• Title/Summary/Keyword: Tri-training

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A Study on Korean 4-connected Digit Recognition Using Demi-syllable Context-dependent Models (반음절 문맥종속 모델을 이용한 한국어 4 연숫자음 인식에 관한 연구)

  • 이기영;최성호;이호영;배명진
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.3
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    • pp.175-181
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    • 2003
  • Because a word of Korean digits is a syllable and deeply coarticulatied in connected digits, some recognition models based on demisyllables have been proposed by researchers. However, they could not show an excellent recognition results yet. This paper proposes a recognition model based on extended and context-dependent demisyllables, such as a tri-demisyllable like a tri-phone, for the Korean 4-connected digits recognition. For experiments, we use a toolkit of HTK 3.0 for building this model of continuous HMMs using training Korean connected digits from SiTEC database and for recognizing unknown ones. The results show that the recognition rate is 92% and this model has an ability to improve the recognition performance of Korean connected digits.

Improvement of Naturalness for a HMM-based Korean TTS using the prosodic boundary information (운율경계정보를 이용한 HMM기반 한국어 TTS 자연성 향상 연구)

  • Lim, Gi-Jeong;Lee, Jung-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.9
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    • pp.75-84
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    • 2012
  • HMM-based Text-to-Speech systems generally utilize context dependent tri-phone units from a large corpus speech DB to enhance the synthetic speech. To downsize a large corpus speech DB, acoustically similar tri-phone units are clustered based on the decision tree using context dependent information. Context dependent information includes phoneme sequence as well as prosodic information because the naturalness of synthetic speech highly depends on the prosody such as pause, intonation pattern, and segmental duration. However, if the prosodic information was complicated, many context dependent phonemes would have no examples in the training data, and clustering would provide a smoothed feature which will generate unnatural synthetic speech. In this paper, instead of complicate prosodic information we propose a simple three prosodic boundary types and decision tree questions that use rising tone, falling tone, and monotonic tone to improve naturalness. Experimental results show that our proposed method can improve naturalness of a HMM-based Korean TTS and get high MOS in the perception test.

Improving Chest X-ray Image Classification via Integration of Self-Supervised Learning and Machine Learning Algorithms

  • Tri-Thuc Vo;Thanh-Nghi Do
    • Journal of information and communication convergence engineering
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    • v.22 no.2
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    • pp.165-171
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    • 2024
  • In this study, we present a novel approach for enhancing chest X-ray image classification (normal, Covid-19, edema, mass nodules, and pneumothorax) by combining contrastive learning and machine learning algorithms. A vast amount of unlabeled data was leveraged to learn representations so that data efficiency is improved as a means of addressing the limited availability of labeled data in X-ray images. Our approach involves training classification algorithms using the extracted features from a linear fine-tuned Momentum Contrast (MoCo) model. The MoCo architecture with a Resnet34, Resnet50, or Resnet101 backbone is trained to learn features from unlabeled data. Instead of only fine-tuning the linear classifier layer on the MoCopretrained model, we propose training nonlinear classifiers as substitutes for softmax in deep networks. The empirical results show that while the linear fine-tuned ImageNet-pretrained models achieved the highest accuracy of only 82.9% and the linear fine-tuned MoCo-pretrained models an increased highest accuracy of 84.8%, our proposed method offered a significant improvement and achieved the highest accuracy of 87.9%.

Ethereum Phishing Scam Detection Based on Graph Embedding (그래프 임베딩 기반의 이더리움 피싱 스캠 탐지 연구)

  • Cheong, Yoo-Young;Kim, Gyoung-Tae;Im, Dong-Hyuk
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.266-268
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    • 2022
  • 최근 블록체인 기술이 부상하면서 이를 이용한 암호화폐가 범죄의 대상이 되고 있다. 특히 피싱 스캠은 이더리움 사이버 범죄의 과반수 이상을 차지하며 주요 보안 위협원으로 여겨지고 있다. 따라서 효과적인 피싱 스캠 탐지 방법이 시급하다. 그러나 전체 노드에서 라벨링된 피싱 주소의 부족으로 인한 데이터 불균형으로 인하여 지도학습에 충분한 데이터 제공이 어려운 상황이다. 이를 해결하기 위해 본 논문에서는 이더리움 트랜잭션 네트워크를 고려한 효율적인 네트워크 임베딩 기법인 trans2vec 과 준지도 학습 모델 tri-training 을 함께 사용하여 라벨링된 데이터뿐만 아니라 라벨링되지 않은 데이터도 최대한 활용하는 피싱 스캠 탐지 방법을 제안한다.

A Study on the development of Test Report Information Service(TRIS) by User survey analysis (사용자 설문분석을 통한 군수품 시험성적서 정보서비스 고도화 방안에 대한 연구)

  • Park, Dongsoo;Lee, Donghun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.2
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    • pp.405-414
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    • 2017
  • In this study, a survey for a satisfaction evaluation of the Test Report Information Service (TRIS) was conducted. A survey questionnaire on modified Information System Success Model(ISSM) of Delone and Mclean was carried out by 183 users in three groups, such as munition quality assurance agency, munition corporation, and test institute. As a survey result, training on the TRIS was in strong demand in all three groups. An understanding and proficiency of the overall system were different from the work process of each user group. In addition, the munition quality assurance agency needs to enhance the system function with its characteristics. Test institute has necessity of the linkage method with the TRIS depending on the authentication system. User groups are different in the operational method of TRIS between the contractor and cooperation. Accordingly, cooperation needs to be educated continually. This study can help in the construction of a Military Quality Integration Information System to secure the reliability of munitions.

GIS-based Landslide Susceptibility Mapping of Bhotang, Nepal using Frequency Ratio and Statistical Index Methods

  • Acharya, Tri Dev;Yang, In Tae;Lee, Dong Ha
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.5
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    • pp.357-364
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    • 2017
  • The purpose of the study is to develop and validate landslide susceptibility map of Bhotang village development committee, Nepal using FR (Frequency Ration) and SI (Statistical Index) methods. For the purpose, firstly, a landslide inventory map was constructed based on mainly high resolution satellite images available in Google Earth Pro, and rest fieldwork as verification. Secondly, ten conditioning factors of landslide occurrence, namely: altitude, slope, aspect, mean topographic wetness index, landcover, normalized difference vegetation index, dominant soil, distance to river, distance to lineaments and rainfall, were derived and used for the development of landslide susceptibility map in GIS (Geographic Information System) environment. The landslide inventory of total 116 landslides was divided randomly such that 70% were used for training and remaining 30% for validating result by receiver operating characteristics curve analysis. The area under the curve were found to be greater than 0.7 indicating an acceptable susceptibility maps obtained using FR and SI methods in GIS for hilly region of Nepal.

In Out-of Vocabulary Rejection Algorithm by Measure of Normalized improvement using Optimization of Gaussian Model Confidence (미등록어 거절 알고리즘에서 가우시안 모델 최적화를 이용한 신뢰도 정규화 향상)

  • Ahn, Chan-Shik;Oh, Sang-Yeob
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.12
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    • pp.125-132
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    • 2010
  • In vocabulary recognition has unseen tri-phone appeared when recognition training. This system has not been created beginning estimation figure of model parameter. It's bad points could not be created that model for phoneme data. Therefore it's could not be secured accuracy of Gaussian model. To improve suggested Gaussian model to optimized method of model parameter using probability distribution. To improved of confidence that Gaussian model to optimized of probability distribution to offer by accuracy and to support searching of phoneme data. This paper suggested system performance comparison as a result of recognition improve represent 1.7% by out-of vocabulary rejection algorithm using normalization confidence.

The Effects of Technology Readiness Index of Artificial Intelligence and Internet of Things on the Recognition of Substitute Employment of Medical Personnel (인공지능, 사물인터넷의 기술준비도가 의료인력 고용대체인지도에 미치는 영향)

  • Kang, Han Seom;Kim, Young Hoon
    • Korea Journal of Hospital Management
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    • v.23 no.2
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    • pp.54-66
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    • 2018
  • Purpose: This study was to figure out relationships of perceived Technology Readiness Index(TRI), usefulness, acceptance intension, and the recognition of substitute employment of medical personnel on the artificial intelligence (AI) and internet of things (IoT) among main technologies. Methodology: To achieve the purpose, this study utilized structured survey tools to conduct a questionnaire survey of nursing, administrative and medical technology professionals at six university hospitals in Korea metropolitan area. A PLS(Partial Least Square) Path analysis was utilized To analyze the material. Findings: In the relation with the technology readiness and perceived usefulness, it had a positive influence to the perceived usefulness when the optimism and innovativeness were higher and the discomfort was lower. In the relation with the technology readiness and acceptance intension, it showed a positive influence when the innovativeness was higher and the discomfort was lower. In the relation with the perceived usefulness and acceptance intension, it had a positive influence to the acceptance intension when the perceived usefulness was higher. In the relation with the acceptance intension and the recognition of substitute employment, it showed a positive influence to the recognition of substitute employment when the acceptance intension was higher. Practical Implications: Judging based on the above study results and reference reviews, it confirmed that it is necessary to prepare in the level of hospital organization in the $4^{th}$ Industrial Revolution. They should increase the efficiency of human resources through the technological factors or changes of employment types for the additional demands of human resources to handle increasing medical demands or induce to secure necessary abilities which are changing at the right time by performing the $4^{th}$ Industrial Revolution related re-training continuously to develop the value of existing human resources.

The Effect of Macroeconomic Factors on Income Inequality: Evidence from Indonesia

  • SESSU, Andi;SAMIHA, Yulia Tri;LAISILA, Maya;CHAMIDAH, Nurul;MURDIFIN, Imaduddin;PUTRA, Aditya Halim Perdana Kusuma
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.55-66
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    • 2021
  • The purpose of this study is to analyze the relationship and effects of variables both directly and indirectly (e.g., investment (INV), government expenditure (GE), unemployment rate (UR), economic growth (EG), and income inequality). The analytical phases consist, first, to transform the data using the Log Natural (Ln) method. Second, to check normality and multicollinearity of data. Third, to test direct effects of variables (government expenditure and investment effect on the unemployment rate and economic growth; investment on government expenditure; economic growth on unemployment rate; economic growth and unemployment rate on income inequality). Fourth, to test indirect effects using Sobel test, which involves UR and EG as intervening variable. Fifth, to test hypotheses with p-value < 0.05. The results of the study reveal that, of the 12 relationships, statistics show that 11 variations of the association have significant positive and negative effects. Theoretically, the different characters and goals of GE and INV in each country will have a different impact on EG and UR goals. The study provides an input, especially for the government. To create optimal EG through GE and INV, it is necessary to allocate budgets to industrial sectors that can absorb a massive labor force and to new economic growth sectors.

Sleep Quality and Poor Sleep-related Factors Among Healthcare Workers During the COVID-19 Pandemic in Vietnam

  • Thang Phan;Ha Phan Ai Nguyen;Cao Khoa Dang;Minh Tri Phan;Vu Thanh Nguyen;Van Tuan Le;Binh Thang Tran;Chinh Van Dang;Tinh Huu Ho;Minh Tu Nguyen;Thang Van Dinh;Van Trong Phan;Binh Thai Dang;Huynh Ho Ngoc Quynh;Minh Tran Le;Nhan Phuc Thanh Nguyen
    • Journal of Preventive Medicine and Public Health
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    • v.56 no.4
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    • pp.319-326
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    • 2023
  • Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic. Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher. Results: Participants' mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95). Conclusions: The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.