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In the future ten years, the mining depths of more than 30% metal mines will exceed 1000 m. Deep metal mining is confronted with complex geological conditions such as high in-situ stress, high ground temperature, highly-changeable grounds and strong mining disturbance, which bring severe challenges to roadway construction. Due to the shortcomings of noncontinuous operation, low construction rate and frequent disaster occurrence, traditional drilling-and-blasting method cannot meet the construction requirement, therefore the use of tunnel boring machine (TBM)for continuous mechanical tunnelling becomes the future development direction of deep metal mine roadway construction. However, due to the distinctive engineering geological features and roadway construction requirements, the application of TBM tunnelling technology in deep metal mine roadway construction still suffers from some technological problems and challenges. First, this paper summarizes the three main application difficulties for TBM tunnelling technology in deep metal mine roadway construction; 1) the lack of adaptative TBM type selection and machine design theory; 2) the lack of high efficient TBM tunnelling technology; 3) the lack of prewarning, prevention and control technology for engineering disasters. Then, this paper introduces the current research progresses for TBM tunnelling technology in deep metal mine roadway construction from six aspects, i. e., efficient rock breakage theory for cutterhead and cutters, adaptative TBM type selection and machine design technology, accurate tunnelling performance prediction and evaluation methodology, tunnelling technology for small turning radius or highly-inclined roadways, intelligent prewarning, prevention and control technology for engineering disasters, intelligent decision-making and assisted-driving technology. The above research progresses primarily indicate the development direction for the extensive application of TBM tunnelling technology for rapid roadway construction in deep metal mines. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Henan University of Science & Technology, Natural Science is the property of Editorial Office of Journal of Henan University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To cope with the problem that individual identification of communication emitter suffers from the lack of labeled samples,the semi-supervised machine learning theory is introduced,and a semi-supervised learning iterative algorithm based on confidence of prediction(CP-TSVM) is proposed. The algorithm iter-ates according to the reliability of the predicted results on the basis of TSVM,which can greatly reduce the computation of the classifier. In the data set of radiation source signal generated by simulation,CP-TSVM can guarantee the recognition accuracy and shorten the model training time nearly 60 s,compared with the TSVM algorithm when the number of labeled samples accounted for 2% of the total samples. [ABSTRACT FROM AUTHOR]

Considering the non-linearity of grain yield, the prediction model of support vector machine was proposed based on hybrid intelligent algorithm. To solve the problem that particle swarm optimization (PSO) was easy to fall into a local optimum, the hybrid intelligent algorithm (GAPSO-AFSA) was proposed by combining the improved PSO and the artificial fish swarm algorithm (AFSA).The objective function value was quickly converged to the global optimal solution by the mutation cross within the swarm and the external competition mechanism. The global search ability of the algorithm was improved to obtain the optimal parameter combination of support vector machine. The support vector machine prediction model was used to predict Chinese grain yield, and the model correctness was verified by the experiments.The results show that the prediction model has good prediction result. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the weak points in the experimental teaching both of Design of Machinery and Theory of Machines and Mechanisms, a comprehensive experimental system for gear transmission based on digital speckle correlation method is developed. The system consists of two parts; an experiment table of gear transmission and data processing. It can complete the measure experiments of gear structure parameters such as the principle of gear meshing, basic parameters, contact ratio, and the mechanics experiments of gear such as bending strength, contact strength, load distribution between teeth. Through non-contact real-time detection and image analysis, the principle of gear meshing and the theory of gear strength can be revealed and verified, the blank of gear strength experiment is filled, and the coverage of the experimental course to the knowledge points is increased. The practice of teaching shows that the application of advanced measurement technology in practical teaching can improve students' understanding of basic theoretical knowledge, and teachers' teaching level of design of machinery and theory of machines and mechanisms. [ABSTRACT FROM AUTHOR]

An aerodynamic modeling method based on machine learning theory applying to large airspace and wide speed range is proposed. This method utilizes aerodynamic parameter identification results from flight trajectory simulation data and adopts neural network technology, so the aerodynamic model has a high precision fitting ability for the aerodynamic data with high nonlinear characteristics, regarding variable height, velocity, attitude angle and control rudder angle conditions. Firstly, the effects of the number of neural network and hidden neural unit number on model accuracy are discussed. The proper neural network layer numbers and hidden neural units are obtained through several neural network modeling calculations. Then we use the flight trajectory simulation data to get the whole aerodynamic parameters by identification method. By using BP neural networks, six aerodynamic models including three aerodynamic force coefficients and three aerodynamic moment coefficients are obtained. The models have high precision according to the comparison between model output results and origin data, as well as the aerodynamic prediction of four trajectories which are not applied to the modeling. The results show that the aerodynamic modeling method based on machine learning is feasible and effective. The aerodynamic models have a great fitting ability and some extrapolations in the ranges of data samples including height, Mach number, attack angle, sideslip angle, angular rate, and control surface angle. This study provides a new method on flight test experiment aerodynamic modeling and a good feasibility of the usage in the field of aerodynamic data mining, flight simulation, and aircraft flight evaluation. [ABSTRACT FROM AUTHOR]

With a three-arm inspection robot taken as an example， a hierarchical planning control strategy was analyzed and divided into a line information library layer， an action planning layer and an execution planning layer. The line information library layer is based on the known information of the high-voltage transmission line to be detected， including information on the type， location， and quantity of obstacles. The overall action planning layer and the execution planning layer are summarized according to the finite-state machine theory that when the input event is a (the second layer of the action planning layer)， under the action of f (the third layer of the execution layer)， the state q (the robot’s initial state) is mapped to the state p (the robot’s termination state). In the end， the trajectory planning of this robot was simulated by Matlab and the experiment of the prototype laboratory spanning the anti-vibration hammer and overhanging metal fittings， whose results verified the effectiveness and feasibility of the control strategy and the trajectory planning method. [ABSTRACT FROM AUTHOR]

Feature extraction is a key of mechanical fault diagnosis, which directly affects the accuracy of fault diagnosis and the reliability of early prediction. The vibration signal components of automata surface are complex, including rich information on the motion states of components and parts, and a lot of noise components. Interference information should be effectively removed in order to make a correct assessment and analysis of the signal. The vibration signal of automata surface has obvious short impact characteristics, and is a typical non-Gaussian, nonlinear signal. Bispectral analysis has certain advantages especially in dealing with non-Gaussian signal and identifying nonlinear system failures. Automata vibration signal is noise-reduced and analyzed by the local wave theory and the Bispectral analysis. [ABSTRACT FROM AUTHOR]

To overcome the shortcomings of long training time and relatively lower individual diagnose rate, principal component analysis (PCA) and extreme learning machine (ELM) was combined to detect liars. The method, called as PCA_ELM, used three-stimulus mode and recorded the EEG signals at Pz from 30 randomly divided guilty and innocent subjects. We averaged each five Probe responses within subject and then extracted wavelet features. PCA was employed to select feature subset with deduced dimensions, which was fed into ELM. The ELM classifier has fast training speed and good generalization performance. However, there is no perfect solution for the number of its hidden nodes (NHN). We used grid searching algorithm to select simultaneously the optimal values of the dimension of feature subset and NHN based on cross-validation method. The best classification mode was decided with the optimal searching values. Experimental results show that PCA_ELM has higher classification accuracy with faster training speed than other widely-used classification modes, which is especially suitable for online lie detection system. [ABSTRACT FROM AUTHOR]

Topic detection was raised in order to help people find an unknown news topic from vast amounts of news reports, and the research of clustering algorithm is the core content to realize topic detection technology based on Tibetan news text. This paper proposes a clustering algorithm is based on simple clustering algorithm. First of all, this algorithm improves the impact that the different text order causes the difference of the clustering results. Secondly, introducing the concept of seed topic, this algorithm determines the subject category through the number of seed topic. The new clustering algorithm of this study has a certain degree of increase, compared with the previous algorithm, in a smaller corpus. The research object of this paper is the text of Tibetan news website news. [ABSTRACT FROM AUTHOR]

In order to further study the conservation laws of a generalized Birkhoffian system, the method of integrating factors for Birkhoffian systems is extended to a generalized Birkhoffian system, which establishes a new method to find the conservation laws of the generalized Birkhoffian system. The generalized Killing equations which are used to determine the integrating factors are presented by finding the necessary conditions for the existence of the conservation laws of a generalized Birkhoffian system and establishing the relation between the conservation laws and the integrating factors. Then, the conservation laws of the generalized Birkhoffian system can be found. The results show that the method of integrating factors can be used to study the conservation laws of a generalized Birkhoffian system. [ABSTRACT FROM AUTHOR]

To solve the training of discrete process neural networks, two training algorithms based on numerical integration were proposed. The cubic spline integration and the parabolic interpolation integration were directly applied to dealing with the aggregation of discrete samples and weights in time-domain, and the gradient descent method was employed to adjusting the networks parameters. Taking the prediction of monthly discharge of the Manwan Reservoir for example, the experimental results show that the performance of two algorithms are relatively close, and superior to the orthogonal basis-based process neural networks. [ABSTRACT FROM AUTHOR]

This paper presented a hybrid evolutionary algorithm (HEA) for solving the single-machine scheduling problem with sequence-dependent setup times to minimize the total tardiness. By incorporating a local search procedure into the framework of evolutionary algorithms, the proposed approach exhibited several distinguishing features, including adopting a newly presented neighbourhood structure, called block move, and restricting the search space to traverse towards more promising search regions, and generating a new combination operator, called block order crossover, to generate new offspring solutions. Applying the proposed algorithm to solve the two sets of 64 public instances widely used in the literature, HEA outperforms the previous best known results for 9 instances, which demonstrate the superiority of the proposed HEA. The proposed HEA achieves highly competitive results over the 4 previous state-of-the-art metaheuristic algorithms in the literature. [ABSTRACT FROM AUTHOR]

Insertion-deletion systems are a class of computation models inspired by the biological process -- mismatched annealing of DNA sequences. In this work, we investigate the computation power of insertion-deletion systems having a context on one side of insertion or deletion rules. We prove that an insertion-deletion system which asymmetrically insert one symbol and delete two symbols is Turing universal; an insertion-deletion system which asymmetrically insert one symbol and delete one symbol is not Turing universal. Three Turing universal one-sided insertion-deletion P systems are presented, where the three corresponding one-sided insertion-deletion systems are not universal. The results partially answer open problems formulated in [Proceedings of 12th International Workshop on Descriptional Complexity of Formal Systems, 2010, 88-98]. [ABSTRACT FROM AUTHOR]

For the reentry terminal guidance problem of ballistic missile with constraint of impact angle, a nonlinear suboptimal guidance law that not only precisely attacks the ground target, but also satisfies the requirement of the terminal angle is designed based on the model predictive static programming technology proposed recently. The flight scenes that the ballistic missile attacks against stationary targets and maneuvering targets are simulated in this paper. The simulation results show that the designed guidance law spends less energy than the APN law. Compared with other guidance laws with impact angle constraint, the designed guidance handles the nonlinear problem as it is (without linearization), and the computational complexity is significantly lower than the guidance law with the angle constraint based on optimal control theory. [ABSTRACT FROM AUTHOR]

Abstract: To get a kind of constant-current source with high reliability and high accuracy during the process of all kinds of low-voltage equipments' adjusting and performance testing, a special high-reliable numerical control constant-current source based on 8-digit microprocessor is designed after analyzing the current main products' design. PID control algorithm is used in the total constant-current source system, and the analog voltage from D/A converter can be changed into constant-current power by applying the designed constant-current power circuit. After the practical application and test, the research results indicate that this kind instrument's output current value can be preset casually from the range 0 mA to 2 000 mA, the amplitude of ripple current is small, and its accuracy and reliability can both reach 0. 1% when changing the value of load. Two kinds of step-adjusting functions (±1 mA and ±10 mA) are also realized by presetting. [ABSTRACT FROM AUTHOR]

Semi-supervised multi-class classification problem opens research focuses in machine learning and pattern recognition, currently it is decomposed into a set of binary classification problems. Two kinds of class label presentation methods that one was class label presentation method of unit disc and the other was that of binary string were proposed for fear that multiple binary classification problems were solved. Besides, local learning has the good feature in semi-supervised binary classification problem. On the basis of it, local learning semi-supervised multi-class classifier was presented in this paper. The effectiveness of the algorithms was confirmed with experiments on benchmark datasets compared to other related algorithms. [ABSTRACT FROM AUTHOR]

The size of the MgO melt pool in the electric arc furnace is important to grow high-purity MgO single crystals. In order to control the size of the MgO melt pool precisely, a soft-sensor based on extreme learning machine (ELM) is proposed according to the analysis of the heat transfer theory of the electric arc furnace. The learning capability and generalization performance of the model are examined by comparison to the model based on the support vector machine (SVM). The comparative results show that ELM has similar control accuracy compared with SVM, but it has obvious advantages in learning speed for feedforward neural network. [ABSTRACT FROM AUTHOR]

The recognition power of three types of two-way two-dimensional finite automata were investigated, including deterministic, nondeterministic and Las Vegas finite automata. By inferences in theory, it was proved that there is a language that can be recognized by two-way two-dimensional Las Vegas finite automaton but can't be recognized by deterministic one, and that there is a language that can be recognized by two-way two-dimensional nondeterministic finite automaton but can't be recognized by Las Vegas one. The following two results are obtained: languages recognized by two-way two-dimensional Las Vegas finite automata strictly contain languages that recognized by deterministic ones; languages recognized by two-way two-dimensional nondeterministic finite automata strictly contain languages that recognized by Las Vegas ones. [ABSTRACT FROM AUTHOR]

This paper considers a problem of uniform-machine scheduling with machine release times to minimize makespan. Firstly, four properties of swapping jobs are proposed. Then, based on the properties, a heuristic algorithm is presented, which takes the LPT schedule as its initial solution and improves the solution by repeatedly swapping the jobs between two machines with the maximal and minimal makespan. Finally, computational results show that the presented heuristic is efficient and effective. [ABSTRACT FROM AUTHOR]

To improve the anti-interference performance of frequency hopping (FH) communications, Raptor code is applied in the FH communication as a forward error correction (FEC) code in this work. The proposed Raptor code is composed of 0.95 rate of regular LDPC pre-code and the cascading Luby transform (LT) code. By modeling and experiments on Matlab platform, the anti-interference performance of the FH communication system in different interference channels was analyzed. The results are as follows. In broadband interference channels, provided that the bit SNR is 2.5 dB, the BER is lower than 10-3 and the system performance would be improved by 17.6 dB. In partial-band interference channels, provided that the bit SNR is 1.0 dB, the BER is lower than 10-3, the system performance would be improved by 16.8 dB. It could be concluded that it is feasible to apply the proposed Raptor codes in FH as the FEC code. [ABSTRACT FROM AUTHOR]

Considering the features and operating characteristics of special robot, a development of high-power multi-axis control system based on TMSF320F2812 and high current half bridge driver BTS7960 is proposed in this paper. Moreover, the modular design was applied to the driver circuit, current sampling circuit, position detection and CAN bus circuit. The abundant peripherals of TMS320F2812 were fully utilized to improve the stability and reliability of the robot and reduce the volume and power consumption. In the software of robot control system, C language was used to realize the main program and the interrupt program. Through the motor control experiment, the performance of high-power multi-axis control system was tested. The results indicate that the high-power multi-axis control system is reliable and highly integrated, which meets the requirements of the special robot. [ABSTRACT FROM AUTHOR]

The feature templates of conditional random fields (CRF) are optimized employing incremental learning' s strategy to improve the performance of recognizing Chinese location names. Combining the linguistic knowledge, a rule base is constructed to avoid the low recall caused by the insufficient knowledge obtained from machine learning model. Finally,a system combining CRF with rules to identify location names in Chinese texts is achieved. Experimental results show that the proposed method is effective. In the MSRA corpus Bakeoff2007 NER task,the recall,precision and F value obtained by this system can reach 94.67%, 92. 35% and 93.50 % respectively in open tests. [ABSTRACT FROM AUTHOR]

A tracking algorithm based on adaptive multi-cue integration mechanism is proposed. The RGB color cue and local binary pattern (LBP) texture cue are utilized to represent the target, and then they are combined by linear weighting to the similarity function. By expanding the similarity function, a new expression consisting of the data items with local information is obtained, and mean shift algorithm is used to find out the optimal location by iterative computation. Sigmoid kernel are used to adjust the feature weight adaptively in the tracking procedure, Bhattacharyya coefficient and reliability index are used as criterions for selective sub model update. Experimental results show that the tracker based on multi-cue integration mean shift works even more robustly. With adaptive multi-cue integration mechanism and selective model update strategy, the problem of tracking failures caused by using single cue or model drift in complex scenes can be solved. [ABSTRACT FROM AUTHOR]

This paper presents a revised type of Asymmetric AdaBoost algorithm--M-Asy AdaBoost. It can ensure the success of training process by sample weight distribution. The weight of classifier is optimized by adopting error rates of positive sample. The capability of recognizing positive sample is enhanced. The detection probability is improved and increased monotonously by restricting the classifier adding in the ensemble. The proposed algorithm can attain high detection rate with low false alarm ratio. In the end, it is proved by computer simulation that the M-Asy AdaBoost is effective. [ABSTRACT FROM AUTHOR]

To deal with the issue of large computational complexity in SLM-OFDM system, a PAPR reduction method using multiple select mapping (MSLM) is present for OFDM system. This method divides the transmit data into multiple groups. Each group has the same data length at transmit end of OFDM system. Other performance of the method is similar to the SLM. Thus, PAPR is reduced by using MSLM method for OFDM signal, and the computational complexity is decreased as well. Simulation results demonstrate that MSLM method outperforms the conventional SLM(CSLM) algorithm with respect to PAPR by 1.3 dB when selection branch number is 16 and CCDF is 10-3. It also has better symbol error ratio performance. [ABSTRACT FROM AUTHOR]

In order to reduce the memory consumption of automata algorithms in the field of multi-pattern matching, this paper proposes an efficient space optimization algorithm based on bitmap. It divides all the states in the automata into two groups by their depth in the data structure "trie", and reduces the memory consumption of the deeper group that will be retrieved less. It also makes use of bitmap to improve the time efficiency of the deeper group. Our experiments show that this algorithm can sharply reduce the memory consumption, and when the number of patterns is more than the level of 10 thousand, the space consumption can be decreased by 25%-70%. [ABSTRACT FROM AUTHOR]

An improved fast algorithm based on wavelet transform is provided. The analysis on wavelet filter coefficients shows that the speed of Mallat algorithm can be improved. A low-frequency coefficient and a high-frequency coefficient can be calculated simultaneously in the decomposition and reconstruction of wavelets, and two adjacent recovered values can also be calculated simultaneously in reconstruction. During the calculation of a pair of values, the later value can be calculated based on the result of the former value. Thus the times of multiplication and addition are decreased and the speed is improved. The comparative data between Mallat algorithm and the improved fast algorithm are provided, which illustrate the advantages of the improved algorithm. [ABSTRACT FROM AUTHOR]

To solve the problem of identifying similar questions in examination database, an algorithm for question similarity identification is proposed in this paper. By introducing domain words to the improvement of the word similarity model in HowNet, a model for question similarity identification is proposed to make the same or similar questions be identified and cut off automatically. This method improves the accuracy of identification compared with other methods. By combining merits of the random selection with those of the backtracking method, a new algorithm of generating papers automatically based on question similarity identification is proposed. It can guarantee the quality of papers. Test results show that the accuracy of question similarity identification of this method is 96% , which approaches to that of manual identification. This method can cut off similar questions not only of the same type, but also of different types. Finally, this method has been applied to the on-line examination of C programming language. [ABSTRACT FROM AUTHOR]

Master production scheduling (MPS) is crucial to production planning and control system in ERP. Most existing MPS algorithms focus on optimizing objectives of time and cost under capacity restraints, however ignore the balanced using of capacities. It makes MPS plans not robust and they need to be replaned frequently, especially when available capacities and customer requirements have unbalanced distributions in the whole plan horizon. In face of such obstacles, an improved heuristic MPS algorithm is presented. It realizes the balanced utilization of bottleneck capacities between periods in the whole plan horizon, improves the robustness of MPS plans, and minimizes the inventory holding cost as well. The merits of the algorithm are proved by experimental results and analysis. [ABSTRACT FROM AUTHOR]

To investigate the stability concerning reorientation of flexible spacecraft with two panels, a one-axis attitude dynamical model with consideration of bending deformations of flexible appendages was established. Based on the states feedback method and the LQ optimal control theory, a control law with flexible parameters in the control gains is presented. Analysis with the sensibility method not only indicates that the control law is able to stabilize the attitude of the spacecraft, but also manifests that the control law has the capability of keeping the robust stability of the spacecraft, even under the parameter perturbed with a quite large scale. Furthermore, simulation results illustrate that the control law provides a satisfying robust stability for the spacecraft. [ABSTRACT FROM AUTHOR]

For reducing the computational complexity of multiple fault diagnosis in a complex system, a diagnosis model based on causal graph is researched in this paper. Firstly, a centralized model was founded using causal networks. Then, centralized model was conversed to several distributed models through directed tree decomposition technology, and the clan table was calculated offline. Finally, the global diagnosis was realized by using a synthesized diagnosis algorithm after the local diagnosis was finished. The application to a satellite power system proves that computational complexity of the centralized model is reduced through the distributed model, the efficiency is increased and coupling faults can be diagnosed by using the calculated clan table and the synthesized diagnosis algorithm, which are suitable for fault diagnosis in complex satellite systems. [ABSTRACT FROM AUTHOR]