• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.229-230
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• 2024

최근 드론으로 극한 환경에서 범죄 수배자 및 실종자를 탐색하는 시도가 활발하다. 이때 생체 인증 기술인 얼굴 인증 기술을 사용하면 탐색 효율이 높아지지만, 암호화되지 않은 인증 프로토콜 적용 시 생체 정보 유출의 위험이 있다. 본 논문에서는 드론이 수집한 얼굴 이미지 템플릿을 암호화하여 안전하게 인증할 수 있는 효율적인 생체 인증 프레임워크인 DF-PPHDM(Privacy-Preserving Hamming Distance biometric Matching for Drone-collected Facial images)을 제안한다. 수집된 얼굴 이미지는 암호문 형태로 서버에 전달되며 서버는 기존 등록된 암호화된 템플릿과의 Hamming distance 분석을 통해 검증한다. 제안한 DF-PPHDM을 RaspberryPI 4B 환경에서 직접 실험하여 분석한 결과, 한정된 리소스를 소유한 드론에서 효율적인 구현이 가능하며, 인증 단계에서 7.83~155.03 ㎲ (microseconds)가 소요된다는 것을 입증하였다. 더불어 서버는 드론이 전송한 암호문으로부터 생체 정보를 복구할 수 없으므로 프라이버시 침해 문제를 예방할 수 있다. 향후 DF-PPHDM에 AI(Artificial Intelligence)를 결합하여 자동화 기능을 추가하고 코드 최적화를 통해 성능을 향상시킬 예정이다.

• Journal of Dairy Science and Biotechnology
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• v.32 no.1
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• pp.47-53
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• 2014

In this study, our aim was to investigate the changes in ginsenosides and polyphenols in red ginseng extract fermented by Lactobacillus acidophilus and to manufacture fresh cheese using fermented red ginseng extract. Red ginseng extract (3%, w/v) was fermented by L. acidophilus for 24 h. On performing lactic acid bacteria counts, we determined that L. acidophilus reached its maximum growth phase after 16 h; this was followed by decrease in growth. During fermentation, the levels of ginsenosides Rg3 (20S) and Rg3 (20R) as well as protopanaxadiol (20R), F1, and compound K increased, while those of s Rb2, Rd, Rf, and Rg1 decreased. The pH, titratable acidity, and viable cell counts in fresh cheese prepared using fermented red ginseng extract were measured during the storage period. The pH decreased over time, while titratable acidity and viable cell counts increased with increase in the duration of the storage period. Sensory tests showed that the overall sensory properties of fresh cheese prepared using 1% fermented red ginseng extract were similar to those of the control groups. This result suggests that L. acidophilus-fermented red ginseng has potential for development as a new bioactive material.

• Journal of Applied Biological Chemistry
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• v.59 no.4
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• pp.273-280
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• 2016

We investigated the contents of total phenols, anthocyanins, carotenoids and the antioxidant capacity of black carrot, black currant, acaiberry, black raspberry, and blueberry. We also examined the physical and organoleptic characteristics of pudding with added black carrot extract following 7 days of storage. Black carrot and black raspberry had the highest total phenols. Blueberry contained the highest anthocyanins and black currant equaled black carrot in carotenoids. Anti-oxidant capacity measured by 1,1-diphenyl-1,2-picrylhydrazyl and 2,2-azino-bis-3-ethyl-benthiazolin-6-sulfonic acid was highest in black raspberry and black currant followed closely by black carrot. In pudding, redness was increased and blueness decreased by adding black carrot extract, but the trend was partially reversed during 7-day storage due to oxidation of the anthocyanins, which are stable in acid situation. As black carrot extract contents were increased, pH value decreased. The pudding's hardness, adhesiveness, springiness, cohesiveness, gumminess and chewiness were optimal with 7.5 % black carrot extract. In conclusion, black carrot is moderately rich in anthocyanins and phenolic compounds. In pudding adding 7.5 % black carrot extract was optimal for organoleptic qualities. However, additional studies are needed to develop methods for protecting anthocyanins from breaking-down during storage of back carrot pudding.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• Korean Journal of Community Nutrition
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• v.8 no.3
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• pp.356-367
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• 2003

This study was to investigate the effects of a silk peptide, and prune and raspberry mixture on the body fat, serum lipid composition and fat distribution in Korean women during the time they received these supplements. During the 4 month period of this research (June to October, 2002), 75 women (average age 22.9 yr) were selected as subjects. Their nutrient intake was investigated by use of a questionnaire and the 24-hour recall method. Antropometric assessments of the subjects were investigated by using the SBIA Method (Segmental Bioimpedance Assay, Inbody 3.0). The results were as follows: their mean body weight was 59.3 kg, their mean body height was 161.7 cm and their mean Basal Metabolic Indices (BMI) was 22.7. The status of their dietary fiber intake significantly increased (p < 0.05) after use of the supplements. Their body fat significantly decreased following the $3^{rd}$ stage of supplementation (p < 0.05), and their percent of body fat signiflcantly decreased after supplementation (p < 0.05). Their triceps and suprailiac circumference significantly decreased following the $3^{rd}$ stage of supplementation (p < 0.05). Their waist circumferences and waist-hip ratios (WHR) significantly decreased after both the $2^{nd}$and $3^{rd}$ stage of supplementation (p < 0.05). Their total cholesterol significantly decreased following the $3^{rd}$ stage of supplementation, as compared to their baseline results and those obtained following the 1$^{st}$ stage of supplementation (p < 0.05). Their LDL-cholesterol and LDL / HDL ratios significantly decreased following the $3^{rd}$ stage of supplementation, as compared to their baseline results and those obtained following the 1$^{st}$ stage of supplementation (p < 0.05). Their 4-HNE and total antioxidant statuses significantly decreased following the $2^{nd}$ and $3^{rd}$stage of supplementation, as compared to their baseline results and those obtained following the $1^{st}$ stage of supplementation (p <0.05). Their $2^{nd}$ stage supplementation results were significantly negatively correlated with their triceps measurements and WHR (p < 0.05). Their $3^{rd}$stage supplementation results were significantly negatively correlated with their anterior thigh measurements (p < 0.05). The above results show that prune, raspberry, silk peptide and dietary fiber supplementation to a routine diet improves body fat distribution, total cholesterol, and triglyceride levels. The decrease of abdominal fat and WHR were especially noteworthy. This implies a decrease of risk factors. (Korean J Community Nutrition 8(3) : 356~367, 2003)003)

• Research in Plant Disease
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• v.17 no.3
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• pp.396-398
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• 2011

Soft rot disease on Raspberry (Rubus crataegifolius Bunge) was observed in sale boxes at Jinju City Wholesale Market of Agricultural Products in June 2010. The infected fruits were rapidly water-soaked, softened, black and eventually rotted. The colonies on the infected fruits were white to light brown, formed numerous sporangiospores. Optimum temperature for the mycelial growth of the causal fungus on PDA was $30^{\circ}C$ and growth was still apparent at $37^{\circ}C$. Sporangia were globose, white at early and gradually to black, and 40-210 ${\mu}m$ in diameter. Sporangiophores were white to mid brown as maturation and 8-20 ${\mu}m$ in diameter. Columella were globose to sub-globose, and the size of the diameter was 85-120 ${\mu}m$ in diameter. Sporangiospores were sub-globose, rhomboidal and irregular, streaked and 5-10 ${\mu}m$ in length. On the basis of symptom, mycological characteristics, ITS rDNA sequence analysis, and pathogenicity of the fungus, the causal fungus was clearly identified as Rhizopus oryzae Went & Prinsen Geerligs. This is the first report of soft rot by R. oryzae on R. crataegifolius in Korea.

• Journal of the Korean Applied Science and Technology
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• v.29 no.3
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• pp.402-411
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• 2012

Natural Bokbunja is used as a material of oriental medicine which it obtains from Rubus or Raspberry. Natural Bokbunja Rubus has natural odor and taste, natural color, and pharmaceutical & chemical characteristics. This experiment tested antimicrobial experiment against microbe and dye experiment against fiber using natural Bokbunja extract. Some conclusions from this characteristics experiment were obtained as follow. The result of antimicrobial experiment could know that ATCC-001(staphylococcus aureus) does not show nearly from 72hrs after cultivation test and ATCC-002(aspergillus niger) shows to propagate continuously according to passage of time. Also, the result of dye experiment could know that cotton and silk using alum mordant($Al_2(SO_4)_3{\cdot}13-14H_2O$) against fiber shows in direction of light beige color. The result of instrument analysis ascertained inorganic components of K(221.100ppm), Mg(17.920ppm), Ca(5.129ppm), Na(2.940ppm), Si(0.638ppm) etc from Bokbunja with ICP/OES, and ascertained organic components of boric acic(1.711), silane(2.142), pyrazole(3.481), propyl isothiocyanate(2.565), furfurole(11.521) etc from Bokbunja with GC/MSD.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• Korean journal of applied entomology
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• v.56 no.1
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• pp.51-60
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• 2017

The striped fruit fly, Bactrocera scutellata, infests pumpkin flowers. Males are attracted to raspberry ketone (RK) and feed the attractant. This study was conducted to determine essential techniques to develop a male annihilation technique (MAT) of this insect pest. Effective attractants were screened in laboratory and field conditions. Both males and females were responsive to methyl eugenol (ME) in laboratory, though no flies were attracted to ME traps in field conditions. In contrast, cuelure (CL), which is a chemical derivative of RK, was effective to attract males of B. scutellata in both laboratory and field conditions. However, RK was equivalent or superior to CL when they were formulated in a form of wax dispenser. A pyrethroid insecticide along with the attractant was effective to attract and kill B. scutellata. Funnel trap was useful for MAT to confirm and count dead flies. These results indicate that MAT against B. scutellata consists of RK and bifenthrin in a wax type formulation, which is installed to a funnel type of trap. These essential factors would be useful to develop MAT applicable to control B. scutellata in fields.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.117-124
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• 2017

A Smart Grid is a system that can efficiently use energy by exchanging real-time information in both directions between a consumer and a power supplier using ICT technology on an existing power network. DR(Demand response) is an arrangement in which electricity users can sell the electricity they save to the electricity market when the price of electricity is high or the power system is crisis. In this study, we developed a power meter data transmission device and power IT system that measure the demand information in real-time using a smart meter and transmit it to a cloud server. The power meter data transmission device developed in this study uses alight sensor connected to a Raspberry Pi 3 to measure the number of blinking lamps on the KEPCO meter per unit of power, in order to provide reliable data without any measurement errors with respect to the KEPCO power data. The power measurement data transmission device uses the standard communication protocol, OpenADR 2.0b. The measured data is transmitted to the power IT system, which consists of the VEN, VTN, and calculation program, via the LTE WiFi communication network and stored in its MySQL DB. The developed power measurement data transmission device issues a power supply instruction and performs a peak reduction DR when a power system crisis occurs. The developed power meter data transmission device has the advantage of allowing the user to adjust it every 1 minute, where as the existing smart metering time is fixed at once every 15 minutes.