• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.39-46
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• 2017

Today, mobile devices are becoming essential for everyday life, and integration of mobile computing, situation recognition and intellectual service accelerates mobile interaction. Surrounding intelligence detection technology is extremely important. These technologies can automatically acquire and recognize surrounding information and situations. Situation recognition can realize wide-range mobile recognition for intellectual services of users' diverse activities, by distinguishing many surrounding devices and recognizing their situations. Thus, this paper suggests application for students' mobile authentication such as college campus attendance authentication, and redesign existing plastic student ID as NFC-compatible mobile authentication system. Experiment results proved NFC-compatible mobile touch-based interactions can maximize the strengths of NFC technology because it can recognize limits in some situations such as tardiness and absences by automating student validation and preventing far-distance reading.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.63-70
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• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.49-56
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• 2005

An electron microbeam system has been developed to investigate the biological effect of cells by irradiating cell-nuclei with low-energy and low-flux electrons. It is essential to discern the cell nucleus from its cytoplasm and the culture medium and to locateit exactly onto the beam exit. The irradiation speed at more than 10,000 cells per hour is another requisite for the observations on cellular response to have good statistics. Long-time labor with patience and high concentration is needed since the frames of $320{\times}240{\mu}m^2$ should be moved more than 500 times for irradiating more than 10,000 cells per an hour. This paper describes the electron microbeam system with a focus on the user interfaces concerning the process of automatically recognizing the cell nuclei and injecting electron beam into the target cell nuclei at the irradiation speed of more than 10,000 cell nuclei per hour.

• Advances in nano research
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• v.12 no.2
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• pp.185-195
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• 2022

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

• Korea Journal of Hospital Management
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• v.28 no.2
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• pp.21-31
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• 2023

Purposes: Patient experience is a tool to evaluate the process and results of medical services provided by medical institutions from the patient's point of view. Patient satisfaction surveys are a meaningful and essential source of information for improving quality in healthcare organizations. This study aims to provide basic data for improving the quality of medical service that patients can feel by analyzing the recommendation intention and satisfaction of inpatients in specialty hospitals. Methodology: The subjects of this study were 879 inpatients in 28 specialty hospitals in 14 designated fields. We conducted a telephone survey with a structured questionnaire on the satisfaction and recommendation intention for specialty hospitals. Findings: In inpatients, hospital satisfaction was higher in nursing care services and hospital satisfaction was low in physicians care services. The overall patient satisfaction score was 91.4(SD=11.9) out of 100, and the intention of recommendation was 92.0(SD=14.1) out of 100. The factors affecting patient experience were designated fields, sex, age, residential area, monthly household income, and perceived health status. Practical Implications: This study confirmed the high level of patient satisfaction and recommendation intention among inpatients of specialty hospitals. Patient satisfaction can be of great value to healthcare providers in recognizing and improving the quality of care, as well as predicting patients' willingness to revisit medical institutions. This study can be used to improve the quality of hospital care services in specialty hospitals rather than general and tertiary general hospitals.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.57-66
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• 2023

Asset valuation of social infrastructure is essential for rational decision-making for efficient management of assets. In addition, it can be an indicator for correctly recognizing assets. In general, Korea applies depreciated replacement cost based on the straight-line method to evaluate asset value, yet this is unsuitable for evaluating actual value because it is depreciated at a constant rate over the useful life period. In order to evaluate the asset value considering the performance of the bridge, the performance index of the bridge is estimated using the Weibull distribution. Using the estimated performance indicators and defect index, a new asset value evaluation method is proposed and compared and analyzed with the existing method. The proposed valuation method can take into account the performance of the bridge, so it is judged to be more objective and reasonable than existing method.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.1-17
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• 1997

Geographic Information Systems(GIS) are very useful for spatial analysis and policy in local government administration. Recognizing the value of GIS, Chungnam province authorities put a spur on the introduction and development of it. But they have some difficulty in this process because of technical restraint, expertise shortage and budget limit. This study has surveyed current achievement and conditions for GIS development and presented general framework and subordinate tasks to build up GIS. First of all, there are a few prior conditions to guarantee the success of GIS: First, we should set up reasonable long-term plan and follow systematic procedures according to the plan. Second, it is essential to clarify what initiatively manage to whole business and so we should make up GIS-Board as an institutional center for this job. Third, we must research how to take advantage of already existing NGIS(National Geographic Information System), so that we may eliminate redundancy of investment. We can save a lot of finance and human resources through it. Fourth, we must focus on the importance of accurate mapping by utilizing new technology like GPS(Global Positioning System). Fifth, we should arrange efficient training program to constantly produce excellent human resources for GIS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.50-53
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• 2022

Recently, there have been cases in which counterfeit foreign ships have entered and left domestic ports several times. Vessels have a ship-specific serial number given by the International Maritime Organization (IMO) to identify the vessel, and IMO marking is mandatory on all ships built since 2004. In the case of airports and ports, which are representative logistics platforms, a security system is essential, but it is difficult to establish a security system at a port and there are many blind spots, which can cause security problems due to insufficient security systems. In this paper, a port security system is designed using deep learning object recognition and OpenCV. The security system process extracts the IMO number of the ship after recognizing the object when entering the ship, determines whether it is the same ship through feature point matching for ships with entry records, and stores the ship image and IMO number in the entry/exit DB for the first arrival vessel. Through the system of this paper, port security can be strengthened by improving the efficiency and system of port logistics by increasing the efficiency of port management personnel and reducing incidental costs caused by unauthorized entry.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.85-93
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• 2016

Convergent education is essential to develop consilient thinking skills, ability to recreate information and knowledge, and problem-solving skills which are demanded in society of convergent knowledge. Accordingly, this study is going to develop a convergent class model of augmented reality and art based on consilient knowledge. Teaching model is designed based on the ADDIE model, which was operated by opening a real class in order to verify the validity. The result showed a high satisfaction of learners showed the ability to adapt to the major areas associated with the cultivation of learners. Characteristics of augmented reality medium were found to enable learners to analyze a new phenomenon and to fuse the necessary knowledge by inducing them to actively interact by the their intention in learning. Therefore, it is possible to cultivate creative and convergent persons of ability equipped with more flexible and creative thinking ability and discernment through deepened education for recognizing and understanding convergent cases between art and scientific technology. There is a study on the validation and the convergence of different subjects in terms of a variety of aspects, left behind of this study.