• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.496-499
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• 1999

This paper describes a medular neural network(MNN) for a vision system which tracks a given object using a sequence of images from a camera unit. The MNN is used to precisely recognize the given robot endeffector and to minize the processing time. Since the robot endeffector can be viewed in many different shapes in 3-D space, a MNN structure, which contains a set of feedforwared neural networks, co be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training patterns for a neural network share the similar charateristics so that they can be easily trained. The trained MNN is less sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.13-18
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• 2007

Human's sight holds the most extents for recognizing information among other senses. If we make much better visualized environment for human, it will become more beneficial in person's emotion or body. Human is using a lot of display units in modern society. Basic hues ate Red, Green and Blue. Using these three colors, we can change hue sense and degree of brightness of display unit. If we control hue of unit to be suitable according to individual environment, we can feel comfortable or reduce stress. In this paper, we present Human-Friendly Intelligent Hue Control System(HFIHCS) that control hue of display unit using fuzzified factors related to human's emotion and environment. The effectiveness of the proposed system is demonstrated by questionnaire.

• The Mathematical Education
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• v.62 no.4
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• pp.457-471
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• 2023

Measurement is an imperative content area of early elementary mathematics, but it is reported that students' understanding of units in measurement situations is insufficient despite its importance. Therefore, this study examined lower-grade elementary students' quantitative reasoning of units in length measurement by identifying the levels of reasoning of units. For this purpose, we collected and analyzed the responses of second-grade elementary school students who engaged in a set of length measurement tasks using an open number line in terms of unitizing, iterating, and partitioning. As a result of the study, we categorized students' quantitative reasoning of unit levels into four levels: Iterating unit one, Iterating a given unit, Relating units, and Transforming units. The most prevalent level was Relating units, which is the level of recognizing relationships between units to measure length. Each level was illustrated with distinct features and examples of unit reasoning. Based on the results of this study, a personalized plan to the level of unit reasoning of students is required, and the need for additional guidance or the use of customized interventions for students with incomplete unit reasoning skills is necessary.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.308-314
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• 2022

As a result of the global effect of infectious diseases like COVID-19, remote patient monitoring has become a vital need. Surgical ICU monitors are attached around the clock for patients in critical care. Most ICU monitor systems, on the other hand, lack an output port for transferring data to an auxiliary device for post-processing. Similarly, strapping a slew of wearables to a patient for remote monitoring creates a great deal of discomfort and limits the patient's mobility. Hence, an unique remote monitoring technique for the ICU monitor's physiologically vital readings has been presented, recognizing this need as a research gap. This mechanism has been put to the test in a variety of modes, yielding an overall accuracy of close to 90%.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.61-71
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• 2009

This study aims to investigate whether the misalignment between syllable and word onsets due to the process of resyllabification affects Korean-English late bilinguals perceiving English continuous speech. Two word-spotting experiments were conducted. In Experiment 1, misalignment conditions (resyllabified conditions) were created by adding CVC contexts at the beginning of vowel-initial words and alignment conditions (non-resyllabified conditions) were made by putting the same CVC contexts at the beginning of consonant-initial words. The results of Experiment 1 showed that detections of targets in alignment conditions were faster and more correct than in misalignment conditions. Experiment 2 was conducted in order to avoid any possibilities that the results of Experiment 1 were due to consonant-initial words being easier to recognize than vowel-initial words. For this reason, all the experimental stimuli of Experiment 2 were vowel-initial words preceded by CVC contexts or CV contexts. Experiment 2 also showed misalignment cost when recognizing words in resyllabified conditions. These results indicate that Korean listeners are influenced by misalignment between syllable and word onsets triggered by a resyllabification process when recognizing words in English connected speech.

• The Journal of the Acoustical Society of Korea
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• v.10 no.2
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• pp.29-35
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• 1991

In this paper, we discuss the method of recognizing allophone unit isolated words using hidden Markov model(HMM). Frist we constructed allophone lexicon by extracting allophones from training data and by training allophone HMMs. And then to recognize isolated words using allophone HMMs, it is necessary to construct word dictionary which contains information of allophone sequence and inter-allophone transition probability. Allophone sequences are represented by allophone HMMs. To see the effects of inter-allophone transition probability and to determine optimal probabilities, we performend some experiments. And we showed that small number of traing data and simple train procedure is needed to train word HMMs of allophone sequences and that not less performance than word unit HMM is obtained.

• Journal of Korean Critical Care Nursing
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• v.10 no.3
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• pp.19-30
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• 2017

Purpose : This study investigated factors affecting the knowledge and attitude of organ procurement from brain dead patients in nurse clinicians. Methods : A survey was conducted with 160 clinical nurses from a university hospital in Seoul. Descriptive statistics, t-tests, an ANOVA, $Scheff{\acute{e}}^{\prime}s$ test, Pearson's correlation coefficient, and a multiple regression analysis were used. Results : The mean score for knowledge of organ procurement from brain dead patients was $12.41{\pm}2.16$ (mean correct answers = 62.1). Factors influencing the knowledge of organ procurement among nurse clinicians were working department (${\beta}=.454$, p < .001), a recent family death (${\beta}=.187$, p = .014), experience recognizing potential brain dead patients (${\beta}=.182$, p = .033), and experience referring to potential brain dead patients (${\beta}=-.192$, p = .048). Conclusion : To ensure effective organ procurement from brain dead patients, it is necessary to continually educate nurse clinicians to improve their attitude and knowledge concerning organ donation.

• Journal for History of Mathematics
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• v.30 no.4
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• pp.221-232
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• 2017

In this paper, we discuss how ancient Egyptians find out the area of the circle based on $\ll$Ahmose Papyrus$\gg$. Vogel and Engels studied the quadrature of the circle, one of the basic concepts of ancient Egyptian mathematics. We look closely at the interpretation based on the approximate right triangle of Robins and Shute. As circumstantial evidence for Robbins and Shute's hypothesis, Egyptians prior to the 12th dynasty considered the perception of a right triangle as examples of 'simultaneous equation', 'unit of length', 'unit of slope', 'Egyptian triple', and 'right triangles transfer to Greece'. Finally, we present a method to utilize the squaring the circle by ancient Egyptians interpreted by Robbins and Shute as the dynamic symmetry of Hambidge.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.283-291
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• 2013

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.