• Title/Summary/Keyword: Source recognition

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Effects of Local Food Value Perception on Purchasing and Experience (로컬푸드에 대한 가치인식이 구매 및 체험에 미치는 영향)

  • Weon, Mi-Keyoung;Park, Young-Hee;Lee, Yeon-Jung
    • Journal of the Korean Society of Food Culture
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    • v.30 no.1
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    • pp.54-63
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    • 2015
  • This study was conducted to examine the effects of local food value perception on purchasing and experience in consumers. ${\chi}^2$-test, ANOVA, and linear regression analysis were conducted. The findings are summarized as follows: The most common place for buying agricultural products was 'hypermarkets' (41.7%), and the most important factor for purchasing local food was 'local government's certification products' (23.7%). The most important value recognition item for local food was 'I think that local food is a high-quality agricultural products'. (3.74 points), followed by 'I think that local food have a value of respect for customers' (3.61 points) and 'I have a faith for the local food'. (3.61 points) in that order. The main tourism experience activity was 'food experience' (49.0%), and information source of local food experience tourism was 'mass media (TV, newspapers, etc.)' (37.3%). As age increased, experience of local food also increased. The most effectual value recognition item for purchasing local food was 'I think that local food have a value of respect for customers'. The most effectual value recognition item for increasing intake experience of local food was 'I think that the local food is high-quality agricultural products'.

HearCAM Embedded Platform Design (히어 캠 임베디드 플랫폼 설계)

  • Hong, Seon Hack;Cho, Kyung Soon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.4
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    • pp.79-87
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    • 2014
  • In this paper, we implemented the HearCAM platform with Raspberry PI B+ model which is an open source platform. Raspberry PI B+ model consists of dual step-down (buck) power supply with polarity protection circuit and hot-swap protection, Broadcom SoC BCM2835 running at 700MHz, 512MB RAM solered on top of the Broadcom chip, and PI camera serial connector. In this paper, we used the Google speech recognition engine for recognizing the voice characteristics, and implemented the pattern matching with OpenCV software, and extended the functionality of speech ability with SVOX TTS(Text-to-speech) as the matching result talking to the microphone of users. And therefore we implemented the functions of the HearCAM for identifying the voice and pattern characteristics of target image scanning with PI camera with gathering the temperature sensor data under IoT environment. we implemented the speech recognition, pattern matching, and temperature sensor data logging with Wi-Fi wireless communication. And then we directly designed and made the shape of HearCAM with 3D printing technology.

A Low-Cost Speech to Sign Language Converter

  • Le, Minh;Le, Thanh Minh;Bui, Vu Duc;Truong, Son Ngoc
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.37-40
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    • 2021
  • This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.

Development of Color Recognition Algorithm for Traffic Lights using Deep Learning Data (딥러닝 데이터 활용한 신호등 색 인식 알고리즘 개발)

  • Baek, Seoha;Kim, Jongho;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.2
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    • pp.45-50
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    • 2022
  • The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

Development of deep learning-based rock classifier for elementary, middle and high school education (초중고 교육을 위한 딥러닝 기반 암석 분류기 개발)

  • Park, Jina;Yong, Hwan-Seung
    • Journal of Software Assessment and Valuation
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    • v.15 no.1
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    • pp.63-70
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    • 2019
  • These days, as Interest in Image recognition with deep learning is increasing, there has been a lot of research in image recognition using deep learning. In this study, we propose a system for classifying rocks through rock images of 18 types of rock(6 types of igneous, 6 types of metamorphic, 6 types of sedimentary rock) which are addressed in the high school curriculum, using CNN model based on Tensorflow, deep learning open source framework. As a result, we developed a classifier to distinguish rocks by learning the images of rocks and confirmed the classification performance of rock classifier. Finally, through the mobile application implemented, students can use the application as a learning tool in classroom or on-site experience.

Clustering Red Wines Using a Miniature Spectrometer of Filter-Array with a Cypress RGB Light Source

  • Choi, Kyung-Mee
    • The Korean Journal of Applied Statistics
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    • v.23 no.1
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    • pp.179-187
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    • 2010
  • Miniature spectrometers can be applied for various purposes in wide areas. This paper shows how a wellmade spectrometer on-a-chip of a low performance and low-cost filter-array can be used for recognizing types of red wine. Light spectra are processed through a filter-array of a spectrometer after they have passed through the wine in the cuvettes. Without recovering the original target spectrum, pattern recognition methods are introduced to detect the types of wine. A wavelength cross-correlation turns out to be a good distance metric among spectra because it captures their simultaneous movements and it is affine invariant. Consequently, a well-designed spectrometer is reliability in terms of its repeatability.

Reliable Sound Source Localization for Human Robot Interaction

  • Kim, Hyun-Don;Choi, Jong-Suk;Lee, Chang-Hoon;Kim, Mun-Sang
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1820-1825
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    • 2004
  • In this paper, we propose a humanoid active audition system which detects the direction of sound and performs speech recognition using just three microphones. Compared with previous researches, this system comprises simpler algorithm and better amplifier system having advantages to increase a detectible distance of sound signal in spite of simple circuit. In order to verify our system's performance, we install the proposed active audition system to the home service robot, called Hombot II, which has been developed at the KIST (Korea Institute of Science and Technology), thus we confirm excellent performance by experimental results

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Image Objects Detection Method for the Embedded System (임베디드 시스템을 위한 영상객체의 검출방법)

  • Kim, Yun-Il;Rho, Seung-Ryong
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.4
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    • pp.420-425
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    • 2009
  • In this paper, image detection and recognition algorithms are studied with respect to embedded carrier system. There are many suggested techniques to detect and recognize objects. But they have the propensity to need much calculation for high hit rate. Advanced and modified method needs to study for embedded systems that low power consumption and real time response are requested. The proposed methods were implemented using Intel(R) Open Source Computer Vision Library provided by Intel Corporation. And they run and tested on embedded system using a ARM920T processor by cross-compiling. They showed 1.6sec response time and 95% hit rate and supported the automated moving carrier system smoothly.

The Recognition of Energized & Deenergized System Using System Matrix in Expert system (전문가 시스템에서의 system matrix를 이용한 정전 및 비정전구간 인식)

  • Ham, W.K.;Chu, J.B.;Kim, K.J.;Sim, K.J.;Jo, H.H.
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.237-240
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    • 1989
  • This paper deals with the expert system for power system recognition of energized and deenergized system using circuit breaker information. The basic idea is isolating the system with the system matrix representing the system configuration and the states of the circuit breakers. The knowledge base is composed of these isolated systems and decision rules. The isolated system with the sources is recognized as the energized system and the system without the source as the deenergized system. The rules use the system matrix and the the inference scheme is simplified in a great deal. Above all, the overall searching labor of the rules is independent on the system size and it is possible to expand into the real system and the real time restoration can be carried out easily. The expert system is written in PROLOG.

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Family Life Issues of Married Womens in Chonbuk: Focused on Family Life Problems & Solution (전라북도 거주 기혼여성의 가족생활실태조사(II): 가족생활문제 및 해결방안을 중심으로)

  • 이성희
    • Journal of the Korean Home Economics Association
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    • v.38 no.8
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    • pp.53-68
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    • 2000
  • This study examines family life problems & solution of married women in Chonbuk area as a part of study on family life Issues. Data were collected by questionnaires. The sample consisted of 1142 married women. The major findings were summarized as follows : (1) The degree of recognition about family life problem is rated economic life > woman's parents-in-law> woman's real parents> spouse> children related problems. (2) In the family conflict solution types, the most used types is a rational. (3) The degree of recognition about the family violence is rated abusive languages of husband>husband behavior under the influence of alcohol wife's child abuse>husband's child abuse>abusive languages of wife>battered wife. (4) The kins are still considered the primary source for functions of personal support. Also, the needs for the children related equipments is higest among the public support equipments.

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