Multi-sector multi-range control for self-organizing wireless networks

In this paper, we propose a distributed multi-sector multi-range (MSMR) control algorithm for supporting self-organizing wireless networks. The algorithm enables us to reduce the unnecessary coverage with fine-tuned range control and also to increase the network-wide capacity with enhanced spatial reusability. The proposed algorithm discovers neighboring nodes within the maximum transmission range at every node, divides its transmission area into multiple non-overlapping angular sectors of a given degree, chooses the home sector for each neighboring node according to its relative position, and constructs a spanning subgraph per sector by determining appropriate transmission range to maintain connectivity. Since the range control influences on network connectivity directly, we prove in the first place that the proposed algorithm preserves both network-wide and local connectivity as far as both connectivity exist in the network that uses the maximum transmission range. In order to investigate the performance of the proposed algorithm, we implemented it in the ns-2 simulator, and performed an extensive set of simulation study in comparison with other transmission range control schemes. The simulation results indicate that the proposed scheme is superior to other schemes with respect to the network-wide throughput and its normalized value per energy in various simulation configurations. In specific, the algorithm achieves minimally one order and maximally two orders of magnitude improvement in those performance evaluations. The improvement becomes more salient as the number of nodes increases and is immune to traffic type, network size, node distribution, or node density.     

基于SDSS的渔业资源预测决策系统

针对经济渔业资源特点,实现渔业资源及决策信息的图形化展示,提出用本体库取代知识库构建空间决策支持系统,优化知识组织方式,提高查询效率。将数据库、模型库、本体库与GIS有机集成,为决策者提供资源发展事态信息。融合灰色预测模型和BP神经网络的优点构建灰色神经网络预测预警模型,通过东海经济渔业资源数据进行实证分析,实验结果表明,该预测预警模型具有较高的精确度及较好的效果。     

Effect of axial and radial velocities on solids mass flow rate measurement

In coal powder flow transportation and combustion, powder mass flow rate is a key parameter to be monitored and controlled. Electrostatics is one of the techniques used for such task with its non-intrusive, robust, and low cost natures. The passive electrostatic meters measure charge induced on the detecting electrodes. As it is known that the induced signal is not only dependent on the solids mass flow rate, but also affected by solids velocity. However, the velocity of particles usually referred to is the axial velocity. In reality, the solids velocity is a vector, its projections in both the radial and tangential directions also need to be investigated. This paper analyses the dynamic sensitivity of ring-shaped electrostatic sensors using the finite element method (FEM), and investigates the influence of the axial and radial velocities on the induced signal on the electrodes.     

Structure and BIBO stability of a three-dimensional fuzzy two-term control system

A novel three-dimensional fuzzy logic controller (3D FLC) was developed recently for spatially distributed systems. In this study, the inherent spatial structure feature of a 3D FLC with two spatial inputs (also called as 3D two-term FLC) is first exposed via an analytical model. Then, the global bounded-input/bounded-output (BIBO) stability of the 3D fuzzy two-term control system is discussed. A sufficient condition is derived and provided as a useful criterion for the controller design of the 3D two-term FLC. Finally, a catalytic packed-bed reactor is presented as an example of spatially distributed process to demonstrate the effectiveness of the controller.     

Change detection in desktop virtual environments: An eye-tracking study

It is common knowledge that attention is important for learning. We need to utilize attention in order to learn something efficiently and effectively. Similarly, we may also need to acquire familiarity with (i.e., learn) our surroundings in order to utilize our attention. In this study, learning is defined as a product of one’s exposure to natural visual stimuli. Using a virtual model of a natural scene, we investigate both attention and its relationship to learning, according to this definition. Specifically, our focus is the effect of environment familiarity on gaze direction. Our findings reveal that the factor of familiarity with one’s surroundings in virtual reality environments exerts a significant influence on peoples’ ability to detect a variety of specific changes that occur within scenes under their observation.     

基于UCON的分布式数据库安全模型

针对分布式数据库系统中已发布数据难以控制的问题,结合基于角色访问控制模型(RBAC)和使用控制模型(UCON)的特点,提出一种基于UCON的分布式数据库安全模型。将分布式数据库分为服务器端和客户端,服务器端采用UCON策略,客户端采用RBAC策略。分析结果表明,该模型能有效控制分布式数据库系统中的数据。     

Video game experience predicts virtual, but not real navigation performance

In recent years, studies have shown that video game experience is related to improvements across a variety of cognitive and visuospatial tasks. This study investigated the relationship between prior video game experience and spatial performance in virtual and real environments. Across two experiments, gaming experience was related to performance in desktop virtual environments; those with more video game experience were more accurate in pointing to nonvisible targets. In contrast, gaming experience was unrelated to three different real environment tasks, suggesting that video games may primarily influence perceptual and cognitive abilities in the visual domain over abilities that also involve kinesthetic or vestibular input. Contrary to expectations, gaming experience was also related to performance in immersive virtual environments, which may be related to the use of a joystick interface during immersive travel. Video game experience was also positively related to performance in a dynamic spatial task and to verbal SAT and math SAT scores. Sex differences in desktop virtual navigation and dynamic spatial ability were eliminated when game experience was included as a covariate.     

The kinematic design of spatial,hybrid closed chains including planar parallelograms

It is presented an integral approach for the kinematic design of spatial, hybrid closed chains which include planar parallelograms into their kinematic structure. It is based on a systematic application of recursive formulae intended for describing the evolution of screws through time. Due to the particular nature of the proposed approach, it can be closely related with Lie algebras and allows to overcome the lacking of group structure offered by a parallelogram when it is going to be considered as a component of a hybrid closed chain. Several application examples are presented in order to show the potential of the proposed approach.     

A spatial warping method for freeform modeling based on a level-set method

Providing an intuitive and effective tool for freeform geometric modeling is important for product design. We introduce in this paper a level-set based spatial warping method for freeform modeling, allowing shape deformation to be initialed by rigid body transformations of volumetric tools. Intuitive user operations including imprinting, deformation and smoothing are developed to shield the user from the underlying geometric complexity. Unlike mesh-based spatial warping methods, the developed method represents a digital model by implicit distance field data and describes its change of geometry by the level-set method. This guarantees the generation of topologically correct triangular mesh models and circumvents the error-prone remeshing and mesh-repairing processes, thus preventing topological errors such as self-intersections. We present this method with algorithm details, numerical experiments and modeling examples.     

Discrete data clustering using finite mixture models

Finite mixture models have been applied for different computer vision, image processing and pattern recognition tasks. The majority of the work done concerning finite mixture models has focused on mixtures for continuous data. However, many applications involve and generate discrete data for which discrete mixtures are better suited. In this paper, we investigate the problem of discrete data modeling using finite mixture models. We propose a novel, well motivated mixture that we call the multinomial generalized Dirichlet mixture. The novel model is compared with other discrete mixtures. We designed experiments involving spatial color image databases modeling and summarization, and text classification to show the robustness, flexibility and merits of our approach.