• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.281-291
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• 2019

Depth from defocus estimates the 3D depth by using a phenomenon in which the object in the focal plane of the camera forms a clear image but the object away from the focal plane produces a blurred image. In this paper, algorithms are studied to estimate 3D depth by analyzing the degree of blur of the image taken with a single camera. The optimized object range was obtained by 3D depth estimation derived from depth from defocus using one image of a single camera or two images of different focus of a single camera. For depth estimation using one image, the best performance was achieved using a focal length of 250 mm for both smartphone and DSLR cameras. The depth estimation using two images showed the best 3D depth estimation range when the focal length was set to 150 mm and 250 mm for smartphone camera images and 200 mm and 300 mm for DSLR camera images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1224-1230
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• 2020

Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.907-913
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• 2022

Approximately 70% of smartphone users around the world use Android operating system-based smartphones, and malicious apps targeting these Android platforms are constantly increasing. Google has provided "Google Play Protect" to respond to the increasing number of Android targeted malware, preventing malicious apps from being installed on smartphones, but many malicious apps are still normal. It threatens the smartphones of ordinary users registered in the Google Play store by disguising themselves as apps. However, most people rely on antivirus programs to detect malicious apps because the average user needs a great deal of expertise to check for malicious apps. Therefore, in this paper, we propose a method to classify unnecessary malicious permissions of apps by using only the categories and permissions that can be easily confirmed by the app, and to easily detect malicious apps through the classified permissions. The proposed method is compared and analyzed from the viewpoint of undiscovered rate and false positives with the "commercial malicious application detection program", and the performance level is presented.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.235-242
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• 2021

Recently, many human activity recognition(HAR) researches using smartphone sensor data have been studied. HAR can be utilized in various fields, such as life pattern analysis, exercise measurement, and dangerous situation detection. However researches have been focused on recognition of basic human behaviors or efficient battery use. In this paper, exercising activities performed indoors and outdoors were defined and recognized. Data collection and pre-processing is performed to recognize the defined activities by SVM, random forest and gradient boosting model. In addition, the recognition result is determined based on voting class approach for accuracy and stable performance. As a result, the proposed activities were recognized with high accuracy and in particular, similar types of indoor and outdoor exercising activities were correctly classified.

• Journal of Chest Surgery
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• v.55 no.2
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• pp.108-117
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• 2022

Background: The efficacy of telemedicine among cancer survivors is uncertain. The Smart After-Care Program (SAP), which is an interactive, smartphone-based remote health monitoring system, was developed to help patients manage their health after leaving the hospital. This study was designed to evaluate the efficacy of our remote health care program for lung cancer patients. Methods: We enrolled 50 patients with lung cancer. Self-monitoring devices were supplied to all patients, who were instructed to enter their daily vital signs and subjective symptoms to the Smart After-Care app. The app also provided information about rehabilitation exercises and a healthy diet for lung cancer patients. All patients received health counseling via telephone once a week and visited an outpatient clinic during weeks 6 and 12 to assess satisfaction with the SAP and changes in quality of life and physical performance. Results: Overall satisfaction with the SAP was very high (very good, 61.9%; good, 26.2%). In the multivariate analysis to identify factors affecting satisfaction, the distance between the patient's residence and the hospital was the only significant independent factor (p=0.013). Quality of life improved along all functional scales (p<0.05). Muscle strength significantly improved in the lower limbs (p=0.012). Two-minute walk distance also significantly improved (p=0.028). Conclusion: This study demonstrated that the SAP was acceptable for and supportive of patients with reduced pulmonary function after lung cancer treatment. The SAP was found to be particularly useful for patients living far from the hospital.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.494-503
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• 2011

In this paper, we propose a recognition application of facial expression for laughter theraphy on smartphone. It detects face region by using AdaBoost face detection algorithm from the front camera image of a smartphone. After detecting the face image, it detects the lip region from the detected face image. From the next frame, it doesn't detect the face image but tracks the lip region which were detected in the previous frame by using the three step block matching algorithm. The size of the detected lip image varies according to the distance between camera and user. So, it scales the detected lip image with a fixed size. After that, it minimizes the effect of illumination variation by applying the bilateral symmetry and histogram matching illumination normalization. After that, it computes lip eigen vector by using PCA(Principal Component Analysis) and recognizes laughter expression by using a multilayer perceptron artificial network. The experiment results show that the proposed method could deal with 16.7 frame/s and the proposed illumination normalization method could reduce the variations of illumination better than the existing methods for better recognition performance.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.199-209
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• 2021

The purpose of this study was to analyze the factors that affect the satisfaction of smart seniors using smartphone delivery applications. We established the hypothesis by dividing the factors that will affect the satisfaction of smart seniors using smartphone delivery applications into the characteristics of the delivery app and the personal characteristics of the smart senior. In order to verify the hypothesis, we surveyed adult men and women aged 50 to 65 years old who had experience using delivery apps, and we performed confirmatory factor analysis, correlation analysis, and path analysis to perform statistical processing for data analysis. The analysis results are as follows. First, we found that usefulness among the characteristics of delivery app had a statistically significant positive effect on the delivery app satisfaction of smart seniors. Second, we found that social empathy among the personal characteristics of smart seniors had a statistically significant positive effect on the delivery app satisfaction of smart seniors. Third, we found that delivery app satisfaction had a statistically significant positive effect on reuse intention. Based on research result, we suggested that in order to improve the satisfaction and use of delivery app by smart seniors, it is necessary to develop delivery app that can be usefully used by smart seniors and focus on social empathy.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.81-92
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• 2022

Objectives : This study aimed to investigate the effect of beat-keeping games in smartphone applications on improving executive functions in children with developmental delays. Methods : Three children diagnosed with developmental delay were included in this study. The ABA design used a single-subject experimental research design. The independent variable was the beat-keeping game. The game was held three times a week for a total of seven times for 20 minutes, including breaks. The dependent variable, "Visual-motor speed," was measured every session to assess if the beat-keeping game was effective in improving the participant's executive function. Further, before and after the intervention, "Children's Color Trails Test (CCTT)", "Block design," and "Finding hidden picture" were measured. Results : All three participants showed improvement in the performance of the beat-keeping game and the executive functions of "Visual-motor speed" and visual attention. Conclusions : Based on the results of this study, various effective applications for learning and intervention can be developed and applied to children with developmental delays who have difficulty in motivating themselves and lack attention.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.344-351
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• 2016

Recently, mobile application for english vocabulary learning is being developed actively. However, most mobile English vocabulary learning applications did not effectively connected with the technical advantages of mobile learning. Also,the study of mobile english vocabulary learning app are still insufficient. Therefore, this paper development a english vocabulary context-learning Agent that can practice context learning more reasonably using a location-based service, a character recognition technology and augmented reality technology based on smart phones. In order to evaluate the performance of the proposed agent, we have measured the precision and usability. As results of experiments, the precision of learning vocabulary is 89% and 'Match between system and the real world', 'User control and freedom', 'Recognition rather than recall', 'Aesthetic and minimalist design' appeared to be respectively 3.91, 3.80, 3.85, 4.01 in evaluation of usability. It were obtained significant results.