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Noise Robust Speech Recognition Based on Parallel Model Combination Adaptation Using Frequency-Variant (주파수 변이를 이용한 Parallel Model Combination 모델 적응에 기반한 잡음에 강한 음성인식)

  • Choi, Sook-Nam;Chung, Hyun-Yeol
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.3
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    • pp.252-261
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    • 2013
  • The common speech recognition system displays higher recognition performance in a quiet environment, while its performance declines sharply in a real environment where there are noises. To implement a speech recognizer that is robust in different speech settings, this study suggests the method of Parallel Model Combination adaptation using frequency-variant based on environment-awareness (FV-PMC), which uses variants in frequency; acquires the environmental data for speech recognition; applies it to upgrading the speech recognition model; and promotes its performance enhancement. This FV-PMC performs the speech recognition with the recognition model which is generated as followings: i) calculating the average frequency variant in advance among the readily-classified noise groups and setting it as a threshold value; ii) recalculating the frequency variant among noise groups when speech with unknown noises are input; iii) regarding the speech higher than the threshold value of the relevant group as the speech including the noise of its group; and iv) using the speech that includes this noise group. When noises were classified with the proposed FV-PMC, the average accuracy of classification was 56%, and the results from the speech recognition experiments showed the average recognition rate of Set A was 79.05%, the rate of Set B 79.43%m, and the rate of Set C 83.37% respectively. The grand mean of recognition rate was 80.62%, which demonstrates 5.69% more improved effects than the recognition rate of 74.93% of the existing Parallel Model Combination with a clear model, meaning that the proposed method is effective.

A Study on Construction and Applicability on of Smart Pole Measuring System for Monitoring Steep Slope Sites (급경사지 모니터링을 위한 스마트폴 계측시스템 구축 및 적용성 연구)

  • Lee, Jin-Duk;Chang, Ki-Tae;Bhang, Kon-Joon
    • Journal of Korean Society of Disaster and Security
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    • v.7 no.2
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    • pp.1-8
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    • 2014
  • Smart Pole Measurement System was constructed with not only the core sensors of a GNSS receiver, a TRS sensor and a soil moisture sensor but supplementary installation of power supply and radio communication for monitoring steep slope sites. Also a data processing software for displacement extraction and visualization was developed. Smart Pole Measurement sensor is composed of a GNSS antenna at the top of the pole, a TRS sensor and a gyro sensor vertical below right of the antenna and a soil moisture sensor at the bottom of the pole. The sensor combination extracts not only ground combination in real time but transltion, slide, settlement and soil moisture content. This measuring/monitoring system which cosists of data receiving part, data collection/transfer part and data processing part was built to exercise their functions and then test measuring/monitoring was conducted by introducing artificial displacement and the results were analyzed to evaluate field applicability.

A Literary Study on Combination of Yeolgyeol $(LU_7)$ and Johae $(KI_6)$ of Eight Confluent Acupoints (팔맥교회혈(八脈交會穴) 중(中).열결(列缺) 조해(照海)의 배합(配合)에 관한 문헌(文獻) 연구(硏究))

  • Jang Jae-Young;Park Sang-Yeon;Hong Jung-A;Jang Jae-Ik;Kim Kyung-Sik;Kim Jae-Hyo;Sohn In-Chul
    • Korean Journal of Acupuncture
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    • v.23 no.4
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    • pp.27-47
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    • 2006
  • Objectives : The aim of this study was to analyze how to treat various symptoms through the combination of Yoelgyoel $(LU_7)$ and Johae $(KI_6)$, according to reviewing the contents and data since Ling Shu (靈樞經) to recent literatures including thirty-five medical books. Methods : It was arranged and considered that the location, needling, and symptoms of each acupoint were described in various literatures before the publication of Chim Kyung Ji Nam (鍼經指南). Through various literature since the Publication of Chim Kyung Ji Nam, it was examined how to be recognized and be referred about Yoelgyoel $(LU_7)$ and Johae $(KI_6)$. Results and Conclusions : The location of Yoelgyoel is the superior 1.5cun at wrist joint striation, medial of extensor carpi radialis longus; the location of Johae is the depression part under foot medial condyle. Yoelgyoel is often used for respiratory organ disease, urinary organ disease, neuopsychiatory disease, musculoskeletal system disease; Johae is often used for urinary organ disease, circulatory organ disease. At Chim Kyung Ji Nam, Yoelgyoel is often used for thoraco-abdominal Pain, gynecological disease, digestive organ disease; Johae is often used for abdominal pain, gynecological disease, digestive organ disease. Therefore, these points are used together for general internal disease. As well, these are not directly continuous with Previous literatures from Chim Kyung Ji Nam. The combination of Yoelgyoel and Johae have been developed to the three categories as follows; it is quoted from as it is; it is reconstructed in the form of song; it has new symptoms enlarged. Consequently, the combination of Yoelgyoel and Johae was not bind to the rule of Up-Bottom harmony (上下配合), but asserted for the rule of Ju-Eng harmony (主應配合), which add specific acupoints to e combination of Yolgyol and Chohae as the complication of the symptoms.

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Imputation Method Using Local Linear Regression Based on Bidirectional k-nearest-components

  • Yonggeol, Lee
    • Journal of information and communication convergence engineering
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    • v.21 no.1
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    • pp.62-67
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    • 2023
  • This paper proposes an imputation method using a bidirectional k-nearest components search based local linear regression method. The bidirectional k-nearest-components search method selects components in the dynamic range from the missing points. Unlike the existing methods, which use a fixed-size window, the proposed method can flexibly select adjacent components in an imputation problem. The weight values assigned to the components around the missing points are calculated using local linear regression. The local linear regression method is free from the rank problem in a matrix of dependent variables. In addition, it can calculate the weight values that reflect the data flow in a specific environment, such as a blackout. The original missing values were estimated from a linear combination of the components and their weights. Finally, the estimated value imputes the missing values. In the experimental results, the proposed method outperformed the existing methods when the error between the original data and imputation data was measured using MAE and RMSE.

A Study of Application of Remotely Sensed Data for the Management of National Parks - in case of Bukhansan National Park- (국립공원관리를 위한 위성영상 활용방안에 관한 연구 -북한산 국립공원을 사례로-)

  • Park, Kyeong;Chang, Eun-Mi;Scene, Sang-Hee
    • Journal of Environmental Impact Assessment
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    • v.10 no.3
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    • pp.167-174
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    • 2001
  • National Parks in Korea occupy about four percents of South Korean land. This paper aims to prove the potentiality of the application of remotely sensed data for the effective management of National Parks. Different satellite images such as Landsat TM, IRS-1C, Alternative image, and IKONOS image are analyzed for the detection of changes, the extraction of degraded areas, and the comparison of Normalized Difference Vegetation Index (NDVI) in Bukhansan National Park. The artificial structures such as buildings and paved areas are overvalued in relatively higher resolution data. The result showed that the choice of images should be determined according to specific purposes and the combination of different resolution data may be the solution for the effective management of National Park.

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A Method for Enhancing Data Transmission Performance in the Power-Line Communication Channel with Low-Voltage Surge Protective Devices (저압용 SPD가 설치된 전력선통신에서 데이터전송 성능 향상)

  • Choi, Jong-Min;Jeon, Tae-Hyun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.26 no.2
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    • pp.78-85
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    • 2012
  • Low-Voltage power lines should equip surge protection devices which protect electronic equipments and human lives against lightning and abnormal voltages. Data transmission capacity of the power line is determined by frequency characteristics of the surge protective devices. To analyze the effects of surge protective devices on the data transmission performance, various combinations of installation methods are tested which include ZnO varistor elements that is compatible with class I, class II and class III. The result claims that ZnO varistor for class III is found to be one of the main factors that deteriorates the transmission performance. To overcome this problem a serial connection methed between Gap type SPD and ZnO varistor is proposed. With the proposed scheme, laboratory experimental results show that the data transmission performance can be improved up to 91.9[%] with proper SPD combination.

Evaluation of Similarity Analysis of Newspaper Article Using Natural Language Processing

  • Ayako Ohshiro;Takeo Okazaki;Takashi Kano;Shinichiro Ueda
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.1-7
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    • 2024
  • Comparing text features involves evaluating the "similarity" between texts. It is crucial to use appropriate similarity measures when comparing similarities. This study utilized various techniques to assess the similarities between newspaper articles, including deep learning and a previously proposed method: a combination of Pointwise Mutual Information (PMI) and Word Pair Matching (WPM), denoted as PMI+WPM. For performance comparison, law data from medical research in Japan were utilized as validation data in evaluating the PMI+WPM method. The distribution of similarities in text data varies depending on the evaluation technique and genre, as revealed by the comparative analysis. For newspaper data, non-deep learning methods demonstrated better similarity evaluation accuracy than deep learning methods. Additionally, evaluating similarities in law data is more challenging than in newspaper articles. Despite deep learning being the prevalent method for evaluating textual similarities, this study demonstrates that non-deep learning methods can be effective regarding Japanese-based texts.

Automated Classification of PubMed Texts for Disambiguated Annotation Using Text and Data Mining

  • Choi, Yun-Jeong;Park, Seung-Soo
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.101-106
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    • 2005
  • Recently, as the size of genetic knowledge grows faster, automated analysis and systemization into high-throughput database has become hot issue. One essential task is to recognize and identify genomic entities and discover their relations. However, ambiguity of name entities is a serious problem because of their multiplicity of meanings and types. So far, many effective techniques have been proposed to analyze documents. Yet, accuracy is high when the data fits the model well. The purpose of this paper is to design and implement a document classification system for identifying entity problems using text/data mining combination, supplemented by rich data mining algorithms to enhance its performance. we propose RTP ost system of different style from any traditional method, which takes fault tolerant system approach and data mining strategy. This feedback cycle can enhance the performance of the text mining in terms of accuracy. We experimented our system for classifying RB-related documents on PubMed abstracts to verify the feasibility.

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Pressure Control of SR Driven Hydraulic Oil-Pump Using Data based PID Controller

  • Lee, Dong-Hee;Kim, Tae-Hyoung;Ahn, Jin-Woo
    • Journal of Power Electronics
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    • v.9 no.5
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    • pp.800-808
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    • 2009
  • This paper presents a practical method of pressure control for a hydraulic oil-pump system using an SR (Switched Reluctance) drive. For a 6Mpa grade hydraulic oil-pump, a 2.6kW SR drive is developed. In order to get high performance pressure dynamics in actual applications, a data based PID control scheme is proposed. The look-up table from a pre-measured data base produces an approximate current reference based on motor speed and oil-pressure. A PID controller can compensate for the pressure error. With the combination of the two references, the proposed control scheme can achieve fast dynamics and stable operation. Furthermore, a suitable current controller considering the nonlinear characteristics of an SRM (Switched Reluctance Motor) and practical test methods for data measuring are presented. The proposed control scheme is verified by experimental tests.

An Efficient Algorithm for Mining Frequent Sequences In Spatiotemporal Data

  • Vhan Vu Thi Hong;Chi Cheong-Hee;Ryu Keun-Ho
    • 한국공간정보시스템학회:학술대회논문집
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    • 2005.11a
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    • pp.61-66
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    • 2005
  • Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

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