Incorporating haptic feedback in simulation for learning physics

The purpose of this study was to investigate the effectiveness of a haptic augmented simulation in learning physics. The results indicate that haptic augmented simulations, both the force and kinesthetic and the purely kinesthetic simulations, were more effective than the equivalent non-haptic simulation in providing perceptual experiences and helping elementary students create multimodal representations of the movements of gears. However, in most cases, force feedback was needed to construct a fully loaded multimodal representation that helps students to comprehend later instruction with less sensory modalities. In addition, the force and kinesthetic simulation was effective in helping to transfer knowledge to new learning situations. These findings suggest that it is important to help elementary students make a solid cognitive grounding with the use of a perceptual anchor.     

Region-based parallelization of irregular reductions on explicitly managed memory hierarchies

Multicore architectures are evolving with the promise of extreme performance for the classes of applications that require high performance and large bandwidth of memory. Irregular reduction is one of important computation patterns for many complex scientific applications, and it typically requires high performance and large bandwidth of memory. In this article, we propose region-based parallelization techniques for irregular reductions on multicore architectures with explicitly managed memory hierarchies. Managing memory hierarchy in software requires a lot of programming efforts and tends to be error-prone. The difficulties are even worse for applications with irregular data access patterns. To relieve the burden of memory management from programmers, we develop abstractions, particularly targeted to irregular reduction, for structuring parallel tasks, mapping the parallel tasks to processing units and scheduling data transfers between the memory hierarchies. Our framework employs iteration reordering based on regions of data along with dynamic scheduling of parallel tasks. We experimentally evaluate the effectiveness of our techniques for irregular reduction kernels on the Cell processor embedded in a Sony PlayStation3. Experimental results show the speedups of 8 to 14 on the six available SPEs.     

Geolocation of Multiple Targets from Airborne Video Without Terrain Data

The task of geolocating targets from airborne video is required for many applications in surveillance, law enforcement, reconnaissance, etc. The usual approaches to target geolocation involve terrain data, single target tracking, gimbal control of camera heads, altimeters, etc. The main goal of this research is to eliminate those requirements and still develop an accurate, efficient, and robust vision-based method for geolocation that can be carried out for multiple targets simultaneously. In that sense, our main contributions to the state-of-the-art in geolocation are fourfold: 1) to eliminate the requirement for gimbal control of the cameras or any particular path planning control for the UAV; 2) to perform instaneous geolocation of multiple targets; 3) to eliminate the requirements for geo-referenced terrain database (elevation maps) or for an altimeter that provides the UAV’s and target’s altitudes; and 4) to use one single camera while still maintaining good overall accuracy. In order to achieve that, the only requirements for our proposed method are: that the intrinsic parameters of the camera be known; that the on board camera be equipped with global positioning system (GPS) and inertial measurement unit (IMU); and that the height of the vehicle can be calculated using feature points extracted from the ground surrounding the image of the targets. To satisfy the first two requirements, we developed and tested a robust calibration procedure that can estimate not only the intrinsic parameters of the camera, but also the IMU-camera parameters (also know in the robotic circles as the hand-eye calibration). The last requirement was addressed using a pseudo-stereo vision technique that maximizes the distance between stereo pairs (baseline) while keeping large the number of common feature points extracted by the algorithm. The result is a method that can reach approximately 25 m of accuracy for an UAV flying at 155 m away from the target. Such performance is demonstrated by computer simulation, in-scale data using a model city, and real airborne video with ground truth.     

Multiwalled carbon nanotubes grafted chitosan nanobiocomposite: A prosperous functional nanomaterials for glucose biosensor application

Multiwalled carbon nanotubes (MWNTs) grafted chitosan (CS) nanowire (NW) was prepared by phase separation method. Glucose oxidase (GOx) was sequentially immobilized into MWNT-CS-NW to obtain MWNT-CS-NW/GOx biosensor. Field emission scanning electron microscopy (FESEM) images of MWNT-CS-NW/GOx reveals the existence of MWNT and CS. Cyclic voltammetry and amperometry were used to evaluate the electrochemical determination of glucose. The MWNT-CS-NW/GOx biosensor shows an excellent performance for glucose at +0.34 V with a high sensitivity (5.03 μA/mM) and lower response time (3 s) in a wide concentration range of 1-10 mM (correlation coefficient of 0.9988). In addition, MWNT-CS-NW/GOx biosensor possesses better reproducibility, storage stability and there is negligible interference from other electroactive components.     

Nano-structured solid oxide fuel cell design with superior power output at high and intermediate operation temperatures

A solid oxide fuel cell (SOFC) with a thin-film yttria-stabilized zirconia (YSZ) electrolyte was developed and tested. This novel SOFC shows a similar multilayer set-up as other current anode-supported SOFCs and is composed of a Ni/8YSZ anode, a gas-tight 8YSZ electrolyte layer, a dense Sr-diffusion barrier layer and a LSCF cathode. To increase the power density and lower the SOFC operating temperature, the thickness of the electrolyte layer was reduced from around 10 μm in current cells to 1 μm, using a nanoparticle deposition method. By using the novel 1 μm electrolyte layer, the current density of our SOFC progressed to 2.7, 2.1 and 1.6 A/cm² at operation temperatures of 800, 700 and 650°C, respectively, and out-performs all similar cells reported to date in the literature. An important consideration is also that cost-effective dip-coating and spin-coating methods are applied for the fabrication of the thin-film electrolyte. Processing of 1 μm layers on the very porous anode substrate material was initially experienced as very difficult and therefore 8YSZ nanoparticle coatings were developed and optimized on porous 8YSZ model substrates and transferred afterwards to regular anode substrates. In this paper, the preparation of the novel SOFC is shown and its morphology is illustrated with high resolution SEM pictures. Further, the performance in a standard SOFC test is demonstrated.     

A spline wavelet finite element formulation of thin plate bending

The wavelet scaling functions of spline wavelets are used to construct the displacement interpolation functions of triangular and rectangular thin plate elements. The displacement shape functions are then expressed by spline wavelet functions. A spline wavelet finite element formulation of thin plate bending is developed by using the virtual work principle. Two numerical examples have shown that the bending deflections and moments of thin plates agree well with those obtained by the differential equations and conventional elements. It is demonstrated that the current spline wavelet finite element method (FEM) can achieve a high numerical accuracy and converges fast. The proposed spline wavelet finite element formulation has a wide range of applicability since it is developed in the same way like conventional displacement-based FEM.     

Graph OLAP: a multi-dimensional framework for graph data analysis

Databases and data warehouse systems have been evolving from handling normalized spreadsheets stored in relational databases, to managing and analyzing diverse application-oriented data with complex interconnecting structures. Responding to this emerging trend, graphs have been growing rapidly and showing their critical importance in many applications, such as the analysis of XML, social networks, Web, biological data, multimedia data and spatiotemporal data. Can we extend useful functions of databases and data warehouse systems to handle graph structured data? In particular, OLAP (On-Line Analytical Processing) has been a popular tool for fast and user-friendly multi-dimensional analysis of data warehouses. Can we OLAP graphs? Unfortunately, to our best knowledge, there are no OLAP tools available that can interactively view and analyze graph data from different perspectives and with multiple granularities. In this paper, we argue that it is critically important to OLAP graph structured data and propose a novel Graph OLAP framework. According to this framework, given a graph dataset with its nodes and edges associated with respective attributes, a multi-dimensional model can be built to enable efficient on-line analytical processing so that any portions of the graphs can be generalized/specialized dynamically, offering multiple, versatile views of the data. The contributions of this work are three-fold. First, starting from basic definitions, i.e., what are dimensions and measures in the Graph OLAP scenario, we develop a conceptual framework for data cubes on graphs. We also look into different semantics of OLAP operations, and classify the framework into two major subcases: informational OLAP and topological OLAP. Second, we show how a graph cube can be materialized by calculating a special kind of measure called aggregated graph and how to implement it efficiently. This includes both full materialization and partial materialization where constraints are enforced to obtain an iceberg cube. As we can see, due to the increased structural complexity of data, aggregated graphs that depend on the underlying “network” properties of the graph dataset are much harder to compute than their traditional OLAP counterparts. Third, to provide more flexible, interesting and informative OLAP of graphs, we further propose a discovery-driven multi-dimensional analysis model to ensure that OLAP is performed in an intelligent manner, guided by expert rules and knowledge discovery processes. We outline such a framework and discuss some challenging research issues for discovery-driven Graph OLAP.     

模糊相关机会规划的蚁群优化算法及收敛性分析

模糊相关机会规划(Fuzzy dependent-chance programming, FDCP)因其非线性、非凸性及模糊性,对经典的优化理论提出了极大的挑战. 本文为解决复杂的模糊相关机会规划问题设计了一种基于模糊模拟的蚁群优化算法, 证明了该算法的收敛性,并通过估算期望收敛时间以分析蚁群优化算法的收敛速度. 数值案例研究验证了该算法的有效性、稳定性及准确性.     

State complexity of basic operations on suffix-free regular languages

We investigate the state complexity of basic operations for suffix-free regular languages. The state complexity of an operation for regular languages is the number of states that are necessary and sufficient in the worst-case for the minimal deterministic finite-state automaton that accepts the language obtained from the operation. We establish the precise state complexity of catenation, Kleene star, reversal and the Boolean operations for suffix-free regular languages.