• Journal of the Institute of Electronics Engineers of Korea CI
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• 제38권1호
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• pp.19-25
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• 2001

A novel approach for the feature extraction of handwritten characters is proposed by using spatial filtering neural networks with 4 layers. The proposed system first removes rough pixels which are easy to occur in handwritten characters. The system then extracts and removes the boundary information which have no influence on characters recognition. Finally, The system extracts feature information and removes the noises from feature information. The spatial filters adapted in the system correspond to the receptive fields of ganglion cells in retina and simple cells in visual cortex. With PE2 Hangul database, we perform experiments extracting features of handwritten characters recognition. It will be shown that the network can extract feature informations from handwritten characters successfully.

• Proceedings of the KOSOMBE Conference
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• 대한의용생체공학회 1996년도 춘계학술대회
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• pp.175-178
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• 1996

The purpose of this thesis is the propose of various signal processing algorithm for the ECG(electrocardiogram) and the design of realtime automated ECG analyzer feasible with these algorithms. The algorithms are composed of (1)filtering procedure fer the estimation and removal of baseline drift, 60Hz power line interference, and muscle artifacts (2)detection procedure of QRS complex and P wave (3)typification procedure for the pattern classification according to the morphologies (4) selection of representative beat, significant point and wave boundary decision procedure and (5) parameter extraction and diagnosis procedure. All verifications are carried out between the algorithms proposed in this paper and other algorithms already proposed by many researchers, for the objective comparison in each procedure. The efficiency of proposed algorithms are demonstrated with the aid of internationally validated CSE database and the performances of filtering procedure are compared on artificial noise signal as well as actual ECG signals with appropriate noise components. for the comparison on the performance of designed automated ECG analyzer, the diagnosis results were compared with ECG analyzer manufactered by Fukuda denshi in Japan.

• The KIPS Transactions:PartB
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• 제14B권7호
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• pp.549-558
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• 2007

Collaborative filtering systems have problems when users rate items and the rated results depend on their feelings, as there is a possibility that the results include noise. The method proposed in this paper optimizes the matrix by excluding irrelevant ratings as information for recommendations from a user-item matrix using dispersion. It reduces the noise that results from predicting preferences based on original user ratings by inflecting the information for items and users on the matrix. The method excludes the ratings values of the utmost limits using a percentile to supply the defects of coefficient of variance and composes a weighted user-item matrix by combining the user coefficient of variance with the median of ratings for items. Finally, the preferences of the active user are predicted based on the weighted matrix. A large database of user ratings for movies from the MovieLens recommender system is used, and the performance is evaluated. The proposed method is shown to outperform earlier methods significantly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2010년도 추계학술대회
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• pp.129-132
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• 2010

Users can obtain useful information from large of data because of development of internet. Since these data rise continuously like stream data, it is required to extract the appropriate information efficiently for the user's needs. In the traditional scheme, they are acquired by processing the user queries after the occurred data are stored at a database. However, it is inefficient to process the user queries over the large volume of continuous data by using the traditional scheme. In this paper, we propose the Event-Profile Model to define the data occurrence on the internet as the events and the user's requirements as the profiles. We also propose and implement the filtering scheme to process the events and the profiles efficiently. We evaluate the performance of the proposed scheme and our experiments show that the new scheme outperforms the other on various dataset.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제20권8호
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• pp.1407-1414
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• 2016

In this study, we develop that Location Recommending System using personal emotion information based on Collaborative Filtering. Previous Location Recommending System recommended a place visited by the user of the rating or the pattern of location for the user place. These systems are not high user satisfaction because that dose not consider the user status or have not objectively the information. Using user's personal emotion information to recommend a high-affinity users who have visited the place felt similar emotions objectively can improve user satisfaction with the place. In this study, a user using a mobile application directly register the recognized emotion information using the current position and bio-signal, and using the registered information measuring the similarity of user with a similarity emotion, predicts a preference for the place it is recommended to emotional place. The system consists of a user interface, a database, a recommendation module.

• Journal of the Korean Society for information Management
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• 제20권4호통권50호
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• pp.23-48
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• 2003

In this study an information filtering system was implemented and a series of relevance feedback experiments were conducted using the system. For the relevance feedback, the original queries were searched against the database and the results were reviewed by the researchers. Based on users' online relevance judgements a pair of 17 refined queries were generated using two methods called 'co-occurrence exclusion method' and 'lower frequencies exclusion method,' In order to generate them, the original queries, the descriptors and category codes appeared in either relevant or irrelevant document sets were applied as elements. Users' relevance judgments on the search results of the refined queries were compared and analyzed against those of the original queries.

• Journal of Broadcast Engineering
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• 제13권5호
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• pp.662-676
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• 2008

This paper presents a video copy detection algorithm that blocks online transfer of illegally copied DTV broadcast programs. Particularly, the proposed algorithm establishes a set of keyframes by detecting abrupt changes of luminance, and then exploits the spatio-temporal features of keyframes. Comparing with the preregistered features stored in the database of DTV broadcast programs, the proposed scheme performs a function of video filtering in order to distinguish whether an uploaded video is illegally copied or not. Note that we analyze only a set of keyframes instead of an entire video frame. Thus, it is highly efficient to identify illegal copied video when we deal with a vast size of broadcast programs. Also, we confirm that the proposed technique is robust to a variety of video edit-effects that are often applied by online video redistribution, such as apsect-ratio change, logo insertion, caption insertion, visual quality degradation, and resolution change (downscaling). In addition, we perform a benchmark test in which the proposed scheme outperforms previous techniques.

• Journal of Service Research and Studies
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• 제5권2호
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• pp.25-33
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• 2015

As Data mining is a method of extracting the information based on the large data, the technique has been used in many application areas to deal with data in particular. However, the status of the algorithm that can deal with the healthcare data are not fully developed. In this paper, One of clustering algorithm, the EM and DBSCAN are used for performance comparison. It could be analyzed using by the same data. To do this, EM and DBSACN algorithm are changing performance according to the variables in Health expenditure database. Based on the results of the experimental data, We analyze more precise and accurate results using by Kernel Filtering. In this study, we tried comparison of the performance for the algorithm as well as attempt to improve the performance. Through this work, we were analyzed the comparison result of the application of the experimental data and of performance change according to expansion algorithm. Especially, Collects data from the various cluster using the medical record, it could be recommended the effective spending on medical services.

• Journal of Internet of Things and Convergence
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• 제10권1호
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• pp.21-27
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• 2024

This paper presents the implementation of a personalized real-time information-providing application utilizing filtering and web crawling technologies. The implemented application performs web crawling based on the user-set keywords within web pages, using the Jsoup library as a basis for the selected keywords. The crawled data is then stored in a MySQL database. The stored data is presented to the user through an application implemented using Flutter. Additionally, mobile push notifications are provided using Firebase Cloud Messaging (FCM). Through these methods, users can efficiently obtain the desired information quickly. Furthermore, there is an expectation that this approach can be applied to the Internet of Things (IoT) where big data is generated, allowing users to receive only the information they need.

• Journal of the Korean Institute of Landscape Architecture
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• 제45권4호
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• pp.131-142
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• 2017

This study aims to create a Local Climate Zone(LCZ) map of Seoul by using World Urban Database and Access Portal Tools(WUDAPT) protocol, and to analyze the characteristics of the Seoul LCZs. For this purpose, training samples of 17 LCZ types were collected by using Landsat images and Google Earth. LCZ Classification and Filtering were performed by SAGA GIS. An ArcGIS was used to analyze the characteristics of each LCZ type. The characteristics of the LCZ types were analyzed by focusing on building surface fraction ratio, impervious surface fraction ratio, pervious surface fraction ratio, building stories and air temperature. The results show that one filtering was found to be most appropriate. While Yangcheongu and Yeongdeungpogu with the higher annual and maximum mean air temperature than other areas have the higher rate of LCZ 3(compact low-rise) and LCZ 4(open high-rise), Jongnogu, Eunpyeonggu, Nowongu and Gwanakgu with the lower value have the higher rate of LCZ A(Dence trees). The values of building surface fraction ratio, impervious surface fraction ratio and building stories of each LCZ were included in the range of WUDAPT for most LCZs. However, the values of pervious surface fraction ratio were out of the range, in particular, in the LCZs 4~6 and 9~10. This study shows the usability and applicability of the WUDAPT methodology and its climate zone classification used in many countries as a basic data for the landscape planning and policy to improve the thermal environment in urban areas.