Journal of Intelligent & Fuzzy Systems - Volume 41, issue 1

Authors: Sha, Gang | Wu, Junsheng | Yu, Bin

Article Type: Research Article

Abstract: With the development of computer technology, more and more deep learning algorithms are widely used in medical image processing. Viewing CT images is a very usual and important way in diagnosing spinal fracture diseases, but correctly reading CT images and effectively segmenting spinal lesions or not is deeply depended on doctors’ clinical experiences. In this paper, we present a method of combining U-net, dense blocks and dilated convolution to segment lesions objectively, so as to give a help in diagnosing spinal diseases and provide a reference clinically. First, we preprocess and augment CT images of spinal lesions. Second, we present …the DenseU-net network model consists of dense blocks and U-net to raise the depth of training network. Third, we introduce dilated convolution into DenseU-net to construct proposed DDU-net(Dilated Dense U-net), in order to raise receptive field of CT images for getting more lesions information. The experiments show that DDU-net has a good segmentation performance of spinal lesions, which can build a solid foundation for both doctors and patients. Show more

Keywords: Deep learning, Segmentation, Dense U-net, DDU-net(Dilated Dense U-net)

DOI: 10.3233/JIFS-211063

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2291-2304, 2021

Authors: Wu, Xiu-Yun | Liao, Chun-Yan | Zhao, Yan-Hui

Article Type: Research Article

Abstract: In this paper, the notion of (L , M )- fuzzy convex derived hull spaces is introduced. It is proved that the category of (L , M )- fuzzy convex derived hull spaces is isomorphic to the category of (L , M )- fuzzy convex spaces and the category of (L , M )- fuzzy convex enclosed relation spaces. Based on this, the notion of (L , M )- fuzzy restricted convex derived hull spaces is introduced. It is further proved that the category of (L , M )- fuzzy restricted convex derived hull spaces is isomorphic to the category …of (L , M )- fuzzy restricted convex hull spaces. Show more

Keywords: (L, M)- fuzzy convex space, (L, M)- fuzzy convex enclosed relation space, (L, M)- fuzzy convex derived hull space, (L, M)- fuzzy restricted convex hull space

DOI: 10.3233/JIFS-211115

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2305-2317, 2021

Authors: Dündar, Erdinç | Ulusu, Uğur

Article Type: Research Article

Abstract: The authors of the present paper, firstly, investigated relations between the notions of rough convergence and classical convergence, and studied on some properties of the rough convergence notion which the set of rough limit points and rough cluster points of a sequence of functions defined on amenable semigroups. Then, they examined the dependence of r -limit LIMr f of a fixed function f  ∈ G on varying parameter r .

Keywords: Rough convergence, rough limit point, rough cluster point, Folner sequence, amenable semigroups

DOI: 10.3233/JIFS-211167

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2319-2324, 2021

Authors: Khan, Majid | Haj Ismail, Abd Al Karim | Ishaque, Iqra | Hussain, Iqtadar

Article Type: Research Article

Abstract: Substitution boxes (S-boxes) are among the most widely recognized and fundamental component of most modern block ciphers. This is on the grounds that they can give a cipher fortifying properties to oppose known and possible cryptanalytic assaults. We have suggested a novel tool to select nonlinear confusion component. This nonlinear confusion component added confusion capability which describes to make the connection among the key and the cipher as complex and engaging as possible. The confusion can be obtained by using substitution box (S-box) and complex scrambling algorithm that relies on key and the input (plaintext). Various statistical and cryptographic characteristics …were introduced to measure the strength of substitution boxes (S-boxes). With the help of the present objective weight methods and ranking technique, we can select an ideal S-box among other constructed confusion component to make our encryption algorithm secure and robust against various cryptographic attacks. Show more

Keywords: Simple additive weighting, entropy weighting, S-boxes

DOI: 10.3233/JIFS-211176

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2325-2338, 2021

Authors: Xiao, Yanjun | Liang, Shitong | Wang, Xiaolei | Jiang, Yunfeng | Liu, Weiling | Sun, Lingyu

Article Type: Research Article

Abstract: The abnormal vibration of the loom spindle will seriously affect the quality of the textile. Based on the inherent embedded control system of the rapier loom, this paper develops an embedded system that monitors and analyzes the vibration signal of the spindle to determine the cause of the spindle failure. The system improves the traditional vibration sensor signal acquisition method, design the sensor peripheral auxiliary circuit and vibration signal conditioning circuit, and design the data storage and communication module so that the system has the characteristics of low cost, strong flexibility and scalability. The embedded algorithm program of Fast Fourier …transform is developed, optimized, and is applied to embedded platform, therefore the system can analyze the characteristics of vibration signal in frequency domain. Finally, back propagation neural network (BPNN) is introduced to investigate and match the relationship between the vibration spectrum characteristics and fault types of the loom spindle. The extracted back propagation (BP) learning result is a mathematical mapping formula, which enables the embedded system to analyze and determine the cause of vibration fault by using this formula. System design is conducive to improving the level of production intelligence and reducing personnel costs in the production process. Show more

Keywords: Loom, vibration detection, embedded system, back propagation neural network, Fast Fourier transform

DOI: 10.3233/JIFS-211269

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2339-2356, 2021

Authors: Chen, Chuanming | Ye, Zhen | Hu, Fan | Gong, Shan | Sun, Liping | Yu, Qingying

Article Type: Research Article

Abstract: Existing trajectory-clustering methods do not consider road-network connectivity, road directionality, and real path length while measuring the similarity between different road-network trajectories. This paper proposes a trajectory-clustering method based on road-network-sensitive features, which can solve the problem of similarity metrics among trajectories in the road network, and effectively combine their local and overall similarity features. First, the method performs the primary clustering of trajectories based on the overall vehicle motion trends. Then, the map-matched trajectories are clustered based on the road segment density, connectivity, and corner characteristics. Finally, clustering is then merged based on the multi-area similarity measure. The visualization …and experimental results on real road-network trajectories show that the proposed method is more effective and comprehensive than existing methods, and more suitable for urban road planning, public transportation planning, and congested road detection. Show more

Keywords: Trajectory clustering, map matching, road-network trajectory, trajectory similarity

DOI: 10.3233/JIFS-211270

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2357-2375, 2021

Authors: Aziz, Fehmi | Tahir, Faheem | Midhat, Sadia | Naz, Shafaq | Qureshi, Naveeda Akhtar

Article Type: Research Article

Abstract:  Present study is an interdisciplinary approach towards rapid and efficient medical diagnosis. The research articulated on data set of cross-sectional study of pregnant females dwelling rural area of Pakistan. The prognosis of gestational wellbeing followed through analyzing heterogenic medical information to develop a holistic picture of ongoing pregnancy. Therefore, for rapid medical diagnosis and precision in decision-making, Fuzzy Soft Set (denoted as FSS) theory selected to develop an algorithm. The algorithm constructed as single point, multipoint and cumulative diagnosis for predicting health status with respect of Hemoglobin, Body Mass Index and Random Glucose Concentration (Respectively denoted as Hb, BMI and …RGC) of subjects under study. We successfully proposed novel approach for complex modeling and provision of algorithm for medical diagnosis. The algorithms successfully dealt with analyzing diversely attributed detailed medical tests/reports as input. The output of complex modeling effectively served efficient decision-making in predicting gestational wellbeing. Show more

Keywords: Medical diagnosis, fuzzy set, soft set, BMI, maternal anemia

DOI: 10.3233/JIFS-190452

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2377-2385, 2021

Authors: Zhou, Jia-Jia | Li, Xiang-Yang

Article Type: Research Article

Abstract:  In present paper, we put forward four types of hesitant fuzzy β covering rough sets (HFβ CRSs) by uniting covering based rough sets (CBRSs) and hesitant fuzzy sets (HFSs). We firstly originate hesitant fuzzy β covering of the universe, which can induce two types of neighborhood to produce four types of HFβ CRSs. We then make further efforts to probe into the properties of each type of HFβ CRSs. Particularly, the relationships of each type of rough approximation operators w.r.t. two different hesitant fuzzy β coverings are groped. Moreover, the relationships between our proposed models and some …other existing related models are established. Finally, we give an application model, an algorithm, and an illustrative example to elaborate the applications of HFβ CRSs in multi-attribute decision making (MADM) problems. By making comparative analysis, the HFβ CRSs models proposed by us are more general than the existing models of Ma and Yang and are more applicable than the existing models of Ma and Yang when handling hesitant fuzzy information. Show more

Keywords: Hesitant fuzzy β covering, hesitant fuzzy β neighborhoods, hesitant fuzzy complement β neighborhoods, HFβCRSs, MADM

DOI: 10.3233/JIFS-190959

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2387-2402, 2021

Authors: Wang, Chuanxu | Song, Changqun | Xu, Lang

Article Type: Research Article

Abstract: Based on an unqualified product recalling process in a supply chain, this paper establishes an evolutionary game model between consumer federation and manufacturer, as well as analyzes the effects of manufacturer’s pricing strategy and consumer federation’s supervision on the decision-making and dynamic tendency. Under this structure, the manufacturers’ pricing strategies on recalls mechanism have two scenarios: the high penalty and low penalty from consumer federation. Results shows that, when the consumer federation adopts high penalty measures, there will be an ESS for consumer federation that can both minimize the cost and protect consumers’ rights. Further, the probability of manufacturer adopting …“recall” strategy is positively correlated with the change in the product price, and both the probability of consumer federation adopting “regulate” strategy and manufacturer adopting “recall” strategy are positively correlated with the penalty coefficient. Show more

Keywords: Recall mechanism, evolutionary game, behavior strategy, consumer federation

DOI: 10.3233/JIFS-200086

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2403-2415, 2021

Authors: Gosain, Anjana | Dahiya, Sonika

Article Type: Research Article

Abstract: DKIFCM (Density Based Kernelized Intuitionistic Fuzzy C Means) is the new proposed clustering algorithm that is based on outlier identification, kernel functions, and intuitionist fuzzy approach. DKIFCM is an inspiration from Kernelized Intuitionistic Fuzzy C Means (KIFCM) algorithm and it addresses the performance issue in the presence of outliers. It first identifies outliers based on density of data and then clusters are computed accurately by mapping the data to high dimensional feature space. Performance and effectiveness of various algorithms are evaluated on synthetic 2D data sets such as Diamond data set (D10, D12, and D15), and noisy Dunn data set …as well as on high dimension real-world data set such as Fisher-Iris, Wine, and Wisconsin Breast Cancer Data-set. Results of DKIFCM are compared with results of other algorithms such as Fuzzy-C-Means (FCM), Intuitionistic FCM (IFCM), Kernel-Intuitionistic FCM (KIFCM), and density-oriented FCM (DOFCM), and the performance of proposed algorithm is found to be superior even in the presence of outliers and noise. Key advantages of DKIFCM are outlier identification, robustness to noise, and accurate centroid computation. Show more

Keywords: Fuzzy clustering, identification of outlier, FCM, IFCM, DOFCM, KIFCM, kernel functions

DOI: 10.3233/JIFS-201858

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 2417-2428, 2021