• Title/Summary/Keyword: result from fuzzy logic

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Characteristics of Ship Movements in a Fairway

  • Kim, Eun Kyung;Jeong, Jung Sik;Park, Gyei-Kark;Im, Nam Kyun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.4
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    • pp.285-289
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    • 2012
  • In a coastal area, all of the vessels are always exposed to the potential risk, taking into the maritime accident statistics account over the last decades. To manage vessels underway safety, the characteristics of ship movements in a fairway should be recognized by VTS system or VTS operators. The IMO has already mandated the shipboard carriage of AIS since 2004, as stated in SOLAS Chapter V Regulation 19. As a result, the static and dynamic information of AIS data has been collected for vessel traffic management in the coastal areas and used for VTS. This research proposes a simple algorithm of recognizing potentially risky ships by observing their trajectories on the fairway. The static and dynamic information of AIS data are collected and the curvature for the ship trajectory is surveyed. The proposed algorithm finds out the irregularity of ship movement. The algorithm effectively monitors the change of navigation pattern from the curvature analysis of ship trajectory. Our method improves VTS functions in an intelligent way by analyzing the navigation pattern of vessels underway.

Application of Artificial Intelligence Technology for Dam-Reservoir Operation in Long-Term Solution to Flood and Drought in Upper Mun River Basin

  • Areeya Rittima;JidapaKraisangka;WudhichartSawangphol;YutthanaPhankamolsil;Allan Sriratana Tabucanon;YutthanaTalaluxmana;VarawootVudhivanich
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.30-30
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    • 2023
  • This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

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Noise Removal using Fuzzy Mask Filter (퍼지 마스크 필터를 이용한 잡음 제거)

  • Lee, Sang-Jun;Yoon, Seok-Hyun;Kim, Kwang-Baek
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.11
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    • pp.41-45
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    • 2010
  • Image processing techniques are fundamental in human vision-based image information processing. There have been widely studied areas such as image transformation, image enhancement, image restoration, and image compression. One of research subgoals in those areas is enhancing image information for the correct information retrieval. As a fundamental task for the image recognition and interpretation, image enhancement includes noise filtering techniques. Conventional filtering algorithms may have high noise removal rate but usually have difficulty in conserving boundary information. As a result, they often use additional image processing algorithms in compensation for the tradeoff of more CPU time and higher possibility of information loss. In this paper, we propose a Fuzzy Mask Filtering algorithm that has high noise removal rate but lesser problems in above-mentioned side-effects. Our algorithm firstly decides a threshold based on fuzzy logic with information from masks. Then it decides the output pixel value by that threshold. In a designed experiment that has random impulse noise and salt pepper noise, the proposed algorithm was more effective in noise removal without information loss.

Robust Pelvic Coordinate System Determination for Pose Changes in Multidetector-row Computed Tomography Images

  • Kobashi, Syoji;Fujimoto, Satoshi;Nishiyama, Takayuki;Kanzaki, Noriyuki;Fujishiro, Takaaki;Shibanuma, Nao;Kuramoto, Kei;Kurosaka, Masahiro;Hata, Yutaka
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.1
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    • pp.65-72
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    • 2010
  • For developing navigation system of total hip arthroplasty (THA) and evaluating hip joint kinematics, 3-D pose position of the femur and acetabulum in the pelvic coordinate system has been quantified. The pelvic coordinate system is determined by manually indicating pelvic landmarks in multidetector-row computed tomography (MDCT) images. It includes intra- and inter-observer variability, and may result in a variability of THA operation or diagnosis. To reduce the variability of pelvic coordinate system determination, this paper proposes an automated method in MDCT images. The proposed method determines pelvic coordinate system automatically by detecting pelvic landmarks on anterior pelvic plane (APP) from MDCT images. The method calibrates pelvic pose by using silhouette images to suppress the affect of pelvic pose change. As a result of comparing with manual determination, the proposed method determined the coordinate system with a mean displacement of $2.6\;{\pm}\;1.6$ mm and a mean angle error of $0.78\;{\pm}\;0.34$ deg on 5 THA subjects. For changes of pelvic pose position within 10 deg, standard deviation of displacement was 3.7 mm, and of pose was 1.28 deg. We confirmed the proposed method was robust for pelvic pose changes.

PC-based Hand-Geometry Verification System

  • Kim Young-Tak;Kim Soo-Jong;Lee Chang-Gyu;Kim Gwan-Hyung;Kang Sung-In;Lee Jae-Hyun;Tack Han-Ho;Lee Sang-Bae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.3
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    • pp.247-254
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    • 2006
  • Biometrics are getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry can be used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. It could also be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. This system presents verification results based on hand measurements of 20 individuals. The verification process has been tested on a size of $320{\times}240$ image, and result of the verification process have hit rate of 95% and FAR of 0.020.

A Study on 3D RTLS at Port Container Yards Using the Extended Kalman Filter

  • Kim, Joeng-Hoon;Lee, Hyun-Woo;Kwon, Soon-Ryang
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.4
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    • pp.228-235
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    • 2007
  • The main purpose of this paper is to manage the container property effectively at the container yard by applying the RTLS technology to the field of port logistics. Yet, many kinds of noises happen to be inputted with the distance value(between the reader and the tag) which is to be inputted into the location identification algorithm, which makes the distance value jumped due to the system noise of the ultrasonic sensor module and the measurement noise. The Kalman Filter is widely used to prevent this jump occurrence; the noises are eliminated by using the EKF(Extended Kalman Filter) while considering that the distance information of the ultrasonic sensor is non-linear. Also, the 3D RTLS system at the port container yard suggested in this research is designed not to be interrupted for its ultrasonic transmission by positioning the antenna at the front of each sector of the container where the active tags are installed. We positioned the readers, which function as antennas for location identification, to four places randomly in the absolute coordinate and let the positions of the active tags identified by using the distance data delivered from the active tags. For the location identification algorithm used in this paper, the triangulation measurement that is most used in general is applied and newly reorganized to calculate the position of the container. In the first experiment, we dealt with the error resulting in the angle and the distance of the ultrasonic sensor module, which is the most important in the hardware performance; in the second, we evaluated the performance of the location identification algorithm, which is the most important in the software performance, and tested the noise cancellation effects for the EKF. According to the experiment result, the ultrasonic sensor showed an average of 3 to 5cm error up to $45^{\circ}$ in case of $60^{\circ}$ or more, non-reliable linear distances were obtained. In addition, the evaluation of the algorithm performance showed an average of $4^{\circ}{\sim}5^{\circ}$ error due to the error of the linear distance-this error is negligible for most container location identifications. Lastly, the experiment results of noise cancellation and jump preservation by using the EKF showed that noises were removed in the distance information which was entered from the input of the ultrasonic sensor and as a result, only signal was extracted; thus, jumps were able to be removed and the exact distance information between the ultrasonic sensors could be obtained.