• Computers and Concrete
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• v.9 no.3
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• pp.215-226
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• 2012

This article employs Support Vector Machine (SVM) for determination of fracture parameters critical stress intensity factor ($K^s_{Ic}$) and the critical crack tip opening displacement ($CTOD_c$) of concrete. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ${\varepsilon}$-insensitive loss function has been adopted. The results are compared with a widely used Artificial Neural Network (ANN) model. Equations have been also developed for prediction of $K^s_{Ic}$ and $CTOD_c$. A sensitivity analysis has been also performed to investigate the importance of the input parameters. The results of this study show that the developed SVM is a robust model for determination of $K^s_{Ic}$ and $CTOD_c$ of concrete.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.201-210
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• 1996

Although FMS implementation in Korea is not yet mature, the worldwide empirical data shows the diffusion of FMS is inevitable in near future. As the reletionships between the high capital cost and the relative benefits and advantages are complex to analyse, it is rather beneficial to prepare the effective operation strategies which exploit the FMS flexibility, such as machine loading with alternative routing and dispatching rules. This paper shows the formulation applying a goal programming model for the loading problem with objectives of minimizing the production cost and maximizing the machine utilization, including constraints such as machine tool capacity and demands, etc. A realistic random FMS model is developed for illustration. Since loading and dispatching are a composite of two interdependent tasks, simulation is made to investigate the interactions between the two.

• Journal of Power Electronics
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• v.12 no.3
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• pp.477-486
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• 2012

This paper proposes a novel current control scheme for vector-controlled induction machine (IM) drives in the overmodulation (OVM) range, with which the voltage utilization of the voltage-source inverter (VSI) can be maximized. In the OVM region, the original voltage reference is modified by changing its magnitude and angle, which causes the motor current to be distorted, resulting in a deterioration of the current control performance. To meet with this situation, the harmonic components in the feedback currents should be eliminated before being input to the PI current controllers. For this, a composite observer is applied to extract the fundamental and harmonic components from the distorted currents, which gives a good performance without a delay and the effect of a fundamental frequency variation. In addition, through a detailed analysis of the response of the PI current controllers in the OVM range, the effectiveness of using the composite observer is demonstrated. Simulation and experimental results for a 3-kW induction motor drive are shown to verify the validity of the proposed method.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.37-39
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• 2007

This paper compared with field weakening operation methods for the spindle motor of machine tool in which high speed drive is required. The maximum torque field weakening algorithm ensures the full utilization of the output torque capability of the machine over 1/Wr method. From simulation, the validity of the Max_Te method is confirmed. It is verified that the Max-Te algorithm provided the improved torque capability over 1/Wr method. So, It is applicable to provide high performance control involving fast acceleration and precise speed control for the adjustable speed drive system of spindle.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.24-35
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• 2013

A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

• Proceedings of the Korean Society of Sericultural Science Conference
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• 1997.06a
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• pp.103-117
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• 1997

Decrease in the cocoon production of Japan is drastic because of low price of cocoon, scarcity of successors and so on. To tide over the difficulty, the automation system in the sericulture was discussed and some trials have been conducted by the Ministry of Agriculture, Forestry and Fisheries of Japan. The attempts are based on a low cost artificial diet which does not rely on mulberry leaves. Automatic machines developed until now are a rearing machine constituted with repeated belt conveyor, an reformation type of former rearing machine "Bombyx" and a mounting machine. Running parallel with them, utilization of 20-hydroxyecdysone extracted from a plant to the mounting was also studied to use their machines efficiently in the fields. In conclusion, 10 tons of law cocoon will come to be produced by two persons labor. At present, an automatic rearing system on low cost artificial diet has been developing for the future sericulture.

• ETRI Journal
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• v.45 no.1
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• pp.60-74
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• 2023

Integration of the machine learning (ML) technique in all-optical networks can enhance the effectiveness of resource utilization, quality of service assurances, and scalability in optical networks. All-optical multistage interconnection networks (MINs) are implicitly designed to withstand the increasing highvolume traffic demands at data centers. However, the contention resolution mechanism in MINs becomes a bottleneck in handling such data traffic. In this paper, a select list of ML algorithms replaces the traditional electronic signal processing methods used to resolve contention in MIN. The suitability of these algorithms in improving the performance of the entire network is assessed in terms of injection rate, average latency, and latency distribution. Our findings showed that the ML module is recommended for improving the performance of the network. The improved performance and traffic grooming capabilities of the module are also validated by using a hardware testbed.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.17-24
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• 2023

Given the surge in the elderly population, and increasing in dementia cases, there is a growing interest in digital therapies that facilitate steady remote treatment. However, in the cognitive assessment of digital therapies through clinical trials, the absence of log data as an essential evaluation factor is a significant issue. To address this, we propose a solution of utilizing weighted derived variables based on high-importance variables' accuracy in log data utilization as an indirect cognitive assessment factor for digital therapies. We have validated the effectiveness of this approach using machine learning techniques such as XGBoost, LGBM, and CatBoost. Thus, we suggest the use of log data as a rapid and indirect cognitive evaluation factor for digital therapy users.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.162-169
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• 2003

Excavation by TBM can be characterized by a rock-machine interaction during the cutting process on a small scale, but on a large scale the interaction between the rock mass and TBM becomes very significant. For the planning and evaluation of TBM tunnelling it needs to understand rock fracture mechanism by a cutter or cutters on a small scale, and to estimate penetration rate, advance rate and utilization on a large scale. In this study rock chipping mechanism due to cutter-penetration is analysed by numerical simulation, showing that rock chipping is mainly occurred by tensile failure. Also, through the analysis of factors that affect on TBM procedures in various assessment systems, it is determined that the key elements that should be considered in the planning and evaluation of TBM tunnelling are classified into rock properties, the geological structures and properties of rock mass, and the structural and functional specifications of the machine. The user-friendly assessment tool is developed, so that penetration rate, advance rate and TBM utilization are evaluated from various input data. The tool developed in this study can be applied to a practical TBM tunnelling by understanding TBM tunnelling procedures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.