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

Authors: Nath, Sudarshan | Das Gupta, Suparna | Saha, Soumyabrata

Article Type: Research Article

Abstract: Skin disease is currently considered to be one of the most common diseases in the globe. Most of the human population has experienced it at some point but not all skin illnesses are as severe as others. There are some diseases that are symptomless or show fewer symptoms. Skin cancer is a potentially fatal outcome of serious skin illnesses that might develop if they are not detected in time. Due to the fact that medical professionals aren’t always quick or reliable enough to make a proper diagnosis. There is a hefty price tag attached to employing sophisticated equipment. Therefore, we …propose a system capable of classifying skin diseases using deep learning approaches, such as CNN architecture and six preset models including MobileNet, VGG19, ResNet, EfficientNet, Inception, and DenseNet. Acne, blisters, cold sores, psoriasis, and vitiligo are some of the most often seen skin conditions, thus we scoured the web resources for relevant photographs of these conditions. We have applied data augmentation methods to extend the size of the dataset and include more image variations. In the validation dataset, we achieved an accuracy rate of approx 99 percent, while in the test dataset; we achieved an accuracy rate of approx 90 percent. Our proposed method would help to diagnose skin diseases in a faster and more cost-effective way. Show more

Keywords: Skin disease, deep learning, CNN, MobileNet, VGG19, ResNet, EfficientNet, Inception, DenseNet, Acne, blisters, cold sore, psoriasis, vitiligo

DOI: 10.3233/JIFS-222773

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7483-7499, 2023

Authors: Shen, Dong | Fang, Haoyu | Li, Qiang | Liu, Jiale | Guo, Sheng

Article Type: Research Article

Abstract: Visual Simultaneous Localization and Mapping (SLAM) is one of the key technologies for intelligent mobile robots. However, most of the existing SLAM algorithms have low localization accuracy in dynamic scenes. Therefore, a visual SLAM algorithm combining semantic segmentation and motion consistency detection is proposed. Firstly, the RGB images are segmented by SegNet network, the prior semantic information is established and the feature points of high-dynamic objects are removed; Secondly, motion consistency detection is carried out, the fundamental matrix is calculated by the improved Random Sample Consistency (RANSAC) algorithm, the abnormal feature points are output by the epipolar geometry method, and …the feature points of low-dynamic objects are eliminated by combining the prior semantic information. Thirdly, the static feature points are used for pose estimation. Finally, the proposed algorithm is tested on the TUM dataset, the algorithm in this paper reduces the average RMSE of ORB-SLAM2 by 93.99% in highly dynamic scenes, which show that the algorithm can effectively improve the localization accuracy of the visual SLAM system in dynamic scenes. Show more

Keywords: Simultaneous localization and mapping (SLAM), semantic segmentation, motion consistency detection, dynamic feature points

DOI: 10.3233/JIFS-222778

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7501-7512, 2023

Authors: Chen, Yong | Long, Feiyu | Kuang, Wei | Zhang, Tianbao

Article Type: Research Article

Abstract: Blast-induced ground vibration is highly possible to result in serious losses such as destroyed buildings. The crucial parameter of the mentioned vibration is peak particle velocity (PPV). Many equations have been developed to predict PPV, however, worse performance has been reported by multiple literatures. This paper developed a method for predicting PPV based on Mamdani Fuzzy Inference System. Firstly, Minimum Redundancy Maximum Relevance was employed to identify the blasting design parameters which significantly contribute to the PPV induced by blasting. Secondly, K-means method was applied to determine the value ranges of the selected parameters. The selected parameters and corresponding value …ranges were combined to input into Mamdani Fuzzy Inference System for obtaining predicted PPV. Totally, 280 samples were collected from a blasting site. 260 out of them were used to train the proposed method and 20 were assigned for test. The proposed method was tested in the comparison with empirical equation USBM, multiple linear regression analysis, pure Mamdani Fuzzy Inference System in terms of the difference between predicted PPV and measured PPV, coefficient of correlation, root-mean-square error, and mean absolute error. The results from that showed that the proposed method has the better performance in PPV prediction. Show more

Keywords: Blasting, peak particle velocity, parameter selection, k-means method, Mamdani Fuzzy Inference System

DOI: 10.3233/JIFS-223195

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7513-7522, 2023

Authors: Praveen, R. | Pabitha, P.

Article Type: Research Article

Abstract: The Internet of Medical Things (IoMT) is a network of medical devices, hardware infrastructure, and software that allows healthcare information technology to be communicated over the web. The IoMT sensors communicate medical data to server for the quick diagnosis. As, it handles private and confidential information of a user, security is the primary objective. The existing IoT authentication schemes either using two-factor(Username, password) or multi-factor (username, password, biometric) to authenticate a user. Typically the structural characteristics-based biometric trait like Face, Iris, Palm print or finger print is used as a additional factor. There are chances that these biometrics can be …fabricated. Thus, these structural biometrics based authentication schemes are fail to provide privacy, security, authenticity, and integrity. The biodynamic-based bioacoustics signals are gained attention in the era of human-computer interactions to authenticate a user as it is a unique feature to each user. So, we use a frequency domain based bio-acoustics as a biometric input. Thus, this work propose a Secure Lightweight Bioacoustics based User Authentication Scheme using fuzzy embedder for the Internet of Medical Things applications. Also, the IoT sensors tends to join and leave the network dynamically, the proposed scheme adopts chinese remainder technique for generate a group secret key to protect the network from the attacks of former sensor nodes. The proposed scheme’s security is validated using the formal verification tool AVISPA(Automated Validation of Internet Security Protocols and Applications). The system’s performance is measured by comparing the proposed scheme to existing systems in terms of security features, computation and communication costs. It demonstrates that the proposed system outperforms existing systems. Show more

Keywords: e-Healthcare, internet of medical things security, remote patient monitoring, user authentication, bioacoustics, fuzzy embedder

DOI: 10.3233/JIFS-223617

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7523-7542, 2023

Authors: Xu, Baohua | Chen, Jiayu | Li, Zhi | Yang, Tao

Article Type: Research Article

Abstract: In recent years, with the continuous occurrence of natural disasters, people have gradually realized the importance of improving emergency response capability, and the weight of time constraints for rational allocation of emergency materials has gradually increased. Therefore, a high-dimensional collaborative allocation method of disaster materials with time window constraints is studied. A high-dimensional collaborative distribution model of disaster materials with time window constraints is constructed by combining four dimensional decision-making indexes: maximizing the satisfaction of material demand, fairness of material distribution and minimizing the total cost of expected emergency response; Build SPEA2 + SDE hybrid algorithm, solve the model and output the …optimal solution set. The simulation results show that this method can have the ability of high-dimensional distribution of disaster materials, obtain the output of the optimal distribution scheme set of disaster materials, and the material satisfaction is more than 0.70. Under the condition of minimum distribution cost, the distribution of disaster materials can be completed. Show more

Keywords: Time window constraint, disaster materials, high dimensional collaborative allocation, multi-objective constraints, decision index

DOI: 10.3233/JIFS-224428

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7543-7552, 2023

Authors: Singh, Varsha | Agrawal, Prakhar | Tiwary, Uma Shanker

Article Type: Research Article

Abstract: Generating natural language description for visual content is a technique for describing the content available in the image(s). It requires knowledge of both the domains of computer vision and natural language processing. For this, various models with different approaches are suggested. One of them is encoder-decoder-based description generation. Existing papers used only objects for descriptions, but the relationship between them is equally essential, requiring context information. Which required techniques like Long Short-Term Memory (LSTM). This paper proposes an encoder-decoder-based methodology to generate human-like textual descriptions. Dense-LSTM is presented for better description as a decoder with a modified VGG19 encoder to …capture information to describe the scene. Standard datasets Flickr8K and Flickr30k are used for testing and training purposes. BLEU (Bilingual Evaluation Understudy) score is used to evaluate the generated text. For the proposed model, a GUI (Graphical User Interface) is developed, which produces the audio description of the output received and provides an interface for searching the related visual content and query-based search. Show more

Keywords: Convolutional neural network (CNN), dense-long short-term memory (Dense-LSTM), bilingual evaluation understudy score (BLEU), textual description generation

DOI: 10.3233/JIFS-222358

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7553-7565, 2023

Authors: Gao, Feng | Ahmadzade, Hamed | Gao, Rong | Zou, Zezhou

Article Type: Research Article

Abstract:  Gini coefficient is a device to characterize dispersion of uncertain variables. In order to measure variation of uncertain variables, the concept of Gini coefficient for uncertain variables is proposed. By invoking inverse uncertainty distribution, we obtain a formula for calculating Gini coefficient for uncertain variables. As an application of Gini coefficient, portfolio selection problems for uncertain returns are solved via mean-Gini models. For better understanding, several examples are provided.

Keywords: Uncertain variables, monte-carlo simulation, inverse uncertainty distribution, portfolio optimization, Gini coefficient

DOI: 10.3233/JIFS-222762

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7567-7575, 2023

Authors: Gao, Bin | Zhang, Naiwen

Article Type: Research Article

Abstract: For urban, the quantity and quality of talent is often an important measure of their development potential. Based on the theory of talent and environment comfort degree and the theory of urban comfort degree, this paper constructs the Evaluation Index System of urban talent development environment. This paper selects 7 coastal urban in Shandong province as the research objects, and uses entropy Weight-TOPSIS and cluster analysis to measure the talent development environment. The research results show that: (1) The talent development environment of seven coastal urban presents the phenomenon of “siphoning” and “distinctness” of talents. On the whole, Qingdao, Weifang, …and Yantai have certain advantages in the talent development environment. (2) Qingdao is the leading city, Weifang, Yantai, Weihai and Dongying are follow-up urban, and Binzhou and Rizhao are backward urban. (3) The environment of the eight first-level indicators forms a “magnetic field” for the development of talents. Only by fully releasing the “magnetic field effect” of the talent development environment can urban ensure that talents are “attracted, retained and used well". This paper puts forward some suggestions to optimize the talent de-velopment environment in coastal urban, which will help to stimulate the vitality and creativity of all kinds of talents in coastal urban. Show more

Keywords: Coastal urban, talent development environment, measurement, entropy weight-topsis method

DOI: 10.3233/JIFS-222889

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7577-7587, 2023

Authors: Wei, Pingping | Zhang, Xin

Article Type: Research Article

Abstract: This paper proposes a robust autoencoder with Wasserstein distance metric to extract the linear separability features from the input data. To minimize the difference between the reconstructed feature space and the original feature space, using Wasserstein distance realizes a homeomorphic transformation of the original feature space, i.e., the so-called the reconstruction of feature space. The autoencoder is used for features extraction of linear separability in the reconstructed feature space. Experiment results on real datasets show that the proposed method reaches up 0.9777 and 0.7112 on the low-dimensional and high-dimensional datasets in extracted accuracies, respectively, and also outperforms competitors. Results also …confirm that compared with feature metric-based methods and deep network architectures-based method, the linear separabilities of those features extracted by distance metric-based methods win over them. More importantly, the linear separabilities of those features obtained by evaluating distance similarity of the data are better than those obtained by evaluating feature importance of data. We also demonstrate that the data distribution in the feature space reconstructed by a homeomorphic transformation can be closer to the original data distribution. Show more

Keywords: Autoencoder, distance measure, feature extraction, linear separability

DOI: 10.3233/JIFS-223017

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7589-7598, 2023

Authors: Ahmed Seghir, Zianou | Djezzar, Meriem | Hemam, Mounir | Zeggari, Ahmed | Hachouf, Fella

Article Type: Research Article

Abstract: The application of 3D technology is rapidly expanding, and stereoscopic imagery is typically used to display 3D data. However, compression, transmission, and other necessary processes may reduce the quality of these images. Stereo image quality assessment (SIQA) has gained more attention to guarantee that customers have a positive watching experience. In order to provide the highest level of experience, it is necessary to develop a quality evaluation mechanism for stereoscopic content that is both dependable and precise. A full-reference method for SIQA is presented in this paper. Compared to previous measures, this method gives users more freedom to use distorted …pixel metrics and edge similarity. The binocular summation map is calculated by adding the left and right images for a stereo pair. Improved gradient similarity based distorted pixel measure (SGSDM) is used to calculate the quality of binocular summation. The scored 3D LIVE IQA database is used to evaluate the correlation of the proposed metric with the DMOS subjective score given by the database. The proposed method’s efficacy is demonstrated by experimental comparisons. Show more

Keywords: Gradient similarity, quality assessment, test image, distorted pixel measure, SIQA

DOI: 10.3233/JIFS-223375

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 5, pp. 7599-7611, 2023