• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.170-178
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• 2011

In this paper, a research was performed to develop a wireless measurement system for bridge monitoring using MEMS sensor and bluetooth wireless communication module. First, in order to prove the suitability of MEMS sensor for the bridge measurement, its ranges of measuring acceleration and of frequency response were experimented. Also, the quality of wireless communication was tested by an experiment on long-distance communication for the knowledge of maximum communication distance, and also by an experiment on the data transmit-receive capability both inside and outside of a steel box bridge. Later, placing the wireless acceleration sensor system that had been developed in our lab on a bridge in public service, we acquired vibration data from the bridge under traffic load and analyzed its dynamic characteristics in realtime. For the analysis of the data, NExT & ERA algorithm were employed. The result of analysis was compared to the FE analysis of the same bridge, and the comparison made it possible to evaluate the performance of wireless acceleration sensor system. As a result, it was proven that the wireless acceleration sensor system developed with the use of MEMS sensor and bluetooth wireless communication module could be effectively applied to the measurement of structure whose vibration feature was low frequency like a bridge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1123-1132
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• 2018

In this paper, we design and implement a public bicycle sharing system based on smart phone application capable of distributing access codes via internet connection. When smartphone user uses the application to request a bicycle unlock code, server receives the request and sends an encrypted code, which is used to unlock the bicycle at the station and the same code is used to return the bicycle. The station's hardware prototypes were built on top of Internet devices such as raspberry pi, arduino, keypad, and motor driver, and smartphone application basically includes shared bike rental and return functionality. It also includes an additional feature of reservation for a certain time period. We tested the implemented system, and found that it is efficient because it shows the average of 3-4 seconds delay. The system can be implemented to manage multiple bikes with a single control box, and as the user can use a smartphone application, this makes the system more cost effective.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.25-36
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• 2008

In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.

• Korean Journal of Cognitive Science
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• v.32 no.3
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• pp.117-139
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• 2021

The way of change detection in which presence of a different item is determined between memory and test arrays with a brief in-between time interval resembles how visual search is done considering that the different item is searched upon the onset of a test array being compared against the items in memory. According to the resemblance, the present study examined whether varying the probability of change occurrence in a visual short-term memory-based change detection task can influence the aspect of response-decision making (i.e., change prevalence effect). The simple-feature change detection task in the study consisted of a set of four colored boxes followed by another set of four colored boxes between which the participants determined presence or absence of a color change from one box to the other. The change prevalence was varied to 20, 50, or 80% in terms of change occurrences in total trials, and their change detection errors, detection sensitivity, and their subsequent RTs were analyzed. The analyses revealed that as the change prevalence increased, false alarms became more frequent while misses became less frequent, along with delayed correct-rejection responses. The observed change prevalence effect looks very similar to the target prevalence effect varying according to probability of target occurrence in visual search tasks, indicating that the background principles deriving these two effects may resemble each other.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.127-133
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• 2021

A recent study of people physically falling focused on analyzing the motions of the falls using a recurrent neural network (RNN) and a deep learning approach to get good results from detecting 2D human poses from a single color image. In this paper, we investigate a detection method for estimating the position of the head and shoulder keypoints and the acceleration of positional change using the skeletal keypoints information extracted using PoseNet from an image obtained with a low-cost 2D RGB camera, increasing the accuracy of judgments about the falls. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion-analysis method. A public data set was used to extract human skeletal features, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than a conventional, primitive skeletal data-use method.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Cartoon and Animation Studies
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• s.29
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• pp.1-36
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• 2012

The (2003) by Pixar, by succeeding at box office hit with good criticism, could be the film that made Pixar the most influential animation producer. Especially such character oriented narrative strategy, by raising the degree of characterizing and relationship, could made remarkable achievement as it is called a textbook of characterizing. This study focused on the inherent fear and desire of characters in . The inherent fear and desire were assumed to be the elements that strengthen characterizing and relationship more dynamically. In general, every single choice and behavior of human beings are likely to be depending on fear and desire, it is believed that human's life is dominated by those two elements. In this point, the characterizing of has three big features. It is that (1) it clearly described the fear inherent in characters and the effort to avoid the fear better than any other films of Pixar. (2) it strikingly accords with the interaction of characteristics of fear and desire established by Enneargram personality types. (3) the way of relieving fear of the main characters (Marlin and Nemo), as a unique feature of rescue and escape plot in which two characters are being apart, is not by interaction of characteristics of two main characters but is by characterizing the spiritual value supplementary to the deficiency of main character as sub character (Dory and Gill). In the previous study, , characterizing of panda 'Poe' is too outstanding and this fact is working as paradoxical limitation. On the other hand, set up of fear and desire of two main characters, Poe and Shifu and dynamics of characteristics are very delicate and effective. On the other hand, in the , in the course of settling down the conflicts between two main characters, father and son, it shows fresh and firm narrative structure with various characters and sub plots. However, though the degree of described fear and desire of main characters are very outstanding, it still reveals it limitation that the course of settlement is somewhat dependent. In conclusion, this study is considered to be another approach to animation characterizing, and also hopefully can be helpful in characterization and setting up relationships in the future.