• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.299-306
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• 2016

In this paper, a method of shape prediction of an endoscope handling robot that can imitate a surgeon's behavior using a sensor network is suggested. Unit sensors, which are composed of a 3-axis magnetometer and 3-axis accelerometer pair comprise the network through CAN bus communication. Each unit of the sensor is used to detect the angle of the points in the longitudinal direction of the robot, which is made from a flexible tube. The signals received from the sensor network were filtered using a low pass Butterworth filter. Here, a Butterworth filter was designed for noise removal. Finally, the Euler angles were extracted from the signals, in which the noise was filtered by the low path Butterworth filter. Using this Euler angle, the position of each sensor on the sensor network is estimated. The robot body was assumed to consist of links and joints. The position of each sensor can be assumed to be attached to the center of each link. The position of each link was determined using the Euler angle and kinematics equation. The interpolation was carried out between the positions of the sensors to be able to connect each point smoothly and obtain the final posture of the endoscope in operation. The experimental results showed that the shape of the colonoscope can be visualized using the Euler angles evaluated from the sensor network suggested and the shape of serial link estimated from the kinematics chain model.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.12
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• pp.17-23
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• 2010

In the mobile cloud computing, the mobile node should request and receive the services while being connected. In PMIPv6, all packets sent by mobile nodes or correspondent nodes are transferred through the local mobility anchor. This unnecessary detour still results in high delivery latency and significant processing cost. Several PMIPv6 route optimization schemes have been proposed to solve this issue. However, they also suffer from the high signaling costs and handover latency when determining the optimized path. We propose the route optimization handover scheme which adopts the prediction algorithm in PFMIPv6. In the proposed scheme, the new mobile access gateway establishes the bi-directional tunnel with the correspondent node's MAG using the context message when the mobile node's handover is imminent. This tunnel may eliminate the need of separate route optimization procedure. Hence, the proposed scheme can reduce the signaling cost than other conventional schemes do. Analytical performance evaluation is preformed to show the effectiveness of the proposed scheme. The result shows that our scheme is more effective than other schemes.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.4
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• pp.428-435
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• 2004

With the rapid and wide-spread use of cellular telephones much attention has been focussed on propagation in the urban area crowed with buildings and houses. It is often surrounded by hills, forests, and mountains. The importance of surface scattering intereference between transmitters and receivers on the rough surfaces has been interested and investigated. Therefore, a prediction method is necessary to estimate the influence of rough surfaces on microwave radio propagation. Moreover, most of the mobile communications are performed based on the digital communication system rather than the analog one. In this case, we must pay more careful attention to the signal delay caused by the phase delay due to the multi-path propagation. In this paper we have analyzed numerically scattering of electromagnetic waves from building walls by using FVTD(Finite Volume Time Domain) method. We consider three different types of rough surfaces such as periodic, random, and composite structures. We calculate the bistatic normalized radar cross section (NRCS) for horizontal and vertical polarization, and we take account of the conventional optical reflection which corresponds to the n-th Bragg reflection for periodic structures. In addition, we investigated what conditions are needed in order to be able to ignore the higher order Bragg reflection for the periodic structures.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1115-1123
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• 2008

When constructing projects such as road embankments, bridge approaches, dikes or buildings on soft, compressible soils, significant settlements may occur due to the consolidation of these soils under the superimposed loads. The compressibility of the soil skeleton of a soft clay is influenced by such factors as structure and fabric, stress path, temperature and loading rate. Although it is possible to determine appropriate relations and the corresponding material parameters in the laboratory, it is well known that sample disturbance due to stress release, temperature change and moisture content change can have a profound effect on the compressibility of a clay. The early research of Tezaghi and Casagrande has had a lasting influence on our interpretation of consolidation data. The 24 hour, incremental load, oedometer test has become, more or less, the standard procedure for determining the one-dimensional, stress-strain behavior of clays. An important notion relates to the interpretation of the data is the ore-consolidation pressure ${\sigma}_p$, which is located approximately at the break in the slope on the curve. From a practical point of view, this pressure is usually viewed as corresponding to the maximum past effective stress supported by the soil. Researchers have shown, however, that the value of ${\sigma}_p$ depends on the test procedure. furthermore, owing to sampling disturbance, the results of the laboratory consolidation test must be corrected to better capture the in-situ compressibility characteristics. The corrections apply, strictly speaking, to soils where the relation between strain and effective stress is time independent. An important assumption in Terzaghi's one-dimensional theory of consolidation is that the soil skeleton behaves elastically. On the other hand, Buisman recognized that creep deformations in settlement analysis can be important. this has led to extensions to Terzaghi's theory by various investigators, including the applicant and coworkers. The main object of this study is to suggestion the modified compression index value to predict settlements by back calculating the $C_c$ from different numerical models, which are giving best prediction settlements for multi layers including very thick soft clay.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.391-403
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• 2014

This study seeks to carry out a literary review of preceding studies and the health improvement model of Pender(1987) on university students majoring in nursing to explain the health improvement behaviors and identify the factors that affect their activities to provide a framework for developing a more effective nursing mediation method that promotes health improvement behaviors. The study subjects were 204 university students majoring in nursing who have had clinical practice experience. The period for data collection was from April 1to May 30, 2014 and a total of 204 copies of the questionnaire were used for analysis. For the collected data, frequency analysis, percentage, ANOVA, t-test and correlation analysis were conducted using SPSS, LISREL, and path analyss was done for hypothesis testing. The overall index of hypothesis model showed a good congruence as ${\chi}^2=.06$(p=.812), df=1, ${\chi}^2(df)=.000$, GFI=0.97, AGFI=1.0, SRMR=.002, NFI=0.947, NNFI=0.957, RMSEA=0.016, CN=266. Looking at the verification of the hypothesis presented in the model, the variables that affect health improvement behaviors were perceived disability, perceived self-efficacy, perceived social support, while stress from clinical practice, perceived health status, persistence and perceived benefits did not affect health improvement behaviors.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.23-47
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• 2003

Traditional studies for customer relationship management (CRM) generally focus on static CRM in a specific time frame. The static CRM and customer behavior knowledge derived could help marketers to redirect marketing resources fur profit gain at that given point in time. However, as time goes, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Customer-based analysis should observe the past purchase behavior of customers to understand their current and likely future purchase patterns in consumer markets, and to divide a market into distinct subsets of customers, any of which may conceivably be selected as a market target to be reached with a distinct marketing mix. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date. In this paper, we propose a dynamic CRM model utilizing data mining and a Monitoring Agent System (MAS) to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the Internet retailer. The proposed model includes an extensive analysis about a customer career path that observes behaviors of segment shifts of each customer: prediction of customer careers, identification of dominant career paths that most customers show and their managerial implications, and about the evolution of customer segments over time. furthermore, we show that dynamic CRM could be useful for solving several managerial problems which any retailers may face.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.284-288
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• 2009

With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.227-233
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• 2021

To obtain a fruitful outcome in intellectual property (IP) education in colleges, it is essential to identify the affecting factors. The relationships between the factors were to be analyzed as a structural equation model. The IP education achievement was measured by the IP total score. The students' characteristics (input factor) were measured by defining the characteristics, parents' expectations, and IP interest. The characteristics after highschool (process factor) were observed as college satisfaction and learning attitude. Students with excellent defining characteristics have not only high college satisfaction but also an excellent learning attitude, so they have a high IP total score. Using indirect effects analysis, the path through which the defining characteristics indirectly affects the IP total score through college satisfaction and learning attitude was identified. This is consistent with the prediction that self-directed students will have high participation in IP classes and achieve excellent results. The IP interest was found to have no significant effect on the IP total score. This contradicts the belief that students with high IP interest will actively participate in IP classes and earn high scores, which is because it overlooks the possibility that participation in IP activities in high school is semi-forced.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3543-3548
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• 2023

Shutdown chemistry evolution is performed in nuclear power plants at each refueling outage (RFO) to establish safe conditions to open system and minimize inventory of corrosion products in the reactor coolant system (RCS). After hydrogen peroxide is added to RCS during shutdown chemistry evolution, corrosion products are released and are removed by filters and ion exchange resins in the chemical volume control system (CVCS). Shutdown chemistry evolution including RCS clean-up time to remove released corrosion products impacts the critical path schedule during RFOs. The estimation of clean-up time prior to RFO can provide more reliable actions for RCS clean-up operations and transients to operators during shutdown chemistry. Electric Power Research Institute (EPRI) shutdown calculator (SDC) enables to provide clean-up time by Co-58 peak activity through operational data from nuclear power plants (NPPs). In this study, we have investigated the results of EPRI SDC by shutdown chemistry data of Co-58 activity using NPP data from previous cycles and modeled the estimated clean-up time by EPRI SDC using average Co-58 activity of the NPP. We selected two RFO data from the NPP to evaluate EPRI SDC results using the purification time to reach to 1.3 mCi/cc of Co-58 after hydrogen peroxide addition. Comparing two RFO data, the similar purification time between actual and computed data by EPRI SDC, 0.92 and 1.74 h respectively, was observed with the deviation of 3.7-7.2%. As the modeling the estimated clean-up time, we calculated average Co-58 peak concentration for normal cycles after cycle 10 and applied two-sigma (2σ, 95.4%) for predicted Co-58 peak concentration as upper and lower values compared to the average data. For the verification of modeling, shutdown chemistry data for RFO 17 was used. Predicted RCS clean-up time with lower and upper values was between 21.05 and 27.58 h, and clean-up time for RFO 17 was 24.75 h, within the predicted time band. Therefore, our calculated modeling band was validated. This approach can be identified that the advantage of the modeling for clean-up time with SDC is that the primary prediction of shutdown chemistry plans can be performed more reliably during shutdown chemistry. This research can contribute to improving the efficiency and safety of shutdown chemistry evolution in nuclear power plants.

• Journal of Korean Society of Disaster and Security
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• v.17 no.1
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• pp.1-8
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• 2024

In Korea, mountainous areas cover 60% of the land, leading to increased factors such as concentrated heavy rainfall and typhoons, which can result in debris flow and landslide. Despite the high risk of disasters like landslides and debris flow, there has been a tendency in most regions to focus more on post-damage recovery rather than preventing damage. Therefore, in this study, precise topographic data was constructed by conducting on-site surveys and drone measurements in areas where debris flow actually occurred, to analyze the risk zones for such events. The numerical analysis program RAMMS model was utilized to perform debris flow analysis on the areas prone to debris flow, and the actual distribution of debris flow was compared and analyzed to evaluate the applicability of the model. As a result, the debris flow generation area calculated by the RAMMS model was found to be 18% larger than the actual area, and the travel distance was estimated to be 10% smaller. However, the simulated shape of debris flow generation and the path of movement calculated by the model closely resembled the actual data. In the future, we aim to conduct additional research, including model verification suitable for domestic conditions and the selection of areas for damage prediction through debris flow analysis in unmeasured watersheds.