Journal of Intelligent & Fuzzy Systems - Volume 45, issue 5

Authors: Malavath, Pallavi | Devarakonda, Nagaraju

Article Type: Research Article

Abstract: A crucial component of human-computer interaction is 3D hand posture assessment. The most recent advancements in computer vision have made estimating 3D hand positions simpler by using deep sensors. The main challenge still stems from unrealistic 3D hand poses because the existing models only use the training dataset to learn the kinematic rules, which is ambiguous, and it is a difficult task to estimate realistic 3D hand poses from datasets because they are not free from anatomical errors. The suggested model in this study is trained using a closed-form expression that encodes the biomechanical rules, thus it does not entirely …reliant on the pictures from the annotated dataset. This work also used a Single Shot Detection and Correction convolutional neural network (SSDC-CNN) to handle the issues in imposing anatomically correctness from the architecture level. The ResNetPlus is implemented to improve representation capability with enhanced the efficiency of error back-propagation of the network. The datasets of the Yoga Mudras, like HANDS2017, and MSRA have been used to train and test the future model. As observed from the ground truth the previous hand models have many anatomical errors but, the proposed hand model is anatomically error free hand model compared to previous hand models. By considering the ground truth hand pose, the recommended hand model has shown good accuracy when compared to the state-of-art hand models. Show more

Keywords: Biomechanical constraints, Anatomical correction, single-shot detection and correction CNN, 3-Dimensional hand pose estimation

DOI: 10.3233/JIFS-231779

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8263-8277, 2023

Authors: Chen, Dongning | Liu, Jitao | Yao, Chengyu | Ma, Lei | Wang, Kuantong | Zhou, Ziyu | Wu, Xuefei | Chen, Yanan

Article Type: Research Article

Abstract: The lack of effective failure correlation analysis is one main reason for the gap between the reliability models and the actual complex systems with mixed static and dynamic characteristics. Takagi and Sugeno (T-S) dynamic fault tree is one powerful tool to analyze the static and dynamic failure logic relationship but it assumes the failure probability of the event is independent. Therefore, this paper proposes a multi-dimensional T-S dynamic fault tree analysis method involving failure correlation. The method integrates the failure probability distribution function of basic events with multi-factors and the multi-dimensional copula function, and the important measure of this method …is also deduced. The reliability model expression for systems with failure correlations, both in series and in parallel, is discussed and verified. Compare the proposed method with the assumption that the probability of a failure event is independent. This method solves the problem of a large error when ignoring the failure correlation between parts and the degree of the correlation between variables can be characterized. The reliability analysis can be conducted on complex systems affected both by multi-factors and failure correlations. The proposed method is applied to the reliability analysis of a hydraulic height adjustment system and the correctness and superiority of the method are verified. Show more

Keywords: Multi-dimensional T-S dynamic fault tree, copula function, failure correlation, importance measure, reliability analysis

DOI: 10.3233/JIFS-231939

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8279-8296, 2023

Authors: Min, Qu | Zhaoxian, Ren | Jiang, Wu

Article Type: Research Article

Abstract: To inherit and promote the excellent design characteristics of Chinese-style furniture, this study focuses on Chinese-style stools and proposes an integrated design and evaluation approach with combination of shape grammar, KANO model, and entropy-weighted VIekriterijumsko KOmpromisno Rangiranje (VIKOR) methods. Firstly, based on the initial forms of five Chinese-style stools, a shape feature library is constructed by extracting shape features using regional cultural symbols. Secondly, combining shape grammar and inference rules, innovative design alternatives are generated for Chinese-style stools, incorporating regional cultural symbol features. Thirdly, an in-depth investigation of Chinese-style furniture market is conducted, and user requirements are analyzed using KANO …model questionnaire, categorizing the requirements into three attributes: appearance, technological, and economic. Based on KANO model’s classification of user requirements, a set of 14 evaluation criteria for Chinese-style stools is established. Finally, to avoid subjective factors in weighting the criteria, the entropy-weighted method is applied, and VIKOR method is utilized to obtain the optimal ranking of the design alternatives for Chinese-style stools, ultimately selecting the optimal alternative. The results show that based on VIKOR method, the optimal solution is the same with comparison to the results obtained from Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), preference ranking organization methods for enrichment evaluations (PROMETHEE) and elimination and et choice translating reality (ELECTRE) methods. In addition, to verify its ergonomic characteristics, feasibility and rationality, the optimal alternative is simulated by JACK software. By integrating shape grammar, KANO model, and the entropy-weighted VIKOR method, this study provides some insights for incorporating regional cultural symbols into the design of Chinese-style furniture and exhibits certain advantages in terms of comprehensive evaluation, user orientation, decision objectivity, and consideration of diversity. Show more

Keywords: Shape grammar, KANO model, entropy weight-VIekriterijumsko KOmpromisno Rangiranje method (VIKOR) method, Chinese-style Stools(CSS)

DOI: 10.3233/JIFS-232580

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8297-8316, 2023

Authors: Gu, Xinxin

Article Type: Research Article

Abstract: In modern social APP interface design, how to effectively improve the corporate image and create the connotation of corporate culture is a significant key problem. With the emergence of APP, a growing number of people use them, increasing communication energy usage and slowing network operation. To improve app compatibility and speed, it is necessary to combine it with the most advanced and dependable technology, such as ZigBee, which is regarded as the best solution for wireless sensor networks. The ZigBee protocol is primarily used to incorporate working and data transmission in wireless sensor networks that are based on ZigBee technology. …As a result, incorporating ZigBee technology into APP interface design in the Internet of Things (IoT) domain can significantly improve brand APP interface design’s network operation efficiency. This paper presents a novel approach to enhance the performance and corporate image of brand mobile applications (APPs) by integrating ZigBee technology. The primary objective is to improve the operating efficiency and user experience of the brand APPs. The study involves a comparison between 10 brand APPs that have not integrated ZigBee technology and 10 brand APPs that have adopted ZigBee technology. The experimental results indicate that the operating efficiency of the brand APPs incorporating ZigBee technology is 97%, while the efficiency of the brand APPs without ZigBee technology is 85%, resulting in a notable difference of 12%. To assess the effectiveness of ZigBee technology integration, the study conducted experiments with 100 users, randomly assigned to interact with both types of brand APPs. The user feedback and observations revealed that brand APPs integrated with ZigBee technology exhibit significantly higher operating efficiency, contributing to a 12% improvement over their counterparts lacking ZigBee integration. Moreover, 90 out of 100 users reported a preference for the brand APPs integrated with ZigBee technology due to their superior user experience. The integration of ZigBee technology in brand APPs not only enhances the user experience but also contributes to the improvement of the company’s corporate image. Adopting ZigBee technology in brand APPs is a valuable strategy that can facilitate the long-term development and success of the company. Show more

Keywords: APP interface, ZigBee technology, Internet of Things, Clustering Algorithm, LEACH algorithm, Internet

DOI: 10.3233/JIFS-233343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8317-8333, 2023

Authors: Senthil Kumar, K. | Anandamurugan, S.

Article Type: Research Article

Abstract: Cloud computing has become a crucial paradigm for large-scale data-intensive applications, but it also brings challenges like energy consumption, execution time, heat, and operational costs. Improving workflow scheduling in cloud environments can address these issues and optimize resource utilization, leading to significant ecological and financial benefits. As data centres and networks continue to expand globally, efficient scheduling becomes even more critical for achieving better performance and sustainability in cloud computing. Schedulers mindful of energy and deadlines will assign resources to jobs in a way that consumes the least energy while upholding the task’s quality standards. Because this scheduling involves a …Non-deterministic Polynomial (NP)-hard problem, the schedulers are able to minimize complexity by utilizing metaheuristic techniques. This work has developed methods like Artificial Bee Colony (ABC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) for optimizing the scheduler. Local search and exploration are respectably supported by heuristic algorithms. The algorithm’s exploration and exploitation features must also be balanced. The primary objective is to optimize computation-intensive workflows in a way that minimizes both energy consumption and execution time while maximizing throughput. This optimization should be achieved without compromising the Quality of Service (QoS) guarantee provided to users. The focus is on striking a balance between energy efficiency and performance to enhance the overall efficiency and cost-effectiveness of cloud computing environments. According to the simulation findings, the suggested ABC has a higher guarantee ratio for 5000 jobs when compared to the GA, PSO, GA with the longest processing time, and GA with the lowest processing time, by 7.14 percent, 4.7 percent, 3.5 percent, and 2.3 percent, respectively. It is observed that the proposed ABC possesses qualities like high flexibility, great robustness, and quick convergence leading to good performance. Show more

Keywords: Cloud computing, virtualization, scheduler, Virtual Machines (VMs), resource management

DOI: 10.3233/JIFS-234776

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8335-8348, 2023

Authors: Wang, Chuncha

Article Type: Research Article

Abstract: The hardness properties of constructional materials should be investigated as important factors in assessing the performance over the operation period. Two tests are performed to determine the stiffness characteristic, including slump and compressive strength (CS). They must be considered to examine efficiency, durability, and resistance to pressure. Due to the structure’s susceptibility and usage in dams, bridges, etc., high-performance concrete must have an appropriate set of these tests. There are two soft-based and laboratory methods for performing these tests. The laboratory method is not economical in terms of cost and time, and artificial intelligence (AI) is used to reduce the …aforementioned factors. Models and optimizers use software-based methods to help reduce errors and increase model accuracy. So, The main purpose of this research has been introducing novel ways of coupling an ensemble model with optimizers by adjusting some internal parameters. In this article, two models, the Radial Basis Function Neural network and Support Vector Regression were combined and coupled with General Normal Distribution Optimization (GNDO) and Archimedes optimization algorithm (AOA) into the two frameworks of SVRRBF-AOA and SVRRBF-GNDO. As a result, the hybrid model of SVRRBF-AOA could perform well by obtaining R2 and RMSE of 0.9915 and 2.71 for the slump and 0.9845 and 3.34 for CS, respectively. Show more

Keywords: High-performance concrete, slump, compressive strength, support vector regression, Radial basis function, generalized normal distribution optimization, archimedes optimization algorithm

DOI: 10.3233/JIFS-232114

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8349-8364, 2023

Authors: Tao, Nana | Hua, Yang | Ding, Chunxiao

Article Type: Research Article

Abstract: It is generally considered that attractivity is a concept that describes the overall characteristics of a system. This paper aims to study Pth moment attractivity for one order uncertain differential systems. According to the theory of uncertain differential systems, the concept of Pth moment attractivity is given. Moreover, the Pth moment attractivity of a class of nonlinear uncertain differential systems is studied and the judgment conditions of linear uncertain differential systems are derived.

Keywords: Pth moment, attractivity, uncertain differential systems, concept, judgment conditions

DOI: 10.3233/JIFS-232233

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8365-8370, 2023

Authors: Yu, Shujuan | Wu, Mengjie | Zhang, Yun | Xie, Na | Huang, Liya

Article Type: Research Article

Abstract: Reading Comprehension models have achieved superhuman performance on mainstream public datasets. However, many studies have shown that the models are likely to take advantage of biases in the datasets, which makes it difficult to efficiently reasoning when generalizing to out-of-distribution datasets with non-directional bias, resulting in serious accuracy loss. Therefore, this paper proposes a pre-trained language model based de-biasing framework with positional generalization and hierarchical combination. In this work, generalized positional embedding is proposed to replace the original word embedding to initially weaken the over-dependence of the model on answer distribution information. Secondly, in order to make up for the …influence of regularization randomness on training stability, KL divergence term is introduced into the loss function to constrain the distribution difference between the two sub models. Finally, a hierarchical combination method is used to obtain classification outputs that fuse text features from different encoding layers, so as to comprehensively consider the semantic features at the multidimensional level. Experimental results show that PLM-PGHC helps learn a more robust QA model and effectively restores the F1 value on the biased distribution from 37.51% to 81.78%. Show more

Keywords: Natural language processing, machine reading comprehension, pre-trained language model, de-biasing framework

DOI: 10.3233/JIFS-233029

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8371-8382, 2023

Authors: Dong, Hao | Ali, Zeeshan | Mahmood, Tahir | Liu, Peide

Article Type: Research Article

Abstract: Algebraic and Einstein are two different types of norms which are the special cases of the Hamacher norm. These norms are used for evaluating or constructing three different types of aggregation operators, such as averaging/geometric, Einstein averaging/geometric, and Hamacher averaging/geometric aggregation operators. Moreover, complex Atanassov intuitionistic fuzzy (CA-IF) information is a very famous and dominant technique or tool which is used for depicting unreliable and awkward information. In this manuscript, we present the Hamacher operational laws for CA-IF values. Furthermore, we derive the power aggregation operators (PAOs) for CA-IF values, called CA-IF power Hamacher averaging (CA-IFPHA), CA-IF power Hamacher ordered …averaging (CA-IFPHOA), CA-IF power Hamacher geometric (CA-IFPHG), and CA-IF power Hamacher ordered geometric (CA-IFPHOG) operators. Some dominant and valuable properties are also stated. Moreover, the multi-attribute decision-making (MADM) methods are developed based on the invented operators for CA-IF information and the detailed decision steps are given. Many prevailing operators are selected as special cases of the invented theory. Finally, the derived technique will offer many choices to the expert to evaluate the best alternatives during comparative analysis. Show more

Keywords: Complex intuitionistic fuzzy sets, power aggregation operators, decision-making problems, hamacher t-norm and t-conorm

DOI: 10.3233/JIFS-230323

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8383-8403, 2023

Authors: Wang, Yubiao | Wen, Junhao | Zhou, Wei | Tao, Bamei | Wu, Quanwang | Fu, Chunlei | Li, Heng

Article Type: Research Article

Abstract: With the development of the Internet and the informatization construction of universities, the massive data accumulated by “campus big data” presents problems such as discreteness and sparseness. Students with abnormal behaviors have become an urgent problem to be solved in student behavior analysis. This paper proposes an early warning method for abnormal behaviour of college students based on multimodal fusion and an improved decision tree (EWMABCS-MFIDT). First, given the insufficient representation of student behavioral portraits and the problems of timeliness and dynamics in behavioral labels, a student behavioral portrait based on the multimodal fusion method is proposed. Second, aiming at …the timeliness and backwardness of abnormal behavior prediction, based on student behavior classification prediction, this paper proposes an improved decision tree-based early warning method for abnormal student behavior. Finally, we design a student behavior analysis and early warning framework under the campus big data environment. Taking the abnormal early warning of students’ academic performance as an example, compared with other early warning algorithms, the EWMABCS-MFIDT method can improve the accuracy of early warning and make students’ educational work more targeted, personalized, and predictive. Show more

Keywords: Education big data, student behavior portrait, multimodal fusion, abnormal behavior early warning, improved decision tree

DOI: 10.3233/JIFS-231509

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 5, pp. 8405-8427, 2023