A2M: Approximate Algebraic Memory Using Polynomials Rings

CRMgeo is a formal ontology intended to be used as a global schema for integrating spatiotemporal properties of temporal entities and persistent items. Its primary purpose is to provide a schema consistent with the CIDOC CRM to integrate geoinformation using the conceptualizations, formal definitions, encoding standards and topological relations defined by the Open Geospatial Consortium in GeoSPARQL. To build the ontology, the same ontology engineering methodology was used as in the CIDOC CRM. CRMgeo first introduced the concept of Spacetime volume that was subsequently included in the CIDOC CRM and provides a differentiation between phenomenal and declarative Spacetime volume, Place and Time-Span. Phenomenal classes derive their identity from real world phenomena like events or things and declarative classes derive their identity from human declarations like dates or coordinates. This differentiation is an essential conceptual background to link CIDOC CRM to the classes, topological relations and encodings provided by Geo-SPARQL and thus allowing spatiotemporal analysis offered by geoinformation systems based on the semantic distinctions of the CIDOC CRM. CRMgeo introduces the classes and relations necessary to model the spatiotemporal properties of real world phenomena and their topological and semantic relations to spatiotemporal information about these phenomena that was derived from historic sources, maps, observations or measurements. It is able to model the full chain of approximating and finding again a phenomenal place, like the actual site of a ship wreck, by a declarative place, like a mark on a sea chart.

This paper introduces a second-level compression scheme on an image which has been already compressed using an existing algorithm. In the proposed technique, error concealment of digital images, implemented by adopting the NFD information hiding technique, is performed in the initial phase, followed by conventional transform based encoding and entropy encoding to achieve the first stage compression. The main contribution of this paper is the second level compression (named PGR compression by the authors) of the entropy encoded image wherein the bit positions of the encoded image are subjected to a mapping procedure with the matched bit positions in a base file (known to both the transmitting and receiving mobile device/stations) to generate a mathematical function which would fit the mapped data set. The conversion of the original image file into a mathematical function, requiring fewer bits, provides very high compression.

7 - LINEAR TRANSFORMATIONS, MATRICES AND DETERMINANTS

Geospatial data are the backbone of spatial analysis, but only current and accurate data can provide the appropriate framework for successful use of GIS technology. The revision of geospatial data is still one of the major open challenges for the successful implementation of Geographic Information Systems (GIS). There is a great need for cost-efficient data revision and quality control methods in order to fulfill the need of most faithful image of the geographic space reality. Maintaining one database per scale without directly maintaining interrelationship between multiple scale databases leads to no update propagation and inter-database consistency is lost. A Multi-resolution/representation-database (MRDB) approach is proposed in this paper to solve this problem. MRDB is a spatial database technology that designed to store one real world phenomena at several specially designed levels of precision, accuracy and resolution. Propagating updates between these different scales datasets in MRDB with the advantage that data consistency and integrity can be significantly improved and enable an automatic incremental update process for the data sets.

The purpose of this research was to analyze the convergent approaches for creativity in elementary mathematics textbooks in Korean and the united States. Convergent approaches have emphasized since NCTM(2000) consistently includes 'connections' as an important factor in mathematics curriculum and KOFAC(Korea Foundation for the Advancement of Science & Creativity) initiated the STEAM(Science, Technology, Engineering, Arts, and Mathematics) in mathematics and science education. For this research, two elementary mathematics textbooks were analyzed focused on their contexts and contents: Korean National Elementary Mathematics Textbooks and Navigations in Numbers, Data, and Space. In both textbooks, it was not easy to find so called the convergent approach in a real sense, but they use some contexts for connections between mathematical concepts and real world phenomena. For the enhancement of convergent approaches in mathematics education, we need to have a broader sense in the convergent approaches and develop various meaningful materials.

Do computer simulations help students learn science? How can we tell? Are there negative implications of using simulations to teach students about real world phenomena? In this paper I describe my experience using a computer simulation on air resistance. In order to parse out the effects of using the computer simulation and of having an interactive learning environment, I compare two classes which both had interactive learning environments. One class used the simulation and the other class used only a set of paper and pencil activities. In the two different learning environments, there appears to be differences in how students approached learning. However, student performance on a common exam question on air resistance was not significantly different.

This chapter presents existence theory for second order boundary value problems on infinite intervals. There are two major approaches in the literature to establish existence of solutions to boundary value problems on infinite intervals. The first approach is based on a diagonalization process whereas the second is based on the Furi-Pera fixed point theorem. Both approaches will be presented in this chapter. In Section 1.2 we list several examples from the real world phenomena which motivate the study of boundary value problems on infinite intervals. In Section 1.3 we discuss some infinite interval problems which date back to 1896 and state several fundamental results which are well known.

Nonlinear Evolution Equations

Sampling from complex networks using distributed learning automata

Although many real world phenomena are vague and characterized by having uncertain location or vague shape, existing spatial data warehouse models do not support spatial vagueness and then cannot properly represent these phenomena. In this paper, we propose the VSCube conceptual model to represent and manipulate shape vagueness in spatial data warehouses, allowing the analysis of business scores related to vague spatial data, and therefore improving the decision-making process. Our VSCube conceptual model is based on the cube metaphor and supports geometric shapes and the corresponding membership values, thus providing more expressiveness to represent vague spatial data. We also define vague spatial aggregation functions (e.g. vague spatial union) and vague spatial predicates to enable vague SOLAP queries (e.g. intersection range queries). Finally, we introduce the concept of vague SOLAP and its operations (e.g. drill-down and roll-up). We demonstrate the applicability of our model by describing an application concerning pest control in agriculture and by discussing the reuse of existing models in the VSCube conceptual model.

Fat and Thin Sex: Fetishised Normal and Normalised Fetish

With the rapidly growing demands for large capacity main memory in server systems and embedded systems, current DRAM-only approach is hitting the limit due to DRAM's capacity scaling issue and significant background power. With the emergence of new non-volatile memories, or storage-class memories (SCMs), we can now explore low power, high capacity memory subsystem by redesigning virtual memory system to be SCM-aware. Most research on virtual memory system design has focused on minimizing page fault frequency due to slow data transfers using storage such as HDD/SSD as virtual memory swap device. However with an SCM-based swap device, its near-DRAM access latency has potential for reducing requisite DRAM size by aggressively evicting pages from DRAM to SCM without sacrificing performance, and thus reducing background power by powering off the freed DRAM space for low power. To select an optimal SCM from among the many candidate SCM technologies, the impact of SCM characteristics was evaluated using full-system simulation. Results show that utilizing SCM with low access latency and low write energy can lead to significant potential reduction of memory subsystem energy by up to 83%, while maintaining performance degradation within acceptable range.

The 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> generation Intel® Xeon Phi processor (codenamed Knights Landing) is Intel's first self-booting Xeon Phi processor that is aimed at the HPC market. Like its predecessor, KNL is a many-core, highly threaded processor featuring an innovative on-die mesh interconnect and an on-package high bandwidth memory MCDRAM in addition to DRAM DDR-2400, which makes it possible for many HPC applications to achieve much higher performance by leveraging heterogeneous memory configuration. In this paper, we look at the programming challenges for software developers to create and manipulate data using different memory modes and a heap management API to satisfy the ever-increasing demand for high bandwidth and low latency. We start with a functional KNL architecture introduction with an emphasis on the memory subsystem and memory usage model, followed by the utility tools required to run the applications under various scenarios. We then present a profiler-based heterogeneous memory optimization framework for all memory-bandwidth-intensive applications. The new memory object features in Intel® VTune™ Amplifier will be introduced and discussed. Finally, we show how to leverage different kinds of memory by using a user extensible memory heap management API also known as memkind API. Throughout our discussions, we will use a classic streaming application in quantitative finance, the Black-Scholes benchmark. We show how to highlight the memory bottleneck using the new memory profiling features in the Intel VTune Amplifier and how to achieve high bandwidth by removing the bottleneck and by allocating memory threads between different types of memory. In the end, we show the peak performance we can achieve on KNL by using a combination of MCDRAM and DDR.

The effective use of modeling, simulation, and analysis (MSA) applications could greatly enhance our nation's ability to achieve homeland security goals. The development of MSA applications has been conducted largely on an ad hoc and piecemeal basis. There is very little, if any, coordination of MSA development activities across government agencies, the research community, the commercial software sector, and various standards organizations. Without coordination and appropriate standards, there is little possibility of software re-use or the establishment of reference data sets that meet homeland security needs. A needs analysis for MSA applications is the first step to the identification of standards requirements. NIST is conducting a needs analysis for the Department of Homeland Security in this area. This paper provides a high level overview of a needs analysis for the homeland security simulation-modeling domain. The modeling domain gives an indication about what is being simulated or the dynamics of the simulation, i.e., the ways in which real world behaviors, processes, phenomena, or effects are generated. Major groupings of modeling domains for categorizing simulations include Social Behavior; Physical Phenomenon; Environment; Economic; Organization; Infrastructure System; and Other System, Equipment, and Tool. The paper briefly describes needs for each of these MSA domains.

Spatio-temporal data may be used to represent the evolution of real world objects and phenomena. Such data can be represented in discrete time, which associates spatial information (like position and shape) to time instants, or in continuous time, in which the representation of the evolution of the phenomena is decomposed into slices and interpolation functions are used to estimate the intermediate position and shape at any time. The use of a discrete model may seem more straightforward but a continuous representation provides potential gains in terms of data management, including in compression and spatio-temporal operations.