• Imaging Science in Dentistry
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• v.54 no.2
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• pp.171-180
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• 2024

Purpose: This study was conducted to identify the typical sites and patterns of peri-implant bone defects on cone-beam computed tomography (CBCT) images, as well as to evaluate the detectability of the identified bone defects on panoramic images. Materials and Methods: The study population included 114 patients with a total of 367 implant fixtures. CBCT images were used to assess the presence or absence of bone defects around each implant fixture at the mesial, distal, buccal, and lingual sites. Based on the number of defect sites, the presentations of the peri-implant bone defects were categorized into 3 patterns: 1 site, 2 or 3 sites, and circumferential bone defects. Two observers independently evaluated the presence or absence of bone defects on panoramic images. The bone defect detection rate on these images was evaluated using receiver operating characteristic analysis. Results: Of the 367 implants studied, 167 (45.5%) had at least 1 site with a confirmed bone defect. The most common type of defect was circumferential, affecting 107 of the 167 implants(64.1%). Implants were most frequently placed in the mandibular molar region. The prevalence of bone defects was greatest in the maxillary premolar and mandibular molar regions. The highest kappa value was associated with the mandibular premolar region. Conclusion: The typical bone defect pattern observed was a circumferential defect surrounding the implant. The detection rate was generally higher in the molar region than in the anterior region. However, the capacity to detect partial bone defects using panoramic imaging was determined to be poor.

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.619-628
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• 2015

In this paper, we consider a method for estimating a stripe-type defect and the reconstruction of a defect-free L/S type mask used in lithography. Comparing diffraction patterns of defected and defect-free masks, we derive equations for the estimation of the location and size of the defect. We construct an analytical model for this problem and derive closed form equations to determine the location and size using phase retrieval problem solving techniques. Consequently, we develop an algorithm that determines a defect-free mask pattern. An example shows the validity of the equations.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.386-393
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• 2010

A defect in an image is a set of pixels forming an irregular shape. Since a defect, in most cases, is not easy to be modeled mathematically, the defect detection problem still resides in a research area. If a given image, however, composed by certain patterns, a defect can be detected by the fact that a non-defect area should be explained by another patch in terms of a rotation, translation, and noise. In this paper, therefore, the defect detection method for a repeated multi-patterned image is proposed. The proposed defect detection method is composed of three steps. First step is the interest point detection step, second step is the selection step of a appropriate patch size, and the last step is the decision step. The proposed method is illustrated using SEM images of semiconductor wafer samples.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.185-192
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• 2010

This research suggests that valuate similarities by using the matches of patterns which is appeared on different two documents. Statistical ways such as fingerprint method are mainly used for evaluate similarities of existing documents. However, this method has a problem of accuracy for the high similarity which is occurred when many similar words are appeared from two irrelevant documents. These issues are caused by simple comparing of statistical parameters of two documents. But the method using patterns suggested on this research solved those problems because it judges similarity by searching same patterns. This method has a defect, however, that takes long time to search patterns, but this research introduce the algorithms complement this defect.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2846-2848
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• 2005

This paper proposes a pattern classification algorithm for the defect distribution of Hard Disk Drive (HDD). In the HDD productions, the defect pattern of defective HDD set is important information to diagnosis of defective HDD set. In this paper, 5 characteristics are determined for the classification to six standard defect pattern classes. A fuzzy inference system is proposed, the inputs of which are 5 characteristic values and the outputs are the possibilities that the input pattern is classified to the standard patterns. Classification result is the pattern with maximum possibility. The proposed algorithm is implemented with a PC system for defective HDD sets and shows its effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.383-389
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• 2005

This paper proposes a pattern classification algorithm for the defect distribution of Hard Disk Drive (HDD). In the HDD production, the defect pattern of defective HDD set is important information to diagnosis of defective HDD set. In this paper, 5 characteristics are determined for the classification to six standard defect pattern classes. A fuzzy inference system is proposed, the inputs of which are 5 characteristic values and the outputs are the possibilities that the input pattern is classified to standard patterns. Therefore, classification result is the pattern with maximum possibility. The proposed algorithm is implemented with the PC system for defective HDD sets and shows its effectiveness.

• Journal of Veterinary Clinics
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• v.25 no.6
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• pp.518-522
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• 2008

An approximately 8-month-old, 2.61 kg, male Siamese kitten was referred with primary complaints of a 1-week history of respiratory distress, exercise intolerance and dyspnea. Diagnostic studies identified III/VI systolic murmur in the cardiac auscultation, right ventricular enlargement patterns in the electrocardiogram, pleural effusion and right-sided cardiomegaly in the thoracic radiography, and right marked ventricular dilatation, right atrial enlargement, atrial septal defect and abnormal left atrium divided by fibromuscular membrane. Based on these findings, the case was diagnosed as cor triatriatum sinistrum complicated with an ostium primum atrial septal defect. The cat was rescued with furosemide, nitroglycerine, oxygen supplement and fluid removal from pleural cavity.

• Journal of Periodontal and Implant Science
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• v.38 no.sup2
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• pp.385-394
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• 2008

Purpose: The aim of this study was to evaluate the factors affecting healing patterns of surgically created circumferential gap defects around implants in dogs. Materials and Methods: In four mongrel dogs, all mandibular premolars were extracted. After 8 weeks of healing periods, implants were submerged. According to the surface treatment, turned surface was designated as a group A and rough surface as a group B. In each dog, surgical defects on the left side were made with a customized tapered step drill and on the right with a customized paralleled drill. Groups were also divided according to the width of the coronal gaps: 1.0mm, 1.5mm, or 2.0mm. The dogs were sacrificed following 8 weeks and the specimens were analyzed histologically and histomorphometrically. Results: During the postoperative period, healing was uneventful and implants were well-maintained. As the size of the coronal gap was increased, the amount of bone-to-implant contact was decreased. The bone healing was greater in rough surface implants compared to the turned ones. About the defect morphology, tapered shape showed much bone healing and direct bone to implant contact even in the smooth surface implants. Conclusion: Healing of the circumferential defect around dental implant is influenced by the implant surface, defect width and the morphology of the defect. When using rough surface implants, circumferential gap defects within 2 mm do not need any kinds of regenerative procedures and the healing appeared to be faster in the tapered defect morphology than the paralleled one.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.149-159
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• 1998

The importance of soundness and safety evaluation in weld zone using by the ultrasonic wave has been recently increased rapidly because of the collapses of huge structures and safety accidents. Especially, the ultrasonic method that has been often used for a major non-destructive testing(NDT) technique in many engineering fields plays an important role as a volume test method. Hence, the defecting any defects of weld Bone in austenitic stainless steel type 304 using by ultrasonic wave and neural network is explored in this paper. In order to detect defects, a distance amplitude curve on standard scan sensitivity and preliminary scan sensitivity represented of the relation between ultrasonic probe, instrument, and materials was drawn based on a quantitative standard. Also, a total of 93％ of defect types by testing 30 defect patterns after organizing neural network system, which is learned with an accuracy of 99％, based on ultrasonic evaluation is distinguished in order to classify defects such as holes or notches in experimental results. Thus, the proposed ultrasonic wave and neural network is useful for defect detection and Ultrasonic Non-Destructive Evaluation(UNDE) of weld zone in austenitic stainless steel 304.

• Proceedings of the KIEE Conference
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• 1999.07d
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• pp.1624-1626
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• 1999

PD in defect of solid insulation system is very harmful since It often leads to deterioration of insulation by the combined action of the discharge ions bombarding the surface and the action of chemical compounds that are formed by the discharge. PD can indicate incipient failure, so it has been used to determine degradation of insulation. In this paper. we investigated PD in defects of solid insulation by using statical method and classified PD patterns with surface discharge, electrical tree and void discharge by using Kohonen network. we used peak charge, average discharge power, average discharge current, repetition rate, skewness, kurtosis, QN of the max pulse height vs. repetition rate $H_q(n)$ for analysis and classification.