Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling

Visual analytics usually deals with complex data and uses sophisticated algorithmic, visual, and interactive techniques. Findings of the analysis often need to be communicated to an audience that lacks visual analytics expertise. This requires analysis outcomes to be presented in simpler ways than that are typically used in visual analytics systems. However, not only analytical visualizations may be too complex for target audience but also the information that needs to be presented. Hence, there exists a gap on the path from obtaining analysis findings to communicating them, which involves two aspects: information and display complexity. We propose a general framework where data analysis and result presentation are linked by story synthesis, in which the analyst creates and organizes story contents. Differently, from the previous research, where analytic findings are represented by stored display states, we treat findings as data constructs. In story synthesis, findings are selected, assembled, and arranged in views using meaningful layouts that take into account the structure of information and inherent properties of its components. We propose a workflow for applying the proposed framework in designing visual analytics systems and demonstrate the generality of the approach by applying it to two domains, social media, and movement analysis

Strongly Localized Electrons in a Magnetic Field: Exact Results on Quantum Interference and Magnetoconductance

We study quantum interference effects on the transition strength for strongly localized electrons hopping on 2D square and 3D cubic lattices in a magnetic field B. In 2D, we obtain closed-form expressions for the tunneling probability between two arbitrary sites by exactly summing the corresponding phase factors of all directed paths connecting them. An analytic expression for the magnetoconductance, as an explicit function of the magnetic flux, is derived. In the experimentally important 3D case, we show how the interference patterns and the small-B behavior of the magnetoconductance vary according to the orientation of B.Comment: 4 pages, RevTe

Resolution in Linguistic Propositional Logic based on Linear Symmetrical Hedge Algebra

The paper introduces a propositional linguistic logic that serves as the basis for automated uncertain reasoning with linguistic information. First, we build a linguistic logic system with truth value domain based on a linear symmetrical hedge algebra. Then, we consider G\"{o}del's t-norm and t-conorm to define the logical connectives for our logic. Next, we present a resolution inference rule, in which two clauses having contradictory linguistic truth values can be resolved. We also give the concept of reliability in order to capture the approximative nature of the resolution inference rule. Finally, we propose a resolution procedure with the maximal reliability.Comment: KSE 2013 conferenc

Thermal and Athermal Swarms of Self-Propelled Particles

Swarms of self-propelled particles exhibit complex behavior that can arise from simple models, with large changes in swarm behavior resulting from small changes in model parameters. We investigate the steady-state swarms formed by self-propelled Morse particles in three dimensions using molecular dynamics simulations optimized for GPUs. We find a variety of swarms of different overall shape assemble spontaneously and that for certain Morse potential parameters coexisting structures are observed. We report a rich "phase diagram" of athermal swarm structures observed across a broad range of interaction parameters. Unlike the structures formed in equilibrium self-assembly, we find that the probability of forming a self-propelled swarm can be biased by the choice of initial conditions. We investigate how thermal noise influences swarm formation and demonstrate ways it can be exploited to reconfigure one swarm into another. Our findings validate and extend previous observations of self-propelled Morse swarms and highlight open questions for predictive theories of nonequilibrium self-assembly.Comment: 21 pages, 7 figure

Modeling and Analyzing Academic Researcher Behavior

. This paper suggests a theoretical framework for analyzing the mechanism of the behavior of academic researchers whose interests are tangled and vary widely in academic factors (the intrinsic satisfaction in conducting research, the improvement in individual research ability, etc.) or non-academic factors (career rewards, financial rewards, etc.). Furthermore, each researcher also has his/her different academic stances in their preferences about academic freedom and academic entrepreneurship. Understanding the behavior of academic researchers will contribute to nurture young researchers, to improve the standard of research and education as well as to boost collaboration in academia-industry. In particular, as open innovation is increasingly in need of the involvement of university researchers, to establish a successful approach to entice researchers into enterprises' research, companies must comprehend the behavior of university researchers who have multiple complex motivations. The paper explores academic researchers' behaviors through optimizing their utility functions, i.e. the satisfaction obtained by their research outputs. This paper characterizes these outputs as the results of researchers' 3C: Competence (the ability to implement the research), Commitment (the effort to do the research), and Contribution (finding meaning in the research). Most of the previous research utilized the empirical methods to study researcher's motivation. Without adopting economic theory into the analysis, the past literature could not offer a deeper understanding of researcher's behavior. Our contribution is important both conceptually and practically because it provides the first theoretical framework to study the mechanism of researcher's behavior

Chemical analysis by X-ray spectroscopy near phase transitions in the solid state

The methods discussed in this work show that the types of changes which may be observed, by precise XAS measurements of Absorbance A versus temperature, across a phase transition are: the changes in the relaxation time of the final states due to fluctuations near a phase transition; the detection of the anomalous Bragg condition coupled to phonon modes XAS enhancement that identifies the temperature interval where the phonon modes are active, the symmetry changes which introduce new allowed transitions to finite states below an element edge, near Tc indicate what symmetry changes occur, and the method of XTDAFST0 = XAFS(T) - XAFS(T0), allows the precise measurement of the progressive changes in the Debye-Waller factor versus T near a phase transition, and identify (when no other structural changes occur, except in the vibrational modes of a specific bond) the bond responsible for the transition. The methods have been applied to the superconducting transition in layer cuprates and the metal to insulator transition in NiS2-xSex

Exploiting resource contention in highly mobile environments and its application to vehicular ad-hoc networks

As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. However, mobile environments also need to consider handover issues. Furthermore, in a highly mobile environment, traditional reactive approaches to handover are inadequate and thus proactive techniques have been investigated. Recent research in proactive handover techniques, defined two key parameters: Time Before Handover and Network Dwell Time for a mobile node in any given networking topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. This proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This paper therefore presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments

Benchmark generator for CEC 2009 competition on dynamic optimization

Evolutionary algorithms(EAs) have been widely applied to solve stationary optimization problems. However, many real-world applications are actually dynamic. In order to study the performance of EAs in dynamic environments, one important task is to develop proper dynamic benchmark problems. Over the years, researchers have applied a number of dynamic test problems to compare the performance of EAs in dynamic environments, e.g., the “moving peaks ” benchmark (MPB) proposed by Branke [1], the DF1 generator introduced by Morrison and De Jong [6], the singleand multi-objective dynamic test problem generator by dynamically combining different objective functions of exiting stationary multi-objective benchmark problems suggested by Jin and Sendhoff [2], Yang and Yao’s exclusive-or (XOR) operator [10, 11, 12], Kang’s dynamic traveling salesman problem (DTSP) [3] and dynamic multi knapsack problem (DKP), etc. Though a number of DOP generators exist in the literature, there is no unified approach of constructing dynamic problems across the binary space, real space and combinatorial space so far. This report uses the generalized dynamic benchmark generator (GDBG) proposed in [4], which construct dynamic environments for all the three solution spaces. Especially, in the rea

Negative Magnetoresistance in the Nearest-neighbor Hopping Conduction

We propose a size effect which leads to the negative magnetoresistance in granular metal-insulator materials in which the hopping between two nearest neighbor clusters is the main transport mechanism. We show that the hopping probability increases with magnetic field. This is originated from the level crossing in a few-electron cluster. Thus, the overlap of electronic states of two neighboring clusters increases, and the negative magnetoresistance is resulted.Comment: Latex file, no figur