• Journal of Korea Port Economic Association
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• v.35 no.1
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• pp.97-116
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• 2019

National industrial complexes, airports, and seaports are major logistics nodes and the availability of their logistics services is a key factor for the successful operation of entire supply chains. For this reason, the central government has established a plan for their development and is investing in development projects. However, some difficulties exist in project prioritization and investment plan creation owing to the absence of a clear appraising method. For a smooth flow of national logistics and efficient investment on facilities, it is necessary to diagnose the logistics facilities' present conditions and practice sustainable management. In this study, a diagnostic method for logistics services, which consists of service factors and facility factors, is proposed. Adopting the method, facility factors can be prioritized to improve facilities' services; further, a standard procedure is proposed to support decision making for effective investments in logistics facilities. The method is applied to actual logistics facilities (three national industrial complexes, three seaports, and two airports) and the results indicate that it can be effectively applied to actual logistics facilities.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.665-682
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• 2005

The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1415-1425
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• 2016

This paper presents a new approach for fault diagnosis in three-level neutral point clamped inverters. The proposed method is based on the average values of the positive and negative parts of normalized output currents. This method is capable of detecting and locating multiple open-circuit faults in the controlled power switches of converters in half of a fundamental period of those currents. The implementation of this diagnostic approach only requires two output currents of the inverter. Therefore, no additional sensors are needed other than the ones already used by the control system of a drive based on this type of converter. Moreover, through the normalization of currents, the diagnosis is independent of the load level of the converter. The performance and effectiveness of the proposed diagnostic technique are validated by experimental results obtained under steady-state and transient conditions.

• Communications for Statistical Applications and Methods
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• v.20 no.3
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• pp.217-223
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• 2013

Two influence diagnostic methods for the common mean model are proposed. First, an investigation of the influence of observations according to minor perturbations of the common mean model is made by adapting the local influence method which is based on the likelihood displacement. It is well known that the maximum likelihood estimates are in general sensitive to influential observations. Case-deletions can be a candidate for detecting influential observations. However, the maximum likelihood estimators are iteratively computed and therefore case-deletions involve an enormous amount of computations. An approximation by Newton's method to the maximum likelihood estimator obtained after a single observation was deleted can reduce much of computational burden, which will be treated in this work. A numerical example is given for illustration and it shows that the proposed diagnostic methods can be useful tools.

• The KSFM Journal of Fluid Machinery
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• v.12 no.2
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• pp.31-38
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• 2009

The valve performance has been evaluated from the theoretical equation based on design information such as packing thrust, spring preload and friction coefficient(${\mu}$). The accuracy of those data can be lower than that of vendor's initial design data. Especially, the friction coefficient can be degraded with time than the original condition and the valve performance calculated using the previous friction coefficient can not be available. Accordingly, this paper is describing a new performance evaluation method of valve based on diagnostic test data which are acquired from a site valve tested in static and dynamic conditions. Especially, this paper provides a new method using friction coefficient(${\mu}$) which is derived from the diagnostic test data acquired in the valve's design basis condition.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1154-1159
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• 2006

In this paper, time-frequency analysis and multi-dimensional spectral analysis methods are applied to source identification and diagnostic of non-stationary sound vibration signals. By checking the coherences for concerned time, this simulation is very well coincident to expected results. The proposed method analyzes the signal instantaneously in both time and frequency domains. The MDSA (Multiple Dimensional Spectral Analysis) analyzes the signal in the plane of instantaneous time and instantaneous frequency at the same time. And it was verified by using the 1500cc passenger car which is accelerated from 70Hz to 95Hz in 4 seconds, the proposed method is effective in determining the vehicle diagnostic problems.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2133-2150
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• 2021

In this work, Esfahan light water subcritical reactor (ELWSCR) is analysed using experimental and theoretical diagnostic methods. Important neutronic parameters of the system such as prompt neutron lifetime, delayed neutron fraction, prompt neutron decay constant, negative reactivity of the core, fuel and moderator temperature coefficient of reactivity, and overall and local void coefficient of reactivity are estimated. Also, neutron flux distribution, reflector saving, water level effect, and lattice pitch of the core including operating point of the facility are studied in details. Theoretical results are calculated by MCNPX and measurements are performed utilizing zero power reactor noise method. Detailed descriptions of the results are explained in the text.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.1
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• pp.23-30
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• 2018

Kudoa septempunctata, a myxosporean parasite that infects olive flounder Paralichthys olivaceus is known to cause Kudoa food poisoning. Entire trunk muscle (ETM) is used for diagnosis of the parasite in fish and this method demands sacrifice of the host, causing a loss of commercial value. We developed a non-destructive method that uses a plastic syringe-style implanter to draw the sample, called the part-point muscle (PPM) sampling technique. We validated the PPM method in fish infected with K. septempunctata at the level detectable by the ETM method. We confirmed that the PPM method is equally sensitive in comparison to the ETM method for diagnosing K. septempunctata spores in olive flounder muscle. Our study also confirmed that the parasite is uniformly distributed in the dorsal muscle of infected fish. Over a period of 1 month, we observed no mortality of the host fish used for sampling by the PPM method. Thus, our studies demonstrate that the PPM sampling technique is an efficient, non-destructive method for diagnosing K. septempunctata in olive flounder.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.229-239
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• 2007

We present a diagnostic method for the quasi-likelihood estimators in generalized linear models. Since these estimators can be usually obtained by iteratively reweighted least squares which are well known to be very sensitive to unusual data, a diagnostic step is indispensable to analysis of data. We extend the local influence approach based on the maximum likelihood function to that on the quasi-likelihood function. Under several perturbation schemes local influence diagnostics are derived. An illustrative example is given and we compare the results provided by local influence and deletion.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.253-260
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• 2014

The intraclass correlation model has a long history of applications in several fields of research. Case deletion diagnostic methods for the intraclass correlation model are proposed. Based on the likelihood equations, we derive a formula for a case deletion diagnostic method which enables us to investigate the influence of observations on the maximum likelihood estimates of the model parameters. Using the Taylor series expansion we develop an approximation to the likelihood distance. Numerical examples are provided for illustration.