• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.683-690
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• 2009

Social Networks which is composed of network with an individual in the center in a web support mutual-understanding of information by searching user profile and forming new link. Therefore, if we apply the Social Network which consists of web users who have similar immanent information to web search, we can improve efficiency of web search and satisfaction of web user about search results. In this paper, first, we make a Social Network using web users linked directly or indirectly. Next, we calculate Similarity among web users using their immanent information according to topics, and then reconstruct Social Network based on varying Similarity according to topics. Last, we compare Similarity with Search Pattern. As a result of this test, we can confirm a result that among users who have high relationship index, that is, who have strong link strength according to personal attributes have similar search pattern. If such fact is applied to search algorithm, it can be possible to improve search efficiency and reliability in personalized and social search.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3E
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• pp.87-89
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• 2005

The acoustical sources of intake and exhaust systems in fluid machines are often characterized by the source impedance and strength using linear frequency-domain modeling. In the case of the sources which are nonlinear and time-variant, however, the source parameters were sometimes incorrectly obtained. In this paper, the source model and direct measurement technique are modified in order to evaluate the effect due to nonlinear and periodically time-varying source character as well as the linear property of the reflectivity of in-duct fluid machine source. With a priori known kinematical information of the source, the types of nonlinear time-variant terms can be presumed by a simple physical model, in which there is practically no restriction on the form of the model. The concept of source impedance can be extendable by introducing the linear frequency response function for each nonlinear or time-variant input. Extending the conventional method and adapting the reverse MISO technique, it is possible to develop a direct method that can deal with the nonlinear time-variant source parameters. The proposed direct method has a novel feature that there is no restriction on the probability or spectral natures of the excited sound pressure data. The present method is verified by the simulated measurements for simplified fluid machines. It is thought that the proposed method would be useful in predicting the insertion loss or the radiated sound level from intake or exhaust systems.

• Geomechanics and Engineering
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• v.31 no.5
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• pp.453-460
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• 2022

It is essential for geotechnical engineers to conduct studies and make predictions about the stability of slopes, since collapse of a slope may result in catastrophic events. The Gaussian process regression (GPR) approach was carried out for the purpose of predicting the factor of safety (FOS) of the slopes in the study that was presented here. The model makes use of a total of 327 slope cases from Iran, each of which has a unique combination of geometric and shear strength parameters that were analyzed by PLAXIS software in order to determine their FOS. The K-fold (K = 5) technique of cross-validation (CV) was used in order to conduct an analysis of the accuracy of the models' predictions. In conclusion, the GPR model showed excellent ability in the prediction of FOS of slope stability, with an R² value of 0.8355, RMSE value of 0.1372, and MAPE value of 6.6389%, respectively. According to the results of the sensitivity analysis, the characteristics (friction angle) and (unit weight) are, in descending order, the most effective, the next most effective, and the least effective parameters for determining slope stability.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.60-74
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• 2007

For quantitative analysis of spatio-temporal distribution pattern on marine environment, spatial autocorrelation statistics on the both global and local aspects was applied to the observed data obtained from Gwangyang Bay in South Sea of Korea. Global indexes such as Moran's I and General G were used for understanding environmental distribution pattern in the whole study area. LISAs (local indicators of spatial association) such as Moran's I ($I_i$) and $G_i{^*}$ were considered to find similarity between a target feature and its neighborhood features and to detect hot spot and/or cold spot. Additionally, the significance test on clustered patterns by Z-scores was carried out. Statistical results showed variations of spatial patterns quantitatively in the whole year. Then all of general water quality, nutrients, chlorophyll-a and phytoplankton had strong clustered pattern in summer. When global indexes showed strong clustered pattern, the front region with a negative $I_i$ which means a strong spatial variation was observed. Also, when global indexes showed random pattern, hot spot and/or cold spot were/was found in the small local region with a local index $G_i{^*}$. Therefore, global indexes were useful for observing the strength and time series variations of clustered patterns in the whole study area, and local indexes were useful for tracing the location of hot spot and/or cold spot. Quantification of both spatial distribution pattern and clustering characteristics may play an important role to understand marine environment in depth and to find the reasons for spatial pattern.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.449-458
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• 2010

As occasion demands to obtain efficient information from many documents and reviews on the Internet in many kinds of fields, automatic classification of opinion or thought is required. These automatic classification is called sentiment classification, which can be divided into three steps, such as subjective expression classification to extract subjective sentences from documents, sentiment classification to classify whether the polarity of documents is positive or negative, and strength classification to classify whether the documents have weak polarity or strong polarity. The latest studies in Opinion Mining have used N-gram words, lexical phrase pattern, and syntactic phrase pattern, etc. They have not used single word as feature for classification. Especially, patterns have been used frequently as feature because they are more flexible than N-gram words and are also more deterministic than single word. Theses studies are mainly concerned with English, other studies using patterns for Korean are still at an early stage. Although Korean has a slight difference in the meaning between predicates by the change of endings, which is 'Eomi' in Korean, of declinable words, the earlier studies about Korean opinion classification removed endings from predicates only to extract stems. Finally, this study introduces the earlier studies and methods using pattern for English, uses extracted sentimental patterns from Korean documents, and classifies polarities of these documents. In this paper, it also analyses the influence of the change of endings on performances of opinion classification.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.69-80
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• 1999

Recently, social requirements of personal identification techniques are rapidly expanding in a number of new application ares. Especially fingerprint recognition is the most important technology. Fingerprint recognition technologies are well established, proven, cost and legally accepted. Therefore, it has more spot lighted among the any other biometrics technologies. In this paper we propose a new on-line fingerprint recognition algorithm for non-inked type live scanner to fit their increasing of security level under the computing environment. Fingerprint recognition system consists of two distinct structural blocks: feature extraction and feature matching. The main topic in this paper focuses on the feature matching using the fingerprint minutiae (ridge ending and bifurcation). Minutiae matching is composed in the alignment stage and matching stage. Success of optimizing the alignment stage is the key of real-time (on-line) fingerprint recognition. Proposed alignment algorithm using clique shows the strength in the search space optimization and partially incomplete image. We make our own database to get the generality. Using the traditional statistical discriminant analysis, 0.05% false acceptance rate (FAR) at 8.83% false rejection rate (FRR) in 1.55 second average matching speed on a Pentium system have been achieved. This makes it possible to construct high performance fingerprint recognition system.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.287-295
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• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1814-1828
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• 2021

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.97-107
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• 2011

Nowadays there are a lot of issues about copyright infringement in the Internet world because the digital content on the network can be copied and delivered easily. Indeed the copied version has same quality with the original one. So, copyright owners and content provider want a powerful solution to protect their content. The popular one of the solutions was DRM (digital rights management) that is based on encryption technology and rights control. However, DRM-free service was launched after Steve Jobs who is CEO of Apple proposed a new music service paradigm without DRM, and the DRM is disappeared at the online music market. Even though the online music service decided to not equip the DRM solution, copyright owners and content providers are still searching a solution to protect their content. A solution to replace the DRM technology is digital audio watermarking technology which can embed copyright information into the music. In this paper, the author proposed a new audio watermarking algorithm with two approaches. First, the watermark information is generated by two dimensional barcode which has error correction code. So, the information can be recovered by itself if the errors fall into the range of the error tolerance. The other one is to use chirp sequence of CDMA (code division multiple access). These make the algorithm robust to the several malicious attacks. There are many 2D barcodes. Especially, QR code which is one of the matrix barcodes can express the information and the expression is freer than that of the other matrix barcodes. QR code has the square patterns with double at the three corners and these indicate the boundary of the symbol. This feature of the QR code is proper to express the watermark information. That is, because the QR code is 2D barcodes, nonlinear code and matrix code, it can be modulated to the spread spectrum and can be used for the watermarking algorithm. The proposed algorithm assigns the different spread spectrum sequences to the individual users respectively. In the case that the assigned code sequences are orthogonal, we can identify the watermark information of the individual user from an audio content. The algorithm used the Walsh code as an orthogonal code. The watermark information is rearranged to the 1D sequence from 2D barcode and modulated by the Walsh code. The modulated watermark information is embedded into the DCT (discrete cosine transform) domain of the original audio content. For the performance evaluation, I used 3 audio samples, "Amazing Grace", "Oh! Carol" and "Take me home country roads", The attacks for the robustness test were MP3 compression, echo attack, and sub woofer boost. The MP3 compression was performed by a tool of Cool Edit Pro 2.0. The specification of MP3 was CBR(Constant Bit Rate) 128kbps, 44,100Hz, and stereo. The echo attack had the echo with initial volume 70%, decay 75%, and delay 100msec. The sub woofer boost attack was a modification attack of low frequency part in the Fourier coefficients. The test results showed the proposed algorithm is robust to the attacks. In the MP3 attack, the strength of the watermark information is not affected, and then the watermark can be detected from all of the sample audios. In the sub woofer boost attack, the watermark was detected when the strength is 0.3. Also, in the case of echo attack, the watermark can be identified if the strength is greater and equal than 0.5.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1272-1277
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• 2010

Target detection and tracking wireless sensor network must have various signal processing ability. Wireless sensor nodes need to light weight signal processing algorithm because of energy constraints and communication bandwidth constraints. General signal processing algorithm of wireless sensor node consists of de-noising, received signal strength computation, feature extraction and signal compression. Wireless sensor network life-time and performance of target detection and classification depend on sensor node signal processing. In this paper, we propose energy efficient signal processing algorithm using wavelet transform. The proposed method estimates exact target position.