• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.957-963
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• 2014

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2449-2463
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• 2014

Hierarchical B-frame coding was introduced into H.264/SVC to provide temporal scalability and improve coding performance. A content analysis-based adaptive group of picture structure (AGS) can further improve the coding efficiency, but damages the inter-frame correlation and temporal scalability of hierarchical B-frame to different degrees. In this paper, we propose a group of pictures (GOP) adaptation coding method based on the positions of video cuts. First, the cut positions are accurately detected by the combination of motion coherence (MC) and mutual information (MI); then the GOP is adaptively and proportionately set by the analysis of MC in one scene. In addition, we propose a binary tree algorithm to achieve the temporal scalability of any size of GOP. The results for test sequences and real videos show that the proposed method reduces the bit rate by up to about 15%, achieves a performance gain of about 0.28-1.67 dB over a fixed GOP, and has the advantages of better transmission resilience and video summaries.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.895-904
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• 2004

Due to the frequent and unpredictable topology changes, multicast still remains as challenge and no one-size-fits-all protocol could serve all kinds of needs in mobile ad hoc network. In this paper, we propose a novel scheme of Hierarchical Eulerian Ring Oriented Multicast Architecture (HEROMA) over mobile ad hoc network. It has features that concentrate on efficiency and robustness simultaneously. It is also an application-driven proposal for hazard detection. Architectures including Eulerian ring, hierarchy and multicast agent are investigated in detail Simulation results different level of improvements on control traffic, end-to-end delay and packet delivery ratio by comparing with tree-based and mesh-based multicast protocols.

• The Plant Pathology Journal
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• v.29 no.1
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• pp.10-16
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• 2013

Hevea brasiliensis is a natural source of rubber and an important plantation tree species in Malaysia. Leaf blight disease caused by Fusicoccum substantially reduces the growth and performance of H. brasiliensis. The aim of this study was to use a combination of both morphological characteristics and molecular data to clarify the taxonomic position of the fungus associated with leaf blight disease. Fusicoccum species were isolated from infected leaves collected from plantations at 3 widely separated locations - Selangor, Perak, and Johor states - in Peninsular Malaysia in 2010. All the isolates were identified according to their conidial patterns and DNA sequences generated from internal transcribed spacers (ITS1 and ITS2), the 5.8S rRNA, and an unknown locus (BotF15) containing microsatellite repeats. Based on taxonomic and sequence data, Neofusicoccum ribis was identified as the main cause of leaf blight disease in H. brasiliensis in commercial plantations in Malaysia. A pathogenicity trial on detached leaves further confirmed that N. ribis causes leaf blight disease. N. ribis is an important leaf pathogen, and its detection in Malaysia has important implications for future planting of H. brasiliensis.

• Korean Journal of Veterinary Research
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• v.58 no.1
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• pp.45-49
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• 2018

The helicase genes and hypervariable regions (HVRs) of three avian hepatitis E viruses (HEVs) detected at three different farms were sequenced and characterized. Two isolates (DW-L and GI-B2) were classified as genotype 2 and one isolate (GR-B) was classified as genotype 1. A phylogenetic tree, based on the helicase gene and HVR nucleotide sequences, revealed the newly detected viruses and other avian HEVs were classified similarly. Unlike previously reported avian HEVs, the DW-L isolate detected in broiler breeders with characteristic lesions of avian HEV had no proline-rich motif in its HVR, suggesting that the proline-rich motif is non-essential for viral replication and infection.

• Proceedings of the KIEE Conference
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• 1997.07e
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• pp.1758-1760
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• 1997

Automatic detection system to detect acoustic emission pulse and fractal dimension were developed, to observe tree deterioration phenomena in LDPE. The purpose of our work are to use acoustic emission system and fractal dimension and to investigate the treeing phenomena in polymeric insulation under applied AC voltage 11[kV] with an artificial needle-shaped void(1.5[mm]) using the above system. We analyzed and phase angle-acoustic emission pulse amplitude-deterioration time ($\Phi$-AEA-t) pattern and phase angle-acoustic emission pulse number-deterioration time($\Phi$-AEN-t) pattern using statistical operators such as skewness, fractal dimension. In this paper show that the correlation of $\Phi$-AEA-t, $\Phi$-AEN-t, fractal dimension using regression analysis by the method of least squares can be used to predict the breakdown just before the breakdown occurs.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.372-381
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• 2006

The purpose of this study was to develop a process management system to manage ingot fabrication and improve ingot quality. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation. Then, modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters. Secondly, rule extraction was performed to find the relation between the production quality and control conditions. The extracted rules can give important information concerning how to handle the process correctly. The dynamic polynomial neural network (DPNN) and decision tree were applied for data modeling and rule extraction, respectively, from the ingot fabrication data.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.523-530
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• 2008

There are many defects that cause the process improvement of lifecycle problems during software development. This paper propose the management method of risk items that removes and manages the lifecycle problems as well. For the similar projects, we can estimate defects and prepare to solve them by using domain expert knowledge and the state analysis of defect items, which can greatly improve the software process. This research provides solution of management of risk items problem and detection of defect transition and its prevention and causes that happen on software development. Also, In this paper propose to making quantity of degree and transition phase.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1927-1929
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• 2000

PD indicates the inception and progress of degradation of solid insulation system, so it has been used to determine degradation of insulation. PD provides means for detection and recognition of defects. However, there is still marked difficult to recognize defects by PD methods. In this paper, we investigated properties of PD in solid insulation by using statistical method with surface discharge, electrical tree and void discharge with source of discharge, we used statistical parameters of PD distributions specified such as $H_n(q)$, $H_{an}(\phi)$, $H_n(\phi)$, $H_a(\phi)$. The parameters induced from its specified distributions are average discharge, average repetition rate, Skewness, Kurtosis, asymmetry and correlation. From the parameters, we classified PD patterns and built up DB(data-base).

• Journal of the Korea Society of Computer and Information
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• v.3 no.4
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• pp.27-34
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• 1998

In this paper we present a method for automatic motion vector and brightness based video indexing and retrieval. We extract a representational frame from each shot and compute some motion vector and brightness based features. For each R-frame we compute the optical flow field; motion vector features are then derived from this flow field, BMA(block matching algorithm) is used to find motion vectors and Brightness features are related to the cut detection of method brightness histogram. A video database provided contents based access to video. This is achieved by organizing or indexing video data based on some set of features. In this paper the index of features is based on a B+ search tree. It consists of internal and leaf nodes stores in a direct access a storage device. This paper defines the problem of video indexing based on video data models.