Brain-like Computing Based on Distributed Representations and Neurodynamics

A key to overcoming the limitations of classical artificial intelligence and to deal well with enormous amounts of information might be brain-like computing in which distributed representations of information are processed by dynamical systems without using symbols. We present a method for such computing. We constructed an inference system using a nonmonotone neural network, which is a kind of recurrent neural network with continuous-time dynamics. This system deduces a conclusion according to state transitions of the network in which knowledge is embedded as trajectory attractors. It has the powerful ability of analogical reasoning without special treatment for exceptional knowledge. We also propose a method of linking different neurodynamical systems and show that two mutually interacting systems can process complex spatiotemporal patterns.     

Learning science in a virtual reality application: The impacts of animated-virtual actors’ visual complexity

As the technology in computer graphics advances, Animated-Virtual Actors (AVAs) in Virtual Reality (VR) applications become increasingly rich and complex. Cognitive Theory of Multimedia Learning (CTML) suggests that complex visual materials could hinder novice learners from attending to the lesson properly. On the other hand, previous studies have shown that visual complexity correlates with presence and may increase the perceived affective quality of the virtual world, towards an optimal experience or flow. Increasing these in VR applications may promote enjoyment and higher cognitive engagement for better learning outcomes. While visually complex materials could be motivating and pleasing to attend to, would they affect learning adversely? We developed a series of VR presentations to teach second-year psychology students about the navigational behaviour of Cataglyphis ants with flat, cartoon, or lifelike AVAs. To assess learning outcomes, we used Program Ratings, which measured perception of learning and perceived difficulty, and retention and transfer tests. The results from 200 students did not reveal any significant differences in presence, perceived affective quality, or learning outcomes as a function of the AVA’s visual complexity. While the results showed positive correlations between presence, perceived affective quality and perception of learning, none of these correlates with perceived difficulty, retention, or transfer scores. Nevertheless, our simulation produced significant improvements on retention and transfer scores in all conditions. We discuss possible explanations and future research directions.     

Z-SKY: an efficient skyline query processing framework based on Z-order

Given a set of data points in a multidimensional space, a skyline query retrieves those data points that are not dominated by any other point in the same dataset. Observing that the properties of Z-order space filling curves (or Z-order curves) perfectly match with the dominance relationships among data points in a geometrical data space, we, in this paper, develop and present a novel and efficient processing framework to evaluate skyline queries and their variants, and to support skyline result updates based on Z-order curves. This framework consists of ZBtree, i.e., an index structure to organize a source dataset and skyline candidates, and a suite of algorithms, namely, (1) ZSearch, which processes skyline queries, (2) ZInsert, ZDelete and ZUpdate, which incrementally maintain skyline results in presence of source dataset updates, (3) ZBand, which answers skyband queries, (4) ZRank, which returns top-ranked skyline points, (5) k-ZSearch, which evaluates k-dominant skyline queries, and (6) ZSubspace, which supports skyline queries on a subset of dimensions. While derived upon coherent ideas and concepts, our approaches are shown to outperform the state-of-the-art algorithms that are specialized to address particular skyline problems, especially when a large number of skyline points are resulted, via comprehensive experiments.     

Existential rigidity and many modalities in order-sorted logic

Order-sorted logic is a useful tool for knowledge representation and reasoning because it enables representation of sorted terms and formulas along with partially ordered sorts (called sort-hierarchy). However, this logic cannot represent more complex sorted expressions when they are true in any possible world (as rigid) or some possible worlds (as modality) such as time, space, belief, or situation. In this study, we extend order-sorted logic by introducing existential rigidity and many modalities. In the extended logic, sorted modal formulas are interpreted over the Cartesian product of sets of possible worlds. We present a new labeled tableau calculus to check the (un)satisfiability and validity of sorted modal formulas.     

Animating Pictures of Fluid using Video Examples

We propose a system that allows the user to design a continuous flow animation starting from a still fluid image. The basic idea is to apply the fluid motion extracted from a video example to the target image. The system first decomposes the video example into three components, an average image, a flow field and residuals. The user then specifies equivalent information over the target image. The user manually paints the rough flow field, and the system automatically refines it using the estimated gradients of the target image. The user semi-automatically transfers the residuals onto the target image. The system then approximates the average image and synthesizes an animation on the target image by adding the transferred residuals and warping them according to the user-specified flow field. Finally, the system adjusts the appearance of the resulting animation by applying histogram matching. We designed animations of various pictures, such as rivers, waterfalls, fires, and smoke.     

Non-photorealistic, depth-based image editing

Recent works in image editing are opening up new possibilities to manipulate and enhance input images. Within this context, we leverage well-known characteristics of human perception along with a simple depth approximation algorithm to generate non-photorealistic renditions that would be difficult to achieve with existing methods. Once a perceptually plausible depth map is obtained from the input image, we show how simple algorithms yield powerful new depictions of such an image. Additionally, we show how artistic manipulation of depth maps can be used to create novel non-photorealistic versions, for which we provide the user with an intuitive interface. Our real-time implementation on graphics hardware allows the user to efficiently explore artistic possibilities for each image. We show results produced with six different styles proving the versatility of our approach, and validate our assumptions and simplifications by means of a user study.     

Decision-Centric Information Monitoring

We are interested in information management for decision support applications, especially those that monitor distributed, heterogeneous databases to assess time-critical decisions. Users of such applications can easily be overwhelmed with data that may change rapidly, may conflict, and may be redundant. Developers are faced with a dilemma: either filter out most information and risk excluding critical items, or gather possibly irrelevant or redundant information, and overwhelm the decision maker. This paper describes a solution to this dilemma called decision-centric information monitoring (DCIM). First, we observe that decision support systems should monitor only information that can potentially change some decision. We present an architecture for DCIM that meets the requirements implied by this observation. We describe techniques for identifying the highest value information to monitor and techniques for monitoring that information despite autonomy, distribution, and heterogeneity of data sources. Finally, we present lessons learned from building LOOKOUT, which is to our knowledge the first implementation of a top-to-bottom system performing decision-centric information monitoring.     

Replica Placement Strategies in Data Grid

Replication is a technique used in Data Grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereby enhancing system reliability. The research addresses the problem of replication in Data Grid environment by investigating a set of highly decentralized dynamic replica placement algorithms. Replica placement algorithms are based on heuristics that consider both network latency and user requests to select the best candidate sites to place replicas. Due to dynamic nature of Grid, the candidate site holds replicas currently may not be the best sites to fetch replicas in subsequent periods. Therefore, a replica maintenance algorithm is proposed to relocate replicas to different sites if the performance metric degrades significantly. The study of our replica placement algorithms is carried out using a model of the EU Data Grid Testbed 1 [Bell et al. Comput. Appl., 17(4), 2003] sites and their associated network geometry. We validate our replica placement algorithms with total file transfer times, the number of local file accesses, and the number of remote file accesses.     

Dynamic diamond anvil cell (dDAC): a novel device for studying the dynamic-pressure properties of materials

We have developed a unique device, a dynamic diamond anvil cell (dDAC), which repetitively applies a time-dependent load/pressure profile to a sample. This capability allows studies of the kinetics of phase transitions and metastable phases at compression (strain) rates of up to 500 GPa/s (approximately 0.16 s(-1) for a metal). Our approach adapts electromechanical piezoelectric actuators to a conventional diamond anvil cell design, which enables precise specification and control of a time-dependent applied load/pressure. Existing DAC instrumentation and experimental techniques are easily adapted to the dDAC to measure the properties of a sample under the varying load/pressure conditions. This capability addresses the sparsely studied regime of dynamic phenomena between static research (diamond anvil cells and large volume presses) and dynamic shock-driven experiments (gas guns, explosive, and laser shock). We present an overview of a variety of experimental measurements that can be made with this device.