• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.227-232
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• 2004

Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed supplies good results in normal conditions. But the estimation error in severe braking is discontented In this paper, we estimate the absolute vehicle speed of UCT(Unmanned Container Transporter) by using the wheel speed data from standard anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used 10 algorithms are verified experimentally to estimate the absolute vehicle speed and one of them is perfectly shown to estimate the vehicle speed within 4％ error during a braking maneuver.

• Atmosphere
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• v.33 no.5
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• pp.519-530
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• 2023

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACI_YrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACI_NoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACI_YrOpt were higher than those of ACI_NoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.801-825
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• 2024

For Internet of Things, it is more preferred to have immediate access to environment information from sensor nodes (SNs) rather than from gateway nodes (GWNs). To fulfill the goal, mutual authentication scheme between user and SNs with session key (SK) negotiation is more suitable. However, this is a challenging task due to the constrained power, computation, communication and storage resources of SNs. Though lots of authentication schemes with SK negotiation have been designed to deal with it, they are still insufficiently secure and/or efficient, and some even have serious vulnerabilities. Therefore, we design an efficient secure authentication scheme with session key negotiation (eSAS2KN) for wireless sensor networks (WSNs) utilizing fuzzy extractor technique, hash function and bitwise exclusive-or lightweight operations. In the eSAS2KN, user and SNs are mutually authenticated with anonymity, and an SK is negotiated for their direct and instant communications subsequently. To prove the security of eSAS2KN, we give detailed informal security analysis, carry out logical verification by applying BAN logic, present formal security proof by employing Real-Or-Random (ROR) model, and implement formal security verification by using AVISPA tool. Finally, computation and communication costs comparison show the eSAS2kN is more efficient and secure for practical application.

• Smart Structures and Systems
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• v.19 no.4
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• pp.341-350
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• 2017

Based on the super elastic properties of the shape memory alloy (SMA) and the inverse piezoelectric effect of piezoelectric (PZT) ceramics, a kind of hybrid semi-active control device was designed and made, its mechanical properties test was done under different frequency and different voltage. The local search ability of genetic algorithm is poor, which would fall into the defect of prematurity easily. A kind of adaptive immune memory cloning algorithm(AIMCA) was proposed based on the simulation of clone selection and immune memory process. It can adjust the mutation probability and clone scale adaptively through the way of introducing memory cell and antibody incentive degrees. And performance indicator based on the modal controllable degree was taken as antigen-antibody affinity function, the optimization analysis of damper layout in a space truss structure was done. The structural seismic response was analyzed by applying the neural network prediction model and T-S fuzzy logic. Results show that SMA and PZT friction composite damper has a good energy dissipation capacity and stable performance, the bigger voltage, the better energy dissipation ability. Compared with genetic algorithm, the adaptive immune memory clone algorithm overcomes the problem of prematurity effectively. Besides, it has stronger global searching ability, better population diversity and faster convergence speed, makes the damper has a better arrangement position in structural dampers optimization leading to the better damping effect.

• The Journal of Industrial Distribution & Business
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• v.5 no.4
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• pp.31-42
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• 2014

Purpose - According to the applied studies knowledge, management implementation can improve organizational performance. The main objective of this study is to develop an understanding of critical success factors that enhance the successful implementation of knowledge management. Research design, data, and methodology - This study used Analytical Hierarchy Procedure (AHP), which is a multi-criteria decision making model that works on fuzzy logic. Using this method, researchers can find the proportion of success due to the contribution of the critical success factors (CSFs). Results - The results show that more than 70% of respondents indicate the possibility of success in knowledge management implementation. Further, the results show that top management support has the greatest relationship with the success of knowledge management implementation. This was followed by information technology, performance measurement, and culture, which had a high relation with knowledge management success. Process and activities have a moderate positive relation, while education and training has a low relation with success. Because of an inappropriate p-value, knowledge management strategies show no relation to the success of knowledge management in the Iranian health Industry. Conclusions - This study was conducted because of a critical issue in the Iranian health industry that indicated that a significant portion of the workforce would retire in 5 to 10 years. Most highly experienced and knowledge oriented employees would become eligible for retirement. Therefore, knowledge management is presented as a complete solution in the Iranian health sector.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.2
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• pp.71-83
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.137-155
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• 1996

본 논문은 다이아몬드 인터체인지에서의 유고감지모형 개발을 위해 퍼지이론을 응용한 연구를 문서화 한 것이다. 지금까지의 교차로와 일반도로(고속도로가 아닌)에서의 유고감지에 관한 연구는 초기에 불과하다. 기존의 알고리즘들은 필요한 데이터 보존의 어 려움과 유고감지의 특성과 관련된 기술적 어려움을 효과적으로 극복하지 못하고 있다. 본 연구의 목적은 다이아몬드 인터체인지에서의 유고감지를 위한 새로운 모형을 개발하는데 있다. 이 연구를 통하여 개발된 유고감지 모형은 차량차단 유고(lane-blocking incidents) 를 감지하는데, 감지의 범위는 차량차단 유고의 경향이 교통 장황에 특정한 패턴을 형성 하고 그에 따른 신호제어전략의 조정이 요구될 때에 국한된다. 이 모형은 전통적인 통계 치를 이용한 유고감지감 고유의 문제를 해결하며, 보다 정확하고 신뢰성 있는 유고감지를 위해 다양한 교통변수를 이용하여 전체적인 유고의 경향을 포착한다. 또한 이 모형은 실 시간 교통대응 다이아몬드 인터체인지 신호제어 시스템 (real-time traffic adaptive diamond interchange control system)의 구성요소로써 사용되며, 그리고 더 큰 교차로 시스템에의 상용을 위하여 확장이 용역하도록 설계되었다. 본 연구를 통해 개발된 프로 토타입(prototype) 유고감지 모형은 실제의 다이아몬드 인터체인지에 적용되어, 감지율, 오보율, 평감지시간의 세 달로써 성능이 평가되었다. 모형의 성능평가 결과는 무적이었으 며, 퍼지이론은 유고감지에 효과적인 접근방법임을 확인할 수 있었다.투자의 타당성을 실증적으로 보여 주고 있다.산정 절차 정립에 엇갈림 알고리즘을 활용하는 방안을 제시하였다.자함수를 추정한 뒤 이를 이용해 업종, 기업규모, 상품유형별로 적합한 모델(Fixed Effects Model)을 결정하고, 각각에 해당하는 통계모형을 구축하였다. 이 결과 (1) 업종 및 기업규모별로 그룹간에 유의한 특성이 발견되었으며, (2) R&D 및 광고투자는 기업의 시장성과를 설명하는 중요한 변수이나, (3) R&D 투자의 경우는 광고에 비해 불확실성이 존재하는 것으로 나타났고, (4) 수리모형에서 도출된 한계원리가 통계모형에서도 유효한 것으로 드러났다.등을 토대로 한 10대 산업을 육성하기 위하여 과학기술부는 기술수요조사를 바탕으로 49개 주요기술을 도출하여, 과학기술 일류 국가 실현, 국민소득 2만불 달성이라는 국가적 슬로건을 내걸고 “차세대 성장동력” 창출을 위한 범정부차원의 기획과 연구비의 집중투자를 추진하고 있다.달성하기 위해서는 종합류류 전산망의 시급한 구축과 함께 화물차의 적재율을 높이고 공차율을 낮출 수 있는 운송체계의 수립이 필요한 것으로 판단된다. 그라나 이러한 화물전용차선의 효과는 단기적인 치유책일 수밖에 없기 때문에 물류유통 시설의 확충을 위한 사회간접자본의 구축을 서둘러 시행하여야 할 것이다.으로 처리한 Machine oil, Phenthoate EC 및 Trichlorfon WP는 비교적 약효가 낮았다.>$^{\circ}$E/$\leq$30$^{\circ}$NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한