• Title/Summary/Keyword: optimal classification method

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A Classifier Capable of Handling Incomplete Data Set (불완전한 데이터를 처리할수 있는 분류기)

  • Lee, Jong-Chan;Lee, Won-Don
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.53-62
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    • 2010
  • This paper introduces a classification algorithm which can be applied to a learning problem with incomplete data sets, missing variable values or a class value. This algorithm uses a data expansion method which utilizes weighted values and probability techniques. It operates by extending a classifier which are considered to be in the optimal projection plane based on Fisher's formula. To do this, some equations are derived from the procedure to be applied to the data expansion. To evaluate the performance of the proposed algorithm, results of different measurements are iteratively compared by choosing one variable in the data set and then modifying the rate of missing and non-missing values in this selected variable. And objective evaluation of data sets can be achieved by comparing, the result of a data set with non-missing variable with that of C4.5 which is a known knowledge acquisition tool in machine learning.

Survey of Intellectual Property Rights in the Ergonomics Field in Korea

  • Park, Jemo;Hwang, Jung Bo;Jung, Hwa Shik
    • Journal of the Ergonomics Society of Korea
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    • v.34 no.5
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    • pp.487-499
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    • 2015
  • Objective: The purpose of this study was to analyze the trend of ergonomics field in overall intellectual property rights in Korea, and suggest the direction for the future development. Background: Many ergonomists are trying to pursue optimal human well-being and safety, and create more convenient designs for human use. For these reasons, intellectual property rights may be used to protect the legitimate rights of originative and innovative ergonomic designs. Method: Intellectual property rights were reviewed by using Korea Intellectual Property Rights Information Service (KIPRIS), and then were classified and analyzed according to three intellectual property rights (patent, utility model, design), International Patent Classification (IPC) and ergonomics application areas. Results: The total number of intellectual property rights registered in the ergonomics field in terms of three intellectual property rights (patent, utility model, design) showed 48,814 which occupied 5.97% of the total registered Korea's intellectual property rights. Within three intellectual property rights, patent (87%) was recorded overwhelmingly higher than utility model (9%) and design (4%). Conclusion: The current trend of patent, utility model and design in the ergonomics field in Korea tend to increase over time. It is suggested based on the analysis in this study that continuing research and development should be focused on electricity section in accordance with the global trend. Application: The results of this study can direct the ergonomists to the areas of intellectual property rights in the ergonomics field that should focus on the research and development in terms of three intellectual property rights, IPC and ergonomics application areas.

A Basic Study on Implementing Optimal Function of Motion Sensor for Bridge Navigational Watch Alarm System

  • Jeong, Tae-Gweon;Bae, Dong-Hyuk
    • Journal of Navigation and Port Research
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    • v.38 no.6
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    • pp.645-653
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    • 2014
  • A Bridge Navigational Watch Alarm System (hereafter 'BNWAS') is to monitor and detect if an officer of watch(hereafter 'OOW') keeps a sharp lookout on the bridge. The careless lookout of an OOW could lead to marine accidents. For this reason on June 5th, 2009, IMO decided that a ship is equipped with a BNWAS. However, an existing BNWAS gives the OOW a lot of inconvenience and stress in its operation. It requires that the OOW should press reset buttons to confirm their alert watch on the bridge at every three to twelve minute. Many OOWs have complained that at some circumstances they cannot focus on their bridge activities including watch-keeping due to a lots of resetting inputs of BNWAS. Accordingly, IMO has allowed the use of a motion sensor as a resetting device. The motion sensor detects the movements of human body on the bridge and subsequently sends reset signals directly to BNWAS automatically. As a result, OOWs can work uninterrupted. However, some of classification societies and flag authorities have a slightly different stance on the use of motion sensor as a resetting method for BNWAS. The reason is that the motion sensor may trigger false reset signals caused by the motion of objects on the bridge, especially a slight movement such as toss and turn of human body which can extend the period of careless watch. As a basic study to minimize the false reset signals, this paper proposes a simple configuration of BNWAS, which consists of only three motion sensors associated with 'AND' and 'OR' logic gates. Additionally, several considerations are also proposed for the implementation of motion sensors. This study found that the proposed configuration which consists of three motion sensors is better than an existing one by reducing false reset signals caused by a slight movement of human body in one's sleep. The proposed configuration in this paper filters false reset signals and is simple to be implemented on existing vessels. In addition, it can be easily installed just by a basic electrical knowledge.

Estimation of Design Rainfall by the Regional Frequency Analysis using Higher Probability Weighted Moments and GIS Techniques(I) (고차확률가중모멘트법에 의한 지역화빈도분석과 GIS기법에 의한 설계강우량 추정(I) -동질성의 지역구분 방법을 중심으로-)

  • 이순혁;박종화;류경식;지호근;전택기;신용희
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.4
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    • pp.57-68
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    • 2001
  • It is matter of common knowledge to give impetus to the water resources development to cope with increasing demand and supply for the water utilization project including agricultural living and industrial water owing to the economic and civilization development in recent years. Regional design rainfall is necessary or the design of the dam reservoir levee and drainage facilities for the development of various kinds of essential waters including agricultural water. For the estimation of the regional design rainfall classification of the climatologically an geographically homogeneous regions should be preceded preferentially This study was mainly conducted to derive the optimal regionalization of the precipitation data which can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Wulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analysis. Both K-means clustering and mean annual precipitation methods are used to identify homogeneous regions all over the regions. Nine and five homogeneous regions for the precipitation were classified by the K-means clustering and mean annual methods, respectively. Finally, Five homogeneous regions were established by the trial and error method with homogeneity test using statistics of $\chi$$^2$ distribution.

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Improving Weak Classifiers by Using Discriminant Function in Selecting Threshold Values (판별 함수를 이용한 문턱치 선정에 의한 약분류기 개선)

  • Shyam, Adhikari;Yoo, Hyeon-Joong;Kim, Hyong-Suk
    • The Journal of the Korea Contents Association
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    • v.10 no.12
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    • pp.84-90
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    • 2010
  • In this paper, we propose a quadratic discriminant analysis based approach for improving the discriminating strength of weak classifiers based on simple Haar-like features that were used in the Viola-Jones object detection framework. Viola and Jones built a strong classifier using a boosted ensemble of weak classifiers. However, their single threshold (or decision boundary) based weak classifier is sub-optimal and too weak for efficient discrimination between object class and background. A quadratic discriminant analysis based approach is presented which leads to hyper-quadric boundary between the object class and background class, thus realizing multiple thresholds based weak classifiers. Experiments carried out for car detection using 1000 positive and 3000 negative images for training, and 500 positive and 500 negative images for testing show that our method yields higher classification performance with fewer classifiers than single threshold based weak classifiers.

Nano Technology Trend Analysis Using Google Trend and Data Mining Method for Nano-Informatics (나노 인포매틱스 기반 구축을 위한 구글 트렌드와 데이터 마이닝 기법을 활용한 나노 기술 트렌드 분석)

  • Shin, Minsoo;Park, Min-Gyu;Bae, Seong-Hun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.237-245
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    • 2017
  • Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

Human Activity Recognition Using Sensor Fusion and Kernel Discriminant Analysis on Smartphones (스마트폰에서 센서 융합과 커널 판별 분석을 이용한 인간 활동 인식)

  • Cho, Jung-Gil
    • Journal of the Korea Convergence Society
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    • v.11 no.5
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    • pp.9-17
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    • 2020
  • Human activity recognition(HAR) using smartphones is a hot research topic in computational intelligence. Smartphones are equipped with a variety of sensors. Fusing the data of these sensors could enable applications to recognize a large number of activities. However, these devices have fewer resources because of the limited number of sensors available, and feature selection and classification methods are required to achieve optimal performance and efficient feature extraction. This paper proposes a smartphone-based HAR scheme according to these requirements. The proposed method in this paper extracts time-domain features from acceleration sensors, gyro sensors, and barometer sensors, and recognizes activities with high accuracy by applying KDA and SVM. This approach selects the most relevant feature of each sensor for each activity. Our comparison results shows that the proposed system outperforms previous smartphone-based HAR systems.

The similarities analysis of location fishing information through 2 step clustering (2단계 군집분석을 통한 해구별 조업정보의 유사성 분석)

  • Cho, Yong-Jun
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.551-562
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    • 2009
  • In this paper, I would present a using method for The Fishing Operation Information(FOI) of National Federation of Fisheries Cooperatives(NFFC) through the availabilities analysis and put out the similarities by the section of the sea through classifying characteristics of fishing patterns by their locations. As a result, although the catch of FOI is nothing more than 33% level to National Fishery Production Statistics(NFPS), FOI data is useful in understanding the patterns of fishing operation by the location because both patterns and correlation were very similar in the usability analysis, comparing the FOI data with NFPS. So I classified optimal clusters for catch, the number of fishing days and the number of fishing vessels through 2 step cluster analysis by the big marine zone and divided fishing patterns.

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Estimation of Residual Strength for an Aged Floating Dock (노후화된 플로팅도크의 잔류 구조강도 평가)

  • Seo, Kwang-Cheol;Hong, Taeho;Park, Joo-Shin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.25 no.1
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    • pp.122-129
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    • 2019
  • Due to its nature the manufacturing industry faces a cyclical economy, and therefore there is an urgent need for a companion industry to cope with this cyclic pattern in the long run. The sector suitable for meeting this demand is the repair and shipbuilding industry. In order to operate a shipbuilding repair business, a floating dock is indispensable, and most obsolete floating docks were imported from overseas and operated through repair/maintenance. However, there is no precise guideline for floating dock safety, and most models have been in use for at least 30 years without being required to enter classification at the time of operation. In this study, structural strength analysis was carried out using measured thickness information of aged floating docks, and the residual structural strength of floating docks in operation was analyzed. The main results derived from this study can be referred to as guidelines for the review of the structural safety of similar equipment, and it is expected that an optimal solution will be found within a short time using this method for repair/maintenance.

Prediction of replacement period of shield TBM disc cutter using SVM (SVM 기법을 이용한 쉴드 TBM 디스크 커터 교환 주기 예측)

  • La, You-Sung;Kim, Myung-In;Kim, Bumjoo
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.21 no.5
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    • pp.641-656
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    • 2019
  • In this study, a machine learning method was proposed to use in predicting optimal replacement period of shield TBM (Tunnel Boring Machine) disc cutter. To do this, a large dataset of ground condition, disc cutter replacement records and TBM excavation-related data, collected from a shield TBM tunnel site in Korea, was built and they were used to construct a disc cutter replacement period prediction model using a machine learning algorithm, SVM (Support Vector Machine) and to assess the performance of the model. The results showed that the performance of RBF (Radial Basis Function) SVM is the best among a total of three SVM classification functions (80% accuracy and 10% error rate on average). When compared between ground types, the more disc cutter replacement data existed, the better prediction results were obtained. From this results, it is expected that machine learning methods become very popularly used in practice in near future as more data is accumulated and the machine learning models continue to be fine-tuned.