• Journal of Biosystems Engineering
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• 제38권4호
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• pp.264-269
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• 2013

Purpose: This study was carried out to develop a classification index and grade levels to rate agricultural heaters for energy efficiency classification. Methods: The classification index was developed mainly by taking simplicity of calculation and easy access to relevant data into consideration. The grade levels were developed on the basis of a 5-grade classification system in which graded heaters are to be normally distributed over the grades. The value of each grade level were determined in terms of the classification index values calculated using the published performance data of agricultural heaters tested at the FACT in Korea over the past 12 years. Results: The thermal efficiency of agricultural heaters based on the enthalpy method was proposed as a reasonable classification index. The grade levels were proposed in equation form for three types of agricultural heaters: fossil fuel heaters, wood pellet heaters and wood pellet boilers. A reasonable energy efficiency classification of agricultural heaters could be performed using the proposed classification index and grade levels. Conclusions: It is expected that energy saving programs will be extended to agricultural machines in the near future. The classification index and grade levels to rate agricultural heaters for energy efficiency classification were developed and proposed for such near future to come.

• 대한원격탐사학회지
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• 제35권4호
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• pp.561-571
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• 2019

In this paper, we analyze the effect of the representative spectral indices, normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI) on classification accuracies of Landsat-8 OLI image.After creating these spectral index images, we propose five methods to select the spectral index images as classification features together with Landsat-8 OLI bands from 1 to 7. From the experiments we observed that when the spectral index image of NDVI or NDWI is used as one of the classification features together with the Landsat-8 OLI bands from 1 to 7, we can obtain higher overall accuracy and kappa coefficient than the method using only Landsat-8 OLI 7 bands. In contrast, the classification method, which selected only NDBI as classification feature together with Landsat-8 OLI 7 bands did not show the improvement in classification accuracies.

• Journal of Biosystems Engineering
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• 제39권2호
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• pp.96-100
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• 2014

Purpose: The objective of this study was to develop a classification index and the grade levels for a five-grade energy efficiency classification of agricultural dryers in Korea. Methods: The classification index and the grade levels were determined by using the performance test data published by the FACT over the last eight years to reflect a state of the art technology for agricultural dryers in Korea. The five grades were designed to have the classified dryers distributed normally over the grades with 15% for the $1^{st}$ grade, 20% for the $2^{nd}$ grade, 30% for the $3^{rd}$ grade, 20% for the $4^{th}$ grade and 15% for the $5^{th}$ grade. Results: The classification index was defined as the total amount of fuel and electrical energy consumed per 1% of the wet basis moisture content evaporated from a unit mass of grain or agricultural crops during the drying process: 1 MT of paddy rice for grain dryers and 1 kg of red pepper for agricultural crop dryers as the standard mass. Conclusions: The grade levels for the five-grade energy efficiency classification of grain dryers, kerosene dryers, and electric dryers were proposed in terms of the classification index value.

• Journal of Biosystems Engineering
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• 제37권4호
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• pp.215-224
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• 2012

Purpose: This study was conducted to classify the energy efficiency of 131 tractor models tested during from 2006 to 2010 in Korea. Methods: Four sub-indexes were developed using the fuel consumptions at 60% and 90% of rated speed with partial loads and at pull speeds of 3.0 km/h and 7.5 km/h with maximum drawbar pull. Weighting factors of the sub-indexes were also considered to reflect the characteristics of tractor's actual working hours in Korea. Four sub-indexes were integrated into a classification index. Using the developed classification index, a five-classification system was made on the basis of normal distribution of tractors over the classification range. Percentage of $1^{st}$ grade interval was expected to be close to 15%, $2^{nd}$ grade 20%, $3^{rd}$ grade 30%, $4^{th}$ grade 20%, $5^{th}$ grade 15%. Results: Number of $1^{st}$ grade was 21, $2^{nd}$ grade 23, $3^{rd}$ grade 39, $4^{th}$ grade 33, $5^{th}$ grade 15 among 131 models. Conclusions: Classification index was developed by integrating four sub-indexes. By the classification method using developed index, distribution of classified tractors was acceptable for practical application.

• 대한원격탐사학회지
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• 제26권6호
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• pp.665-673
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• 2010

The role of remote sensing in phenological studies is increasingly regarded as a key in understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for vegetation classification using seasonal variation patterns. The vegetation seasonal variation phase of Seoul and provinces in Korea was inferred using 8 day composite MODIS NDVI (Normalized Difference Vegetation Index) dataset of 2006. The seasonal vegetation classification approach is performed with reclassification of 4 categories as urban, crop land, broad-leaf and needle-leaf forest area. The BISE (Best Index Slope Extraction) filtering algorithm was applied for a smoothing processing of MODIS NDVI time series data and fuzzy classification method was used for vegetation classification. The overall accuracy of classification was 77.5% and the kappa coefficient was 0.61%, thus suggesting overall high classification accuracy.

• Journal of Astronomy and Space Sciences
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• 제20권2호
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• pp.101-108
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• 2003

This study reports one approach for the classification of magnetic storms into recurrent patterns. A storm event is defined as a local minimum of Dst index. The analysis of Dst index for the period of year 1957 through year 2000 has demonstrated that a large portion of the storm events can be classified into a set of recurrent patterns. In our approach, the classification is performed by seeking a categorization that minimizes thermodynamic free energy which is defined as the sum of classification errors and entropy. The error is calculated as the squared sum of the value differences between events. The classification depends on the noise parameter T that represents the strength of the intrinsic error in the observation and classification process. The classification results would be applicable in space weather forecasting.

• Journal of Multimedia Information System
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• 제3권3호
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• pp.53-61
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• 2016

This research proposes the index optimization as a classification task and application of the graph based KNN. We need the index optimization as an important task for maximizing the information retrieval performance. And we try to solve the problems in encoding words into numerical vectors, such as huge dimensionality and sparse distribution, by encoding them into graphs as the alternative representations to numerical vectors. In this research, the index optimization is viewed as a classification task, the similarity measure between graphs is defined, and the KNN is modified into the graph based version based on the similarity measure, and it is applied to the index optimization task. As the benefits from this research, by modifying the KNN so, we expect the improvement of classification performance, more graphical representations of words which is inherent in graphs, the ability to trace more easily results from classifying words. In this research, we will validate empirically the proposed version in optimizing index on the two text collections: NewsPage.com and 20NewsGroups.

• Journal of Ecology and Environment
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• 제35권2호
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• pp.91-98
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• 2012

This study was performed in order to suggest the possibility of tree species classification using high-resolution QuickBird-2 images spectral characteristics comparison(digital numbers [DNs]) of tree species, tree species classification, and accuracy verification. In October 2010, the tree species of three conifers and eight broad-leaved trees were examined in the areas studied. The spectral characteristics of each species were observed, and the study area was classified by image classification. The results were as follows: Panchromatic and multi-spectral band 4 was found to be useful for tree species classification. DNs values of conifers were lower than broad-leaved trees. Vegetation indices such as normalized difference vegetation index (NDVI), soil brightness index (SBI), green vegetation index (GVI) and Biband showed similar patterns to band 4 and panchromatic (PAN); Tukey's multiple comparison test was significant among tree species. However, tree species within the same genus, such as $Pinus$ $densiflora-P.$ $rigida$ and $Quercus$ $mongolica-Q.$ $serrata$, showed similar DNs patterns and, therefore, supervised classification results were difficult to distinguish within the same genus; Random selection of validation pixels showed an overall classification accuracy of 74.1% and Kappa coefficient was 70.6%. The classification accuracy of $Pterocarya$ $stenoptera$, 89.5%, was found to be the highest. The classification accuracy of broad-leaved trees was lower than expected, ranging from 47.9% to 88.9%. $P.$ $densiflora-P.$ $rigida$ and $Q.$ $mongolica-Q.$ $serrata$ were classified as the same species because they did not show significant differences in terms of spectral patterns.

• 한국도서관정보학회지
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• 제41권3호
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• pp.155-183
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• 2010

도서색인은 일종의 위치탐색 장치체계로서, 일반적으로 텍스트에 나오는 용어의 집합과 텍스트 속에서 그 용어가 출현하는 위치를 연결해 주는 역할만 한다. 반면에 DDC 상관색인의 용어는 페이지 수를 지시하기 보다는 분류번호나 혹은 본표에서 발견될 수 있는 이에 상응하는 범주어들을 가리킨다. DDC 색인은 DDC의 탄생 이상으로 그 중요성이 높다. 그래서 연구의 목적은 DDC 색인을 연구하는데 두었다. 상관색인은 본표나 보조표와는 정반대로 '표목 + 관점 + 분류기호'로 구성되어 있다. DDC에서 최초로 응용한 상관색인의 특성을 분석하여 그 기능을 종합하였으며, 또한 DDC 상관색인의 구조적 특성을 분석하였다.

• 한국측량학회지
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• 제31권6_2호
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.