• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.304-313
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• 2006

This paper describes a novel way of applying capacitive sensing technology to a mobile user interface. The key idea is to use grip-pattern, which is naturally produced when a user tries to use the mobile device, as a clue to determine an application to be launched. To this end, a capacitive touch sensing system is carefully designed and installed underneath the housing of the mobile device to capture the information of the user's grip-pattern. The captured data is then recognized by dedicated recognition algorithms. The feasibility of the proposed user interface system is thoroughly evaluated with various recognition tests.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.102-110
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• 2015

The main source of noise in computed tomography (CT) images is a quantum noise, which results from statistical fluctuations of X-ray quanta reaching the detector. This paper proposes a neural network (NN) based hybrid filter for removing quantum noise. The proposed filter consists of bilateral filters (BFs), a single or multiple neural edge enhancer(s) (NEE), and a neural filter (NF) to combine them. The BFs take into account the difference in value from the neighbors, to preserve edges while smoothing. The NEE is used to clearly enhance the desired edges from noisy images. The NF acts like a fusion operator, and attempts to construct an enhanced output image. Several measurements are used to evaluate the image quality, like the root mean square error (RMSE), the improvement in signal to noise ratio (ISNR), the standard deviation ratio (MSR), and the contrast to noise ratio (CNR). Also, the modulation transfer function (MTF) is used as a means of determining how well the edge structure is preserved. In terms of all those measurements and means, the proposed filter shows better performance than the guided filter, and the nonlocal means (NLM) filter. In addition, there is no severe restriction to select the number of inputs for the fusion operator differently from the neuro-fuzzy system. Therefore, without concerning too much about the filter selection for fusion, one could apply the proposed hybrid filter to various images with different modalities, once the corresponding noise characteristics are explored.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.28-36
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• 2020

As many types of magnetic sensors are widely applied in various industries, the analysis and processing of magnetic sensor data need to be accurate. On the other hand, owing to the complexity of the magnetic field line caused by a moving magnet, the magnetic data generated by magnetic sensors are unpredictably nonlinear. Many industry systems using magnetic sensors have struggled with the nonlinear nature of magnetic sensor data. To reduce the effect of the nonlinearity, they have the target objects fixed firmly. Therefore, to collect accurate and reliable data, considerable efforts have been made to resolve the issues with the expensive tools and systems required. Through this paper, to tackle the issues, the data analysis and methodologies, including intelligent algorithms, are presented for the wrist rehabilitation system using magnetic sensors while being implemented without using expensive tools or systems. On processing magnetic sensor data, this paper adopted an intelligent algorithm, fuzzy logic, and compared the performance of other algorithms for comparison.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.6
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• pp.52-62
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• 1999

This paper presents a system which recognizes dynamic hand gestures on-line for controlling motion of numan avatar in virtual environment(VF). A dynamic hand gesture is a method of communication between a computer and a human being who uses gestures, especially both hands and fingers. A human avatar consists of 32 degree of freedom(DOF) for natural motion in VE and navigates by 8 pre-defined dynamic hand gestures. Inverse kinematics and dynamic kinematics are applied for real-time motion control of human avatar. In this paper, we apply a fuzzy min-max neural network and feature analysis method using fuzzy logic for on-line dynamic hand gesture recognition.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.149-155
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• 2009

Attacks in wireless sensor networks (WSN), are similar to the attacks in ad-hoc networks because there are deployed on a wireless environment. However existing security mechanism cannot apply to WSN, because it has limited resource and hostile environment. One of the typical attack in WSN is setting up wrong route that using wormhole. To overcome this threat, Ji-Hoon Yun et al. proposed WODEM (WOrmhole attack DEfense Mechanism) which can detect and counter with wormhole. In this scheme, it can detect and counter with wormhole attacks by comparing hop count and initial TTL (Time To Live) which is pre-defined. The selection of a initial TTL is important since it can provide a tradeoff between detection ability ratio and energy consumption. In this paper, we proposed a fuzzy rule-based system for TTL determination that can conserve energy, while it provides sufficient detection ratio in wormhole attack.

• Steel and Composite Structures
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• v.48 no.2
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• pp.179-190
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• 2023

Many recent attempts have sought accurate prediction of pile pullout resistance (P_ul) using classical machine learning models. This study offers an improved methodology for this objective. Adaptive neuro-fuzzy inference system (ANFIS), as a popular predictor, is trained by a capable metaheuristic strategy, namely equilibrium optimizer (EO) to predict the P_ul. The used data is collected from laboratory investigations in previous literature. First, two optimal configurations of EO-ANFIS are selected after sensitivity analysis. They are next evaluated and compared with classical ANFIS and two neural-based models using well-accepted accuracy indicators. The results of all five models were in good agreement with laboratory P_uls (all correlations > 0.99). However, it was shown that both EO-ANFISs not only outperform neural benchmarks but also enjoy a higher accuracy compared to the classical version. Therefore, utilizing the EO is recommended for optimizing this predictive tool. Furthermore, a comparison between the selected EO-ANFISs, where one employs a larger population, revealed that the model with the population size of 75 is more efficient than 300. In this relation, root mean square error and the optimization time for the EO-ANFIS (75) were 19.6272 and 1715.8 seconds, respectively, while these values were 23.4038 and 9298.7 seconds for EO-ANFIS (300).

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.472-477
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• 2003

멸종위기종의 서식지를 효율적으로 관리하기 위해서는 해당 종의 서식 가능한 지역의 분포를 알아야 한다. 본 연구의 목적은 GIS와 퍼지집합을 이용하여 산양(Nemorhaedus caudatus)의 서식지적합성모형을 개발하여 멸종 위기종의 서식지를 관리하기 위한 정보를 제공하는 것이다. 산양의 서식지적합성모형 개발을 위한 본 연구의 주요내용은 다음과 같다. 첫째, 산양 서식지 이용에 관한 기존 연구를 바탕으로 산양의 잠재적 서식지 환경변수를 분류하였으며, 분석 대상지의 산양 흔적 조사를 통해 서식지 환경변수의 재분류 및 x²검정(Chi-square test)을 통한 변수들의 유용성을 파악하고, 쌍체비교를 통한 환경변수별 가중치를 계산하였다. 둘째, 기존 부울논리(boolean logic)의 단점을 보완하기 위해 현장 조사의 결과를 바탕으로 퍼지논리(fuzzy logic)에 의한 산양 서식지의 각 환경변수별 주제도를 작성하고, 주제도들의 상관관계를 분석하여 상호 관련성이 높은 변수들의 중복을 피하였다. 셋째, 환경변수별 주제도와 변수별 가중치를 바탕으로 다기준평가기법(MCE, Multi-Criteria Evaluation)을 이용하여 분석대상지의 산양 서식지적합성모형을 개발하였다. 마지막으로, 개발된 서식지적합성모형의 타당성을 검증하기 위해 분석대상지 외부 지역을 대상으로 검증을 실시하였다. 분석 결과 분석대상지의 분류정확도는 서식가능성 0.5를 기준으로 93.94%의 매우 높은 분류정확도를 나타내었으며, 검증대상지에서는 95.74%의 분류정확도를 나타내어 본 모형의 분류정확도는 일관성이 높은 것으로 판단되었다. 또한 전체 공원구역에서 서식가능성 0.5이상의 면적은 59%를 차지하였다.퇴적이 우세한 것으로 관측되었다.보체계의 구축사업의 시각이 행정정보화, 생활정보화, 산업정보화 등 다양한 분야와 결합하여 보다 큰 시너지 효과와 사용자 중심의 서비스 개선을 창출할 수 있는 기반을 제공할 것을 기대해 본다.. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. O

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.774-779
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• 2020

The seismic response reduction capacity of a smart mid-story isolation system was investigated using the RNN model in this study. For this purpose, an RNN model was developed to make a dynamic response prediction of building structures subjected to seismic loads. An existing tall building with a mid-story isolation system was selected as an example structure for realistic research. A smart mid-story isolation system was comprised of an MR damper instead of existing lead dampers. The RNN model predicted the seismic responses accurately compared to those of the FEM model. The simulation time of the RNN model can be reduced significantly compared to the FEM model. After the numerical simulations, the smart mid-story isolation system could effectively reduce the seismic responses of the existing building compared to the conventional mid-story isolation system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.