Abstract:Traditional units of genome-wide association studies have serious defects such as low repeatability, difficulty to interpret, and epistasis analysis based on machine learning has troubles such as high computational complexity and insufficient prediction accuracy. This paper presented a new approach for the analysis of genome-wide epistatic. This method uses the framework of two-phase epistatic analysis method. It includes a filtering stage and an epistatic combinatorial optimization stage. The characteristics of the filtering stage presents a multicriteria fusion strategy for the evaluation of genetic loci from multiple perspectives to ensure that the weak effect of susceptibility loci can be retained, and then, this method uses the multiple criteria sorting fusion strategy to eliminate the low degree of genetic variation associated with disease states. Epistatic combinatorial optimization phase uses the greedy algorithm combination of heuristic search space in order to reduce the time complexity. Finally, a support vector machine was used as the epistatic evaluation model. Experiments with different parameters of linkage disequilibrium SNPruler with classical algorithms were compared with the performance of the ACO, and the experiment results show that the method can effectively keep weak effect locus and improve disease forecasting accuracy considerably.

Abstract:Aiming at the problem that the trajectory prediction error in existing vehicle collision warning system(CWS) is relatively large, a DGPS and other vehicle sensors based vehicle trajectory prediction was proposed. Real time vehicle position estimate was realized by using extended Kalman filter (EKF). Then, constant rate of acceleration change, constant yaw rate acceleration model for vehicle position prediction and V2X technology based cooperative collision warning system(CCWS) were proposed. Based on this, the longitudinal control simulation was realized by using fuzzy theory to validate the method. The simulation results show that the vehicle position prediction model based on constant rate of acceleration change, constant yaw rate acceleration model has lower error, and zCWS can get warnings or brake earlier.

Abstract:This paper took an SUV vehicle as the prototype, established a frequency-domain model of vehicle with KDSS-fitted, based on the transfer matrix method to derive the impedance matrix of hydraulic subsystem, solved the eigenvalue in numerical optimization iteration method, compared and analyzed the modal parameters of KDSS-fitted vehicle, ARB-fitted vehicle and no-ARB-fitted vehicle model. The results indicate that KDSS is able to effectively reduce the roll motion of sprung mass in the same way as anti-roll bar, and simultaneously maintain the ride comfort performance. At the same time, the wheel torsion stiffness, compared with ARB, is greatly reduced. This gives the wheels full contact with the ground and improves the passing ability of the vehicle.

Abstract:To meet the demands of today's market fast fine design and to solve the bulk material conveying machinery's problem of long cycle of product design and slow process of optimization, we developed a platform of rapid design system for bulk material conveying machinery. Taking the bucket and wheel body of a company's bucket wheel mechanism as an examples, we firstly built parametric dimension driven design models, and then used the finite element analysis software to establish multi-objective optimization models based on the principle of parametric, realized the quick optimization of product design, and improved the design efficiency and the accuracy of the complex steel structure. Finally, the parametric design and parametric analysis of the optimization module were highly integrated and the rapid design system platform was completed. Users can use the interactive interface of the rapid design system platform input parameters to get the product they need. The example has indicated that the rapid design system has good application prospects in the serialization development of bulk material conveying machinery.

Abstract:In order to improve the consistency for lithium-ion power battery of electric vehicle, to raise the available power and the utilization ratio of capacity for the battery pack, this paper put forward a battery sorting method based on the inconsistency mechanism analysis of battery. Firstly, the traditional sorting method, the main factor sorting method and the total factor sorting method for battery were completed respectively, and the comparative results show that the total factor sorting method is optimal. Secondly, the dynamic characteristics sorting was carried by fuzzy c-means clustering algorithm based on the total factor sorting results. Finally, the sorting effect was verified through experiments and the result shows that this sorting method can improve the inconsistency for battery pack effectively, and has a certain practical significance.

Abstract:The analysis and test of a rear wheel pulsed active steering control strategy was proposed. First, the effect of installation and operation of hydraulic pulse actuator on the suspension parameters and the improvement of the vehicle's steady and transient state response due to the control of active pulse were investigated. Second, a full vehicle model of a SUV equipped with the steering actuator was built in Carsim and co-simulated with Simulink as the control module.The structure of control strategy considering yaw rate error and side-slip angle error was designed to improve the stability and path. Finally, a whole test bed was designed and assembled for a SUV to carry out road experiments with different maneuvers to validate the results obtained from the simulations and to assess the applicability of the pulsed active steering system. Simulation and test results have indicated that considerable improvement in the yaw stability control can be achieved. Meanwhile, the rear wheel pulse active controller can reduce the lateral acceleration and the roll angle.

Abstract:In order to study the biomechanical response and injury mechanisms of pedestrian`s lower limb during impact, a three-dimensional FE model of lower limb for adult pedestrians with high precision was developed on the basis of human anatomical structure. The lower limb model included complete anatomical structure of femur, tibia, fibula, patella as well as soft tissues such as skin, fresh, ligaments, capsule meniscus and cartilage. Considering the nonuniformity of the section of cortical bone, a long bone model was developed based on CT data with the thickness and the shape of the cortical bone section varying continuously. In comparison with other modeling methods, cortical bone was modeled with two-layer solid elements to obtain higher precision and efficiency. The injury criterions of pedestrians′ lower limb such as the ultimate bending moment of femur and tibia were obtained by modeling related biomechanical experiments. In addition, the influence of the thickness of cortical bone and the impact direction to injury mechanism and injury parameters of lower limb were analyzed. The injury parameters can provide important reference for the design of cars.

Abstract:Aimingat on the coupling between the multi-valve structure of the conventional hydraulic excavator and the machine performance，the no-matching problem of machine control generated by the low precision of hydraulic control system, a parameter turning method of control system based on electronically controlled multi-valve of hydraulic excavator was proposed to achieve simplified design of hydraulic excavator multi-valve and adaptive change of the machine control systems. The output of electrical control handles was defined as 0-1 digital signal. Considering the structural characteristics of the multi-valve，the first-order control system of variable parameters for electronically controlled multi-valve of the hydraulic excavator is designed. An evaluating algorithm of parameter tuning was put forward, combining the system shock，energy efficiency，and the following performance. By designing hardware-in-Loop simulation, which is formed of the electrical control handles, controller, performance digital platform of hydraulic excavator, it shows that the control systems are effective, and the parameter T and K of the first-order control system，which the controller responds to，can base on the machine performance to be tuned. It is also found that time constant T can be determined by the natural frequency of multi-valve spool and the valve opening，and has smaller correlation with the spool-valve damping ratio. The design method of the hydraulic excavator provides good application value for the machine multi-valve design，which is associated with the design of control and operation.

Abstract:Gray model is widely used in mid-long term electricity demand forecasting, but the model fits exponentially increasing data more precisely. Due to China's economic growth rate fluctuations, the increase in electricity consumption is slowing down, and electricity varies stochastically. So it is necessary to propose a new model to reflect the new situation. To solve the problem of the poor anti-interference ability of grey model, this paper proposes a model with Fourier series and Markov theory residual error correction based on grey model. This model applies Fourier series method to optimize electricity changing rate, and Markov chain method to embed the random property in gray forecasting model for doubly correcting the residual error, which can improve the adaptability and flexibility. The proposed model is verified by actual load data, and it indeed improves the forecasting accuracy.

Abstract:In order to improve the prediction accuracy of the output power of the wind farm under the premise of ensuring safe operation, a combination of wind power forecasting model based on Ensemble Empirical Mode of Decomposition (EEMD), Improved Gravitational Search Algorithm (IGSA) and Least Squares Support Vector Machine (LSSVM) was established. Firstly, the wind power time series was decomposed into a series of subsequences with significant differences in complexity by using EEMD algorithm. Secondly, the decomposed subsequence was reconstructed by the phase space reconstruction (PSR), and then, an IGSA-LSSVM prediction model of each sub-sequence reconstructed was established respectively. In order to analyze the differences of LSSVM which sets up different kernel functions, eight kinds of kernel function LSSVM prediction models were established, and the IGSA algorithm was adopted to solve those models. Finally, taking a wind farm in Inner Mongolia of China as an example, the simulation and calculation results illustrate that LSSVM prediction model based on the exponential radial basis kernel function and penalty factor obtained by using the IGSA algorithm has higher prediction accuracy. Compared with five conventional combined models such as EMD-WNN and EMD-PSO-LSSVM, the combined model EEMD-IGSA-LSSVM of exponential radial basis kernel function mentioned above can forecast wind power in an effective and accurate way.

Abstract:In traditional UHVDC transmission systems, the filtering and reactive power compensation devices are generally installed at the power grid side of the converter stations. In order to reduce the negative effects caused by harmonic currents on the converter transformers, a harmonic suppression method of inductive filtering converter transformers with parallel filtering windings was proposed. This paper described the corresponding detailed wiring schemes, explained the filtering mechanism and compared it with the traditional filtering solution. Referring to the engineering parameters of the Jiuquan-Hunan ±800 kv UHVDC transmission project, the simulation models of the proposed harmonic filtering scheme and the traditional schemes were established respectively. Based on the comparative analysis of the currents at the grid and valve sides of the two models, it can come to the conclusion that the proposed harmonic suppression scheme has a better operational performance in contrast with the traditional one.

Abstract:Permanent magnet synchronous generator is directly connected with PWM converter in the wind power system based on direct-driven permanent magnet synchronous generator, which results in the increase of the stator losses of the permanent magnet synchronous generator, and even leads to the irreversible demagnetization of permanent magnet materials. To solve this problem, this paper analyzed the influence of amplitude modulation radio and frequency modulation radio on eddy current losses and stator losses of permanent magnet synchronous generator under SVPWM modulation. Finally, this paper compared the results of AnSoft simulation and Fourier analysis with the results obtained from the calculation models of this paper, which verifies the correctness of the calculation model proposed. The calculation models presented have reference value for setting proper amplitude modulation radio and frequency modulation radio under SVPWM modulation. This can ensure the safe operation of the permanent magnet synchronous generator.

Abstract:To meet the requirements of acquisition, transport and spot efficient processing of the received signal in shallow surface frequency-domain electromagnetic detection, a digital processing system for shallow surface frequency-domain electromagnetic detection based on FPGA+DSP was proposed. Data acquisition, control, and transmission FIFO module were compiled in FPGA. New universal parallel port UPP was used to achieve high data transfer. Efficient data processing algorithm was written with orthogonal lock-in amplification method based on TMS320C6748. The system was controlled and the results were displayed with PC software through the RJ45 network port. Test results have shown that the digital processing system of the proposed architecture for different metals has a strong ability of discovery. Data transmission rate is accelerated, system working time is shortened and work efficiency is improved.

Abstract:A new method based on optimized TLD (Track-Learning-Detection) and SVM (Support Vector Machine) for tracking pedestrian was proposed. First, with pedestrians as positive samples and the background as negative samples respectively, HOG (Histogram of Oriented Gradient) descriptor of pedestrian was extracted and combined with linear SVM to train the pedestrian classifier，which was used to obtain the calibrated pedestrian area accurately. Then, adaptive tracking and online learning on the pedestrians on the basis of TLD were integrated to estimate the reliability of the positive and negative samples, to rectify error existing in the current frame caused by detection and to update the tracking data simultaneously to avoid subsequent similar mistakes. The experiment results demonstrate that, compared with the conventional tracking algorithm, the proposed algorithm can not only significantly adapt to occlusions and appearance changes but also automatically identify and track pedestrian targets at arbitrary position, manifesting stronger robustness.

Abstract:To meet the demand of ankle rehabilitation training in degree of freedom (DOF), workspace and stiffness, this paper proposed a three-DOF parallel mechanism with a novel 3RPS/UPS structure. By adding a redundant driving chain with UPS structure under the foundation of the conventional 3RPS mechanism, the proposed structure can meet the demand of DOF and enhance the stiffness simultaneously. Consequently, the shaking and deformation of the operating platform is decreased, and the operation accuracy is improved as well. In this paper, we conducted a systematic analysis on the aspect of inverse kinematics, workspace and stiffness, and then demonstrated the feasibility of the proposed 3RPS/UPS structure to ankle rehabilitation training with the characteristics of heavy-load, microoperation and so on. To verify the applicability in practical operation of the proposed 3RPS/UPS structure, we conducted kinematics control simulation and obtained a high accuracy in dynamic trajectory tracking.

Abstract:Starting from the Maxwell equations, this article studied the boundary conditions of 3D MT. By using the weighted residual method, we derived the three-dimensional MT finite element equation. The three-dimensional vector finite element hexahedral meshing mode was introduced and the basis functions were selected. Then we derived the three-dimensional magnetotelluric vector finite element stiffness coefficient matrix and discrete format. A three-dimensional vector finite element magnetotelluric forward Matlab program was done. The apparent resistivity curve of the dimensional COMMEMI 3D-1 model matches the international standard test data, which proves the correctness of 3D magnetotelluric forward program. With the analysis of high and low resistivity anomalies, it shows that tensor impedance map can roughly determine the anomaly characteristics, which enriches the magnetotelluric response characteristics of expression.

Abstract:In order to improve the efficiency of cloud service selection and to guarantee trustworthy, available and reliable cloud service, a new model of cloud service selection based on trust trend was proposed. Base on this model, we firstly calculated the determined trust value in two parts: trust value and trust trend value (TTV). Trust value was calculated with Bayes theorem. Trust trend value was calculated with least squares linear regression. Trust trend value aims to illustrate the trust trend of changes in a given period. Then, we obtained the objective QoS value in the QoS quantitative model of could services. At the same time, the measuring strategy of trust relationship among cloud services was designed based on information entropy. The experiment result shows that this method can reflect changes in trust cloud services, enhance the predictive ability and effectively improve the success rate of cloud service selection.

Abstract:An approximate algorithm of Top-k query based on sampling and weight in wireless sensor network was presented. The algorithm divides the network into several disjoint clusters in the sink node and the nodes in cluster to take sampling process. In the process of sampling, greater weight for reliable and important sensor node is given. The sensor node sensing data has a time correlation, and sampling threshold filtering in the cluster. Each cluster head node receives a Top-k candidate subset of the cluster, and then sends the subset to the sink node. Finally, the sink node can receive a Top-k sample candidate that represents the whole network. Simulation experiments show that the algorithm only needs to send small data and smaller samples, and can satisfy arbitrary precision requirements.

Abstract:To address the task scheduling problem in distributed systems, based on an important feature of task scheduling in distributed computing environment, we have established a non-cooperative game framework for multi-layer multi-role, and put forward a distributed reinforcement learning algorithm of the joint scheduling strategy of Nash equilibrium. Compared with static scheduling algorithm, the proposed algorithm needs less system information. It enables the scheduler to actively learn task arrival, perform related knowledge and adapt to the adjacent scheduler allocation policy. The target is to move the schedulers strategy toward Nash equilibrium. Simulation experiments show that the proposed algorithm achieves excellent performance in expected response time of tasks and fairness, compared with classical scheduling algorithms such as OLB, MET and MCT.

Abstract:Tensor-based restoration of medical images and video images was studied with limited samples. On the basis of the theory of tensor singular value decomposition (t-SVD), a tensor rank-correction model (CRTNN) was proposed to correct the tensor nuclear norm minimization model (TNN). A two-stage rank correction method is given as follows: the first stage is used to generate a pre-estimator by solving the TNN model, and the second stage is to solve the CRTNN model to generate a high-accuracy recovery by the pre-estimator. A tensor proximal point algorithm was proposed to solve the CRTNN model and the TNN model, making it possible to calculate tensor directly in the real field. The convergence of the algorithm was proved in theory. Numerical experiments of medical images and video images verify the efficiency of the proposed model and method. The experiment results show that tensor rank-correction model and method can achieve higher-accuracy recovery.