Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Predictor for Co-Simulation with Multistep Sub-System Solvers

An industrial model of a dynamic system is usually not just a set of diﬀer-ential equations. External inputs acting on the system are common, such as an external force acting on a body or wind pressing on a car. Update of these inputs needs to be handled by the numerical solver in an eﬃcient way. In dynamical simulation, multistep methods are commonly used. A multi-step method uses the solution history in order to predict the future solution. When an input is changed, the history is no longer a good approximation for the future solution which may result in order reductions and simulation failure. In this paper, a modiﬁcation of the predictor is presented. Modifying the predictor, instead of restarting the method, results in an increased performance of the method. The cost of the modiﬁcation must be weighed with the cost of restarting the method. Experiments show that the beneﬁt of modifying the predictor outweighs the cost of a restart.
Imagine Real Avatars and Flying Shepherds: Involvement and Engagement in Innovative Ict Conference Item Imagine Real Avatars and Flying Shepherds: Involvement and Engagement in Generating Innovative Project Ideas

Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. ABSTRACT This paper takes as its starting point Kyng's (2010) challenges for future participatory design practices in the context of a technology landscape which has changed enormously since the emergence of both 'Scandinavian' PD and the participatory politics of 1960s US radicalism. We describe the Infinite Bandwidth, Zero Latency (IBZL)) project, from its use of the 'Imagine' workshop method to envisage potential technological futures, through to its involvement of stakeholder representatives and potential users in assessing one such vision of potential technological 'futures', the 'real avatar''. IBZL was originally conceived as an intervention in policy debates in the UK about the significance and potential of 'next generation' or 'superfast' broadband networks, and as a way of mobilizing wider audiences to consider the possibility of innovative applications of them. By their very nature, the significance of these networks transcends particular workplaces. This case study describes responses to several of the challenges for PD practice raised by Kyng, including the roles of companies, intellectual property, funding, the involvement of social actors as users, the engagement of users in multiple roles.
How do some concepts vanish over time ? Conference or Workshop Item

This paper presents the current stage of my PhD research focused on the use of machine learning in supporting the human learn from examples. I present here an approach to answer how some concepts change their contexts in time, using two techniques suitable for indexing and data mining: latent semantic indexing (LSI) and the APRIORI algorithm.
Potential role of molecular mimicry between Helicobacter pylori lipopolysaccharide and host Lewis blood group antigens in autoimmunity

Helicobacter pylori is involved in gastritis, gastric and duodenal ulcers, gastric adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma. Earlier studies already suggested a role for autoimmune phenomena in H. pylori-linked disease. We now report that lipopolysaccharides (LPS) of H. pylori express Lewis y, Lewis x, and H type I blood group structures similar to those commonly occurring in gastric mucosa. Immunization of mice and rabbits with H. pylori cells or purified LPS induced an anti-Lewis x or y or anti-H type I response, yielding antibodies that bound human and murine gastric glandular tissue, granulocytes, adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma cells. Experimental oral infections in mice or natural infection in humans yielded anti-Lewis antibodies also. The beta chain of gastric (H+,K+)-ATPase, the parietal cell proton pump involved in acid secretion, contained Lewis y epitopes; gastric mucin contained Lewis x and y antigenic determinants. Growth in mice of a hybridoma that secretes H. pylori-induced anti-Lewis y monoclonal antibodies resulted in histopathological evidence of gastritis, which indicates a direct pathogenic role for anti-Lewis antibodies. In conclusion, our observations demonstrate that molecular mimicry between H. pylori LPS and the host, based on Lewis antigens, and provide understanding of an autoimmune mechanism for H. pylori-associated type B gastritis.
Endotoxin-induced enhancement of glucose influx into murine peritoneal macrophages via GLUT1

Hypoglycemia is among the most injurious metabolic disorders caused by endotoxemia. In experimental endotoxemia with lipopolysaccharide (LPS) in animals, a marked glucose consumption is observed in macrophage-rich organs. However, the direct effect of LPS on the uptake of glucose by macrophages has not been fully understood, and the present study was undertaken to shed light on this point. The consumption and uptake of glucose, as measured with 2-deoxy-D-[3H]glucose, by murine peritoneal exudate macrophages in culture were accelerated two- to threefold by stimulation with 3 ng of LPS per ml. The rate of glucose uptake reached a plateau after 20 min of stimulation and remained at the maximum as long as LPS was present. Northern (RNA) blot analysis with cDNA probes for five known isoforms of glucose transporter (GLUT) revealed that the expression of GLUT by macrophages was restricted to the GLUT1 isoform during LPS stimulation and the amount of GLUT1 mRNA was increased by the stimulation. These results suggest that macrophage responses to LPS are supported by a rapid and sustained glucose influx via GLUT1 and that this is a participating factor in the development of systemic hypoglycemia when endotoxemia is prolonged.
A Conceptual Framework for Digital Libraries for K–12 Mathematics Education: Part 1, Information Organization, Information Literacy, and Integrated Learning1

This article is the first of two that present a six‐part conceptual framework for the design and evaluation of digital libraries meant to support mathematics education in K–12 settings (see also pt. 2). This first article concentrates on (1) information organization, (2) information literacy, and (3) integrated learning with multimedia materials. The second article reviews (4) adoption of new standards for mathematics education, (5) integration of pertinent changes in educational policy, and (6) ensuring pedagogic and political accountability. Each article concludes with specific recommendations for digital libraries meant to support K–12 mathematics education appropriate to the topics the article discusses. This framework, which may be of some use to researchers and educators in many settings and countries, emphasizes the importance of communication, community building, and learning activities that use different media for the design of digital functionalities and online collections of mathematics learning materials. The major goal of the framework described here is to consider how to bring the larger computationally intensive collections called digital libraries closer to the existing structures and practices of learners and teachers while recognizing the new functionalities and learning opportunities that digital libraries offer.
Derandomizing Arthur-Merlin Games using Hitting Sets

We prove that AM (and hence Graph Nonisomorphism) is in NP if for some > 0, some language in NE ∩ coNE requires nondeterministic circuits of size 2 n. This improves recent results of Arvind and Köbler and of Klivans and Van Melkebeek who proved the same conclusion, but under stronger hardness assumptions, namely, either the existence of a language in NE ∩ coNE which cannot be approximated by nondeterministic circuits of size less than 2 n or the existence of a language in NE ∩ coNE which requires oracle circuits of size 2 n with oracle gates for SAT (satisfiability). The previous results on derandomizing AM were based on pseudorandom generators. In contrast, our approach is based on a strengthening of Andreev, Clementi and Rolim’s hitting set approach to derandomization. As a spin-off, we show that this approach is strong enough to give an easy (if the existence of explicit dispersers can be assumed known) proof of the following implication: For some > 0, if there is a language in E which requires nondeterministic circuits of size 2 n, then P=BPP. This differs from Impagliazzo and Wigderson’s theorem “only” by replacing deterministic circuits with nondeterministic ones. ∗Basic Research in Computer Science, Centre of the Danish National Research Foundation.
Interacting with the real world – design principles for intelligent systems

The last two decades in the field of artificial intelligence have clearly shown that true intelligence always requires the interaction of an agent with a real physical and social environment. The concept of embodiment that has been introduced to designate the modern approach to designing intelligence has far-reaching implications. Rather than studying computation alone, we must consider the interplay between morphology, materials, brain (control), and the environment. A number if case studies are presented, and it is demonstrated how artificial evolution and morphogenesis can be used to systematically investigate this interplay. Taking these ideas into account requires entirely novel ways of thinking, and often leads to surprising results.
VisIRR: A Visual Analytics System for Information Retrieval and Recommendation in Large-Scale Document Data

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through a query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efﬁcient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents, VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This paper presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Additionally, we present preliminary user study results for evaluating the effectiveness of the system.
Reproducibility Report for ACM SIGMOD 2020 Paper: ``Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects''

2 SUBMISSION The submission was supplemented by a reproducibility guide. This document contained information about the necessary hardand software, as well as a seemingly step-by-step guide (see Section 4.1 for clarification) for the overall reproducibility process and contact information of two persons, who could support in case help was needed. The required code was hosted on the authors’ webspace and easily obtainable. Table 1 gives an overview about the relevant provided files.
Neighborhood Repulsed Metric Learning for Kinship Verification

Kinship verification from facial images is an interesting and challenging problem in computer vision, and there are very limited attempts on tackle this problem in the literature. In this paper, we propose a new neighborhood repulsed metric learning (NRML) method for kinship verification. Motivated by the fact that interclass samples (without a kinship relation) with higher similarity usually lie in a neighborhood and are more easily misclassified than those with lower similarity, we aim to learn a distance metric under which the intraclass samples (with a kinship relation) are pulled as close as possible and interclass samples lying in a neighborhood are repulsed and pushed away as far as possible, simultaneously, such that more discriminative information can be exploited for verification. To make better use of multiple feature descriptors to extract complementary information, we further propose a multiview NRML (MNRML) method to seek a common distance metric to perform multiple feature fusion to improve the kinship verification performance. Experimental results are presented to demonstrate the efficacy of our proposed methods. Finally, we also test human ability in kinship verification from facial images and our experimental results show that our methods are comparable to that of human observers.
DECISION SCIENCES INSTITUTE

This study applies the cultural fit perspective to examine effectiveness of quality management practices. It reviews the literatures on quality management practices and organizational culture, particularly the competing values framework. Eight propositions have been articulated with respect to how QM practices fit organizational cultural characteristics and how the good fit can achieve positive outcomes. Their implications for theory and practice have been discussed in the paper.
DECISION SCIENCES INSTITUTE

Supply chain management requires companies to develop multiple capabilities to reduce operations uncertainties and obtain sustainable competitive advantages. This study investigates the impacts of Just-in-time (JIT) and supply chain integration (SCI) on companies’ performance, and the mechanism between JIT and SCI. Our findings reveal that JIT to supplier (JITS) can improve cost and innovation performance, while customer integration (CI) can only improve innovation performance. Through supplier integration (SI) does not directly impact on each performance, it positively relates to cost and innovation performance through improving JITS. Our findings can enrich JIT and SCI knowledge academically and practically.
DECISION SCIENCES INSTITUTE

Reshoring and offshoring have been investigated separately by the literature, undermining a deeper comprehension of the firms’ international expansion paths. Our paper seeks to fill this gap by: identifying common pattern in offshoring and reshoring initiatives; understanding the interdependencies among offshoring and reshoring motivations; and exploring whether reshoring is a “failure” of the offshoring initiative, or rather an evolution of the firm’s strategy. We review literature on offshoring and reshoring motivations and conduct a multiple-case study analysis. This allows us to discuss how the motivations (Why) connect with the How (governance modes), and Where (geographical locations) of offshoring and reshoring.
DECISION SCIENCES INSTITUTE

In this paper, we propose a drug demand forecasting system for regional pharmacy chain stores. Drugs are categorized into three types based on the amount of available historical data and on regularity, namely, new products, non-seasonal long-term products, and seasonal long-term products. Grey forecasting method and time-series methods including moving average, exponential smoothing, and autoregressive integrated moving average are applied in the system. Moreover, we discuss whether the model and parameters should be reconstructed when new demand data are updated. Finally, the forecasting system are examined with real data and the results indicate that the proposed forecasting system can determine a suitable model for predicting demand accurately.
A Text Mining Technique Using Association Rules Extraction

— This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TF-IDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), A ssociation Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.
A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling

Job shop scheduling, as one of the classical scheduling problems, has been widely studied in literatures, and proved to be mostly NP-hard. Although it is extremely difficult to solve job shop scheduling with no-wait constraint to optimality, the two-machine no-wait job shop scheduling to minimise makespan could be solvable in polynomial time when each job has exactly two equal length operations (proportionate job shop). In the present paper, an extension is attempted by considering a proportionate flexible two-stage no-wait job shop scheduling problem with minimum makespan, and a set-covering formulation is put forward which contains a master problem and a pricing problem. To solve this problem, a column generation (CG)-based approach is implemented. In comparison, a mixed integer programming model is constructed and optimised by Cplex. A series of randomly generated numerical instances are calculated. And the testing result shows that the mixed integer model handled by Cplex can only solve small scale cases, while the proposed CG-based method can conquer larger size problems in acceptable time.
Dendrites decrease the synaptic weight resolution necessary to compute

In theory, neurons can compute all threshold functions, but in practice, synaptic weight resolution limits their computing capacity. Here, we study how dendrites alleviate this practical limitation by demonstrating a computation where dendrites considerably decrease the necessary synaptic weights resolution. We show how a biophysical neuron model with two passive dendrites and a soma that can implement this computation more eﬃciently than a point neuron. The latter requires synaptic weight orders of magnitudes larger than the others, the former implement the computation with equivalent synaptic weights. This work paves the way for a new generation of neuromorphic chips composed of dendritic neurons. These chips will require less space and less energy to function.
Exact minimum-width transistor placement without dual constraint for CMOS cells

This paper proposes flat and hierarchical approaches for generating a minimum-width transistor placement of CMOS cells in presence of non-dual P and N type transistors. Our approaches are the first exact method which can be applied to CMOS cells with any types of structure. We formulate the transistor placement problem into Boolean Satisfiability (SAT) problem considering the P and N type transistors individually. The experimental results show that our flat approach generates smaller width placement for 29 out of 103 dual cells than that of the conventional method, and the width of only 3 out of 147 cells solved by our hierarchical approach are larger than that of the flat approach. Using the hierarchical approach, 81% of 340 cells in an industrial standard-cell library of 90 nm technology are solved within one hour for each cell, whereas 32% using the conventional exact method.
Memristive Devices and Networks for Brain‐Inspired Computing

As the era of big data approaches, conventional digital computers face increasing difficulties in performance and power efficiency due to their von Neumann architecture. As a result, there is recently a tremendous upsurge of investigations on brain‐inspired neuromorphic hardware with high parallelism and improved efficiency. Memristors are considered as promising building blocks for the realization of artificial synapses and neurons and can therefore be utilized to construct hardware neural networks. Here, a review is provided on existing approaches for the implementation of artificial synapses and neurons based on memristive devices; and the respective advantages and disadvantages of these approaches are evaluated. This is followed by a discussion of hardware accelerators and neuromorphic computing systems that exploit the parallel, in‐memory and analog characteristics of memristive crossbar arrays as well as the intrinsic dynamics of memristors. Finally, the outstanding challenges are addressed that have not yet been resolved in the present studies, and future advances are discussed that might be needed for building intelligent and energy efficient neuromorphic systems.
Model simulations of ion and electron density profiles in ionospheric E and F regions

We develop a time‐dependent theoretical numerical model to simulate the density profiles of the ions (i.e., O+(2P), O+(2D), N2+, O+(4S), N+, O2+, and NO+) and free electrons in E and F regions. In this model, the ion photoionization production rates, the photoelectron ionization production effect, and the chemical reactions between the ionized species and the neutral compositions are considered, and the plasma transport processes are not included. The simulation results show that the mean electron density ratios of the model simulations to the AE‐C satellite measurements for the Solar Dynamics Observatory‐Extreme Ultraviolet Variability Experiment (SDO‐EVE), EUV flux model for Aeronomic Calculations, and Hinteregger‐Fukui‐Gilson solar irradiance models are, respectively, 0.97, 0.79, and 0.71 in a height range 140–400 km and 0.79, 0.75, and 0.64 in a height range 90–150 km. A comparison shows that the electron densities simulated by the model developed in this study are much more consistent with the in situ measurements made by the AE‐C satellite than those predicted by the International Reference Ionosphere model and simulated by the Thermosphere Ionosphere Electrodynamics General Circulation Model. The model simulations with SDO‐EVE solar irradiance input indicate that the photoelectron impact production process contributes about 20%–30% of the total atomic ion densities throughout the height range 130–400 km around noon. However, the photoelectron production effect on the molecular ion densities is very minor (less than about 7%) above 275 km. Below 250 km, its effect increases with the decrease of height for O2+ and N2+, from about 4% and 10% at 250 km to 13% and 27% at 150 km, respectively.
Random walks of circle packings

A notion of random walks for circle packings is introduced. The geometry behind this notion is discussed, together with some applications. In particular, we obtain a short proof of a result regarding the type problem for circle packings, which shows that the type of a circle packing is closely related to the type of its tangency graph.