• The KIPS Transactions:PartC
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• v.15C no.5
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• pp.329-342
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• 2008

The Sensor Networks have limitations in utilizing energies, developing energy-efficient routing protocol and secure routing protocol are important issues in Sensor Network. In the field of data management, Tributaries and Deltas(TD) which incorporates tree topology and multi-path topology effectively have been suggested to provide efficiency and robustness in data aggregation. And our research rendered hierarchical property to TD and proposed Clustering-based Tributaries-Deltas. Through this new structure, we integrated efficiency and robustness of TD structure and advantages of hierarchical Sensor Network. Clustering-based Tributaries-Deltas was proven to perform better than TD in two situations through our research. The first is when a Base Station (BS) notices received information as wrong and requests the network's sensing data retransmission and aggregation. And the second is when the BS is mobile agent with mobility. In addition, we proposed key establishment mechanism proper for the newly proposed structure which resulted in new Sensor Network structure with improved security and energy efficiency as well. We demonstrated that the new mechanism is more energy-efficient than previous one by analyzing consumed amount of energy, and realized the mechanism on TmoteSKY sensor board using TinyOS 2.0. Through this we proved that the new mechanism could be actually utilized in network design.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.446-457
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• 2017

In order to reduce the size of frame memory or bus bandwidth, frame memory compression (FMC) recompresses reconstructed or reference frames of video codecs. This paper proposes a novel FMC design based on discrete wavelet transform (DWT) - set partitioning in hierarchical trees (SPIHT), which supports fine-scalable throughput and is area-efficient. In the proposed design, multi-cores with small block sizes are used in parallel instead of a single core with a large block size. In addition, an appropriate pipelining schedule is proposed. Compared to the previous design, the proposed design achieves the processing speed which is closer to the target system speed, and therefore it is more efficient in hardware utilization. In addition, a scheme in which two passes of SPIHT are merged into one pass called merged refinement pass (MRP) is proposed. As the number of shifters decreases and the bit-width of remained shifters is reduced, the size of SPIHT hardware significantly decreases. The proposed FMC encoder and decoder designs achieve the throughputs of 4,448 and 4,000 Mpixels/s, respectively, and their gate counts are 76.5K and 107.8K. When the proposed design is applied to high efficiency video codec (HEVC), it achieves 1.96% lower average BDBR and 0.05 dB higher average BDPSNR than the previous FMC design.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.509-516
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• 2015

Intangibility, measurement difficulty and irreversibility, which are the characteristics of service, have such problems as obscurity and uncertainty in quality evaluation. Technical entrepreneurship education, a sort of public service, also contains such characteristics of service. To objectively evaluate the service quality of technical entrepreneurship education, this paper drew up factors as hierarchical structure, centered on FAHP technique, and conducted pre-processing, inputted those factors into triangular fuzzy number fuzzy judgement matrix, and calculated their weights. In this manner, this paper proposed a TESE system, through which an analysis can be conducted by drawing relative importance and priorities of the factors. The proposed system can efficiently evaluate the qualitative technical start-up education service quality factors quantitatively in the diversely changing technical start-up environment in view of the highest result quality (41%), which means performance in the relative importance of major factors. Namely, this paper confirmed that clear decision making can be made through an experiment.

• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.57-63
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• 2018

IoT devices are used in many areas to perform various roles and functions in a cloud environment. However, a method of access control that can stably control the IoT device has not been proposed yet. In this paper, we propose a hierarchical multi-level property access control scheme that can perform stable access of IoT devices used in a cluster environment. In order to facilitate the access of the IoT device, the proposed method not only provides the ID key (security token) unique to the IoT device by providing the IoT Hub, but also allows the IoT Hub to authenticate the X.509 certificate and the private key, So that the private key of the IoT device can not be seen outside the IoT device. As a result of the performance evaluation, the proposed method improved the authentication accuracy by 10.5% on average and the processing time by 14.3%. The overhead of IoT Hub according to the number of IoT attributes was 9.1% lower than the conventional method.

• Journal of Advanced Navigation Technology
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• v.13 no.3
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• pp.459-465
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• 2009

Digital watermarking is a technique to insert a visually imperceptible information into an image so that the information can be extracted for the purposes of ownership verification or authentication. And watermarking techniques can be classified as either fragile or robust. Robust watermarks are useful for copyright and ownership assertion purposes. They cannot be easily removed and should resist common image manipulation procedures such as rotation, scaling, cropping, etc. On the other hand, fragile watermarks are easily corrupted by any image processing procedure, it can detect any change to an image as well as localizing the areas that have been changed. In this paper, we propose a fragile watermarking algorithm using a special hierarchical structure for integrity verification of image and detection of manipulated location. In the proposed method, the image to be watermarked is divided into blocks in a multi-level hierarchy and calculating block digital signatures in this hierarchy. The proposed method thwarts the cut-and-paste attack and the experimental results to demonstrate the effectiveness of the proposed method.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.311-320
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• 2008

In general, routing algorithms that were applied to ad-hoc networks are not suitable for the environment with many nodes over several thousands. To solve this problem, hierarchical management to these nodes and clustering-based protocols for the stable maintenance of topology are used. In this paper, we propose the clustering-based modified LEACH protocol that can applied to an environment which moves around metal containers within communication nodes. In proposed protocol, we implemented a module for detecting the movement of nodes on the clustering-based LEACH protocol and improved the defect of LEACH in an environment with movable nodes. And we showed the possibility of the effective communication by adjusting the configuration method of multi-hop. We also compared the proposed protocol with LEACH in four points of view, which are a gradual network composition time, a reconfiguration time of a topology, a success ratio of communication on an containers environment, and routing overheads. And to conclude, we verified that the proposed protocol is better than original LEACH protocol in the metal containers environment within communication of nodes.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.123-130
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• 2009

Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around $1.2{\sim}5.2$ times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.857-866
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• 2006

Performance of an image retrieval system is usually very low because of the semantic gap between the low level feature and the high level concept in a query image. Semantically relevant images may exhibit very different visual characteristics, and may be scattered in several clusters. In this paper, we propose a content based image rertrieval approach which combines region based image retrieval and a new relevance feedback method using adaptive clustering together. Our main goal is finding semantically related clusters to narrow down the semantic gap. Our method consists of region based clustering processes and cluster-merging process. All segmented regions of relevant images are organized into semantically related hierarchical clusters, and clusters are merged by finding the number of the latent clusters. This method, in the cluster-merging process, applies r: using v principal components instead of classical Hotelling's $T_v^2$ [1] to find the unknown number of clusters and resolve the singularity problem in high dimensions and demonstrate that there is little difference between the performance of $T^2$ and that of $T_v^2$. Experiments have demonstrated that the proposed approach is effective in improving the performance of an image retrieval system.