• 한국식품조리과학회지
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• 제30권6호
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• pp.792-799
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• 2014

This study was conducted to determine the optimal conditions of acetic acid fermentation of aronia using the response surface methodology (RSM). Alcohol content of aronia wine was 13.1% after alcohol fermentation of aronia fruits. The optimal conditions of acetic acid fermentation were determined by five levels of initial aronia alcohol content, initial acetic acid content, and acetic acid bacteria, using the central composite design. The acetic acid yields, residual alcohol contents, pH, and color values (L, a, b) of acetic acid fermentation products were very significantly different ($p{\leq}0.01$), and were 26.34~57.82 g/L, 0.80~1.53%, 3.19~3.43, 47.58~71.00, 31.77~51.15, and 18.45~48.57, respectively. For the results, the optimal conditions of acetic acid fermentation of aronia were 7.78% of the initial alcohol concentration, 1.58% of the initial acetic acid, and 19.39% of the acetic acid bacteria.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1471-1478
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• 2016

In this study, the system to manage the power automatically was implemented by using Arduino, Raspberry pi, and Beacon technologies. Before the research, pre-research was carried out with the analysis on the existing power management systems in the market in order to find a solution to reduce burdens from standby power and power waste with the increase of electric charges. The system is designed to be able to deliver and receive data through IEEE 802.15.4 wireless protocol, by using Xbee module. Arduino was tested to verify whether it is able to control SSR(Solid State Relay), and it was found that there is no problem. Meanwhile, it was also tested whether it is possible to organize a star topology network through Arduino and Raspberry Pi, and it was confirmed that normal wireless communication is possible through IEEE 802.15.4 wireless protocol. It is designed that the signal from Android smartphone application is to be delivered to Raspberry Pi and then, to be delivered to Arduino through Xbee so that Arduino could control SSR. In addition to this, wireless protocol required to control Arduino with Raspberry Pi is also designed and applied to this research.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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• pp.129-131
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• 2019

본 논문에서는 다양한 아두이노 무선센서 모듈과 Raspberry Pi, 웹서버를 이용한 IOT 기반 환경정보 수집 시스템을 구현하고, 상품추천시스템을 제안한다. 이 시스템은 사용자가 주변 환경의 데이터를 정확하게 확인하고 활용할 수 있도록 한다. 상품추천 시스템에서는 상점 외부에 부착된 다양한 무선센서 모듈들을 이용해 상점 주변의 환경데이터를 수집하고, 무선통신을 통해 Raspberry Pi로 데이터를 전송한다. 전송된 데이터는 Server로 보내져 Server DB에 저장되고 Server에서 센서값들의 평균값을 계산해 Raspberry Pi로 다시 보내주면 Raspberry Pi에 연결된 모니터를 통해 실시간으로 주변의 데이터와 주변 상황에 맞는 경고 메시지를 보여주고, 이후 필요한 물건을 추천해준다.

• International Journal of Industrial Entomology and Biomaterials
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• 제44권2호
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• pp.44-54
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• 2022

The food source of white-spotted flower chafer, Protaetia brevitarsis is important to economical performance. The P. brevitarsis larva were feed by mulberry and oak fermented sawdust. The effect of additional additives, Korean black raspberry (called bokbunja) marc and blueberry marc to fermented sawdust feed on the development and oviposition characteristics were investigated. The development periods of P. brevitarsis was decreased from 165.7 d to 40.0 d (mulberry sawdust) and 169.3 d to 39.0 d (oak sawdust), but the survival rate of larva was not affected by the addition of Korean black raspberry marc to fermented sawdust. However, blueberry marc addition to the fermented sawdust did not significant effect on the development period and survival rate of P. brevitarsis. The percentage of larva weight over 2.5 g was tend to increase by addition of Korean black raspberry marc and/or blueberry marc. The number of oviposition was also tend to increase by adding additional feed to sawdust but there was no significant different.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.205-207
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• 2021

IoT 장치를 개발하는 방법은 응용이 요구하는 센서를 아두이노나 라즈베이 파이 같은 플랫폼에 장착하고 그 센서의 드라이버와 응용을 작성하는 것이다. 이때 그 센서를 위한 구동 드라이버가 이미 작성되어 있고 응용에서 그 드라이버를 표준화된 API로 접근할 수 있다면 센서의 Plug&Play가 가능할 것이다. 이를 위한 과거의 방식은 센서 인터페이스가 너무 복잡하여 현재의 플랫폼에서는 사용하기 어렵다. 본 논문에서는 USB단자를 갖는 표준화된 센서와 드라이버가 라즈베리 파이에 Plug되면 자동으로 드라이버가 설치되는 기법을 제안한다. 응용 개발자는 센서 드라이버는 고민하지 않고 Linux의 파일 접근 API로 센서 값을 얻을 수 있다. 제안된 기법은 현재 라즈베리-파이 상에서 구현 중이다.

• 원예과학기술지
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• 제32권1호
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• pp.115-122
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• 2014

유용성분 함량이 많고 생리기능성이 우수한 산딸기 품종의 육성을 위해 국내 농가에서 재배되고 있는 7종의 산딸기와 야생에서 자생하는 2종의 산딸기를 복분자 연구소에서 재배한 후 이들을 대상으로 과실의 품질특성, 유용성분의 함량, 항산화능을 측정하였다. 충남 아산의 야생 산딸기가 크기는 작았지만 당도는 16.20%로 시료 산딸기 중 가장 높고 산도는 가장 낮았다. 경북 울릉도의 야생 산딸기는 작은 크기에 당도 및 산도가 매우 낮아 과실로서의 이용가치는 매우 낮았으나, 총 페놀성 화합물과 ellagic acid 함량은 각각 182.97, $55.25mg{\cdot}100g^{-1}FW$로 시료 중 가장 높았다. 경남 김해에서 재배되는 산딸기 중 '왕딸'은 크기가 크고 당도는 12.80%로 다소 낮은 반면, 품종이 불명확한 다른 산딸기는 야생 산딸기 정도로 크기는 작지만 당도는 14.4%로 '왕딸' 보다 높았다. 김해 지역에서 재배되는 '왕딸'과 품종이 불명확한 산딸기의 총 페놀성 화합물(159.62, $165.94mg{\cdot}100g^{-1}FW$) 및 ellagic acid(45.7, $52.1mg{\cdot}100g^{-1}FW$) 함량은 울릉도 야생 산딸기보다 낮았으나, 총 플라보노이드 화합물(14.28, $14.90mg{\cdot}100g^{-1}FW$)과 총 안토시아닌(28.69, $30.48mg{\cdot}100g^{-1}FW$) 함량은 이보다 높았다. 경북 울릉도 야생 산딸기, 김해 지역의 '왕딸' 및 품종이 불명확한 산딸기는 FRAP법에 의한 항산화능과 DPPH 및 ABTS radical 소거능도 다른 품종의 산딸기보다 현저하게 높아 육종 소재 및 기능성 성분 소재로서의 이용 가치가 높은 것으로 사료된다.

• International journal of advanced smart convergence
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• 제6권1호
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• pp.44-49
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• 2017

In the modern technology era, it is possible to connect objects and the internet anytime and anywhere through IoT of hyper-connected society. Accordingly, a smart shopping cart was designed and realized by applying IoT. Therefore, this paper builds the IoT shopping cart system according to the trend of IoT environment.. When RFID is installed in the Arduino and the tagged item is inserted into the IoT shopping cart, the product information and price are displayed on the Arduino linked Raspberry Pi. We built a web server on the Raspberry Pi to handle this data, and built an App on the smartphone to implement the IoT shopping cart environment. Consumers can receive pricing and product information through smartphone apps through raspberry pie, can make quick calculations through smartphone, and provide various information to consumers through apps.

• 한국환경과학회지
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• 제25권10호
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• pp.1389-1396
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• 2016

A monitoring system for a field magnetometer was configured with assistance of a Raspberry Pi as a data logger. The suggested geomagnetic system uses a semi-real-time data transmission module. The system consists of two parts: a field-observation part and a data-center part. The field-observation part comprises a Raspberry Pi, magnetometer, LTE router, and power source, while the data center part takes samples at the site. The collected magnetometer data are then sent to the data center through the LTE router. The newly designed monitoring system was deployed and checked in Jeju-do island, and found to operate stably. The suggested system is promising in that it is simple and cost saving, providing at least physical insight and knowledge on the complex natural phenomena.

• International Journal of Advanced Culture Technology
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• 제5권1호
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• pp.70-75
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• 2017

Recent development of IT industry including smart phones and communication technologies has resulted in rapid growth of Internet of Things (IoT) technology and relevant markets. The access to IoT is becoming easier thanks to the boards and IoT products, such as Arduino and Raspberry Pi. Large-scale business sites use IoT technology to manage inventories, but small-scale business sites do not. In the present study, We ported Linux-based Raspbian to Raspberry Pi, It utilizes web server communication to control the Arduino through the application We used a color sensor to figure out the kind of inventory. We also built a database using MySQL to store the data. We used raspberry pi to check whether the proposed system works and apply it to small-scale business.

• 수산해양교육연구
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• 제28권2호
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• pp.376-383
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• 2016

In this paper, the blue-green algae monitoring program of applying IoT(Internet of things) technologies is designed and implemented that can check out the status of the river's water quality in real time. The proposed system is to extract the image data from the camera of raspberry pi by an wireless network, and it is analyzed through the HSV color model. We measure the temperature using a DS18B20 1-wire temperature sensor. The extracted information of image data and temperature is then analyzed in C and Python programs for use with Raspberry Pi. The XML data in PHP program is made from the analyzed information and provides Web services. It also allows to refer the XML data using mobile devices.