• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.27-37
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• 1991

In this paper, the novel PLD (Preceding Layer Driven) MLP (Multi Layer Perceptron) neural network model and its learning algorithm is described. This learning algorithm is different from the conventional. This integer weights and hard limit function are used for synaptic weight values and activation function, respectively. The entire learning process is performed by layer-by-layer method. the number of layers can be varied with difficulty of training data. Since the synaptic weight values are integers, the synapse circuit can be easily implemented with CMOS. PLD MLP neural network was applied to English Characters, arbitrary waveform generation and spiral problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.34-42
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• 2013

In this study, we develop a method for analyzing business process based on the event-driven process chain (EPC) model. The method consists of five stages such as identifying abnormal events, finding causes for the abnormal events and problems caused by the abnormal events, making cause-and-effect chains, drawing root-cause map, and defining improvement areas. We illustrate how to apply the method with some examples for the domestic registered mail delivery process.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.8
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• pp.351-357
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• 2005

This paper presents vibration minimization of a PMLSM driven feed-slide by using optimized smooth velocity curve with finite jerk. First of all, the PMLSM was designed and made to reduce detent force. Next, a PMLSM driven feed-slide system was mathematically modeled as a 4-degree-of-freedom lumped parameter model. The key idea of our vibration minimization method is to find out the most appropriate smooth velocity(feedrate) curve with finite jerk. The validity of our proposed method has been verified by comparing computer simulation results of the feed-slide model with experimental ones.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.630-642
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• 2015

In Jøsang's subjective logic, the fusion operator is not able to fuse three or more opinions at a time and it cannot consider the effect of time factors on fusion. Also, the base rate (a) and non-informative prior weight (C) could not change dynamically. In this paper, we propose an Improved Subjective Logic Model with Evidence Driven (ISLM-ED) that expands and enriches the subjective logic theory. It includes the multi-agent unified fusion operator and the dynamic function for the base rate (a) and the non-informative prior weight (C) through the changes in evidence. The multi-agent unified fusion operator not only meets the commutative and associative law but is also consistent with the researchers's cognitive rules. A strict mathematical proof was given by this paper. Finally, through the simulation experiments, the results show that the ISLM-ED is more reasonable and effective and that it can be better adapted to the changing environment.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.317-320
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• 2015

Documenting work-in-progress on construction sites using images captured with smartphones, point-and-shoot cameras, and Unmanned Aerial Vehicles (UAVs) has gained significant popularity among practitioners. The spatial and temporal density of these large-scale site image collections and the availability of 4D Building Information Models (BIM) provide a unique opportunity to develop BIM-driven visual analytics that can quickly and easily detect and visualize construction progress deviations. Building on these emerging sources of information this paper presents a pipeline for model-driven visual analytics of construction progress. It particularly focuses on the following key steps: 1) capturing, transferring, and storing images; 2) BIM-driven analytics to identify performance deviations, and 3) visualizations that enable root-cause assessments on performance deviations. The information requirements, and the challenges and opportunities for improvements in data collection, plan preparations, progress deviation analysis particularly under limited visibility, and transforming identified deviations into performance metrics to enable root-cause assessments are discussed using several real world case studies.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.6 s.249
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• pp.553-559
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• 2006

Most diesel injector, which is currently used in high-pressure common rail fuel injection system of diesel engine, is driven by the solenoid coil energy for its needle movement. The main disadvantage of this solenoid-driven injector is a high power consumption, high power loss through solenoid coil and relatively fixed needle response's problem. In this study, a prototype piezo-driven injector, as a new injector mechanism driven by piezoelectric energy based on the concept of inverse piezo-electric effect, has been designed and fabricated to know the effect of piezo-driven injection processes on the diesel spray structure and internal nozzle flow. Firstly we investigated the spray characteristics in a constant volume chamber pressurized by nitrogen gas using the back diffusion light illumination method for high-speed temporal photography and also analyzed the inside nozzle flow by a fully transient simulation with cavitation model using VOF(volume of fraction) method. The numerical calculation has been performed to simulate the cavitating flow of 3-dimensional real size single hole nozzle along the injection duration. Results were compared between a conventional solenoid-driven injector and piezo-driven injector, both equipped with the same micro-sac multi-hole injection nozzle. The experimental results show that the piezo-driven injector has short injection delay and a faster spray development and produces higher injection velocity than the solenoid-driven injector. And the predicted simulation results with the degree of cavitation's generation inside nozzle for faster needle response In a piezo-driven injector were reflected to spray development in agreement with the experimental spray images.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.5
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• pp.359-369
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• 2024

Data-driven model for estimating fuel oil consumption in seaways is suggested using the model test results and operation data. The data-driven model requires the forecasted wind speed, direction, and the desired ship speed as inputs to predict the engine speed, power, and fuel oil consumption. The structure of the data-driven model is based on the deterministic model of added power of a similar vessel of which model test results in the calm water and head seas are accessible. For a given wind speed, the wind resistance and added resistance in irregular waves presented by Pierson-Moskowitz spectrum are computed to be applied to the propulsion performance prediction. The deterministic model takes a cubic approximation between the wind speed and engine speed. The model is tuned by actual operation data in seaways with various wind direction groups. The shaft power and fuel oil consumption estimation are added to the model to be validated with the operation data. The prediction model is validated with the operation data to confirm that the estimation of the engine speed is the most significant uncertainty source.

• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.5
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• pp.207-214
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• 2004

This paper presents the characteristics of transient and effective impulse impedances for deeply driven grounding electrodes used in soil with high resistivity or in downtown areas. The laboratory test associated with the time domain performance of grounding piles subjected to a lightning stroke current has been carried out using an actual-sized model grounding system. The ground impedances of the deeply driven ground rods and grounding pile under impulse currents showed inductive characteristics, and the effective impulse ground impedance owing to the inductive component is higher than the power frequency ground impedance. Both power frequency ground impedance and effective impulse ground impedance decrease upon increasing the length of the model grounding electrodes. Furthermore, the effective impulse ground impedances of the deeply driven grounding electrodes are significantly amplified in impulse currents with a rapid rise time. The reduction of the power frequency ground impedance is decisive to improve the impulse impedance characteristics of grounding systems.

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.784-794
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• 2020

In order to effectively evaluate the urban water security, the study investigates a novel system to assess factors that impact urban water security and builds an urban water poverty evaluation index system. Based on the contribution rates of Resource, Access, Capacity, Use, and Environment, the study adopts the Water Poverty Index (WPI) model to evaluate the water poverty levels of 14 cities in Gansu during 2011-2018 and uses the least variance method to evaluate water poverty space drive types. The case study results show that the water poverty space drive types of 14 cites fall into four categories. The first category is the dual factor dominant type driven by environment and resources, which includes Lanzhou, Qingyang, Jiuquan, and Jiayuguan. The second category is the three-factor dominant type driven by Access, Use, and Capability, which includes Longnan, Linxia, and Gannan. The third category is the four-factor dominant type driven by Resource, Access, Capability, and Environment, which includes Jinchang, Pingliang, Wuwei, Baiyin, and Zhangye. The fourth category is the five-factor dominant type, which includes Tianshui and Dingxi. The driven types impacting the urban water security factors reflected by the WPI and its model are clear and accurate. The divisions of the urban water security level supply a reliable theoretical and numerical basis for an urban water security early warning mechanism.