An Environment for Rapid Prototyping of Interactive Systems

This paper shows an environment which supports the development of multi-thread dialogue interactive systems.The environment includes several tools and run-time support programs for the design and implementation of the user interface of an interactive system.First,methods of user interface specifica- tion with Elementary Nets are discussed.Then,the syntax of a user interface specification language based on Elementary Nets and the pre-compiler for the language as well as a graphic editor for Elemen- tary Nets construction are described.Finally,an example is given to illustrate the design process of a user interface.

Graph-enhanced neural interactive collaborative filtering

To improve the training efficiency and recommendation accuracy in cold-start interactive recommendation systems,a new graph structure called item similarity graph is proposed on the basis of real data from a public dataset.The proposed graph is built from collaborative interactions and a deep reinforcement learning-based graph-enhanced neural interactive collaborative filtering(GE-ICF)model.The GE-ICF framework is developed with a deep reinforcement learning framework and comprises an embedding propagation layer designed with graph neural networks.Extensive experiments are conducted to investigate the efficiency of the proposed graph structure and the superiority of the proposed GE-ICF framework.Results show that in cold-start interactive recommendation systems,the proposed item similarity graph performs well in data relationship modeling,with the training efficiency showing significant improvement.The proposed GE-ICF framework also demonstrates superiority in decision modeling,thereby increasing the recommendation accuracy remarkably.

Forming different planetary systems

With the increasing number of detected exoplanet samples, the statistical properties of planetary systems have become much clearer. In this review, we sum- marize the major statistical results that have been revealed mainly by radial velocity and transiting observations, and try to interpret them within the scope of the classical core-accretion scenario of planet formation, especially in the formation of different orbital architectures for planetary systems around main sequence stars. Based on the different possible formation routes for different planet systems, we tentatively classify them into three major catalogs： hot Jupiter systems, standard systems and distant giant planet systems. The standard systems can be further categorized into three sub-types under different circumstances： solar-like systems, hot Super-Earth systems, and sub- giant planet systems. We also review the theory of planet detection and formation in binary systems as well as planets in star clusters.

THE INTERACTIONS OF SHOCK WAVES OF NONSTRICTLY HYPERBOLIC SYSTEMS

The interaction of shock waves is investigated for the following nonstrictly hyperbolic system: [GRAPHICS] The interaction of shock waves is complicated, with new types of shock waves, and new singula rities in the dependence of interaction on the relative positions of the three states separated by shock waves. Several ideas are introduced to helo organize and clarify the new phenomena.

The Effect of the Interaction among Multi-Scale Systems and the Asymmetric an

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IDSS: Designing to Extend the Cognitive Limits

The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.

DATA: Digital Archiving and Transformed Analytics

As cloud service becomes more and more capable, available and powerful, wiseCIO has emerged from an innovative roadmap toward archival Content Management Service (aCMS) and massive Content Delivery Service (mCDS) in support of Anything-as-a-Service (XaaS) via Digital Archiving and Transformed Analytics (DATA);DATA aims to automate UBC with FAST solutions throughout a feasible, analytical, scalable and testable approach. This paper, based on the novel wiseCIO (web-based intelligent service engaging Cloud Intelligence Outlet), presents digital archiving and transformed analytics via machine learning automata for intelligent UBC processes to liaise with Universal interface for human-computer interaction, enable Brewing aggregation (differing from traditional web browsing), and engage Centered user experience. As one of the most practical aspects of artificial intelligence, machine learning is applied to analytical model building and massive and/or multidimensional Online Analytical Processing (mOLAP) for more intelligent cloud service with little explicit coding required. DATA is central to useful information via archival transformation and analytics, and utilizable intelligence for Business, Education and Entertainment (iBEE) in support of decision-making. As a result, DATA orchestrates wiseCIO to promote ACTiVE XaaS that enables accessibility, contextuality and traceability of information for vast engagement with various cloud services, such as aCMS (archival Content Management Service), COSA (Context-Oriented Screening Aggregation), DASH (Deliveries Assembled for fast Search and Hits), OLAS (Online Learning via Analytical Synthesis), REAP (Rapid Extension and Active Presentation), and SPOT (Special Points On Top) with great ease.

On the Development of Meso-Scale Heavy Rain Parcels in China

Heavy rains occur in China frequently, which often bring us floods and serious disasters in the summer half-year. The meso-scale heavy rain parcels (MHRP) in the mid-latitude are usually developed in following cases:I.By the approaching, meeting and / or overlapping of different weather systems, when two or more different rainfall systems are getting to conjugate, some MHRPs could be developed, such as: 1) a new cold/warm front or squall line approaches an old front or squall, even when the old one is somewhat decrepit; 2) at the places where two or more synoptic systems with different characteristics are meeting together, such as the meeting of tropical cyclone with the cold airs coming from the mid- and / or high-latitudes, or the low latitude vortex meeting with the westerly trough; 3) at the intersections of some different weather systems, such as the intersection of drylines, squall lines or fronts moving from different directions; and 4) by the overlapping of rainfall parcels produced continuously from a meso-generation centre.II.Resonance Effect and Tibetan Plateau Influence are two reasons why high frequency of heavy and torrential rains arround the meiyu front is discussed also.

Limits of One-dimensional Interacting Particle Systems with Two-scale Interaction

This paper characterizes the limits of a large system of interacting particles distributed on the real line.The interaction occurring among neighbors involves two kinds of independent actions with different rates.This system is a generalization of the voter process,of which each particle is of type A or a.Under suitable scaling,the local proportion functions of A particles converge to continuous functions which solve a class of stochastic partial differential equations driven by Fisher-Wright white noise.To obtain the convergence,the tightness of these functions is derived from the moment estimate method.

Stability of interacting grid-connected power converters

The power grid in a typical micro distribution system is non-ideal,presenting itself as a voltage source with significant impedance.Thus,grid-connected converters interact with each other via the non-ideal grid.In this study,we consider the practical scenario of voltage-source converters connected to a three-phase voltage source with significant impedance.We show that stability can be compromised in the interacting converters.Specifically,the stable operating regions in selected parameter space may be reduced when grid-connected converters interact under certain conditions.In this paper,we develop bifurcation boundaries in the parameter space with respect to Hopftype instability.A small-signal model in the dq-frame is adopted to analyze the system using an impedance-based approach.Moreover,results are presented in design-oriented forms so as to facilitate the identification of variation trends of the parameter ranges that guarantee stable operation.

Combining IFS and VQ in Fractal Image Coding

A novel paradigm for fractal coding selectively corrects the fractal code for selected domain blocks with an image-adaptive VQ codebook. The codebook is generated from the initial uncorrected fractal code and is, therefore, available at the decoder. An efficient trade-off is generated between incremental performance and bit rate.

A hazard analysis via an improved timed colored petri net with time–space coupling safety constraint

Petri nets are graphical and mathematical tools that are applicable to many systems for modeling, simulation, and analysis. With the emergence of the concept of partitioning in time and space domains proposed in avionics application standard software interface (ARINC 653), it has become difficult to analyze time–space coupling hazards resulting from resource partitioning using classical or advanced Petri nets. In this paper, we propose a time–space coupling safety constraint and an improved timed colored Petri net with imposed time–space coupling safety constraints (TCCP-NET) to fill this requirement gap. Time–space coupling hazard analysis is conducted in three steps: specification modeling, simulation execution, and results analysis. A TCCP-NET is employed to model and analyze integrated modular avionics (IMA), a real-time, safety-critical system. The analysis results are used to verify whether there exist time–space coupling hazards at runtime. The method we propose demonstrates superior modeling of safety-critical real-time systems as it can specify resource allocations in both time and space domains. TCCP-NETs can effectively detect underlying time–space coupling hazards. © 2016 Chinese Society of Aeronautics and Astronautics

Some Random Batch Particle Methods for the Poisson-Nernst-Planck and Poisson-Boltzmann Equations

We consider in this paper random batch interacting particle methods forsolving the Poisson-Nernst-Planck (PNP) equations, and thus the Poisson-Boltzmann(PB) equation as the equilibrium, in the external unbounded domain. To justify thesimulation in a truncated domain, an error estimate of the truncation is proved inthe symmetric cases for the PB equation. Then, the random batch interacting particle methods are introduced which are O(N) per time step. The particle methods cannot only be considered as a numerical method for solving the PNP and PB equations,but also can be used as a direct simulation approach for the dynamics of the chargedparticles in solution. The particle methods are preferable due to their simplicity andadaptivity to complicated geometry, and may be interesting in describing the dynamics of the physical process. Moreover, it is feasible to incorporate more physical effectsand interactions in the particle methods and to describe phenomena beyond the scopeof the mean-field equations.

Effect of tensor correlations on the depletion of nuclear Fermi sea within the extended BHF approach

We have investigated the effect of tensor correlations on the depletion of the nuclear Fermi sea in symmetric nuclear matter within the framework of the extended Brueckner-Hartree-Fock approach by adopting the AV 18 two-body interaction and a microscopic three-body force.The contributions from various partial wave channels including the isospin-singlet T = 0 channel,the isospin-triplet T = 1 channel and the T = 0 tensor 3SD1 channel have been calculated.The T =0 neutron-proton correlations play a dominant role in causing the depletion of nuclear Fermi sea.The T =0 correlation-induced depletion turns out to stem almost completely from the 3SD1 tensor channel.The isospin-singlet T = 0 3SD1 tensor correlations are shown to be responsible for most of the depletion,which amounts to more than 70 percent of the total depletion in the density region considered.The three-body force turns out to lead to an enhancement of the depletion at high densities well above the empirical saturation density and its effect increases as a function of density.

The _(ΛΛ)~4n system

Using local central Yukawa-type Malfliet-Tjon interactions reproducing the low-energy parameters and phase shifts of the nn system, and the latest updates of the nΛ and ΛΛ Nijmegen ESC08c potentials, we study the possible existence of a ^4 ΛΛn bound state. Our results indicate that the ^4 ΛΛn is unbound, being just above threshold.We discuss the role played by the -1S0 nn repulsive term of the Yukawa-type Malfliet-Tjon interaction.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network（interactome） indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy（IDCM） data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.