• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.259-265
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• 2016

In this paper, new method was proposed to classify lung tissues such as Broncho vascular, Emphysema, Ground Glass Reticular, Ground Glass, Honeycomb, Normal for early lung disease detection. 459 Statistical features was extraced from joint histogram matrix based on multi resolution analysis, volumetric LBP, and CT intensity, then dominant features was selected by using adaboost learning. Accuracy of proposed features and 3D AMFM was 90.1% and 85.3%, respectively. Proposed joint histogram based features shows better classification result than 3D AMFM in terms of accuracy, sensitivity, and specificity.

• Imaging Science in Dentistry
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• v.32 no.2
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• pp.99-105
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• 2002

Purpose: To evaluate the diagnostic accuracy of transcranial radiographs and magnetic resonance imaging (MRI) of the temporomandibular joint (TMJ) in the assessment of osseous changes of the condylar head and articular eminence. Materials and Methods: Osseous changes of the TMJ were evaluated in forty-three patients. Osseous changes of the condylar head and articular eminence were observed in 41 joints and 64 joints, respectively on transcranial radiographs, and 48 joints and 59 joints, respectively on MRI. Results: The flattening, sclerosis, erosion, and osteophyte formation of the condylar heads were observed in 36.6%, 43.9%, 12.2%, and 7.3%, respectively on transcranial radiographs compared with 35.4%, 20.8%, 37.5%, and 6.3%, respectively on MRI. While, the flattening, sclerosis, and erosion of the articular eminences were observed in 26.6%, 67.2%, and 6.2%, respectively on transcranial radiographs compared with 32.2%, 59.3%, and 8.5%, respectively on MRI. Conclusion: There were no statistical differences between transcranial radiographs and MRI scans in the detection of osseous changes of the TMJ. However, MRI scans were superior to the transcranial radiographs in the detection of erosion of the condylar head (p<0.01).

• Journal of Acupuncture Research
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• v.32 no.2
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• pp.1-9
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• 2015

Objectives : The present study was an evaluation and standardization of herbal components in order to establish the efficacy and safety of Shinbaro pharmacopuncture. Methods : Among the raw materials of Shinbaro pharmacopuncture, the components Cibotii Rhizoma, Eucommiae Cortex, and Ledebouriellae Radix were assessed through ingredient verification experiments using thin-layer chromatography(TLC) and ultraviolet rays(UV) lamps. In addition, we standardized Acanthopanacis Cortex and Achyranthis Radix through validation using high performance liquid chromatograph-diode array detector(HPLC-DAD). Results : As result appeared a blue-white fluorescence under ultraviolet rays; changed to dark green after adding 1 % ferric chloride solution(due to Cibotii Rhizoma), and presented a yellow-green fluorescence when mixed with an ethyl ether under UV lamps by way of the ethyl ether layer, confirming Eucommiae Cortex. Ledebouriellae Radix was confirmed as dark brown spots at Rf values of 0.56 and 0.71 using TLC. Additionally, Acanthopanacis Cortex and Achyranthis Radix HPLC test results showed that linearity was $R^2{\geq}0.99$, and detection limit and quantitation limit were 0.23 to $1.29{\mu}g/mL$, and 0.71 to $3.90{\mu}g/mL$, respectively. Furthermore, precision and accuracy were confirmed to have relative standard deviation(RSD) values of 0.10 to 1.89 % and 96.19 to 103.72 %, respectively. Shinbaro pharmacopuncture did not have any overlapping or interference from other peaks in detection under the abovementioned analysis conditions. Conclusions : In conclusion, we confirmed that maintenance of Shinbaro pharmacopuncture validity was possible by means of quality control of Cibotii Rhizoma, Eucommiae Cortex, and Ledebouriellae Radix through ingredient identification and Acanthopanacis Cortex and Achyranthis Radix through high performance liquid chromatograph(HPLC) analysis. Further, we hope to contribute to the development strategy of herbal industry acupuncture.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.460-468
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• 2023

Developmental Dysplasia of the Hip (DDH) is a pathological condition commonly occurring during the growth phase of infants. It acts as one of the factors that can disrupt an infant's growth and trigger potential complications. Therefore, it is critically important to detect and treat this condition early. The traditional diagnostic methods for DDH involve palpation techniques and diagnosis methods based on the detection of keypoints in the hip joint using X-ray or ultrasound imaging. However, there exist limitations in objectivity and productivity during keypoint detection in the hip joint. This study proposes a deep learning model-based keypoint detection method using X-ray and ultrasound imaging and analyzes the performance of keypoint detection using various deep learning models. Additionally, the study introduces and evaluates various data augmentation techniques to compensate the lack of medical data. This research demonstrated the highest keypoint detection performance when applying the residual network 152 (ResNet152) model with simple & complex augmentation techniques, with average Object Keypoint Similarity (OKS) of approximately 95.33 % and 81.21 % in X-ray and ultrasound images, respectively. These results demonstrate that the application of deep learning models to ultrasound and X-ray images to detect the keypoints in the hip joint could enhance the objectivity and productivity in DDH diagnosis.

• Journal of the Korea Computer Industry Society
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• v.8 no.1
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• pp.57-64
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• 2007

In the paper, considers the design of a detection system, consisting of n identical detectors, to process the sum of spatially invariant signal fields $S_\jmath(t)$, an additive, homogeneous, spatially isotropic (in the array plane x). covariance_separable, and zero_mean Gaussian random noise field n(t, x). consisting of arrey receivers for use in optical communication through optimum turbulence atmosphers and covriance_circuit, staistical analysis through detection the maximum gain are compared with analysis theoretical analysis theoretical value and get through experimental measured value, as well the measured valus are confirmed to agreement joint Gaussian theoretical curves.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.35-38
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• 2002

Real defects in composite structures were detected by using laser measuring system. Four types of specimens, that is, a composite laminate, a honeycomb structure, a free-edge delamination and an adhesive joint, were used to study the applicability of ESPI and Shearography to composite structures. Thermal loading method, which can easily induce the surface deformation of specimen, was used to detect defects. Experimental results show that defects in composite structures can be easily detected by ESPI and Shearography. Moreover, it shows that ESPI and Shearography can be usefully applied to the detection of defects in various kinds of composite structures.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.3
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• pp.152-156
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• 2010

Non-line-of-sight (NLOS) propagation is one of the challenges in radio positioning. Distinguishing the transmission status of the communication as line-of-sight (LOS) or NLOS is of great importance for the wireless communication systems. This paper focuses on the identification of NLOS based on time-of-arrival (TOA) distance estimates and the received signal strength (RSS) measurements. We set a path loss threshold based on the joint TOA and RSS based NLOS detection method to determine LOS or NLOS. Simulation results show that the proposed method ensures the correct of detection for the LOS condition and can improve the NLOS identification for the weak noise and long distance.

• Journal of Welding and Joining
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• v.14 no.4
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• pp.79-88
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• 1996

For improvement in productivity and weld quality, weld seam tracking and welding parameter control are very essential in the welding of a structure which can not be cxactly fit-up due to mismatch, discontinous gap, deflection, etc.. In this study, an automatic weld seam tracking system is developed for I-butt joint structure, and the system consists of XYZ working table, vision sensor and user interface program. In the developed vision sensor system, an image projection algorithm for weld-line detection and an adaptive current control algorithm for gap variation were implemented. The user interface program developed in this study by basing on the objct oriented concept could provide very convenient way to utilize the tracking system with the pull-down menu driven structure. The developed system showed a good seam tracking and weld quality control capability corresponding to deflected weld lines and gap variations.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.1029-1042
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• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.593-595
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• 2020

본 논문에서는 5G NR 시스템을 위한 동기 신호를 이용한 cell ID 검출 방법에 대한 성능을 비교하였다. 5G NR(fifth-generation new radio) 시스템의 송신기는 SS/PBCH (synchronization signal/physical broadcast channel) 블록을 송신하며, 수신기는 수신된 SS/PBCH 블록을 이용하여 주파수 및 타이밍 오프셋 (frequency and timing offset)을 추정 할 수 있으며, cell ID (cell identity)는 PSS (primary synchronization signal)와 SSS (secondary synchronization signal)를 통해 검출할 수 있다. 본 논문에서는 cell ID 를 검출할 수 있는 방법으로서 2-stage 디코딩 방법과 결합 최대우도 결정 규칙 (joint maximum-likelihood decision rule: joint ML) 디코딩 방법을 사용하였다. Joint ML 디코딩 방법은 2-stage 디코딩 방법에 비해 더 좋은 검출 성능을 보이지만, 복잡도 측면에서는 2-stage 디코딩 방법이 joint ML 디코딩 방법에 비해 더 낮은 복잡도를 갖는 것을 확인하였다.