• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.1-13
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• 2010

It is not easy to set RED(Random Early Detection) parameter according to environment in managing Network Device. Especially, it is more difficult to set parameter in the case of maintaining the constant service rate according to the change of environment. In this paper, we hypothesize the router that has Multi-core CPU in output queue and propose AI RED(Artificial Intelligence RED), which directly induces Genetic Algorithm of Artificial Intelligence in the output queue that is appropriate to the optimization of parameter according to RED environment, which is automatically adaptive to workload. As a result, AI RED Is simpler and finer than FuRED(Fuzzy-Logic-based RED), and RED parameter that AI RED searches through simulations is more adaptive to environment than standard RED parameter, providing the effective service. Consequently, the automation of management of RED parameter can provide a manager with the enhancement of efficiency in Network management.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.238-247
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• 2023

Liquefied petroleum gas (LPG) is an attractive fuel for ships considering its current technology and economic viability. However, safety guidelines for LPG-fueled ships are still under development, and there have been no cases of applying LPG propulsion systems to small and medium-sized ships in Korea. The purpose of this study was to perform an objective risk assessment for the first marine LPG engine system and propose safe operational standards. First, hazard and operability (HAZOP) analysis was used to divide the engine system into five nodes, and 58 hazards were identified. To compensate for the subjectivity of qualitative evaluation using HAZOP analysis, fuzzy set theory was used, and additional risk factors, such as detectability and sensitivity, were included to compare the relative weights of the risk factors using a fuzzy analytical hierarchy process. As a result, among the five risk factors, those with a major impact on risk were determined to be the frequency and severity. Finally, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the risk rank more precisely by considering the weights of the risk factors. The risk level was divided into 47 groups, and the major hazard during the operation of the engine system was found through the analysis to be gas leakage during maintenance of the LPG supply line. The technique proposed can be applied to various facilities, such as LPG supply systems, and can be utilized as a standard procedure for risk assessment in developing safety standards for LPG-powered ships.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.428-433
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• 1997

This paper presents a new control strategy for the position and force control of flexible manipulators. The governing equation of motion of a two-link flexible manipulator which features piezoceramic actuators bonded on each flexible beam is derived via Hamilton's principle. The control torque of the motor to command desired position and force is determined by a sliding mode controller on the basis of the rigid-mode dynamics. In the controller formulation, the sliding mode controller with perturbation estimation(SMCPE) is adopted to determine appropriate control gains. The SMCPE is then incorporated with the fuzzy technique to mitigate inherent chattering problem while maintaining the stability of the system. A set of fuzzy parameters and control rules are obtained from a relation between estimated perturbation and actual perturbation. During the commanded motion, undesirable oscillation is actively suppressed by applying feedback control voltages to the piezoceramic actuators. These feedback voltages are also determined by the SMCPE. Consequently, accurate force and position control of a two-link flexible manipulator are achieved. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control methodology.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.144-156
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• 2023

Smart agriculture is a rapidly growing field that seeks to optimize crop yields and reduce risk through the use of advanced technology. A key challenge in this field is the need to create a comprehensive smart farm system that can effectively monitor and control the growth environment of crops, particularly when cultivating new varieties. This is where fuzzy theory comes in, enabling the collection and analysis of external environmental factors to generate a rule-based system that considers the specific needs of each crop variety. By doing so, the system can easily set the optimal growth environment, reducing trial and error and the user's risk burden. This is in contrast to existing systems where parameters need to be changed for each breed and various factors considered. Additionally, the type of house used affects the environmental control factors for crops, making it necessary to adapt the system accordingly. While developing such a framework requires a significant investment of labour and time, the benefits are numerous and can lead to increased productivity and profitability in the field of smart agriculture. We developed an AI platform for optimal control of facility houses by integrating data from mushroom crops and environmental factors, and analysing the correlation between optimal control conditions and yield. Our experiments demonstrated significant performance improvement compared to the existing system.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.506-511
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• 2006

This paper considers a method to design sliding mode observers for a class of uncertain systems using Linear Matrix Inequalities(LMI). In an LMI-based sliding mode observer design method for a class of uncertain systems the switching surface is set to be the difference between the observer and system output. In terms of LMIs, a necessary and sufficient condition is derived for the existence of a sliding-mode observer guaranteeing a stable sliding motion on the switching surface. The gain matrices of the sliding-mode observer are characterized using the solution of the LMI existence condition. The results are illustrated by an example.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.843-851
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• 2020

This study focuses on identifying and prioritizing the broader performance measures for the service supply chains by taking the case of Majan Electricity Company, Sohar, in the Sultanate of Oman. For an examination of the uniformity of ultimate objectives and the priorities therein, two strata of respondents with a total of fourteen respondents were approached for their valuable insights. Suitable structured instruments were personally administered to elicit the insightful and worthy responses. The two multi-criteria decision-making techniques, namely, the Fuzzy Analytical Hierarchy Process and the Best-Worst Method were used to reach a meaningful prioritization of the identified and refined broader performance measurement dimensions. The results show that there exists a minor gap between the two respondents' groups in terms of their prioritizations. The major finding points to the difference in terms of the topmost priorities as revealed by the two set of respondents. For one group of respondents, the customer satisfaction matters the most, whereas for the other group, it is the overall profitability that matters the most. This gap against the utopian state assists in concluding that there is a requirement to reorient the employees so as to have a shared and common understanding of the organizational priorities.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.53-64
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• 2023

Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1365-1372
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• 2018

The purpose of this study is to analyze the importance of the determinants of housing sales agency's role in the sale of apartment housing. For this purpose, a hierarchical decision model was constructed to understand the role and importance of the sales agency. The analytical variable items structured by the research model were set up through literature review, precedent research, and expert brainstorming. The questionnaire consisted of two comparisons for AHP analysis and the importance of absolute importance for fuzzy analysis. Afterwards, the work of correcting the importance was carried out. As a result of the analysis, it was found that the contractor prioritized the sale conditions and the sales agency had priority over the planning for the sale. As a result of analysis, planning of customer pre-sale counseling data, planning of client subscription and contract maximization plan, planning method of advertisement public media method were found to be the most important factors. The results of measurement of absolute importance(fuzzy) & relative importance(,AHP) showed similar tendency. Therefore, it can be seen that the timing of the model house operation is an important period in which the subscription rate depends on the role of the sales agency and the marketing strategy.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.1 s.41
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• pp.61-70
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• 2005

Shaking table tests are carried out on a single-degree-of-freedom mass that is equipped with a hybrid base isolation system. The isolator consists of a set of four specially-designed friction pendulum systems (FPS) and a magnetorheological (MR) damper. The structure and its hybrid isolation system are subjected to various intensities of near- and far-fault earthquakes on a large shake table. The proposed fuzzy controller uses feedback from displacement or acceleration transducers attached to the structure to modulate resistance of the semi-active damper to motion. Results from several types of passive and semi-active control strategies are summarized and compared. The study shows that a combination of FPS isolators and an adjustable MR damper can effectively provide robust control of vibration for a large full-scale structure undergoing a wide variety of seismic loads.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.62-72
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• 2011

Currently, The failure of construction project is increasing to be caused by a changing construction environment. According to this circumstances, Researches of project success factors affecting performance have been presented to develop strategies for efficient construction project management in the construction industry. However, Conducting efficient construction project management is difficult because project manager could not know which project success factors can be improved or not. Especially, although the project characteristics were derived the level of difficulty for performance, research of the project characteristics which could not be improved as influence factor to performance is lacking. Therefore, This paper has developed the Performance Predicting System(PPS) with Fuzzy set theory to establish. PPS has been developed to establish efficient project management strategies and to save time and effort. As Contractor inputs the project characteristics, PPS can predict the level of difficulty of performance.