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

Authors: Dhamija, Ashutosh | Dubey, R. B.

Article Type: Research Article

Abstract: Face recognition is one of the most challenging and demanding field, since aging affects the shape and structure of the face. Age invariant face recognition is a relatively new area in face recognition studies, which in real-world implementations recently gained considerable interest due to its huge potential and relevance. The Age invariant face recognition, however, is still evolving and evolving, providing substantial potential for further study and progress in accuracy. Major issues with the age invariant face recognition involve major variations in appearance, texture, and facial features and discrepancies in position and illumination. These problems restrict the age invariant face …recognition systems developed and intensify identity recognition tasks. To address this problem, a new technique Quadratic Support Vector Machine- Principal Component Analysis (QSVM-PCA) is introduced. Experimental results suggest that our QSVM-PCA achieved better results especially when the age range is larger than other existing techniques of face-aging dataset of FGNET. The maximum accuracy achieved by demonstrated methodology is 98.87%. Show more

Keywords: Age-invariant face recognition, feature extraction, PCA and QSVM

DOI: 10.3233/JIFS-202485

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 683-697, 2021

Authors: Yang, Yulei | Zhang, Jin | Sun, Wenjie | Pu, Yun

Article Type: Research Article

Abstract: Under the background of the new medical reform, the pharmaceutical industry is in constant transformation and upgrading, and the establishment of a rational and efficient pharmaceutical logistics system is imminent. Carbon emission, cost and time are set as the target to construct the model of location-routing-inventory optimization of highway, rail and air transport hubs with capacity limits. Then the warehouse of pharmaceutical logistics hub is selected, and the distribution path of pharmaceutical logistics and the inventory strategy are planned to realize the scientific decision of the system. The NSGA-III algorithm is used to solve the problem. The diversity of the …population is maintained by the well-distributed reference points, and the optimal solution set of nondominant Pareto is obtained. Spacing, HRS, PR and GD are used to measure the performance of the algorithm. The example analysis shows that the number of Pareto optimal solutions solved by the algorithm is large and evenly distributed, and convergence and operation efficiency of algorithm is good. The sensitivity analysis of three kinds of freight rates shows that the influence of the freight rates on the objective function value should be fully considered when making decisions. The method focuses on the problem of optimizing the layout of multi-modal transport hubs and improves the existing theories of it. Show more

Keywords: Pharmaceutical warehouse, carbon emission, location-routing-inventory problem, NSGA-III

DOI: 10.3233/JIFS-202508

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 699-713, 2021

Authors: Mousa, A.A. | Higazy, M. | Abdel-Khalek, S. | Hussein, Mohamed A. | Farouk, Ahmed

Article Type: Research Article

Abstract: The application and analysis of effective blood supply chain network under natural disaster imposed many critical challenges which addressed through an optimization of multiple objectives functions. In this article, relies on reference point algorithm, a user-preference based enriched swarm optimization algorithm is proposed where, inner reference points were produced depending on the perturbed reference point. For each inner reference point, weakly/ɛ -properly Pareto optimal solution was generated using augmented achievement function. All the generated solutions (points) are presented as potential positions for particles in the particle swarm optimization PSO. The proposed algorithm has been reinforced with a novel chaotic contraction …operator to retain the feasibility of the particles. To prove the validity of our algorithm, the obtained results are compared with true Pareto optimal front and three of the most salient evolutionary algorithms using inverted generational distance metric IGD. In addition it was implement to detect the most cost and time efficient blood supply chain to provide the required blood types demand on the blood transfusion center in emergence situation, where, it is required to solve this real life application with predefined supply time and predefined supply cost, which is considered as reference point to get the nearby Pareto optimal solution. By the experimental outcomes, we proved that the proposed algorithm is capable to find the set of Paetro optimal solutions nearby the predefined reference points. Show more

Keywords: Particle swam optimization, reference point, multi-objective optimization, blood supply chain

DOI: 10.3233/JIFS-202529

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 715-733, 2021

Authors: Ranjith Pillai, R. | Murali, Ganesan

Article Type: Research Article

Abstract: Miniature flexible parallel robots, popularly used for micro positioning application demands the use of non conventional actuators. Shape memory alloys (SMA) are popular smart actuators because of its light weight, integration compatibility, ease of actuation and high power density. Inclusion of shape memory alloy actuators to the parallel robot brings in control challenges due to its nonlinearity, coupling effects and cocontraction of antagonistic pair of actuators in the mechanism in order to achieve bi directional motion. In this paper, a PID like fuzzy controller is designed and applied to a nonlinear SMA spring actuator connected to a symmetric 2 DOF …miniature parallel robot. The fuzzy rules are designed from the general response plot and modified to be applied to a parallel mechanism which involves cocontraction of antagonistic actuators. The paper has also presented the control and electrical circuit design used in the experimental set up. The fuzzy control is implemented in the hardware controller with model based position feedback and tested for the trajectory tracking characteristics of the end effector with disturbances. Experimental results are presented with quantitative analysis to show the effectiveness of the proposed controller in handling nonlinearities and disturbances compared to the conventional PID control and nonlinear Sliding mode control (NSMC). The test results has demonstrated the superior nature of proposed control over other controllers in the trajectory tracking with disturbances and also linearizing the hysteresis of controlled system. Show more

Keywords: SMA actuated parallel robot, PID like fuzzy control, control of cocontraction of actuators, flexible robot, SMA spring control

DOI: 10.3233/JIFS-202572

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 735-755, 2021

Authors: Adu, Kwabena | Yu, Yongbin | Cai, Jingye | Dela Tattrah, Victor | Adu Ansere, James | Tashi, Nyima

Article Type: Research Article

Abstract: The squash function in capsule networks (CapsNets) dynamic routing is less capable of performing discrimination of non-informative capsules which leads to abnormal activation value distribution of capsules. In this paper, we propose vertical squash (VSquash) to improve the original squash by preventing the activation values of capsules in the primary capsule layer to shrink non-informative capsules, promote discriminative capsules and avoid high information sensitivity. Furthermore, a new neural network, (i) skip-connected convolutional capsule (S-CCCapsule), (ii) Integrated skip-connected convolutional capsules (ISCC) and (iii) Ensemble skip-connected convolutional capsules (ESCC) based on CapsNets are presented where the VSquash is applied in the dynamic …routing. In order to achieve uniform distribution of coupling coefficient of probabilities between capsules, we use the Sigmoid function rather than Softmax function. Experiments on Guangzhou Women and Children’s Medical Center (GWCMC), Radiological Society of North America (RSNA) and Mendeley CXR Pneumonia datasets were performed to validate the effectiveness of our proposed methods. We found that our proposed methods produce better accuracy compared to other methods based on model evaluation metrics such as confusion matrix, sensitivity, specificity and Area under the curve (AUC). Our method for pneumonia detection performs better than practicing radiologists. It minimizes human error and reduces diagnosis time. Show more

Keywords: Artificial intelligence, capsule network, convolutional neural network, deep learning, pneumonia, x-ray imaging

DOI: 10.3233/JIFS-202638

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 757-781, 2021

Authors: Huang, Danyang | Zhou, Zhiheng | Deng, Ming | Li, Zhihao

Article Type: Research Article

Abstract: Detecting vehicle at night is critical to both assistant driving systems and autonomous driving systems. In this paper, we propose a deep network scheme assisted by light information with good generalization to detect vehicle at night. Our approach is divided into two branches, the object stream and the pixel stream. The object stream generates a batch of bounding boxes, and the pixel stream utilizes the vehicle light information to calibrate the bounding boxes of the object stream. In the object stream, we propose a new structure, Direction Attention Pooling (DAP), to improve the accuracy of the prior boxes. DAP leads …into attention mechanism. The feature maps obtained from backbone network is divided into two branches. One branch obtains direction perception information through IRNN layer, and the other branch learns attention weights. The weights are multiplied with the direction perception features in an element-wise manner. In the pixel stream, we propose a corner localization algorithm based on Bayes to get more accurate corners with the vehicle light pixels. The locations of the corners are considered as a discrete random variable. When the mask of the object is known, solving the probability distribution of the corner of the object is the next step. The corners with the highest probability is the correct corner. On the nighttime vehicle detection datasets CHUK and SYSU, our method achieves the accuracy of 97.2% and 96.86%, which outperforms other state-of-the-art methods by at least 0.31% and 0.34%. Show more

Keywords: Nighttime vehicle detection, advanced driver-assistance systems, attention mechanism, deep learning

DOI: 10.3233/JIFS-202676

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 783-801, 2021

Authors: Noorullah, R.M. | Mohammed, Moulana

Article Type: Research Article

Abstract: Topic models are widely used in building clusters of documents for more than a decade, yet problems occurring in choosing the optimal number of topics. The main problem is the lack of a stable metric of the quality of topics obtained during the construction of topic models. The authors analyzed from previous works, most of the models used in determining the number of topics are non-parametric and the quality of topics determined by using perplexity and coherence measures and concluded that they are not applicable in solving this problem. In this paper, we used the parametric method, which is an …extension of the traditional topic model with visual access tendency for visualization of the number of topics (clusters) to complement clustering and to choose the optimal number of topics based on results of cluster validity indices. Developed hybrid topic models are demonstrated with different Twitter datasets on various topics in obtaining the optimal number of topics and in measuring the quality of clusters. The experimental results showed that the Visual Non-negative Matrix Factorization (VNMF) topic model performs well in determining the optimal number of topics with interactive visualization and in performance measure of the quality of clusters with validity indices. Show more

Keywords: Interactive visualization, visual non-negative matrix factorization model, an optimal number of topics, cluster validity indices, twitter data clustering

DOI: 10.3233/JIFS-202707

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 803-817, 2021

Authors: Shabir, Muhammad | Mushtaq, Rimsha | Naz, Munazza

Article Type: Research Article

Abstract: In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of …these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop. Show more

Keywords: N-soft set, algebraic structure, top complement, bottom complement, TOPSIS

DOI: 10.3233/JIFS-202717

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 819-839, 2021

Authors: Cheng, Haodong | Han, Meng | Zhang, Ni | Li, Xiaojuan | Wang, Le

Article Type: Research Article

Abstract: Traditional association rule mining has been widely studied, but this is not applicable to practical applications that must consider factors such as the unit profit of the item and the purchase quantity. High-utility itemset mining (HUIM) aims to find high-utility patterns by considering the number of items purchased and the unit profit. However, most high-utility itemset mining algorithms are designed for static databases. In real-world applications (such as market analysis and business decisions), databases are usually updated by inserting new data dynamically. Some researchers have proposed algorithms for finding high-utility itemsets in dynamically updated databases. Different from the batch processing …algorithms that always process the databases from scratch, the incremental HUIM algorithms update and output high-utility itemsets in an incremental manner, thereby reducing the cost of finding high-utility itemsets. This paper provides the latest research on incremental high-utility itemset mining algorithms, including methods of storing itemsets and utilities based on tree, list, array and hash set storage structures. It also points out several important derivative algorithms and research challenges for incremental high-utility itemset mining. Show more

Keywords: Survey, pattern mining, incremental mining, high-utility patterns, frequent itemsets

DOI: 10.3233/JIFS-202745

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 841-866, 2021

Authors: Yang, Zhan | Li, Chengliang | Zhao, Zhongying | Li, Chao

Article Type: Research Article

Abstract: Aspect-based sentiment classification, a fine-grained sentiment analysis task, aims to predict the sentiment polarity for a specified aspect. However, the existing aspect-based sentiment classification approaches cannot fully model the dependency-relationship between words and are easily disturbed by irrelevant aspects. To address this problem, we propose a novel approach named Dependency-Relationship Embedding and Attention Mechanism-based LSTM. DA-LSTM first merges the word hidden vector output by LSTM with the dependency-relationship embedding to form a combined vector. This vector is then fed into the attention mechanism together with the aspect information which can avoid interference to calculate the final word representation for sentiment …classification. Our extensive experiments on benchmark data sets clearly show the effectiveness of DA-LSTM. Show more

Keywords: Aspect-based sentiment analysis, sentiment classification, dependency-relationship, attention mechanism

DOI: 10.3233/JIFS-202747

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 867-877, 2021