Key problems in validation of intelligent models

To provide a realistic simulation environment for users,intelligent models have become key components in military simulations. After the analysis of modeling nature of intelligent models,the validation criteria for defining the validation points and validation metrics for measuring the agreements between human experts and intelligent models were presented. Further,such methods as graphical comparison,feature analysis and face validation were discussed according to the characteristics of intelligent models. Based on the validation criteria,validation metrics and validation methods,the intelligent models can be effectively validated,which has been proved in current developed intelligent models.     

Water quality and growth of phytoplankton for the Yellow River estuary reservoirs—The nutrients release from reservoir sediments

Effects of nutrients released from sediments on eutrophication in lakes and reservoirs were not well known in China. In the test, the release conditions of nitrogen and phosphorus from the sediments were observed by batch experiment. The test results revealed that the content released is correlated to the initial content of organic matter in sediments. In the Gengjing area, when the water quality of waterway, grit chamber and reservoir were compared, the water quality of the waterway was the highest, and lowered in the order of the grit chamber and the reservoir. The grit chamber could get not only fine sand removal but also the organic substance, nitrogen, phosphorus and phytoplankton, therefore it is important to operate and maintain the grit chamber to preserve the water quality of the reservoir. Due to little organic substance in sediments, ammonium nitrogen and phosphorus weren’t released during the incubation. But from the absorptiometric turbidity unit (ATU) test results, although the release of ammonium concentration was very low, ammonium oxidizing and nitrite oxidizing bacteria existed in sediments.     

Residual monomer content and its release into water from the denture base nanocomposite using organic montmorillonite as reinforcement

A novel kind of denture base nanocomposite was prepared by polymethyl methyacrylate（PMMA） and cethyltrimethylammonium bromide modified organic montmorillonite （OMMT）. The dispersion of montmorillonite in the polymer matrix was characterized by x-ray diffraction （XRD） and transimission electron microscope （TEM）.The content of residual MMA in nanocomposites and the amount of MMA released to water from nanocomposites were determined by gas chromatography （GC）. The analysis of TEM and XRD showed that exfoliated-intercalated and intercalated nanocomposites were formed when the content of OMMT was 3% and 5% in the PMMA powder respectively. The results of GC showed that the residual MMA increased with the increase of OMMT content in the polymer matrix. After 7 days in water, the amount of MMA released into water from the nanocomposites tended to be stable. The results of one-way ANOVA and t-test showed that OMMT gave a significant increase of residual MMA concentration （p〈0.05） in nanocomposites.     

Prediction on contaminant migration in aquifer of fractured granite substrata of landfill

Nowadays, a certain amount of landfills in China were constructed without horizontal liner system. The research conducted focuses mainly on the contaminants from landfill leachate migrating in the aquifer of a fractured granite area, and pollution predictions for groundwater were made by establishing numerical model with Visual Modflow combining field investigation like geological surveys, drilling, geophysical explorations, hydrogeological experiments, water quality analysis. The transportation of the chloride ion from landfill in the aquifer was simulated in the model with time frames of 2 555, 3 650, 5 475 and 7 300 d. The model shows that from 2 555 d to 7300 d starting from 2003, the chloride ion migrated from 900 m to 1300 m, respectively, along the groundwater flow. The results indicate that as leachate plume migrated in the aquifer, the concentration of the pollutants can be up to 19.74 to 251.76 times that of background value. The research proves that the leachate poses a threat to the local water body and offers a reference towards groundwater pollution prevention for fractured granite landfill sites.     

Hazard degree identification of goafs based on scale effect of structure by RS-TOPSIS method

In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set(RS)theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western China, whose indexes parameters were measured by cavity monitoring system(CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades’ typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution(TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified.Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement,while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.     

Mathematical model of heat transfer for bloom continuous casting

A mathematical model for heat transfer during solidification in continuous casting of automobile steel, was established on researching under the influence of the solidifying process of bloom quality of CCM in the EAF steelmaking shop, at Shijiazhuang Iron and Steel Co. Ltd. Several steel grades were chosen to research, such as, 40Cr and 42CrMo. According to the results of the high temperature mechanical property tests of blooms, the respective temperature curves for controlling the solidification of different steels were acquired, and a simulating software was developed. The model was verified using two methods, which were bloom pinshooting and surface strand temperature measuring experiments. The model provided references for research on the solidifying process and optimization of a secondary cooling system for automobile steel. Moreover, it was already applied to real production. The calculated temperature distribution and solidification trend of blooms had offered a reliable theory for optimizing the solidifying process of blooms, increasing withdrawal speed, and improving bloom quality. Meanwhile, a new secondary cooling system was designed to optimize a secondary cooling water distribution, including choice and arrangements of nozzles, calculation of cooling water quantity, and so on. 2008 University of Science and Technology Beijing. All rights reserved.     

Outdoor thermal environmental research of the mountainous city by GIS

The study of urban outdoor thermal environment was carried out in one of the mountainous cities by using geography information system（GIS） technique which is connected with predicting and evaluating models for the outdoor thermal environment, monitoring data and simulating data. A prediction and evaluation system were set up. A typical mountainous city, i. e. , Yunyang city in Chongqing in China, was taken as an example, its urbanization trend and population growth was predicted and evaluated. The heat island intensity and its trend were simulated, the temperature field, velocity field and the humidity field were analyzed. The results show that GIS is an effective tool to deal with the outdoor thermal environment, especially for the mountainous cities with special geographical particularities. GIS can be used in the environmental management and the city planning especially for the mountainous cities.     

Visual attention and clustering-based automatic selection of landmarks using single camera

An improved method with better selection capability using a single camera was presented in comparison with previous method. To improve performance, two methods were applied to landmark selection in an unfamiliar indoor environment. First, a modified visual attention method was proposed to automatically select a candidate region as a more useful landmark. In visual attention, candidate landmark regions were selected with different characteristics of ambient color and intensity in the image. Then, the more useful landmarks were selected by combining the candidate regions using clustering. As generally implemented, automatic landmark selection by vision-based simultaneous localization and mapping（SLAM） results in many useless landmarks, because the features of images are distinguished from the surrounding environment but detected repeatedly. These useless landmarks create a serious problem for the SLAM system because they complicate data association. To address this, a method was proposed in which the robot initially collected landmarks through automatic detection while traversing the entire area where the robot performed SLAM, and then, the robot selected only those landmarks that exhibited high rarity through clustering, which enhanced the system performance. Experimental results show that this method of automatic landmark selection results in selection of a high-rarity landmark. The average error of the performance of SLAM decreases 52% compared with conventional methods and the accuracy of data associations increases.     

Geometric precision evaluation methodology of multiple reference station network algorithms

To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.     

New empirical model to evaluate groundwater flow into circular tunnel using multiple regression analysis

There are various analytical, empirical and numerical methods to calculate groundwater inflow into tunnels excavated in rocky media. Analytical methods have been widely applied in prediction of groundwater inflow to tunnels due to their simplicity and practical base theory. Investigations show that the real amount of water infiltrating into jointed tunnels is much less than calculated amount using analytical methods and obtained results are very dependent on tunnel‘s geometry and environmental situations.In this study, using multiple regression analysis, a new empirical model for estimation of groundwater seepage into circular tunnels was introduced. Our data was acquired from field surveys and laboratory analysis of core samples. New regression variables were defined after perusing single and two variables relationship between groundwater seepage and other variables. Finally, an appropriate model for estimation of leakage was obtained using the stepwise algorithm. Statistics like R, R~2, R_P~2 and the histogram of residual values in the model represent a good reputation and fitness for this model to estimate the groundwater seepage into tunnels. The new experimental model was used for the test data and results were satisfactory. Therefore, multiple regression analysis is an effective and efficient way to estimate the groundwater seepage into tunnels.     

A novel SINR and mutual information based radar jamming technique

The improvements of anti-jamming performance of modem radar seeker are great threats to military targets. To protect the target from detection and estimation, the novel signal-to-interference-plus-noise ratio （SINR）-based and mutual information （Ml）-based jamming design techniques were proposed. To interfere with the target detection, the jamming was designed to minimize the S1NR of the radar seeker. To impair the estimation performance, the mutual information between the radar echo and the random target impulse response was used as the criterion. The spectral of optimal jamming under the two criteria were achieved with the power constraints. Simulation results show the effectiveness of the jamming techniques. SINR and MI of the SINR-based jamming, the MI-based jamming as well as the predefined jamming under the same power constraints were compared. Furthermore, the probability of detection and minimum mean-square error （MMSE） were also utilized to validate the jamming performance. Under the jamming power constraint of I W, the relative decrease of the probability of detection using S1NR-based optimal jamming is about 47%, and the relative increase of MMSE using Ml-based optimal jamming is about 8%. Besides, two useful jamming design principles are concluded which can be used in limited jamming power situations.     

Distributed collaborative extremum response surface method for mechanical dynamic assembly reliability analysis

To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline （MOMD）,distributed collaborative extremum response surface method （DCERSM） was proposed based on extremum response surface method （ERSM）.Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function （ERSF）.Finally,this model was applied to the reliability analysis of blade-tip radial running clearance （BTRRC） of an aeroengine high pressure turbine （HPT） to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability （DAR） analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.     

A unified approach of observability analysis for airborne SLAM

An unmanned aerial vehicle （UAV） is arranged to explore an unknown environment and to map the features it finds when GPS is denied.It navigates using a statistical estimation technique known as simultaneous localization and mapping （SLAM） which allows for the simultaneous estimation of the location of the UAV as well as the location of the features it sees.Obscrvability is a key aspect of the state estimation problem of SLAM.However,the dimension and variables of SLAM system might be changed with new features.To solve this issue,a unified approach of observability analysis for SLAM system is provided,through reorganizing the system model.The dimension and variables of SLAM system keep steady,then the PWCS theory can be used to analyze the local or total observability,and under special maneuver,some system states,such as the yaw angle,become observable.Simulation results validate the proposed method.     

Competitive adsorption of Cu（Ⅱ） and Pb（Ⅱ） ions from aqueous solutions by Ca-alginate immobilized activated carbon and Saccharomyces cerevisiae

To establish a theoretical foundation for simultaneous removal of multi-heavy metals,the adsorption of Cu（Ⅱ） and Pb（Ⅱ） ions from their single and binary systems by Ca-alginate immobilized activated carbon and Saccharomyces cerevisiae （CAS） was investigated.The CAS beads were characterized by Scanning electron microscope （SEM） and Fourier transformed infrared spectroscopy （FTTR）.The effect of initial pH,adsorbent dosage,contact time and initial metal ions concentration on the adsorption process was systematically investigated.The experimental maximum contents of Cu（Ⅱ） and Pb（Ⅱ） uptake capacity were determined as 64.90 and 166.31 mg/g,respectively.The pseudo-second-order rate equation and Langmuir isotherm model could explain respectively the kinetic and isotherm experimental data of Cu（Ⅱ） and Pb（Ⅱ） ions in single-component systems with much satisfaction.The experimental adsorption data of Cu（Ⅱ） and Pb（Ⅱ） ions in binary system were best described by the extended Freundlich isotherm and the extended Langmuir isotherm,respectively.The removal of Cu（lⅡ） ions was more significantly influenced by the presence of the coexistent Pb（Ⅱ） species,while the Pb（Ⅱ） removal was affected slightly by varying the initial concentration of Cu（Ⅱ）.The CAS was successfully regenerated using 1 mol/L HNO3 solution.     

Dynamic assets allocation based on market microstructure model with variable-intensity jumps简

In order to characterizc large fluctuations of the financial markets and optimize financial portfolio, a new dynamic asset control strategy was proposed in this work. Firstly, a random process item with variable jump intensity was introduced to the existing discrete microstructure model to denote large price fluctuations. The nonparametric method of LEE was used for detecting jumps. Further, the extended Kalman filter and the maximum likelihood method were applied to discrete microstructure modeling and the estimation of two market potential variables： market excess demand and liquidity. At last, based on the estimated variables, an assets allocation strategy using evolutionary algorithm was designed to control the weight of each asset dynamically. Case studies on IBM Stock show that jumps with variable intensity are detected successfully, and the assets allocation strategy may effectively keep the total assets growth or prevent assets loss at the stochastic financial market.     

Thermogravimetric characteristics and different kinetic models for medical waste composition containing polyvinyl chloride-transfusion tube简

Thermogravimetric study of medical transfusion tube （MTT） waste containing polyvinyl chloride （PVC） was carried out using the thermogravimetric analyser （TGA） with N2, at different heating rates of 5, 10, 20, 30, 50 ℃/min. The purpose is to obtain pyrolysis characteristics and kinetic parameters of medical waste. The experimental results indicate that the pyrolysis behavior of the MTT sample is in agreement with its main ingredient of PVC, appearing two stair stepping stages. The influence of the additives in MTT on pyrolysis behavior was also revealed, which could improve MTT pyrolysis at lower temperature in the first stage, and cause obvious unsmoothness and asymmetry of the second DTG peak. Four n-order kinetic models of Coats-Redfern, Ozawa, Kissinger and Freeman-carroll were used to get the kinetic parameters. Furthermore, a novel ＂two-step four-reaction model＂ was established to simulate the whole continuous process. The different methods and the kinetic parameters thus obtained were discussed and compared with each other in literatures. The reasons of deviation among kinetic values were tried to be elucidated. The new established model could more satisfactorily describe the pyrolysis process of MTT, being more mechanistic and conveniently serving for the engineering.     

Resolution performance analysis of cumulants-based rank reduction estimator in presence of unexpected modeling errors

Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and mitigating the negative influences of the Gaussian colored noise. However, in the presence of unexpected modeling errors, the resolution behavior of the FOC-RARE also deteriorate significantly as SOS-RARE, even for a known array covariance matrix. For this reason, the angle resolution capability of the FOC-RARE was theoretically analyzed. Firstly, the explicit formula for the mathematical expectation of the FOC-RARE spatial spectrum was derived through the second-order perturbation analysis method. Then, with the assumption that the unexpected modeling errors were drawn from complex circular Gaussian distribution, the theoretical formulas for the angle resolution probability of the FOC-RARE were presented. Numerical experiments validate our analytical results and demonstrate that the FOC-RARE has higher robustness to the unexpected modeling en＇ors than that of the SOS-RARE from the resolution point of view.     

Effects of H3PO4 and Ca（H2PO4）2 on mechanical properties and water resistance of thermally decomposed magnesium oxychloride cement

The effects of H3PO4 and Ca（H2PO4）2 on compressive strength, water resistance, hydration process of thermally decomposed magnesium oxychloride cement （TDMOC） pastes were studied. The mineral composition, hydration products and hydration heat release were analyzed by XRD, FT-IR, SEM and TAM air isothermal calorimeter, etc. After being modified by H3PO4 and Ca（HzPO4）2, the properties of the TDMOC are improved obviously. The compressive strength increases from 14.8 MPa to 48.1 MPa and 37.1 MPa, respectively. The strength retention coefficient （Kn） increases from 0.38 to 0.99 and 0.94, respectively. The 24 h hydration heat release decreases by 10% and 4% and the time of hydration peak appearing is delayed from 1 h to about 10 h. The XRD, FT-IR and SEM results show that the main composition is 5Mg（OH）z＇MgCIz＇8H20 in the modified TDMOC pastes. The possible mechanism for the strength enhancement was discussed. The purposes are to extend the potential applications of the salt lake magnesium resources and to improve the mechanical properties of TDMOC.     

Human action recognition based on chaotic invariants

A new human action recognition approach was presented based on chaotic invariants and relevance vector machines （RVM）. The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action. The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory. Then, some chaotic invariants representing action can be captured in the reconstructed phase space. Finally, RVM was used to recognize action. Experiments were performed on the KTH, Weizmann and Ballet human action datasets to test and evaluate the proposed method. The experiment results show that the average recognition accuracy is over 91.2%, which validates its effectiveness.     

Independent component analysis approach for fault diagnosis of condenser system in thermal power plant简

A statistical signal processing technique was proposed and verified as independent component analysis （ICA） for fault detection and diagnosis of industrial systems without exact and detailed model. Actually, the aim is to utilize system as a black box. The system studied is condenser system of one of MAPNA＇s power plants. At first, principal component analysis （PCA） approach was applied to reduce the dimensionality of the real acquired data set and to identify the essential and useful ones. Then, the fault sources were diagnosed by ICA technique. The results show that ICA approach is valid and effective for faults detection and diagnosis even in noisy states, and it can distinguish main factors of abnormality among many diverse parts of a power plant＇s condenser system. This selectivity problem is left unsolved in many plants, because the main factors often become unnoticed by fault expansion through other parts of the plants.