Journal of Intelligent & Fuzzy Systems - Volume 36, issue 2

Authors: Chen, Yao-Mei | Ho, Wen-Hsien | Chen, Yenming J. | Chen, Kuan-Shan | Liu, Wei-Hsiu

Article Type: Research Article

Abstract: This paper aims to develop a realistic triage system to better quantify a patient’s disease severity for the evaluation of admission or discharging. A good triage can reduce loads of doctors and draw attention of staffs to critical conditions. However, existing systems score on readings of vital signs and the superficial scores usually are apart from doctors’ judgement. Instead of summing up rating score, we take a Bayesian network approach to estimate the source diseases that lead to the observed vital signs, such as temperature, lactate, HCT, and CRP, etc. Because the purpose of this assessment is not making a …correct diagnosis, the source diseases are only stratified to four disease categories. Based on the reading of vital signs, Bayes belief network inferences the probability distributions of the severity for each one of the four disease categories. Finally, the four distributions are then sufficient to rank a patient’s final severity by a probabilistic decision framework. Diffing from traditional paper based evaluation, our method is required to use computer to perform the computation. Our triage results closely match doctors’ judgement. Sensitivity and specificity are improved significantly, comparing to traditional APACH II systems. Absolute and relative assessment gains were calculated and proved to be practical. Show more

Keywords: Bayesian belief network, admission triage, assessment gain, disease severity score

DOI: 10.3233/JIFS-169880

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1049-1055, 2019

Authors: Jeong, Sang-Ki | Choi, Hyeung-Sik | Kang, Jin-Il | Oh, Ji-Youn | Kim, Seo-Kang | Minh Nhat, Thieu Quang

Article Type: Research Article

Abstract: The underwater glider (UG) is an underwater exploration equipment that propels itself with very low power consumption by converting the vertical motion into a horizontal motion using a buoyancy control device and a wing. To enhance gliding performance of the UG, a hybrid underwater glider (HUG) has been developed to compensate for the disadvantages of slow speed and horizontal movement and limited navigation accuracy of the UG by attaching propellant to the UG [15 ]. In this paper, the structure, control system and control algorithm of the HUG are presented. Also, for the developed HUG, motion performance of the …HUG is simulated by computer. To realize precise navigation of the developed HUG, an attitude reference system (ARS) composed of a ring laser gyroscope(RLG) and a geomagnetic sensor is developed with the Extended Kalman Filter (EKF) algorithm. To control the HUG, the six degrees of freedom equations of the HUG with the hydrodynamic force coefficient were studied. A control algorithm based on the neural network was proposed to reduce tracking error of the HUG. To validate the proposed control algorithm, a computer simulation using Matlab / Simulink was performed [13 ]. Show more

Keywords: Hybrid underwater glider, ARS (Attitude Reference System), underwater navigation, neural network self- tuning -PID, neural network - PID parallel controller

DOI: 10.3233/JIFS-169881

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1057-1072, 2019

Authors: Li, Jun-Jun | Xu, Bo-Wei | Wu, Hua-Feng

Article Type: Research Article

Abstract: Immersed tube tunnel serves as a preferred method of construction in large underwater tunnel engineering. In this work, modified quantum particle swarm optimization for translation control of immersed tunnel element with pontoons is studied aiming at its specific configuration. The translation control model is built based on the resistances of immersed tunnel element and two floating pontoons. To expand the search space, particles are coded according to Bloch coordinates. To make full use of three positions in each particle, they are selected with certain probabilities in accordance with the corresponding fitness values. Main dimension change and phase shift are implemented …to improve the efficiency of velocity update for particles. Simulation results of Hong Kong-Zhuhai-Macao Bridge project delivers performance improvement of the proposed method. Show more

Keywords: Immersed tunnel element with pontoons, translation control, quantum particle swarm optimization, Bloch coordinates of qubits

DOI: 10.3233/JIFS-169882

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1073-1081, 2019

Authors: Wong, Ching-Chang | Feng, Hsuan-Ming | Lai, Yu-Cheng | Yu, Chia-Jun

Article Type: Research Article

Abstract: A visual servo control system combines with the model-based image segmentation and an Ant Colony Optimization (ACO) algorithm to design an excellent six-Degree-of-Freedom (6-DOF) robot manipulator for solving the complicated combinations of pick-and-place tasks. A simple but efficient vision-based segmentation methodology is developed to extract the object information by getting appropriate feature of the controlled platform when the robot is tracking the manipulated image patterns. The evolutionary ACO learning algorithm explores the near-optimal path selections to drive the 6 ROF robot arm kinematics model for completing the Pick-and-Place tasks as soon as possible. Inverse orientation kinematic machine is proposed to …successfully guide the robot manipulator into the desired position. Several software simulations include image segmentations, the shortest path selection, and the performance validation in various experiments. These results are described and presented to demonstrate that the designed image model-based robot manipulator wins the excellent Pick-and-Place task. Not only the software simulation, the practical robot synchronously performed in real-world to reach the higher feasible functions in the eye-to-hand experiments. Show more

Keywords: Robot manipulator, pick-and-place task, Ant Colony Optimization, image segmentation, eye-to-hand

DOI: 10.3233/JIFS-169883

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1083-1098, 2019

Authors: Zhao, Jing | Lin, Chih-Min

Article Type: Research Article

Abstract:  This paper aims to propose a more efficient algorithm for the multi-dimensional classifier design. A novel model of wavelet fuzzy brain emotional learning neural network (WFBELNN) is proposed. This model comprises a wavelet function, a fuzzy inference system and a brain emotional learning neural network. As a result, the learning speed and the classifying accuracy can be effectively improved by the proposed model. The structure of WFBELNN is constructed first, and then the gradient-descent method is used to online tune the parameters of WFBELNN. Finally a medical pattern recognition system is studied to verify that the accurate multi-dimensional pattern recognition …can be achieved by using the proposed model. A comparison between the proposed WFBELNN and other models shows that the proposed model can achieve the most accurate classification of the medical pattern recognition and it is also more suitable to deal with the influence of the uncertainties. Show more

Keywords: Classifier, wavelet function, emotional neural network, sensory neural network, fuzzy system

DOI: 10.3233/JIFS-169884

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1099-1107, 2019

Authors: Pan, Nan | Kan, Lifeng | Liu, Yi | Fu, Wei | Hou, Zhanwei | Li, Gang | Qian, Junbin | Fu, Xiaodong

Article Type: Research Article

Abstract: There are lots of line traces on the surface of the broken ends which left in the cable cutting case crime scene along the high-speed railway in China. The line traces usually present nonlinear morphological features and has strong randomness. It is not very effective when using existing image-processing and three-dimensional scanning methods to do the trace comparison, therefore, a fast algorithm based on wavelet domain feature aiming at the nonlinear line traces is put forward to make fast trace analysis and infer the criminal tools. The proposed algorithm first applies wavelet decomposition to the 1-D signals which picked up …by single point laser displacement sensor to partially reduce noises. After that, the dynamic time warping is employed to do trace feature similarity matching. Finally, using linear regression machine learning algorithm based on gradient descent method to do constant iteration. The experiment results of cutting line traces sample data comparison demonstrate the accuracy and reliability of the proposed algorithm. Show more

Keywords: Signal detection, wavelet transforms, lasers, machine learning

DOI: 10.3233/JIFS-169885

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1109-1120, 2019

Authors: Chen, Yung-Yao | Hsia, Chih-Hsien | Lu, Chiao-Wen

Article Type: Research Article

Abstract: Multiple exposure fusion (MEF) is attracting considerable attention in research on high dynamic range (HDR) imaging: Eliminating the need to generate an intermediate HDR image, MEF directly expands an image’s dynamic range and thus provides greater detail enhancement than traditional HDR techniques. However, in the fusion stage, the optimal weights of each pixel in the images input to the final synthesized image are challenging to determine and usually required manual tuning of parameters. In addition, many MEF algorithms have been proposed, but most have lacked a self-regulation mechanism. To tackle the above disadvantages, we apply fuzzy theory and present a …novel MEF framework with a fuzzy feedback structure. In this work, over- and under-exposed images are generated from a single input image using local histogram stretching. This avoids the creation of ghost artifacts when multiple exposed images are fused in the dynamic scene containing object motion. In the fusion stage, fuzzy logic is used to determine pixel weights based on gradient and chrominance analysis, and a guided image filter is used to suppress noise and enhance edges in the weight maps. To ensure detail enhancement without excessive or insufficient sharpness, we developed a simple sharpness measure named the edge-map overlapping rate (EOR). With EOR and the feedback structure, users are allowed to manipulate the output synthesized image to their preferred sharpness level, and the above weights are appropriately redesigned by automatically regulating the magnitude of the fuzzy input. From experimental results, this work demonstrated excellent image quality and outperformed other existing HDR/MEF methods. Show more

Keywords: Fuzzy logic, fuzzy feedback, high dynamic range (HDR), multiple exposure fusion (MEF)

DOI: 10.3233/JIFS-169886

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1121-1132, 2019

Authors: Lin, Ting-Lan | Chuang, Chien-Hui | Chen, Shih-Lun | Lin, Nung-Hsiang | Miaou, Shaou-Gang | Lin, Szu-Yin | Chen, Chiung-An | Liu, Hui-Wen | Villaverde, Jocelyn Flores

Article Type: Research Article

Abstract:  For dentists, it is very important to determine the color of the denture. Shade selection in dental practice is an important and difficult task. In the dental shade matching process, the shade selection will be affected by the observer’s physiological conditions such as age, mood, fatigue, and so on. These will make a difference on the judgement between the matching shade and the actual teeth color. In the past, dentists use shade tabs as a reference basis to match the teeth in the intra-oral environment. In this paper, an efficient color analysis methodology based on image processing and fuzzy decision …techniques is proposed for dental shade matching. Since the color information is a very important index for the shade matching, the proposed methodology used the chrominance values Cb and Cr to increase the accuracy of color analysis. In order to improve the performance of the proposed methodology, three formulas, such as PSNR value of Cb, PSNR value of Cr, and S-CIELAB value, were selected by a fuzzy decision model. As shown in the results, the proposed efficient methodology based on fuzzy decision techniques improved at least 1.92 % in average accuracy and 0.59 in average score from the PSNR (Cb) and PSNR (Cr) in this work. In addition, the average values of the accuracies and scores in this work are 92.31% and 98.74, respectively, which are much better than the previous studies. To summarized, this work is the first study that applied fuzzy decision with the PSNR (Cb), PSNR (Cr) and S-CLIELAB information for dental shade matching. The results showed that the proposed methodology performs better than the previous work and other methods. Show more

Keywords: Dental shade matching, fuzzy decision, chrominance, Cb, Cr, PSNR (Peak Signal-to-Noise Ratio), S-CLIELAB

DOI: 10.3233/JIFS-169887

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1133-1142, 2019

Authors: Jian, Liu | Zequn, Jin | Rui, Zhang | Meiju, Liu | Enyang, Gao

Article Type: Research Article

Abstract: One difficulty that remains in image processing is the accurate location of key points in depth images. This paper presents an intelligent location method for identifying key points in depth images based on deep convolutional neural networks. This study used Kinect to process images, calculating the differences in depth as well as the directional gradient in subject depth images. The entirety of each depth image was traversed through a sliding window to identify the feature vector. Principal component analysis was used to reduce image dimensions. The random forest technique was used to select characteristics of strong classification as well as …to actualize training and testing. A depth convolutional neural network was used to detect key points in images of pedestrians. During the study, an experimental test was conducted in a general environment under various conditions, including occlusion and low light. Even under these suboptimal conditions, the detection rate of the proposed method was 87.72%. Furthermore, this method was compared with the GEBCF and FCF algorithms, and proved to increase the detection rate by 0.92% and 0.68%, respectively. Using the depth convolutional neural network in the pedestrian key point positioning experiment, the average error obtained when comparing the predicted point coordinates to the sample mark coordinates was 2.102 pixels. These experimental results show that this method has good accuracy and robustness for the key point location problem of pedestrians in depth images. Show more

Keywords: Pedestrian detection, depth image, key point location, deep learning

DOI: 10.3233/JIFS-169888

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1143-1151, 2019

Authors: Lai, Qinghui | Yu, Qingxu | Dong, Jiayu

Article Type: Research Article

Abstract: Rotary tiller gearbox bears alternate and complex dynamic load. To provide accurate load for its design, use UG software to establish 3D parametric modeling of main parts. Import 3D parametric modeling of blade and shaft into EDEM software. Use Bonding model to establish simulation model of soil particles. Through numerical simulation of the impact load from blade and soil, the dynamic load parameters of blade and shaft are derived. Obtain the model of gearbox housing in ANSYS software and import it into ADAMS software as flexible body. Based on the dynamic load parameters of blade and the model of gearbox …housing, multi-body dynamical rigid-flexible coupling simulation analysis for rotary tiller is done with ADAMS software. ADAMS software solves the model by adopting Lagrange dynamics equation, rigidity integral algorithm and sparse matrix technology, through which the load model of gearbox is derived. Finally, import the load model into ANSYS software, and make stress and strain analysis on the rotary tiller gearbox, by applying the load same as recorded in load file, to find out design defects and weakness of rotary tiller gearbox, which provide references for the design of rotary tiller gearbox, and help to optimize the design. Show more

Keywords: Rotary tiller gearbox, EDEM, ADAMS, ANSYS, rigid-flexible coupling

DOI: 10.3233/JIFS-169889

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1153-1160, 2019