• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.425-435
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• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.96-98
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• 2003

1. Standard and regulations for functional food evaluation cases form overseas (1) Japan For food function indication, Food Nutrition Improvement Act was amended in September 1991 and they managed functional food after setting specific health food in one of classification of special functional foods. For manification of raw material usage, the classification of health functional foods was performed by their application on: the control of internal organ status, cholesterol, blood pressure, mineral absorption, and prevention of dental caries. (omitted)

• Resources Recycling
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• v.25 no.1
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• pp.40-47
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• 2016

Nickel laterite ore is classified into two principal ore types: saprolite (silicate ore) and limonite (oxide ore). Saprolite-type ore characterized by high magnesia and silica contents is treated by pyrometallurgy process. On the other hand, limonite-type ore is subjected to hydrometallurgy process to produce nickel products. Hydrometallurgy process requires that a raw material to meet the demands that Si+Mg contents lower than 10% and Fe content over than 40%. It is therefore required that separation of saprilite-type ore to use nickel laterite ore as a raw material for hydrometallurgy process. In this study, separation of sparolite-type ore and limonite-type ore from nickel laterite ore from New Caledonia has been tried by dry classification. The results show that -5 mm size fraction and +5 mm size fraction of the nickel laterite ore contains mainly limonite-type ore and saprolite-type ore, respectively. To understand the moisture content of the raw ore on the dry classification, nickel laterite ore with different moisture contents of 23.0% and 9.1% were subjected to the dry classification. The results show that drying of the ore makes the separation more efficient as the amount of the fine product, that can be subjected to hydrometallurgy process without further separation or drying operations, was increased.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.2
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• pp.189-194
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• 2005

The morphological properties of various structure materials of domestic and foreign reconstituted tobacco products(RTP) were investigated by using the Bauer-McNett classifier and the image analyzer. The results of the fiber classification showed the fraction of the bigger size structure materials was larger in a domestic RTP than that in two foreign RTPs. In case of fine fraction, the domestic RTP had bigger fine fraction than two foreign RTPs. Images of each structure materials showed the scrap in the foreign RTPs kept the original shape which were rare in the domestic RTP fractions. Those results deduced that the raw materials in a foreign RTP process might be treated separately depending on the mechanical and morphological properties, which could reduce the amount of fine generation and increase the efficiency in raw material treatment.

• Resources Recycling
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• v.27 no.2
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• pp.11-23
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• 2018

The need for remanufacturing automotive parts is required due to the depletion of resources, rising raw material prices and strengthening environmental regulations. For remanufacturing, stable supply and demand of core must be accompanied. At present, remanufacturing companies collect cores through various routes, but the recovery rate of cores from the End-of-Life Vehicles is low. If we can systematically collect cores from hundreds of thousands of ELVs that were generated each year, the recovery rate of the core for remanufacturing will be further improved. Therefore, in this paper, we tried to establish a classification system for the ELV as a method for collecting the cores from the ELV. First, we selected the elements affecting the classification and determined the scope for the evaluation. The final rating classification is established by calculating the weights among the influence elements. Finally, through the case study, the dismantling grade of the actual ELV was evaluated to derive the second grade.

• Land and Housing Review
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• v.15 no.1
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• pp.147-156
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• 2024

This study aims to reduce CO₂ generated during the manufacturing process by using limestone (CaCO₃), a carbonate mineral used in the production of cement clinker, as a decarbonated raw material that does not contain CO₂. Among various industrial by-products, we attempted to use cement paste attached to waste concrete. In general, limestone for cement must have a CaCO₃ content of at least 80% (CaO, 44% or more) to ensure the quality of cement clinker. However, the CaO content of waste concrete fine powder is about 20% on average, so in order to use it as a cement clinker raw material, the CaO content must be increased to more than 35%. Therefore, by using the difference in hardness of the mineral composition of waste concrete fine powder to selectively crush CaO type minerals with relatively low hardness, classify and sieve, the CaO content can be increased by more than 35%. Accordingly, in this study, we experimentally and statistically reviewed and analyzed the optimal conditions for efficiently separating CaO and SiO₂ and other components by selectively pulverizing minerals containing relatively low CaO through a grinding process. As a result of the optimal grinding conditions experiment, it was found that the optimal conditions were a grinding time of less than 5 minutes, a type of material to be crushed of 30 mm, and an amount of material to be crushed of 1.0 or more. However, it is judged that it is necessary to review pulverized materials of mixed particle sizes rather than pulverized products of single particle size.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.95-99
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• 2023

Forest healing is an activity that enhances immunity and human health using various elements of nature, such as fragrance and scenery. Particularly, phytoncide composed of terpene, a natural volatile substance emitted by forest plants, activates the immune function and is an important raw material in health-related products, such as antibacterial and insect repellents. Moreover, phytoncide is used as a measure to evaluate the impact of the forest atmosphere on the human body. This study aims to implement a highly sensitive gas sensor system that can measure phytoncide in real-time, which is an essential element for realizing a forest healing environment. A gas generation apparatus was implemented by using an adsorption tube in consideration of filed applicability in a laboratory atmosphere to enable the measurement of α-pinene and limonene, which are among the main components of phytoncide. Throughout the experimental trials, the sensitivity of gas sensor arrays to α-pinene and limonene was confirmed. In addition, the classification results demonstrated the AVOCs and NVOCs can be well discriminated using PCA. The primary results confirmed the possibility of developing a high-sensitivity gas sensor system for phytoncide sensing in real time.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.66-73
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• 2023

The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.