• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.333-342
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• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• The Journal of Bigdata
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• v.7 no.1
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• pp.75-87
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• 2022

This study investigates a dynamic flexible flow shop scheduling problem under uncertain rework operations for an automobile pipe production line. We propose a weighted dispatching rule (WDR) based on the multiple dispatching rules to minimize the weighted sum of average flowtime and tardiness. The set of weights in WDR should be carefully determined because it significantly affects the performance measures. We build a discrete-event simulation model and propose a genetic algorithm to optimize the set of weights considering complex and variant operations. The simulation experiments demonstrate that WDR outperforms the baseline dispatching rules in average flowtime and tardiness.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.187-194
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• 2011

Optimizing truck dispatching-intervals is imperative in ready mixed concrete (RMC) delivery process. Intervals shorter than optimal may induce queuing of idle trucks at a construction site, resulting in a long delivery cycle time. On the other hand, intervals longer than optimal can trigger work discontinuity due to a lack of available trucks where required. Therefore, the RMC delivery process should be systematically scheduled in order to minimize the occurrence of waiting trucks as well as guarantee work continuity. However, it is challenging to find optimal intervals, particularly in urban areas, due to variations in both traffic conditions and concrete placement rates at the site. Truck dispatching intervals are usually determined based on the concrete plant managers' intuitive judgments, without sufficient and reliable information regarding traffic and site conditions. Accordingly, the RMC delivery process often experiences inefficiency and/or work discontinuity. Automatic data collection (ADC) techniques (e.g., RFID or GPS) can be effective tools to assist plant managers in finding optimal dispatching intervals, thereby enhancing delivery performance. However, quantitative evidence of the extent of performance improvement has rarely been reported to data, and this is a central reason for a general reluctance within the industry to embrace these techniques, despite their potential benefits. To address this issue, this research reports on the development of a discrete event simulation model and its application to a large-scale building project in Abu Dhabi. The simulation results indicate that ADC techniques can reduce the truck idle time at site by 57% and also enhance the pouring continuity in the RMC delivery process.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.158-168
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• 2024

There is hardly any person in modern times who has not taken soft drinks instead of drinking water. The rate of people taking soft drinks being surprisingly high, researchers around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases and so on. Therefore, in this work an image-based tool is developed to monitor the nutritional information of soft drinks by using deep convolutional neural network with transfer learning. At first, visual saliency, mean shift segmentation, thresholding and noise reduction technique, collectively known as 'pre-processing' are adopted to extract the location of drinks region. After removing backgrounds and segment out only the desired area from image, we impose Discrete Wavelength Transform (DWT) based resolution enhancement technique is applied to improve the quality of image. After that, transfer learning model is employed for the classification of drinks. Finally, nutrition value of each drink is estimated using Bag-of-Feature (BoF) based classification and Euclidean distance-based ratio calculation technique. To achieve this, a dataset is built with ten most consumed soft drinks in Bangladesh. These images were collected from imageNet dataset as well as internet and proposed method confirms that it has the ability to detect and recognize different types of drinks with an accuracy of 98.51%.

• Journal of Hydrogen and New Energy
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• v.35 no.3
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• pp.345-351
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• 2024

The unitized regenerative fuel cell (URFC) is a method that can reduce costs and increase system simplification by unitizing a fuel cell system and a water electrolysis system. The spray method is suitable as the membrane electrode assembly (MEA) manufacturing method for URFC because it is easy to control the amount of catalyst, the size of the system is small, and economical manufacturing is possible. In this study, a numerical analysis of the effect of solution concentration on the spray method was performed to use it as basic data for the spray method to be used in MEA manufacturing. As result, as the Nafion solution concentration decreases it was found that the spray speed and the mass flow rate and the discrete phase model concentration increases and the spray range widens.

• Structural Engineering and Mechanics
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• v.89 no.2
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• pp.181-197
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• 2024

A numerical method is presented in this paper, for buckling analysis of thin arbitrary stiffened composite cylindrical shells under axial compression. The stiffeners can be placed inside and outside of the shell. The shell and stiffeners are operated as discrete elements, and their interactions are taking place through the compatibility conditions along their intersecting lines. The governing equations of motion are obtained based on Koiter's theory and solved by utilizing the principle of the minimum potential energy. Then, the buckling load coefficient and the critical buckling load are computed by solving characteristic equations. In this formulation, the elastic and geometric stiffness matrices of a single curved strip of the shell and stiffeners can be located anywhere within the shell element and in any direction are provided. Moreover, five stiffened composite shell specimens are made and tested under axial compression loading. The reliability of the presented method is validated by comparing its numerical results with those of commercial software, experiments, and other published numerical results. In addition, by using the ANSYS code, a 3-D finite element model that takes the exact geometric arrangement and the properties of the stiffeners and the shell into consideration is built. Finally, the effects of Poisson's ratio, shell length-to-radius ratio, shell thickness, cross-sectional area, angle, eccentricity, torsional stiffness, numbers and geometric configuration of stiffeners on the buckling of stiffened composite shells with various end conditions are computed. The results gained can be used as a meaningful benchmark for researchers to validate their analytical and numerical methods.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1153-1164
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• 2024

In recent years, unmanned ground vehicles (UGVs) have been used to search for lost or stolen radioactive sources to avoid radiation exposure for operators. To achieve autonomous localization of radioactive sources, the UGVs must have the ability to automatically determine the next radiation measurement location instead of following a predefined path. Also, the radiation field of radioactive sources has to be reconstructed or inverted utilizing discrete measurements to obtain the radiation intensity distribution in the area of interest. In this study, we propose an effective source localization framework and method, in which UGVs are able to autonomously explore in the radiation area to determine the location of radioactive sources through an iterative process: path planning, radiation field reconstruction and estimation of source location. In the search process, the next radiation measurement point of the UGVs is fully predicted by the design path planning algorithm. After obtaining the measurement points and their radiation measurements, the radiation field of radioactive sources is reconstructed by the Gaussian process regression (GPR) model based on machine learning method. Based on the reconstructed radiation field, the locations of radioactive sources can be determined by the peak analysis method. The proposed method is verified through extensive simulation experiments, and the real source localization experiment on a Cs-137 point source shows that the proposed method can accurately locate the radioactive source with an error of approximately 0.30 m. The experimental results reveal the important practicality of our proposed method for source autonomous localization tasks.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.5
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• pp.289-296
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• 2024

Recently, with the acceleration of global warming, the importance of carbon neutrality is being emphonasized. In response to this, various technologies are being developed to achieve carbon neutrality, with Carbon Capture, Utilization, and Storage (CCUS) being a prominent example. Research has been conducted on the injection technology to environmentally discharge carbon captured by using one of the carbon capture technologies, HAK-CRS. In this study, numerical simulations were performed using commercial software, ANSYS Fluent, to understand the dispersed multiphase flow between a water jet and CaCO₃ particles. The analysis focused on the differences in particle behavior when injecting CaCO₃ with different flow rates. It was observed that as the mass flow rate of CaCO₃ increased, there was a tendency for the particles to deviate from the flow of the jet and rapidly fall, influenced significantly by gravity. These results indicate that, for CaCO₃ particles to disperse widely, the flow rate should not be excessively high. Given the potential adverse impacts on marine ecosystems due to the high density of CaCO₃, research on injection technology should also be conducted.

• Journal of Korean Society of Steel Construction
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• v.24 no.3
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• pp.289-299
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• 2012

The goal of this paper is to apply the multi-step Taylor method to a space truss, a non-linear discrete dynamic system, and analyze the non-linear dynamic response and unstable behavior of the structures. The accurate solution based on an analytical approach is needed to deal with the inverse problem, or the dynamic instability of a space truss, because the governing equation has geometrical non-linearity. Therefore, the governing motion equations of the space truss were formulated by considering non-linearity, where an accurate analytical solution could be obtained using the Taylor method. To verify the accuracy of the applied method, an SDOF model was adopted, and the analysis using the Taylor method was compared with the result of the 4th order Runge-Kutta method. Moreover, the dynamic instability and buckling characteristics of the adopted model under step excitation was investigated. The result of the comparison between the two methods of analysis was well matched, and the investigation shows that the dynamic response and the attractors in the phase space can also delineate dynamic snapping under step excitation, and damping affects the displacement of the truss. The analysis shows that dynamic buckling occurs at approximately 77% and 83% of the static buckling in the undamped and damped systems, respectively.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.50-60
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• 2018

Recently, modular construction method has been widely applied to projects with repetitive processes including dormitory, the residential facility, and the hotel construction due to reduced labor input and shortened construction schedule. Generally, about 40% of total on-site construction cost excluding unit installation cost, is put on exterior finishing work, and thus management of finishing work is deemed important in maintaining the targeted schedule and cost. Since limited equipment is shared so that subsequent activities are not affected while carrying out on-site installation and finishing work, lifting plan becomes more important for modular projects with greater portion of finishing work load. In this regard, tower crane operation plan may take the form of a single cycle or multiple cycles in which equipment efficiency can be affected. However, difficulties exist in evaluating alternatives to tower crane operation plans supporting unit installation and finishing work. Therefore, this study aims to evaluate the alternative of tower crane operation method according to the cyclic period setting in modular building site to determine the effect on T/C uptime and process by parameterizing lifting time for unit and exterior finishing material, lift cycle for unit and exterior finishing material and time required for finishing work. Accordingly, this study develops a simulation model that can increase the tower crane efficiency by controlling the work speed. An academic contribution of this study is to suggest a resource leveling method applying the concept of lifting cycle, and further is expected to be managerially used as a basis for an alternative evaluation of equipment plan.