• Title/Summary/Keyword: Automatic convert

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Creating Songs Using Note Embedding and Bar Embedding and Quantitatively Evaluating Methods (음표 임베딩과 마디 임베딩을 이용한 곡의 생성 및 정량적 평가 방법)

  • Lee, Young-Bae;Jung, Sung Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.11
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    • pp.483-490
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    • 2021
  • In order to learn an existing song and create a new song using an artificial neural network, it is necessary to convert the song into numerical data that the neural network can recognize as a preprocessing process, and one-hot encoding has been used until now. In this paper, we proposed a note embedding method using notes as a basic unit and a bar embedding method that uses the bar as the basic unit, and compared the performance with the existing one-hot encoding. The performance comparison was conducted based on quantitative evaluation to determine which method produced a song more similar to the song composed by the composer, and quantitative evaluation methods used in the field of natural language processing were used as the evaluation method. As a result of the evaluation, the song created with bar embedding was the best, followed by note embedding. This is significant in that the note embedding and bar embedding proposed in this paper create a song that is more similar to the song composed by the composer than the existing one-hot encoding.

Database Generation and Management System for Small-pixelized Airborne Target Recognition (미소 픽셀을 갖는 비행 객체 인식을 위한 데이터베이스 구축 및 관리시스템 연구)

  • Lee, Hoseop;Shin, Heemin;Shim, David Hyunchul;Cho, Sungwook
    • Journal of Aerospace System Engineering
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    • v.16 no.5
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    • pp.70-77
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    • 2022
  • This paper proposes database generation and management system for small-pixelized airborne target recognition. The proposed system has five main features: 1) image extraction from in-flight test video frames, 2) automatic image archiving, 3) image data labeling and Meta data annotation, 4) virtual image data generation based on color channel convert conversion and seamless cloning and 5) HOG/LBP-based tiny-pixelized target augmented image data. The proposed framework is Python-based PyQt5 and has an interface that includes OpenCV. Using video files collected from flight tests, an image dataset for airborne target recognition on generates by using the proposed system and system input.

Analysis of Fish Activity in Relation to Feeding Events Using Infrared Cameras (적외선 카메라를 활용한 급이 유무에 따른 어류 활동성 분석)

  • Roh, Tae Kyoung;Ha, Sang Hyun;Kim, Ki Hwan;Kang, Young Jin;Jeong, Seok Chan
    • The Journal of Information Systems
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    • v.32 no.4
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    • pp.137-147
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    • 2023
  • Purpose The domestic aquaculture industry in South Korea utilizes both formulated feeds and live feeds for the cultivation of fish. While nutrient-rich live feeds, particularly using fry, have been preferred since the past, formulated feeds are gaining attention due to issues related to overfishing and environmental concerns. Formulated feeds are advantageous for storage and supply but require a sustained feeding regimen due to the comparatively slower growth rate compared to live feeds. As the aging population in rural areas leads to a shortage of labor, automated feeding systems are increasingly being adopted in aquaculture facilities. To enhance the efficiency of such systems, it is crucial to quantitatively analyze the behavioral changes in fish based on the presence or absence of feed. Design/methodology/approach In the study, RGB cameras and infrared cameras were used to analyze fish activity according to feeding, and an outline extraction algorithm was applied to analyze the differences resulting from this. Findings Unlike RGB cameras, infrared cameras are more suitable for analyzing underwater fish activity as they convert objects' thermal energy into images. It was observed that Canny, Sobel, and Prewitt filters showed the most distinct identification of fish activity.

A Study of Standard eBook Contents Conversion (전자책 표준간의 컨텐츠 변환에 관한 연구)

  • Ko, Seung-Kyu;Sohn, Won-Sung;Lim, Soon-Bum;Choy, Yoon-Chul
    • The KIPS Transactions:PartD
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    • v.10D no.2
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    • pp.267-276
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    • 2003
  • Many countries have established eBook standards adequate to their environments. In USA, OEB PS is announced for distribution and display of eBooks, in Japan, JepaX is announced for storage and exchange, and in Korea, EBKS is made for clear exchange of eBook contents. These diverse objectives lead to different content structures. These variety of content structure will cause a problem in exchanging them. To correctly exchange eBook contents, the content structure should be considered. So, In this paper, we study conversion methods of standard eBooks contents based on Korean eBook standard, with contemplating content structure. To convert contents properly, the mapping relations should be clearly defined. For this, we consider standard's structure and extension mechanisms, and use path notations and namespaces for precise description. Moreover, through analysis of each mapping relationships, we classify conversion cases into automatic, semi-automatic, and manual conversions. Finally we write up conversion scripts and experiment with them.

Estimation of Daily Maximum/Minimum Temperature Distribution over the Korean Peninsula by Using Spatial Statistical Technique (공간통계기법을 이용한 전국 일 최고/최저기온 공간변이의 추정)

  • 신만용;윤일진;서애숙
    • Korean Journal of Remote Sensing
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    • v.15 no.1
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    • pp.9-20
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    • 1999
  • The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

Deep learning-based speech recognition for Korean elderly speech data including dementia patients (치매 환자를 포함한 한국 노인 음성 데이터 딥러닝 기반 음성인식)

  • Jeonghyeon Mun;Joonseo Kang;Kiwoong Kim;Jongbin Bae;Hyeonjun Lee;Changwon Lim
    • The Korean Journal of Applied Statistics
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    • v.36 no.1
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    • pp.33-48
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    • 2023
  • In this paper we consider automatic speech recognition (ASR) for Korean speech data in which elderly persons randomly speak a sequence of words such as animals and vegetables for one minute. Most of the speakers are over 60 years old and some of them are dementia patients. The goal is to compare deep-learning based ASR models for such data and to find models with good performance. ASR is a technology that can recognize spoken words and convert them into written text by computers. Recently, many deep-learning models with good performance have been developed for ASR. Training data for such models are mostly composed of the form of sentences. Furthermore, the speakers in the data should be able to pronounce accurately in most cases. However, in our data, most of the speakers are over the age of 60 and often have incorrect pronunciation. Also, it is Korean speech data in which speakers randomly say series of words, not sentences, for one minute. Therefore, pre-trained models based on typical training data may not be suitable for our data, and hence we train deep-learning based ASR models from scratch using our data. We also apply some data augmentation methods due to small data size.

Mobile Contents Transformation System Research for Personalization Service (개인화 서비스를 위한 모바일 콘텐츠 변환 시스템 연구)

  • Bae, Jong-Hwan;Cho, Young-Hee;Lee, Jung-Jae;Kim, Nam-Jin
    • Journal of Intelligence and Information Systems
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    • v.17 no.2
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    • pp.119-128
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    • 2011
  • The Sensor technology and portable device capability able to collect recent user information and the information about the surrounding environment haven been highly developed. A user can be made use of various contents and the option is also extending with this technology development. In particular, the initial portable device had simply a call function, but now that has evolved into 'the 4th screen' which including movie, television, PC ability. also, in the past, a portable device to provided only the services of a SMS, in recent years, it provided to interactive video service, and it include technology which providing various contents. Also, it is rising as media which leading the consumption of contents, because it can be used anytime, anywhere. However, the contents available for the nature of user's handheld devices are limited. because it is very difficult for making the contents separately according to various device specification. To find a solution to this problem, the study on one contents from several device has been progressing. The contents conversion technology making use of the profile of device out of this study comes to the force and profile study has been progressing for this. Furthermore, Demand for a user is also increased and the study on the technology collecting, analyzing demands has been making active progress. And what is more, Grasping user's demands by making use of this technology and the study on the technology analyzing, providing contents has been making active progress as well. First of all, there is a method making good use of ZigBee, Bluetooth technology about the sensor for gathering user's information. ZigBee uses low-power digital radio for wireless headphone, wireless communication network, and being utilized for smart energy, automatic home system, wireless communication application and wireless sensor application. Bluetooth, as industry standards of PAN(Personal Area Networks), is being made of use of low power wireless device for the technology supporting data transmission such as drawing file, video file among Bluetooth device. With analyzing the collected information making use of this technology, it utilizes personalized service based on network knowledge developed by ETRI to service contents tailor-made for a user. Now that personalized service builds up network knowledge about user's various environments, the technology provides context friendly service constructed dynamically on the basis of this. The contents to service dynamically like this offer the contents that it converses with utilizing device profile to working well. Therefore, this paper suggests the system as follow. It collects the information, for example of user's sensitivity, context and location by using sensor technology, and generates the profile as a means of collected information as sensor. It collects the user's propensity to the information by user's input and event and generates profile in the same way besides the gathered information by sensor. Device transmits a generated profile and the profile about a device specification to proxy server. And proxy server transmits a profile to each profile management server. It analyzes profile in proxy server so that it selects the contents user demand and requests in contents server. Contents server receives a profile of user portable device from device profile server and converses the contents by using this. Original source code of contents convert into XML code using the device profile and XML code convert into source code available in user portable device. Thus, contents conversion process is terminated and user friendly system is completed as the user transmits optimal contents for user portable device.

An Algorithm for Translation from RDB Schema Model to XML Schema Model Considering Implicit Referential Integrity (묵시적 참조 무결성을 고려한 관계형 스키마 모델의 XML 스키마 모델 변환 알고리즘)

  • Kim, Jin-Hyung;Jeong, Dong-Won;Baik, Doo-Kwon
    • Journal of KIISE:Databases
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    • v.33 no.5
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    • pp.526-537
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    • 2006
  • The most representative approach for efficient storing of XML data is to store XML data in relational databases. The merit of this approach is that it can easily accept the realistic status that most data are still stored in relational databases. This approach needs to convert XML data into relational data or relational data into XML data. The most important issue in the translation is to reflect structural and semantic relations of RDB to XML schema model exactly. Many studies have been done to resolve the issue, but those methods have several problems: Not cover structural semantics or just support explicit referential integrity relations. In this paper, we propose an algorithm for extracting implicit referential integrities automatically. We also design and implement the suggested algorithm, and execute comparative evaluations using translated XML documents. The proposed algorithm provides several good points such as improving semantic information extraction and conversion, securing sufficient referential integrity of the target databases, and so on. By using the suggested algorithm, we can guarantee not only explicit referential integrities but also implicit referential integrities of the initial relational schema model completely. That is, we can create more exact XML schema model through the suggested algorithm.

A study on user defined spoken wake-up word recognition system using deep neural network-hidden Markov model hybrid model (Deep neural network-hidden Markov model 하이브리드 구조의 모델을 사용한 사용자 정의 기동어 인식 시스템에 관한 연구)

  • Yoon, Ki-mu;Kim, Wooil
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.2
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    • pp.131-136
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    • 2020
  • Wake Up Word (WUW) is a short utterance used to convert speech recognizer to recognition mode. The WUW defined by the user who actually use the speech recognizer is called user-defined WUW. In this paper, to recognize user-defined WUW, we construct traditional Gaussian Mixture Model-Hidden Markov Model (GMM-HMM), Linear Discriminant Analysis (LDA)-GMM-HMM and LDA-Deep Neural Network (DNN)-HMM based system and compare their performances. Also, to improve recognition accuracy of the WUW system, a threshold method is applied to each model, which significantly reduces the error rate of the WUW recognition and the rejection failure rate of non-WUW simultaneously. For LDA-DNN-HMM system, when the WUW error rate is 9.84 %, the rejection failure rate of non-WUW is 0.0058 %, which is about 4.82 times lower than the LDA-GMM-HMM system. These results demonstrate that LDA-DNN-HMM model developed in this paper proves to be highly effective for constructing user-defined WUW recognition system.

Study on the Projectile Velocity Measurement Using Eddy Current Probe (와전류 탐촉자를 이용한 총구 탄속 측정에 관한 연구)

  • Shin, Jungoo;Son, Derac
    • Journal of the Korean Magnetics Society
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    • v.25 no.3
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    • pp.83-86
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    • 2015
  • Nowadays the weapon systems are employed air bursting munition (ABM) as smart programmable 40 mm shells which have been developed in order to hit the target with programmed munition that can be air burst after a set distance in the battlefield. In order to improve the accuracy of such a bursting time, by measuring the speed of the munition from the barrel, weapon systems calculate the exact time of flight to the target and then the time information must be inputted to the munition. In this study, we introduce a device capable of detecting a shot at K4 40 mm automatic grenade. The shot is composed of a rotating copper band to convert linear motion into rotary motion when it passes through the barrel, the steel section is exert the effect of fragment and aluminum section to give fuze information. The aluminum section was used to detect munition using eddy current method. To measure muzzle velocity by means of non-contact method, two eddy current probes separated 10 cm was employed. Time interval between two eddy current probe detection times was used as muzzle velocity. The eddy current probe was fabricated U-shape Mn-Zn ferrite core with enamelled copper wire, and 200 kHz alternating current was used to detect inductance change. Measured muzzle velocity using the developed sensor was compared to the Doppler radar system. The difference was smaller than 1%.