• Imaging Science in Dentistry
• /
• v.51 no.3
• /
• pp.313-321
• /
• 2021

Ankylosis of the temporomandibular joint (TMJ) is a disabling disease resulting from fibrous or bony fusion of the mandibular condyle and the glenoid fossa. Early diagnosis and surgical treatment are essential to prevent facial deformity and other complications. Conventional radiography has limitations in demonstrating the true extent of ankylosis. It is important for surgeons to be aware of the size and degree of bony ankylosis in order to perform complete resection of the ankylotic mass. In addition, a detailed evaluation of the relationship with adjacent vital structures such as the internal maxillary artery, inferior alveolar nerve canal, external auditory canal, and skull base are crucial to avoid iatrogenic injury. Multidetector computed tomography (MDCT) is the current imaging modality of choice for preoperative assessments. Herein, the authors propose a structured CT reporting template for TMJ ankylosis to strengthen the value of the preoperative imaging report and to reduce the rates of intraoperative complications and recurrence.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5624-5638
• /
• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Journal of muscle and joint health
• /
• v.29 no.2
• /
• pp.113-123
• /
• 2022

Purpose: The present study aims to identify research trends on diabetes mellitus (DM) self-management intervention, suggesting directions for follow-up studies through a scoping review. Methods: This study conducted the scoping review process outlined by Arskey and O' Malley using the JBI (Joanna Briggs Institute) template. The databases used were Riss, Kiss, NDSL, KMbase, Google Scholar. This study searched the literature published between January 2011 and November 2021 by entering keywords related to DM self-management. Results: Thirty-five studies were selected for analysis. The period for 24 articles was 12 weeks or longer. The interventions consisted of education, exercise, counseling, and coaching. Not all studies applied the theory of behavior change. Fourteen studies included three factors relating to behavioral, cognitive, emotional, and blood sugar changes to measure effectiveness, while ten studies included all four factors. Most interventions were effective both in DM self-management and self-care. Further, the intervention persistence effect of each study varied. Conclusion: While research on DM self-management intervention has been conducted at domestically and abroad, this decreased during COVID-19 pandemic. This study suggests the importance of systematically developing effective necessary optimal DM self-management interventions that can change behaviors to prevent diabetic complications and improve quality of life.

• The Journal of the Korea Contents Association
• /
• v.11 no.12
• /
• pp.619-628
• /
• 2011

Normally vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment. On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part. In this paper, we describe a development of interactive game contents using pose recognition interface that using 3D human body joint information. Our system was proposed for the purpose that users can control the game contents with body motion without any additional equipment. Poses are recognized comparing current input pose and predefined pose template which is consist of 14 human body joint 3D information. We implement the game contents with the our pose recognition system and make sure about the efficiency of our proposed system. In the future, we will improve the system that can be recognized poses in various environments robustly.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.55 no.2
• /
• pp.183-188
• /
• 2022

It is a difficult task to estimate parameters in even a simple stock assessment model such as a surplus production model, using only data about temporal catch-per-unit-effort (CPUE) (or survey index) and fishery yields. Such difficulty is exacerbated when time-varying parameters are treated as random effects (aka state variables). To overcome the difficulty, previous studies incorporated somewhat subjective assumptions (e.g., B₁=K) or informative priors of parameters. A key is how to build an objective joint prior of parameters, reducing subjectivity. Given the limited data on temporal CPUEs and fishery yields from 1999-2020 for common squid Todarodes pacificus, we built a joint prior of only two parameters, intrinsic growth rate (r) and carrying capacity (K), based on the resilience level of the population (Froese et al., 2017), and used a Bayesian state-space production assessment model. We used template model builder (TMB), a R package for implementing the assessment model, and estimating all parameters in the model. The predicted annual biomass was in the range of 0.76×10⁶ to 4.06×10⁶ MT, the estimated MSY was 0.13×10⁶ MT, the estimated r was 0.24, and the estimated K was 2.10×10⁶ MT.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.2
• /
• pp.44.2-44.2
• /
• 2021

Detecting lensed quasar systems and estimating their time delays using the unresolved joint light curves can be the next frontier among the cosmological probes in the near future. One can get the independent measurement of the Hubble constant from the time delays but without requiring the systems to be resolved a priori followed by monitoring the image light curves using high-resolution telescopes for years. In this work, we propose a novel technique that can identify lensed quasars only using the observed unresolved light curves and without assuming a template or any prior information. Following a set of conservative selection criteria that gives zero false-positive outcome, we can accurately estimate the time delay for almost all the lensed systems with marginal noise in the data. For the case of noisy data, our approach can still correctly identify a substantial number of lensed systems with high certainty and measure the time delay accurately.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.12
• /
• pp.1233-1240
• /
• 2010

In the flat panel display and semiconductor industries, the visual alignment system is considered as a core technology which determines the productivity of a manufacturing line. It consists of the vision system to extract the centroids of alignment marks and the stage control system to compensate the alignment error. In this paper, we develop a Kalman filter algorithm to estimate the alignment mark postures and propose a coarse-fine alignment control method which utilizes both original fine images and reduced coarse ones in the visual feedback. The error compensation trajectory for the distributed joint servos of the alignment stage is generated in terms of the inverse kinematic solution for the misalignment in task space. In constructing the estimation algorithm, the equation of motion for the alignment marks is given by using the forward kinematics of alignment stage. Secondly, the measurements for the alignment mark centroids are obtained from the reduced images by applying the geometric template matching. As a result, the proposed Kalman filter based coarse-fine alignment control method enables a considerable reduction of alignment time.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.11 no.4
• /
• pp.331-338
• /
• 2017

In this study, a portable x-ray generator was manufactured and a real-time image acquisition system was constructed using the image intensifier from the generated generator. We have developed a real - time position error verification system that can verify whether the artificial joint position is different from the initial image from the acquired image. The template image of the region of interest is extracted from the reference image using the pattern matching technique and compared with the image to be compared. As a result, It is shown that real - time position error verification is achieved by displaying the difference angle. This system is portable type, has a self-shielding facility, and the output of the irradiation device can be manufactured in a small size of 1kw and can be used as a portable type. In case of emergency patients in the non-destructive field for industrial use, It has proved effective for use in small areas such as feet.

• Journal of Sensor Science and Technology
• /
• v.31 no.5
• /
• pp.307-311
• /
• 2022

With the development of Internet of Things (IoT) technologies, numerous people worldwide connect with various electronic devices via Human-Machine Interfaces (HMIs). Considering that HMIs are a new concept of dynamic interactions, wearable electronics have been highlighted owing to their lightweight, flexibility, stretchability, and attachability. In particular, wearable strain sensors have been applied to a multitude of practical applications (e.g., fitness and healthcare) by conformally attaching such devices to the human skin. However, the stretchable elastomer in a wearable sensor has an intrinsic stretching limitation; therefore, structural advances of wearable sensors are required to develop practical applications of wearable sensors. In this study, we demonstrated a 3-dimensional (3D), porous, and piezoelectric strain sensor for sensing body movements. More specifically, the device was fabricated by mixing polydimethylsiloxane (PDMS) and polyvinylidene fluoride nanoparticles (PVDF NPs) as the matrix and piezoelectric materials of the strain sensor. The porous structure of the strain sensor was formed by a sugar cube-based 3D template. Additionally, mixing methods of PVDF piezoelectric NPs were optimized to enhance the device sensitivity. Finally, it is verified that the developed strain sensor could be directly attached onto the finger joint to sense its movements.

• Journal of the Korea Computer Graphics Society
• /
• v.20 no.2
• /
• pp.1-11
• /
• 2014

The quality of 2D-to-3D conversion depends on the accuracy of the assigned depth to scene objects. Manual depth painting for given objects is labor intensive as each frame is painted. Specifically, a human is one of the most challenging objects for a high-quality conversion, as a human body is an articulated figure and has many degrees of freedom (DOF). In addition, various styles of clothes, accessories, and hair create a very complex silhouette around the 2D human object. We propose an efficient method to estimate visually pleasing depths of a human at every frame in a monocular video. First, a 3D template model is matched to a person in a monocular video with a small number of specified user correspondences. Our pose estimation with sequential joint angular constraints reproduces a various range of human motions (i.e., spine bending) by allowing the utilization of a fully skinned 3D model with a large number of joints and DOFs. The initial depth of the 2D object in the video is assigned from the matched results, and then propagated toward areas where the depth is missing to produce a complete depth map. For the effective handling of the complex silhouettes and appearances, we introduce a partial depth propagation method based on color segmentation to ensure the detail of the results. We compared the result and depth maps painted by experienced artists. The comparison shows that our method produces viable depth maps of humans in monocular videos efficiently.