• Journal of Microbiology and Biotechnology
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• v.27 no.4
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• pp.838-843
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• 2017

Sepsis is a major health problem worldwide, with an extremely high rate of morbidity and mortality, partly due to delayed diagnosis during early disease. Currently, sepsis diagnosis requires bacterial culturing of blood samples over several days, whereas PCR-based molecular diagnosis methods are faster but lack sensitivity. The use of biosensors containing nucleic acid aptamers that bind targets with high affinity and specificity could accelerate sepsis diagnosis. Previously, we used the systematic evolution of ligands by exponential enrichment technique to develop the aptamers Antibac1 and Antibac2, targeting the ubiquitous bacterial peptidoglycan. Here, we show that these aptamers bind to four gram-positive and seven gram-negative bacterial sepsis agents with high binding efficiency. Thus, these aptamers could be used in combination as biological recognition elements in the development of biosensors that are an alternative to rapid bacteria detection, since they could provide culture and amplification-free tests for rapid clinical sepsis diagnosis.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.403-408
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• 2015

Kinect sensors have the ability to recognize the behavior and voice of the user. Due to its low-cost and high accessibility, Kinect sensors have been used in various fields, including healthcare, education and so on. In this paper, we propose to use Kinect in piano education. Specifically, the proposed method first recognizes the coordinate values of user's posture, compares them with coordinate values of teacher's posture and provide real-time feedbacks to the user. This enables user to keep the correct posture even when he is learning piano without a teacher. However, since the piano education is a long process, it is difficult to achieve the correct posture as a teacher immediately. Thus, we propose a user-oriented method to measure the error tolerance rate. The proposed method is the first feedback based piano education system that uses Kinect sensors.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.19 no.3
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• pp.141-149
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• 2015

Objectives Recently the fuzzy logic is widely used in the decision making, identification, pattern recognition, optimization in various fields. In this study, we propose the fuzzy logic as the objective method of distinguishing hot and cold, the basis of diagnosis in Korean medicine. Methods We developed fuzzy inference system to distinguish whether the subjects had hot or cold. The cold and hot questionnaire of Korean traditional university textbook, the pulse rate and the DITI value of face used in the system. These three kinds of information were defined as 'fuzzy sets,' and 54 fuzzy rules were established on the basis of clinical practitioners' knowledge. The fuzzy inference was performed by using the Mamdani's method. To evaluate the usefulness of the fuzzy inference system, 200 cases of data measured in the Woosuk university hospital of oriental medicine were used to compare the determining hot, normal, cold results obtained from the experts and from the proposed system. Results As a result, 100 cases of "cold", 54 cases of "normal", and 34 cases of "hot" were matched between the experts and the proposed system. This fuzzy system showed the conformity degree of 94%(${\kappa}=0.853$). Conclusions In this study, we could express the process of distinguishing hot-cold using the fuzzy logic for objectification and quantification of hot-cold identification. This is the first study that introduce a fuzzy logic for distinguish pattern identification. The degree of the heat characteristic of the patients inferred by this system could provide a more objective basis for diagnosing the hot-cold of patients.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.111-124
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• 1999

The Purpose of this thesis is to develop a vehicle classification algorithm using single Magnetometer detector during presence time of vehicle detection and is to examine a held application from field test. We collected data using Magnetometer detector on freeway and used digital data to change voltage values according to magnetic flux density in analysis. We collected these datum during the presence time and then obtained characteristics from wave form in these datum. Based on these characteristics, We used the following three methods for this a1gorithm :1. Template Matching Method,2. Neural Network Method using Back-propagation Algorithm 3. Complex Method using changed slope points and mixing method 1, 2. Of course, Before processing of over three methods, These data were processed normalizing by 20, 40 of size in only X axis and moving average by 0, 3, 4, 5 of size. Vehicle classification were Processed in three steps ; 2, 3, 5 types classification. In 2 types vehicle classification, recognition rate is 83% by template matching method.

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.1032-1042
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• 2009

This research is for early extraction and utilization of semantic information from the tags in tagged Web image retrieval. Generally, users attach a tag to a Web image with little thought of the order, up to over 100 ones. In this paper, we suggest a method of selecting prior tags based on their importance when tagged images are uploaded, and using them in image retrieval. Ideas came from the recognition of the important tags which give a better description of the image as the tags sharing more semantic information with other tags of the same image. This method includes calculation of relation scores between tags based on WordNet and multilevel search of tagged images with the scores. For evaluation, we compared the suggested method and other retrieval methods searching images with simple matching of tags to a given keyword. As the results, we found the superiority of our method in precision and recall rate.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.258-267
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• 2005

We propose the ubiFloor system to track and recognize users in ubiquitous computing environments such as ubiHome. Conventional user identification systems require users to carry tag sensors or use camera-based sensors to be very susceptible to environmental noise. Though floor-type systems may relieve these problems, high cost of load cell and DAQ boards makes the systems expensive. We propose the transparent user identification system, ubiFloor, exploiting user's walking pattern to recognize the user with a set of simple ON/OFF switch sensors. The experimental results show that the proposed system can recognize the 10 enrolled users at the correct recognition rate of $90\%$ without users' awareness of the system.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.93-102
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• 2005

This paper proposes an approach to verify signature using autonomous self-organized Neural Network Model , fused with fuzzy membership equation of fuzzy c-means algorithm, based on the features of the signature. To overcome limitations of the functional approach and Parametric approach among the conventional on-line signature recognition approaches, this Paper presents novel autonomous signature classification approach based on clustering features. Thirty-six globa1 features and twelve local features were defined, so that a signature verifying system with FE-SONN that learns them was implemented. It was experimented for total 713 signatures that are composed of 155 original signatures and 180 forged signatures yet 378 original signatures written by oneself. The success rate of this test is more than 97.67$\%$ But, a few forged signatures that could not be detected by human eyes could not be done by the system either.

• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.423-431
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• 2018

The Purpose of the study was to explore the experience and meaning of employment in the outside hospital of graduates of nursing college with an affiliated hospital. The participants were five senior nursing students, data were collected by three times of Focus group interviews from July, 2017, and analyzed using content analysis. Five Themes and thirteen sub-themes were identified. Implications of the employment experience were 'selection criteria for various employment hospitals according to personal value and experience', 'recognition and reward for hard work', 'influence of hospital name value', 'opportunity to develop own potential', and 'fear coming from employment in non-affiliated hospital'. The results of this study are significant in that it provides basic information that can be taken into account in the employment guidance of nursing college students and the turnover rate of new nurses.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.2
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• pp.183-192
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• 2009

SAR(Synthetic Aperture Radar) is an all-weather imaging radar and is widely used in military and civil application. Especially high-resolution SAR images are very important in military purpose because it can be used at target recognition application. LIG Nex1 developed a SAR system called NexSAR with bandwidth of 600 MHz and resolution of 30 cm to obtain technologies required for high-resolution SAR. To achieve 600 MHz bandwidth of waveform generator, two DDSs are used and its output signals are SSB modulated. And deramp technique is used to reduce the sampling rate of ADC at high resolution mode. NexSAR has stripmap and spotlight modes and its functionality and performances are evaluated through ground and flight tests.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.95-101
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• 2009

As RFID technology has been developed rapidly, its technical potential has it be widely used in many industrial fields. Particularly, in the physical distribution industry, the introduction of RFID has enormously contributed to effectively monitoring locations and information of products in real-time. Also, a significant decline in tag prices and RFID related technical competitiveness enabled each tag to be managed much more minutely by attaching it to an item, not a pallet nor a container. However, if a very large volume of tag data are continuously flowed into a RFID middleware with limited hardware resources, its entire data processing time may become considerably longer. Therefore, specific technologies are in great demand to handle and further to reduce the load of the middleware. In this paper, we proposed a mobile agent-based software module to efficiently reduce the load of the middleware by pre-processing a lot of tag data while items are in transit. Simulation results show that using the proposed software module considerably enhances the speed of processing tag data than otherwise. This behavior increases the tag recognition rate in a certain time limit and improves reliability of RFID middlewares.