• Journal of Platform Technology
• /
• v.9 no.3
• /
• pp.52-62
• /
• 2021

Quality control is critical at manufacturing sites and is key to predicting the risk of quality defect before manufacturing. However, the reliability of manual quality control methods is affected by human and physical limitations because manufacturing processes vary across industries. These limitations become particularly obvious in domain areas with numerous manufacturing processes, such as the manufacture of major nuclear equipment. This study proposed a novel method for predicting the risk of quality defects by using natural language processing and machine learning. In this study, production data collected over 6 years at a factory that manufactures main equipment that is installed in nuclear power plants were used. In the preprocessing stage of text data, a mapping method was applied to the word dictionary so that domain knowledge could be appropriately reflected, and a hybrid algorithm, which combined n-gram, Term Frequency-Inverse Document Frequency, and Singular Value Decomposition, was constructed for sentence vectorization. Next, in the experiment to classify the risky processes resulting in poor quality, k-fold cross-validation was applied to categorize cases from Unigram to cumulative Trigram. Furthermore, for achieving objective experimental results, Naive Bayes and Support Vector Machine were used as classification algorithms and the maximum accuracy and F1-score of 0.7685 and 0.8641, respectively, were achieved. Thus, the proposed method is effective. The performance of the proposed method were compared and with votes of field engineers, and the results revealed that the proposed method outperformed field engineers. Thus, the method can be implemented for quality control at manufacturing sites.

• The KIPS Transactions:PartD
• /
• v.11D no.6
• /
• pp.1221-1230
• /
• 2004

In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.5
• /
• pp.512-519
• /
• 2023

Noise pollution poses significant challenges to human well-being and marine ecosystems. It is primarily caused by the flow around ships and marine installations, emphasizing the need for accurate noise evaluation of flow noise to ensure environmental safety. Existing flow noise analysis methods for underwater environments typically use a hybrid method combining computational fluid dynamics and Ffowcs Williams-Hawkings acoustic analogy. However, this approach has limitations, neglecting near-field effects such as reflection, scattering, and diffraction of sound waves. In this study, an alternative using direct method flow noise analysis via the lattice Boltzmann method (LBM) is incorporated. The LBM provides a more accurate representation of the underwater structural boundaries and acoustic wave effects. Despite challenges in underwater environments due to numerical instabilities, a novel DM-TS LBM collision operator has been developed for stable implementations for hydroacoustic applications. This expands the LBM's applicability to underwater structures. Validation through flow noise analysis in pipe orifice demonstrates the feasibility of near-field analysis, with experimental comparisons confirming the method's reliability in identifying main pressure peaks from flow noise. This supports the viability of near-field flow noise analysis using the LBM.

• Korean Chemical Engineering Research
• /
• v.57 no.2
• /
• pp.198-204
• /
• 2019

For the removal of carbon dioxide from the chemical process, a chemical absorption method is typically used industrially. Development of new processes for the removal of carbon dioxide by the chemical absorption method has been developing new absorbents by using various absorbents. Thermodynamic data of the sorbent mixture in the new process design using hybrid absorbent is essential to reduce the equipment cost and operating costs of the process. In this study, densities of water+diisopropanolamine (DIPA), DIPA+MDEA(Methyldiethanolamine) binary systems and Water+DIPA+MDEA ternary system were measured over the full range of composition at temperatures from 303.15 K to 333.15 K by using an Anton Paar digital vibrating tube densimeter (DMA4500). The experimental excess volumes have been obtained from the experimental density results and have been fitted using the Redlich-Kister-Muggianu expression. The parameters obtained from the binary excess volume data were used for the correlation of ternary system with one additional ternary parameter for each isotherm. All investigated binary and ternary systems are completely miscible, because the values of excess volume are negative under the examined conditions.

• Journal of Intelligence and Information Systems
• /
• v.19 no.4
• /
• pp.55-79
• /
• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Polymer(Korea)
• /
• v.32 no.1
• /
• pp.26-30
• /
• 2008

This study was designed to investigate the effect of hybridization of synthetic/natural materials for annulus fibrosus (AF) tissue regeneration in vitro and in vivo. The synthetic/natural hybrid scaffolds were prepared using PLGA (poly (lactic-co-glycolic) acid), SIS (small intestinal submucosa) and DBP (demineralized bone particles). PLGA, PLGA/SIS(20%), PLGA/DBP(20%) and PLGA/SIS (10%)/DBP (10%) scaffold were manufactured by solvent casting/salt leaching method. Compressive strength was measured. Rabbit AF cells were isolated, cultured and seeded into experimental groups. Hydroxyproline production and DNA quantity of AP cells on each scaffold was measured at 2, 4 and 6 weeks after in vitro culture. Cell-scaffold composites were implanted subcutaneously into athymic mice. After 1,4 and 6 weeks postoperatively, specimens were taken and H&E, Safranin-O and type I collagen staining were carried out concerning formation of cartilagenous tissue. In vitro PLGA/SIS scaffold was evaluated for total collagen content (bydroryproline/DNA content) and PLGA scaffold was evaluated for compressive strength.

• Journal of the Korean Chemical Society
• /
• v.53 no.5
• /
• pp.521-529
• /
• 2009

Molecular structures of the various conformers for the 1,3-dimethoxy-p-tert-butylthiacalix[4] crown-5-ether (3) were optimized by using DFT B3LYP/6 - 31 + G(d,p) and mPW1PW91/6 - 31 + G(d,p) (hybrid HF-DF) calculation methods. We have analyzed the energy differences and structures of eight in/out orientations (cone_oo, cone_oi, pc_oo, pc_io, pc_oi, pc_ii, 13a_oo, 13a_io) of two methoxy groups in three major conformations (cone, partial-cone and 1,3-alternate). The 13a_oo (out-out orientation of the 1,3-alternate conformer) is calculated to be the most stable among eight different conformations of 3, and in accord with the experimental result. The ordering of relative stability resulted from the mPW1PW91/6 - 31 + G(d,p) calculation method is following: 13a_oo > 13a_io$\sim$pc_io$\sim$cone_oo > cone_oi$\sim$pc_oo$\sim$pc_oi > pc_ii.

• Journal of the Korea Concrete Institute
• /
• v.24 no.3
• /
• pp.305-313
• /
• 2012

Unreinforced masonry buildings represent a significant portion of the existing and historical buildings around the world. Recent earthquakes have shown the need for seismic retrofitting for these types of buildings. Various types of retrofitting materials (i.e., shotcrete, ECC and Fiber Reinforced Polymer sheets (FRPs)) for unreinforced masonry buildings (URM) have been developed. Engineers prefer to use FRPs, because these materials enhance the shear strength of the wall without expansion of wall sectional area and adding weight to the total structure. However, the complexity of the mechanical behavior of the masonry wall and the lack of experimental data from walls retrofitted by FRPs may cause problems for engineers to determine an appropriate retrofitting level. This paper investigate in-plane behavior of URM and retrofitted masonry walls using two different types of FRP materials to determine and provide information for the retrofitting effect of FRPs on masonry shear walls. Specimens were designed to idealize the wall of a low-rise apartment which was built in 1970s in Korea with no seismic reinforcements with an aspect ratio of 1. Retrofitting materials were carbon FRP and Hybrid sheets which have different elastic modulus and ultimate strain capacities. Consequently, this study evaluated the structural capacity of masonry shear walls and the retrofitting effect of an FRP sheet for in-plane behavior. Also, the results were compared to the results obtained from the evaluation method for a reinforced concrete beam retrofitted with FRPs.

• Steel and Composite Structures
• /
• v.34 no.5
• /
• pp.743-767
• /
• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.4
• /
• pp.683-688
• /
• 2018

Recently, the demand for electric energy has been increasing due to the spread of hybrid electric vehicles. In this study, to meet this demand, the ANSYS MAXWELL electromagnetic simulation system was used to compare the power generation characteristics of three types of suspension system that can generate electricity using energy harvesting technology. Next, the optimal design was determined for each model by using the commercial PIDO (Process Integration and Design Optimization) tool, PIANO (Process Integration, Automation and Optimization). We selected three design variables and constructed an approximate model based on the experimental design method through electromagnetic analysis for 18 experimental points derived from Orthogonal Arrays among the experimental design methods. Then, we determined the optimal design by applying the Evolutionary Algorithm. Finally, the optimal design results were verified by electromagnetic simulation of the optimum design result model using the same analysis conditions as those of the initial model. After comparing the power generation characteristics for the optimal structure for each linear generator model, the maximum power generation amounts in the 8pole-8slot, 12pole-12slot, and 16pole-16slot structures were 366.5W, 466.7W and 579.7W, respectively, and it was found that as the number of slots and poles increases, the power generation increases.