• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1979-1986
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• 2010

Biological early warning system detects toxicity by looking at behavior of organisms in water. The system uses classifier for judgement about existence and amount of toxicity in water. Boosting algorithm is one of possible application method for improving performance in a classifier. Boosting repetitively change training example set by focusing on difficult examples in basic classifier. As a result, prediction performance is improved for the events which are difficult to classify, but the information contained in the events which can be easily classified are discarded. In this paper, an incremental learning method to overcome this shortcoming is proposed by using the extended data expression. In this algorithm, decision tree classifier define class distribution information using the weight parameter in the extended data expression by exploiting the necessary information not only from the well classified, but also from the weakly classified events. Experimental results show that the new algorithm outperforms the former Learn++ method without using the weight parameter.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2036-2041
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• 2005

The underwater multi-agent technology has many potential for the various activities related to ocean development/conservation in the near future. For example, in such fields as water pollution investigation, aquaculture control, or coral reef research, we feel a growing need for a system that realizes underwater continuous monitoring in the wide rang e. In this case, the target monitoring area will be sliced planar hierarchically toward the depth as monitoring layers, and many AUVs arranged on each layer track the given trajectory and gather various environmental information continuously, with communicating each other in the layer or with other layers. To realize those systems we need to develop AUV multi-agent technologies. So we are now building basic systems for basin experiment for the development of AUV multi-agent behavior. We must experience many situations and problems to be solved for the development of its elemental technologies by using real systems as well as our computer simulations. In this paper we introduce our concept of the experiment in the near future and the hardware/software design of our two types of handy AUVs and ultrasound ranging/communication system for that experiment. One AUV is designed using a 17inches-diameter glass sphere with DOS/V and RT-Linux based subsystems, which is intended to use not only in the basin but also in the calm real sea. The other AUV is designed for the basin experiment using a 7inches-diameter acrylic sphere with low-cost embedded system with SH-2 based subsystems. The basin experiment to verify the basic AUV facilities and ultrasound ranging for position detection was carried out.

• Bulletin of the Korean Chemical Society
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• v.26 no.4
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• pp.579-584
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• 2005

The 3-[(2-furylmethylene)amino]-2-thioxo-1,3-thiazolidin-4-one (FTT) was used as an excellent ionophore in construction of a $Zn^{2+}$ PVC-based membrane sensor. The best performance was obtained with a membrane composition of 30% poly(vinyl chloride), 62% nitrobenzen (NB), 3% FTT and 5% sodium tetraphenyl borate (TBP). This membrane sensor shows very good selectivity and sensitivity towards $Zn^{2+}$ over a wide variety of cations, including alkali, alkaline earth, transition and heavy metal ions. The membrane sensor revealed a great enhancement in selectivity coefficients for $Zn^{2+}$ ions, in comparison to the previously reported $Zn^{2+}$ membrane sensors. Theoretical studies also showed the selective interaction of TFF and $Zn^{2+}$ ions. The proposed membrane sensor exhibits a Nernstian behavior (with slope of 29.3 ${\pm}$ 0.3 mV per decade) over a wide concentration range (1.0 ${\times}$ $10^{-6}$-1.0 ${\times}$ $10^{-2}$) with a detection limit of 8.5 ${\times}$ $10^{-7}$ M (52 ng mL$^{-1}$). It shows relatively fast response time, in the whole concentration range ($\lt$ 20 s), and can be used for at least 10 weeks in a pH range of 3.0-7.0. The proposed membrane sensor was successfully used in direct determination of $Zn^{2+}$ ions in wastewater of industrial zinc electroplating companies, and also as an indicator electrode in titration with EDTA.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.1-8
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• 2011

Traffic congestion is a source of significant economic and social costs in urban areas. Intelligent Transportation Systems (ITS) are a promising means to help alleviate congestion by utilizing advanced sensing, computing, and communication technologies. This paper proposes and investigates a basic and advanced ITS framework Advanced Traveler Information System (ATIS) using wireless Vehicle to Roadside (Centralized ATIS model: CA model) and Vehicle to Vehicle (DeCentralized ATIS model: DCA model) communication and assuming an ideal communication environment in the typical $6{\times}6$ urban grid traffic network. Results of this study indicate that an ATIS using wireless communication can save travel time given varying combinations of system characteristics: traffic flow, communication radio range, and penetration ratio. Also, all tested metrics of the CA and DCA models indicate that the system performance of both models is almost identical regardless of varying traffic demand and penetration ratios. Therefore, DCA model can be a reasonable alternative to the fixed infrastructure based ATIS model (CA model).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.45-51
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• 2011

In this paper, we propose an unsupervised learning method for modeling motion trajectory patterns effectively. In our approach, observations of an object on a trajectory are treated as words in a document for latent dirichlet allocation algorithm which is used for clustering words on the topic in natural language process. This allows clustering topics (e.g. go straight, turn left, turn right) effectively in complex scenes, such as crossroads. After this procedure, we learn patterns of word sequences in each cluster using Baum-Welch algorithm used to find the unknown parameters in a hidden markov model. Evaluation of abnormality can be done using forward algorithm by comparing learned sequence and input sequence. Results of experiments show that modeling of semantic region is robust against noise in various scene.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.377-399
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• 2015

Objective: The aim of this study is to understand and identify the critical issues in vision research area using content analysis and network analysis. Background: Vision, the most influential factor in information processing, has been studied in a wide range of area. As studies on vision are dispersed across a broad area of research and the number of published researches is ever increasing, a bibliometric analysis towards literature would assist researchers in understanding and identifying critical issues in their research. Method: In this study, content and network analysis were applied on the meta-data of literatures collected using three search keywords: 'visual search', 'eye movement', and 'eye tracking'. Results: Content analysis focuses on extracting meaningful information from the text, deducting seven categories of research area; 'stimuli and task', 'condition', 'measures', 'participants', 'eye movement behavior', 'biological system', and 'cognitive process'. Network analysis extracts relational aspect of research areas, presenting characteristics of sub-groups identified by community detection algorithm. Conclusion: Using these methods, studies on vision were quantitatively analyzed and the results helped understand the overall relation between concepts and keywords. Application: The results of this study suggests that the use of content and network analysis helps identifying not only trends of specific research areas but also the relational aspects of each research issue while minimizing researchers' bias. Moreover, the investigated structural relationship would help identify the interrelated subjects from a macroscopic view.

• Journal of Preventive Medicine and Public Health
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• v.41 no.4
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• pp.255-264
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• 2008

Objectives: This study adopted a qualitative method to explore the layman's beliefs and experience concerning high blood pressure and its management in order to develop a strategy to increase adherence to proper medical treatment. Methods: Semi-structured interviews that focused on personal experiences with hypertension and its management were conducted with 26 hypertensive patients. The participants were selected according to a BP above 140/90 mmHg (hypertension stage 1), based on the seventh report of the Joint National Committee on prevention, detection, evaluation and treatment of high blood pressure (JNC-VII). The interviews lasted for approximately 30 minutes (range: 20-60 minutes). The resulting questions were formulated into open-ended questions. The interview questionnaire was composed 17 items to examine non-adherence to treatment and 19 items to examine adherence to treatment. Results: Most participants recognized that the direct cause of high blood pressure was unhealthy behavior rather than inheritance. Thus, the hypertensive patient believed they could recover their blood pressure to a normal level through removing the direct cause of hypertension (weight reduction, diet, exercise) instead of taking drugs. The reasons for these statements were that the drugs for controlling hypertension are not natural or they are artificial, and they may have side effects, and drugs are not treatment for the root cause of hypertension. Most of the hypertensive patients chose to manage their behaviors as soon as they knew their blood pressure was high. Therefore, we should not divide the subjects into two groups according to their taking drugs or not, but they should be divided into two groups according to their willingness or not to manage their condition. Conclusions: For developing a strategy for an individual approach to hypertension management, we need to develop a client-centered attitude and strategy. That is, we need to tailor our approach to individual cases to avoid generalizations and stereotyping when developing an adherence increasing strategy.

• Journal of the Korean Chemical Society
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• v.38 no.1
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• pp.50-54
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• 1994

Spectrophotometric determination of some light lanthanide ions by flow injection method is described. Chromeazurol S forms water soluble complex with lanthanide ions in the presence of DTAB. The absorption maximum of the complexes are from 650 nm to 655 nm and the molar absorptivities were ca. $1.8{\times}10^5\;L mol^{-1}cm^{-1}$ on Tris buffer (pH 10.5). The calibration curves for Nd(III), Eu(III) and Sm(III) obtained by FIA are over the range of 0.1 to 0.6 ppm and the correlation coefficient were ca. 0.9993. The detection limits (S/N) were from 10 ppb for Nd(III) and Eu(III) to 20 ppb for Sm(III). The relative standard deviations was ${\pm}$.2% for 0.4 ppm sample. The samples throughput was ca. $50\;cm^{-1}$.

• Journal of the Korean Society for Heat Treatment
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• v.13 no.5
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• pp.309-317
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• 2000

Demand for new nondestructive evaluations is growing to detect tensile crack growth behavior to predict long term performance of materials and structure in aggressive environments, especially when they are in non-visible area. Acoustic emission technique is well suited to these problems and has drawn a keen interests because of its dynamic detection ability, extreme sensitivity and location of growing defects. In this study, we investigated the strength of fire resistance steel for frame structure by tensile test after degradation treatment and analysed acoustic emission signals obtained from tensile test with time frequency analysis methods. In the T and TN specimens(under $600^{\circ}C$-10min ) consisting of ferrite and pearlite structure, most of acoustic emission events were produced near yield point, mainly due to the dislocation activities during the deformation. However, B specimen under $600^{\circ}C$-10min had a two peak which was attribute to the presence of martensite phase. The first peak is before yield point and the second after yield point. The sources of second acoustic emission peak were the debonding of martensite-martensite interface and the micro-cracking of brittle martensite phase. In $600^{\circ}C$-30min to $700^{\circ}C$-60min, many signals were observed before yield point and were decreased after yield point.

• Journal of Sensor Science and Technology
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• v.29 no.4
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• pp.249-254
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• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.