• Proceedings of the Korea Inteligent Information System Society Conference
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.416-425
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• 2003

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering (CF) has been known to be the most successful recommendation technology. However its widespread use in e-commerce has exposed two research issues, sparsity and scalability. In this paper, we propose several hybrid recommender procedures based on web usage mining, clustering techniques and collaborative filtering to address these issues. Experimental evaluation of suggested procedures on real e-commerce data shows interesting relation between characteristics of procedures and diverse situations.

• Journal of Environmental Health Sciences
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• 제30권5호
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• pp.432-439
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• 2004

Korean certification regulation for particulate filtering respirators requires inward leakage (IL) test as European Standards (EN) and the standard levels of regulation are the same as those of EN. This study was conducted to evaluate particulate filtering respirators being commercially used in the market by using IL and assess the characteristics of IL. The study began with discussing the concept of IL, comparison of IL with fit test, and IL measurement method. Three brands of half masks and 10 brands of filtering facepieces (two top class, four 1st class and four 2nd class), total 13 brands respirators, and 10 test panels (subjects) who were classified in 9 facial grids in accordance with face length and lip length, were selected for IL test. IL tests were conducted in the laboratory of 3M Innovation Center which was established by EN standard. As expected ILs of half masks were lower than those of filtering facepiece mask. ILs of half masks and some filtering facepieces were significantly different in manufacturers. ILs of 1st class filtering facepieces were found to be much more than those of 2nd class and thus the result would cause wearers to get confused to select a mask. Four of six brands being no compliance with standards were thought that they should be tested again for certification because of a lot of differences from standards. There were no significant differences among ILs of five exercises. In 6 out of 13 brands lognormal distribution of ILs may be a better fit distribution and in 7 brands both lognormal and normal distributions were rejected. The result indicates that geometric mean may be better than arithmetic mean to establish standard.

• Transactions of the Korean Society of Automotive Engineers
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• 제1권3호
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• pp.55-62
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• 1993

Autoregressive moving average(ARMA) model which is a time domain parametric modeling method is implemented for modeling and reproducing characteristics of exhaust noise of an automobile in various RPM range. Experiments have been carried out using 9 set of exhaust noise signals measured at 1,000-3,000 RPM range. Characteristics of sampled signals were estimated using ARMA modeling and Akaike's FPE(final prediction error) criterion to define exact model structure and for model validation. The digital filter consisted of the esitmated ARMA(70,1) model parameters was programed to reproduce exhaust noise. The spectral analysis of reproduced noise is very close to original. The results show that our approaching technique for reproducing acoustic characteristics is valid and feasible to apply in the field of noise quality control.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제29권6호
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• pp.641-650
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• 2011

Airborne LIDAR system, utilized in various forest studies, provides efficiently spatial information about vertical structures of forest areas. The tree height is one of the most essential measurements to derive forest information such as biomass, which can be estimated from the forest terrain model. As the terrain model is generated by the interpolation of ground points extracted from LIDAR data, filtering methods with high reliability to classify reliably the ground points are required. In this paper, we applied three representative filtering methods to forest LIDAR data with diverse characteristics, measured the errors and performance of these methods, and analyzed the causes of the errors. Based on their complementary characteristics derived from the analysis results, we have attempted to combine the results and checked the performance improvement. In most test areas, the convergence method showed the satisfactory results, where the filtering performance were improved more than 10% in maximum. Also, we have generated DTM using the classified ground points and compared with the verification data. The DTM retains about 17cm RMSE, which can be sufficiently utilized for the derivation of forest information.

• Tribology and Lubricants
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• 제39권4호
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• pp.133-138
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• 2023

This paper presents a discussion on lubricating oil filters. The maintenance of lubricating oil filters can improve the performance of mechanical systems and extend the service life of the lubricating oil. Therefore, the effective management of the lubricating oil can extend the service life of the machine and reduce maintenance costs. A representative method for managing lubricating oil is filtering the lubricating oil using a lubricant filter. However, effectively managing a lubricating oil using a lubricant filter requires an understanding of the related knowledge. In this paper, we present the definition, classification, characteristics, specifications, performance, and self-cleaning function of lubricating oil filters. The lubricant filters are classified based on the filter material, filtering method, filtering location, and amount of filtered fluid. Cellulose and glass fiber materials are conventionally used as materials for lubricant filters, and recently, metal materials, which show excellent durability, are being increasingly adopted. The filtering methods can be classified into physical, chemical, magnetic, and electric field methods, and the lubricant filters can be classified according to their location in the lubrication system. The beta ratio and efficiency of the lubricant filter can be determined based on the performance of the filter. Finally, there are many products or technologies that add a self-cleaning function to the filter to remove foreign substances or contaminants for efficient management.

• The Journal of Korean Association of Computer Education
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• 제6권2호
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• pp.147-156
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• 2003

Collaborative Filtering is a popular technology in electronic commerce, which adapt the opinions of entire communities to provide interesting products or personalized resources and items. It has been applied to many kinds of electronic commerce domain since Collaborative Filtering has proven an accurate and reliable tool. But educational application remain limited yet. We design collaborative filtering recommendation system using user's ratings in educational contents recommendation. Also We propose a method of similarity compensation using user's information for improvement of recommendation accuracy. The proposed method is more efficient than the traditional collaborative filtering method by experimental comparisons of mean absolute error(MAE) and reciever operating characteristics(ROC) values.

• Journal of the Korea Society of Computer and Information
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• 제28권7호
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• pp.19-27
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• 2023

In the process of collecting social reviews, a number of noise reviews irrelevant to a given search keyword can be included in the search results. To filter out such reviews, machine learning can be used. However, if the number of reviews is insufficient for a target place to be analyzed, filtering accuracy can be degraded due to the lack of training data. To resolve this issue, we propose a supervised learning method to improve accuracy of the noise review filtering for the places with insufficient reviews. In the proposed method, training is not performed by an individual place, but by a group including several places with similar characteristics. The classifier obtained through the training can be used for the noise review filtering of an arbitrary place belonging to the group, so the problem of insufficient training data can be resolved. To verify the proposed method, a noise review filtering model was implemented using LSTM and BERT, and filtering accuracy was checked through experiments using real data collected online. The experimental results show that the accuracy of the proposed method was 92.4% on the average, and it provided 87.5% accuracy when targeting places with less than 100 reviews.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• 제24권11호
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• pp.915-919
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• 2011

We analyzed various forces affective to the charged particles in closed space, to explain the image degradation and lifetime-shortening phenomena because of particle lumping which is one of the serious problems in reflective displays. It is possible to predict the quantity of q/m which is the most important parameter in determining the optical and electrical characteristics, by calculating the image force and kinetic energy. For stable driving, the quantity of q/m must be in the defined range but it changes during the fabrication process, so we added the filtering process to solve this problem and obtained the well-defined nonlinear driving voltage coinciding with the threshold voltage. And we obtained the fully-driving property which prevents the particle lumping and decides the image quality and lifetime of panel from the optical characteristics and occupation surface of moving particles.

• Korean Journal of Remote Sensing
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• 제22권6호
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• pp.533-542
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• 2006

Lidar point clouds provide three dimensional information of terrain surface and have a great advantage to generate precise digital elevation model (DEM), particularly over forested area where some laser signals are transmitted to vegetation canopy and reflected from the bare ground. This study initially investigates the characteristics of lidar-derived height information as related to vertical structure of forest stands. Then, we propose a new filtering method to separate ground points from Lidar point clouds, which is a prerequisite process both to generate DEM surface and to extract biophysical information of forest stands. Laser points clouds over the forest stands in central Korea show that the vertical distribution of laser points greatly varies by the stand characteristics. Based on the characteristics, the proposed filtering method processes first and last returns simultaneously without setting any threshold value. The ground points separated by the proposed method are used to generate digital elevation model, furthermore, the result provides the possibilities to extract other biophysical characteristics of forest.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.117-122
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• 2002

Electrical discharge machining uses thermal energy from electrical discharge, while wire electrical discharge machining (WEDM) technology is widely used in conductive material machining. This paper proposes a method for evaluating the characteristics of wires in WEDM. In order to evaluate the wire processing performance, processing speed and roughness, straightness, corner processing have been assessed with precision experiment equipment and image processing including Laplacian filtering with various threshold levels.