• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.1-7
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• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2337-2342
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• 2010

There is a vast field of application for RFID(Radio Frequency IDentification) technology. In the case of hospitals, RFID can be used for organizing patient data. Generally, patient data has been handled with medical cards. In order to look up data about a patient, the medical card would have to be found first, within a lot of other medical cards, by hand or with a computer. This is a very inconvenient system. Also, if the card is searched by the name of the patient, fatal medical accidents may occur in cases of mix-ups. If remote RFID Tag monitoring systems are applied in this case, the patient data would be accessible in the hospital. This article will discuss the grafting of RFID systems and wireless data communicating technology. The EM4095 chip, which uses 125KHz carrier waves was used in this study. And a Bluetooth module was added for wireless data communication. The ATMEGA128 microcomputer was used to control the RFID system and wireless module. A LCD monitor was connected to the extension port for nurses to view patient data, and also, the same information was displayed on PC monitors for doctors to see. The circuit was designed to consume minimal amounts of electricity for portability, and to transmit Tag ID's in environments with a lot of noise. The article is concluded with a diagram of the whole system, and performance of each data transmitting section has been analyzed.

• Analytical Science and Technology
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• v.14 no.5
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• pp.432-441
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• 2001

An automated on-line portable preconcentration-short column gas chromatograph was developed, which used preconcentrator using adsorption tube with Tenax-GR and Curie-point heating. The developed system operated with 3 steps of processing, preconcentration, thermal desorption, and analysis and cleaning, and could continued operating within 1~2 min cycle. The recoveries of preconcentrator for toluene was ranged between $94.7{\pm}6.6%$ and $103.8{\pm}3.1%$ with less than 7% of RSD. For benzene, toluene and xylene(BTX) standard gas test, IDL was 41, 49, $472ng/m^3$ benzene, toluene and o-xylene, respectively. The BTX mixture was analyzed within 30 sec with baseline separation by the system equipped with 4 m long capillary column. The deficiency of separation power caused by short column was solved by the control of sample injection volume and inlet/outlet pressure ratio. The automated portable preconcentration-short column gas chromatograph system was found to be useful for the continuous air monitoring of BTX at ppb levels in ambient air.

• Journal of Radiation Protection and Research
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• v.45 no.3
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• pp.117-129
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• 2020

Background: Radiation portal monitors (RPMs) involving plastic scintillators installed at the border inspection sites can detect illicit trafficking of radioactive sources in cargo containers within seconds. However, RPMs may generate false alarms because of the naturally occurring radioactive materials. To manage these false alarms, we previously suggested an energy-weighted algorithm that emphasizes the Compton-edge area as an outstanding peak. This study intends to evaluate the identification of radioactive sources using an improved energy-weighted algorithm. Materials and Methods: The algorithm was modified by increasing the energy weighting factor, and different peak combinations of the energy-weighted spectra were tested for source identification. A commercialized RPM system was used to measure the energy-weighted spectra. The RPM comprised two large plastic scintillators with dimensions of 174 × 29 × 7 ㎤ facing each other at a distance of 4.6 m. In addition, the in-house-fabricated signal processing boards were connected to collect the signal converted into a spectrum. Further, the spectra from eight radioactive sources, including special nuclear materials (SNMs), which were set in motion using a linear motion system (LMS) and a cargo truck, were estimated to identify the source identification rate. Results and Discussion: Each energy-weighted spectrum exhibited a specific peak location, although high statistical fluctuation errors could be observed in the spectrum with the increasing source speed. In particular, ¹³⁷Cs and ⁶⁰Co in motion were identified completely (100%) at speeds of 5 and 10 km/hr. Further, SNMs, which trigger the RPM alarm, were identified approximately 80% of the time at both the aforementioned speeds. Conclusion: Using the modified energy-weighted algorithm, several characteristics of the energy weighted spectra could be observed when the used sources were in motion and when the geometric efficiency was low. In particular, the discrimination between ⁶⁰Co and ⁴⁰K, which triggers false alarms at the primary inspection sites, can be improved using the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.32-40
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• 2015

In this paper, the optimum antenna placement is analyzed by considering the interference between airborne antennas mounted on the unmanned aerial vehicle(UAV). The analysis is implemented by selecting the antennas that the distance and operational frequency band between airborne antennas is close to each other among the omni-directional antennas. The analyzed antennas are the control datalink, TCAS(Traffic Collision & Avoidance System), IFF(Identification Friend or Foe), GPS(Global Positioning System), and RALT(Radar ALTimeter) antennas. There are three steps for the optimum antenna placement analysis. The first step is selecting the antenna position having the optimum properties by monitoring the variation of radiation pattern and return loss by the fuselage of UAV after selecting the initial antenna position considering the antenna use, type, and radiation pattern. The second one is analyzing the interference strength between airborne antennas considering the coupling between airborne antennas, spurious of transmitting antenna, and minimum receiving level of receiving antenna. In case of generating the interference, the antenna position without interference is selected by analyzing the minimum separation distance without interference. The last one is confirming the measure to reject the frequency interference by the frequency separation analysis between airborne antennas in case that the intereference is not rejected by the additional distance separation between airborne antennas. This analysis procedure can be efficiently used to select the optimum antenna placement without interference by predicting the interference between airborne antennas in the development stage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.541-550
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• 2014

This paper describes a multi-scale user interaction based tiled display visualization system using multiple input devices for monitoring and analyzing Geostationary Ocean Color Imager (GOCI) observation satellite imagery. This system provides multi-touch screen, Kinect motion sensing, and moblie interface for multiple users to control the satellite imagery either in front of the tiled display screen or far away from a distance to view marine environmental or climate changes around Korean peninsular more effectively. Due to a large amount of memory required for loading high-resolution GOCI satellite images, we employed the multi-level image load technique where the image was divided into small tiled images in order to reduce the load on the system and to be operated smoothly by user manipulation. This system performs the abstraction of common input information from multi-user Kinect motion and gestures, multi-touch points and mobile interaction information to enable a variety of user interactions for any tiled display application. In addition, the unit of time corresponding to the selected date of the satellite images are sequentially displayed on the screen and multiple users can zoom-in/out, move the imagery and select buttons to trigger functions.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.727-737
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• 1999

프로세스 중심 소프트웨어 개발 환경(PSEE : Process-centered Software Engineering Environment)은 소프트웨어 개발자를 위한 여러가지 정보의 제공과 타스크의 수행, 소프트웨어 개발 도구의 수행 및 제어, 필수적인 규칙이나 업무의 수행등과 같은 다양한 행위를 제공하는 프로세스 모형의 수행을 통하여 소프트웨어 개발 행위를 지원한다. SEED(Software Engineering Environment for Development)는 효율적인 소프트웨어 개발과 프로세스 모형의 수행을 제어하기 위해 ETRI에서 개발된 PSEE이다.본 논문에서는 SEED에서 프로세스 모형을 설계하기 위해 사용되는 SimFlex 프로세스 프로그래밍 언어와, 수행지원시스템인 SEED Engine의 구현에 대하여 기술한다. SimFlex는 간단한 언어 구조를 가진 프로세스 프로그래밍 언어이며, 적절한 적합화를 통하여 다른 PSEE에서 사용될 수 있다. SimFlex 컴파일러는 SimFlex에 의해 기술된 프로세스 모형을 분석하고, 모형의 오류를 검사하며, SEED Engine에 의해 참조되는 중간 프로세스 모형을 생성한다. 중간 프로세스 모형을 사용하여 SEED Engine은 외부 모니터링 도구와 연관하여 사용자를 위한 유용한 정보뿐만 아니라 SimFlex에 의해 기술된 프로세스 모형의 자동적인 수행을 제공한다. SimFlex 언어와 수행지원 시스템의 지원을 통하여 소프트웨어 프로세스를 모형화하는데 드는 비용과 시간을 줄일 수 있으며, 편리하게 프로젝트를 관리하여 양질의 소프트웨어 생산물을 도출할 수 있다. Abstract Process-centered Software Engineering Environments(PSEEs) support software development activities through the enaction of process models, providing a variety of activities such as supply of various information for software developers, automation of routine tasks, invocation and control of software development tools, and enforcement of mandatory rules and practices. The SEED(Software Engineering Environment for Development) system is a PSEE which was developed for effective software process development and controlling the enactment of process models by ETRI.In this paper, we describe the implementation of the SimFlex process programming language used to design process models in SEED, and its runtime support system called by SEED Engine. SimFlex is a software process programming language to describe process models with simple language constructs, and it could be embedded into other PSEEs through appropriate customization. The SimFlex compiler analyzes process models described by SimFlex, check errors in the models, and produce intermediate process models referenced by the SEED Engine. Using the intermediate process models, the SEED Engine provides automatic enactment of the process models described by SimFlex as well as useful information for agents linked to the external monitoring tool. With the help of the SimFlex language and its runtime support system, we can reduce cost and time in modeling software processes and perform convenient project management, producing well-qualified software products.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.472-478
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• 2021

Background: The Legionella case detection and notification rate have increased in public artificial water environments where people visit, including large buildings, public baths, and hospitals. Objectives: In this study, the distribution of Legionella and its epidemiologic characteristics were analyzed in the water systems of public facilities in Chungcheongnam-do Province in South Korea. Methods: Culture and PCR analysis were performed on 2,991 environmental water system samples collected from 2017 to 2019, and associations with year, facilities, seasons, and temperature of water system were statistically analyzed by using R-Studio for Windows. Descriptive data was compared using chi-square tests and independent t-tests. Results: The detection rate of Legionella increased from 3.1% in 2017 to 10.3% in 2019, appearing most frequently in the order of public baths, large-scale buildings, hospitals, and apartments. It was detected mainly in summer from June to August, over 1.0×10³ CFU/L on average in 133 cases (66.5%). Lots of germs were detected in bathtub water, cooling tower water, and warm water (p<0.001), and it was detected at higher rates in the cities where multipurpose facilities were concentrated than in rural areas (p=0.018). Conclusions: This study suggests that continuous monitoring and control are required for Legionella in the water system environment of high risk facilities. Moreover, these results will be helpful to prepare efficient management plans to prevent the Legionellosis that occurs in Chungcheongnam-do Province.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.