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The problems of mapping and load balancing applications on arbitrary networks are considered. A novel diffusion algorithm is presented to solve the mapping problem. It complements the well known diffusion algorithms for load balancing which have enjoyed success on massively parallel computers (MPPs). Mapping is more difficult on interconnection networks than on MPPs because of the variations which occur in network topology. Popular mapping algorithms for MPPs which depend on recursive topologies are not applicable to irregular networks. The most celebrated of these MPP algorithms use information from the Laplacian matrix of a graph of communicating processes. The diffusion algorithm presented in this paper is also derived from this Laplacian matrix. The diffusion algorithm works on arbitrary network topologies and is dramatically faster than the celebrated MPP algorithms. It is delay and fault tolerant. Time to convergence depends on initial conditions and is insensitive to problem scale. This excellent scalability, among other features, makes the diffusion algorithm a viable candidate for dynamically mapping and load balancing not only existing MPP systems but also large distributed systems like the Internet, small cluster computers, and networks of workstations.

Micro-beam scanning system for PIXE analysis newly installed in National Institute of Radiological Sciences (NIRS) was introduced in this paper. Fine ring structure of a fish scale was observed using elemental mapping with proton micro-beam scanning. Pollen was analyzed as one example of single cell to demonstrate the elemental distribution. The minimum size of the proton beam is estimated as 0.4×0.65 μ m.

In March 1999, electrostatic accelerator, Tandetron (Model 4117MC, High Voltage Engineering Europe Co.) was installed in the Electrostatic Accelerator Building for PIXE (Particle Induced X-ray Emission) analysis. The accelerating voltage is 0.4 to 1.7MV, and the maximum beam current is 5μA at 3.4MeV. This system has three beam ports for different types of PIXE analysis: normal, micro-beam and in-air. The first beam port is used for normal PIXE. Since two types of X-ray detecting device, Si (Li) and CdZnTe detectors, are available here, elements from Na (Z=11) to U (Z=92) are detectable. Fifteen samples can semi automatically be measured at one time using a proton beam of optical beam size from 0.5 to 2.0 mm at 100 nA beam current. A quadrupole triplet magnet (Model OM2000, Oxford Micro beams, Ltd.) attached to the second beam port produces a proton micro-beam of square shape less than 1μm×1μm. Micro-beam scanning PIXE analysis is carried out with this beam at 50pA current and scanning area up to 2.0mm square. The in-air PIXE analysis is performed using the third beam port. The operation of this machine has been scheduled to start from April 2000 and is controlled by Division of Technology and Safety. Some results preliminarily obtained are also shorn.

The fastest supercomputers today such as Blue Gene/L, Blue Gene/P, Cray XT3 and XT4 are connected by a three-dimensional torus/mesh interconnect. Applications running on these machines can benefit from topology-awareness while mapping tasks to processors at runtime. By co-locating communicating tasks on nearby processors, the distance traveled by messages and hence the communication traffic can be minimized, thereby reducing communication latency and contention on the network. This paper describes preliminary work utilizing this technique and performance improvements resulting from it in the context of a n-dimensional k-point stencil program. It shows that even for simple benchmarks, topology-aware mapping can have a significant impact on performance. Automated topology-aware mapping by the runtime using similar ideas can relieve the application writer from this burden and result in better performance. Preliminary work towards achieving this for a molecular dynamics application, NAMD, is also presented. Results on up to 32,768 processors of IBM's Blue Gene/L, 4,096 processors of IBM's Blue Gene/P and 2,048 processors of Cray's XT3 support the ideas discussed in the paper.

This paper addresses the problem of mapping the modules of a task precedence graph to the processing elements of a parallel computer. The goal of the mapping is to minimize the total execution time of the task, sum of the computation and communications time, within a processor network of limited size. We consider the special instance where the precedence graph is a binary precedence tree. We present a linear time procedure for mapping an almost full binary precedence tree of n nodes to any p processor hypercube, with unit dilation cost and optimal execution time. The computation time under the mapping is seen to be O(n/p) and the communications time is seen to be log p.

This paper discusses algorithmic issues when computing with a heterogeneous network of work-stations (the typical poor man's parallel computer). Dealing with processors of different speeds requires to use more involved strategies than block-cyclic data distributions. Dynamic data distribution is a first possibility but may prove impractical and not scalable due to communication and control overhead. Static data distributions tuned to balance execution times constitute another possibility but may prove ineffcient due to variations in the processor speeds (e.g. because of different workloads during the computation). We introduce a static distribution strategy that can be refined on the fly, and we show that it is well-suited to parallelizing scientific computing applications such as finite-difference stencils or LU decomposition.

In the previous paper on a tree-to-tree editing problem some errors were included. This letter describes the corrected definition of a structure preserving mapping between rooted and ordered trees and a computing method of the tree distance based on the mapping.

Network on Chip (NoC) is a new communication medium used for systems-on-chip (SoCs). In an SoC, the placement of the communicating elements across the network has an impact on system performance. Such a placing is called the MAPPING phase in networks on chip design process. Many approaches dealing with the mapping phase have been proposed but selecting the best technique for a given NoC remains a challenging problem. This paper attempts to provide an answer to this issue. It motivates and presents a definition and a classification according to some criteria: (i) the algorithms used for solving the mapping problem, (ii) the moment in which the mapping is executed, (iii) the impact of combining mapping with other phases during NoC design and (iv) the target architecture.

In this paper, we investigate the complex dynamics of a mapping derived from a differential equation with simple time-periodic delay. Firstly, we calculate the truncated normal form of 1:1 resonance of the mapping at a degenerate fixed point and obtain an approximating system of the mapping by using Picard iteration. By analyzing the approximate system, we find that the mapping will undergo a 1:1 resonance at the degenerate fixed point. Secondly, the qualitative property and the stability of the degenerate fixed point are determined, which provide a new view to understand the dynamic of differential equation with simple time-periodic delay. However, the approximate system does not have the versal unfolding of the Bogdanov–Takens singularity of codimension 2. These phenomena show that simple time-periodic delay can support complex dynamics. Finally, a numerical simulation is carried out to verify the analytic results.

We present the use of mapping functions to automatically generate levels of detail with known error bounds for polygonal models. We develop a piece-wise linear mapping function for each simplification operation and use this function to measure deviation of the new surface from both the previous level of detail and from the original surface. In addition, we use the mapping function to compute appropriate texture coordinates if the original model has texture coordinates at its vertices. Our overall algorithm uses edge collapse operations. We present rigorous procedures for the generation of local orthogonal projections to the plane as well as for the selection of a new vertex position resulting from the edge collapse operation. The algorithm computes guaranteed error bounds on surface deviation and produces an entire continuum of levels of detail with mappings between them. We demonstrate the effectiveness of our algorithm on several models: a Ford Bronco consisting of over 300 parts and 70, 000 triangles, a textured lion model consisting of 49 parts and 86, 000 triangles, a textured, wrinkled torus consisting of 79, 000 triangles, a dragon model consisting of 871, 000 triangles, a Buddha model consisting of 1,000,000 triangles, and an armadillo model consisting of 2, 000, 000 triangles.

Several approaches have been proposed in the literature for offering RDF views over databases. In addition to these, a variety of tools exist that allow exporting database contents into RDF graphs. The approaches in the latter category have often been proved demonstrating better performance than the ones in the former. However, when database contents are exported into RDF, it is not always optimal or even necessary to export, or dump as this procedure is often called, the whole database contents every time. This paper investigates the problem of incremental generation and storage of the RDF graph that is the result of exporting relational database contents. In order to express mappings that associate tuples from the source database to triples in the resulting RDF graph, an implementation of the R2RML standard is subject to testing. Next, a methodology is proposed and described that enables incremental generation and storage of the RDF graph that originates from the source relational database contents. The performance of this methodology is assessed, through an extensive set of measurements. The paper concludes with a discussion regarding the authors' most important findings.

The purpose of this study was to develop a model to estimate lower extremity joint moments during level gait. A three-layer artificial neural network was developed to map diverse inputs (demographics, anthropometrics, electromyography, kinematics) onto sagittal plane resultant joint moments for a sample of healthy young adults. Overall model performance and prediction accuracy were acceptable for the hip, knee, and ankle, with coefficients of determination (r²) reaching 0.90 for the hip and knee and 0.95 for the ankle. Estimates in the case-specific validation produced r² values of 0.95, 0.94, and 0.99 for the hip, knee, and ankle, respectively. Absolute errors of estimation for peak data were within the ranges published previously for other joint moment models. The results indicated that the model used in this study is accurate in estimating sagittal plane joint moments about the hip, knee, and ankle. Furthermore, the model retained accuracy with a reduced list of inputs (kinematics and demographics). Future development will include clinical samples to determine the adaptability of this model to the diverse conditions of musculoskeletal gait dysfunction common in the clinical setting.

Infinitus Establishes Three Additional Scientific Research Platforms to Facilitate Its Product Innovation.

BGI Partners with NRGene to Provide Broadest Genomic Analysis Available.

CHINA AID - A Platform for Chinese Senior Care Industry.

Modern Biotechnological Tools Contribute to Biodiversity Conservation.

Older Adults Use Brain Regions Involved in Speaking to Compensate for Bad Hearing.

Chinese Scientists Discover Molecules to Repair Organs.

CAS Sits Atop of Nature Index 2016 Rising Star List.

Chinese Researchers to Develop 3D Skin Printing Technology.

Varian Chosen to Equip First Government Owned Proton Centre in China.

HONG KONG NEWS – Amgen Launches Commercial Office in Hong Kong.

The hypercubic family of interconnection networks, encompassing the hypercube and its derivatives and variants, has a wide range of applications in parallel processing. Various problems in general complex networks can be addressed by choosing a hypercubic network as a skeleton. In this paper, we provide insight into why hypercubic networks are suitable as network skeletons and discuss a mapping scheme to take advantage of the symmetry of such networks for developing efficient algorithms.

Sequences formed by symbols are found in diverse fields, including genome sequences, written texts and computer codes. An interesting question is whether a sequence of symbols contains correlated structures. Existing methods to characterize correlations require a numerical representation of the sequence. In this regard, mapping a sequence of text into a sequence of numerical values is a key step for assessing correlation analysis. This work proposes a methodology to study correlations in a sequence of symbols. In the first step, the sequence of symbols is mapped in a multivariate numerical sequence formed by unit vectors in a vectorial space. The main feature of such mapping is that symbols are equally weighted, thus avoiding the numerical overrepresentation of symbols. In the second step, a multivariate version of the detrended fluctuation analysis is used to quantify correlations in the numerical sequence. Genome sequences (first COVID-19), written English texts and comovements between Bitcoin and gold markets were used to illustrate the proposed methodology’s performance. The results showed that the balanced numerical mapping of symbolic sequences and the multivariate DFA provides valuable insights into the correlations in a sequence of symbols.

Ontologies are widely used to represent knowledge explicitly but it is impractical to expect all individuals and organisations to agree on using one or a small subset of ontologies. The adoption of multiple ontologies causes ontology mismatches which make their inherent vocabularies and relationships become inconsistent, resulting in difficulty for one system to understand and reuse these ontologies. To achieve knowledge sharing and reuse, ontology mediation is required to reconcile mismatches between heterogeneous ontologies. In this paper, we investigate the application of ontology in knowledge management (KM). Many KM approaches have been developed with the purpose of managing organisational knowledge. However, these approaches only focus on managing intra-organisational knowledge, which is inadequate in current business environment because users are often required to access inter-organisational knowledge to complete their tasks. These approaches also fail to collaborate with each other as their designs are based on their own business and KM requirement in managing organisational knowledge. We argue that ontology and its mediation methods can be used to overcome limitation of non-collaborative problem in which individual organisation is unable to reuse inter-organisational knowledge. An ontology-based inter-organisational KM network is therefore proposed to allow organisations accessing and retrieving inter-organisational knowledge of common domain.

Trace Base Management System (TBMS) offers processing and querying functionalities for traces that may be of interest to users of tracked systems. Our goal is to ensure the importing of various external traces into kernel for Trace-Based System (kTBS), which is a TBMS developed in the LIRIS laboratory. To overcome the problem of traces heterogeneity, we propose to define a generic collector. To this end, a user with enough knowledge of the tracked system is prompted to define its kTBS trace model and correspondences between the elements of this model and the elements of the trace to import. The system generalises the mappings previously elicited by the user through interaction to create mapping rules. After this phase, the collector will generate modelled traces from the existing ones and the already defined mapping rules.

In this paper, we present a method for controlling a motorized, string-driven marionette using motion capture data from human actors and from a traditional marionette operated by a professional puppeteer. We are interested in using motion capture data of a human actor to control the motorized marionette as a way of easily creating new performances. We use data from the hand-operated marionette both as a way of assessing the performance of the motorized marionette and to explore whether this technology could be used to preserve marionette performances. The human motion data must be extensively adapted for the marionette because its kinematic and dynamic properties differ from those of the human actor in degrees of freedom, limb length, workspace, mass distribution, sensors, and actuators. The motion from the hand-operated marionette requires less adaptation because the controls and dynamics are a closer match. Both data sets are adapted using an inverse kinematics algorithm that takes into account marker positions, joint motion ranges, string constraints, and potential energy. We also apply a feedforward controller to prevent extraneous swings of the hands. Experimental results show that our approach enables the marionette to perform motions that are qualitatively similar to the original human motion capture data.

Humanoid robots still have a low-level perception of their surroundings, which is a formidable obstacle to performing complex tasks. To improve their perceptual capabilities, high-level semantic information can be incorporated into their perceptual framework so that they can gain the ability to infer and understand their environment accurately. Among the various techniques available, semantic Simultaneous Localization and Mapping (SLAM) becomes a promising avenue for achieving this perception enhancement. While semantic SLAM can enhance a robot’s ability to perform tasks, the accurate perception, and association of semantic objects in complex and dynamic environments remain challenging. Hence, the need arises for a solution that swiftly and precisely associates object measurements with landmarks, considering their motion properties, and promptly rectifies erroneous associations in real time. To this end, we propose a semantic perception approach designed explicitly for dynamic environments, adept at distinguishing between dynamic and static objects. Furthermore, we propose two association strategies: dynamic object association based on semantic map points and static object association based on object pose information. And as the number of object measurements associated with the landmarks increases, we perform the association validation algorithm to verify the association for the landmark to improve the accuracy of the association. The proposed method is extensively evaluated on both simulated indoor sequences obtained from humanoid robot viewpoints and the KITTI dataset. Experimental results show that our approach significantly improves the robustness and accuracy of object association and trajectory estimation.

This paper estimates the economic costs from storm surge scenarios in the Free and Hanseatic City of Hamburg. Hydrodynamic and damage models simulate the direct damages to residential and commercial buildings and equipment in a part of the city named Hamburg–Wilhelmsburg. They are assigned to individual economic sectors and then integrated into an economic model. This model accounts for the indirect impacts due to the interruption of production processes. Furthermore, the indirect costs are allocated to the flooded and non-flooded area in the whole city of Hamburg and then to each firm according to its relative size. Thus, the spatial distribution of indirect damages can be visualized. The approach is a helpful tool to simulate potential total damages from storm surge scenarios at the city scale and can be used to assess the effectiveness of possible protection measures. The inclusion of indirect costs into flood risk mapping complements common risk mapping procedures.