• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.416-422
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• 2016

Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.

• Resources Recycling
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• v.26 no.1
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• pp.69-77
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• 2017

Used small household appliances(small e-waste) consists of a variety of complex materials and components. The small e-waste is mainly composed of plastics and an important potential source of waste plastic. The black plastics, particularly are very difficult to separate by resin type and therefore these are mainly recycled in the form of a mixtures. In the present study, the sorting technologies such as gravity and electro static separation, near-infrared ray(NIR) and IR/Raman optical sorting separation on mixture of black plastics were analyzed and their limitations on sorting process were also investigated. The Laser Induced Breakdown Spectroscopy(LIBS) spectrum of each black plastics was used for identification of black plastics by resin type, and after analyzing the normalization operation, Principal Component Analysis(PCA) was carried out. The spectrum data was optimized through PCA process. In order to improve the identification accuracy and sorting efficiency of black plastics, it is necessary to design a classifier with high efficiency and to improve the performance and reliability of the classifier by applying the field of intelligent algorithms.

• Journal of Ecology and Environment
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• v.44 no.1
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• pp.45-53
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• 2020

Background: The black soldier fly (Hermetia illucens) is gaining attention as an efficient decomposer of food waste. However, recalcitrant compounds such as plastics mixed into food waste may have negative effects on its growth and survival. Moreover, its efficiency of food waste degradation may also be affected by plastics. In addition, salt (NaCl) can also be present in high concentrations, which also reduces the efficiency of H. illucens-mediated food waste treatment. In this study, we assessed the growth of black soldier fly larvae (BSFL) reared on food waste containing polyethylene (PE) and polystyrene (PS) and NaCl. The weight of BSFL was measured every 2-4 days. Survival and substrate reduction rates and pupation ratio were determined at the end of the experiment. Results: The total larval weight of Hermetia illucens reared on food waste containing PS was greater than that of the control on days 20 and 24. However, the survival rate was lower in the group treated with 5% PS, as was substrate reduction in all PS-treated groups. The weight of BSFL reared on food waste containing PE was lower than that of the control on day 6. PE in food waste did not affect the survival rate, but the pupation ratio increased and substrate consumption decreased with increasing PE concentrations. Regardless of the plastic type, the addition of NaCl resulted in decreased larval weight and pupation ratio. Conclusions: Larval growth of black soldier fly was inhibited not by plastics but by substrate salinity. Additional safety assessments of larvae reared on food waste containing impurities are needed to enable wider application of BSFL in vermicomposting.

• Resources Recycling
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• v.26 no.6
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• pp.73-83
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• 2017

Used small household appliances have a wide variety of product types and component materials, and contain high percentage of black plastics. However, they are not being recycled efficiently as conventional sensors such as near-infrared ray (NIR), etc. are not able to detect black plastic by types. In the present study, an automatic sorting system was developed based on laser-induced breakdown spectroscopy (LIBS) to promote the recycling of waste plastics. The system we developed mainly consists of sample feeder, automatic position recognition system, LIBS device, separator and control unit. By applying laser pulse on the target sample, characteristic spectral data can be obtained and analyzed by using CCD detectors. The obtained data was then treated by using a classifier, which was developed based on artificial intelligent algorithm. The separation tests on waste plastics also were carried out by using a lab-scale automatic sorting system and the test results will be discussed. The classification rate of the radial basis neural network (RBFNNs) classifier developed in this study was about > 97%. The recognition rate of the black plastic by types with the automatic sorting system was more than 94.0% and the sorting efficiency was more than 80.0%. Automatic sorting system based on LIBS technology is in its infant stage and it has a high potential for utilization in and outside Korea due to its excellent economic efficiency.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.477-484
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• 2016

Small industrial appliances such as fan, audio, electric rice cooker mostly consist of ABS, PP, PS materials. In colored plastics, it is possible to classify by near infrared(NIR) spectroscopy, while in black plastics, it is very difficult to classify black plastic because of the characteristic of black material that absorbs the light. So the RBFNNs pattern classifier is introduced for sorting electrical and electronic waste plastics through LIBS(Laser Induced Breakdown Spectroscopy) spectrometer. At the preprocessing part, PCA(Principle Component Analysis), as a kind of dimension reduction algorithms, is used to improve processing speed as well as to extract the effective data characteristics. In the condition part, FCM(Fuzzy C-Means) clustering is exploited. In the conclusion part, the coefficients of linear function of being polynomial type are used as connection weights. PSO and 5-fold cross validation are used to improve the reliability of performance as well as to enhance classification rate. The performance of the proposed classifier is described based on both optimization and no optimization.

• Proceedings of the IEEK Conference
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• 2001.10a
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• pp.215-219
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• 2001

Impurities removal from waste carbon black was carried out to produce high-grade carbon black. A lot of hydrophilic carbon black is produced as a byproduct of the hydrogen production process by flame decomposition of water. Due to its impurity content such as sulphur, iron, ash and etc., it can only be used as low-grade carbon or burnt out. High-grade hydrophilic carbon black is 3-5 times more expensive than oil-based carbon black because of its process difficulties and requires pollutant treatment. Hydrophilic carbon is normally used far conductive materials for batteries, pigment for plastics, electric wire covering, additives for rubber, etc.. In these applications, hydrophilic carbon must maintain its high purity. In this study magnetic separation, froth flotation and ultrasonic treatment were employed to remove impurities from the low-grade hydrophilic carbon black. As results, the ash, iron and sulphur content of product decreased to less than 0.01wt.%, 0.0lwt.% and 0.3wt.% respectively, and the surface area of product was about 930 $m^2$/g.

• Resources Recycling
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• v.26 no.2
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• pp.46-55
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• 2017

In this study, the design methodology of Radial Basis Function Neural Networks is developed with the aid of Laser Induced Breakdown Spectroscopy and also applied to the practical plastics sorting system. To identify black plastics such as ABS, PP, and PS, RBFNNs classifier as a kind of intelligent algorithms is designed. The dimensionality of the obtained input variables are reduced by using PCA and divided into several groups by using K-means clustering which is a kind of clustering techniques. The entire data is split into training data and test data according to the ratio of 4:1. The 5-fold cross validation method is used to evaluate the performance as well as reliability of the proposed classifier. In case of input variables and clusters equal to 5 respectively, the classification performance of the proposed classifier is obtained as 96.78%. Also, the proposed classifier showed superiority in the viewpoint of classification performance where compared to other classifiers.

• Carbon letters
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• v.7 no.2
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• pp.87-96
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• 2006

This paper describes the physical properties of filled Nylon6 composites resin with nano-sized carbon black particle and graphite nanofibers prepared by melt extrusion method. In improving adhesions between resin and fillers, the surface of the carbon filler materials were chemically modified by thermo-oxidative treatments and followed by treatments of silane coupling agent. Crystallization temperature and rate of crystallization increased with increases in filler concentration which would act as nuclei for crystallization. The silane treatments on the filler materials showed effect of reduction in crystallization temperature, possibly from enhancement in wetting property of the surface of the filler materials. Percolation transition phenomenon at which the volume resistivity was sharply decreased was observed above 9 wt% of carbon black and above 6 wt% of graphite nanofiber. The graphite nanofibers contributed to more effectively in an increase in electrical conductivity than carbon black did, on the other hand, the silane coupling agent negatively affected to the electrical conductivity due to the insulating property of the silane. Positive temperature coefficient (PTC) phenomenon, was observed as usual in other composites, that is, temperature increase results conductivity increase. The dispersity of the fillers were excellently approached by melt extrusion of co-rotational twin screw type and it could be illustrated by X-ray diffraction and SEM.

• Journal of the Korean Society of Safety
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• v.3 no.1
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• pp.37-45
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• 1988

This research investigated the condition for plant design on reclamation of waste plastic by heat decomposition. The results were summarized as follows 1. The highest of oil product by heat decomposition is about 54.7％. 2. The optimum reaction temperature is about 300­40$0^{\circ}C$. 3. The optimum reaction time is 2­3 hours. 4. When the flow rate of 8­16 cm/sec in column reactor the yield is maximum. 5. Waste plastics yielded of carbon black product by heat decomposition at the optimum condition is about 23.5%. 6. Calorific values 0：1 were 9820 Kcal/kg.

• Proceedings of the Ginseng society Conference
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• 1974.09a
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• pp.137-146
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• 1974

This experiment was on the purpose to study the effects of different shading of Mulching treatments on the quality and yield of ginseng root. This experiment were conducted at Mei-Feng for one year, from July, 1972 to July, 1973. The variety been used was introduced Korea Panax ginsvng. Three different Shading of Mulching treatments have been studied. The results were summerized as follows: 1. The growth of ginseng plant is good under around 4,300 Lux of light intensity. Fig . showed the shadow treatment of straw had a better effect than that of black or grey plastic film. The differences between treatments were significant. 2. The adequate soil temperature for ginseng culture was in the range of $16-18^{\circ}C$. Fig 2. showed that there were significant differences among treatments, of which the straw shadow treatment had the best effect. 3. The growth of ginseng plant was greatly affected wth various shadow treatments. Fig 1. showed both straw and black plastic film treatments had a better effects on growth of stem, leaf area and leaf numbers. 4. Fig. 2. 3. 4. 5 indicated there were distingished differences among all treatments. The straw and black plastics film mulching treatments had a better effects on root length, root diameter, root weight and leaf weight than the grey plastic film. 5. The amount of plant alkaloids and panacene content had related to the shadow treatment, as showed in Fig. 6 and 7 that straw shadow treatment had greatly increased the procuction of plant alkaloids and panacene content. 6. The quality and yield of roots of ginseng greatly affected by different shading of mulching treatments.