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안재준,Kashif Akram,백지영,김연주,김문영,정일윤,권중호 한국식품과학회 2012 Food Science and Biotechnology Vol.21 No.3
EN 1788:2001 suggests defining the temperature range for the thermoluminescence (TL) heating unit to calculate the TL ratio (TL1/TL2). In the present study,practical temperature ranges were established by using well-characterized lithium fluoride (LiF, TLD-100®) at 4different research institutes in Korea. Temperature ranges differed according to models of TLD heating unit, which were wide in the case of RISØ (160-249°C) as compared with Harshaw (155-232oC) TLD readers. The silicate minerals separated from irradiated turmeric samples were measured to check these intervals on a practical basis. The X-ray diffraction (XRD) analysis of separated minerals showed that quartz and feldspar minerals were the main source of well-characterized TL glow curve following irradiation. The TL glow peaks from the separated minerals were narrower in Harshaw than RISØ TLD readers. The TL ratios determined after re-irradiation (1 kGy) for the tested minerals, using the pre-defined temperature intervals, provided the satisfactory results.
Application of Simple Biological Analyses to Screen Irradiated Brown Rice, Soybean and Sesame Seeds
안재준,Hafiz Muhammad Shahbaz,박기환,권중호 한국응용생명화학회 2014 Applied Biological Chemistry (Appl Biol Chem) Vol.57 No.2
The efficacy of biological screening assays such asgermination test and direct epiuorescent lter technique (DEFT)and aerobic plate count (APC) was evaluated to detect theirradiation status of different seeds. DEFT/APC help to calculatethe difference between dead and living microorganisms in asample after a possible irradiation treatment. Likewise, theirradiation can significantly affect the physiological and biochemicalprocesses in germinating seeds, which provides the basis for thegermination test. In the present study, three different seeds (brownrice, soybean, and sesame) of Korean and Chinese origins weresubjected to gamma-irradiation (0.5, 1, 2, and 4 kGy) and theeffects on the germination characteristics were evaluated. Theresults revealed that the growth rate and shoot length decreasedwith increasing irradiation doses. Particularly, 4 kGy of irradiationhad a pronounced effect on all the germination characteristics inall seed samples. The DEFT counts did not change, which wereindependent of the irradiation dose, whereas the APC countsgradually decreased with dose increment. The results showed thepotential of the germination test and DEFT/APC as usefulscreening methods for irradiated seeds.
안재준,Kashif Akram,김병근,백지영,곽지영,박은주,김효영,김청태,정일윤,이주운,한상배,권중호 한국식품과학회 2013 Food Science and Biotechnology Vol.22 No.4
Thermoluminescence (TL) technique for identifying γ-irradiated (0-10 kGy) anchovies (dried), kelp (dried), and mackerel (fresh) was validated in an interlaboratory blind trial. Different irradiation detection laboratories were involved by using 2 methods of mineral separation (density separation and acid hydrolysis) for the analysis. Key TL parameters, including the TL glow-curve shape, intensity, and the TL ratio (TL1/TL2) were used to characterize the irradiation status. All irradiated samples exhibited an intense TL peak at approximately 200oC,which was absent in non-irradiated samples. TL glow curve interpretations were also confirmed by determining the TL ratio. Different participating laboratories reported 89-100%correct results. Both methods of mineral separation were equally effective; however, some variation was observed in the results from different laboratories for irradiated mackerel,which might be due to a lack of isolated minerals, differences in personnel expertise, and different TL instruments.
안재준,심현식 한국반도체디스플레이기술학회 2022 반도체디스플레이기술학회지 Vol.21 No.4
As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.