Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Wen, Bor-Jiunn | Lin, Yung-Sheng | Tu, Hsing-Min | Hsieh, Cheng-Chang

Article Type: Research Article

Abstract: This study proposes a cloud tele-measurement technique on an electromechanical system, and uses a neural network algorithm based on principal-component analysis (PCA) to quickly diagnose its performance. Three vibration, three temperature, electrical voltage, and current sensors were mounted on the electromechanical system, and the external braking device was used to provide different load-states to simulate the operating states of the motor under different conditions. Moreover, a single-chip multiprocessor was used through the sensor to instantly measure the various load-state simulations of the motor. The operating states of the electromechanical system were classified as normal, abnormal, and required-to-be-turned-off states using a …principal-component Bayesian neural network algorithm (PBNNA), to enable their quick diagnosis. Furthermore, PBNNA successfully reduces the dimensionality of the multivariate dataset for rapid analysis of the electromechanical system’s performance. The accuracy rates of health-diagnosis based on the Bayesian neural network algorithm and PBNNA models were obtained as 97.7% and 98%, respectively. Finally, the single-chip multiprocessor based on PBNNA is used to automatically upload the measurement and analysis results of the electromechanical system to the cloud website server. The establishment of this model system can optimize prediction judgment and decision-making based on the damage situation to achieve the goals of intelligence and optimization of factory reconstruction. Show more

Keywords: Tele-measurement, electromechanical system, principal-component bayesian neural network algorithm, health-diagnosis, cloud website server

DOI: 10.3233/JIFS-189587

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7671-7680, 2021

Authors: Cheng, Cheng-Feng | Chen, Ta-Cheng

Article Type: Research Article

Abstract: This study aims to explore the configurations of potential relevant antecedents in 3D printing medical Market for achieving high user satisfaction from both the suppliers’ and users’ perspectives. The important antecedents in this study include relationship marketing, innovation, 3D printing perceived values, and 3D printing perceived risk. Firstly, this study investigates the relationships among potential relevant antecedents and user satisfaction. Furthermore, to explore the gap between users’ evaluation and innovation suppliers’ perception, this study addresses this issue based on both perspectives of suppliers and buyers. To assess the applicability of the proposed model, we employed questionnaires survey and collected primary …data from 3D printing suppliers and their customers. Moreover, the fuzzy set qualitative comparative analysis (fsQCA) approach has been applied for evaluating the effectiveness of relationship marketing and innovation in 3D printing medical market. Finally, the numerical results indicate that there is one causal configuration (i.e. , 1A) found to be sufficient for high user satisfaction for the perspectives of 3D printing suppliers and three configurations for the perspectives of 3D printing customers. In the perspectives of 3D printing suppliers, the combination of relationship marketing, innovation, and 3D printing perceived value is sufficient conditions causing high user satisfaction. However, there are three causal configurations (i.e. , 1B, 2B, and 3B) found to be sufficient for high user satisfaction for the perspectives of 3D printing customers. Show more

Keywords: Relationship marketing, innovation, perceived value, perceived risk, user satisfaction, fuzzy set qualitative comparative analysis

DOI: 10.3233/JIFS-189588

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7681-7690, 2021

Authors: Chen, Yen-Hung | Chang, Arthur | Huang, ChunWei

Article Type: Research Article

Abstract: The cloud computing and Internet of Things (IoT) have become two key technologies to meet future business requirements. However, a massive scale of Distributed Denial-of-Service (DDoS) has been widely applied to congest network critical links and to paralyze the cloud and IoT service. This is mainly due to DDoS is easily implemented, obfuscated, and occulted by launching large-scale legitimate low-speed flows and rolling target links to paralyze target network areas. Many metrics and risk access management frameworks to evaluate the impact of DDoS are proposed. However, they all lack time granularity to evaluate the cost of different scales of attacks …in IoT or large-scale network structure. This study proposes an AI Driven Evaluation framework, called ADE, that applies Convolution Neural Networks to statistically evaluate the network status through end-to-end functionality (Input: network status; Output: DDoS detected or not) without any manual intervention. ADE provides quantitative security risk analysis by using learning time as the control variable, network structure as the independent variable, and time to identify DDoS as the dependent variable. The learning time to detect DDoS event and recover the system is then applied to evaluate the scale of this DDoS, the reasonability of the regulated RTO, and the vulnerability of the current net-work topology and the improvement due to the new security solution. The experiment results demonstrate the contributions of ADE are (1) providing objective and quantitative analytical security risk assessment indicator, (2) providing an autonomic DDoS defense framework without any manual intervention which allows cloud computing and Internet of Things company focuses on their service and leaves security defending to ADE, and (3) demonstrating the possibility of AI assisted risk assessment which enables security defense solution buyer with less security domain experts to evaluate suitable network defense strategy. Show more

Keywords: SDN, machine learning, IoT, mobile broadband, convolutional neural networks, distributed denial-of-service

DOI: 10.3233/JIFS-189589

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7691-7699, 2021

Authors: Hsieh, Yi-Chih | You, Peng-Sheng

Article Type: Research Article

Abstract: In this study, we investigate a new multi-maintenance with sequential operation (MMSO) problem, in which a variety of tasks must be processed on multiple machines. In the MMSO problem, each task has multiple sequential operations that must be processed for each machine. In addition to maintenance, the MMSO problem has many other practical applications, such as physical examination scheduling. The proposed MMSO, which is an NP-hard problem, generalizes typical job shop scheduling problems. Thus, a novel encoding scheme, which is embedded into an immune-based algorithm (IBA), is proposed in this study to convert any sequence of random numbers into a …feasible solution of the MMSO problem to solve the MMSO problem. Numerical results of applications in aircraft maintenance and physical examination scheduling are reported and compared with those of particle swarm optimization and genetic algorithm. Experimental results show that IBA outperforms the two other algorithms. Show more

Keywords: Scheduling, maintenance, sequential operations, immune-based algorithm, optimization

DOI: 10.3233/JIFS-189590

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7701-7710, 2021

Authors: You, Peng-Sheng | Hsieh, Yi-Chih

Article Type: Research Article

Abstract: Leveraging their networks, bike rental companies usually provide customers with services for renting and returning bikes at different bike stations. Over time, however, rental networks may encounter problems with unbalanced bike stocks. The potential imbalance between supply and demand at bike stations may result in lost sales for stations with relatively high demand and underutilization for stations with relatively low demand. This paper proposed a constrained mixed-integer programming model that uses operator-based redistribution and user-based price approach to rebalance bikes across bike stations. This paper aims to maximize total profit over a planning horizon by determining operator-based bike transfers and …dynamic pricing. The proposed model is a non-deterministic polynomial-time problem, and thus, a heuristic was developed based on linear programming and evolutionary computation to perform model solving. Numerical experiments reveal that the proposed method performed better than Lingo, a well-known commercial software. Sensitivity analyses were also performed to investigate the impact of changes in system parameters on computational results. Show more

Keywords: Bike-rental, rebalancing, operator-based redistribution, user-based price, mixed integer programming, heuristic

DOI: 10.3233/JIFS-189591

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7711-7722, 2021

Authors: Wang, Sheng-Chuan | Chen, Ta-Cheng

Article Type: Research Article

Abstract: Multi-objective competitive location problem with cooperative coverage for distance-based attractiveness is introduced in this paper. The potential facilities compete to be selected to serve all demand points which are determined by maximizing total collective attractiveness of all demand points from assigned facilities and minimizing the fixed and distance costs between all demand points and selected facilities. Facility attractiveness is represented as a coverage of the facility with full, partial and none coverage corresponding to maximum full and partial coverage radii. Cooperative coverage, which the demand point is covered by at least one facility, is also considered. The problem is formulated …as a multi-objective optimization model and solution procedure based on elitist non-dominated sorting genetic algorithms (NSGA-II) is developed. Experimental example demonstrates the best non-dominated solution sets obtained by developed solution procedure. Contributions of this paper include introducing competitive location problem with facility attractiveness as a distance-based coverage of the facility, re-categorizing facility coverage classification and developing solution procedure base upon NSGA-II. Show more

Keywords: Competitive location problem, facility attractiveness, distance-based coverage, cooperative coverage, elitist non-dominated sorting genetic algorithms (NSGA-II)

DOI: 10.3233/JIFS-189592

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7723-7734, 2021

Authors: Heo, Tak-Sung | Kim, Jong-Dae | Park, Chan-Young | Kim, Yu-Seop

Article Type: Research Article

Abstract: Sentence similarity evaluation is a significant task used in machine translation, classification, and information extraction in the field of natural language processing. When two sentences are given, an accurate judgment should be made whether the meaning of the sentences is equivalent even if the words and contexts of the sentences are different. To this end, existing studies have measured the similarity of sentences by focusing on the analysis of words, morphemes, and letters. To measure sentence similarity, this study uses Sent2Vec, a sentence embedding, as well as morpheme word embedding. Vectors representing words are input to the 1-dimension convolutional neural …network (1D-CNN) with various sizes of kernels and bidirectional long short-term memory (Bi-LSTM). Self-attention is applied to the features transformed through Bi-LSTM. Subsequently, vectors undergoing 1D-CNN and self-attention are converted through global max pooling and global average pooling to extract specific values, respectively. The vectors generated through the above process are concatenated to the vector generated through Sent2Vec and are represented as a single vector. The vector is input to softmax layer, and finally, the similarity between the two sentences is determined. The proposed model can improve the accuracy by up to 5.42% point compared with the conventional sentence similarity estimation models. Show more

Keywords: Sentence similarity, siamese network, Sent2vec, convolutional neural network, self-attention

DOI: 10.3233/JIFS-189593

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7735-7744, 2021

Authors: Oh, Byoung-Doo | Lee, Yoon-Kyoung | Song, Hye-Jeong | Kim, Jong-Dae | Park, Chan-Young | Kim, Yu-Seop

Article Type: Research Article

Abstract: Speech pathology is a scientific study of speech disorders. In this field, the study also analyzes and evaluates language abilities for the purpose of improving speech and hearing. Speech therapy first performs evaluation of speech ability, which is expensive. In order to solve this problem, software methodologies have been applied to language analysis, but most of them have been applied to only part of the whole process. In this study, the degree of language development is judged by determining the age group of the speaker (Pre-school children, Elementary school, Middle and high school, Adults, and Senior citizen) using deep learning …and simple statistics. We use transcription data from the counseling contents and multi-kernel CNN model. At this time, in order to understand the characteristics of Korean language belonging agglutinative languages, experiments are carried out in words, morphemes, characters, Jamo, and Jamo with POS tag-level. And we analyze the distribution of the results for each sentence of the speakers to predict their age groups and to check the degree of language development. The proposed model shows an average accuracy of about 74.6 %. Show more

Keywords: Language analysis, age group analysis, convolutional neural networks, deep learning, statistical analysis

DOI: 10.3233/JIFS-189594

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7745-7754, 2021

Authors: Chen, Lili

Article Type: Research Article

Abstract: These years, the laboratory safety situation in Colleges and universities has improved, but the safety problem still needs to be improved. Based on the research basis of previous literature, this paper extracts the causes of laboratory accidents in Colleges and universities in the past six years, uses the grey system theory to carry out correlation analysis, sorts the correlation degree of influencing factors of laboratory safety behavior, and through empirical analysis, the organization system, safety education, laboratory environment management, foundation safety ,professional safety show a decreasing relationship in the influencing factors of laboratory safety. On the basis of this conclusion, …the safety management path of related laboratories is proposed: Improve the laboratory organization and management system; carry out safety education regularly; strict professional operation process; orderly laboratory environment; effective basic safety management. These path studies have positive practical significance for laboratory safety management. Show more

Keywords: University Laboratory Safety, analysis of grey correlation degree, Security management path

DOI: 10.3233/JIFS-189596

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7755-7762, 2021

Authors: Hsieh, Yi-Chih | You, Peng-Sheng | Chuang, Hao-Chun

Article Type: Research Article

Abstract: In this paper, we study the forest harvesting problem (FHP). A forest is assumed to be divided into several identical square units, and each unit has its harvesting value based on its type. Harvesting a unit will affect the growth and values of its neighboring units. In this FHP, the best harvesting plan of a unit must be identified to maximize three various objectives simultaneously. The FHP is a multiobjective mathematical and an NP-hard problem. We apply three artificial intelligence algorithms, namely, immune algorithm, genetic algorithm, and particle swarm optimization, for maximizing the weighted objective to solve the FHP. We …also solve the following two sets of test problems: (i) a set of randomly generated FHP problems and (ii) a practical problem in Taiwan. Numerical results show the performance of the three algorithms for the test problems. Finally, we compare and discuss the effects of various weights for the three objectives. Show more

Keywords: Forest harvesting problem, optimization, immune algorithm, genetic algorithm, particle swarm optimization

DOI: 10.3233/JIFS-189597

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7763-7774, 2021