• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.33-46
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• 1999

In distributed computing platforms like CORBA, wrappers are used to integrate heterogeneous systems or databases. A spatial data provider is one of the wrappers because it provides clients with uniform access interfaces to diverse data sources. The individual implementation of spatial data providers for each of different data sources is not efficient because of redundant coding of the wrapper modules. This paper presents a new architecture of the spatial data provider which consists of two layered objects : independent wrapper components and dependent wrapper components. Independent wrapper components would be reused for implementing a new data provider for a new data source, which dependent wrapper components should be newly coded for every data source. This paper furthermore discussed the issues of implementing the representation of query results in the middleware. There are two methods of keeping query results in the middleware. One is to keep query results as non-CORBA objects and the other is to transform query results into CORBA objects. The evaluation of the above two methods shows that the cost of making CORBA objects is very expensive.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.11a
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• pp.371-374
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• 2004

Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment. Safety, reliability, efficiency, and performance are some of the major concerns of induction motor applications. Preventive maintenance of induction motors has been a topic great interest to industry because of their wide range application of industry. Since the use of mechanical sensors, such as vibration probes, strain gauges, and accelerometers is often impractical, the motor current signature analysis (MACA) techniques have gained murk popularity as diagnostic tool. Fault tolerant control (FTC) strives to make the system stable and retain acceptable performance under the system faults. All present FTC method can be classified into two groups. The first group is based on fault detection and diagnostics (FDD). The second group is independent of FDD and includes methods such as integrity control, reliable stabilization and simultaneous stabilization. This paper presents the fundamental FDD-based FTC methods, which are capable of on-line detection and diagnose of the induction motors. Therefore, our group has developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. This paper presents its architecture. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module is checking stator current, voltage, temperatures, vibration and speed of the motor. The DSPs share information from each sensor or DSP through DPRAM with hardware implemented semaphore. And it communicates the motor status through field bus (CAN, RS485). From the designed system, we get primitive sensors data for the case of normal condition and two abnormal conditions of 3 phase induction motor control system is implemented. This paper is the first step to drive multi-motors with serial communication which can satisfy the real time operation using CAN protocol.

• The Journal of Korean Association of Computer Education
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• v.16 no.5
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• pp.39-47
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• 2013

In the case of a weak self-control youth, young students easily tend to fall into addiction by using the Internet as a sensation seeking and an alternative to escape the reality. Until now, internet addiction self-diagnosis techniques such as Internet addiction scale have been developed and used to solve this kind of internet addiction issue. However, traditional methods do not assess the correlation of addiction and the effects of the environment systematically because they are simply composed of redundant addiction scale criteria and questionnaire forms of the diagnostic methods. Thus, in this paper, we propose a new internet addiction self-diagnosis technique based on Formal Concept Analysis (FCA) and implement a self-diagnosis system in order to make a systematic internet addiction self-diagnosis system. In addition, we analyze the correlation of the measured data based on different perspectives such as home environment, family relationships, peer relationships, school life, and so on.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5015-5038
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• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

• Archives of Plastic Surgery
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• v.41 no.4
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• pp.398-402
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• 2014

Background Non-incisional blepharoplasty is a simple, less invasive method for creating a more natural-appearing double eyelid than classical incisional blepharoplasty. However, in aging patients, non-incisional blepharoplasty is not effective due to more severe blepharochalasis. Traditionally, incisional blepharoplasty is a common surgical method used for older patients, but blepharoplasty in elderly patients typically results in prolonged recovery times, and final blepharoplasty lines may be located in unintended or asymmetrical positions. Here, we introduce a new modified combination technique for geriatric blepharoplasty. Methods A total of ten patients were treated from July 2010 through July 2012 using the combination method. First, we performed non-incisional blepharoplasty using tarsodermal fixation. Then, incisional blepharoplasty with additional elliptical excision of the upper eyelid skin was performed. We removed pretarsal tissue, fat, the orbicularis oculi muscle, and orbital fat. Telephone surveys were administered to all patients for follow-up. The questionnaire was composed of eight questions that addressed recurrence and satisfaction with aesthetics and the procedure. Results A total of nine patients (90%) responded to the telephone survey. All cases of moderate to severe blepharochalasia were corrected and there were no major complications. Patients who underwent blepharoplasty had higher satisfaction scores. All patients were satisfied with the postoperative shapes of their eyelids. Conclusions The advantages of the proposed technique include: ease of obtaining a natural-looking fold with symmetry at the desired point; reproducible methods that require short operation times; fast postoperative recovery that results in a natural-appearing double-eyelid line; and high patient satisfaction.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.5
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• pp.80-86
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• 2005

Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment. Safety, reliability, efficiency, and performance are some of the major concerns of induction motor applications. Fault tolerant control (FTC) strives to make the system stable and retain acceptable performance under the system faults. All present FTC method can be classified into two groups. The first group is based on fault detection and diagnostics (FDD). The second group is includes of FDD and includes methods such as integrity control, reliable stabilization and simultaneous stabilization. This paper presents the fundamental FDD-based FTC methods, which are capable of on-line detection and diagnose of the induction motors. Therefore, our group has developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. This paper presents its architecture. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module processes the stator current, voltage, temperatures, vibration signal of the motor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.35-40
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• 2011

In this paper, we compare and analyze data aggregation methods based on event area in wireless sensor networks. Data aggregation methods consist of two methods: the direct transmission method and the aggregation node method. The direct aggregation method has some problems that are data redundancy and increasing network traffic as all nodes transmit own data to neighbor nodes regardless of same data. On the other hand the aggregation node method which aggregate neighbor's data can prevent the data redundancy and reduce the data. This method is based on location of nodes. This means that the aggregation node can be selected the nearest node from a sink or the centered node of event area. So, we describe the benefits of data aggregation methods that make up for the weak points of direct data dissemination of sensor nodes. We measure energy consumption of the existing ways on data aggregation selection by increasing event area. To achieve this, we calculated the distance between an event node and the aggregation node and the distance between the aggregation node and a sink node. And we defined the equations for distance. Using these equations with energy model for sensor networks, we could find the energy consumption of each method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.83-92
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• 2004

Gene expression profile is numerical data of gene expression level from organism measured on the microarray. Generally, each specific tissue indicates different expression levels in related genes, so that we can classify cancer with gene expression profile. Because not all the genes are related to classification, it is needed to select related genes that is called feature selection. This paper proposes a new gene selection method using forward selection method in regression analysis. This method reduces redundant information in the selected genes to have more efficient classification. We used k-nearest neighbor as a classifier and tested with colon cancer dataset. The results are compared with Pearson's coefficient and Spearman's coefficient methods and the proposed method showed better performance. It showed 90.3% accuracy in classification. The method also successfully applied to lymphoma cancer dataset.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1041-1047
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• 2017

There are many methods for surveying the status of a road, and the use of unmanned aerial vehicle (UAV) photo is one such method. When the UAV images are too large to be processed and suspected to be redundant, a texture extraction technique is used to transform the data into a reduced set of feature representations. This is an important task in 3D simulation using UAV images because a huge amount of data can be inputted. This paper presents a texture extraction method from UAV images to obtain high-resolution images of bridges. The proposed method is in three steps: firstly, we use the 3D bridge model from the V-World database; secondly, textures are extracted from oriented UAV images; and finally, the extracted textures from each image are blended. The result of our study can be used to update V-World textures to a high-resolution image.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.345-354
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• 2005

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have a priori knowledge about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper presents the motion detection algorithm that can run robustly about recusive motion. The motion detection compares and analyzes two frames each other, motion of whether happened judge. Through experiments, we show significant improvements in the reduction of the computational time in terms of the number of search steps without much quality degradation in the predicted image.