• Journal of Acupuncture Research
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• v.39 no.1
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• pp.59-63
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• 2022

Spontaneous osteonecrosis of the knee (SONK) is a common form of osteonecrosis of the knee and mainly affects the medial condyle due to localized vascular insufficiency. We report a case of SONK in a 65-year-old woman who had severe knee pain in her left knee whichimpeded her capacityto walk beyond 10 minutes. Bilateral knee X-rays revealed degenerative osteoarthritis of both knees and magnetic resonance imaging revealed R/O SONK in the lateral aspect of the medial femoral condyle, as well as a medial meniscal posterior horn root tear, and a Grade 1 medial collateral ligament injury. She was hospitalized at Jaseng Hospital of Korean Medicine for 21 days and receivedcombination therapy includingacupuncture, pharmacopuncture, and herbal medicine. Patient-reported scales indicated that her pain and physical functional limitations were alleviated. Combination therapy consisting of Korean traditional medicine may bean alternative nonoperative treatment approach for patients with SONK.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2788-2808
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• 2023

Brain tumors are one of the most threatening malignancies for humans. Misdiagnosis of brain tumors can result in false medical intervention, which ultimately reduces a patient's chance of survival. Manual identification and segmentation of brain tumors from Magnetic Resonance Imaging (MRI) scans can be difficult and error-prone because of the great range of tumor tissues that exist in various individuals and the similarity of normal tissues. To overcome this limitation, the Amended Convolutional Neural Network (ACNN) model has been introduced, a unique combination of three techniques that have not been previously explored for brain tumor detection. The three techniques integrated into the ACNN model are image tissue preprocessing using the Kalman Bucy Smoothing Filter to remove noisy pixels from the input, image tissue segmentation using the Isotonic Regressive Image Tissue Segmentation Process, and feature extraction using the Marr Wavelet Transformation. The extracted features are compared with the testing features using a sigmoid activation function in the output layer. The experimental findings show that the suggested model outperforms existing techniques concerning accuracy, precision, sensitivity, dice score, Jaccard index, specificity, Positive Predictive Value, Hausdorff distance, recall, and F1 score. The proposed ACNN model achieved a maximum accuracy of 98.8%, which is higher than other existing models, according to the experimental results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.2
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• pp.73-79
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• 2001

In this paper, the transmitted noise reduction performance of piezoelectric smart panels is experimentally studied. The proposed piezoelectric smart panels are comprised of plate structure on which piezoelectric sensor/actuators are bonded and sound absorbing material is provided. It is a combination of passive and active approaches utilizing a passive effect at high frequencies and an active effect at low frequencies. To prove the concept of piezoelectric smart panels, an acoustic measurement experiment is performed. An acoustic tunnel is designed and its acoustic characteristics are tested. Below 800Hz, the tunnel exhibits a plane wave guide characteristics. When an absorbing material is bonded on a single plate, a remarkable transmitted noise reduction in mid frequency range is observed except the first resonance frequency. By enabling the active control of single smart panel with negative feedback control. about 10dB noise reduction is achieved at the resonance frequencies. The double smart panel got 4dB at the first resonance frequency and has more potential to reduce the transmitted noise in a wide range frequency. Piezoelectric smart panels incorporating passive absorbing material and active piezoelectric devices is a promising technology for noise reduction in a wide range frequency.

• Journal of Veterinary Clinics
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• v.35 no.5
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• pp.178-183
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• 2018

The object of this study was to compare magnetic resonance imaging (MRI) findings and neurological signs in canine brain diseases. Brain diseases can cause severe neurological deficits and may be life-threatening. The antemortem diagnosis of the brain diseases is difficult for the clinician, since definitive diagnosis is based upon histopathological confirmation. Brain diseases are often associated with specific clinical signs, signalment, progression, and location. Accurate lesion localization through neurological examination and MRI findings is helpful for developing a differential diagnosis. A retrospective study was performed to compare the neurological examination of dogs with suspected brain disease to the MRI findings. Based on this study, neurological examination is a reliable way to localize most brain lesions. Postural reaction deficits do not provide sufficient information to localize lesions. Additionally, not all brain lesions present clinical signs and inflammatory lesions may cause no detectable abnormalities on MRI. Therefore, in clinical practice, a combination of neurological examination and MRI findings recommended for accurate brain lesion localization.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.2
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• pp.143-151
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• 2010

In this paper, a novel rectangular patch antenna is proposed to have Zeroth Order Resonance(ZOR) generated based on the Metamaterial Complosite Right- and Left-Handed(CRLH) structure. Making the in-phase electric field over the entire antenna other than a half-wavelength as the fundamental resonance mode of a standard microstrip patch or its positive multiple, the metallic patch is suggested to be capacitively coupled with only one surrounding rectangular ring, different from the previous 1D ZOR antennas commonly having several metal cells in line. The performance of the proposed antenna is simulated by a 3D field solver that inputs the sizes of the physical structure corresponding to the equivalent circuit designed to have ZOR at 2.4 GHz. Consequently, the resonance frequency, the gain and the antenna efficiency are observed 2.4 GHz, 5 dB and 98%, respectively. Besides, the important property of the proposed antenna is addressed as the combination of the low profile as an advantage of microstrip patch antennas, and the omni-directional field pattern typical of monopole antennas.

• Investigative Magnetic Resonance Imaging
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• v.21 no.4
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• pp.210-222
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• 2017

Purpose: To develop a novel combination of controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) with integrated SSFP (CAIPI-iSSFP) for accelerated SSFP imaging without banding artifacts at 3T. Materials and Methods: CAIPI-iSSFP was developed by adding a dephasing gradient to the balanced SSFP (bSSFP) pulse sequence with a gradient area that results in $2{\pi}$ dephasing across a single pixel. Extended phase graph (EPG) simulations were performed to show the signal behaviors of iSSFP, bSSFP, and RF-spoiled gradient echo (SPGR) sequences. In vivo experiments were performed for brain and abdominal imaging at 3T with simultaneous multi-slice (SMS) acceleration factors of 2, 3 and 4 with CAIPI-iSSFP and CAIPI-bSSFP. The image quality was evaluated by measuring the relative contrast-to-noise ratio (CNR) and by qualitatively assessing banding artifact removal in the brain. Results: Banding artifacts were removed using CAIPI-iSSFP compared to CAIPI-bSSFP up to an SMS factor of 4 and 3 on brain and liver imaging, respectively. The relative CNRs between gray and white matter were on average 18% lower in CAIPI-iSSFP compared to that of CAIPI-bSSFP. Conclusion: This study demonstrated that CAIPI-iSSFP provides up to a factor of four acceleration, while minimizing the banding artifacts with up to a 20% decrease in the relative CNR.

• Korean Journal of Optics and Photonics
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• v.14 no.1
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• pp.97-102
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• 2003

Multi-channel images of 11-MUA(11-Mercaptoundecanoic acid) and 11-MUOH(11-Mercaptoundecanol) self-assembled monolayers were obtained by using two-dimensional surface plasmon resonance (SPR) absorption. The patterning process was simplified by exploiting direct photo-oxidation of thiol bonding (photolysis) instead of conventional photolithography. Sharper images were resolved by using a white light source in combination with a narrow bandpass filter in the visible region, minimizing the diffraction patterns on the images. The line profile calibration of the image contrast caused by different resonance conditions at each point on the sensor surface (at a fixed incident angle) enables us to discriminate the monolayer thickness in nanometer scale. Furthermore, there is no signal degradation such as photo bleaching or quenching, which are common in the detection methods based on fluorescence.

• Journal of Korean Neurosurgical Society
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• v.48 no.4
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• pp.383-387
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• 2010

Complete removal of three-compartment trigeminal schwannomas is a challenge to neurosurgeons. To expand exposure of each compartment, the combination and modification of skull base approaches are necessary. The 61-year-old woman was admitted with chronic headache. Preoperative magnetic resonance imaging showed $47{\times}50{\times}40\;mm$-sized tumor originating primarily in the middle cranial fossa extended to the posterior and the infratemporal fossa. We performed operation in five stage; 1. Zygomatic osteotomy, 2. Inferior temporal fossa plate removal and foramen ovale opening, 3. Cavernous sinus opening, 4. Tailored anterior petrosectomy, 5. Meckel's cave opening. Combination of skull base surgery should be concerned according to the patient. In this study, extradural basal extension with zygomatic osteotomy, interdural posterior extension with tailored anterior petrosectomy, and intracavemous exploration are reasonable options for remodeling three-compartment lesion into a single compartment. Tailoring of bone resection and exploring through natural pathway between meningeal layers accomplish single-stage operation for complete removal of tumors.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.401-406
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• 2013

This paper presents experimental evaluation of IRE (isolation roller bearing) seismic isolation device. From the combination of base isolation on the IRE system displacement response spectrum and acceleration response spectrum, the compressive strength and the coefficient of friction experiments. Also the IRE system is evaluated by environment test according to KS standards. Both the resonance and seismic experiments using a combination of the IRE and Natural Rubber Bearing (NRB) are performed in order to analyze the seismic isolation of the IRE system dynamic characteristics. For the given load and exciting frequency, the resonant frequency becomes lower, but the resonant magnification remains to be same. However, it is shown that when we consider the IRE only, the vibration on the table with the horizontal movement and the independent horizontal displacement due to the rolling motion of the plate and roller are significantly reduced. This result verifies that the proposed optimal design method of the IRE system is very effective.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.667-675
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• 2021

The treatments for symptoms of Alzheimer's disease are being provided and for the early diagnosis several researches are undergoing. In this regard, by using T1-weighted images several classification techniques had been proposed to distinguish among AD, MCI, and Healthy Control (HC) patients. In this paper, we also used some traditional Machine Learning (ML) approaches in order to diagnose the AD. This paper consists of an improvised feature selection method which is used to reduce the model complexity which accounted an issue while utilizing the ML approaches. In our presented work, combination of subcortical and cortical features of 308 subjects of ADNI dataset has been used to diagnose AD using structural magnetic resonance (sMRI) images. Three classification experiments were performed: binary classification. i.e., AD vs eMCI, AD vs lMCI, and AD vs HC. Proposed Feature Selection method consist of a combination of Principal Component Analysis and Recursive Feature Elimination method that has been used to reduce the dimension size and selection of best features simultaneously. Experiment on the dataset demonstrated that SVM is best suited for the AD vs lMCI, AD vs HC, and AD vs eMCI classification with the accuracy of 95.83%, 97.83%, and 97.87% respectively.