Microstructure and mechanical properties of modified ultrahigh carbon (1.6%C) steels with different Mo additions (0, 0.3%, 0.5%, and 0.8%, mass fraction) were studied in their as-cast and quenched then tempered conditions by optical microscopy, scanning electronic microscopy, X-ray diffraction and hardness and toughness tests, respectively. The results show that the continuous eutectic carbide network structure has been broken down and changed to partial isolated and finer particles embedded in matrix of as-cast alloy by modification. Carbides in both quenched and tempered specimens have been refined effectively after the addition of Mo. Specimen containing 0.5% Mo shows the finest microstructures with carbides dispersed homogeneously in martensite matrix and demonstrates highest impact toughness of 18.4 J/cm² and hardness of 50 HRC.

PAN (Polyacrylonitrile)-based carbonaceous fibers were prepared at the heat treatment temperature (HTT) range of 650 to 900 °C. The relationships among HTT, carbon content and volume resistivity of the carbonaceous fibers were investigated. The carbonaceous fibers/PTFE (Polytetrafluoroethylene) antistatic coatings were prepared by the spraying technology and the effects of carbonaceous fibers and pigments on surface resistivity of the coatings were systematically discussed. Micrographs provide insight into the antistatic mechanism of the coating. The results show that carbon content of the carbonaceous fibers increases from 68.8% to 74.8% (mass fraction) and the volume resistivity decreases drastically from 1.94×10³ to 8.27×10⁻² Ω·cm. The surface resistivity of the antistatic coating is adjustable between 10⁵ and 10⁸ Ω to fit the different antistatic materials. Static is dissipated by a conductive network of short fibers and the tunneling effect between the neighboring fibers and conductive pigments. Conductive pigments make the conductive network more perfect and improve the antistatic ability, but insulating pigments acting as barriers for the formation of conductive channel increases the surface resistivity of the coatings. The influence of pigments on the surface resistivity drops gradually with the decrease of the carbonaceous fibers volume resistivity.

The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in Al-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the Al alloy TEM (transmission electron microscope) digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized (growing rate minimum to 2% and maximum to 400% in samples), accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.

In this work, a comprehensive comparison regarding the impacts of M (M=Cu, Co, Mn) substitution for Ni on the structures and the hydrogen storage kinetics of the nanocrystalline and amorphous Mg₂₀Ni_10−xM_x (M=Cu, Co, Mn; x=0–4) alloys prepared by melt spinning has been carried out. The analysis of XRD and TEM reveals that the as-spun (M=None, Cu) alloys display an entire nanocrystalline structure, whereas the as-spun (M=Co, Mn) alloys hold a mixed structure of nanocrystalline and amorphous structure when M content x=4, indicating that the substitution of M (M=Co, Mn) for Ni facilitates the glass formation in the Mg₂Ni-type alloy. Besides, all the as-spun alloys have a major phase of Mg₂Ni but M (M=Co, Mn) substitution brings on the formation of some secondary phases, MgCo₂ and Mg phases for M=Co as well as MnNi and Mg phases for M=Mn. Based upon the measurements of the automatic Sieverts apparatus and the automatic galvanostatic system, the impacts engendered by M (M=Cu, Co, Mn) substitution on the gaseous and electrochemical hydrogen storage kinetics of the alloys appear to be evident. The gaseous hydriding kinetics of the alloys first rises and then declines with the growing of M (M=Cu, Co, Mn) content. Particularly, the M (M= Mn) substitution results in a sharp drop in the hydriding kinetics when x=4. The M (M=Cu, Co, Mn) substitution ameliorates the dehydriding kinetics dramatically in the order (M=Co)>(M=Mn)>(M=Cu). The electrochemical kinetics of the alloys visibly grows with M content rising for (M=Cu, Co), while it first increases and then declines for (M=Mn).

A simple strategy to prepare a hybrid of nanocomposites of anatase TiO₂/graphene nanosheets (GNS) as anode materials for lithium-ion batteries was reported. The morphology and crystal structure were studied by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM). The electrochemical performance was evaluated by galvanostatic charge-discharge tests and alternating current (AC) impedance spectroscopy. The results show that the TiO₂/GNS electrode exhibit higher electrochemical performance than that of TiO₂ electrode regardless of the rate. Even at 500 mA/g, the capacity of TiO₂/GNS is 120.3 mAh/g, which is higher than that of TiO₂ 61.6 mAh/g. The high performance is attributed to the addition of graphene to improve electrical conductivity and reduce polarization.

A new MoO₃/SO₄²⁻-TiO₂ catalyst was prepared by a conventional impregnation of SO₄²⁻/TiO₂ as carrier with an aqueous solution of ammonium molybdate and used for the synthesis of transesterification of dimethyl carbonate (DMC) with phenol. A series of MoO₃/SO₄²⁻-TiO₂ catalysts with different MoO₃ loadings were investigated and characterized using X-ray diffraction (XRD), Fourier transform infrared spectrometer (FTIR), NH₃-temperature programmed desorption (NH₃-TPD) and X-ray photoelectron spectroscopy (XPS). The results show that MoO₃ loading is related to the activity of transesterification reaction. With the increase of MoO₃ loading, the activity of transesterification reaction increases. The sulfur species in the catalyst have an influence on the molybdenum species, and lead to an increase in the electropositive of molybdenum, which promotes the catalytic activity of MoO₃/SO₄²⁻-TiO₂. Among the series of catalysts prepared, MoO₃/SO₄²⁻-TiO₂ with 10% MoO₃ and 823 K calcinated is found to be the most active catalyst for transesterification reaction. Under the reaction conditions of 453 K and 12 h, the conversion of DMC is 30.5 %, and the yields of MPC and DPC reach 21.2 % and 8.7 %, respectively.

It is difficult for polyethylene terephthalate (PET) to degrade, which caused severe pollution. In this work, polylactic acid (PLA) was introduced to improve the degradation of PET. PET/PLA was synthesized by extrusion blending. The thermal, crystalline and mechanical properties of blends were investigated with TGA, DSC, WAXD and universal testing machine. The degradation of the blends in soil, acid and alkaline buffer solutions was assessed, respectively. It was found that the introduction of a little PLA promoted crystallization of PET during injection molding process. The starting decomposition temperature lowered from 412.1 °C of pure PET to 330.4 °C at 50% PLA content, tensile and bending strength of blends gradually decreased with the PLA content increasing, while the degradation rate improved. Alkaline environment was most beneficial for blends to degrade. The degradation mechanism was discussed.

In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost function was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost functions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.

The recovery of indium from waste indium tin oxide (ITO) target has great significance for the economy and environment. Based on our previous study on the optimization of acid leaching technique, the present study focuses on tin removal via zinc substitution and indium recovery from a tin-free leach solution. The results show that when the amount of added zinc powder and reaction time increase, the tin removal effect can be improved. The optimal conditions obtained are as follows: additional content of zinc powder from 20 g/L to 25 g/L, reaction temperature of 60 °C, and reaction time from 3 h to 4 h. Under this condition, the tin removal rate exceeds 98%, and the tin content in the tin removal solution is lower than 0.05 g/L. After tin removal, the substitution time could be reduced from 3–5 d to 1–2 d by neutralizing the residual acid by using alkaline residue and maintaining the pH value less than 2. The indium recovery rate is also improved when this condition is used. The indium content in the tin residue is reduced to lower than 0.1% and the acid-insoluble β-SnO₂ could be obtained via the strong nitric acid leaching of the indium-containing tin residue. Indium could be recovered from ITO with a high purity of 99.995% via electrorefining.

Nickel oxide (NiO) microsphere with a large surface area was novelly synthesized through nickel bicarbonate (Ni(HCO₃)₂) precursor. The obtained nickel oxide (NiO) microsphere was characterized by X-ray pattern diffraction, scanning electron microscopy, CO₂ temperature-programmed desorption, H₂ temperature-programmed reduction, N₂ adsorption/desorption and laser scattering particle size distribution analyzer. It was found that nickel oxide (NiO) synthesized by the thermal decomposition of Ni(HCO₃)₂ through area hydrolysis, presented very nice microsphere with high surface area. The catalytic properties of obtained nickel oxide (NiO) microsphere were studied in the reaction of carbon dioxide reforming of methane where 91.3% conversion of CH₄ with 93% conversion of CO₂ was observed. Besides, the catalyst maintained high stability over 200 h on the stream.

The extraction and separation of Cu(II) and Fe(III) from HCl media using Cyanex 921 in kerosene were investigated. The effect of shaking time, aqueous phase acid concentration, Fe(III)/Cu(II) concentration, Cyanex 921 concentration, temperature and aqueous to organic phase ratio on the separation of Cu(II) and Fe(III) was studied using 0.1 mol/L Cyanex 921 in kerosene. Maximum separation was achieved from 2 mol/L HCl containing 0.001 mol/L Cu(II) and 0.005 mol/L Fe(III) with 0.1 mol/L Cyanex 921 in kerosene. Feasible separation of copper and iron was also possible from 5 mol/L HCl using 0.02 mol/L Cyanex 921.

Giant reed is a suitable pioneer plant for metal-contaminated soil phytoremediation, however, it is imperative to dispose the metal-contaminated biomass after harvesting. The liquefaction of metal-contaminated giant reed biomass in ethylene glycol system with sulfuric acid as catalyst for the precursors of polyurethane compounds was studied. The results show that giant reed biomass from metal-contaminated soil is potentially liquefied and significantly affected by solvent/solid ratio, liquefaction temperature and liquefaction time (P<0.05). The liquefaction rate of biomass in acidified ethylene glycol system can reach 85.2% with optimized conditions of 60 min, 170 °C, 3% sulfuric acid and solvent/biomass ratio of 5:1. The hydroxyl value of liquefied products is of 481 mg KOH/g while reactive hydroxyl groups of them are abundant, which is promised as potential precursors for polyurethane compounds. The solvent liquefaction is a potential method to dispose the metal-contaminated biomass, however, the containing-metal liquefied products should be studied deeply in order to get the suitable precursors in future.

The kinetics of reductive leaching of manganese from a low-grade manganese oxide ore were studied using cellulose as reductant in dilute sulfuric acid medium. It was found that when the stirring speed was higher than 200 r/min, the effect of gas film diffusion on manganese extraction efficiency could be neglected, and the kinetic behavior was investigated under the condition of elimination of external diffusion influence on the leaching process. Effects of leaching temperature, mass ratio of cellulose and ore, and the sulfuric acid concentration on manganese extraction efficiency were discussed. The kinetic data were analyzed based on the shrinking core model, which indicated that the leaching process was dominated by both ash layer diffusion and chemical reaction at the initial stage, with the progress of leaching reaction, the rate-controlling step switched to the ash layer diffusion. It was also concluded that the sulfuric acid concentration had the most significant influence on the leaching rate, the reaction orders with respect to the sulfuric acid concentration were 2.102 in the first 60 min, and 3.642 in the later 90 min, while the reaction orders for mass ratio of cellulose and ore were 0.660 and 0.724, respectively. An Arrhenius relationship was used to relate the temperature to the rate of leaching, from which apparent activation energies were calculated to be 46.487 kJ/mol and 62.290 kJ/mol at the two stages, respectively. Finally, the overall leaching rate equations for the manganese dissolution reaction with cellulose in sulphuric acid solution were developed. The morphological changes and mineralogical forms of the ore before and after the chemical treatment were discussed with the support of SEM and XRD analyses.

The enrichment of Ni from a low-grade saprolitic laterite ore, which has been pre-treated by high pressure grinding roller(HPGR) to be 74% passing 0.074 mm and contains 0.92% Ni, 18.47% Fe, 10.61% MgO and 42.27% SiO₂, was conducted by using pelletizing, rotary kiln reduction and magnetic separation process on a semi industrial scale, and the effects of reduction duration, mass ratio of coal to pellets(C/P), the types of magnetic separator, the sections of grinding-separation and the grinding fineness on the recovery of Ni and Fe were examined. It is shown that nickel concentrate containing 3.13 % Ni and 59.20 % Fe was achieved at recoveries of 84.36 % and 71.51 % for Ni and Fe, respectively under the following conditions: reducing at (1120±40) °C for 120 min, C/P being 1.0, wet grinding of reduced pellets up to 70%–87% passing 0.074 mm and a magnetic field intensity of 238.8 kA/m during the first section of grinding-magnetic separation, and a grinding fineness of 84%–91% passing 0.045 mm and a magnetic intensity of 39.8 kA/m during the second section of grinding-magnetic separation. The enriched Ni containing concentrate has a low content of S and P, and can be used for further processing to produce high-grade ferronickel alloy.

An underactuated finger structure actuated by tendon-driven system is presented. Kinematics and static analysis of the finger is done, and the results indicate that the prosthetic finger structure is effective and feasible. Based on the design of finger, a prosthetic hand is designed. The hand is composed of 5 independent fingers and it looks more like humanoid. Its size is about 85% of an adult’s hand and weights about 350 g. Except the thumb finger, each finger is actuated by one DC motor, gear head and a tendon, and has three curling/extension joints. The thumb finger which is different from other existing prostheses is a novel design scheme. The thumb finger has four joints including three curling/extension joints and a joint which is used to realize the motion of the thumb related to the palm, and these joints are also driven by one DC motor, harmonic drive and a tendon. The underactuation and adaptive curling/extension motion of the finger are realized by joint torsion springs. A high-powered chip of digital signal processing (DSP) is the main part of the electrical system which is used for the motors control, data collection, communication with external controlling source, and so on. To improve the reliability of the hand, structures and sensors are designed and made as simply as possible. The hand has strong manipulation capabilities that have been verified by finger motion and grasping tests and it can satisfy the daily operational needs and psychological needs of deformities.

Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem. A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable (on-line) environment is proposed. The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated. Also, the governing equations for the shortest path are derived. The proposed mathematical model describes the motion (satisfying constraints of the mobile robot) along a collision-free path. Further, the algorithm is applicable to dynamic environments with fixed or moving targets. Simulation results show the effectiveness of the proposed algorithm. Comparison of results with the improved artificial potential field (iAPF) algorithm shows that the proposed algorithm yields shorter path length with less computation time.

The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only with robot’s vision. By imitating spatial cognizing mechanism of human, the robot constantly received the information of artificial labels at cognitive-guide points in a wide range of structured environment to achieve the perception of the environment and robot navigation. The immune network algorithm was used to form the environmental awareness mechanism with “distributed representation”. The color recognition and SIFT feature matching algorithm were fused to achieve the memory and cognition of scenario tag. Then the cognition-guide-action based cognizing semantic map was built. Along with the continuously abundant map, the robot did no longer need to rely on the artificial label, and it could plan path and navigate freely. Experimental results show that the artificial label designed in this work can improve the cognitive ability of the robot, navigate the robot in the case of semi-unknown environment, and build the cognizing semantic map favorably.

To resolve the path tracking problem of autonomous ground vehicles, an analysis of existing path tracking methods was carried out and an important conclusion was got. The vehicle-road model is crucial for path following. Based on the conclusion, a new vehicle-road model named “ribbon model” was constructed with consideration of road width and vehicle geometry structure. A new vehicle-road evaluation algorithm was proposed based on this model, and a new path tracking controller including a steering controller and a speed controller was designed. The difficulties of preview distance selection and parameters tuning with speed in the pure following controller are avoided in this controller. To verify the performance of the novel method, simulation and real vehicle experiments were carried out. Experimental results show that the path tracking controller can keep the vehicle in the road running as fast as possible, so it can adjust the control strategy, such as safety, amenity, and rapidity criteria autonomously according to the road situation. This is important for the controller to adapt to different kinds of environments, and can improve the performance of autonomous ground vehicles significantly.

In order to measure the backhoe vibratory excavating resistance of a hydraulic excavator fast and precisely, the influences of vibratory excavating depth, angle, vibratory frequency, amplitude, bucket inserting velocity and soil type on the vibratory excavating resistance were analyzed. Simulation analysis was carried out to establish the bucket inserting velocity, amplitude and vibratory frequency considered as secondary variables and excavating resistance as primary variable. A fuzzy membership function was introduced to improve the anti-noise capacity of support vector machine, which is a soft-sensing model on the hydraulic excavator’s backhoe vibratory excavating resistance based on fuzzy support vector machine. The simulation result reveals that its maximum relative training and testing error are nearly 0.68% and −0.47%, respectively. It is concluded that the model has quite high modeling precision and generalization capacity, and it can measure the vibratory excavating resistance accurately, reliably and fast in an indirect way.

To improve the maintainability design efficiency and quality, a layout optimization method for maintainability of multi-component systems was proposed. The impact of the component layout design on system maintainability was analyzed, and the layout problem for maintainability was presented. It was formulated as an optimization problem, where maintainability, layout space and distance requirement were formulated as objective functions. A multi-objective particle swarm optimization algorithm, in which the constrained-domination relationship and the update strategy of the global best were simply modified, was then used to obtain Pareto optimal solutions for the maintainability layout design problem. Finally, application in oxygen generation system of a spacecraft was studied in detail to illustrate the effectiveness and usefulness of the proposed method. The results show that the concurrent maintainability design can be carried out during the layout design process by solving the layout optimization problem for maintainability.

Narrowband radar has been successfully used for high resolution imaging of fast rotating targets by exploiting their micro-motion features. In some practical situations, however, the target image may suffer from aliasing due to the fixed pulse repetition interval (PRI) of traditional radar scheme. In this work, the random PRI signal associated with compressed sensing (CS) theory was introduced for aliasing reduction to obtain high resolution images of fast rotating targets. To circumvent the large-scale dictionary and high computational complexity problem arising from direct application of CS theory, the low resolution image was firstly generated by applying a modified generalized Radon transform on the time-frequency domain, and then the dictionary was scaled down by random undersampling as well as the atoms extraction according to those strong scattering areas of the low resolution image. The scale-down-dictionary CS (SDD-CS) processing scheme was detailed and simulation results show that the SDD-CS scheme for narrowband radar can achieve preferable images with no aliasing as well as acceptable computational cost.

Modeling method for the current control loop of a grid-connected PWM inverter with the LCL output filter was discussed. Firstly, the current control loop with the LCL inverter-side current as feedback was established. Then, parameters of PI controller were calculated on the basis of an equivalent controlled object. Finally, Norton equivalent circuit for the current control loop of grid-connected system was derived by integrating one control equation, which connected the PWM inverter output voltage and the LCL inverter-side current, with two circuit equations, separately using the LCL inverter-side current and the injected current as loop currents. With the induced Norton equivalent circuit, system-level resonant and unstable issues on real grid-connected system applied in weak distributed power systems can be easily analyzed. The validity of substituting Norton equivalent circuit for grid-connected system is verified by simulation and experiment.

A virtual reconfigurable architecture (VRA)-based evolvable hardware is proposed for automatic synthesis of combinational logic circuits at gate-level. The proposed VRA is implemented by a Celoxica RC1000 peripheral component interconnect (PCI) board with an Xilinx Virtex xcv2000E field programmable gate array (FPGA). To improve the quality of the evolved circuits, the VRA works through a two-stage evolution: finding a functional circuit and minimizing the number of logic gates used in a feasible circuit. To optimize the algorithm performance in the two-stage evolutionary process and set free the user from the time-consuming process of mutation parameter tuning, a self-adaptive mutation rate control (SAMRC) scheme is introduced. In the evolutionary process, the mutation rate control parameters are encoded as additional genes in the chromosome and also undergo evolutionary operations. The efficiency of the proposed methodology is tested with the evolutions of a 4-bit even parity function, a 2-bit multiplier, and a 3-bit multiplier. The obtained results demonstrate that our scheme improves the evolutionary design of combinational logic circuits in terms of quality of the evolved circuit as well as the computational effort, when compared to the existing evolvable hardware approaches.

During the last decade, many variants of the original particle swarm optimization (PSO) algorithm have been proposed for global numerical optimization, but they usually face many challenges such as low solution quality and slow convergence speed on multimodal function optimization. A composite particle swarm optimization (CPSO) for solving these difficulties is presented, in which a novel learning strategy plus an assisted search mechanism framework is used. Instead of simple learning strategy of the original PSO, the proposed CPSO combines one particle’s historical best information and the global best information into one learning exemplar to guide the particle movement. The proposed learning strategy can reserve the original search information and lead to faster convergence speed. The proposed assisted search mechanism is designed to look for the global optimum. Search direction of particles can be greatly changed by this mechanism so that the algorithm has a large chance to escape from local optima. In order to make the assisted search mechanism more efficient and the algorithm more reliable, the executive probability of the assisted search mechanism is adjusted by the feedback of the improvement degree of optimal value after each iteration. According to the result of numerical experiments on multimodal benchmark functions such as Schwefel, Rastrigin, Ackley and Griewank both with and without coordinate rotation, the proposed CPSO offers faster convergence speed, higher quality solution and stronger robustness than other variants of PSO.

Quadrature signaling-based cooperative transmission is an efficient and simple scheme to obtain spatial diversity. However, this scheme causes date rate loss compared with direct transmission. In this work, our focus is on recovering from the data rate loss while simultaneously achieving spatial diversity. Particularly, an enhanced quadrature signaling-based cooperative scheme was designed, which can realize full-rate transmission by using the signal space diversity (SSD) technique. Then, accurate bit error rate (BER) expression for the full-rate scheme was derived over independent and non-identically distributed (INID) Rayleigh fading channels. Specifically, a closed-form BER expression is obtained, which is quite tight over the whole SNR range, and thus allows for rapid and efficient evaluation of system performance under various channel conditions. Moreover, an asymptotic approximation of the BER was derived to show that the full-rate scheme can achieve full diversity. Simulation results verify the tightness of the analysis and show that the full-rate scheme significantly outperforms the traditional quadrature signaling-based scheme by about 2 dB with the same complexity order.

In order to effectively solve combinatorial optimization problems, a membrane-inspired quantum bee colony optimization (MQBCO) is proposed for scientific computing and engineering applications. The proposed MQBCO algorithm applies the membrane computing theory to quantum bee colony optimization (QBCO), which is an effective discrete optimization algorithm. The global convergence performance of MQBCO is proved by Markov theory, and the validity of MQBCO is verified by testing the classical benchmark functions. Then the proposed MQBCO algorithm is used to solve decision engine problems of cognitive radio system. By hybridizing the QBCO and membrane computing theory, the quantum state and observation state of the quantum bees can be well evolved within the membrane structure. Simulation results for cognitive radio system show that the proposed decision engine method is superior to the traditional intelligent decision engine algorithms in terms of convergence, precision and stability. Simulation experiments under different communication scenarios illustrate that the balance between three objective functions and the adapted parameter configuration is consistent with the weights of three normalized objective functions.

Seismic signal is generally employed in moving target monitoring due to its robust characteristic. A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural network. For analyzing the seismic signal of the moving objects, the seismic signal of person and vehicle was acquisitioned from the seismic sensor, and then feature vectors were extracted with combined methods after filter processing. Finally, these features were put into the improved BP neural network designed for effective signal classification. Compared with previous ways, it is demonstrated that the proposed system presents higher recognition accuracy and validity based on the experimental results. It also shows the effectiveness of the improved BP neural network.

Feature-based image matching algorithms play an indispensable role in automatic target recognition (ATR). In this work, a fast image matching algorithm (FIMA) is proposed which utilizes the geometry feature of extended centroid (EC) to build affine invariants. Based on affine invariants of the length ratio of two parallel line segments, FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features, and increases the feature diversity of different targets, thus reducing misjudgment rate during recognizing targets. However, it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation. An advanced FIMA is designed to cope with these problems. Experiments prove that the proposed algorithms have better robustness for Gaussian noise, gray-scale change, contrast change, illumination and small three-dimensional rotation. Compared with the latest fast image matching algorithms based on geometry features, FIMA reaches the speedup of approximate 1.75 times. Thus, FIMA would be more suitable for actual ATR applications.

Objective speech quality is difficult to be measured without the input reference speech. Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm. The degraded speech is firstly separated into three classes (unvoiced, voiced and silence), and then the consistency measurement between the degraded speech signal and the pre-trained reference model for each class is calculated and mapped to an objective speech quality score using data mining. Fuzzy Gaussian mixture model (GMM) is used to generate the artificial reference model trained on perceptual linear predictive (PLP) features. The mean opinion score (MOS) mapping methods including multivariate non-linear regression (MNLR), fuzzy neural network (FNN) and support vector regression (SVR) are designed and compared with the standard ITU-T P.563 method. Experimental results show that the assessment methods with data mining perform better than ITU-T P.563. Moreover, FNN and SVR are more efficient than MNLR, and FNN performs best with 14.50% increase in the correlation coefficient and 32.76% decrease in the root-mean-square MOS error.

Singular point (SP) extraction is a key component in automatic fingerprint identification system (AFIS). A new method was proposed for fingerprint singular points extraction, based on orientation tensor field and Laurent series. First, fingerprint orientation flow field was obtained, using the gradient of fingerprint image. With these gradients, fingerprint orientation tensor field was calculated. Then, candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space. The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model. As a global descriptor, the Laurent polynomial coefficients were allowed for rotational invariance. Furthermore, a support vector machine (SVM) classifier was trained to remove spurious SPs, using cross-correlation coefficient as a feature vector. Finally, experiments were performed on Singular Point Detection Competition 2010 (SPD2010) database. Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%, the accuracy of proposed algorithm is 45.34%. The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin, and the detection is invariant to rotational transformations.

Complex conditional statement is one of the bad code smells, which affects the quality of the code and design of software. In the proposed approach, two commonly-used design patterns for handling complex conditional statements are selected, and they are the factory method pattern and the strategy pattern. Two pattern-directed refactoring approaches based on the two design patterns are proposed. Each approach contains a refactoring opportunities identification algorithm and an automated refactoring algorithm. After parsing the abstract syntax tree generated from source code, the refactoring opportunities are identified effectively and automatically. Then, for candidate code, refactoring algorithms are executed automatically, which are used to simplify or remove complex conditional statements. By empirical analysis and quality assessment, the code after refactoring has better maintainability and extensibility, and the proposed approach for automated pattern-directed refactoring succeeds to reduce code size and complexity of classes.

An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter (SHAPF) to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controller was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.

In this work, hydrogen is produced from partial oxidation reforming of dimethyl ether (DME) by a plasma-catalyst hybrid reformer under atmospheric pressure. The plasma-catalyst hybrid reformer which includes both plasma and catalyst reactors is designed. A spark discharge is used as a non-equilibrium plasma source, and it is used to ionize the mixture of DME and air. The performances of the reformer are characterized experimentally in terms of gas concentrations, hydrogen yield, DME conversion ratio, and specific energy consumption. The effects of discharge frequency, reaction temperature, air-to-DME ratio and space velocity are investigated. The experimental results show that the plasma-catalyst hybrid reformer enhances hydrogen yield when reaction temperature drops below 620 °C. At 450 °C, hydrogen yield of hybrid reforming is almost three times that of catalyst reforming. When space velocity is 510 h⁻¹, hydrogen yield is 67.7%, and specific energy consumption is 12.2 kJ/L-H₂.

The reduction of Cr(VI) in aqueous solution by using bauxite ore was investigated. Experimental results for Cr(VI) reduction in aqueous solution depending on some factors such as time, sulfuric acid amount, bauxite dosage, initial Cr(VI) concentration, formic acid concentration, daylight and temperature were presented. The obtained results show that sulfuric acid amount, bauxite dosage and initial Cr(VI) concentration of solution are most effective parameters on the reduction process. Also, it has been found that the 60 g/L of bauxite dosage is sufficient to reduce up to 100% of Cr(VI) from acidic solution under the condition of low initial Cr(VI) mass concentrations such as 10 mg/L. The reduction reaction is completed within 30 min at 25 °C under the experimental conditions: bauxite dosage of 60 g/L, amount of sulfuric acid 40–60 stoichiometric and initial mass concentration of Cr(VI), 10 mg/L. It was determined that reduction percentage is decreasing with increasing initial Cr(VI) concentration. The chemical oxygen demand of bauxite ore was found to be 26 mg COD/g.

The removal of phosphate from aqueous solution by Donnan dialysis with anion-exchange membrane was investigated. The results show that phosphate could be removed from aqueous solution without supplying external high pressure or electrical potential. Under the conditions of influent phosphate of 2.0 mg/L, counterion(Cl⁻) concentration of 0.1 mol/L, stirring speed of 500 r/min and phase temperature of 298 K, the removal of phosphate achieves 70.0%. Decreasing counterion concentration has little influence on the removal of phosphate, but phosphate amount in anion-exchange membrane increases significantly. With the increase of stirring speed and phase temperature, the removal efficiency of phosphate greatly is improved. Existing forms of phosphate in aqueous solution affected transport of phosphate and only strong acidic pH of feed solution (pH=3.0) decreases the removal of phosphate. Transport of phosphate is also accompanied by change of pH value of feed solution. In consequence, it might be a promise potential process for phosphate advanced wastewater treatment, especially in the area where high salted nature water can be utilized.

The adsorption of sulfate in aqueous solutions onto organo-nano-clay prepared by natural zeolite and cationic surfactant cetyltrimethylammonium bromide (CTAB) was studied. Parameters such as adsorbent dosage, contact time and temperature were investigated using batch adsorption studies. The results show that the uptake of sulfate increases with the increase of contact time and temperature, and decreases with the increase of dosage. The Freundlich isotherm model is fit to explain the sulfate adsorption onto organo-nano-clay. The maximum adsorption capacity is found to be 38.02 mg/g at 40 °C. The kinetic data fit well the pseudo-second-order and Elovich models with a R² more than 0.98. It is suggested that chemisorption is the rate-controlling step for adsorption of sulfate onto organo-nano-clay, meanwhile both intraparticle diffusion and boundary layer diffusion also contribute as well. Ion-exchange between sulfate anions and bromide ions and complexation between sulfate anions and CTAB cations are responsible for the mechanism of sulfate adsorption.

The mechanism of removing phosphate by MSWI (municipal solid waste incineration) fly ash was investigated by SEM (scanning electron microscopy) with EDS (energy dispersion spectrum), XRD (X-ray diffraction), FT-IR (Fourier transform infrared spectroscopy), BET (specific surface area), and BJH (pore size distribution). The results indicate that the removal rate of phosphate (100 mg/L) in 50 mL phosphorus wastewater reaches at 99.9% as the dosage of MSWI fly ash being 0.9000 g under room temperature. The specific surface area of MSWI fly ash is less than 6.1 m²/g and the total pore volume is below 0.021 cm³/g, suggesting that the absorption capacity of calcite is too weak to play an important role in phosphate removal. SEM images show that drastic changes had taken place on its specific surface shape after reaction, and EDS tests indicate that some phosphate precipitates are formed and attached onto MSWI fly ash particles. Chemical precipitation is the main manner of phosphate removal and the main reaction is: 3Ca²⁺+2 PO₄³⁻+xH₂O→Ca₃(PO₄)₂↓·xH₂O. Besides, XRD tests show that the composition of MSWI fly ash is complex, but CaSO₄ is likely to be the main source of Ca²⁺. The soluble heavy metals in MSWI fly ash are stabilized by phosphate.

High salinity industrial wastewater is difficult to treat using biological treatment system because of the high concentrations of salt. The potential of a sequencing batch biofilm reactor (SBBR) process in treating synthetic high salinity wastewater was evaluated at laboratory scale during a 110-day operation. The reactor was operated in a 12 h cycle, and each cycle consisted of 0.25 h influent addition, 8 h aeration, 3 h anoxic reaction, 0.5 h sedimentation and 0.25 h effluent withdrawal. Gradual increase in salinity gradient was applied during the acclimatization period. The acclimated SBBR system was demonstrated to be an effective process to remove organic compounds and ammonia nitrogen under high salinity conditions with chemical oxygen demand (COD) and ammonia nitrogen (NH₃-N) removal efficiencies of 88% and 80%, respectively. The microscopic examination indicated that rather than rotifers or vorticella, the zoogloea, filamentous fungus mingled with a small quantity of swimming infusorians were dominant bacteria in SBBR system. The removal efficiencies close to 80% in COD and 75% in NH₃-N were achieved at an organic loading rate (OLR) of 0.96 kg COD/(m³·d), pH of 7.0, salinity of 14 g/L and NH₃-N of 30 mg/L.

The elevated supersaturation of total dissolved gas (TDG) downstream of a high-dam spill has deleterious effects on fish in a large range. A one-dimensional (1-D) longitudinal model is optimal for the prediction of supersaturated TDG dissipation over a long distance. The key issue of the model is to determine the dissipation coefficient accurately. In agreement with field observations and experiment data, dimensional analysis and regression were performed to propose a formula for estimating the dissipation coefficient of supersaturated TDG in various rivers and reservoirs, and it involves the effects of the turbulence intensity, the hydro-pressure and the solid-liquid interface. The friction velocity, water depth, hydraulic radius and Froude number are independent variables in the formula which are easy to determine in practical applications. The 1-D longitudinal model is implemented to calculate the dissipation of TDG in a reach of the Jinsha River. Good agreement is found between the calculated results and field data for both the dissipation coefficient and the dissipation process.

Soil cadmium (Cd) contamination resulted from mining and smelting is a major environmental concern, and health risk associated with Cd exposure to multi-media through muti-pathway is increasing. Cd concentrations in soils, vegetables and paddy rice were investigated, and potential non-carcinogenic and carcinogenic health risks exposure to Cd were estimated at six villages around the Dabaoshan Mine, South China. A total of 87 soil samples were found to exceed the China’s maximum permission level (MPL) for Cd, while the highest value of 4.42 mg/kg was found near irrigation ditch associated with Hengshi River in Xinyi (XY) Village. Cd contents in vegetables and rice exceeded the maximum permissible concentration by more than five times in every village. Cadmium accumulation in plants is in the order of celery > lactuca sativa L > Chinese cabbage > Romaine lettuce > asparagus lettuce > mustard > cabbage mustard > cabbage. The mean hazard quotient (HQ) of all villages is in the range of [5.29, 25.75], and the mean values of cancer risk for investigated areas are more than 10 times greater than the USEPA (2009) threshold limit value of 10⁻⁴. Moreover, human non-carcinogenic and carcinogenic risks are mainly attributable to paddy rice intake, followed by vegetables intake, soil ingestion, inhalation, and dermal contact. The results indicate that Cd has a huge potential risk on human health for the local residents.

Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation. This work introduces a geostatistical technique that has been developed and tested in an iron ore deposit at Bafq mining district, in central Iran, and that, based on a probability criterion, helps to objectively model the geometry of this iron ore deposit. The main problem in reserve estimation of this ore body is its geometrical modeling and uncertainty in geological boundaries. This work deals with the geostatistical method of multiple indicator kriging, which is used to determine the real boundaries of ore body in different categories. This approach has potential to improve project performance and decrease operational risk. For this purpose, the ore body is separated into two categories including rich iron zone (w(Fe)>45%) and poor iron zone (20%<w(Fe)<45%). It significantly benefits to decrease the risk of reserve evaluation in the deposit. This case study also highlights the value of multiple indicator kriging as a tool for estimates the position of grade boundaries within the deposit. Comparison of the resultant probability maps with the real ore/waste contacts on the extracted levels shows that the first indicator model could separate the whole ore body (poor plus rich) from the waste zone by probability of more than 0.35, which concludes the total reserve of 53 million tons. The second indicator model applied to separate the rich and poor domains and the results show that the blocks with the estimated probability of equal to or more than 0.4 lay within the rich ore zone consisting of 15.8 million tons reserve.

Nonlinear resistivity inversion requires efficient artificial neural network (ANN) model for better inversion results. An evolutionary BP neural network (BPNN) approach based on differential evolution (DE) algorithm was presented, which was able to improve global search ability for resistivity tomography 2-D nonlinear inversion. In the proposed method, Tent equation was applied to obtain automatic parameter settings in DE and the restricted parameter F_crit was used to enhance the ability of converging to global optimum. An implementation of proposed DE-BPNN was given, the network had one hidden layer with 52 nodes and it was trained on 36 datasets and tested on another 4 synthetic datasets. Two abnormity models were used to verify the feasibility and effectiveness of the proposed method, the results show that the proposed DE-BP algorithm has better performance than BP, conventional DE-BP and other chaotic DE-BP methods in stability and accuracy, and higher imaging quality than least square inversion.

Yingcheng Formation is a set of volcanic strata composed of lava rocks, volcanic clastic rocks and sedimentary rocks, filled in some fault depressions in Songliao Basin, early Cretaceous. The study about litho-facies succession of Yingcheng Formation in the outcropped area of the southeast margin and in Xujiaweizi fault depression and its distribution based on analysis of seismic data, shows that the sequence of volcanic strata is quite different from the clastic sedimentary sequence. To study the architecture of volcanic sequence and its structural control of Yingcheng Formation in Songliao Basin, in this work, dividing of the volcanic sequence and dating of the sequence boundaries were finished firstly, then displacement and displacement rate of faults were calculated. The results show that, sample ages of top of the first member, the seconde member, and the third member are 127 Ma, 115 Ma, 110.7 Ma, respectively and sample age of the bottom of the third member is 114.7 Ma. The maximum displacement and displacement rate of the fault 1 are 3 km and 300 m/Ma, respectively, and those of the fault 2 are 3 km and 1000 m/Ma. Studies suggest that, the cooling unit of lava rock or pyroclastic rock is a basic genetic stratigraphic unit in volcanic sequence stratigraphy. Cooling units can construct a parasequence reflecting a volcanic eruption stage. A sequence was superimposed by some parasequences, responding to a volcanic active cycle. There are three types of volcanic sequences in Yingcheng Formation: type of explosion, type of effusion and type of mixed explosion-effusion. The surface of the volcanic sequence, an unconformity surface widely spread and traced in seismic profiles, is a base for analysis of volcanic sequence. The development of volcanic sequence was controlled by faulting, and the curves of fault displacement (rate) can reflect this control. The preservation of volcanic sequence was controlled by the type of volcanic structure and the regional subsidence, also different from that of the sedimentary. The type of volcanic structure of Xujiaweizi was a volcanic depression during the forming of Yingcheng Formation, and the breakdowns of volcanoes and structural subsidence were key factors in the volcanic sequences preservation.

Employing an ideal elasto-plastic model, the typically used strength reduction method reduced the strength of all soil elements of a slope. Therefore, this method was called the global strength reduction method (GSRM). However, the deformation field obtained by GSRM could not reflect the real deformation of a slope when the slope became unstable. For most slopes, failure occurs once the strength of some regional soil is sufficiently weakened; thus, the local strength reduction method (LSRM) was proposed to analyze slope stability. In contrast with GSRM, LSRM only reduces the strength of local soil, while the strength of other soil remains unchanged. Therefore, deformation by LSRM is more reasonable than that by GSRM. In addition, the accuracy of the slope’s deformation depends on the constitutive model to a large degree, and the variable-modulus elasto-plastic model was thus adopted. This constitutive model was an improvement of the Duncan-Chang model, which modified soil’s deformation modulus according to stress level, and it thus better reflected the plastic feature of soil. Most importantly, the parameters of the variable-modulus elasto-plastic model could be determined through in-situ tests, and parameters determination by plate loading test and pressuremeter test were introduced. Therefore, it is easy to put this model into practice. Finally, LSRM and the variable-modulus elasto-plastic model were used to analyze Egongdai ancient landslide. Safety factor, deformation field, and optimal reinforcement measures for Egongdai ancient landslide were obtained based on the proposed method.

Effect of soil displacement on friction single pile in the cases of tunneling, surcharge load and uniform soil movement was discussed in details with finite element method. Lateral displacement of the pile caused by soil displacement reached about 90% of the total displacement, which means that P-Δ effect of axial load can be neglected. The maximum moment of pile decreased from 159 kN·m to 133 kN·m in the case of surcharge load when the axial load increased from 0 to the ultimate load. When deformation of pile caused by soil displacement is large, axial load applied on pile-head plays the role of reducing the maximum bending moment in concrete pile to some extent. When pile is on one side of the tunnel, soil displacements around the pile are all alike, which means that the soil pressures around the pile do not decrease during tunneling. Therefore, Q-s curve of the pile affected by tunneling is very close to that of pile in static loading test. Bearing capacities of piles influenced by surcharge load and uniform soil movement are 2480 kN and 2630 kN, respectively, which are a little greater than that of the pile in static loading test (2400 kN). Soil pressures along pile increase due to surcharge load and uniform soil movement, and so do the shaft resistances along pile, as a result, when rebars in concrete piles are enough, bearing capacity of pile affected by soil displacement increases compared with that of pile in static loading test.

Based on the axial stress-axial strain curves, the effect of fissure angle on the strength and deformation behavior of sandstone specimens containing combined flaws is analyzed. The mechanical parameters of sandstone specimens containing combined flaws are all lower than that of intact specimen, but the reduction extent is distinctly related to the fissure angle. The results of sandstone specimens containing combined flaws are obtained by the acoustic emission, which can be used to monitor the crack initiation and propagation. The ultimate failure mode and crack coalescence behavior are evaluated for brittle sandstone specimens containing combined flaws. Nine different crack types are identified on the basis of their geometry and crack coalescence mechanism (tensile crack, hole collapse, far-field crack and surface spalling) for combined flaws. The photographic monitoring was also adopted for uniaxial compression test in order to confirm the sequence of crack coalescence in brittle sandstone specimens containing combined flaws, which recorded the real-time crack coalescence process during entire deformation. According to the monitored results, the effect of crack coalescence process on the strength and deformation behavior is investigated based on a detailed analysis for brittle sandstone specimens containing combined flaws by using digital photogrammetry.

The stress state around circular openings, such as boreholes, shafts, and tunnels, is usually needed to be evaluated. Solutions for stresses, strains and ultimate bearing capacities of pressurized hollow cylinder are common cases. Stress analytical method for plane problem of a double-layered thick-walled cylinder subjected to a type of non-uniform pressure on the outer surface and uniform radial pressure on the inner surface is given. The power series method of complex function is used. The stress analytical solution is obtained with the assumption that two layers of a cylinder are fully contacted. The distributions of normal and tangential contact stress along the interface, tangential stress on the inner boundary and stresses in the radial direction at θ=0°, 45° and 90°, are obtained. An example indicates that, when the elastic modulus of the inner layer of a double-layered thick-walled cylinder is smaller than that of the outer layer, the tangential stress is smaller than that in the corresponding point for a traditional cylinder composed of homogeneous materials. In that way, stress concentration at the inner surface can be alleviated and the stress distribution is more uniform. This is a capable way to enhance the elastic ultimate bearing capacity of thick-walled cylinder.

Due to outstanding ductility and high strength, the steel plate shear wall (SPSW) is recognized as a good lateral system for building structures; particularly as it interacts with earthquake resistant design. This study aims to reveal the dynamic and cyclic behavior of steel plated shear wall. Finite element method of analysis was implemented in order to simulate the behavior of such a wall structure. To determine the dynamic behavior of un-stiffened plate shear wall, two different analytical models were implemented. The post buckling strength of steel plate subjected to lateral loading was also employed. The story shear-drift diagrams of steel shear wall system were presented. The strength and ductility of the system obtained from the analysis were compared with those of steel shear wall tests reported before. The pertinent parameters of the steel shear wall system such as plate thickness, column and beam stiffness and the plate aspect ratio were recognized and their effects were recorded. The effect of stiffeners on the behavior of the SPSW was also investigated.

Fatigue has become critical issue for bridge with orthotropic steel deck. Number of stress cycle and equivalent stress amplitude were adopted as two investigated fatigue effects. As presented from fatigue monitoring comparison of two series-lined bridges, three local geometric parameters of steel box girder have significant influence on fatigue performance of two welded joints. They are thickness of longitudinal ribs (T_r), longitudinal spacing of transverse floor plate (S_c) and longitudinal truss (L_T). Fatigue analytical models were created for parametric study of fatigue effects under wheel load. Consequently, three local parameters have exhibited insignificant influence on number of stress cycle. Compared with T_r and S_c, configuration of L_T has brought about foremost effect on the equivalent stress amplitude. For equivalent stress amplitude of rib-to-deck and rib-to-rib welded joints, the influence regions of L_T are respectively longitudinal strap and quadrate with the geometric length of 600 mm. Enough attention ought to be paid for local stiffen structure on fatigue performance of orthotropic steel deck in fatigue design and monitoring.

To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states, a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work. First of all, the road traffic running states were divided into several different modes. The concept of the regional traffic attracters of the target link was put forward for effective matching. Then, the reference sequences of characteristics of traffic running states with the contents of the target link’s traffic running states and regional traffic attracters under different modes were established. In addition, the current and historical regional traffic attracters of the target link were matched through certain matching rules, and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data, which were processed with Kalman filter to obtain the final recovery data. Finally, some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm. The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.