• Proceedings of the Korean Vacuum Society Conference
• /
• 2011.02a
• /
• pp.449-449
• /
• 2011

We reported the direct effect of intrinsic surface energy of dry adhesive material to the Van der Waals and capillary forces contributions of the total adhesion force in an artificial gecko-inspired adhesion system. To mimic the gecko foot we fabricated tilted nanohairy structures using both lithography and ion beam treatment. The nanohairy structures were replicated from Si wafer mold using UV curable polymeric materials. The control of nanohairs slanting angles was based on the uniform linear argon ion irradiation to the nanohairy polymeric surface. The surface energy was studied utilizing subsequent conventional oxygen ion treatment on the nanohairy structures which resulted in gradient surface energy. Our shear adhesion test results were found in good agreement with the accepted Van der Waals and capillary forces theory in the gecko adhesion system. Surface energy would give a direct impact to the effective Hamaker constant in Van der Waals force and the filling angle (${\varphi}$) of water meniscus in capillary force contributions of gecko inspired adhesion system. With the increasing surface energy, the effective Hamaker constant also increased but the filling angle decreased, resulting in a competition between the two forces. Using a simple mathematical model, we compared our experimental results to show the quantitative contributions of Van der Waals and capillary forces in a single adhesion system on both hydrophobic and hydrophilic surfaces. We found that the Van der Waals force contributes about 82.75% and 89.97% to the total adhesion force on hydrophilic and hydrophobic test surfaces, respectively, while the remaining contribution was occupied by capillary force. We also showed that it is possible to design ultrahigh dry adhesive with adhesion strength of more than 10 times higher than apparent gecko adhesion force by controlling the surface energy and the slanting angle induced-contact line of dry adhesive the materials.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.5 s.311
• /
• pp.38-47
• /
• 2006

Conventional classification method uses a single classifier based on shape or motion feature. However this method exhibits a weakness if naively used since the classification performance is highly sensitive to the accuracy of moving region to be detected. The detection accuracy, in turn, depends on the condition of the image background. In this paper, we propose to resolve the drawback and thus strengthen the classification reliability by employing a Bayesian decision fusion and by optimally combining the decisions of three classifiers. The first classifier is based on shape information obtained from Fourier descriptors while the second is based on the shape information obtained from image gradients. The third classifier uses motion information. Our experimental results on the classification Performance of human and vehicle with a static camera in various directions confirm a significant improvement and indicate the superiority of the proposed decision fusion method compared to the conventional Majority Voting and Weight Average Score approaches.

• Journal of Korean Neurosurgical Society
• /
• v.60 no.1
• /
• pp.54-59
• /
• 2017

Objective : Postoperative pain is one of the major complaints of patients after lumbar fusion surgery. The authors evaluated the effects of intravenous patient controlled analgesia (IV-PCA) using fentanyl or sufentanil on postoperative pain management and pain-related complications. Methods : Forty-two patients that had undergone surgery with lumbar instrumentation and fusion at single or double levels constituted the study cohort. Patients were equally and randomly allocated to a sufentanil group (group S) or a fentanyl group (group F) for patient controlled analgesia (PCA). Group S received sufentanil at a dose of $4{\mu}g/kg$ IV-PCA and group F received fentanyl $24{\mu}g/kg$ IV-PCA. A numeric rating scale (NRS) of postoperative pain was applied before surgery, and immediately and at 1, 6, and 24 hours (hrs) after surgery. Oswestry disability index (ODI) scores were obtained before surgery and one month after surgery. Opioid-related side effects were also evaluated. Results : No significant intergroup difference was observed in NRS or ODI scores at any of the above-mentioned time points. Side effects were more frequent in group F. More specifically, nausea, vomiting rates were significantly higher (p=0.04), but pruritus, hypotension, and headache rates were non-significantly different in the two groups. Conclusion : Sufentanil displayed no analgesic advantage over fentanyl postoperatively. However, sufentanil should be considerable for patients at high risk of GI issues, because it had lower postoperative nausea and vomiting rates than fentanyl.

• Journal of Korean Neurosurgical Society
• /
• v.60 no.5
• /
• pp.567-576
• /
• 2017

Objective : Preoperative parameters including the T1 slope (T1S) and C2-C7 sagittal vertical axis (SVA) have been recognized as predictors of kyphosis after laminoplasty, which is accompanied by posterior neck muscle damage. The importance of preoperative parameters has been under-estimated in anterior cervical discectomy and fusion (ACDF) because there is no posterior neck muscle damage. We aimed to determine whether postoperative subsidence and pseudarthrosis could be predicted according to specific parameters on preoperative plain radiographs. Methods : We retrospectively analyzed 41 consecutive patients (male : female, 22 : 19; mean age, $51.15{\pm}9.25years$) who underwent ACDF with a stand-alone polyether-ether-ketone (PEEK) cage (>1 year follow-up). Parameters including SVA, T1S, segmental angle and range of motion (ROM), C2-C7 cervical angle and ROM, and segmental inter-spinous distance were measured on preoperative plain radiographs. Risk factors of subsidence and pseudarthrosis were determined using multivariate logistic regression. Results : Fifty-five segments (27 single-segment and 14 two-segment fusions) were included. The subsidence and pseudarthrosis rates based on the number of segments were 36.4% and 29.1%, respectively. Demographic data and fusion level were unrelated to subsidence. A greater T1S was associated with a lower risk of subsidence (p=0.017, odds ratio=0.206). A cutoff value of T1S<$28^{\circ}$ significantly predicted subsidence (sensitivity : 70%, specificity : 68.6%). There were no preoperative predictors of pseudarthrosis except old age. Conclusion : A lower T1S (T1S<$28^{\circ}$) could be a risk factor of subsidence following ACDF. Surgeons need to be aware of this risk factor and should consider various supportive procedures to reduce the subsidence rates for such cases.

• Asian Spine Journal
• /
• v.12 no.6
• /
• pp.1100-1105
• /
• 2018

Study Design: Prospective observational study. Purpose: To determine the incidence of postoperative urinary retention (POUR) in patients undergoing elective posterior lumbar spine surgery and identify the risk factors associated with the development of POUR. Overview of Literature: POUR following surgery can lead to detrusor dysfunction, urinary tract infections, prolonged hospital stay, and a higher treatment cost; however, the risk factors for POUR in spine surgery remain unclear. Methods: A prospective, consecutive analysis was conducted on patients undergoing elective posterior lumbar surgery in the form of lumbar discectomy, lumbar decompression, and single-level lumbar fusions during a 6-month period. Patients with spine trauma, preoperative neurological deficit, previous urinary disturbance/symptoms, multiple-level fusion, and preoperative catheterization were excluded from the study. Potential patient- and surgery-dependent risk factors for the development of POUR were assessed. Univariate analysis and a multiple logistical regression analysis were performed. Results: A total of 687 patients underwent posterior lumbar spine surgery during the study period; among these, 370 patients were included in the final analysis. Sixty-one patients developed POUR, with an incidence of 16.48%. Significant risk factors for POUR were older age, higher body mass index (BMI), surgery duration, intraoperative fluid administration, lumbar fusion versus discectomy/decompression, and higher postoperative pain scores (p<0.05 for all). Sex, diabetes, and the type of inhalational agent used during anesthesia were not significantly associated with POUR. Multiple logistical regression analysis, including age, BMI, surgery duration, intraoperative fluid administration, fusion surgery, and postoperative pain scores demonstrated a predictive value of 92% for the study population and 97% for the POUR group. Conclusions: POUR was associated with older age, higher BMI, longer surgery duration, a larger volume of intraoperative fluid administration, and higher postoperative pain scores. The contribution of postoperative pain scores in the multiple regression analysis was a significant predictor of POUR.

• The Journal of Society for e-Business Studies
• /
• v.26 no.4
• /
• pp.1-13
• /
• 2021

With the development of big data-related technologies, it has become possible to process vast amounts of data that could not be processed before. Accordingly, the establishment of an automated data selection and fusion process for the realization of big data-based services has become a necessity, not an option. In this paper, we propose an automation technique to create meaningful new information by fusing datasets containing spatial information. Firstly, the given datasets are embedded by using the Node2Vec model and the keywords of each dataset. Then, the semantic similarities among all of datasets are obtained by calculating the cosine similarity for the embedding vector of each pair of datasets. In addition, a person intervenes to select some candidate datasets with one or more spatial identifiers from among dataset pairs with a relatively higher similarity, and fuses the dataset pairs to visualize them. Through such semi-automatic data fusion processes, we show that significant fused information that cannot be obtained with a single dataset can be generated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.416-418
• /
• 2022

Glioma is a type of brain tumor that occurs in glial cells and is classified into two types: high hrade hlioma with a poor prognosis and low grade glioma. Magnetic resonance imaging (MRI) as a non-invasive method is widely used in glioma diagnosis research. Studies to obtain complementary information by combining multiple modalities to overcome the incomplete information limitation of single modality are being conducted. In this study, we developed a 3D CNN-based model that applied input-level fusion to MRI of four modalities (T1, T1Gd, T2, T2-FLAIR). The trained model showed classification performance of 0.8926 accuracy, 0.9688 sensitivity, 0.6400 specificity, and 0.9467 AUC on the validation data. Through this, it was confirmed that the grade of glioma was effectively classified by learning the internal relationship between various modalities.

• Journal of Advanced Navigation Technology
• /
• v.28 no.2
• /
• pp.238-245
• /
• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.1
• /
• pp.35-45
• /
• 2013

A autonomous vehicle requires improved and robust perception systems than conventional perception systems of intelligent vehicles. In particular, single sensor based perception systems have been widely studied by using cameras and laser radar sensors which are the most representative sensors for perception by providing object information such as distance information and object features. The distance information of the laser radar sensor is used for road environment perception of road structures, vehicles, and pedestrians. The image information of the camera is used for visual recognition such as lanes, crosswalks, and traffic signs. However, single sensor based perception systems suffer from false positives and true negatives which are caused by sensor limitations and road environments. Accordingly, information fusion systems are essentially required to ensure the robustness and stability of perception systems in harsh environments. This paper describes a perception system for autonomous vehicles, which performs information fusion to recognize road environments. Particularly, vision and laser radar sensors are fused together to detect lanes, crosswalks, and obstacles. The proposed perception system was validated on various roads and environmental conditions with an autonomous vehicle.

• Journal of Korean Neurosurgical Society
• /
• v.65 no.4
• /
• pp.549-557
• /
• 2022

Objective : This study analyzed the risk factors in patients who developed distal junctional kyphosis (DJK) after posterior cervical fusion. Methods : We retrospectively analyzed the clinical and radiographic outcomes of 64 patients, aged ≥18 years (51 and 13 male and female patients, respectively), who underwent single-staged multilevel (3-6 levels) posterior cervical fusion surgery due to multiple cervical spondylotic myelopathy. The surgeries were performed by a single spinal surgeon between January 2012 and December 2017. Demographic data, clinical outcomes, and radiological results were collected. We divided the patients into a DJK group and a non-DJK group according to the presence of DJK and investigated the risk factors by comparing the differences between the two groups. Results : Of the 64 patients, 13 developed DJK. No significant differences in clinical results were observed between the two groups before and immediately after the surgery. At the final follow-up, a higher visual analog score for neck pain was observed in the DJK group compared to the non-DJK group (p<0.01). The DJK group had a significantly lower T1 slope and a significantly higher C2-7 sagittal vertical axis (SVA) before surgery compared to the non-DJK group (p=0.03 and p<0.01, respectively). Immediately after surgery, the difference between the two groups decreased and no significant difference was observed. However, at the last follow-up, a significantly higher C2-7 SVA was observed in the DJK group (p<0.01). At the last follow up, there is no discrepancy in T1S-CL. In multiple logistic regression analysis, preoperative higher C2-7 SVA and preoperative lower T1 slope were identified as independent risk factors (p=0.03 and p<0.01, respectively). As a result, it was confirmed that DJK occurred along the process of returning to preoperative values. Conclusion : DJK can be considered to be caused by cervical misalignment due to excessive change in the surgical site in patients with low T1 slope and high C2-7 SVA before surgery. This also affects the clinical outcome after surgery. It is recommended to refrain from excessive segmental lordosis changes during multilevel cervical post fusion surgery, especially in patients with a small preoperative T1 slope and a large SVA value.