• Journal of Power System Engineering
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• v.14 no.4
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• pp.43-49
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• 2010

In the present study, optimization of throttle margin for high pressure turbine to be retrofitted or partially modified for power uprating or life extension in nuclear power plant, has been performed to increase the electrical output. Throttle margin for high pressure turbine is required to maintain all the time the rated power by opening more of governor valves whenever inlet pressure is decreased due to the tube plugging of steam generator. If throttle margin of high pressure turbine is too much compared to remaining lifetime, loss of electrical output due to pressure drop of governor valves is inevitable. On the contrary, if it is too little, the rated power operation can not be accomplished when inlet pressure of high pressure turbine is dropped after many years operation. So, throttle margin for high pressure turbine in nuclear power plant is compromised considering for the degradation of steam generator, governor valve capacity, manufacturing tolerance of high pressure turbine, future plan of power uprating, and remaining lifetime of power plant.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1258-1275
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• 2023

Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

• KSBB Journal
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• v.21 no.2
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• pp.79-84
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• 2006

In order to minimize the reduction of lysine productivity by accumulation of lysine and byproducts in the end of fed-batch fermentations, a salt-tolerant mutant C14-49-3-15-7-3-20, which could grow at high concentrations of NaCl was isolated through mutagenesis from the Corynebacterium glutamicum mother strain I. In the evaluation of L-lysine productivity by fed-batch fermentations using a 5 L jar fermenter, the salt-tolerant mutant strain C14-49-3-15-7-3-20 produced 130.6 g/L of L-lysine with a 48.6% of yield. The mother strain I produced L-lysine concentration only 104.9 g/L with a yield 41.8%, implying the improvement of L-lysine productivity by introduction of salt-tolerance character.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.6
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• pp.649-653
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• 2014

Although many reliability analysis and reliability-based design optimization (RBDO) methods have been developed to estimate system reliability, many studies assume the uncertainty of the design variable to be constant. In practice, because uncertainty varies with the design variable's value, this assumption results in inaccurate conclusions about the reliability of the optimum design. Therefore, uncertainty should be considered variable in RBDO. In this paper, we propose an RBDO method considering variable uncertainty. Variable uncertainty can modify uncertainty for each design point, resulting in accurate reliability estimation. Finally, a notable optimum design is obtained using the proposed method with variable uncertainty. A mathematical example and an engine cradle design are illustrated to verify the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.29-34
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• 2017

In this paper, we report a method of improving the productivity of lead wire fabricated through the rolling process by increasing its linear velocity. The most important point to consider when raising the linear velocity is that the original specifications must still be adhered to. In other words, the dimensional tolerance must be satisfied when increasing the linear velocity of the wire without causing cracks. However, if the linear velocity of the wire is increased, the degree of reduction must also be increased, which causes more damage to the wire and increases the load on its surface. Therefore, we studied a three step rolling process which can satisfy the specifications of the wire produced through the two step rolling process and improve the productivity. In this study, only the roll gap of the three-stage rolling roller is assumed to be a variable, while the other conditions are the same as the field conditions. In addition, through the PIANO (Process Integration, Design and Optimization) tool, the (optimum?) surface roughness and maximum stress are maintained.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.120-127
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• 2011

Checkpointing is one of common methods of realizing fault-tolerance for real-time systems. This paper presents a scheme to determine checkpoint intervals using probabilistic optimization. The considered real-time systems comprises multiple tasks in which transient faults can happen with a Poisson distribution. Also, multi-tasks are scheduled by the non-preemptive Rate Monotonic (RM) algorithm. In this paper, we present an optimization problem where the probability of task completion is described by checkpoint numbers. The solution to this problem is the optimal set of checkpoint numbers and intervals that maximize the probability. The probability computation includes schedulability test for the non-preemptive RM algorithm with respect to given numbers of checkpoint re-execution. A case study is given to show the applicability of the proposed scheme.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1414-1420
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• 2022

High dose rate (HDR) brachytherapy treatment planning usually involves optimization methods to deliver uniform dose to the target volume and minimize dose to the healthy tissues. Four optimizations were used to evaluate the high-risk clinical target volume (HRCTV) coverage and organ at risk (OAR). Dose-volume histogram (DVH) and dosimetric parameters were analyzed and evaluated. Better coverage was achieved with PGO (mean CI = 0.95), but there were no significant mean CI differences than GrO (p = 0.03322). Mean EQD₂ doses to HRCTV (D₉₀) were also superior for PGO with no significant mean EQD₂ doses than GrO (p = 0.9410). The mean EQD₂ doses to bladder, rectum, and sigmoid were significantly higher for NO plan than PO, GrO, and PGO. PO significantly reduced the mean EQD₂ doses to bladder, rectum, and sigmoid but compromising the conformity index to HRCTV. PGO was superior in conformity index (CI) and mean EQD₂ doses to HRCTV compared with the GrO plan but not statistically significant. The mean EQD₂ doses to the rectum by PGO plan slightly exceeded the limit from ABS recommendation (mean EQD₂ dose = 78.08 Gy EQD₂). However, PGO can shorten the treatment planning process without compromising the CI and keeping the OARs dose below the tolerance limit.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1305-1308
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• 2003

A new technique is presented to construct a predictive model of plasma etch process. This was accomplished by combining a backpropagation neural network (BPNN) and a genetic algorithm (GA). The predictive model constructed in this way is referred to as a GA-BPNN. The GA played a role of controlling training factors simultaneously. The training factors to be optimized are the hidden neuron, training tolerance, initial weight magnitude, and two gradients of bipolar sigmoid and linear functions. Each etch response was optimized separately. The proposed scheme was evaluated with a set of experimental plasma etch data. The etch process was characterized by a $2^3$ full factorial experiment. The etch responses modeled are aluminum (A1) etch rate, silica profile angle, A1 selectivity, and dc bias. Additional test data were prepared to evaluate model appropriateness. The GA-BPNN was compared to a conventional BPNN. Compared to the BPNN, the GA-BPNN demonstrated an improvement of more than 20% for all etch responses. The improvement was significant in the case of A1 etch rate.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.5 no.2
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• pp.36-41
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• 2006

This study was carried out to install the lifting force of a two hinge type stand mechanism by 6 Sigma process in advance. This unit is designed for the display device in order to enhance the ergonomics for effective height adjustment and maintenance at any preferred position. The unit will be very useful for the mechanism fabricated with coil springs and disc springs as a torque generator. The 6 Sigma process was applied to select two key factors among 7 elements to lift the head unit and to find out applicable tolerance securing the 3.4 ppm of defects as well as what deviation of lifting force we can expect between calculation and experiment at the design stage of development. The result of this study can be applied to various units for the optimization of the smooth lift.