• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.12
• /
• pp.561-568
• /
• 2021

In recent years, autonomous driving technologies have become a high-value-added technology that attracts attention in the fields of science and industry. For smooth Self-driving, it is necessary to accurately detect an object and estimate its movement speed in real time. CNN-based deep learning algorithms and conventional dense optical flows have a large consumption time, making it difficult to detect objects and estimate its movement speed in real time. In this paper, using a single camera image, fast object detection was performed using the YOLOv5 algorithm, a deep learning algorithm, and fast estimation of the speed of the object was performed by using a local dense optical flow modified from the existing dense optical flow based on the detected object. Based on this algorithm, we present a system that can predict the collision time and probability, and through this system, we intend to contribute to prevent tram accidents.

• Journal of Broadcast Engineering
• /
• v.27 no.4
• /
• pp.499-510
• /
• 2022

This paper introduces a video editing system for senior creator who is not familiar to video editing. Based on video analysis techniques, it provide various information and delete unwanted shot. The system detects shot boundaries based on RNN(Recurrent Neural Network), and it determines the deletion of video shots. The shots can be deleted using shot-level significance, which is computed by detecting focused area. It is possible to delete unfocused shots or motion-blurred shots using the significance. The system detects object and face, and extract the information of emotion, age, and gender from face image. Users can create video contents using the information. Decorating tools are also prepared, and in the tools, the preferred design, which is determined from user history, places in the front of the design element list. With the video editing system, senior creators can make their own video contents easily and quickly.

• Clinics in Shoulder and Elbow
• /
• v.26 no.2
• /
• pp.182-190
• /
• 2023

Elbow traumas represent a relatively common condition in clinical practice. However, there is a lack of evidence regarding the most accurate tests for screening these potentially serious conditions and excluding elbow fractures. The purpose of this investigation was to analyze the literature concerning the diagnostic accuracy of clinical tests for the detection or exclusion of suspected elbow fractures. A systematic review was performed using the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines. Literature databases including PubMed, Cumulative Index to Nursing and Allied Health Literature, Diagnostic Test Accuracy, Cochrane Library, the Web of Science, and ScienceDirect were searched for diagnostic accuracy studies of subjects with suspected traumatic elbow fracture investigating clinical tests compared to imaging reference tests. The risk of bias in each study was assessed independently by two reviewers using the Quality Assessment of Diagnostic Accuracy Studies 2 checklist. Twelve studies (4,485 patients) were included. Three different types of index tests were extracted. In adults, these tests were very sensitive, with values up to 98.6% (95% confidence interval [CI], 95.0%-99.8%). The specificity was very variable, ranging from 24.0% (95% CI, 19.0%-30.0%) to 69.4% (95% CI, 57.3%-79.5%). The applicability of these tests was very high, while overall studies showed a medium risk of bias. Elbow full range of motion test, elbow extension test, and elbow extension and point tenderness test appear to be useful in the presence of a negative test to exclude fracture in a majority of cases. The specificity of all tests, however, does not allow us to draw useful conclusions because there was a great variability of results obtained.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.639-641
• /
• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1996.06c
• /
• pp.314-324
• /
• 1996

A high speed NMR quality evaluation sensor was designed , constructed and tested . The device consists of an NMR spectrometer coupled to a conveyor system. The conveyor was run at speeds ranging from 0 to 250 mm/s. Spectral of avocado fruits and one-dimensional magnetic resonance images of pickled olives were acquired while the samples were moving on a conveyor belt mounted through a 20Tesla NMR magnet with a 20 mm diameter surface coil and a 150 mm diameter imaging coil respectively. Fro a magnetic resonance spectrum analysis, motion through variations in the magnetic field tends to narrow spectral line width just like using sample rotation in high resolution NMR to narrow spectral line width. Spectrum analysis was used to detect the dry weight of avocado fruits using the ratio oil and water resonance peaks. Good correlations maximum r=0.970@ 50 mm/s and minimum r=0.894@250mm/s ) between oil and water resonance peak ratio and dry weight of avocados were observed at speeds ra ging from0 to 250mm/s. For the application of magnetic resonance imaging (MRI) method, the projections were used to distinguish between pitted and non-pitted olives . Effect of fruit position in the coil was tested and coil degree effects were noticed when projects were generated under dynamic conditions. Various belt speeds (up to 250mm/s) were tested and detection results were compared to static measurements. Higher classification errors were occurred at dynamic conditions compared to errors while olives were at rest.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1653-1659
• /
• 2022

Virtual reality content provides users with a high sense of immersion by using HMD devices. However, while wearing the HMD device, it is difficult to determine the user's location or distance from obstacles, resulting in injuries due to physical collisions. In this paper, we propose a reminder module to prevent accidents by notifying the risk of collision with obstacles while wearing the HMD device. The proposed module receives the user's state from the acceleration and gyro sensor and determines the motion that is likely to cause a collision. If there is an obstacle in the expected collision range, a buzzer sounds to the wearer. As a result of the experiment, the accuracy of obstacle detection in the state of wearing the HMD was 86.6% in the 1st stage and 83.3% in the 2nd stage, confirming the performance of the accident prevention reminder.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.178-180
• /
• 2022

An application implementation that allows users to train yoga posture based on the landmark of yoga posture of yoga instructors obtained from the Google Firebase ML Kit was introduced. Using the ML Kit, the user's posture is classified and landmarks corresponding to each joint are obtained. The accuracy measurement reference value for the yoga posture is set through the angle formed by the joints of the obtained landmark. The accuracy between the reference landmark for the yoga posture of professional yoga instructors and the landmark for the user's pose through the ML Kit was compared. According to the accuracy reference value, information on malfunction and correct motion is provided to the user through Text-to-Speech (TTS). Users are managed effectively with Firebase, and a system that displays the amount of exercise through a counter and timer when the user performs an exercise that meets the accuracy reference value was explained.

• Korea Science and Art Forum
• /
• v.30
• /
• pp.367-376
• /
• 2017

This study introduces conducting practice tool for conducting majoring students. There have been various types of related research, but most of them have not been optimized for the conducting major. In addition, we thought that it would be a tool to be able to carry like a musical instrument in order to practice conducting without restriction of place and time. And also, it will be one of the few tools to focus on queuing. The practice tool presented in this study use the Doppler effect to overcome the limitations of previous studies. It was concluded that the Doppler method, which is highly compatible, simple, and accurate, is superior to motion detection methods using existing sensors. It is expected that it will be used not only as a conducting but also as an interaction tool of various media.

• Smart Media Journal
• /
• v.13 no.2
• /
• pp.145-155
• /
• 2024

As the importance of software and artificial education is emphasized on the digital transformation era, various educational materials are being developed and distributed. To achieve the purpose of software education, various software education programs suitable for school settings need to be provided. In this paper, we developed a software education program using self-driving that can be applied to secondary school software education and applied it to secondary school students. The developed software education program is a physical computing program consisting of various motion control programs such as object detection, line tracing using various sensors, focusing on experience and practice. As a result of the survey, students' attitudes and career orientation toward software and artificial intelligence, and satisfaction with software education were over 90%, and satisfaction with the proposed program was over 95%.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.1
• /
• pp.40-46
• /
• 2008

Weak target detection and localization in the presence of loud surface ship noise is a critical problem for matched field processing (MFP) in shallow water. For stationary sources, each signal component of received signal can be separated and interference can be suppressed using eigen space analysis schemes. However, source motion, in realistic cases, causes spreading of signal energies in their subspace. In this case, eigenvalues of target and interfere signal components are mixed and hard to be separated with usual phone space eigenvector decomposition (EVD) approaches. Our technique is based on mode space and utilizes the difference in their physical characteristics of surface and submerged sources. Performing EVD for modal cross spectral density matrix, interference components in the mode amplitude subspace can be classified and eliminated. This technique is demonstrated with synthetic data, and results are discussed.