• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.47-54
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• 2015

The number of users of SNS such as Twitter and Facebook increases due to the development of internet and the spread of supply of mobile devices such as smart phone. Moreover, there are also an increasing number of content pollution problems that pollute SNS by posting a product advertisement, defamatory comment and adult contents, and so on. This paper proposes an improved method of extracting the feature of content polluter for detecting a content polluter in SNS. In particular, this paper presents a method of extracting the feature of content polluter on the basis of incremental approach that considers only increment in data, not batch processing system of entire data in order to efficiently extract the feature value of new user data at the stage of predicting and classifying a content polluter. And it comparatively assesses whether the proposed method maintains classification accuracy and improves time efficiency in comparison with batch processing method through experiment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.98-105
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• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.631-634
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• 2008

인터넷을 이용한 사람들의 사회 참여가 확대되면서 다양한 의견(Opinion)들이 급속도로 증가하고 있으며 이러한 의견을 분석하여 유용한 정보로 활용하기 위한 연구가 활발히 진행되고 있다. 그 중에서도 상품리뷰는 기업에서 연구, 개발, 마케팅의 주요 자료로 사용되고 있으며 사용자가 상품의 구매를 결정하는 중요한 요인 중 하나로 작용하고 있다. 본 논문에서는 한국어로 이루어진 상품 리뷰를 분석하여 의견 자질(Feature)을 추출하고 분류(Classification)하는 시스템을 설계하고 구현하였다. 한글 의견 자질 추출을 위하여 먼저 한글 상품 리뷰를 분석하여 의견 사전을 구축하였다. 의견 사전으로는 의견 자질과 의견 어휘, 독립의견어휘, 의견 숙어, 부정어 등의 각기 다른 세부 사전을 구축하여 리뷰 분석 시 단계적으로 적용하여 정확도를 높일 수 있도록 설계하였다. 이렇게 구현된 시스템을 평가하기 위하여 각기 다른 3개의 도메인에서 실제 한국어 리뷰를 수집하여 실험을 수행하였으며 자질 추출에서는 평균 78.86% 정확률, 61.41% 재현율을, 극성 분류에서는 평균 69.46% 정확률, 42.26% 재현율을 나타냈다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.155-162
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• 2016

In recent years, hoping the interaction of individuals and rather than software development process and tools, and customers want software that works first, rather than a comprehensive document, in cooperation with the customer, rather than the developer negotiate a contract, to each other stick to the plan I think even more so than the value that corresponds to the change. In view of this, software development is given the autonomy and motivation to project team rather than process-oriented and have a passion and vision and human relations oriented management approach is required. In recent years, increasing the productivity benefits of agile development processes, improved quality, efficiency and customer satisfaction as is demonstrated in the methodology selected to promote the project, attention was given to the experts. Contemporary demands with regard to the methodology chosen to meet your needs, in this paper in the organization, and to solve the problems of product-based Cross functional team proposed methodology Feature Team model, this model is an organizational Cross functional team and the team is not the outcome (product) basis, were examined for the model that points to progress the development across multiple product as a functional unit, value-plan through the driven agile technique-based model and proposed a difference. And the domain analysis, required extraction by conventional JAD (joint application development) meeting the targets for the object-oriented modeling, in modeling and organize, review, aware in advance and the UML Structure and Behavior Diagrams and proposed to proceed with the project.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.131-137
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• 2014

Although illegal reproduction of cartoon books are prevalent with rapid growth of webhard services and smartphone use, fingerprinting technology for product identification, as seen in music and videos, has not been developed yet. This leads to indiscriminate illegal reproduction of cartoon books, causing great amount of copyright damages from copyright infringement of the rightful owners. The copyright R&D project granted from the Korea Copyright Permission (Project Title: Identification and Copy Protection Technology of Bookscaned Text/Comic Books) has been carried out in order to develop technology to effectively identify illegal reproduction and distribution of scanned cartoon books. The developed technology will contribute to increase of royalty payments and robust ecosystem of cartoon book markets. The study is to propose an enhanced implementation model for identification of scanned cartoon books on the basis of hierarchical symmetric difference feature algorithms adopted from existing feature extraction algorithms for video.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1157-1162
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.813-822
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• 2012

Abnormal operating sounds radiated from a moving transfer robot in LCD (liquid crystal display) product lines have been used for the fault detection line of a robot instead of other source signals such as vibrations, acoustic emissions, and electrical signals. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone, despite a relatively low sensitivity. The wavelet packet transform for feature extraction and the artificial neural network for fault classification are employed. It can be observed that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.394-399
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• 2012

In recent years, MEMS sensors show huge attraction in machine condition monitoring, which have advantages in power, size, cost, mobility and flexibility. They can integrate with smart sensors and MEMS sensors are batch product. So the prices are cheap. And the suitability of it for condition monitoring is researched by experimental study. This paper presents a comparative study and performance test of classification of MEMS sensors in target machine fault classification by 3 intelligent classifiers. We attempt to signal validation of MEMS sensor accuracy and reliability and performance comparisons of classifiers are conducted. MEMS accelerometer and MEMS current sensors are employed for experiment test. In addition, a simple feature extraction and cross validation methods were applied to make sure MEMS sensors availabilities. The result of application is good for using fault classification.

• Management & Information Systems Review
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• v.3
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.587-591
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.