Artificial Intelligence-Based Prediction of Individual Differences in Psychological Occupational Therapy Intervention Guided by the Realization of Occupational Values by Hongmei Jin, Yu Pang, Xiaohui Du, Leilei Shi

“…Finally, the predicted results of different groups of employees were compared, revealing the effectiveness of our algorithm.…”
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Induced spoofing detection method based on error valuation accumulation open-loop correction by Lunlong ZHONG, Jiongpo LIU, Yongyu LIU

“…Induced satellite spoofing interference can induce the aircraft to gradually deviate from the predetermined trajectory, and it is difficult to detect.So timely and effective detection of interference is the guarantee of flight safety.Based on the existing tightly integrated navigation system, an error valuation accumulation open-loop correction structure was designed.It was proved that the performance of the designed structure was equivalent to the performance of traditional tightly integrated navigation system with closed-loop correction.On the basis of designed structure, combining the tightly integrated navigation system with the adaptive sequential probability ratio test method, an induced spoofing detection method based on the error valuation accumulation open-loop correction was proposed.A spoofing detection statistic for induced spoofing detection was constructed by integrating the tightly integrated navigation information with other navigation information that was not affected by spoofing interference.Simulation results show that the designed open-loop correction structure can avoid the divergence problem of the integrated navigation filter caused by the inertial navigation system error accumulated over time.Moreover, the proposed spoofing detection method can improve the detection effect of the algorithm of the small induced spoofing under the “worst” case further.…”
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D2D cooperative caching strategy based on graph collaborative filtering model by Ningjiang CHEN, Linming LIAN, Pingjie OU, Xuemei YUAN

“…A D2D cooperative caching strategy based on graph collaborative filtering model was proposed for the problem of difficulty in obtaining sufficient data to predict user preferences in device-to-device (D2D) caching due to the limited signal coverage of base stations.Firstly, a graph collaborative filtering model was constructed, which captured the higher-order connectivity information in the user-content interaction graph through a multilayer graph convolutional neural network, and a multilayer perceptron was used to learn the nonlinear relationship between users and content to predict user preferences.Secondly, in order to minimize the average access delay, considering user preference and cache delay benefit, the cache content placement problem was modeled as a Markov decision process model, and a cooperative cache algorithm based on deep reinforcement learning was designed to solve it.Simulation experiments show that the proposed caching strategy achieves optimal performance compared with existing caching strategies for different content types, user densities, and D2D communication distance parameters.…”
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Accurate identification of oxygen desaturation status in COPD by using classifier ensemble. by Yue-Fang Wu, Xin Shu, Shiqi Wang, Xiaojun Xu, Pei-Li Sun

“…In the proposed method, five different features of each data point from the time series of SpO2 and pulse are extracted and then combined to form the discriminative feature of the corresponding data point; then, multiple base classifiers with different balanced training subsets are trained and then integrated by using AdaBoost Algorithm. The comparative computational results on the 6-min walk test (6MWT) of the recruited participants show that the proposed method achieved the best global performance with AUC (Area Under Curve) value of 0.8532, indicating that the proposed method can be effectively used for the identification of EIOD and could assist the clinic diagnosis of COPD.…”
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Tourism Demand Forecasting Based on Grey Model and BP Neural Network by Xing Ma

“…Secondly, in the structure algorithm of the BP neural network, the BP neural network model is established using the data series of travel time and the number of people. …”
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Throughput optimization of multi-hop and multi-path cooperation in WPSNs with hardware noises by Lina Yuan, Huajun Chen, Jing Gong

“…To enhance the minimum achievable data rate, we propose a multi-hop communication protocol based on time-division-multiple-access and an optimal throughput path algorithm. We formulate the time allocation optimization problem about energy and information transmission of the proposed multi-hop cooperation, and confirm through abundant simulation experiments that the proposed scheme can availably improve user unfairness and spectral efficiency, and thus enhance its throughput performance.…”
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Cloud-Assisted Scalable Video Delivery Solution over Mobile Ad Hoc Networks by Lujie Zhong, Shijie Jia

“…A novel supplier scheduling algorithm that assigns resource suppliers for fast responding user request in terms of their load and serving capacity is proposed. …”
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Development and application of machine learning models in US consumer price index forecasting: Analysis of a hybrid approach by Yunus Emre Gur

“…The data were combined with key economic indicators of the US, and the hyperparameters of the forecasting models were optimized using genetic algorithm and Bayesian optimization methods. According to the VAR model results, variables such as past values of CPI, oil prices (OP), and gross domestic product (GDP) have strong and significant effects on CPI. …”
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A Crude Oil Spot Price Forecasting Method Incorporating Quadratic Decomposition and Residual Forecasting by Yonghui Duan, Ziru Ming, Xiang Wang

“…Additionally, this work proposes to optimize the support vector regression model (SVR) by the seagull optimization algorithm (SOA). Ultimately, the empirical investigation created the feature-variable system and predicted the filtered features. …”
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Fault Diagnosis of PV Array Based on Time Series and Support Vector Machine by Ying Zhong, Bo Zhang, Xu Ji, Jieping Wu

“…Using the time series values as input data for a “one-to-one” multiclass classifier, we can identify and classify typical operational faults such as random shading, fixed shading, and aging degradation of PV arrays. The developed algorithmic model is trained and tested for different fault conditions using the data sets generated by the PV array simulation device. …”
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Investigation into effective mechanical properties of porous material produced by the additive manufacturing method by Seyed Mohammad Javad Tabatabaee, Mahdi Fakoor

“…Additive manufacturing techniques offer opportunities to create complex structures, and in this paper, we investigate the effective mechanical properties of porous material produced by the Fused Displacement Modeling (FDM) technique. We also propose an algorithm for generating a porous body containing irregularly shaped holes with arbitrary distributions in size and location while maintaining specific porosity. …”
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A stochastic artificial neural network model for investigating street vendor behavior in a night market by Pao-Kuan Wu, Tsung-Chih Hsiao, Ming Xiao

“…The artificial neural network model, which is renowned for its pattern classification abilities, is a type of deterministic algorithm. However, combining artificial neural network with Bayesian probability can convert the deterministic artificial neural network model into a stochastic artificial neural network model that is useful for conducting dynamic simulations. …”
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Application of deep residual networks to predict the effective properties of fiber-reinforced composites with voids by Mahdi Karimian, Seyed Ali Hosseini Kordkheili

“…In order to generate mechanical properties and image data for learning, appropriate RVEs together with periodic boundary conditions are used in FEMs. Using a random algorithm in RVEs, voids and fiber with different diameters are generated; the resulted composites consist of void and fiber volume fractions in the range of 0.00–0.03 and 0.40–0.65, respectively. …”
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Multicooperation of Turtle-inspired amphibious spherical robots by Liang Zheng, Yuke Ma, Hui Yu, You Tang

“…First, a novel underwater kinematic model using the unit quaternion (UQ) algorithm is proposed based on attitude interpolation to realize MDOF movement. …”
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Performance analysis of 60 GHz pulse multiuser communication system based on cross-layer strategy by Xuehua LI, Chen SHEN, Yuanyuan YAO

“…Due to the advantages of license-free,strong directionality,high system capacity,and high transmission rate of Gbit/s,60 GHz band is listed as one of the candidate bands for new radios (new radio).In 5G ultra-dense networking scenario,the randomness of node switching caused by the decrease of the distance between network nodes may cause severe multiple access interference and resource mismatch problems.In this regard,based on the concept of cross-layer collaborative design,a resource scheduling strategy based on fairness was proposed.The multiple access performance of the strategy was simulated in a 60 GHz pulsed wireless communication system based on TH-PAM (time hopping pulse amplitude modulation).Simulation results show that compared with the system with pure physical layer optimization algorithm,the multiple access system which adopts this strategy shows stronger fairness and lower system error rate,but it needs increase the transmission power to meet the requirements of the coverage of the equivalent communication system.That is,there is a certain trade-off between the energy and fairness of the system,which can be used to guide the structure and deployment of the actual communication system.…”
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Research on HMM based link prediction method in heterogeneous network by Rong QIAN, Jianting XU, Kejun ZHANG, Hongyu DONG, Fangyuan XING

“…In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM⁽¹⁾) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM⁽²⁾) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data.…”
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Multiagent Systems as an Approach to Building Fuzzy voter Communities using fuzzy languages by Milambu Belangany, Pierre Kasengadia Motumbe, Eugène Mbuyi Mukendi

“…The study introduces an algorithm to detect communities by creating links between fuzzy voters, ultimately forming groups based on their linguistic similarities. …”
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PREDICTION AND OPTIMIZATION ANALYSIS OF DURABILITY PERFORMANCE OF AUTOMOTIVE CLOSURES by GUO PengBo, LIU Zhe, LI Hui, GAO DaWei

“…Aiming at the fatigue failure problem of a car door opening and closing process.The Hypermesh was used to construct a finite element model of door opening and closing,and then Ls⁃Dyna,an explicit dynamics solver,was used to establish a nonlinear transient dynamics model of door opening and closing.The d3plot file containing the stress⁃time history solved by the nonlinear transient analysis was imported into nCode DesignLife to build the fatigue analysis module,and the results were verified with 100000 times of door opening and closing durability tests,and the conclusions show that both of them have good consistency in terms of the damage location and the damage degree.Finally,multi⁃particle swarm optimization(MPSO)was used to optimize the door with the objectives of door lightweight and minimum damage,and the optimal solution was selected according to the engineering reality,which reduced the mass of the door assembly by 0.17 kg,and the damage value of the door was reduced by about 24.33%.The optimization results show that the MPSO algorithm can be effectively applied to the multi⁃objective optimization design of the door,which provides certain ideas for the design and development of the subsequent door.…”
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FPGA multi-unit parallel optimization and implementation of post-quantum cryptography CRYSTALS-Kyber by Bin LI, Xiaojie CHEN, Feng FENG, Qinglei ZHOU

“…In lattice-based post-quantum cryptography, polynomial multiplication is complicated and time-consuming.In order to improve the computational efficiency of lattice cryptography in practical applications, an FPGA multi-unit parallel optimization and implementation of post-quantum cryptography CRYSTALS-Kyber was proposed.Firstly, the flow of Kyber algorithm was described and the execution of NTT, INTT and CWM were analyzed.Secondly, the overall structure of FPGA was given, the butterfly arithmetic unit was designed by pipeline technology, and the Barrett modulus reduction and CWM scheduling optimization were used to improve the calculation efficiency.At the same time, 32 butterfly arithmetic units were executed in parallel, which shortens the overall calculation cycle.Finally, the multi-RAM channel was optimized to improve the memory access efficiency with alternate data access control and RAM resource reuse.In addition, with the loosely coupled architecture, the overall operation scheduling was realized by DMA communication.The experimental results and analysis show that the proposed scheme implemented can complete NTT, INTT and CWM operations within 44, 49, and 163 clock cycles, which is superior to other schemes and has high energy efficiency ratio.…”
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A New Aerodynamic Optimization Method with the Consideration of Dynamic Stability by Mi Baigang, Wang Xiangyu

“…Then, combined with the PSO (particle swarm optimization) algorithm, a dynamic stability derivative that must not be decreased is added to the constraints of optimization and the lift-drag ratio is chosen as the optimization objective. …”
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