A DNA sequence alignment algorithm using quality information and a fuzzy inference method

DNA sequence alignment algorithms in computational molecular biology have been improved by diverse methods. In this paper, we propose a DNA sequence alignment that uses quality information and a fuzzy inference method developed based on the characteristics of DNA fragments and a fuzzy logic system in order to improve conventional DNA sequence alignment methods that uses DNA sequence quality information. In conventional algorithms, DNA sequence alignment scores are calculated by the global sequence alignment algo- rithm proposed by Needleman-Wunsch, which is established by using quality information of each DNA fragment. However, there may be errors in the process of calculating DNA sequence alignment scores when the quality of DNA fragment tips is low, because only the overall DNA sequence quality information are used. In our proposed method, an exact DNA sequence alignment can be achieved in spite of the low quality of DNA fragment tips by improvement of conventional algorithms using quality information. Mapping score param- eters used to calculate DNA sequence alignment scores are dynamically adjusted by the fuzzy logic system utilizing lengths of DNA fragments and frequencies of low quality DNA bases in the fragments. From the experiments by applying real genome data of National Center for Biotechnology Information, we could see that the proposed method is more efficient than conventional algorithms.     

Reliability Estimation of Aviation Pyrotechnics System Based on Mixed Beta Distribution

For evaluating reliability of an aviation pyrotechnics system,a Bayesian reliability estimation method utilizing reliability information of a system and its units was put forward. Firstly,an inheritance factor was determined by chi-square goodness of fit test.Then the mixed prior distribution was obtained based on the inheritance factor. Finally, the density function of posterior distribution was obtained and used to assess the reliability of system.According to the new method, the reliability of an aviation pyrotechnics system was evaluated to reach 0. 989 6 at the confidence level of 0. 90. To reach the reliability index,the required numbers of trials of system and its units were given. It is instructional to apply the new method on the reliability estimation of aviation pyrotechnics systems.     

Using Fuzzy Relations and GIS Method to Evaluate Debris Flow Hazard

The study area, located in the southeast of Tibet along the Sichuan-Tibet highway, is a part of Palongzangbu River basin where mountain hazards take place frequently. On the ground of field surveying, historical data and previous research, a total of 31 debris flow gullies are identified in the study area and 5 factors are chosen as main parameters for evaluating the hazard of debris flows in this study. Spatial analyst functions of geographic information system （GIS） are utilized to produce debris flow inventory and parameter maps. All data are built into a spatial database for evaluating debris flow hazard. Integrated with GIS techniques,the fuzzy relation method is used to calculate the strength of relationship between debris flow inventory and parameters of the database. With this methodology,a hazard map of debris flows is produced. According to this map,6.6% of the study area is classified as very high hazard, 7.3% as high hazard,8.4% as moderate hazard,32. 1% as low hazard and 45.6% as very low hazard or non-hazard areas. After validating the results, this methodology is ultimately confirmed to be available.     

Interoperability for Global Observation Data by Ontological Information

The Ontology registry system is developed to collect, manage, and compare ontological information for integrating global observation data. Data sharing and data service such as support of metadata deign, structuring of data contents, support of text mining are applied for better use of data as data interoperability. Semantic network dictionary and gazetteers are constructed as a trans-disciplinary dictionary. Ontological information is added to the system by digitalizing text based dictionaries, developing "knowledge writing tool" for experts, and extracting semantic relations from authoritative documents with natural language processing technique. The system is developed to collect lexicographic ontology and geographic ontology.     

Miniaturized volume holographic optical data storage and correlation system with a storage density of 10 Gb／cm^3

The general idea of holographic optical data storage (HODS) is briefly introduced. Based on the recent advances of HODS, the key techniques and the challenges of HODS are discussed. Some new techniques are proposed to improve the system. A miniaturized volume holographic data storage and correlation system is presented. It can achieve a density of 10 Gb/cm^3 and a fast correlation recognition rate of more than 2000 images per second. It shows the attracting potential advantages over other conventional storage methods in the information storage as well as information processing.     

Nonlinear fault diagnosis method based on kernel principal component analysis

To ensure the system run under working order, detection and diagnosis of faults play an important role in industrial process. This paper proposed a nonlinear fault diagnosis method based on kernel principal component analysis (KPCA). In proposed method, using essential information of nonlinear system extracted by KPCA, we constructed KPCA model of nonlinear system under normal working condition. Then new data were projected onto the KPCA model. When new data are incompatible with the KPCA model,it can be concluded that the nonlinear system is out of normal working condition. Proposed method was applied to fault diagnosis on rolling bearings. Simulation results show proposed method provides an effective method for fault detection and diagnosis of nonlinear system.     

A New Algorithm for the Establishing Data Association Between a Camera and a 2-D LIDAR

In this paper,we propose a new algorithm to establish the data association between a camera and a 2-D Light Detection And Ranging sensor （LIDAR）.In contrast to the previous works,where data association is established by calibrating the intrinsic parameters of the camera and the extrinsic parameters of the camera and the LIDAR,we formulate the map between laser points and pixels as a 2-D homography.The line-point correspondence is employed to construct geometric constraint on the homography matrix.This enables checkerboard to be not essential and any object with straight boundary can be an effective target.The calculation of the 2-D homography matrix consists of a linear least-squares solution of a homogeneous system followed by a nonlinear minimization of the geometric error in the image plane.Since the measurement quality impacts on the accuracy of the result,we investigate the equivalent constraint and show that placing the calibration target nearby the 2-D LIDAR will provide sufficient constraints to calculate the 2-D homography matrix.Simulation and experimental results validate that the proposed algorithm is robust and accurate.Compared with the previous works,which require two calibration processes and special calibration targets such as checkerboard,our method is more flexible and easier to perform.     

A BP neural network based information fusion method for urban traffic speed estimation

Obtaining comprehensive and accurate information is very important in intelligent traffic system (ITS). In ITS, the GPS floating car system is an very important approach for traffic data acquisition. However, in this system, the GPS blind areas caused by tall buildings and tunnels could affect the acquisition of traffic information and depress the system performance. Aiming at this problem, we developed a novel method employing a back propagation (BP) neural network to estimate the traffic speed in the GPS blind areas. When the speed of one road section is lost, we can use the speed of its related road sections to estimate its speed. The complete historical data of these road sections are used to train the neural network, using Levenberg-Marquardt learning algorithm. Then, the current speed of the related roads is used by the trained neural network to get the speed of the road section without GPS signal. We compare the speed of the road section estimated by our method with the real speed of this road section, and the experimental results show that the speed of this road section estimated by our method is better.     

Integration of naval distributed tactical training simulation system based on advanced message queuing protocol①

Aiming at the problems of unreliable data transmission , poor steadiness , nonsupport of complex data types , direct couple between data transmission and exchange , a high-level method based on ad-vanced message queuing protocol ( AMQP) is proposed to integrate naval distributed tactical training simulation system after serious consideration with current information exchange features of military combat system .Transferring layer in traditional user datagram protocol is implemented by publishing and subscribing scheme of message middleware .By creating message model to standardize message structure , integration architecture is formulated to resolve potential information security risks from in-consistent data type and express data transmission .Meanwhile , a communication model is put for-ward based on AMQP , which is in the center position of the whole transmission framework and re-sponsible for reliably transferring battlefield data among subsystems .Experiments show that the method can accurately post amounts of data to the subscriber without error and loss , and can get ex-cellent real-time performance of data exchange .     

Modeling Multisource-heterogeneous Information Based on Random Set and Fuzzy Set Theory

This paper presents a new idea, named as modeling multisensor-heterogeneous information, to incorporate the fuzzy logic methodologies with mulitsensor-multitarget system under the framework of random set theory. Firstly, based on strong random set and weak random set, the unified form to describe both data （unambiguous information） and fuzzy evidence （uncertain information） is introduced. Secondly, according to signatures of fuzzy evidence, two Bayesian-markov nonlinear measurement models are proposed to fuse effectively data and fuzzy evidence. Thirdly, by use of ＂the models-based signature-matching scheme＂, the operation of the statistics of fuzzy evidence defined as random set can be translated into that of the membership functions of relative point state variables. These works are the basis to construct qualitative measurement models and to fuse data and fuzzy evidence.     

Survey of nutrients and quality assessment of crab paste by 1H NMR spectroscopy and multivariate data analysis

Crab paste is a traditional and popular food for people in the coastal area of China.Visual inspection is currently the only method of quality assessment.We developed a new analytical method of a comprehensive survey of nutrients and quality assessment for crab paste based on a combination of 1 H NMR spectroscopy with multivariate data analysis.The aqueous extract of crab paste was dominated by amino acids,sugars,carboxylic acids,nucleotides and amines(including 19 first-time-reported compounds such as choline,uracil and guanosine).Two grades of crab paste had significant compositional differences in terms of amino acids,lactate,N-acetylglutamate,choline,dimethylamine,uridine,1-methylnicotinamide and 2-pyridienmethanol.These results provided important information on the grade-dependence of crab-paste composition,and demonstrated that NMR-MDA was effective not only for the comprehensive survey of nutrients,but also for quality assessment of crab paste.     

Resources Allocation Schemas for Web Information Monitoring

The web is an extremely dynamic world where information is updated even every second. A web information monitoring system fetches information from the web continuously and finds changes by comparing two versions of the same page. The updating of a specific web page is modeled as a Poisson process with parameter to indicate the change frequency. As the amount of computing resources is limited, it is necessary to find some policies for reducing the overall change-detection time. Different allocation schemas are evaluated experimentally to find out which one is the most suitable for the web information monitoring problem. The experimental data shows the runtime characteristics of the overall system performance and the relationship to the total amount of resources.     

Dynamic prediction of building subsidence deformation with data-based mechanistic self-memory model

This paper describes a building subsidence deformation prediction model with the self-memorization principle.According to the non-linear specificity and monotonic growth characteristics of the time series of building subsidence deformation,a data-based mechanistic self-memory model considering randomness and dynamic features of building subsidence deformation is established based on the dynamic data retrieved method and the self-memorization equation.This model first deduces the differential equation of the building subsidence deformation system using the dynamic retrieved method,which treats the monitored time series data as particular solutions of the nonlinear dynamic system.Then,the differential equation is evolved into a difference-integral equation by the self-memory function to establish the self-memory model of dynamic system for predicting nonlinear building subsidence deformation.As the memory coefficients of the proposed model are calculated with historical data,which contain useful information for the prediction and overcome the shortcomings of the average prediction,the model can predict extreme values of a system and provide higher fitting precision and prediction accuracy than deterministic or random statistical prediction methods.The model was applied to subsidence deformation prediction of a building in Xi’an.It was shown that the model is valid and feasible in predicting building subsidence deformation with good accuracy.     

Parallel bulk-loading of spatial data with MapReduce: An R-tree case

Current literature on parallel bulk-loading of R-tree index has the disadvantage that the quality of produced spatial index decrease considerably as the parallelism increases.To solve this problem,a novel method of bulk-loading spatial data using the popular MapReduce framework is proposed.MapReduce combines Hilbert curve and random sampling method to parallel partition and sort spatial data,thus it balances the number of spatial data in each partition.Then the bottom-up method is introduced to simplify and accelerate the sub-index construction in each partition.Three area metrics are used to test the quality of generated index under different partitions.The extensive experiments show that the generated R-trees have the similar quality with the generated R-tree using sequential bulk-loading method,while the execution time is reduced considerably by exploiting parallelism.     

System identification of channel roughness for Mid-Route Project of South-to-North Water Diversion

This paper presents a new method for the system identification of the channel roughness for the water di- version projects. According to the principle of hydraulics, the function relationship among channel roughness n, roughness height ks and hydraulic radius R is established, and then a linear model is deduced by means of the mathematical transformation to make use of the least square method for identification. Finally, based on the proto- type observation data from the South-to-North Water Diversion Project and considering the influence of channel lengths, cross-section shapes and bottom slopes, etc, a universal formula is obtained for calculation of channel roughness by the system identification.     

Research of EDM Spark Locations in Die-sinking

Detection of 2-dimention spark locations by electromagnetic detection method in electrical discharge machining (EDM) is studied. The method, which is applied and investigated, is based on the fact that the release of energy from a spark is transformed into electromagnetic wave around the workpiece. A new sensor system composed of high precision linear Hall components and cubic ferrite is used to detect the intensity of magnetic field. Relation equation between the output of the sensor system and 2-dimention spark locations experiment under a spiculate electrode is introduced, and its diagram of curve is drawn. As a result, the information that can be achieved by detecting spark‘s location gives new possibilities for an extended analysis of the EDM-process.     

Modeling and simulation of heat transfer for glass bulb mold

Cooling system design in glass bulb pressing operation can greatly affect the productivity and the quality of the final product. The concept of cyclic-averaged steady temperature field is proposed in modeling. Heat transfer in the mold region is considered to be a cyclic-steady, three-dimensional conduction; heat transfer within the glass melt region is treated as a transient, one-dimensional conduction; heat exchange between the cooling system surface and coolant is treated as a steady heat convection. A hybrid model consisting of a three-dimensional boundary element method for the mold region and a finite-difference method with a variable mesh for the melt region is used for numerical simulation. Compared with the experimental data, the numerical model developed here is computationally efficient and sufficiently accurate.     

A Low-Cost Dual Energy CT System with Sparse Data

Dual Energy CT （DECT） has recently gained significant research interest owing to its ability to discriminate materials, and hence is widely applied in the field of nuclear safety and security inspection. With the current technological developments, DECT can be typically realized by using two sets of detectors, one for detecting lower energy X-rays and another for detecting higher energy X-rays. This makes the imaging system expensive, limiting its practical implementation. In 2009, our group performed a preliminary study on a new low-cost system design, using only a complete data set for lower energy level and a sparse data set for the higher energy level. This could significantly reduce the cost of the system, as it contained much smaller number of detector elements. Reconstruction method is the key point of this system. In the present study, we further validated this system and proposed a robust method, involving three main steps： （1） estimation of the missing data iteratively with TV constraints; （2） use the reconstruction from the complete lower energy CT data set to form an initial estimation of the projection data for higher energy level; （3） use ordered views to accelerate the computation. Numerical simulations with different number of detector elements have also been examined. The results obtained in this study demonstrate that 1 ＋ 14% CT data is sufficient enough to provide a rather good reconstruction of both the effective atomic number and electron density distributions of the scanned object, instead of 2 sets CT data.     

The New Time-Spatial Information System

In this paper,the author puts torward a new concept Time-Spatial information system, which is based on the old Geo-information system during such a present era. The new concept is just very right whichever you comprehend in breadth or depth and give you more valuable information to research time-space information svstem as welh     

多少学生准备好书写符合编码标准的高质量程序:一个案例分析

The compliance with coding standards is becoming an evaluating index for a software engineer's teamwork capability or international cooperation capability.The best place to solve this problem should be in an educational environment such as college where students begin to write their introductory programs.After constructing a web-based evaluating system,a case was studied in our school of software and some important conclusions were made such as(1)the evaluating results were not so satisfactory because of the absence of necessary training and(2)students' ability to comply with coding standards did not improve automatically with the assignments one by one without timely feedback.In short,there is a long way to run before the students can write quality code meeting the requirement of software industry.