilateral 60 teeth with $4{\sim}6mm$ in probing pocket depth 1 week after supragingival scaling were selected. On half of them the intrapocket irradiation($300{\mu}m$ fiber optic, 1.5W power, for 2min.) of a pulsed-Nd : YAG laser(EL.EN.EN06O, Italy) was applied as the lased group. On the contralateral 30 teeth the subgingival curettage was accomplished by Gracey curettes as the curattage group. The periodontal pocket tissues were surgically excised by the modified Widman flap technique immediately after the intrapocket irradiation or subgingival curettage, subsequently fixed with 10% neutral formalin, sectioned in $4{\sim}6{\mu}m$ thickness, and stained with hematoxylin-eosin. Surface characteristics and incomplete removal of the pocket epithelium were evaluated under light microscope. And the difference between the lased group and the curettage group was statistically analyzed by Chi-square test in Microstat program. The results were as follows ; 1. The plane surface was observed more frequently in the curettage group(73.3%) than in the lased group(23.3%), and the rough surface was observed more frequently in the lased grOoup(63.3%) than in the curettage group(6.7%)(p<0.05). 2. The rate of incomplete removal of the pocket epithelium was relatively high in both the lased group(76.6%) and the curettage group(86.6%), and there was no significant difference between the lased group and the curettage group(p>0.l). The results suggest that the further studies including various power control of laser should be succeeded in order to obtain more favorable results by the intrapocket irradiation of a pulsed Nd:YAG laser than the subgingival curettage with Gracey curettes.

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Characteristics of speech rate and pause in children with spastic cerebral palsy and their relationships with speech intelligibility (경직형 뇌성마비 아동의 하위그룹별 말속도와 쉼의 특성 및 말명료도와의 관계)

  • Jeong, Pil Yeon;Sim, Hyun Sub
    • Phonetics and Speech Sciences
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    • v.12 no.3
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    • pp.95-103
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    • 2020
  • The current study aimed to identify the characteristics of speech rate and pause in children with spastic cerebral palsy (CP) and their relationships with speech intelligibility. In all, 26 children with CP, 4 with no speech motor involvement and age-appropriate language ability (NSMI-LCT), 6 with no speech motor involvement and impaired language ability (NSMI-LCI), 6 with speech motor involvement and age-appropriate language ability (SMI- LCT), and 10 with speech motor involvement and impaired language ability (SMI-LCI) participated in the study. Speech samples for the speech rate and pause analysis were extracted using a sentence repetition task. Acoustic analysis were made in Praat. First, it was found that regardless of the presence of language impairment, significant group differences between the NSMI and SMI groups were found in speech rate and articulation rate. Second, the SMI groups showed a higher ratio of pause time to sentence production time, more frequent pauses, and longer durations of pauses than the NSMI groups. Lastly, there were significant correlations among speech rate, articulation rate, and intelligibility. These findings suggest that slow speech rate is the main feature in SMI groups, and that both speech rate and articulation rate play important roles in the intelligibility of children with spastic CP.

Study on Satisfaction and Features of Patient Groups Treated with Korean Medicine Steam Therapy(KMST) at Korean Medicine Hospital (한방병원에서 열기훈법(熱氣熏法) 치료를 받은 환자군의 특성 및 만족도 연구)

  • Chae, Min-Soo;Kim, Jun-Ho;Park, Seung-Hyeok;Hwang, Deok-Sang;Lee, Jin-Moo;Lee, Chang-Hoon;Lee, Kyung-Sub;Jang, Jun-Bock
    • The Journal of Korean Obstetrics and Gynecology
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    • v.27 no.3
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    • pp.28-40
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    • 2014
  • Objectives: This study aimed to investigate the satisfaction and features of patient groups treated with KMST. Methods: From December 4th 2013 to May 8th 2014, 94 outpatients and 37 inpatients were treated with KMST, and we analyzed their medical records and satisfaction level questionnaires. Results: Mean age of total inpatients and OB&GY inpatients, total outpatients and OB&GY outpatients treated with KMST was $50.84{\pm}9.72$ years, $46.86{\pm}8.43$ years, $44.39{\pm}12.16$ years and $44.01{\pm}11.20$ years respectively. Mean value of treatment numbers per person of each group was 14.70 times, 14.58 times, 3.29 times and 3.41 times respectively. Mean interval between treatments per person of each group was 1.32 days, 1.23 days, 10.90 days and 11.62 days each. Chief complaints of OB&GY inpatients in the order of frequency were lower abdominal pain, dyspepsia and vaginal discharge. As for OB&GY outpatients, they were cold hypersensitivity, vaginal discharge, dyspepsia and infertility. The satisfaction level questionnaires for KMST showed a mean value of $7.98{\pm}1.82$ out of 10-point scale in 6 multiple-choice questions. Conclusions: Most of the patients treated with KMST were female. Pain, dyspepsia and cold hypersensitivity, vaginal discharge were frequent chief complaints in OB&GY inpatients and outpatients group each. It was found that overall satisfaction level of patients treated with KMST was high and there was no reported side effect.

Application and Evaluation of the Attention U-Net Using UAV Imagery for Corn Cultivation Field Extraction (무인기 영상 기반 옥수수 재배필지 추출을 위한 Attention U-NET 적용 및 평가)

  • Shin, Hyoung Sub;Song, Seok Ho;Lee, Dong Ho;Park, Jong Hwa
    • Ecology and Resilient Infrastructure
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    • v.8 no.4
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    • pp.253-265
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    • 2021
  • In this study, crop cultivation filed was extracted by using Unmanned Aerial Vehicle (UAV) imagery and deep learning models to overcome the limitations of satellite imagery and to contribute to the technological development of understanding the status of crop cultivation field. The study area was set around Chungbuk Goesan-gun Gammul-myeon Yidam-li and orthogonal images of the area were acquired by using UAV images. In addition, study data for deep learning models was collected by using Farm Map that modified by fieldwork. The Attention U-Net was used as a deep learning model to extract feature of UAV in this study. After the model learning process, the performance evaluation of the model for corn cultivation extraction was performed using non-learning data. We present the model's performance using precision, recall, and F1-score; the metrics show 0.94, 0.96, and 0.92, respectively. This study proved that the method is an effective methodology of extracting corn cultivation field, also presented the potential applicability for other crops.

Automated Classification of Ground-glass Nodules using GGN-Net based on Intensity, Texture, and Shape-Enhanced Images in Chest CT Images (흉부 CT 영상에서 결절의 밝기값, 재질 및 형상 증강 영상 기반의 GGN-Net을 이용한 간유리음영 결절 자동 분류)

  • Byun, So Hyun;Jung, Julip;Hong, Helen;Song, Yong Sub;Kim, Hyungjin;Park, Chang Min
    • Journal of the Korea Computer Graphics Society
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    • v.24 no.5
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    • pp.31-39
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    • 2018
  • In this paper, we propose an automated method for the ground-glass nodule(GGN) classification using GGN-Net based on intensity, texture, and shape-enhanced images in chest CT images. First, we propose the utilization of image that enhances the intensity, texture, and shape information so that the input image includes the presence and size information of the solid component in GGN. Second, we propose GGN-Net which integrates and trains feature maps obtained from various input images through multiple convolution modules on the internal network. To evaluate the classification accuracy of the proposed method, we used 90 pure GGNs, 38 part-solid GGNs less than 5mm with solid component, and 23 part-solid GGNs larger than 5mm with solid component. To evaluate the effect of input image, various input image set is composed and classification results were compared. The results showed that the proposed method using the composition of intensity, texture and shape-enhanced images showed the best result with 82.75% accuracy.

Zoning Permanent Basic Farmland Based on Artificial Immune System coupling with spatial constraints

  • Hua, Wang;Mengyu, Wang;Yuxin, Zhu;Jiqiang, Niu;Xueye, Chen;Yang, Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1666-1689
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    • 2021
  • The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.

LRM's Characterics and Applications Plan Through Comparing with FRBR (FRBR과 비교를 통한 LRM의 특징 및 적용방안)

  • Lee, Mihwa
    • Journal of Korean Library and Information Science Society
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    • v.53 no.2
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    • pp.355-375
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    • 2022
  • This study is to grasp LRM's feature and applications plan to reflect LRM to cataloging related standards and individual system through comparing and analyzing LRM with the FR model in terms of entities, attributes, and relationships. The application plan is suggested as follows. First, the entity can be extended by defining sub-entities of each entity in the standards and the individual system in order to reflect LRM, even though entities such as families, groups, identifiers, authorized access points, concepts, objects, events, agency and rules have been deleted in LRM. Second, the attribute should be subdivided in the standards and the individual system in order to apply LRM, though many attributes have been changed to relationships for linked data and decreased in LRM. In particular, more specific and detailed property names in the standards and the individual system should be clearly presented, and the vocabulary encoding scheme corresponding to each property should be also developed, since properties with similar functions or repetition in various entities, and material specific properties are generalized and integrated into comprehensive property names. Third, the relationship should be extended through newly declaring the refinement or subtype of the relationship and considering a multi-level relationship, since the relationship itself is general and abstract under increasing the number of relationships in comparing to the property. This study will be practically utilized in cataloging related standards and individual system for applying LRM.

Predicting the amount of water shortage during dry seasons using deep neural network with data from RCP scenarios (RCP 시나리오와 다층신경망 모형을 활용한 가뭄시 물부족량 예측)

  • Jang, Ock Jae;Moon, Young Il
    • Journal of Korea Water Resources Association
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    • v.55 no.2
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    • pp.121-133
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    • 2022
  • The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.