• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.574-575
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• 2018

The generation of redundant data according to the spatial-temporal correlation in a wireless sensor network that reduces the network lifetime by consuming unnecessary energy. In this paper, data collection experiment through the particulate matter sensor is carried out to confirm the spatial-temporal data redundancy and we propose permitted limit setting method for data transmission to solve this problem. In the proposed method, the data transmission permitted limit is set by using the integrated average value in the cluster. The set permitted limit reduces the redundant data of the member node and it is shows that redundant data reduction is possible even in a variable environment of collected data by resetting the permitted limit in the cluster head.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.218-224
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• 1998

The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.198-209
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• 1996

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR) and classification capability.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.605-610
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• 1994

Optimal design of fault-tolerant, spatial type maniplators is treated in this paper. Design objective is to guarantte three degree-of-freedom translational motions in the task space, upon failure of one arbitrary joint of 4 degree-of -freedom manipulators. Realizing the nonfault-tolerant characteristics of current, wrist-type industrial manipulators, several 4 degree-of-freedom redundant structures with one joint redundancy are suggested as the fault-tolerant spatial -type manipulators. Fault-tolerant charactersitics are investigated basedon the analysis of the self-motion and the null-space elements, of a redundant manipulator. Finally, in order to maximize the fault-tolerant capability,optimal design is performed for a spatial-type manipulator with respect to the global isotropic index, and the performance enhancement of the optimized case is shown by simulation.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.97-108
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• 1996

Optimal design of fault-tolerant, spatial type redundant manipulators is treated in this paper. Design objective is to guarantte three degree-of -freedom translational motions in the task space, upon failure of one arbitrary joint of 4 degree-of-freedom manipulators. Noticing the nonfault-tolerant characteristics of current, wrist-type industrial manipulators, five different fault-tolerant spatial-type manipulators which have 4 degree-of-freedom structures with one joint redundancy are suggested. Faault-tolerant character-sitics of two redundant manipulators anr investigated based on the analysis of the self-motion and the null-space elements. Finally, in order to maximize the fault-tolerant capability, optimal design is performed for a spatial-type manipulator with respect to the global isotropic index, and the performance enhancement of the optimized case is shown by simulation.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3124-3130
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• 1999

A duplex system enhances reliability by tolerating faults through spatial redundancy. Faults can be detected by duplicating identical tasks in pairs of modules. However, this kind of systems cannot even detect the fault if it occurs coincidently due to either malfunctions of common component such as power supply and clock or due to such environmental disruption as EMI. In the paper, we propose a method to reduce those effects of coincident faults in the duplex controller computer. Specifically, a duplex system tolerates coincident faults by using a sophistication sequencing of scheduling technique with certain timing redundancy. In particular when all tasks should be completed in the sense of real-time, the suggested scheduling method works properly to minimize the probability of faulty tasks due to coincident fault without missing the timing constraints.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.31-34
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• 2000

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1722-1732
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• 1997

In this paper, we propose a coding method of remotely sensed satellite image data using region classification and interband correlation. This method classifies each pixel vector consider spectral characteristics. Then we perform the classified intraband VQ to remove spatial (intraband redundancy for a reference band image. To remove interband redundancy effectively, we perform the classified interband prediction for the band images that the high correlation spectrally and perform the classified interband VQ for the remaining band images. Experiments on LANDSAT TM image show that the coding efficiency of the proposed method is better than that of the conventional Gupta's method. Especially, this method removes redundancies effectively for satellite iamge including various geographical objects and for and images that have low interband correlation.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.385-398
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• 2021

The complexity of deep learning models affects the real-time performance of gesture recognition, thereby limiting the application of gesture recognition algorithms in actual scenarios. Hence, a residual learning neural network based on a deep convolutional neural network is proposed. First, small convolution kernels are used to extract the local details of gesture images. Subsequently, a shallow residual structure is built to share weights, thereby avoiding gradient disappearance or gradient explosion as the network layer deepens; consequently, the difficulty of model optimisation is simplified. Additional convolutional neural networks are used to accelerate the refinement of deep abstract features based on the spatial importance of the gesture feature distribution. Finally, a fully connected cascade softmax classifier is used to complete the gesture recognition. Compared with the dense connection multiplexing feature information network, the proposed algorithm is optimised in feature multiplexing to avoid performance fluctuations caused by feature redundancy. Experimental results from the ISOGD gesture dataset and Gesture dataset prove that the proposed algorithm affords a fast convergence speed and high accuracy.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.521-531
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• 2003

Multi-level geographic data can be mainpulated by a window query such as a zoom operation. In order to handle multi-level geographic data efficiently, a spatial indexing method supporting a window query is needed. However, the conventional spatial indexing methods are not efficient to access multi-level geographic data quickly. To solve it, other a few spatial indexing methods for multi-level geographic data are known. However these methods do not support all types of multi-level geographic data. This paper presents a new efficient spatial indexing method, the MLR-tree for window query of multi-level geographic data. The MLR-tree offers both high search performance and no data redundancy. Experiments show them. Moreover, the MLR-tree supports all types of multi-level geographic data.