• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.58 no.4
• /
• pp.359-366
• /
• 2022

In this study, the load fluctuation of the main engine is considered to be a disturbance for the jacket coolant temperature control system of the low-speed two-stroke main diesel engine on the ships. A nonlinear PID temperature control system with satisfactory disturbance rejection performance was designed by rapidly transmitting the load change value to the controller for following the reference set value. The feed-forwarded load fluctuation is considered the set points of the dual loop control system to be changed. Real-coded genetic algorithms were used as an optimization tool to tune the gains for the nonlinear PID controller. ITAE was used as an evaluation function for optimization. For the evaluation function, the engine jacket coolant outlet temperature was considered. As a result of simulating the proposed cascade nonlinear PID control system, it was confirmed that the disturbance caused by the load fluctuation was eliminated with satisfactory performance and that the changed set value was followed.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.9
• /
• pp.375-384
• /
• 2021

Deep learning techniques have been proven to have high performance in image processing and are applied in various fields. The most widely used methods for validating a deep learning model include a holdout verification method, a k-fold cross verification method, and a bootstrap method. These legacy methods consider the balance of the ratio between classes in the process of dividing the data set, but do not consider the ratio of various features that exist within the same class. If these features are not considered, verification results may be biased toward some features. Therefore, we propose a deep learning model validation method based on data feature coverage for image classification by improving the legacy methods. The proposed technique proposes a data feature coverage that can be measured numerically how much the training data set for training and validation of the deep learning model and the evaluation data set reflects the features of the entire data set. In this method, the data set can be divided by ensuring coverage to include all features of the entire data set, and the evaluation result of the model can be analyzed in units of feature clusters. As a result, by providing feature cluster information for the evaluation result of the trained model, feature information of data that affects the trained model can be provided.

• Journal of Korean Institute of Industrial Engineers
• /
• v.25 no.1
• /
• pp.75-86
• /
• 1999

The improvement of automotive seating system, particularly for the driver, has been the subject of intense interest. In this study, the methods for evaluating the seating comfort are investigated. A subjective evaluation has been the general method for evaluating the seating comfort of automotive seat. Therefore, the survey using the roadside interview is conducted. In addition, the subjective evaluation with a questionnaire using the laboratory set-up is investigated. With this subjective evaluation, in order to evaluate the comfort objectively, the body pressure distribution, seat physical characteristics and eletromygram are investigated. These objective evaluation methods are compared with the subjective evaluation. As a result, the body pressure distribution, seat physical characteristics and electromyogram are recommended as the objective technique for the seating comfort evaluation.

• Proceedings of the PSK Conference
• /
• 2002.10a
• /
• pp.328.3-329
• /
• 2002

A convenient bioassay of nerve growth factor(NGF) is essential for assessing its potency during the course of product development and quality controls afterwards. We have set up a cell-based bioassay for determining the potency of recombinant NGF using rat pheochromocytoma (PC12) cells. Cell survival was measured by monitoring the reduction of the alamarBlue$^{TM}$ dye by living cells. (omitted)d)

• Journal of the Ergonomics Society of Korea
• /
• v.18 no.3
• /
• pp.105-125
• /
• 1999

As speech is the human being's most natural communication medium, using it gives many advantages. Currently, most user interfaces of a computer are using a mouse/keyboard type but the interface using speech recognition is expected to replace them or at least be used as a tool for supporting it. Despite the advantages, the speech recognition interface is not that popular because of technical difficulties such as recognition accuracy and slow response time to name a few. Nevertheless, it is important to optimize the human-computer system performance by improving the usability. This paper presents a set of guidelines for designing speech recognition interfaces and provides a method for evaluating the usability. A total of 113 guidelines are suggested to improve the usability of speech-recognition interfaces. The evaluation method consists of four major procedures: user interface evaluation; function evaluation; vocabulary estimation; and recognition speed/accuracy evaluation. Each procedure is described along with proper techniques for efficient evaluation.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.27 no.1
• /
• pp.53-73
• /
• 2002

The launch of a new business is crucial to the future growth and profitability of a company. A new business project typically requires a large amount of resources while it has a high possibility of failure. The evaluation of new business opportunities is therefore quite a critical decision-making to companies. This evaluation includes screening of a large number of criteria at a time which often makes desision-making very complicated. Management should evaluate the business alternatives in a sound and consistent manner that is hard to achieve because the new business evaluation is a typical semi/unstructured decision-making problem. The difficulty in such an evaluation will increase if it is required for management to consider both quantitative and qualitative criteria simultaneously. Under these circumstances, this study has proposed a decision-making framework that utilizes analytical hierarchy process(AHP). This study has identified a set of criteria essential to the new business evaluation and suggested a systematic framework for it. Both qualitative and quantitative evaluations are incorporated into the single framework in this study.

• Journal of Korea Multimedia Society
• /
• v.22 no.2
• /
• pp.203-209
• /
• 2019

The performance of an intelligent classifier for detecting malwares added to multimedia contents based on machine learning is highly dependent on the properties of feature set. Especially, in order to determine the malicious code in real time the size of feature set should be as short as possible without reducing the accuracy. In this paper, we introduce an optimal feature selection method to satisfy both high detection rate and the minimum length of feature set against the feature set provided by PEFeatureExtractor well known as a feature extraction tool. For the evaluation of the proposed method, we perform the experiments using Windows Portable Executables 32bits.

• Journal of Power Electronics
• /
• v.19 no.1
• /
• pp.168-178
• /
• 2019

Discrete space vector modulation (DSVM) is an effective method to improve the steady-state performance of the finite control set predictive control for permanent magnet synchronous motor drive systems. However, it requires complex computations due to the presence of numerous virtual voltage vectors. This paper proposes an improved finite control set model-free predictive control using DSVM to reduce the computational burden. First, model-free deadbeat current control is used to generate the reference voltage vector. Then, based on the principle that the voltage vector closest to the reference voltage vector minimizes the cost function, the optimal voltage vector is obtained in an effective way which avoids evaluation of the cost function. Additionally, in order to implement double-objective control, a two-level decisional cost function is designed to sequentially reduce the stator currents tracking error and the inverter switching frequency. The effectiveness of the proposed control is validated based on experimental tests.

• Structural Engineering and Mechanics
• /
• v.41 no.2
• /
• pp.243-262
• /
• 2012

Nonlinear static analysis as an essential part of performance based design is now widely used especially at design offices because of its simplicity and ability to predict seismic demands on inelastic response of buildings. Since the accuracy of nonlinear static procedures (NSP) to predict seismic demands of buildings affects directly on the entire performance based design procedure, therefore lots of research has been performed on the area of evaluation of these procedures. In this paper, one of the popular NSP, FEMA356, is evaluated and compared with modal pushover analysis. The ability of these procedures to simulate seismic demands in a set of reinforced concrete (RC) buildings is explored with two level of base acceleration through a comparison with benchmark results determined from a set of nonlinear time history analyses. According to the results of this study, the modal pushover analysis procedure estimates seismic demands of buildings like inter story drifts and hinges plastic rotations more accurate than FEMA356 procedure.

• Journal of Korea Society of Industrial Information Systems
• /
• v.2 no.2
• /
• pp.159-179
• /
• 1997

Traditionally, the evaluation and selection of suppliers have been a major purchasing function. A growing concern for just in-time purchasing, global sourcing, and long-term partnership between buyers and suppliers makes selecting a righ supplier become more critical decision making process. Consequently, a rigorous and systematic method for evaluation suppliers is a must. However, assessing the values of factors(e.g. qulaity , delivery, and service) selected for evaluating suppliers contains elements of uncertainty. Although several methods have been developed for uncertainty analysis, they may not be proper tools for evaluating suppliers under uncertainty. In this paper, a methodology using a fuzzy-set approach in combination with a multicriterion decision-making (MCDM) technique is developed to use as a tool for evaluating suppliers under uncertainty. An numerical example is presented to demonstrate the method in practice.