• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.115-124
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• 2024

To detect and prevent structural damage caused by various loads on marine structures and ships, structural health monitoring procedure is essential. Estimating loads acting on the structures which are measured by sensors that are mounted properly are crucial for structural health monitoring. However, attaching an excessive number of sensors to the structure without consideration can be inefficient due to the high costs involved and the potential for inducing structural instability. In this study, we introduce a method to determine the optimal number of sensors and their optimized locations for strain measurement sensors, allowing for accurate load estimation throughout the structure using model expansion method. To estimate the loads exerted on the entire structure with minimal sensors, we construct a strain-load interpolation matrix using the strain mode shapes of the finite element (FE) model and select the optimal sensor locations by applying D-Optimal Design and the row exchange algorithm. Finally, we estimate the loads exerted on the entire structure using the model expansion method. To validate the proposed method, we compare the results obtained by applying the optimal sensor placement and model expansion method to an FE model subjected to arbitrary loads with the loads exerted on the entire FE model, demonstrating efficiency and accuracy.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.53-68
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• 2017

The response sensitivity method in time domain has been applied extensively for damage identification. In this paper, the relationship between the error of damage identification and the sensitivity matrix is investigated through perturbation analysis. An index is defined according to the perturbation amplify effect and an optimal sensor placement method is proposed based on the minimization of that index. A sequential sub-optimal algorithm is presented which results in consistently good location selection. Numerical simulations with a two-dimensional high truss structure are conducted to validate the proposed method. Results reveal that the damage identification using the optimal sensor placement determined by the proposed method can identify multiple damages of the structure more accurately.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.442-442
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• 2000

The intelligent auto-tuning method fur a strongly stable adaptive control system of a DC motor with great load inertia variation is proposed. The stable characteristic polynomial that is designed by an optimal servo is specified for the adaptive pole placement control system. The appropriate adaptive control system can be derived, by adjusting automatically the weight of a performance criterion in optimal control by means of the fuzzy inference on the basis of the stability index.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.9 s.90
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• pp.819-826
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• 2004

A multi-step optimum strategy for the selection of the locations and directions of strain gauges is proposed in this paper to capture at best the modal response of blade in a series of modes on fan blades. It is consist of three steps including two pass reduction step, genetic algorithm and fine optimization to find the locations-directions of strain gauges. The optimization is based upon the maximum signal-to-noise ratio(SNR) of measured strain values with respect to the inherent system measurement noise, the mispositioning of the gauge in location and gauge failure. Optimal gauge positions for a fan blade is analyzed to prove the effectiveness of the multi-step optimum methodology and to investigate the effects of the considering parameters such as the mispositioning level, the probability of gauge failure, and the number of gauges on the optimal strain gauge position.

• Journal of KIISE:Information Networking
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• v.28 no.2
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• pp.229-235
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• 2001

With the explosive popularity of the World Wide Web, the low penonnance of network often leads web clients to wait a long time for web server's response. To resolve this problem, web caching (proxy) has been considered as the most efficient technique for web server to handle this problem. The placement of web proxy is critical to the overall penonnance, and Li et al. showed the optimal placement of proxies for a web server in the internet with the linear and tree topology when the number of proxies, ]M, is given [4, 5]. They focused on minimizing the over all access time. However, it is also considerable for target web server to minimize the total number of proxies while each proxy server guarantees not to exceed certain res(Xlnse time for each request from its clients. In this paper, we consider the problem of finding the optimal number and placement of web proxies with the lin~ar and tree topology under the given threshold cost for delay time.

• Journal of Dental Anesthesia and Pain Medicine
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• v.17 no.4
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• pp.307-312
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• 2017

Background: The aim of this study was to estimate the optimal depth of nasotracheal tube placement. Methods: We enrolled 110 patients scheduled to undergo oral and maxillofacial surgery, requiring nasotracheal intubation. After intubation, the depth of tube insertion was measured. The neck circumference and distances from nares to tragus, tragus to angle of the mandible, and angle of the mandible to sternal notch were measured. To estimate optimal tube depth, correlation and regression analyses were performed using clinical and anthropometric parameters. Results: The mean tube depth was $28.9{\pm}1.3cm$ in men (n = 62), and $26.6{\pm}1.5cm$ in women (n = 48). Tube depth significantly correlated with height (r = 0.735, P < 0.001). Distances from nares to tragus, tragus to angle of the mandible, and angle of the mandible to sternal notch correlated with depth of the endotracheal tube (r = 0.363, r = 0.362, and r = 0.546, P < 0.05). The tube depth also correlated with the sum of these distances (r = 0.646, P < 0.001). We devised the following formula for estimating tube depth: $19.856+0.267{\times}sum$ of the three distances ($R^2=0.432$, P < 0.001). Conclusions: The optimal tube depth for nasotracheally intubated adult patients correlated with height and sum of the distances from nares to tragus, tragus to angle of the mandible, and angle of the mandible to sternal notch. The proposed equation would be a useful guide to determine optimal nasotracheal tube placement.

• Steel and Composite Structures
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• v.19 no.2
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• pp.349-368
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• 2015

This paper presents a new algorithm to find the optimal distribution of steel diagonal braces (SDB) using artificial bee colony optimization technique. The four different objective functions are employed based on the transfer function amplitude of; the top displacement, the top absolute acceleration, the base shear and the base moment. The stiffness parameter of SDB at each floor level is taken into account as design variables and the sum of the stiffness parameter of the SDB is accepted as an active constraint. An optimization algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed to minimize the objective functions. The proposed ABC algorithm is applied to determine the optimal SDB distribution for planar buildings in order to rehabilitate existing planar steel buildings or to design new steel buildings. Three planar building models are chosen as numerical examples to demonstrate the validity of the proposed method. The optimal SDB designs are compared with a uniform SDB design that uniformly distributes the total stiffness across the structure. The results of the analysis clearly show that each optimal SDB placement, which is determined based on different performance objectives, performs well for its own design aim.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.839-846
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• 1999

This paper presents an efficient algorithm for determining the location, size and number of capacitors in unbalanced radial distribution system. The objective function formulated consists of two terms: cost for energy loss and cost related to capacitor purchase and capacitor installation. The cost function associated with capacitor placement is considered as step function due to banks of standard discrete capacities. Genetic algorithms(GA) are used to obtain the population is derived. The strings in each population consist of the bus number index and size of capacitors to be installed. In order to determine the number of capacitor placement, the length mutation operator is used. Its efficiency is proved through the application in unbalanced radial distribution systems made of 10 buses with 9 distribution lines and 25 buses with 24 distribution lines.

• Journal of the Korea Society for Simulation
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• v.6 no.2
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• pp.89-104
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• 1997

Performance bottleneck of parallel computer systems has mostly been I/O devices because of disparity between processor speed and I/O speed. Therefore I/O node placement strategy is required such that it can minimize the number of I/O nodes, I/O access time and I/O traffic in an interconnection network. In this paper, we propose an optimal distance-k embedding algorithm, and analyze its effect on system performance when this algorithm is applied to n x n torus architecture. We prove this algorithm is an efficient I/O node placement using software simulation. I/O node placement using the proposed algorithm shows the highest performance among other I/O node placements in all cases. It is because locations of I/O nodes are uniformly distributed in the whole network, resulting in reduced traffic in the intE'rconnection network.