• Journal of Korean Academy of Fundamentals of Nursing
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• v.6 no.3
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• pp.570-582
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• 1999

Although computers cannot analyze textual data in the same way as they analyze numerical data. they can nevertheless be of great assistance to qualitative researchers. Thus, the use of computers in analyzing qualitative data has increased since the 1980s. The purpose of this article was to explore advantages and disadvanteges of using computers to analyze textual data and to suggest strategies to prevent problems of using computers. In additon, it illustrated characteristics and functions of softwares designed to analyze qualitative data to help researchers choose the program wisely. It also demonstrated precise functions and procedures of the NUDIST program which was designed to develop a conceptual framework or grounded theory from unstructured data. Major advantage of using computers in qualitative research is the management of huge amount of unstructured data. By managing overloaded data, researcher can keep track of the emerging ideas, arguments and theoretical concepts and can organize these tasks mope efficiently than the traditional method of 'cut-and-paste' technique. Additional advantages are the abilities to increase trustworthiness of research, transparency of research process, and intuitional creativity of the researcher, and to facilitate team and secondary research. On the other hand, disvantages of using computers were identified as worries that the machine could conquer the human understanding and as probability of these problems. it suggested strategies such as 1) deep understanding of orthodoxy in analytical process. To overcome philosophical and theoretical background of qualitative research method, 2) deep understanding of the data as a whole before using software, 3) use of software after familiarity with it, 4) continuous evaluation of software and feedback from them, and 5) continuous awareness of the limitation of the machine, that is computer, in the interpretive analysis.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.4
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• pp.97-103
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• 2018

Force is a crucial element to be measured in various industries, especially the machine tool industry. Mega units of force are required in fields such as the heavy and ship industries. Micro/nano units of force are required for microparticles. The detection of force generates a physical transformation due to the force imposed from the outside, atlrnd electrical voltage signals are obtained from the system. For the detection of force, an octagonal ring load cell based on circular ring theory is designed and produced. To design the octagonal strain ring, theoretical values with data from the ANSYS program are compared to determine the size of the octagonal strain ring. An octagonal strain ring of the chosen size is made with the SCM415 material. The strain gauges are attached to the octagonal strain ring, designed to construct a full Wheatstone bridge. The LabVIEW program is used to measure the data, and strain values are found. With the octagonal ring load cell completed in this way, experiments are conducted by imposing forces on the tangential axis and radial axis. Experiments are performed to verify if the octagonal ring load cell conducts measurements properly, and theoretical values are analyzed to find any differences. The data will later be used in further research to develop a machine-tool dynamometer.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.549-557
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• 2000

Distributed Memory Machine(DMM) is necessary for the effective computation of the data which is complicated and very large. Task scheduling is a method that reduces the communication time among tasks to reduce the total execution time of application program and is very important for the improvement of DMM. Task Duplicated based Scheduling(TDS) method improves execution time by reducing communication time of tasks. It uses clustering method which schedules tasks of the large communication time on the same processor. But there is a problem that cannot optimize communication time between task sending data and task receiving data. Hence, this paper proposes a new method which solves the above problem in TDS. Modified Task Duplicated based Scheduling(MTDS) method which can approximately optimize the communication time between task sending data and task receiving data by checking the optimal condition, resulted in the minimization of task execution time by reducing the communication time among tasks. Also system modeling shows that task execution time of MTDS is about 70% faster than that of TDS in the best case and the same as the result of TDS in the worst case. It proves that MTDS method is better than TDS method.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.4
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• pp.142-149
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• 1996

Pyramid type three roll bending machines are widely used in roll-bending process to produce singly curved plate. In forming singly curved plate, controlling the vertical displacement of the center roller is most important to acquire the shape required and automation system of the process. In this paper roller bending process is modeled as an elastic-plastic phenomenon and analyzed using beam theory and finite element method. In finite element analysis the workpiece is modeled by using beam elements and plane strain elements respectively. Through the analyses vertical center roller displacement is obtained to get constant curvature distribution along arc length. The relationship between center roller displacement and curvature in steady state as well as residual stress and strain along plate thickness direction are calculated through finite element analysis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.297-301
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• 2014

게임에는 많은 종류의 장르가 있다. 어떤 장르의 게임이 되었건 플레이어와 많은 상호작용을 하는 A.I는 게임에 있어 중요한 요소 이며 어드벤처 게임(Adventure Game) 장르도 예외는 아니다. A.I(Artificial Intelligence)I의 행동이나 상황에 따른 플레이어와의 상호작용은 게임에 있어 플레이어에게 몰입감을 주며 게임을 좀 더 현실감 있게 해주는 게임의 수많은 요소 중 하나다. 본 논문에서는 FSM(Finite-State Machine) 기법을 사용하여 어드벤처 게임에서플레이어에게 '몰입'을 유발 시키는 방법으로 FSM 기법의 NPC(None-Player Character) A.I 패턴을 디자인을 통해 플레이어의 '몰입'을 유발 하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.2
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• pp.142-149
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• 2010

Interior Permanent Magnet Synchronous Motor(IPMSM) have gained an increasing popularity in recent years for a variety of industrial applications, because of their high power density, high efficiency and possibility of flux weakening operation. Because the efficiency of IPMSM is one of the important performance characteristic, the Maximum Torque Per Ampere(MTPA) operating method has been indispensible. In theory, MTPA operating point can be calculated using the exact values of the machine parameters. However, the values of the IPMSM parameters are known to vary widely according to the operating condition. Therefore, to operate the IPMSM in the MTPA operating point, the machine parameters should be estimated in real-time. In this paper, the new MTPA operating method based on the signal injection is presented. By injecting the high frequency current signal, the MTPA operating criteria can be calculated by measuring the input power to IPMSM. The proposed method can find the MTPA operating point with simple signal processing regardless of the parameter variation.

• Journal of Biomedical Engineering Research
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• v.27 no.5
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• pp.250-259
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• 2006

The information of eye movement is used in various fields such as psychology, ophthalmology, physiology, rehabilitation medicine, web design, HMI(human-machine interface), and so on. Various devices to detect the eye movement have been developed but they are too expensive. The general methods of eye movement tracking are EOG(electro-oculograph), Purkinje image tracker, scleral search coil technique, and video-oculograph(VOG). The purpose of this study is to embody the algorithm which tracks the location of the gazing point at a pupil. Two kinds of location data were compared to track the gazing point. One is the reference points(infrared LEDs) which is effected from the globe. Another is the center point of the pupil which is gained with a CCD camera. The reference point was captured with the CCD camera and infrared lights which were not recognized by human eyes. Both of images which were thrown and were not thrown an infrared light on the globe were captured and saved. The reflected reference points were detected with the brightness difference between the two saved images. In conclusion, the circumcenter theory of a triangle was used to look for the center of the pupil. The location of the gazing point was relatively indicated with the each center of the pupil and the reference point.

• Advances in aircraft and spacecraft science
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• v.3 no.3
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• pp.351-366
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• 2016

Macroperforations improve the sound absorption performance of porous materials in acoustic cavities and in waveguides. In an acoustic cavity, enhanced noise reduction is achieved using porous materials having macroperforations. Double porosity materials are obtained by filling these macroperforations with different poroelastic materials having distinct physical properties. The locations of macroperforations in porous layers can be chosen based on cavity mode shapes. In this paper, the effect of variation of macroporosity and double porosity in porous materials on noise reduction in an acoustic cavity is presented. This analysis is done keeping each perforation size constant. Macroporosity of a porous material is the fraction of area covered by macro holes over the entire porous layer. The number of macroperforations decides macroporosity value. The system under investigation is an acoustic cavity having a layer of poroelastic material rigidly attached on one side and excited by an internal point source. The overall sound pressure level (SPL) inside the cavity coupled with porous layer is calculated using mixed displacement-pressure finite element formulation based on Biot-Allard theory. A 32 node, cubic polynomial brick element is used for discretization of both the cavity and the porous layer. The overall SPL in the cavity lined with porous layer is calculated for various macroporosities ranging from 0.05 to 0.4. The results show that variation in macroporosity of the porous layer affects the overall SPL inside the cavity. This variation in macroporosity is based on the cavity mode shapes. The optimum range of macroporosities in poroelastic layer is determined from this analysis. Next, SPL is calculated considering periodic and nodal line based optimum macroporosity. The corresponding results show that locations of macroperforations based on mode shapes of the acoustic cavity yield better noise reduction compared to those based on nodal lines or periodic macroperforations in poroelastic material layer. Finally, the effectiveness of double porosity materials in terms of overall sound pressure level, compared to equivolume double layer poroelastic materials is investigated; for this the double porosity material is obtained by filling the macroperforations based on mode shapes of the acoustic cavity.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.24-34
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• 2021

The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.