Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Almarashi, Abdullah M. | Algarni, Ali | Abdel-Khalek, S. | Khalil, E.M.

Article Type: Research Article

Abstract:  In this article we estimate the nonlocal correlation between a two qubits and OF (optical field) initially started in the even deformed binomial distribution (EDBS). Explicit forms of the EDBS as the initial states of the RF are presented. We investigate the dynamical and statistical properties of the linear entropy as a quantifier of the correlation and purity of the proposed system. Also, the correlation between the two qubits is quantified by the negativity. Some statistical estimations of the RF are investigated by of Mandel parameter and compared by the two types of correlation The relation between the qubit inversion, …two qubits-RF nonlocal correlation, negativity and Mandel parameter is obtained. The effective of Stark shift on the dynamical operators for the RF distribution is examined. The results are shown the a high amount of field-qubit nonlocal is reached for a high value of deformation parameter. Also, the statistical properties of the field is Poissonian or sub-Poissonian photon distribution. Show more

Keywords: Even deformed binomial distribution, mandel parameter, negativity, nonlocal correlation

DOI: 10.3233/JIFS-179559

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Hsiao, Shou-Ching | Liu, Zi-Yuan | Tso, Raylin | Kao, Da-Yu | Chen, Chien-Ming

Article Type: Research Article

Abstract: Gated Recurrent Unit (GRU) has wide application fields, such as sentiment analysis, speech recognition, and other sequential data processing. For efficient prediction, a growing number of model owners choose to deploy the trained GRU models through the machine-learning-as-a-service method (MLaaS). However, deploying a GRU model in cloud generates privacy issues for both model owners and prediction clients. This paper presents the architecture of PrivGRU and designs the privacy-preserving protocols to complete the secure inference. The protocols include base protocols and principal protocols. Base protocols define basic linear and non-linear computations, while principal protocols construct the gating mechanisms of GRUs. The …main benefit of PrivGRU is to address privacy problems while enjoying the efficiency and convenience of MLaaS. The overall secure inference is performed on shares, which retain two properties of security: correctness and privacy. To prove the security, this work adopts Universal Composability (UC) framework with the honest-but-curious corruption model. As each protocol is proved to UC-realize the ideal functionality, it can be arbitrarily composed in any manner. This strong security feature makes PrivGRU more flexible and practical in future implementation. Show more

Keywords: Privacy-preserving, MLaaS, gated recurrent unit, additive secret sharing, UC framework

DOI: 10.3233/JIFS-179652

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Liu, Wei | Mao, Yu | Ci, Linlin | Zhang, Fuquan

Article Type: Research Article

Abstract:  It is not foolproof for intrusion detection to focus only on the network level and the program level. Internal security and external security of information systems should be given equal attention. User-level intrusion detection can deter and curtail attackers from damaging information systems. Even if the mimic attacker has gained and enhanced the host user privileges that he illegally obtained. In this paper, a novel method based on recurrent neural networks (RNNs) is used to predict user command sequences and prophesy user behaviors. The experimental results show that our command sequence-to-sequence model is robust and effective for solving long sequential …problem on three different data sets including Purdue University data set, SEA data set and self-collected data set. Show more

Keywords: User behavior, recurrent neural networks, anomaly intrusion detection, attacks and defenses

DOI: 10.3233/JIFS-179659

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Liu, Mingtang | Wang, Li | Qin, Zening | Liu, Jiaqi | Chen, Jian | Liu, Xuemei

Article Type: Research Article

Abstract: In order to make the feature data more linearly separable for support vector machine(SVM) classifier, a set of different scale and direction parameter was proposed for improving the recognition effect of cement slope damage in high fill channels. The Gabor wavelet was used to extract the multi-scale and multi-directional features of the high-fill channel’s abrupt features. Then SVM algorithm was utilized to perform damage classification and level recognition. To compare the recognition effect of the Gabor-SVM method, histogram-SVM, grayscale symbiotic matrix -SVM, canny-SVM algorithm were adopted to identify the damage degree of cement surface in the same environment, and these …damage recognition rates are compared with Gabor-SVM’s. The experimental results show that the damage recognition model, based on Gabor-SVM, tends to better stable value when the wavelet takes 6 scale and 12 directions. The recognition rate of the normal slope is 0.98, while the recognition rate of the crack, hole, and broken slope are 0.63, 0.88 and 0.90, respectively. Overall, the damage recognition model, based on Gabor-SVM, has better recognition effect, and it will provide technical support for finding potential leakage hazards in the high fill channel of South-to-North Water Diversion Project. Show more

Keywords: Key words: Middle route of South-to-North Water Diversion Project, Feature extraction of multiple scales and directions, damage recognition, Gabor wavelet, support vector machine

DOI: 10.3233/JIFS-190767

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Zhaoyan, Hu | Yonglong, Luo | Xiaoyao, Zheng | Yannian, Zhao

Article Type: Research Article

Abstract:  With the popularity of networks and the increasing number of online users, recommender systems have suffered from the privacy leakage of sensitive information. While people enjoy recommender services, their information is exposed to the networks. To protect the privacy of users when using the recommender services, we propose a multi-level combined privacy-preserving model that maintains high accuracy of recommendation with privacy protection and alleviates the data sparsity problem. Our scheme contains two steps of recommendation. First, a multi-level combined random perturbation (MCRP) model is proposed on the client side. Our model dynamically divides multiple disturbance levels and adds noise of …different ranges to the rating matrix according to Gaussian and uniform mixed disturbances. Second, on the server side, we propose a pseudo rating prediction filling (PRPF) algorithm based on the matrix factorization model. Combining the PRPF algorithm with the MCRP method significantly improves the recommender accuracy and effectively increases privacy security. Sensitive analysis and comparison experiments show that the proposed privacy method has certain advantages in security and recommender accuracy by using three publicly available datasets. Show more

Keywords: Recommender system, matrix factorization, privacy protection, random perturbation, sparse data

DOI: 10.3233/JIFS-191287

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Vinh An, Truong | Van Hoa, Ngo

Article Type: Research Article

Abstract:  In this work, we consider a new form of fuzzy fractional Volterra integral equations (FFVIEs) involving the generalized kernel functions. By using the monotone iterative technique (MIT) combined with the method of lower and upper solutions, the existence of extremal solutions of FFVIEs is established. Some examples are given to illustrate our main results.

Keywords: Fuzzy fractional integral equations, generalized kernel functions, extremal solutions, monotone iterative technique

DOI: 10.3233/JIFS-191746

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Xue, Z.-A. | Zhao, Li-Ping | Zhang, Min | Sun, Bing-Xin

Article Type: Research Article

Abstract: Three-way decisions have become a representative of the models dealing with decision-making problems with uncertainty and fuzziness. However, most of the current models are single granular structures that cannot meet the needs of complex fuzzy environmental decision-making. Multi-granulation rough sets can better deal with fuzzy problems of multiple granularity structures. Therefore, three-way decisions will be a more reasonable decision-making model to address uncertain decision problems in the context of multiple granularity structures. In this paper, firstly we propose the four different conditional probabilities based on support intuitionistic fuzzy sets, which are referred to as support intuitionistic fuzzy probability. Then, a …multi-granulation support intuitionistic fuzzy probabilistic approximation space is defined. Secondly, we calculate the thresholds α and β by the Bayesian theory, and construct four different types of multi-granulation support intuitionistic fuzzy probabilistic rough sets models in multi-granulation support intuitionistic fuzzy probabilistic approximation space. Moreover, some properties of lower and upper approximation operators of these models are discussed. Thirdly, by combining these proposed models with three-way decision theory, the corresponding three-way decision models are constructed and three-way decision rules are derived. Finally, an example of person-job fit procedure is given to prove and compare the validity of these proposed models. Show more

Keywords: Support intuitionistic fuzzy sets, rough sets, support intuitionistic fuzzy probabilistic, multi-granulation rough sets, three-way decisions

DOI: 10.3233/JIFS-191657

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2020

Authors: Vinh An, Truong | Van Hoa, Ngo

Article Type: Research Article

Abstract: In this work, a new class of generalized fractional integral equations involving the kernel ψ -function in the fuzzy setting is introduced. With this problem, we can recover a wide class of fractional fuzzy integral equations by choosing the kernel ψ -function. In this sense, we provide sufficient conditions for the existence, uniqueness of solutions and δ -Ulam-Hyers-Rassias stability of the given problems. Some examples are given to illustrate our main results.

Keywords: δ-Ulam-Hyers-Rassias, kernel ψ-functions, Fuzzy fractional integral equations

DOI: 10.3233/JIFS-191743

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Wu, Mu-En | Lin, Sheng-Hao | Wang, Jia-Ching

Article Type: Research Article

Abstract: The objective in using the Kelly criterion for money management is to maximize returns; however, in many cases, the risk level exceeds that which the investor can bear. In this study, we present an algorithm to calculate the bidding fraction, while taking into account the level of risk (i.e., the maximum drawdown). The proposed algorithm is based on ensemble learning with a combination of bagging and subset resampling. Our assessment results obtained using the FF48 (i.e., Fama-French-48) dataset revealed that when the maximum drawdown was 5% and 10%, ensemble learning outperformed the conventional approach by 2% and 4%, respectively.

Keywords: Kelly criterion, ensemble learning, Monte Carlo simulation, money managemen

DOI: 10.3233/JIFS-179654

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Qu, Junsuo | Qiao, Ning | Shi, Haonan | Su, Chang | Razi, Abolfazl

Article Type: Research Article

Abstract: In this paper, we designed a smart bracelet to realize human behavior recognition, remote monitoring, fall detection, alarm and other functions. We use a six-axis inertial measurement module to collect a large amount of human body posture data. The Kalman filter is used to preprocess the data of acceleration and gyroscope, and then the processed series data is segmented by sliding window method. At last these data are put into a convolutional neural network(CNN) to identify human activities. Furthermore, we designed a two-level fall behavior judgment, the first-level threshold determination is performed through smart bracelet, when a suspected fall behavior …occurred, the sequence data are uploaded to the cloud platform, the second CNN discriminant model is triggered to accurately determine whether a fall behavior occurs. Show more

Keywords: Convolutional neural network, human behavior recognition, fall detection

DOI: 10.3233/JIFS-179651

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020