• Korean Journal of Computational Design and Engineering
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• v.12 no.2
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• pp.146-152
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• 2007

Presented in the paper is an algorithm to generate a section curve by slicing a point cloud which may include tens of thousands of points. Although there are couple of previous results, they are very sensitive on the density variations and local noising points. In the paper, three technological requirements are identified; 1) dominant point sampling, 2) avoiding local vibration, and 3) robustness on the density changes. To satisfy these requirements, we propose a new slicing algorithm which is based on a node-circle diagram. The algorithm has been implemented and tested with various examples.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.692-703
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• 2021

Recently, with the development of computer graphics technology, research on technology for expressing real objects as more realistic virtual graphics is being actively conducted. Point cloud is a technology that uses numerous points, including 2D spatial coordinates and color information, to represent 3D objects, and they require huge data storage and high-performance computing devices to provide various services. Video-based Point Cloud Compression (V-PCC) technology is currently being studied by the international standard organization MPEG, which is a projection based method that projects point cloud into 2D plane, and then compresses them using 2D video codecs. V-PCC technology compresses point cloud objects using 2D images such as Occupancy map, Geometry image, Attribute image, and other auxiliary information that includes the relationship between 2D plane and 3D space. When increasing the density of point cloud or expanding an object, 3D calculation is generally used, but there are limitations in that the calculation method is complicated, requires a lot of time, and it is difficult to determine the correct location of a new point. This paper proposes a method to generate additional points at more accurate locations with less computation by applying 2D interpolation to the image on which the point cloud is projected, in the V-PCC technology.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.47 no.6
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• pp.164-169
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• 2015

Nowadays blending ratio of OMG (old magazine) in recovered paper used for manufacturing newspaper have been increased. When large amount of OMG is consumed in newsprint mill, brightness can be improved by inorganic pigments of coating layer. On the other hand decrease in yield of deinking process will be encountered because the pigments can be removed as reject of froth flotation process. Therefore selection of the optimal deinking agent is an important. Non-ionic surfactant have been used widely in newsprint mill. Non-ionic surfactant has amphoteric characteristics. Hydrophilic group is ethylene and propylene oxide that can induce hydrogen bonding with water molecules. In this regard, cloud point is an important parameter in order to control efficiency of deinking process because hydration of the hydrophobic group can be varied according to temperature of a system. In this study, deinking properties of ONP at high blending ratio of OMG was analyzed according to cloud points of non-ionic surfactants. $L^*$, $a^*$, $b^*$, brightness and effective residual ink concentration did not affected by the change of cloud points. Especially, flotation reject decreased significantly according to increase in cloud point of the non-ionic surfactant. Consequently, when a nonionic surfactant having a cloud point higher than the temperature of the system is used, properties of the deinked pulp can be maintained and yield of deinking process can be improved.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2034-2042
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• 2006

In this study, a complete 3D surface reconstruction method is proposed based on the concept that the vertices, of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out. Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.135-149
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• 2016

Cloud radio access network (C-RAN) refers to the virtualization of base station functionalities by means of cloud computing. This results in a novel cellular architecture in which low-cost wireless access points, known as radio units or remote radio heads, are centrally managed by a reconfigurable centralized "cloud", or central, unit. C-RAN allows operators to reduce the capital and operating expenses needed to deploy and maintain dense heterogeneous networks. This critical advantage, along with spectral efficiency, statistical multiplexing and load balancing gains, make C-RAN well positioned to be one of the key technologies in the development of 5G systems. In this paper, a succinct overview is presented regarding the state of the art on the research on C-RAN with emphasis on fronthaul compression, baseband processing, medium access control, resource allocation, system-level considerations and standardization efforts.

• Convergence Security Journal
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• v.17 no.3
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• pp.15-20
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• 2017

Cloud computing is a service that to use IT resources (software, storage, server, network) through various equipment in an Internet-enabled environment. Due to convenience, efficiency, and cost reduction, the utilization rate has increased recently. However, Cloud providers have become targets for attack Also, Abuse of cloud service is considered as the top security threat. The existing digital forensic procedures are suitable for investigations on individual terminals. In this paper, we propose a new investigation model by analyzing the vulnerable points that occur when you investigate the cloud environment with the existing digital forensic investigation procedure. The proposed investigation model adds a way to obtain account information, and can apply public cloud and private cloud together. Cloud services are also easily accessible and are likely to destroy digital evidence. Therefore, the investigation model was reinforced by adding an account access blocking step.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.553-565
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• 2021

Point cloud is a set of points for representing a 3D object, and consists of geometric information, which is 3D coordinate information, and attribute information, which is information representing color, reflectance, and the like. In this way of expressing, it has a vast amount of data compared to 2D images. Therefore, a process of compressing the point cloud data in order to transmit the point cloud data or use it in various fields is required. Unlike color information corresponding to all 2D geometric information constituting a 2D image, a point cloud represents a point cloud including attribute information such as color in only a part of the 3D space. Therefore, separate processing of geometric information is also required. Based on these characteristics of point clouds, MPEG under ISO/IEC standardizes V-PCC, which imitates point cloud images and compresses them into 2D DCT-based 2D image compression codecs, as a compression method for high-density point cloud data. This has limitations in accurately representing 3D spatial information to proceed with compression by converting 3D point clouds to 2D, and difficulty in processing non-existent points when utilizing 3D DCT. Therefore, in this paper, we present 3D Discrete Cosine Transform-based Point Cloud Compression (3DCT PCC), a method to compress point cloud data, which is a 3D image by utilizing 3D DCT, and confirm the efficiency of 3D DCT compared to V-PCC based on 2D DCT.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.101-107
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• 2013

Generally the commercial high-resolution images have their coordinates, but the locations are locally different according to the pose of sensors at the acquisition time and relief displacement of terrain. Therefore, a process of image co-registration has to be applied to use the multi-temporal images together. However, co-registration is interrupted especially when images include the cloud-covered regions because of the difficulties of extracting matching points and lots of false-matched points. This paper proposes an automatic co-registration method for the cloud-covered high-resolution images. A scale-invariant feature transform (SIFT), which is one of the representative feature-based matching method, is used, and only features of the target (cloud-covered) images within a circular buffer from each feature of reference image are used for the candidate of the matching process. Study sites composed of multi-temporal KOMPSAT-2 images including cloud-covered regions were employed to apply the proposed algorithm. The result showed that the proposed method presented a higher correct-match rate than original SIFT method and acceptable registration accuracies in all sites.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.346-353
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• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.5
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• pp.127-134
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• 2007

Presented in the paper is an algorithm to generate a section curve by slicing a point cloud including tens of thousands of points. Although, there have been previous research results on the slicing problem, they are quite sensitive on the density variations of the point cloud, as well as on the local noise in the point cloud. To relive the difficulties, three technological requirements are identified; 1) dominant point sampling, 2) avoiding local vibration, and 3) robustness on the density changes. To satisfy these requirements, we propose a new slicing algorithm which is based on a node-sphere diagram. The algorithm has been implemented and tested with various examples.