• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1462-1477
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• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.50-54
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• 1999

This paper is proposed to image retrieval system using color and shape feature. Color feature used to four maximum value feature among the maximum value extracted from local color distribution histogram. The preprocessing of shape feature consist of edge extraction and weight central point extraction and angular sampling. The sum of distance from weight central point to contour and variation and max/min used to shape feature. The similarity is estimated compare feature of query image with the feature of images in database and the candidate of image is retrieved in order of similarity. We evaluate the effectiveness of shape feature and color feature in experiment used to two hundred of the closed image. The Recall and the Precision is each 0.72 and 0.53 in the result of average experiment. So the proposed method is presented useful method.

• The Korea Journal of Herbology
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• v.27 no.3
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• pp.15-21
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• 2012

Objective : This study aimed to compare the difference between $Angelica$ $decursiva$, Peucedanum $praeruptorum$ and $Anthriscus$ $sylvestris$ which have been used as herbal medicine, Jeonho (Angelicae Decursivae Radix) in Korea and provided the evidence to exclude $A.$ $sylvestris$ not to use as Joenho. Methods : The similarities of original medicinal herb with samples from local market were evaluated including morphological appearance and chromatographic fingerprint. In addition, relation between original medicinal herb and local samples were analyzed using statistical clustering methods. Results : $A.$ $decursiva$, $P.$ $praeruptorum$ and $A.$ $sylvestris$ represented different morphological appearances and chromatographic fingerprint. Several samples from China exhibited similar morphological and chromatographic appearance with $A.$ $decursiva$ or $P.$ $praeruptorum$. Eleven samples from Korea showed identical similarity to $A.$ $sylvestris$. Conclusions : Since $A.$ $sylvestris$ represented obvious differences compared to $A.$ $decursiva$ and $P.$ $praeruptorum$, it is required not to use $A.$ $sylvestris$ as medicinal herb, Jeonho. Additionally, exact identification and quality control must be applied to $A.$ $decursiva$ or $P.$ $praeruptorum$ from China in order to maintain therapeutical efficacy.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.147-153
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• 2014

In this paper, we present a non-dyadic lens distortion correction model and image restoration method based on local self-similarity to remove jagging and blurring artifacts in the peripheral region of the geometrically corrected image. The proposed method can be applied in various application areas including vehicle real-view cameras, visual surveillance systems, and medical imaging systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.47-53
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• 2023

Devices such as X-Ray, CT, MRI, scanners, etc. can generate S&P noise from several sources during the image acquisition process. Since S&P noise appearing in the image degrades the image quality, it is essential to use noise reduction technology in the image processing process. Various methods have already been proposed in research on S&P noise removal, but all of them have a problem of generating residual noise in an environment with high noise density. Therefore, this paper proposes a filtering algorithm based on a three-dimensional plane equation by setting the grayscale value of the image as a new axis. The proposed algorithm subdivides the local mask to design the three closest non-noisy pixels as effective pixels, and applies cosine similarity to a region with a plurality of pixels. In addition, even when the input pixel cannot form a plane, it is classified as an exception pixel to achieve excellent restoration without residual noise.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.679-684
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• 2023

Venous puncture is widely used to obtain blood samples for pathological examination. Because the invasive venipuncture method using a needle is repeatedly performed, the pain suffered by the patient increases, so our research team pre-developed a miniaturized near-infrared (NIR) imaging system in advance. To improve the image quality of the acquired NIR images, this study aims to model the non-local means (NLM) algorithm, which is well known to be efficient in noise reduction, and analyze its applicability in the system. The developed NIR imaging system is based on the principle that infrared rays pass through dichroic and long-pass filters and are detected by a CMOS sensor module. The proposed NLM algorithm is modeled based on the principle of replacing the pixel from which noise is to be removed with a value that reflects the distances between surrounding pixels. After acquiring an NIR image with a central wavelength of 850 nm, the NLM algorithm was applied to segment the final vein area through histogram equalization. As a result, the coefficient of variation of the NIR image of the vein using the NLM algorithm was 0.247 on average, which was an excellent result compared to conventional filtering methods. In addition, the dice similarity coefficient value of the NLM algorithm was improved by 62.91 and 9.40%, respectively, compared to the median filter and total variation methods. In conclusion, we demonstrated that the NLM algorithm can acquire accurate segmentation of veins acquired with a NIR imaging system.

• Journal of the Korean Institute of Rural Architecture
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• v.21 no.4
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• pp.61-68
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• 2019

This research aimed to propose an organizational system that implements a planning agreement in local small and medium sized city, Korea. To conduct this research, three successful cases were deduced using integration systems to investigate purpose and background of the planning agreement. Articles, reports, media, and participation in meetings and workshops related on this topic are used for collecting data and interview of regional activists and experts, and public officials were carried out. Among them, the case of Yeongju city that used the new integration system instead of pre-adminstration system was examined in detail. There are three local governments; Yeongwol-gun, Jeungpyeong-gun, and Yeongju city which have successfully fulfilled projects from various departments of central adminstration not projects of planning agreement. The similarity noticed between those three cases is to continue various projects from several departments of central adminstration for numerous years and contribute to regional revitalization. A successful factor was to establish organizational system and manage it for the integration plan and performance for appropriate regional and administrative characteristics. In particular, in the case of Yeongju city, organization for urban architectural management composed of civilian experts were formed, authorized status on administrative organization was established, and the function and role were identified. It is helpful to other local governments to carry out the projects of planning agreement as the case of Yeongju city is now a new method.

• Korean Journal of Environmental Biology
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• v.21 no.1
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• pp.45-51
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• 2003

Genetic diversity of local populations among geologically isolated groups of Rana amurensis was refined by sequence comparison of the mitochondrial (mt) 165 rDNA genes. Each 401 base pairs of DNA sequences, which was determined from four local populations of Rana amurensis, two local populations of R. nigromacutata, and three species of the genus Rana were used in this analysis. Despite morphological similarity of Rana amurensis, Korean populations were well distinguished from the other groups on the basis of 105 rDNA gene difference. Further analyses for additional local populations belonging to R. amurensis will be necessary to clarify the taxonomic status.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.101-109
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• 2011

In most of the urbanized cities, socio-economic attributes tend to cluster as patterns of similarity in space, namely spatial autocorrelation, by agglomeration forces. The classical linear regression model, the most frequently adopted in the trip generation step, cannot sufficiently represent this effect. In order to take into account the effect properly, we need a model which adequately deals with the spatial dependence patterns. In this study, the Geographically Weighted Regression (GWR) model is adopted as an alternative method for the local analysis of relationships in multivariate data sets; that is GWR extends this traditional regression framework by estimating local rather than global parameters. This study shows the existence of spatial effects in the production and attraction of home base/non-home based trips through the GWR model using travel data collected in Daegu metropolitan area. Furthermore, LISA is employed to verify the fact that the local spatial autocorrelation exists.