• Journal of the Korean Society of Industry Convergence
• /
• v.22 no.3
• /
• pp.315-324
• /
• 2019

This paper present a novel 6-axis robotic base platform with force/moment sensing. The robotic base platform is made up of six loadcells connecting the moving plate to the fixed plate by spherical joints at the both ends of loadcells. The statics relation is derived, the robotic base platform prototype and the loadcell measurement system are developed. The force/moment calibrations in joint and Cartesian spaces are performed. The algorithm to detect external force applied at a working robot is derived, and using a 6-DOF robot mounted on the robotic base platform, force/moment measurement experiments have been performed.

• Journal of Multimedia Information System
• /
• v.7 no.4
• /
• pp.257-262
• /
• 2020

In this paper, a method of detecting the emergency situations such as body fall is proposed by using color images. We detect body areas and key parts of a body through a pre-learned Mask R-CNN in the images captured by a camera. Then we find the centerline of the body through the joint points of both shoulders and feet. Also, we calculate an angle to the center line and then calculate the amount of change in the angle per hour. If the angle change is more than a certain value, then it is decided as a suspected fall. Also, if the suspected fall state persists for more than a certain frame, then it is determined as a fall situation. Simulation results show that the proposed method can detect body fall situation accurately.

• Journal of Korean Society for Geospatial Information Science
• /
• v.1 no.1 s.1
• /
• pp.193-201
• /
• 1993

In a number of areas, there are important benefits to be gained when we bring both the detection and monitoring abilities of remote sensing as well as the philosophical approach and analytic capabilities of a geographic information system to bear on a problem. A key area in the joint applications of remote sensing technology and GIS is to identify change. Whether this change is of interest for its own sake, or because the change causes us to act (for example, to update a map), remote sensing provides an excellent suite of tools for detecting change. At the same time, a GIS is perhaps the best analytic toot for quantifying the process of change. There are two alternative methods for quantifying changes. The conceptually simple approach is to un the pixel values in each of the images. This method is practical but may be too simple to identify the variety of changes in a complex scene. The common alternative is called symbolic change detection. The analyst first decides on a set of thematic categories that are important to distinguish for the application. This approach is useful only if accurate landuse/cover classifications can be obtained. Persons conducting digital change detection must be intimately familiar with the environment under study, the quality of the data set and the characteristics of change detection algorithms. Also, much work remains to identify optimum change detection algorithms for specific geographic areas and problems.

• Korean Journal of Environmental Biology
• /
• v.39 no.4
• /
• pp.415-422
• /
• 2021

Cotton is an important fiber crop, and its seeds are used as feed for dairy cattle. Crop biotechnology has been used to improve agronomic traits and quality in the agricultural industry. The frequent unintentional release of LM cotton into the environment in South Korea is attributed to the increased application of living modified (LM) cotton in food, feed, and processing industries. To identify and monitor the LM cotton, a method for detecting the approved LM cotton in South Korea is required. In this study, we developed a method for the simultaneous detection of four LM cotton varieties, MON757, MON88702, COT67B, and GHB811. The genetic information of each LM event was obtained from the European Commission-Joint Research Centre and Animal and Plant Quarantine Agency. We designed event-specific primers to develop a multiplex PCR method for LM cotton and confirmed the specific amplification. Using specificity assay, random reference material(RM) mixture analysis and limit of detection(LOD), we verified the accuracy and specificity of the multiplex PCR method. Our results demonstrate that the method enabled the detection of each event and validation of the specificity using other LM RMs. The efficiency of multiplex PCR was further verified using a random RM mixture. Based on the LOD, the method identified 25 ng of template DNA in a single reaction. In summary, we developed a multiplex PCR method for simultaneous detection of four LM cotton varieties, for possible application in LM volunteer analysis.

• Journal of the Society of Disaster Information
• /
• v.20 no.2
• /
• pp.302-314
• /
• 2024

Purpose: This study proposes a fall detection model based on a top-down deep learning pose estimation model to automatically determine falls of multiple workers in an underground utility tunnel, and evaluates the performance of the proposed model. Method: A model is presented that combines fall discrimination rules with the results inferred from YOLOv8-pose, one of the top-down pose estimation models, and metrics of the model are evaluated for images of standing and falling two or fewer workers in the tunnel. The same process is also conducted for a bottom-up type of pose estimation model (OpenPose). In addition, due to dependency of the falling interference of the models on worker detection by YOLOv8-pose and OpenPose, metrics of the models for fall was not only investigated, but also for person. Result: For worker detection, both YOLOv8-pose and OpenPose models have F1-score of 0.88 and 0.71, respectively. However, for fall detection, the metrics were deteriorated to 0.71 and 0.23. The results of the OpenPose based model were due to partially detected worker body, and detected workers but fail to part them correctly. Conclusion: Use of top-down type of pose estimation models would be more effective way to detect fall of workers in the underground utility tunnel, with respect to joint recognition and partition between workers.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.2
• /
• pp.95-111
• /
• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Journal of Acupuncture Research
• /
• v.17 no.4
• /
• pp.79-87
• /
• 2000

Objectives : To evaluate the findings useful for differential diagnosis and associated abnormaiities of isthmic spondylolisthesis and degenerative spondylolisthesis on CT. Materials and methods : We reviewed retrospectively the CT images of 65 patients who were diagnosed spondylolisthesis during 3 years period. Our technique was 5mm slices at 5mm intervals with gantry angle to parallel the interspaces. Also reformatted sagittal views were taken. 41 patients were isthmic spondylolisthesis and 24 patients were degenerative spondylolisthesis. Resuits : Isthmic spondylolisthesis. 1. Isthmic type was more common at L5-S1. 2. The degree of anterior displacement was grade I and II. 3. The plane of defect was more horizontal than the usual facet joint. 4. The defect had an irregular shape. 5. Medial aspect of bone just anterior to defect had a small round prominence. 6. Anteroposterior elongation of the spinal canal was common. 7. Pseudobulging disk was common. 8. The most common associated abnormality was a HNP at the upper level of the defect. Degenerative spondylolisthesis. 1. Degenerative type was more common at L4-5. 2. The degree of anterior disptacement was grade I and II. 3. The Plane of facet joint was oriented obliquely instead of horizontally. 4. The posterior facet(inferior facet of superior vertebra) was anteriorly displaced. 5. Bony spur of the posterior portion of anterior facet was seen. 6. The facet joints often contain gas(vaccum phenomenum). 7. The most common associated abnormality was a HNP at the level of the displacement. Conclusions : CT is a highly accurate and most sensitive technique for recognition, differential diagnosis of isthmic and degenerative types and the detection of associated abnormalities.

• Journal of Oral Medicine and Pain
• /
• v.45 no.1
• /
• pp.12-16
• /
• 2020

Chronic otitis media (COM) is a chronic inflammatory disease which affects the middle ear, mastoid cavity. It presents hearing loss, ear pain, dizziness, headache, temporomandibular joint (TMJ) inflammation and intracranial complication. Intracranial complications such as skull base osteomyelitis (SBO) may occur secondary to COM due to transmission of infection by a number of possible routes. SBO is an uncommon condition with a significant morbidity and mortality if not treated in the early stages. We report a-67-year-old male patient with diabetes and untreated COM who presented atypical severe TMJ, periorbital and postmandibular pain. By computerized tomography (CT), magnetic resonance imaging (MRI) and whole body bone scan (WBBS), he was diagnosed with SBO spreading from untreated COM via infective arthritis of TMJ. Through this case, we suggest proper utilization of diagnostic imaging, especially CT or MRI for the early detection of SBO in the case of COM accompanying with the greater risk of infection developments such as diabetes.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.4
• /
• pp.851-859
• /
• 2011

In this paper, we propose the method that automatically extracts the silhouette and the joints of consecutive input image, and track joints to trace object for interaction between human and computer. Also the proposed method presents the action of human being to map human body using joints. To implement the algorithm, we model human body using 14 joints to refer to body size. The proposed method converts RGB color image acquired through a single camera to hue, saturation, value images and extracts body's silhouette using the difference between the background and input. Then we automatically extracts joints using the corner points of the extracted silhouette and the data of body's model. The motion of object is tracted by applying block-matching method to areas around joints among all image and the human's motion is mapped using positions of joints. The proposed method is applied to the test videos and the result shows that the proposed method automatically extracts joints and effectively maps human body by the detected joints. Also the human's action is aptly expressed to reflect locations of the joints

• The Journal of the Korea Contents Association
• /
• v.11 no.4
• /
• pp.215-224
• /
• 2011

There have been studying many researches to detect human body and to track one with increasing interest on human and computer interaction. In this paper, we propose the algorithm that automatically extracts joints, linked points of human body, using the ratio of human body under single camera and tracks object. The proposed method gets the difference images of the grayscale images and ones of the hue images between input image and background image. Then the proposed method composes the results, splits background and foreground, and extracts objects. Also we standardize the ratio of human body using face' length and the measurement of human body and automatically extract joints of the object using the ratio and the corner points of the silhouette of object. After then, we tract the joints' movement using block-matching algorithm. The proposed method is applied to test video to be acquired through a camera and the result shows that the proposed method automatically extracts joints and effectively tracks the detected joints.