Use of GIS Based Maps for Preliminary Assessment of Subsoil of Guwahati City

Guwahati, the major city in the North Eastern region of India is growing rapidly in every aspect with major infrastructures like sports complex, educational institutions, hospitals, flyovers, multiplex halls, etc. Knowledge of the subsurface soil condition is necessary to ensure the structural safety and serviceability of the above mentioned structures before any construction. Therefore, contour maps of Standard penetration test N value, ground water table and shear wave velocity map using Geographical Information System (GIS) platform will be of great help to the foundation designers at the initial stage for site selection and preliminary foundation design under static and seismic condition. Contour maps of Standard penetration test N value at different depth and average contour map of N value of Guwahati city have been prepared. Standard penetration Test N values and depth of water table were taken from a data base of 200 boreholes up to 30 meter depth to prepare N value contour map of Guwahati city. A regression equation between shear wave velocity Vs and Standard penetration test N value based on twenty seven previous similar correlations was also developed. This regression equation was used to determine shear wave velocity of Guwahati city. The average shear wave velocities for 30 m depth for all locations had been determined and used to generate map on (GIS) platform. Other subsurface geotechnical information of Guwahati city like soil classification and depth to water level from ground surface is also presented in the form of GIS based maps in order to form a data base.

Map-based control method for vehicle stability enhancement

This work proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. A 2-DOF vehicle model and Pacejka's tire model are used to evaluate the proposed map-based control method. The properties of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with a low friction coefficient. However, map-based control determines a compensated yaw moment to maintain the vehicle within the stability region,so the typical responses of vehicle enable to converge rapidly. The simulation results with sine and step steering show that map-based control provides better the tracking responsibility and control performance than model-referenced control.

A MAP Approach for Vision-based Self-localization of Mobile Robot

一当场，自我本地化系统为在有深入的 3D 里程碑的 3D 环境起作用的活动机器人被开发。机器人通过合并从 odometry 和单向性的照相机收集的信息的一个地图评估者递归地估计它的姿势。我们为这二个传感器造非线性的模型并且坚持说机器人运动和不精密的传感器大小的无常操作应该全部被嵌入并且追踪我们的系统。我们在一个概率的几何学观点和使用 unscented 变换描述无常框架宣传无常，它经历给定的非线性的功能。就我们的机器人的处理力量而言，图象特征在相应投射特征的附近被提取。另外，数据协会被统计距离评估。最后，一系列系统的实验被进行证明我们的系统的可靠、精确的性能。

QTL Mapping for Fiber Quality Traits Based on a Dense Genetic Linkage Map with SSR,TRAP,SRAP and AFLP Markers in Cultivated Tetraploid Cotton

Cotton is one of the most important economic crops in the world,and it provides natural fiber for the textile industry.With the advancement of the textile technology and increased consumption demands on cotton fiber,both cotton yield and quality should be enhanced.However,cotton yield

Hot deformation of spray formed nickel-base superalloy using processing maps

The hot compression testing of hot isostatically pressed(HIPed) spray formed(SF) nickel-base superalloy was carried out by thermal mechanical simulator in the temperature range of 1 050-1 140 ℃ at strain rates of 0.01-10 s-1 and engineering strain of 50%. A processing map was developed on the basis of these data by using the principles of dynamic materials modeling. The microstructural evolution of deformed samples was also examined on the basis of optical and electron microscopic observations. The map exhibits two domains: the instability domain at the temperatures of 1 050 ℃ -1 110 ℃ and strain rate of 0.01 s-1, the stability domain at the temperatures of 1 110 ℃- 1 140 ℃ and strain rates of 1 s-1-10 s-1, with a peak efficiency of about 40%. The dynamic recrystallization(DRX) is observed in the stability domain and the deformed specimens are no cracking or instabilities. However, there is no DRX in the instability domain and the alloy exhibits flow instability with cracks due to poor workability. The optimum hot working condition was determined in the stability domain.

Scan matching using line segment relationships for map-based localization of mobile robot

A new scan matching method for mobile robot localization is presented, which takes line segment as the feature and matches the real scans in the given reference map by relationships of the directional-defined line segments. The alignment was done by hierarchically identifying the multiple relationships and the result was recorded in a correspondence matrix, where the best match is defined and selected for localization. It is indicated that the searching algorithm of the best match can find the ambiguities and get rid of them. This method with less computational cost works well in occluded environment, and can correct the error in pose estimation without the need for the estimation itself. The efficiency, accuracy and robustness of this method were verified by experiments of localization in an occluded environment and a long-distance indoor navigation.

3DV quality model based depth maps for view synthesis in FTV system

Depth maps are used for synthesis virtual view in free-viewpoint television （FTV） systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts in the synthesized views. To solve this problem, a 3D video quality model base depth maps （D-3DV） for virtual view synthesis and depth map coding in the FTV applications is proposed. First, the relationships between distortions in coded depth map and rendered view are derived. Then, a precisely 3DV quality model based depth characteristics is develop for the synthesized virtual views. Finally, based on D-3DV model, a multilateral filtering is applied as a pre-processed filter to reduce rendering artifacts. The experimental results evaluated by objective and subjective methods indicate that the proposed D-3DV model can reduce bit-rate of depth coding and achieve better rendering quality.

Mapping Soil Salinity Using a Similarity-based Prediction Approach:A Case Study in Huanghe River Delta,China

Spatial distribution of soil salinity can be estimated based on its environmental factors because soil salinity is strongly affected and indicated by environmental factors. Different with other properties such as soil texture, soil salinity varies with short-term time. Thus, how to choose powerful environmental predictors is especially important for soil salinity. This paper presents a similarity-based prediction approach to map soil salinity and detects powerful environmental predictors for the Huanghe(Yellow) River Delta area in China. The similarity-based approach predicts the soil salinities of unsampled locations based on the environmental similarity between unsampled and sampled locations. A dataset of 92 points with salt data at depth of 30–40 cm was divided into two subsets for prediction and validation. Topographical parameters, soil textures, distances to irrigation channels and to the coastline, land surface temperature from Moderate Resolution Imaging Spectroradiometer(MODIS), Normalized Difference Vegetation Indices(NDVIs) and land surface reflectance data from Landsat Thematic Mapper(TM) imagery were generated. The similarity-based prediction approach was applied on several combinations of different environmental factors. Based on three evaluation indices including the correlation coefficient(CC) between observed and predicted values, the mean absolute error and the root mean squared error we found that elevation, distance to irrigation channels, soil texture, night land surface temperature, NDVI, and land surface reflectance Band 5 are the optimal combination for mapping soil salinity at the 30–40 cm depth in the study area(with a CC value of 0.69 and a root mean squared error value of 0.38). Our results indicated that the similarity-based prediction approach could be a vital alternative to other methods for mapping soil salinity, especially for area with limited observation data and could be used to monitor soil salinity distributions in the future.

An Object-based Approach for Two-level Gully Feature Mapping Using High-resolution DEM and Imagery： A Case Study on Hilly Loess Plateau Region, China

Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.

Neural Network Nonlinear Predictive Control Based on Tent-map Chaos Optimization

With the unique ergodicity,irregularity,and special ability to avoid being trapped in local optima,chaos optimization has been a novel global optimization technique and has attracted considerable attention for application in various fields,such as nonlinear programming problems.In this article,a novel neural network nonlinear predic- tive control(NNPC)strategy based on the new Tent-map chaos optimization algorithm(TCOA)is presented.The feedforward neural network is used as the multi-step predictive model.In addition,the TCOA is applied to perform the nonlinear rolling optimization to enhance the convergence and accuracy in the NNPC.Simulation on a labora- tory-scale liquid-level system is given to illustrate the effectiveness of the proposed method.

Mineral Prospectivity Mapping Method Integrating Multi-Sources Geology Spatial Data Sets and Case-Based Reasoning

Extracting and synthesizing information from existing and massive amounts of geology spatial data sets is of great scientific significance and has considerable value in its applications. To make mineral exploration less expensive, more efficient, and more accurate, it is important to move beyond traditional concepts and establish a rapid, efficient, and intelligent method of predicting the existence and location of minerals. This paper describes a case-based reasoning (CBR) method for mineral prospectivity mapping that takes spatial features of geology data into account and offers an intelligent approach. This method include a metallogenic case representation that combines spatial and attribute features, metallogenic case-based storage organization, and a metallogenic case similarity retrieval model. The experiments were performed in the eastern Kunlun Mountains, China using CBR and weights-of-evidence (WOE), respectively. The results show that the prediction accuracy of the CBR is higher than that of the WOE.

Research on Ubiquitous Map Information Organization Oriented to Location-Based Aggregation

In the era of information and communication technology (ICT) and big data, the map gradually shows a new qualitative feature of “spatiotemporal ubiquitous” due to the extension of its object space and the geographic information it contains, which brings new challenges to map information organization. This paper analyzes the concept and information characteristics of the ubiquitous map. Based on that, it proposes a ubiquitous map information organization model oriented to location-based aggregation. This new model includes three parts as “ubiquitous map instance”, “location-based aggregation mode” and “map scene”. This paper focuses on the “map scene” part which is the core of the model and contains two mutually mapped aspects as “content scene” and “representation scene”. And both aspects are divided into three levels as “features” ←→ “elements” ←→ “scenes” according to ubiquitous map information characteristics and location-based aggregation mode. With cases of map decomposition, the application of the model is explained to illustrate its effectiveness. The model is expected to provide powerful data organization and management capabilities for ubiquitous map production and use.

MAP-based Audio Coding Compensation for Speaker Recognition

The performance of the speaker recognition system declines when training and testing audio codecs are mismatched. In this paper, based on analyzing the effect of mismatched audio codecs in the linear prediction cepstrum coefficients, a method of MAP-based audio coding compensation for speaker recognition is proposed. The proposed method firstly sets a standard codec as a reference and trains the speaker models in this codec format, then learns the deviation distributions between the standard codec format and the other ones, next gets the current bias via using a small number adaptive data and the MAP-based adaptive technique, and then adjusts the model parameters by the type of coming audio codec format and its related bias. During the test, the features of the coming speaker are used to match with the adjusted model. The experimental result shows that the accuracy reached 82.4% with just one second adaptive data, which is higher 5.5% than that in the baseline system.

Object-based image analysis for mapping geomorphic zones of coral reefs in the Xisha Islands, China

Mapping regional spatial patterns of coral reef geomorphology provides the primary information to understand the constructive processes in the reef ecosystem. However, this work is challenged by the pixel-based image classification method for its comparatively low accuracy. In this paper, an object-based image analysis(OBIA)method was presented to map intra-reef geomorphology of coral reefs in the Xisha Islands, China using Landsat 8satellite imagery. Following the work of the Millennium Coral Reef Mapping Project, a regional reef class hierarchy with ten geomorphic classes was first defined. Then, incorporating the hierarchical concept and integrating the spectral and additional spatial information such as context, shape and contextual relationships, a large-scale geomorphic map was produced by OBIA with accuracies generally more than 80%. Although the robustness of OBIA has been validated in the applications of coral reef mapping from individual reefs to reef system in this paper, further work is still required to improve its transferability.

Neuronal injury in the motor cortex after chronic stroke and lower limb motor impairment: a voxelbased lesion symptom mapping study

Many studies have examined motor impairments using voxel-based lesion symptom mapping, but few are reported regarding the corresponding relationship between cerebral cortex injury and lower limb motor impairment analyzed using this technique. This study correlated neuro- nal injury in the cerebral cortex of 16 patients with chronic stroke based on a voxel-based lesion symptom mapping analysis. Neuronal injury in the corona radiata, caudate nucleus and putamen of patients with chronic stroke could predict walking speed. The behavioral measure scores were consistent with motor deficits expected after damage to the cortical motor system due to stroke. These findings suggest that voxel-based lesion symptom mapping may provide a more accurate prognosis of motor recovery from chronic stroke according to neuronal injury in cerebral motor cortex.

METHOD OF HIGH-LEVEL TECHNOLOGY MAPPING BASED ON KNOWLEDGE(RULE)

This paper studies the linkage problem between the result of high-level synthesis and back-end technology, presents a method of high-level technology mapping based on knowl edge, and studies deeply all of its important links such as knowledge representation, knowledge utility and knowledge acquisition. It includes: (1) present a kind of expanded production about knowledge of circuit structure; (2) present a VHDL-based method to acquire knowledge of tech nology mapping; (3) provide solution control strategy and algorithm of knowledge utility; (4)present a half-automatic maintenance method, which can find redundance and contradiction of knowledge base; (5) present a practical method to embed the algorithm into knowledge system to decrease complexity of knowledge base. A system has been developed and linked with three kinds of technologies, so verified the work of this paper.

Correction of Inertial Navigation System’s Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.

Automated soil resources mapping based on decision tree and Bayesian predictive modeling

This article presents two approaches for automated building of knowledge bases of soil resources mapping.These methods used decision tree and Bayesian predictive modeling, respectively to generate knowledge from training data.With these methods, building a knowledge base for automated soil mapping is easier than using the conventional knowledge acquisition approach. The knowledge bases built by these two methods were used by the knowledge classifier for soil type classification of the Longyou area, Zhejiang Province, China using TM hi-temporal imageries and GIS data. To evaluate the performance of the resultant knowledge bases, the classification results were compared to existing soil map based on field survey. The accuracy assessment and analysis of the resultant soil maps suggested that the knowledge bases built by these two methods were of good quality for mapping distribution model of soil classes over the study area.