• Smart Structures and Systems
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• v.14 no.4
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• pp.617-641
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• 2014

The energy constraint is still a common issue for the practical application of wireless sensors, since they are usually powered by batteries which limit their lifetime. In this paper, a practical compound energy efficiency strategy is proposed and realized in the implementation of a real time wireless sensor platform. The platform is intended for wireless structural monitoring applications and consists of three parts, wireless sensing unit, base station and data acquisition and configuration software running in a computer within the Matlab environment. The high energy efficiency of the wireless sensor platform is achieved by a proposed adaptive radio transmission power control algorithm, and some straightforward methods, including adopting low power ICs and high efficient power management circuits, low duty cycle radio polling and switching off radio between two adjacent data packets' transmission. The adaptive transmission power control algorithm is based on the statistical average of the path loss estimations using a moving average filter. The algorithm is implemented in the wireless node and relies on the received signal strength feedback piggybacked in the ACK packet from the base station node to estimate the path loss. Therefore, it does not need any control packet overheads. Several experiments are carried out to investigate the link quality of radio channels, validate and evaluate the proposed adaptive transmission power control algorithm, including static and dynamic experiments.

• Knowledge Management Research
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• v.2 no.1
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• pp.25-44
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• 2001

There are two types of organizational knowledge in terms of its creation process: experiential and analytical knowledge. The experiential knowledge is created by repetitive experiences of an individual or team through task execution, while the analytical knowledge is acquired by analyzing accumulated data or information in the organization. The experiential knowledge often remains tacit or implicit in the organization because it is primarily acquired at an individual or team level. Therefore, the issue on the experiential knowledge is to share it actively within the organization. On the other hand, the analytical knowledge is explicit in its nature since it is extracted from data or information. Thus, it is important to guide a systematic creation of the analytical knowledge rather than encourage to share it. The current trend of "knowledge management" mainly focuses on the experiential knowledge - know-how, idea, case, etc - and neglects another important knowledge in the organization. i. e., analytical knowledge. This paper tries to shed a new light on the "knowledge management" arena by introducing rather new perspective in the concept of knowledge. The purpose of this study is to identify the factors affecting the analytical knowledge creation in the organization. We conducted an exploratory case study of three companies with a previously defined research framework and found some critical factors for the analytical knowledge creation. They are "organizational resource", "effectiveness of feedback process", "data source management", and "experimental mind set". Finally, we proposed research model and propositions regarding the analytical knowledge creation in the organization.

• Korean Journal of Computational Design and Engineering
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• v.13 no.5
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• pp.342-351
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• 2008

ISO 10303-AP241 is an Application Protocol of ISO 10303, which specifies the representation of AEC facility's life cycle information. The Working Draft of AP241 was submitted to the TC184/SC4 of ISO in July, 2007 by Korean team of ISO TC184/SC4/WG3. This paper introduces the currently developed draft Ap241 core model, and describes the life cycle support modules which are required to represent the life cycle information of AEC facilities. The draft core model is developed as a generic data model which is useful as a basis for implementation in a data warehouse. This core model could be used in combination with reference data such as PLCS RDL, Gellish table and RDL of ISO 15926. These concepts already exists in ISO 10303-AP221, AP239 and ISO 15926. In order to support maintenance and feedback of operational information concerning the AEC facilities, the AP241 team re-used many modules from AP239, and developed various STEP Application Modules which are adapted from the ISO 15926.

• Journal of Agricultural Extension & Community Development
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• v.7 no.2
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• pp.307-320
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• 2000

Agricultural extension services in Korea need to build new extension system to cope with the digital age and especially with shortage of extension educators which has been originated from the changing status from central to local government. The new trends including development of multi-media, wide-spreading of internet, and advent of internet broadcasting are offering the opportunities for new agricultural extension service. Utilization of agricultural internet broadcasting could be a new alternative for enhancing the efficiency of agricultural extension services. Agricultural internet broadcasting could support decision making of farmers by forwarding unique agricultural data which have been collected, compiled and processed by the Rural Development Administration. Farmers will be able to search useful agricultural data through agricultural internet broadcasting for more efficient farm management and marketing farm products. Agricultural internet broadcasting could utilize more prompt and abundant agricultural technology and management data compiled by the Rural Development Administration, and through this process, agricultural internet broadcasting could compensate the shortage of extension manpower. Through feedback process of agricultural internet broadcasting. farmers will be able to communicate more efficiently with extension educators to increase agricultural production and income. Agricultural Internet broadcasting could be an alternative to prevent farmers from being shunned in the information-based society.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.157-162
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• 2020

In this paper, we propose an analyze the effects of CPR education for kindergarten students, to determine their role as first responders, and to use them as basic data for the development and activation of CPR education programs for future kindergarten students. Five CPR training sessions were repeated for 10 weeks for children aged 6 and 7 years in kindergarten in J city, and objective data was collected using feedback equipment. The data were analyzed by t-test and paired t-test using SPSS 23.0 for win statistics program. The results showed that chest compression depth, chest compression velocity, and chest compression hand position increased significantly after repeated training. In conclusion, the cardiopulmonary resuscitation training for kindergarten students was effective, and the kindergarten students could play the role of first responders.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.127-134
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• 2004

In this paper, human motor behaving model based sensory motor coordination(SMC) algorithm is implemented on robotic grasping task. Compare to conventional SMC models which connect sensor to motor directly, the proposed method used biologically inspired human behaving system in conjunction with SMC algorithm for fast grasping force control of robot arm. To characterize various grasping objects, pressure sensors on hand gripper were used. Measured sensory data are simultaneously transferred to perceptual mechanism(PM) and long term memory(LTM), and then the sensory information is forwarded to the fastest channel among several information-processing flows in human motor system. In this model, two motor learning routes are proposed. One of the route uses PM and the other uses short term memory(STM) and LTM structure. Through motor learning procedure, successful information is transferred from STM to LTM. Also, LTM data are used for next moor plan as reference information. STM is designed to single layered perception neural network to generate fast motor plan and receive required data which comes from LTM. Experimental results showed that proposed method can control of the grasping force adaptable to various shapes and types of greasing objects, and also it showed quicker grasping-behavior lumining time compare to simple feedback system.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.138-145
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• 1997

Models of upward flame spread have been attempted in the past, but in the current work an emphasis has been placed on developing a practical model that will be useful across a broad range of materials. Some of the important aspects of the model we: the addition of external radiation to simulate a wall that is a part of an enclosure fire and has flaming walls radiating to it, the use of a correlation for flame heat feedback distribution to the sample surface based on data available in the literature, and the use of an experimentally measured mass loss rate for the sample material, In this paper, the development of the numerical model is presented along with predictions of flame spread for three materials: hardboard, a relatively homogeneous wood-based material; plywood, which is made of laminated wood bonded by adhesives; and a composite material made of fiberglass matrix embedded in epoxy. Predictions are compared with measured data at several levels of external radiation for each material. For the materials tested, the model correctly predicts trends and does a reasonable job predicting flame heights. The need for thermal property data for practical materials, which would be appropriate for flame spread models, is indicated by this work.

• ETRI Journal
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• v.43 no.1
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• pp.95-108
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• 2021

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3897-3908
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• 2022

High-fidelity nuclear data libraries and neutronics simulation tools are essential for the development of fast reactors. The IAEA coordinated research project on "Neutronics Benchmark of CEFR Start-Up Tests" offers valuable data for the qualification of nuclear data libraries and neutronics codes. This paper focuses on the verification and validation of the CEFR start-up modelling using OpenMC Monte-Carlo code against the experimental measurements. The OpenMC simulation results agree well with the measurements in criticality, control rod worth, sodium void reactivity, temperature reactivity, subassembly swap reactivity, and reaction distribution. In feedback coefficient evaluations, an additional state method shows high consistency with lower uncertainty. Among 122 relative errors in the benchmark of the distribution of nuclear reaction, 104 errors are less than 10% and 84 errors are less than 5%. The results demonstrate the high reliability of OpenMC for its application in fast reactor simulations. In the companion paper, the influence of cross-section libraries is investigated using neutronics modelling in this paper.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2445-2453
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• 2021

Since the nuclear data forms a vital component in reactor physics computations, the nuclear community needs processing codes as tools for translating the Evaluated Nuclear Data Files (ENDF) to simulate nuclear-related problems such as an ACE format that is used for MCNP. Errors, inaccuracies or discrepancies in library processing may lead to a calculation that disagrees with the experimentally measured benchmark. This paper provides an overview of the processing and preparation of ENDF/B-VIII.0 incident neutron data with NECP-Atlas and NJOY codes for implementation in the MCNP code. The resulting libraries are statistically inter-compared and tested by conducting benchmark calculations, as the mutualcomparison is a source of strong feedback for further improvements in processing procedures. The database of the benchmark experiments is based on a selection taken from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP handbook) and those proposed by Russell D. Mosteller. In general, there is quite good agreement between the NECP-Atlas1.2 and NJOY21^(1.0.0.json) results with no substantial differences, if the correct input parameters are used.