• Korean Parent-Child Health Journal
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• v.13 no.2
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• pp.63-77
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• 2010

Purpose: The purpose of this study was to develop child's health assessment tools and tailored home visiting nursing service model in a community. Methods: Based on the literature review and several types of workshops participated with the child health nursing professors and visiting nurses in public health centers from May to December 2009, the standards of child health assessment tools, service model and education materials for visiting nurses were developed. Results: Some record forms were newly developed, including neonatal assessment, breast feeding, mother-infant interaction, oral care, vaccination and safety, and appropriate developmental screening tests in the community were selected. For systematic health care management in the community, problem list, problem criteria, health care plan, outcome criteria were also developed. Conclusion: On the demand of growing need for health promotion and early intervention for children and their association with parenting and socioeconomic status, assessment and control measures are indispensable to the promotion of child health for vulnerable population. Children's health and developmental problems, and safe circumstances can be assessed using this assessment tools, and can be used for tailored home visiting nursing care for children.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.7
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• pp.78-86
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• 2010

This paper discusses the programming model of SODA-II that is a baseband processor for software defined radio (SDR) systems. Signal processing On-Demand Architecture Ⅱ (SODA-II) is an on-chip multiprocessor architecture consisting of four processor cores and each core has both an wide SIMD datapath and a scalar datapath. This architecture is appropriate for baseband processing that is a mixture of vector computations and scalar computations. The programming model of the SODA-II is based on C library routines. Because the library routines hide the details of complex SIMD datapath control procedures, end users can easily program the SODA-II without deep understanding on its architecture. In this paper, we discuss the details of library routines and how these routines are exploited in the implementation of baseband signal processing algorithms. As application examples, we show the implementation result of W-CDMA multipath searcher and OFDM demodulator on the SODA-II.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.81-90
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• 2008

While increasing demand of the service for the disabled and the elderly people, assistive technologies have been developed rapidly. The natural signal of human such as voice or gesture has been applied to the system for assisting the disabled and the elderly people. As an example of such kind of human robot interface, the Soft Remote Control System has been developed by HWRS-ERC in $KAIST^[1]$. This system is a vision-based hand gesture recognition system for controlling home appliances such as television, lamp and curtain. One of the most important technologies of the system is the hand gesture recognition algorithm. The frequently occurred problems which lower the recognition rate of hand gesture are inter-person variation and intra-person variation. Intra-person variation can be handled by inducing fuzzy concept. In this paper, we propose multivariate fuzzy decision tree(MFDT) learning and classification algorithm for hand motion recognition. To recognize hand gesture of a new user, the most proper recognition model among several well trained models is selected using model selection algorithm and incrementally adapted to the user's hand gesture. For the general performance of MFDT as a classifier, we show classification rate using the benchmark data of the UCI repository. For the performance of hand gesture recognition, we tested using hand gesture data which is collected from 10 people for 15 days. The experimental results show that the classification and user adaptation performance of proposed algorithm is better than general fuzzy decision tree.

• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.41-53
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• 2001

Multi-distributed web cluster model built for high availability E-Business model exposes internal system nodes on its structural characteristics and has a potential that normal job performance is impossible due to the intentional prevention and attack by an illegal third party. Therefore, the security system which protects the structured system nodes and can correspond to the outflow of information from illegal users and unfair service requirements effectively is needed. Therefore the suggested distributed invasion detection system is the technology which detects the illegal requirement or resource access of system node distributed on open network through organic control between SC-Agents based on the shared memory of SC-Server. Distributed invasion detection system performs the examination of job requirement packet using Detection Agent primarily for detecting illegal invasion, observes the job process through monitoring agent when job is progressed and then judges the invasion through close cooperative works with other system nodes when there is access or demand of resource not permitted.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.153-160
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• 2020

Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's predictive models of energy consumption. The data used includes lagging and leading reactive power lagging and leading current variable, emission of carbon dioxide (tCO2) and load type. Four statistical models are trained and tested in the test set: (a) Linear Regression (LR), (b) Radial Kernel Support Vector Machine (SVM RBF), (c) Gradient Boosting Machine (GBM), and (d) Random Forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used for calculating regression model predictive performance. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Advances in Computational Design
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• v.8 no.1
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• pp.13-36
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• 2023

The Puebla-Morelos Earthquake (Mw 7.1) occurred in Mexico in 2017 causing 44 buildings to collapse in Mexico City. This work evaluates the non-linear response of a 6-story reinforced concrete (RC) frame prototype model with masonry infill walls on upper floors. The prototype model was designed using provisions prescribed before 1985 and was subjected to seismic excitations recorded during the earthquakes of 1985 and 2017 in different places in Mexico City. The building response was assessed through a damage index (DI) that considers low-cycle fatigue of the steel reinforcement in columns of the first floor, where the steel was modeled including buckling as was observed in cases after the 2017 earthquake. Isocurves were generated with 72 seismic records in Mexico City representing the level of iso-demand on the structure. These isocurves were compared with the location of 16 collapsed (first-floor column failure) building cases consistent with the prototype model. The isocurves for a value greater than 1 demarcate the location where fatigue failure was expected, which is consistent with the location of 2 of the 16 cases studied. However, a slight increase in axial load (5%) or decrease in column cross-section (5%) had a significant detrimental effect on the cumulated damage, increasing the intensity of the isocurves and achieving congruence with 9 of the 16 cases, and having the other 7 cases less than 2 km away. Including column special detailing (tight stirrup spacing and confined concrete) was the variable with the greatest impact to control the cumulated damage, which was consistent with the absence of severe damage in buildings built in the 70s and 80s.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.101-110
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• 2012

Recently, social network sites are very popular with the enhancement of mobile device function and distribution. This gives rise to the registrations of the people on the social network sites and the usage of services on the social sites is also getting active. However, social network sites' venders do not provide services enough compared to the demand of users' to share contents from diverse roots by users effectively. In addition, the personal information can be revealed improperly in processes sharing policies and it is obvious that it raises a privacy invasion problem when users access the contents created from diverse devices according to the relationship by policies. However, the existing methods for the integration management of social network are weak to solve this problem. Thus, we propose a model to preserve user privacy, categorize contents efficiently, and give the access control permissions at the same time. In this paper, we encrypt policies and the trusted third party classifies the encrypted policies when the social network sites share the generated contents by users. In addition, the proposed model uses the RCBAC model to manage the contents generated by various devices and measures the similarity between relationships after encrypting when the user policies are shared. So, this paper can contribute to preserve user policies and contents from malicious attackers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.672-678
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• 2020

The parallel-feeding operation of an AC traction power supply system has the advantages of extending the power supply section and increasing the power supply capacity by reducing the voltage drop and peak demand caused by a train operation load. On the other hand, the parallel-feeding operation is restricted because of the circulating power flow induced from the phase difference between substations. Moreover, the power supply capacity is limited because of the unbalanced substation load depending on the trainload distribution, which can be changed by the train operation along the railway track. This paper suggests a Thyristor-controlled Phase Angle Regulator (TCPAR) to reduce the circulating power flow and the unbalanced substation load, which depends on the phase difference and the trainload distribution and provides a feasibility study. A dedicated control model of TCPAR is also provided, which uses substation power supplies as the input to control the circulating power flow and an unbalanced substation load depending on the phase difference and the trainload distribution. Simulation studies using PSCAD/EMTDC shows that the proposed TCPAR control model can reduce the circulating power flow and the unbalanced substation load depending on the phase difference and the trainload distribution. The proposed TCPAR can extend the parallel-feeding operation of an AC traction power system and increase the power supply capacity.

• Molecules and Cells
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• v.38 no.9
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• pp.743-749
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• 2015

Production of genome-edited animals using germline-competent cells and genetic modification tools has provided opportunities for investigation of biological mechanisms in various organisms. The recently reported programmed genome editing technology that can induce gene modification at a target locus in an efficient and precise manner facilitates establishment of animal models. In this regard, the demand for genome-edited avian species, which are some of the most suitable model animals due to their unique embryonic development, has also increased. Furthermore, germline chimera production through longterm culture of chicken primordial germ cells (PGCs) has facilitated research on production of genome-edited chickens. Thus, use of avian germline modification is promising for development of novel avian models for research of disease control and various biological mechanisms. Here, we discuss recent progress in genome modification technology in avian species and its applications and future strategies.