Classification Index and Grade Levels for Energy Efficiency Classification of Agricultural Heaters in Korea

신창섭,장지훈,김영태,김경욱 한국농업기계학회 2013 바이오시스템공학 Vol.38 No.4

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.

문화콘텐츠의 분류: 비판과 대안

임대근 글로벌 문화콘텐츠학회 2020 글로벌문화콘텐츠 Vol.0 No.44

This paper argues the classification of cultural contents as the research subjects to pursue the scientific nature of cultural contents studies. We can see the attitude of ‘compulsion toward the system’ from literature studies. In addition, they did not provide examples of detailed classification. This is due to the broadness and complexity of cultural contents. Therefore, this paper abandon the compulsion of systematic classification, and concentrate on contextual classification. The ‘folksonomy’, which emerged as an alternative concept of ‘taxonomy’, which has contributed to the systematization and structuring of knowledge since the modern era, adds strength to this idea. Classification can be divided into categorization, which is an approach based on a supervised structure, and clustering that is not. Reviewing the concept of classification, the following premise can be established. (1) ‘Classification’ does not necessarily have to be replaced with the term ‘Classification System’, (2) ‘Standards’ must be flexibly understood in the classification, (3) The objects classified as a result of classification need not always mutually exclusive, and (4) Classification is instrumental. Based on this premise, this article attempts to classify cultural contents. They are as following: according to the nature of the contents media(digital contents and analog contents), based on whether it is based on ‘story’(storytelling contents and non-storytelling contents), according to the sense of users(visual contents, auditory contents, tactile contents, taste contents, olfactory contents), according to the planning and production process and results(purpose contents, tool contents, subject contents), and genre contents(publishing contents, image contents, performance contents, exhibition contents, games contents, festival contents, theme park contents). 이 글은 문화콘텐츠연구의 과학성을 담보하기 위해서 문화콘텐츠라는 연구대상의 분류를 다룬다. 그 선행 논의를 살펴본 바, 대체로 형성 중인 학문으로서 문화콘텐츠연구를 어떤 체계로 구조화할지에 집중하는 ‘체계에 대한 강박’이라는 태도가 드러났다. 또한, 선행 논의들은 결과적으로 세부 분류의 실례를 제공하지 못했다. 이는 문화콘텐츠의 광범위성과 복잡성에서 말미암는다. 따라서 이 글은 문화콘텐츠에 대한 체계적 분류라는 강박을 버리고 맥락적 분류에 더욱 관심을 갖는다. 근대 이후 지식을 체계화, 구조화하는데 기여해온 ‘분류학’(taxonomy)의 대안 개념으로 출현한 ‘폭소노미’(folksonomy)는 이런 구상에 힘을 더해준다. 분류(classification)는 사전에 정의된(supervised) 구조를 바탕으로 한 접근법인 범주화(categorization)와 그렇지 않은 군집화(clustering)로 구분할 수 있다. 분류 개념을 검토하면 다음과 같은 전제를 확립할 수 있다. (1) ‘분류’가 반드시 ‘분류 체계’라는 용어로 대체될 필요가 없으며, (2) 분류 행위에 있어 ‘기준’은 유연하게 이해되어야 하고, (3) 분류 결과 구분된 대상이 항상 상호배타적일 필요는 없으며, (4) 분류는 도구적 행위이다. 이 글은 이런 전제를 바탕으로 문화콘텐츠의 맥락적 분류를 시도한다. 콘텐츠 매개체의 성질에 따른 분류(디지털콘텐츠와 아날로그콘텐츠), ‘스토리’ 기반 여부에 따른 분류(스토리텔링콘텐츠와 비스토리텔링콘텐츠), 향유자의 수용 감각에 따른 분류(시각콘텐츠, 청각콘텐츠, 촉각콘텐츠, 미각콘텐츠, 후각콘텐츠), 기획과 생산 과정 및 결과에 따른 분류(목적콘텐츠, 도구콘텐츠, 주제콘텐츠), 콘텐츠 장르에 따른 분류로서의 장르콘텐츠(출판콘텐츠, 영상콘텐츠, 공연콘텐츠, 전시콘텐츠, 게임콘텐츠, 축제콘텐츠, 테마파크콘텐츠)가 그것이다.

생물 분류와 무생물 분류과정의 두뇌 활성 비교를 통한 예비교사의 분류전략에 대한 인지적 분석

변정호(Jung-Ho Byeon) 한국교원대학교 뇌기반교육연구소 2021 Brain, Digital, & Learning Vol.11 No.2

The classification is one type of convergent problem-solving in the context of creative problem-solving. The classification learning method in curriculum and textbook is not discriminate using the animate and inanimate object as learning material. However, the classification of animate and inanimate is related to the different neurological systems of the human brain. For the success of classification learning in class, we need to clarify pre service teacher’s cognitive strategy during animate and inanimate classification involved categorization. The researcher recruited 24 pre-service teachers to investigate brain activation during the classification of animate and inanimate using fMRI. As a result of this study, the researcher could find the similarity and difference of brain activation between animate and inanimate classification. The activation of DLPFC, PMC, the secondary visual cortex in the human brain equally checked out on animate and inanimate classification. Also the activation of LIP in the parietal region was showed on inanimate classification, and the activation of the occipitotemporal cortex was confirmed on animate classification. Consequently, pre-service teachers’ animate classification was related to the frontal temporal path of information processing, and inanimate classification was related to the frontal-parietal path of information processing.

Accuracy Estimation of a Classifier Based on the Differences in Samples

Min Zhang,Shengbo Yu 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.11

The classification accuracy is an important standard to measure the quality of the classifier. Usually, the classification accuracy is assessed later, not during the classification process. Problems such as classification accuracy drops cannot be timely and effectively found. It is necessary that marking test samples when estimating classification accuracy. It is a problem that we care about that how much is the classification accuracy when a group of new samples obtained. The problem must be concerned when using and improving the classifier in the case of growing data. To solve this problem, this paper put forward different estimates from different perspectives which based on the difference between samples. One estimate is based on the difference in samples distribution, which is from the Bayesian criterion. Another estimate is based on the difference in each sample instance, which is from the K nearest neighbor classification. Classification accuracy is also estimated by using the artificial neural networks, which combine the characteristics of the above two methods. And results show the proposed methods have good effects.

Classification Index and Grade Levels for Energy Efficiency Classification of Agricultural Heaters in Korea

Shin, Chang Seop,Jang, Ji Hoon,Kim, Young Tae,Kim, Kyeong Uk Korean Society for Agricultural Machinery 2013 바이오시스템공학 Vol.38 No.4

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.

생물 분류와 무생물 분류에서 나타나는 고등학생과 예비교사의 시선집중 및 시선이동 패턴 분석

변정호 한국생물교육학회 2020 생물교육 Vol.48 No.2

The purpose of this study is the analysis of attention patterns on animate and inanimate classification between general high school students and pre-teacher. The animate and inanimate classification are related to different brain systems. Therefore they could promote the different responses on classification learning and activity. However, it is confused to use the animate and inanimate classification on textbooks and curriculum to enhance student's competence. So Researcher analyzed classification quotient and attention patterns during animate and inanimate classification between general high school student and pre-teacher by using the eye-tracking method. As a result, the first, it was revealed the difference between animate and inanimate classification ability between high school students and pre-teacher. Second, the case fixation pattern was affected by the main effect of animate and inanimate more than group effect. Third, the difference between the two types of classification was caused by the difference of categorization strategy as like rule-based or similarity- based strategy. Consequently, teachers should consider object and strategy when they construct a classification learning activity, because of the cognitive difference between animate and inanimate classification. Also teachers need to prepare the inquiry activity for classification learning on their students.

실제 네트워크 모니터링 환경에서의 ML 알고리즘을 이용한 트래픽 분류

정광본(Kwang Bon Jung),최미정(Mi Jung Choi),김명섭(Myung Sup Kim),원영준(Young J. Won),홍원기(James W. Hong) 한국통신학회 2008 韓國通信學會論文誌 Vol.33 No.8B

Traffic classification의 방법은 동적으로 변하는 application의 변화에 대처하기 위하여 페이로드나 port를 기반으로 하는 것에서 ML 알고리즘을 기반으로 하는 것으로 변하여 가고 있다. 그러나 현재의 ML 알고리즘을 이용한 traffic classification 연구는 offline 환경에 맞추어 진행되고 있다. 특히, 현재의 기존 연구들은 testing 방법으로 cross validation을 이용하여 traffic classification을 수행하고 있으며, traffic flow를 기반으로 classification 결과를 제시하고 있다. 본 논문에서는 testing방법으로 cross validation과 split validation을 이용했을 때, traffic classification의 정확도 결과를 비교한다. 또한 바이트를 기반으로 한 classification의 결과와 flow를 기반으로 한 classification의 결과를 비교해 본다. 본 논문에서는 J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, NaiveBayes와 같은 ML 알고리즘과 다양한 feature set을 이용하여 트래픽을 분류한다. 그리고 split validation을 이용한 traffic classification에 적합한 최적의 ML 알고리즘과 feature set을 제시한다. The methodology of classifying traffics is changing from payload based or port based to machine learning based in order to overcome the dynamic changes of application's characteristics. However, current state of traffic classification using machine learning (ML) algorithms is ongoing under the offline environment. Specifically, most of the current works provide results of traffic classification using cross?validation as a test method. Also, they show classification results based on traffic flows. However, these traffic classification results are not useful for practical environments of the network traffic monitoring. This paper compares the classification results using cross validation with those of using split validation as the test method. Also, this paper compares the classification results based on flow to those based on bytes. We classify network traffics by using various feature sets and machine learning algorithms such as J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, and NaiveBayes. In this paper, we find the best feature sets and the best ML algorithm for classifying traffics using the split validation.

브라운의 주제분류법 연구

곽철완 한국정보관리학회 2018 정보관리학회지 Vol.35 No.4

The purpose of this study is to analyze the first edition of Brown’s Subject Classification and to understand the implications of today’s library classification. For this purpose, the first edition of the Subject Classification published in 1906 was analyzed. The analysis results are divided into three main areas. First, SC is divided into eleven main classes and each class is subdivided into enumerated subdivisions from 000 to 999. Second, As a method of synthesizing the classification numbers, there were three methods of synthesis. There was a flexibility to insert a new classification number at the appropriate location when a new topic that does not appear in the main table appeared. Implications for classification studies can be divided into four main categories. First, SC proposed a method of classification number synthesis for composite topics, which is an innovative method that was not available in previous library classification. Second, the subject matter was explained in various aspects through the operation of auxiliary tables supporting the facets. Third, it is possible to easily insert a new topic into the classification system by using the SC that can have a flexible classification system for each library, or to use a short classification number according to the size of the library collection. Fourth, it provided a directory that can be considered as access points for digital materials. 이 연구의 목적은 브라운의 주제분류법 초판을 분석하여 오늘의 분류법 연구에 대한 시사점을 파악하는 것이다. 이를 위해 1906년에 발표한 주제분류법 초판을 분석 대상으로 삼았다. 분석 결과는 다음과 같다. 첫째, 분류체계의 구성에서 주제분류법의 주류는 크게 11가지로 구분되며, 각 주류는 000에서 999로 세분되어 열거식으로 나열되었다. 둘째, 분류기호 합성 방법은 크게 3가지가 있다. 셋째, 새로운 주제 처리 방법으로 본표에 없는 새로운 주제가 나타나면 적절한 위치에 새로운 분류기호를 삽입할 수 있는 유연성이 있었다. 분류법 연구에 대한 시사점은 크게 네 가지로 구분할 수 있다. 첫째, 이전의 분류법에는 없었던 혁신적인 방법인 복합 주제에 대한 분류기호 합성 방법을 제시하였다. 둘째, 패싯을 지원하는 보조표 운영을 통하여 주제를 다양한 측면에서 설명하였다. 셋째, 자관별로 유연한 분류체계를 가질 수 있도록 한 분류법으로 분류체계에 새로운 주제를 쉽게 삽입할 수 있거나 도서관 장서 규모에 따라 간략한 분류기호를 사용할 수 있도록 하였다. 넷째, 디지털 자료에 대한 접근점으로 고려할 수 있는 디렉토리를 제공하였다.

물질안전보건자료 대상물질의 유해성 분류기준 적용 연구

이혜진,이나루,이인섭 한국산업보건학회 2020 한국산업보건학회지 Vol.30 No.3

Objectives: Hazard classification is a controversial issue in the new MSDS system in which chemical companies have to prepare and submit MSDS for chemicals that they manufacture or import to the competent authorities according to the amended Occupational Safety and Health Act. The aim of this study is to suggest how to apply and manage harmonized hazard classification criteria and results by investigating current hazard classification systems and trends. Methods: The domestic issues about different hazard classification criteria and results were investigated by reviewing the literature and business outcomes regarding KOSHA. We also checked official and unofficial reports from the UN to understand international discussion about the topic. Chemical hazard classification results from agencies providing chemical information were analyzed to compare a harmonized rate between classifications. Furthermore, a field survey of a few chemical companies was conducted. Results: Under the related competent authorities, an integrated standard proposal was developed to harmonize the domestic hazard classification criteria. Although harmonized chemical information is strongly needed, we recognized the uncertainty and difficulty of harmonized hazard classification from the UN global list project review. In practice the harmonization rate of the classification was generally low between the classification in KOSHA, MoE, and EU CLP. Among hazard classes, health hazards largely led the disharmony. The field survey revealed a change of perception that the main body of chemical information production is manufacturers. Approaches and solutions about hazard classification issues differed depending on business size, types of chemical handling, and other factors. Conclusions: We proposed reasonable ways by time and step to apply hazard classification in the new MSDS system. Chemical manufacturers should make and offer chemical information including responsible hazard classifications. The government should primarily accept these classifications, evaluate them by priority, and support or supervise workplaces in order to communicate reliable chemical information.

카테고리 계층을 고려한 회선신경망의 이미지 분류

정노권,조수선 한국멀티미디어학회 2018 멀티미디어학회논문지 Vol.21 No.12

In order to improve the performance of image classifications using Convolutional Neural Networks (CNN), applying a category hierarchy to the classification can be a useful idea. However, the visual separation of object categories is very different according to the upper and lower category levels and highly uneven in image classifications. Therefore, it is doubtable whether the use of category hierarchies for classification is effective in CNN. In this paper, we have clarified whether the image classification using category hierarchies improves classification performance, and found at which level of hierarchy classification is more effective. For experiments we divided the image classification task according to the upper and lower category levels and assigned image data to each CNN model. We identified and compared the results of three classification models and analyzed them. Through the experiments, we could confirm that classification effectiveness was not improved by reduction of number of categories in a classification model. And we found that only with the re-training method in the last network layer, the performance of lower category classification was not improved although that of higher category classification was improved.