Journal of Intelligent & Fuzzy Systems - Volume 44, issue 5

Authors: Awan, Tehreem | Khan, Khan Bahadar | Mannan, Abdul

Article Type: Research Article

Abstract: COVID-19 is an epidemic, causing an enormous death toll. The mutational changing of an RNA virus is causing diagnostic complexities. RT-PCR and Rapid Tests are used for the diagnosis, but unfortunately, these methods are ineffective in diagnosing all strains of COVID-19. There is an utmost need to develop a diagnostic procedure for timely identification. In the proposed work, we come up with a lightweight algorithm based on deep learning to develop a rapid detection system for COVID-19 with thorax chest x-ray (CXR) images. This research aims to develop a fine-tuned convolutional neural network (CNN) model using improved EfficientNetB5. Design is …based on compound scaling and trained on the best possible feature extraction algorithm. The low convergence rate of the proposed work can be easily deployed into limited computational resources. It will be helpful for the rapid triaging of victims. 2-fold cross-validation further improves the performance. The algorithm proposed is trained, validated, and testing is performed in the form of internal and external validation on a self-collected and compiled a real-time dataset of CXR. The training dataset is relatively extensive compared to the existing ones. The performance of the proposed technique is measured, validated, and compared with other state-of-the-art pre-trained models. The proposed methodology gives remarkable accuracy (99.5%) and recall (99.5%) for biclassification. The external validation using two different test dataset also give exceptional predictions. The visual depiction of predictions is represented by Grad-CAM maps, presenting the extracted features of the predicted results. Show more

Keywords: COVID-19, Chest X-rays, Deep learning, EfficientNets

DOI: 10.3233/JIFS-223704

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7887-7907, 2023

Authors: Suresh Kumar, M. | Sathish Kumar, G.A.

Article Type: Research Article

Abstract: This paper aims to formulate an enhanced ant colony optimization algorithm that helps find a suitable data route that improves energy efficiency and reduces the time consumption for the delivery of packets. Energy equations have been framed to analyze energy used at the transmitting, receiving, and relay nodes. The network is segmented into smaller virtual segments for easier analysis of the proposed algorithm. Each segment is assumed to have nodes with a cluster head. The sink gathers information from different cluster heads as it moves from one segment to another. The nodes not in close connection with the network used …the overhearing mechanism to share the information with the sink. The simulation has been done using Cisco Packet Tracer software. The proposed algorithm has been applied to different types of wireless networks to determine their efficiency. The wireless networks considered for this purpose are Bluetooth, Wi-Max, and Wi-Fi. Packet delivery ratio, end-to-end delay, collision, and lifetime are evaluated for the different types of wireless networks. The obtained results are analyzed, and graphs are plotted. Show more

Keywords: Ant colony optimization, energy efficient, mobile sink, wireless sensor networks, packet delivery ratio, WiFi, WiMax, energy

DOI: 10.3233/JIFS-221856

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7909-7917, 2023

Authors: Qi, Ju

Article Type: Research Article

Abstract: In the big data and “Internet+” era, the research related cybersecurity risk has attracted much attention. However, Premium pricing for cybersecurity insurance remains in its early days. In this paper, we established a premium pricing method for cybersecurity risks. Firstly, the losses during the cyber infection is modeled by an interacting Markov SIS (Susceptible-Infected-Susceptible) epidemic model. we also proposed a premium simulation method called the Gillespie algorithm, which can be used for simulation of a continuous-time stochastic process. At last, as an example, we calculated the premiums by using premium principles and simulation in a simple network respectively. The numerical …case studies demonstrate the premium pricing model performs well, and the premiums based on simulations are rather conservative, and recommended using in practice by comparing the results of premiums. Show more

Keywords: SIS epidemic model, cybersecurity insurance, premium pricing, renewal reward process, gillespie simulation algorithm

DOI: 10.3233/JIFS-222308

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7919-7933, 2023

Authors: Hu, Limei

Article Type: Research Article

Abstract: The traditional failure mode and effect analysis (FMEA), as an effective risk analysis technique, has several limitations in the uncertainty modeling and the weights determination of the risk indicators. This paper aims to propose a hybrid risk prioritization method simultaneously considering the characteristics of the reliability associated with the FMEA team members’ evaluation information and their psychological behavior to enhance the performance of the traditional FMEA model. The hybrid risk prioritization method is developed based on the generalized TODIM method and the weighted entropy measure with the linguistic Z-numbers (LZNs). First, the LZNs are adopted to depict the FMEA team …members’ cognition information and the reliability of these information. Second, a weighted entropy measure based on the fuzzy entropy and the LZNs is developed to obtain the risk indicators’ weights. Finally, the generalized TODIM method with the LZNs is constructed to obtain the risk priority orders of failure modes, which can effectively simulate the FMEA team members’ psychological character. The applicability and effectiveness of the proposed risk prioritization method is validated through an illustrative example of an integrated steel plant. The results of sensitivity analysis and comparative analysis indicate that the proposed hybrid risk prioritization method is effective and valid, and can get more accurate and practical risk ranking results to help enterprises formulate accurate risk prevention and control plans. Show more

Keywords: INDEX TERMS: Failure mode and effect analysis, risk prioritization, Linguistic Z-numbers, fuzzy entropy, the generalized TODIM method

DOI: 10.3233/JIFS-223132

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7935-7955, 2023

Authors: Parida, Subhashree | Acharya, Milu | Patnaik, Srikanta

Article Type: Research Article

Abstract: In the present era, the most delicate environmental issue is global warming, and because of this, countries across the globe are trying to manage the most hazardous emissions by making certain investments in projects to promote green industrial practices. The proposed study creates sustainable deteriorating inventory models in both crisp and fuzzy environments, with both cloudy and intuitionistic fuzzy considerations, where the demand is taken to be time-dependent. In the current study, the emission of CO2 from transportation is controlled by the optimum investments in green technology (GT). This work develops the previous research that has worked on a …sustainable inventory system with controllable greenhouse facilities through green investment. The present research includes an optimum GT investment in an inventory system with two warehouses to restrict carbon emissions due to the transportation of goods from owned to rented warehouses and then to customers. To have control over the total cost, this work considers two warehouses to manage the stock-out conditions and represents models with shortages for crisp, cloudy fuzzy (CF), and intuitionistic fuzzy (IF) environments. A multiple prepayment option for the purchasing cost involving an installment is provided to the retailers. In the present research, we develop non-linear crisp and fuzzy deteriorating inventory models and suggest an algorithm for the solution process. Model problems are illustrated through numerical examples and validated through sensitivity analysis. A comparative inquiry is conducted for the optimum results obtained in all three cases. Show more

Keywords: Carbon emissions, green technology, disposal cost, cloudy fuzzy, intuitionistic fuzzy, ranking method

DOI: 10.3233/JIFS-223385

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7957-7976, 2023

Authors: Khan, Izaz Ullah | Shah, Jehanzeb Ali | Bilal, Muhammad | Faiza, | Khan, Muhammad Saqib | Shah, Sajid | Akgül, Ali

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-220781

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7977-7993, 2023

Authors: Sarfaraz, Amir Homayoun | Yazdi, Amir Karbassi | Hanne, Thomas | Hosseini, Raheleh Sadat

Article Type: Research Article

Abstract: Technology transfer plays an essential role in developing an organization’s capabilities to perform better in the market. Several protocols are defined for technology transfer. One of the main techniques in technology transfer is licensing, which significantly impacts profit and income. This study intends to develop a decision framework that integrates both a Fuzzy Inference System (FIS) and a two steps Fuzzy Quality Function Deployment (F-QFD) to assist an organization in selecting a licensor. To illustrate the decision framework’s performance, it has been implemented in an Iranian lubricant producer to select the best licensor among the 13 targeted companies. A complete …product portfolio, brand image enhancement, increasing the market share of the high-value products, and improving the technical knowledge of manufacturing products were identified as the most important expectations of the licensees. A sensitivity analysis for the recommended framework has been conducted. For doing so, 27 rules of the FIS were categorized into four group and then changed. The results are compared using the Pearson correlation coefficient. Inference rules detect unconventional changes, while logical changes are appropriately considered. Show more

Keywords: Technology transfer, licensing, fuzzy inference system, fuzzy quality function deployment, fuzzy QFD

DOI: 10.3233/JIFS-222232

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7995-8014, 2023

Authors: Monika, | Singh, Pardeep | Chand, Satish

Article Type: Research Article

Abstract:  Pedestrians are the most critical and vulnerable moving objects on roads and public areas. Learning pedestrian movement in these areas can be helpful for their safety. To improve pedestrian safety and enable driver assistance in autonomous driver assistance systems, recognition of the pedestrian direction of motion plays an important role. Pedestrian movement direction recognition in real world monitoring and ADAS systems are challenging due to the unavailability of large annotated data. Even if labeled data is available, partial occlusion, body pose, illumination and the untrimmed nature of videos poses another problem. In this paper, we propose a framework that considers …the origin and end point of the pedestrian trajectory named origin-end-point incremental clustering (OEIC). The proposed framework searches for strong spatial linkage by finding neighboring lines for every OE (origin-end) lines around the circular area of the end points. It adopts entropy and Q measure for parameter selection of radius and minimum lines for clustering. To obtain origin and end point coordinates, we perform pedestrian detection using the deep learning technique YOLOv5, followed by tracking the detected pedestrian across the frame using our proposed pedestrian tracking algorithm. We test our framework on the publicly available pedestrian movement direction recognition dataset and compare it with DBSCAN and Trajectory clustering model for its efficacy. The results show that the OEIC framework provides efficient clusters with optimal radius and minlines. Show more

Keywords: Unsupervised learning, line clustering method, origin-end point, pedestrian direction of motion, YOLOv5

DOI: 10.3233/JIFS-223283

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 8015-8027, 2023

Authors: Zhang, Mingyue | Zhou, Zhiheng | Tao, Xiyuan | Zhang, Na | Deng, Ming

Article Type: Research Article

Abstract: The modern world contains a significant number of applications based on computer vision, in which human-computer interaction plays a crucial role, pose estimation of the hand is a crucial approach in the field of human-computer interaction. However, previous approaches suffer from the inability to accurately measure position in real-world scenes, difficulty in obtaining targets of different sizes, the structure of complex network, and the lack of applications. In recent years, deep learning techniques have produced state-of-the-art outcomes but there are still challenges that need to be overcome to fully exploit this technology. In this research, a fish skeleton CNN (FS-HandNet) …is proposed for hand posture estimation from a monocular RGB image. To obtain hand pose information, a fish skeleton network structure is used for the first time. Particularly, bidirectional pyramid structures (BiPS) can effectively reduce the loss of feature information during downsampling and can be used to extract features from targets of different sizes. It is more effective at solving problems of different sizes. Then a distribution-aware coordinate representation is employed to adjust the position information of the hand, and finally, a convex hull algorithm and hand pose information are applied to recognize multiple gestures. Extensive studies on three publicly available hand position benchmarks demonstrate that our method performs nearly as well as the state-of-the-art in hand pose estimation. Additionally, we have implemented hand pose estimation for the application of gesture recognition. Show more

Keywords: Hand pose estimation, FS-HandNet, distribution-aware coordinate representation, convex hull algorithm, the application of gesture recognition

DOI: 10.3233/JIFS-224271

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 8029-8042, 2023

Authors: Guo, Xiaobin | Liu, Kun

Article Type: Research Article

Abstract: This paper discusses a new approximate solution of a class of fully fuzzy linear systems A ˜ x ˜ = b ˜ in which the coefficient matrix A ˜ is a positive fuzzy matrix. The original fuzzy linear systems is extended into simple crisp linear equation using the obtained approximate multiplication of positive fuzzy number and near zero fuzzy number. Two cases are analysed: (a) the unknown vector x ˜ is a near zero fuzzy vector with positive mean value; …(b) the unknown vector x ˜ is a near zero fuzzy vector with negative mean value. Two computing models are established and respective expression of the solution to fully fuzzy linear system are derived, and the sufficient condition for the existence of strong fuzzy solution are analyzed correspondingly. Some numerical examples are given to illustrated our proposed method. Show more

Keywords: Fuzzy numbers, matrix computation, fuzzy linear systems, fuzzy approximate solutions

DOI: 10.3233/JIFS-222421

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 8043-8052, 2023