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High capacity reversible data hiding in encrypted images based on adaptive quadtree partitioning andMSB prediction Research Article

Kaili QI, Minqing ZHANG, Fuqiang DI, Yongjun KONG,1804480181@qq.com

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8,   Pages 1156-1168 doi: 10.1631/FITEE.2200501

Abstract: To improve the embedding capacity of , a new RDH-EI scheme is proposed based on and most significantbit (MSB) prediction.In the data embedding stage, the adaptive MSB prediction method proposed by Wang and He (2022) is improved

Keywords： Adaptive quadtree partitioning     Adaptive most significant bit (MSB) prediction     Reversible data hiding    

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: Concrete compressive strength prediction is an essential process for material design and sustainabilityThis study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionaryANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive    

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An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings

Yanfeng PENG, Junsheng CHENG, Yanfei LIU, Xuejun LI, Zhihua PENG

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 301-310 doi: 10.1007/s11465-017-0449-7

Abstract: obtaining the health states, appropriate features are selected by DET for increasing the classification and predictionIn the prediction process, each vibration signal is decomposed into several components by empirical mode

Keywords： Gaussian mixture model     distance evaluation technique     health state     remaining useful life     rolling bearing    

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The most influential “Top 10 Events” in carbon neutrality and climate change in 2022

Frontiers in Energy 2023, Volume 17, Issue 1,   Pages 1-4 doi: 10.1007/s11708-023-0869-5

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Prediction of falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptive

Frontiers of Structural and Civil Engineering   Pages 812-826 doi: 10.1007/s11709-023-0940-7

Abstract: ., a genetic algorithm (GA)-optimized adaptive neuro-fuzzy inference system (ANFIS-GA), to predict Y1

Keywords： falling weight deflectometer     modulus of subgrade reaction     elastic modulus     metaheuristic algorithms    

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Coverage performance of the multilayer UAV-terrestrial HetNet with CoMP transmission scheme Research Article

Weihao WANG, Yifan JIANG, Zesong FEI, Jing GUO,weihaowang@bit.edu.cn,jiangyifan@bit.edu.cn,feizesong@bit.edu.cn,jingguo@bit.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 1,   Pages 61-72 doi: 10.1631/FITEE.2100310

Abstract: To support the ubiquitous connectivity requirement of sixth generation communication, s (UAVs) play a key role as a major part of the future communication networks. One major issue in UAV communications is the interference resulting from spectrum sharing and line-of-sight links. Recently, the application of the technology has been proposed to reduce the interference in the UAV-terrestrial heterogeneous network (HetNet). In this paper, we consider a three-dimensional (3D) multilayer UAV-terrestrial HetNet, where the aerial base stations (ABSs) are deployed at multiple different altitudes. Using stochastic geometry, we develop a tractable mathematical framework to characterize the aggregate interference and evaluate the coverage probability of this HetNet. Our numerical results show that the implementation of the CoMP scheme can effectively reduce the interference in the network, especially when the density of base stations is relatively large. Furthermore, the system parameters of the ABSs deployed at higher altitudes dominantly influence the of the considered 3D HetNet.

Keywords： Unmanned aerial vehicle     Poisson point process     Coordinated multipoint (CoMP)     Statistics of interference     Coverage performance    

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Erratum to: On the potential of iPhone significant location data to characterize individual mobility

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 9, doi: 10.1007/s11783-022-1556-1

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Minimax Q-learning design for H∞ control of linear discrete-time systems Research Articles

Xinxing LI, Lele XI, Wenzhong ZHA, Zhihong PENG,lixinxing_1006@163.com,xilele.bit@gmail.com,zhawenzhong@126.com,peng@bit.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3,   Pages 438-451 doi: 10.1631/FITEE.2000446

Abstract: The method is an effective approach for attenuating the effect of disturbances on practical systems, but it is difficult to obtain the ler due to the nonlinear Hamilton–Jacobi–Isaacs equation, even for linear systems. This study deals with the design of an ler for linear discrete-time systems. To solve the related game algebraic Riccati equation (GARE), a novel model-free method is developed, on the basis of an offline algorithm, which is shown to be Newton’s method for solving the GARE. The proposed method, which employs off-policy , learns the optimal control policies for the controller and the disturbance online, using only the state samples generated by the implemented behavior policies. Different from existing -learning methods, a novel gradient-based policy improvement scheme is proposed. We prove that the method converges to the saddle solution under initially admissible control policies and an appropriate positive learning rate, provided that certain persistence of excitation (PE) conditions are satisfied. In addition, the PE conditions can be easily met by choosing appropriate behavior policies containing certain excitation noises, without causing any excitation noise bias. In the simulation study, we apply the proposed method to design an load-frequency controller for an electrical power system generator that suffers from load disturbance, and the simulation results indicate that the obtained load-frequency controller has good disturbance rejection performance.

Keywords： H∞ control     Zero-sum dynamic game     Reinforcement learning     Adaptive dynamic programming     Minimax Q-learning    

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Presentation of machine learning methods to determine the most important factors affecting road traffic

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 5,   Pages 657-666 doi: 10.1007/s11709-022-0827-z

Abstract: For more accurate prediction, Multi-Layer Perceptron (MLP) and Radius Basis Function (RBF) neural networksAmong the models, MLP had a better performance, so that the prediction accuracy of MLR, MLP, and RBFdue to higher accuracy, showed that the variable of reason of accident had the highest effect on the predictionthe variables of not paying attention to the front and then vehicle-motorcycle/bike accidents had the most

Keywords： safety     rural accidents     multiple logistic regression     artificial neural networks    

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On the potential of iPhone significant location data to characterize individual mobility for air pollution

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 5, doi: 10.1007/s11783-022-1542-7

Abstract:

● We evaluated the accuracy of iPhone data in capturing time-activity patterns.

Keywords： Air pollution exposure     Human mobility     iPhone     Significant Location     Smartphone data    

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Characterization of the genes involved in nitrogen cycling in wastewater treatment plants using DNA microarray and most

Junqin PANG, Masami MATSUDA, Masashi KURODA, Daisuke INOUE, Kazunari SEI, Kei NISHIDA, Michihiko IKE

Frontiers of Environmental Science & Engineering 2016, Volume 10, Issue 4, doi: 10.1007/s11783-016-0846-x

Abstract: nitrogen cycling genes in various processes of municipal WWTPs by employing two molecular-based methods:mostFurthermore, most processes in the WWTPs that were researched shared a pattern:the and the bacterial

Keywords： DNA microarray analysis     Nitrogen cycling functional genes     Most probable number-polymerase chain reaction    

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The World’s Most Powerful Rocket

Mitch Leslie

Engineering 2019, Volume 5, Issue 5,   Pages 822-823 doi: 10.1016/j.eng.2019.08.010

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Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control

Cong-ying Cai, Xiao-lan Yao,yaoxiaolan@bit.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 10,   Pages 1413-1534 doi: 10.1631/FITEE.1900586

Abstract: super giant slalom (Super-G) is a speed event in alpine skiing, in which the skier trajectory has a significant
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A review of cooperative path planning of an unmanned aerial vehicle group

Hao Zhang, Bin Xin, Li-hua Dou, Jie Chen, Kaoru Hirota,brucebin@bit.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 12,   Pages 1671-1814 doi: 10.1631/FITEE.2000228

Abstract: As a cutting-edge branch of unmanned aerial vehicle (UAV) technology, the of a group of UAVs has attracted increasing attention from both civil and military sectors, due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks, e.g., search and rescue, fire-fighting, reconnaissance, and surveillance. Cooperative (CPP) is a key problem for a UAV group in executing tasks collectively. In this paper, an attempt is made to perform a comprehensive review of the research on CPP for UAV groups. First, a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements, i.e., task, UAV group, and environment, as a basis for a comprehensive classification of different types of CPP problems. By following the proposed framework, a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified way. Then, a review and a statistical analysis are presented based on the taxonomy, emphasizing the coordinative elements in the existing CPP research. In addition, a collection of challenging CPP problems are provided to highlight future research directions.
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Optimal one-bit perturbation in Boolean networks based on cascading aggregation Research Articles

Jin-feng PAN, Min MENG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 2,   Pages 294-303 doi: 10.1631/FITEE.1900411

Abstract: We investigate the problem of finding optimal one-bit perturbation that maximizes the size of the basinnecessary and sufficient condition is given to ensure the invariance of desired attractors after one-bitSecond, an algorithm is proposed to identify whether the one-bit perturbation will cause the emergenceNext, the change of the size of BOAs after one-bit perturbation is provided in an algorithm.

Keywords： Large-scale Boolean network     Attractor     Cascading aggregation     One-bit perturbation    

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Title Author Date Type Operation

High capacity reversible data hiding in encrypted images based on adaptive quadtree partitioning andMSB prediction

Kaili QI, Minqing ZHANG, Fuqiang DI, Yongjun KONG,1804480181@qq.com

Journal Article

Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings

Yanfeng PENG, Junsheng CHENG, Yanfei LIU, Xuejun LI, Zhihua PENG

Journal Article

The most influential “Top 10 Events” in carbon neutrality and climate change in 2022

Journal Article

Prediction of falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptive

Journal Article

Coverage performance of the multilayer UAV-terrestrial HetNet with CoMP transmission scheme

Weihao WANG, Yifan JIANG, Zesong FEI, Jing GUO,weihaowang@bit.edu.cn,jiangyifan@bit.edu.cn,feizesong@bit.edu.cn,jingguo@bit.edu.cn

Journal Article

Erratum to: On the potential of iPhone significant location data to characterize individual mobility

Journal Article

Minimax Q-learning design for H∞ control of linear discrete-time systems

Xinxing LI, Lele XI, Wenzhong ZHA, Zhihong PENG,lixinxing_1006@163.com,xilele.bit@gmail.com,zhawenzhong@126.com,peng@bit.edu.cn

Journal Article

Presentation of machine learning methods to determine the most important factors affecting road traffic

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

Journal Article

On the potential of iPhone significant location data to characterize individual mobility for air pollution

Journal Article

Characterization of the genes involved in nitrogen cycling in wastewater treatment plants using DNA microarray and most

Junqin PANG, Masami MATSUDA, Masashi KURODA, Daisuke INOUE, Kazunari SEI, Kei NISHIDA, Michihiko IKE

Journal Article

The World’s Most Powerful Rocket

Mitch Leslie

Journal Article

Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control

Cong-ying Cai, Xiao-lan Yao,yaoxiaolan@bit.edu.cn

Journal Article

A review of cooperative path planning of an unmanned aerial vehicle group

Hao Zhang, Bin Xin, Li-hua Dou, Jie Chen, Kaoru Hirota,brucebin@bit.edu.cn

Journal Article

Optimal one-bit perturbation in Boolean networks based on cascading aggregation

Jin-feng PAN, Min MENG

Journal Article