The commercial vehicle is prone to instability when the vehicle is turning and driving at high speed. The control of the prevention of instability is carried out based on a kind of electric-hydraulic coupling steering system. A method of torque control is adopted that the power is actively adjusted to ensure the vehicle driving in the stable area to prevent instability. First, the structure of electric-hydraulic coupling steering system is briefly described. Second, the theoretical analysis of the vehicle instability is carried out, then the steering system can be used to control the stability of the vehicle and the 2-DOF reference model is built. Third, based on the flexible PID, the desired value of the yaw rate is tracked. The adaptive increasing algorithm is used to reduce the power of assist motor when the driving condition exceeds the stable area. Considering the change of road adhesion coefficient, the vehicle stable for prevention of instability can be obtained. The output value to the motor consists of the compensation value and the basic power value. The power characteristics of the motor are adjusted by the compensation value, so as to achieve prevention of instability control of commercial vehicles on different roads. In order to verify the control method, a hardware in the loop experiment based on electric-hydraulic coupling steering system was carried out. Results show that when the vehicle is in a critical state, the torque of the motor and the steering wheel angle both decrease, the yaw rate decreases. Therefore, the instability phenomenon can be effectively suppressed using the proposed method on different roads.

Fuel consumption models based on quasi-static dynamics were built for conventional and mild hybrid trucks. Energy consumption features of conventional truck and fuel saving rate brought by five measures of the hybrid truck were analyzed and predicted under target driving cycle. Then that factors influencing fuel saving, including driving cycle and power-train, were studied. Combined with the predicted fuel economy results, a total life cycle cost model was put forward. Results show that hybrid truck gain obvious cost advantage. The proposed prediction models based on theoretical analysis provide accurate economic and total life cycle cost results for hybrid power-train system quickly.

In order to control and optimize the protection performance of the passenger in advanced vehicle design, Body-in-White (BIW) seat anchorage strength is studied according to the national law of seat pull. The body structure strength performance is evaluated and improved under seat pull load case. The body structure passes the bench test, which indicates that the method of strength analysis under seat pull load case possesses a big advantage regarding reliability and appication.

In order to study the effects of temperature and humidity on the mechanical properties of the bonding structure on the vehicle, four temperature and five humidity combinations were selected to test the performance of the single lap joint. Using statistical analysis of the experimental data, the variation rule of the average failure strength of the joints were obtained with the changes of temperature and humidity. The effects of temperature and humidity on the joint failure strength were analyzed, and a mathematical model of the effects of temperature and humidity on the experimental results was obtained by using the response surface analysis. The results show that the average failure strength of the joint is exponentially attenuated with the increase in temperature at certain humidity level, and decreases by quadratic polynomial with the increase in humidity at a certain temperature level. The effect of temperature on the joint failure strength is more significant than the effect of humidity.

Large temperature difference can deteriorate the reliable operation of electric vehicle and battery cycle life. So it is essential to improve the temperature uniformity of battery pack. To enhance the heat transfer and reduce the temperature difference in a battery pack, a mixed inner air-flow Integrated Thermal Management (ITM) method is proposed by employing a small size axial fan. The performance of temperature control and temperature uniformity of single liquid Thermal Management (TM) and mixed inner air-flow ITM are analyzed and compared by Computational Fluid Dynamics (CFD). Furthermore, simulation on the thermal characteristic synergy of the mixed inner air-flow ITM is conducted by altering the aerodynamic characteristics and the position of the fan. Results show that the proposed method can effectively improve the temperature uniformity, thus enhancing the battery cycle life and the total performance of electric vehicle.

In order to reduce the degree of speed reduction in the stability control and the longitudinal force utilization of the tires, the longitudinal force of each wheel is assigned by the secondary programming method based on the distributed electric vehicle platform. The yaw moment distribution based on the wheel motor output driving/braking force is preferred. When the required yaw moment exceeds the maximum torque of the wheel motors, the hydraulic brake system is activated to compensate. The results of Double Lane Change (DLC) simulation test demonstrate that, compared with the differential braking control system, the error between distributed electric vehicle stability control system and the ideal vehicle speed is kept within 1 km/h, the vehicle speed decreases by 82.25%, and the average tire force utilization rate is reduced by 9.71%. The stability control system can improve the stability and the safety of the driving vehicle. Under the acceleration/deceleration conditions, it provides good robustness.

Engine start-stop system is widely used as it can reduce fuel consumption by turning off the engine while idling. But in traffic congestion conditions, the engine start-stop system increases fuel consumption because of turning off engine during short time idling. To solve this problem, Least Square Support Vector Machine (LS-SVM) is applied to predict the idling time, that the engine will not be turned off during short time idling. Experiment results show that the accuracy of idling time prediction using LS-SVM can reach 80%. The engine start-stop system using this method can reduce fuel consumption by about 0.2% during smooth hour. Meanwhile the driving comfort can be improved by reducing more than 50% start-stop numbers during rush hour and more than 15% during smooth hour.

With regard to the big gap between fuel consumption measurement and actual driving performance of passenger car, the typical driving cycle of passenger car in Changchun city was researched. One year's driving data were collected in Changchun city, from which 3 538 335 valid data were acquired for the research. Cluster method and Markov chain principle were applied to construct the typical driving cycle, and Changchun cycle was compared with Shanghai cycle and NEDC cycle. The results show that the average absolute deviation of the characteristic parameters between the constructed cycle and sample database population is 4.03%, which is obviously lower than the 10% deviation requirement and indicates that the constructed cycle could accurately reflect the driving characteristics in Changchun city. The driving characteristics of Changchun cycle differ widely from that of Shanghai cycle and NEDC cycle. The average absolute deviation of the characteristic parameters between Changchun cycle and the other two cycles is 22.7% and 21.1% respectively. The driving characteristics of NEDC cycle can not accurately describe the driving characteristics of passenger car in China. Therefore, it is necessary to construct driving cycle that conforms with the situations of China. The results of this research may provide references for promoting the accuracy of measurement and assessment on passenger car in Changchun city.

In this paper, first, the daily travel pattern is defined based on activity theory. Then, a logic model system for detection of daily travel pattern-trip purpose using GPS data is constructed. The results indicate that this study covers interrelationship among daily trips and enhances the identifying prediction as a result by determining the trip purpose based daily travel pattern. The findings can be applied to the detection of trip purpose and travel pattern with GPS data. The model system is also one of the significant sections in identifying travel behavior with GPS data. The findings are benefit for replacing traditional residential travel survey with detecting travel data from big data platform. This study enhances the efficiency and accuracy of travel survey and contributes to transportation planning and management.

In order to improve the accuracy of location selection of the variable information board and improve the benefit of traffic guidance, the urban road network is divided from the point of view of traffic induction using random walk algorithm. Based on the analysis of the network built by taking road section as node, the Laplacian matrix of the network graph is constructed. Then, the model is solved by the method of solving the combining Dirichlet problem. Taking Shenyang Road Network as an example, the feasibility of the proposed model is verified.

Considering the integration of urban and rural public transport, taking the urban hubs and hubs in central towns as a whole, a tree-star-star network is constructed. Meanwhile, considering the capacity constraints of the hubs, a hierarchical hub location model for integration of urban and rural public transport is established that aims at the minimum total cost. Then, the model is validated and parameter sensitivity is analyzed using the actual urban and rural passenger transportation data. The results show that the hierarchical hub location model can determine hub locations in the cities and central towns from the perspective of the integration of urban, urban-rural junctions, and townships. Compared to complete network, hub links in the incomplete network carry larger volume of traffic with a modest cost increase, which can take advantages of hub scale and improve the utilization of the links.

To meet the requirement of the working performance and security of automated warehouse, the mathematical model of multi-objective slotting allocation optimization is constructed. The outbound-inbound operation time, the equivalent center of gravity of overall shelf and the degree of relative accumulation of related products are taken as the multi-objective functions. A Simple Weighted Genetic Algorithm (SWGA) is used to solve the model obtained by weighted and normalized multi-objective models. To avoid the problem of premature convergence, a Multi-population Genetic Algorithm (MPGA) is proposed to solve the optimization model of slotting allocation. Combined with experiment of toy car assembly and experiment of automated warehouse, the results of slotting allocation are obtained. The effectiveness of the MPGA is verified by comparison and analysis of the two results. This study provides an effective solution for automated warehouse slotting allocation and optimization.

Time series of vehicle running status parameters not only present randomness, but also present chaotic characteristics. Therefore it is necessary to accurately identify the data characteristics of vehicle running status parameters, in order to identify if its parameter time series is random or chaotic. To obtain the maximum availed data information of the vehicle running status parameters. Delay-coordinate space reconstruction and the largest Lyapunov exponent method were used to carry out nonlinear dynamic analysis. Speed time series is used as an example, the results show that based on the Delay-coordinate phase space reconstruction, the saturate correlation dimension obtained by G-P algorithm is not an integer, and the Max-Lyapunov exponent is grater than zero, which demonstrate speed time series is chaotic time series from two aspects. Thus, data characteristics of the vehicle running status parameters can be identified by nonlinear dynamic analysis, and then appropriate methods can be used in follow-up research based on the identification, which is more scientific.

Based on the Peck formula and the double-line superposition principle, the concept of the variation coefficient C of the surface subsidence of double-line shield tunnel is proposed. The shape of the double-line tunnel settlement curve gradually changes from the V-type into W-type, and then into two independent V-types. C=2 and C=7, are respectively the critical points of the “single peak” becoming “double peak”, then becoming two independent “single peaks”. The three-dimensional finite element model was established according to the different influence factors. The effects of different influence factors on the surface subsidence of the double-line shield tunnel were obtained. The measured data of Changchun Metro Line 2 were collected and reliability of the finite element method was verified.

In order to solve the problem of low accuracy and low efficiency of thermal parameter identification, a method of step identification for internal and external models is proposed. First, the selection principle of local model is built by analysis of the influence depth of surface convection. Second, the convergence of parameter identification is demonstrated by the global analysis method. Finally, a method of fitting the optimal solution with multiple recognition results is proposed. The results show that, in the first 96 h, the local model can reflect the law of the whole model, which can be used to improve the recognition efficiency. Convergence tolerance can cause 3% to 10% parameter error, and the fitting method can effectively reduce the error. The efficiency and accuracy of this method are verified by the example of a concrete pylon.

Two kinds of different shapes of steel square tube confined steel reinforced concrete column steel frame ring beam joint were designed. ABAQUS finite element software was used to establish the numerical analysis model of the node. The hysteretic behavior, stress distribution and failure mode of the joints were analyzed. The influences of the outer diameter thickness ratio of steel tube, steel form, joint height, concrete strength and axial compression ratio on the seismic performance of the nodes were also investigated. The results show that the hysteresis curves of this kind of node are full and the energy dissipation is good, the steel distribution and failure mode are in accordance with the requirement of "strong column, weak beam and stronger joint" in seismic design. This study provides theoretical support for the design and research of this kind of nodes.

Based on the characteristics of the starting process of 2.8TC diesel engine, the starting process is divided into two periods, the towing period and starting period. Different metering valve control strategy of high pressure pump for different period is designed and the targets of the first injection pressure and injection speed are determined. In the towing period, the effects of the opening time and opening size of the fuel metering valve on the dynamic characteristics of the rail pressure are studied by experiment, and the control method of the fuel pump is optimized. In the starting period, the effects of the opening size and control method of the fuel metering valve on the dynamic characteristics of the rail pressure are also investigated by experiment. The results show that the phased control strategy of high pressure pump fuel metering valve can effectively improve the stability and following performance of the target of first injecting pressure in starting process. It provides a good injection condition for improving the starting performance.

Based on the working model of a diesel engine, the influences of two Miller cycle strategies, Early Intake Valve Closure (EIVC) and Late Intake Valve Closure (LIVC) on the combustion and emissions of diesel engine were analyzed by 1-Dimensional simulation. Then, the working condition of each Miller cycle strategy on the engine under the rated speed was optimized through the adjust of the valve timing, the boost pressure and the injection timing. It was found that both delaying and advancing the closure timing of the intake valve can decrease the pressure and temperature during compression stroke, prolonging the ignition delay. However, due to the decrease of the working media inside the cylinder, the average in-cylinder temperature and soot emission increase, which can be alleviated by raising the boost pressure and the resulting compensation of the intake air loss. The study also found that together with increasing boost pressure and delaying injection timing, both EIVC and LIVC can reduce NO_x and soot emission simultaneously. The simulation results show that while keeping the peak firing pressure the same as the original engine, M-50 together with constant peak firing pressure boosting and a 6 °CA injection delay can decrease the Fuel Consumption (FC) by 1.21%, and NO_x emission by 22%, and soot emission by 58.1%, while M100 together with constant peak firing pressure boosting and a 4 °CA injection delay can reduce the FC by 1.56%, and NO_x emission by 12.96%, and soot emission by 54.75%.

Linear Range-Extender (LRE) is an innovative energy conversion device, which can convert fuel chemical energy into electrical energy. Due to simple structure, multi-fuel flexibility and high power density, LRE can be used as an auxiliary power unit for hybrid vehicles. Simulation structure coupling MATLAB/Simulink model and AVL_Fire model is established. For estimating scavenging process quality, scavenging efficiency, capture ratio and turbulent kinetic energy at the end of scavenging process are selected as the indexes. Under different piston strokes, working frequencies and intake pressures, scavenging process for stable operation of LRE is investigated. The accuracy of the simulation structure is validated by a prototype. Results show that the scavenging characteristics are sensitive to intake pressure. The scavenging quality can be improved by increasing the piston stroke and working frequency.

A mathematical model of Catalytic Diesel Particulate Filter (CDPF) was built up. The exhaust parameters and structure parameters were analyzed, and the model was validated through experimental data. The results show that the mass in the filter wall increases steeply and then decreases slowly. Soot distribution in the cake layer has a minimum thickness for appropriately 30% of the total channel length. While, the edges at the inlet and outlet have the maximum thickness. The exhaust parameters, including temperature, flow rate, the concentration of O₂ and the concentration of NO₂, mainly influence the thickness of soot distribution by influencing performance of the NO₂ assisted regeneration. The temperature has the largest influence, and the thickness of soot distribution in the cake layer is more sensitive to the concentration of NO₂ than O₂. The structure parameters, including the ratio of length to diameter, the ratio of inlet diameter to outlet diameter and channel density have significant effects on the shape of the soot distribution in the cake layer. With the increase in the structure parameters, the soot distribution tends to be uneven, and the channel density has the largest impact, which means the position of the lowest point tends to move to the rear end, while the increase in the ratio of inlet diameter to outlet diameter leads the point to move to the front end.

Experiments were conducted in a constant-volume combustion chamber system to study the laminar burning velocity and flame cellular instability of methane with dissociated methanol at different temperatures, pressures, dissociated methanol fractions, equivalence ratio. Experiments were also done to methane with carbon monoxide in the same conditions. The results show that the laminar burning velocity increases with the temperature and dissociated methanol fraction, while decreases with the increase in pressure. With the increase in pressure, hydrodynamic effect caused by significant reduction of the flame thickness plays an important role in the flame cellular instability.

Based on the experimental data of swirling impinging jet from published literature, a numerical simulation method with RNG-k-ε turbulence model was developed to accurately simulate heat transfer characteristics of swirling impinging jets. Three types of inserts, screw rod, twisted tape and guide vane, were used to produce the swirl flow. Swirling impinging jets issuing from the nozzles of these inserts were numerically studied. The effect of jet Reynolds number on swirling number at the exit of the nozzles was evaluated and the effect of swirl number on heat transfer of the swirling impinging jets was analyzed. Numerical results show that the large deviation of swirl number occurs as jet Reynolds number is not considered. The swirl number of the swirling jets by the inserts with medium helix angles of 30° and 45° is very sensitive to changes in jet Reynolds number. Different patterns of red spot with high heat transfer rates are shown on the target surface by swirling impinging jet issuing from the nozzles. Shapes and sizes of red spots are related to swirl number of the swirl jets. The peak of Nussle number is increased and the uniformity of heat transfer is enhanced as the swirl number increases. Heat transfer characteristics of the swirling jets depend on the combined effect of jet Reynolds number and swirl number of the jets. The optimum swirl generator is the type of insert with screw rod. Comparing to the other two swirl generators of the inserts with twisted tape and guide vane, the highest heat transfer coefficient with the best uniformity on the target surface by this swirl generator can be achieved under the same working condition.

Direct Drive Volume Control (DDVC) servo system is a novel hydraulic servo system. With the continuous development of motor servo technology, it has been widely used in industrial and aerospace applications. The system has advantages of compact structure and high efficiency, but also has defects in dead zone and non-linear characteristics. In order to solve these problems, the state equation of the system was established and discretized. By using the third-order integral chain differentiator, the real-time values of the rod velocity and acceleration were obtained from the measurement signal of displacement, which constitute the full state feed-back control system. A nonlinear controller was designed with the Discrete Variable Structure Control (DVSC) algorithm based on the approach law. The simulation and experimental results show that the DVSC controller has better position tracing characteristics than traditional PID controller, which improves the controlling performance of DDVC servo system.

To improve the mixing effect of the fluids under micro scale condition and the mixing efficiency of micromixer, a novel PMMA micromixer embedded with 3D channel based piezoelectric actuation was developed. The micromixer uses PZT micropump with double chambers in series as the driving source, and is embedded with Y type mixing channel and 3D multi-corner spiral flow channel. The micromixer is manufactured by PMMA bonding process under certain temperature and pressure condition. The related structural parameters are optimized using the CAE software. The final optimized dimensions are 50 mm × 35 mm × 7.2 mm. The pulsating and mixing effect experiments were carried out in the laboratory. Results show that when the frequency is 50 Hz and the output flow rate is about 1 mL/min, the pulsation effect of mixing fluids is obvious in the flow channel. The pulsation mixing technique and the multi-corner flow channel structure improve the mixing effect, which is a novel micro mixing technology that combines with the characteristics of active and passive micromixers.

An integrated squirrel-cage flexible support ball bearing quasi-dynamic iterative Finite Element Model (FEM) is established, which is used to calculate the deformation of the support structure and raceway. The dynamic characteristics of the bearing are analyzed using the noncircular raceway quasi-dynamic model. The internal load distribution of the integrated squirrel-cage flexible ball bearing is studied, and the influence of the integrated flexible support structure on the dynamic characteristics of the bearing is analyzed. The results show that the integrated squirrel-cage flexible support structure reduces the maximum bearing internal contact load by 10.94%, increases the fatigue lifetime by 11.3%, reduces the bearing radial stiffness by an order of magnitude, and increases the slide ratio by 15.8%.

This paper combines the connecting rod fracture splitting experiment, three-dimensional (3D) reconstruction technology and finite element technique to study the performance of fracture-split connecting rod. The true fracture joint surface of a connecting rod is obtained by fracture splitting, and the fracture joint mode is reconstructed by reverse engineering. A real 3D geometric model of the fracture-split connecting rod is then established. The strength and stiffness of the fracture-split connecting rod are analyzed using finite element simulation and are compared with traditional machining connecting rod. The results show that the static strengths of the fracture slitting connecting rod and the flat incision connecting rod are basically the same. The 3D concavo-convex surface of the fracture-split connecting rod has the bearing capacity, which effectively reduces the shearing stress of the bolt. The fracture-split connecting rod has better shear performance than the flat incision connecting rod. The 3D jagged characteristics of the joint surface can make the rod close contact with the cover and lock each other to reduce the relative movement. The overall deformation of the fracture-split connecting rod is less than the flat incision connecting rod, thus, the stiffness of the fracture-split connecting rod is better than that of flat incision connecting rod.

6062 aluminum alloy is annealed, and then is treated by deep cryogenic temperature at different time. Through stretching, hardness measurement and punch-shearing experiments, the effect of cryogenic temperature on the material properties is analyzed. The results show that the mean annealing and cryogenic temperature at different time can improve the smooth zone and reduce burr or reduce burr height. With the increase in cryogenic time, the intensity is reduced, however, the plasticity is improved. While, the temperature returns from cryogenic to normal the intensity increases step by step, and the burrs are reduced and smooth zone increases and then decreases. The tests were treated by deep cryogenic temperature for 8 h and kept real-time cryogenic temperature, and punch-shearing was carried out and comprehensive quality, such as collapse angle, burr and smooth zone, is best. If the target is to reduce the burr, after 8 h cryogenic treatment and return to room temperature, the result of real-time punch shearing is better.

To improve the wear resistance of aluminum substrate, Al-Nb cladded layers were prepared by double argon arc cladding method at different currents with pre-coated niobium and aluminum mixed powder. The metallographic analysis and the test results on microhardness and wear resistance show that the cladded layers consist of α-Al, NbAl₃ and a small amount of niobium phases. Also, the formation mechanism of NbAl₃ phase was analyzed which grew in the dendrites and distributed on the edge of the rich niobium zone. The increase in argon arc currents results in less NbAl₃ phase and dendrites but more α-Al solid solution resistance, which reduces the microhardness and deteriorates the wear resistance of the cladded layers. The average microhardness peak and the best wear resistance were achieved when the argon arc current was 100 A.

The geometric shapes, size parameters and correlations between dimensions of more than ten maize varieties are measured and analyzed. On the basis of the analyses, a modeling method of a single maize kernel and a maize assembly is proposed based on the sphere filling method. Two maize varieties are selected as examples. By comparison of the experimental results and the Discrete Element Method (DEM) simulation results of the maize kernel packing tests and “elf-flow screening” tests, respectively, it is concluded that when the number of the filling spheres is 16 for a single maize kernel, a good agreement between them is reached. The effectiveness of the maize kernel modeling method proposed in this work is verified. A case is used to show how to employ the maize kernel model and DEM to analyze the discharge process of a silo.

The algorithm of actuator Fault Diagnosis (FD) of the vehicle Electronic Stability Control (ESC) system is studied. A seven-degree-of -freedom model of the vehicle with crosswind and actuator failure is built to obtain the information of the actual actuator failure. In order to realize the actuator FD of the ESC system in the presence of crosswind interference, a differential homeomorphic transformation is executed so that the undetectable interference is transformed into the measurable input of the system. Subsequently, the observer for actuator FD is proposed corresponding to the transformed system. The actuator fault can be positioned on a certain wheel by the residual, and the actual actuator failure estimation is obtained. The effectiveness of the method is verified by simulation.

This paper investigates the stability problem of a linear system with time-varying delay. The time-varying delay is assumed to belong to a given interval. A new Lyapunov-Krasovskii function is constructed which contains some tripe integral terms. Using some integral inequalities including the recent proposed free-matrix-based integral inequality, new sufficient stability conditions are obtained, which are presented in terms of Linear Matrix Inequality (LMI). Finally, two examples are given to demonstrate that the obtained results are less conservative than some existing method.

In order to address the issue that sentences may contain context-information with reference to the facts, this paper presents a Clause-Level Context-aware Open Information Extraction approach (ClauseContextIE). ClauseContextIE extends the scale of context-information that can be identified, and takes advantage of the dependency-parsing to extract the context-information and general clauses in a top-down way, so that it can construct a graph that expresses the hierarchical structure. Finally, ClauseContextIE assigns the corresponding context-information to each tuple extracted from general clauses in a bottom-up approach. ClauseContextIE avoids extracting context-information as a relation tuple, and assigns context-information to correct relation tuples accurately. Experiments were conducted to compare ClauseContextIE with ReVerb, OLLIE and ClausIE on three datasets, ReVerb dataset, Wiki dataset and NYT dataset. Experimental results show that ClauseContextIE achieves significantly higher accuracy and recall than the other extractors.

A logistic regression classifier based on second-order Markov assumption is proposed for heterophilous network. The algorithm employs the second-order Markov links, extends neighbors' link distributions of node neighbors in order to construct structured logistic regression model. At the same time it combines the first-order Markov logistic regression model to update the class distributions progressively using relaxation labeling collective inference method. Comparison of experiment results shows that the enhanced algorithm performs better on the heterophilious network.

An intelligent interaction agent based on action language is proposed. The keyword matching technology is used to obtain the key information of the users' requirement, and the spus2asp system is triggered to drive the regulation strategy based on the knowledge and rules described in the action language to achieve intelligent human-computer interaction. After that, it uses its reasoning module to generate a sequence of actions for home services and convert them into equipment control instructions to eventually achieve intelligent management of the home environment.

The three-factor authentication and key agreement protocol proposed by Guo et al can not achieve perfect forward secrecy and can not support the update of user's biometric. In order to remedy these flaws, we propose an improved authentication protocol for multi-server architecture by use of Diffie-Hellman key exchange technology. Analysis shows that the proposed protocol is able to remedy the security flaws of the original scheme, meet the security requirements of multi-server environment and is able to withstand various possible attacks.

DNA sequence classification is a very important step in metagenomic study, and k-mer frequency is a commonly used feature for DNA sequence classification. The dimension of k-mer grows exponentially with k, easily leading to the “dimension disaster”. To solve this problem, this paper proposes a k-mer optimization based metagenomic DNA sequence classification method. First, the k-mer frequency is extracted for each DNA sequence. Second, the k-mer frequency is optimized based on Non-negative Matrix Factorization (NMF) algorithm. Finally, the fuzzy C-means clustering algorithm is used for DNA sequence clustering. Experimental results on metagenomic datasets containing different species show that the proposed method can effectively overcome the shortcoming of traditional classification method, and the classification performance is better than that of several similar algorithms.

Using traditional label propagation algorithm in network clustering, the initial allocation of taps, the node selection and updating order of the labels are all random processes, which affect the clustering results. To overcome this problem, a new method of network clustering based on improved label propagation algorithm is proposed, in which the graph is used to describe the network and provide the basis for the network clustering. The process of the improved label propagation algorithm includes the following steps. First, the average malpractice in the network order of any two nodes with the largest common neighbor number is obtained. Second, the most similar node and neighbor node are taken as the initial core community and its initial label is assigned. Third, the random walk similarity matrix is introduced based on the node selection and the label of the node with the highest similarity. Fourth, by using the H index on the label algorithm, the update order is improved. Finally, according to the improved result, the clustering process is realized according to the clustering process of the label propagation algorithm network. Experimental results show that the proposed network clustering method has higher accuracy and stability.

To suppress iris noise and improve algorithm versatility, it is proposed to use Laplacian of Gaussian (LOG) operator and adaptive optimization Gabor filtering in iris recognition. The LOG operator suppresses iris noise and 40 sets of Gabor filtering with different frequencies and directions extract iris features and transform the features into binary feature codes. The filtering parameters are adaptively optimized for different iris libraries using Mutation Particle Swarm Optimization (MPSO) algorithm. The iris category is determined by calculating the Hamming distance between irises. Compared with other Gabor filtering and machine learning algorithm, the proposed algorithm can effectively suppress iris noise interference and improve recognition accuracy. At the same time, this algorithm has higher versatility in recognition of various iris libraries.

In traditional medical image fusion process based on single pixel, the information similarity is ignored and detailed information may loss. To solve these problems, an image fusion technology based on Nonsubsampled Contourlet (NSCT) and Robust Principal Component Analysis (RPCA) model with similar information is proposed. First, the initial matrix constructed by the image block from the original images is decomposed into low frequency and high frequency parts by NSCT transformation. Second, the low rank component is decomposed into low rank matrix and spare error matrix by using the low rank matrix model with similar information. Third, the low rank matrix of the two images, the spare error matrix and high-frequency components are fused by fusion rule of the absolute maximum method. Finally the fusion image is replaced by the inverse transform. The experiment results on CT and MRI show that the proposed method can maintain more edge and texture detailed information of the source images.

Prior contour detectors based on single scale input images usually extract multi-scale low-level cues to increase the detection accuracy, however, this kind of methods do not improve accuracy much due to the extracted noisy boundaries. The reason behind this is the lack of object-level features. To address this problem, this paper proposes a boundary fusion method which is capable of combining low-level and object-level cues on multiple scales. For a single scale image, at the beginning, we use Trimaps and an image matting method to generate object-level features, then we combine the object-level features with extracted low-level cues. For multi-scale images, we fuse the boundary maps extracted from each single scale image to reduce noisy boundaries. Experiments show that our method outperforms the single-scale boundary detector on the BSDS500 dataset.