Topology Optimization Methods for 3D Structural Problems A Comparative Study

The work provides an exhaustive comparison of some representative families of topology optimization methods for 3D structural optimization, such as the SolidIsotropic Material with Penalization (SIMP), the Level-set, the BidirectionalEvolutionary Structural Optimization (BESO), and the Variational TopologyOptimization (VARTOP) methods . The main differences and similarities of these approaches are highlighted from an algorithmic standpoint .…

JOET Sustainable Vehicle assisted Edge Computing for Internet of Vehicles

Task offloading in Internet of Vehicles involves numerous steps andoptimization variables such as: where to offload tasks, how to allocate resources and how to adjust offloading ratio and transmit power for offloading . In this paper, we provide a Mixed Integer NonlinearProgramming Problem (MINLP) formulation for such task offloading under energyand deadline constraints in IoV.…

Association between productivity and journal impact across disciplines and career age

The association between productivity and impact of scientific production is controversial and poorlyunderstood . We present a large-scale analysis of the association between publication numbers and average journal-impact metrics for the Brazilianscientific elite . We find this association to be discipline-specific, career-age dependent, and similar among researchers with outlier andnon-outlier performance .…

JOET Sustainable Vehicle assisted Edge Computing for Internet of Vehicles

Task offloading in Internet of Vehicles involves numerous steps andoptimization variables such as: where to offload tasks, how to allocate resources and how to adjust offloading ratio and transmit power for offloading . In this paper, we provide a Mixed Integer NonlinearProgramming Problem (MINLP) formulation for such task offloading under energyand deadline constraints in IoV.…

RIS assisted UAV Communications for IoT with Wireless Power Transfer Using Deep Reinforcement Learning

Many of the devices used in Internet-of-Things (IoT) applications are energy-limited . supplying energy while maintaining seamless connectivity for IoT devices is of considerable importance . We propose a simultaneous wireless power transfer and information transmissionscheme . We jointly optimize the trajectory ofthe UAV, the energy harvesting scheduling of IoT devices, and the phaseshiftmatrix of the RIS .…

Topology Optimization Methods for 3D Structural Problems A Comparative Study

The work provides an exhaustive comparison of some representative families of topology optimization methods for 3D structural optimization, such as the SolidIsotropic Material with Penalization (SIMP), the Level-set, the BidirectionalEvolutionary Structural Optimization (BESO), and the Variational TopologyOptimization (VARTOP) methods . The main differences and similarities of these approaches are highlighted from an algorithmic standpoint .…

Topology Optimization Methods for 3D Structural Problems A Comparative Study

The work provides an exhaustive comparison of some representative families of topology optimization methods for 3D structural optimization, such as the SolidIsotropic Material with Penalization (SIMP), the Level-set, the BidirectionalEvolutionary Structural Optimization (BESO), and the Variational TopologyOptimization (VARTOP) methods . The main differences and similarities of these approaches are highlighted from an algorithmic standpoint .…

JOET Sustainable Vehicle assisted Edge Computing for Internet of Vehicles

Task offloading in Internet of Vehicles involves numerous steps andoptimization variables such as: where to offload tasks, how to allocate resources and how to adjust offloading ratio and transmit power for offloading . In this paper, we provide a Mixed Integer NonlinearProgramming Problem (MINLP) formulation for such task offloading under energyand deadline constraints in IoV.…

Quantum Meets the Minimum Circuit Size Problem

Minimum Circuit Size Problem (MCSP) is a problem to compute the circuitcomplexity of Boolean functions . MCSP is a fascinating problem in complexitytheory—its hardness is mysterious, and a better understanding of its hardness could have surprising implications to many fields in computer science .…

Variational approach to relaxed topological optimization closed form solutions for structural problems in a sequential pseudo time framework

The work explores a specific scenario for structural computational computationaloptimization based on the following elements: (a) a relaxed optimizationsetting considering the ersatz (bi-material) approximation, (b) a treatment based on a nonsmoothed characteristic function field as a topological design variable, (c) the consistent derivation of a relaxed topological derivative whose determination is simple, general and efficient, (d) formulation of theoverall increasing cost function topological sensitivity as a suitableoptimality criterion, and (e) consideration of a pseudo-time framework for the solution, ruled by the problem constraint evolution .…

The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies

Algorithmic risk assessment instruments (RAIs) are increasingly adopted to assist decision makers . However, researchers have come to recognize that assessing theirimpact requires understanding their human interactants . In a vignette study, laypersons are tasked with predicting future re-arrests . Participants do not anchor on the RAI’s predictions, and Judicialdecisions, unlike participants’ predictions, depend in part on factors that areorthogonal to the likelihood of re arrest .…

Variational approach to relaxed topological optimization closed form solutions for structural problems in a sequential pseudo time framework

The work explores a specific scenario for structural computational computationaloptimization based on the following elements: (a) a relaxed optimizationsetting considering the ersatz (bi-material) approximation, (b) a treatment based on a nonsmoothed characteristic function field as a topological design variable, (c) the consistent derivation of a relaxed topological derivative whose determination is simple, general and efficient, (d) formulation of theoverall increasing cost function topological sensitivity as a suitableoptimality criterion, and (e) consideration of a pseudo-time framework for the solution, ruled by the problem constraint evolution .…

Generation of High Order Coarse Quad Meshes on CAD Models via Integer Linear Programming

We propose an end-to-end pipeline to robustly generate high-quality,high-order and coarse quadrilateral meshes on CAD models . This kind of meshenables the use of high-order analysis techniques such as high order finiteelement methods or isogeometric analysis . Validation on several CAD models shows that our approach is fast,robust, strictly respects the CAD features, and achieves interesting results interms of coarseness and quality .…

Four Valued Semantics for Deductive Databases

In this paper, we introduce a novel approach to deductive databases meant totake into account the needs of current applications in the area of dataintegration . We extend the formalism of standard deductivedatabases to the context of Four-valued logic so as to account for unknown,inconsistent, true or false information under the open world assumption .…

Geometric Embeddability of Complexes is exists mathbb R complete

We show that the decision problem of determining whether a given (abstractsimplicial) $k$-complex has a geometric embedding in $\mathbb R^d$ is complete for the Existential Theory of the Reals for all $d\geq 3$ and $k\in\{d-1,d\}$. This implies that the problem is polynomial time equivalent to determiningwhether a polynomorphic equation system has a real root .…

Generation of High Order Coarse Quad Meshes on CAD Models via Integer Linear Programming

We propose an end-to-end pipeline to robustly generate high-quality,high-order and coarse quadrilateral meshes on CAD models . This kind of meshenables the use of high-order analysis techniques such as high order finiteelement methods or isogeometric analysis . Validation on several CAD models shows that our approach is fast,robust, strictly respects the CAD features, and achieves interesting results interms of coarseness and quality .…

Next Gen Gas Network Simulation

To overcome many-query optimization, control, or uncertainty quantification work loads in reliable gas and energy network operations, model order reduction is the mathematical technology of choice . To this end, we enhance the model,solver and reductor components of the “morgen” platform, introduced in Himpe etal, to this end .…

Next Gen Gas Network Simulation

To overcome many-query optimization, control, or uncertainty quantification work loads in reliable gas and energy network operations, model order reduction is the mathematical technology of choice . To this end, we enhance the model,solver and reductor components of the “morgen” platform, introduced in Himpe etal, to this end .…

Generation of High Order Coarse Quad Meshes on CAD Models via Integer Linear Programming

We propose an end-to-end pipeline to robustly generate high-quality,high-order and coarse quadrilateral meshes on CAD models . This kind of meshenables the use of high-order analysis techniques such as high order finiteelement methods or isogeometric analysis . Validation on several CAD models shows that our approach is fast,robust, strictly respects the CAD features, and achieves interesting results interms of coarseness and quality .…

Generation of High Order Coarse Quad Meshes on CAD Models via Integer Linear Programming

We propose an end-to-end pipeline to robustly generate high-quality,high-order and coarse quadrilateral meshes on CAD models . This kind of meshenables the use of high-order analysis techniques such as high order finiteelement methods or isogeometric analysis . Validation on several CAD models shows that our approach is fast,robust, strictly respects the CAD features, and achieves interesting results interms of coarseness and quality .…

Next Gen Gas Network Simulation

To overcome many-query optimization, control, or uncertainty quantification work loads in reliable gas and energy network operations, model order reduction is the mathematical technology of choice . To this end, we enhance the model,solver and reductor components of the “morgen” platform, introduced in Himpe etal, to this end .…

Implementing the BBE Agent Based Model of a Sports Betting Exchange

Bristol BettingExchange is a new agent-based model that simulates a contemporary sports-betting exchange, such as those offered commercially by companies such as Betfair, Smarkets, and Betdaq . It is aimed at producing synthetic data for in-play betting (also known as in-race or in-game betting) where bettors can place bets on the outcome of a track-race event after the race has started and for as long as the race is underway, with bets only ceasing when the race ends .…

Q error Bounds of Random Uniform Sampling for Cardinality Estimation

Random uniform sampling has been studied in various statistical tasks but few have covered the Q-error metric for cardinality estimation (CE) In this paper, we analyze the confidence intervals of random uniform sampling withand without replacement for single-table CE . Results indicate that the upperQ-error bound depends on the sample size and true cardinality .…

Variational approach to relaxed topological optimization closed form solutions for structural problems in a sequential pseudo time framework

The work explores a specific scenario for structural computational computationaloptimization based on the following elements: (a) a relaxed optimizationsetting considering the ersatz (bi-material) approximation, (b) a treatment based on a nonsmoothed characteristic function field as a topological design variable, (c) the consistent derivation of a relaxed topological derivative whose determination is simple, general and efficient, (d) formulation of theoverall increasing cost function topological sensitivity as a suitableoptimality criterion, and (e) consideration of a pseudo-time framework for the solution, ruled by the problem constraint evolution .…

A Longitudinal Multi modal Dataset for Dementia Monitoring and Diagnosis

Dementia is a family of neurogenerative conditions affecting memory and cognition in an increasing number of individuals in our globally aging population . Automated analysis of language, speech and paralinguisticindicators have been gaining popularity as potential indicators of cognitivedecline . Here we propose a novel longitudinal multi-modal dataset collected from people with mild dementia and age matched controls over a period ofseveral months in a natural setting .…

High Performance Uncertainty Quantification with Parallelized Multilevel Markov Chain Monte Carlo

Numerical models of complex real-world phenomena often necessitate HighPerformance Computing . We present a parallelization strategy for multilevel Markov chain MonteCarlo, a state-of-the-art, algorithmically scalable Uncertainty Quantification(UQ) algorithm for Bayesian inverse problems . The main scalability challenge presents itself in the form of strong data dependencies introduced by the MLMCMC method, prohibitingtrivial parallelization .…

High Performance Level 1 and Level 2 BLAS

The introduction of the Basic Linear Algebra Subroutine (BLAS) in the 1970s paved the way for different libraries to solve the same problem with animproved approach and hardware . The new BLAS implementation led to high-Performance Computing (HPC) innovation . We rely on the FMA instruction, OpenMP, and the compiler tooptimize the code rather than implementing the algorithm in assembly .…

From Analogue Science to AI powered Digital Science

Phase transition from the human-limited, “analogue” way of research enquiry to the silicon-based, artificial intelligence (AI)-powered digital science isforthcoming . To facilitate this transition, I propose three project ideas: 1)CryptoScience platform, aimed to provide tools for endemic digitalization &open access of the research data .…

A FAIR and AI ready Higgs Boson Decay Dataset

Researchers aim to create scientific datasets that adhere to the principles of findability, accessibility, interoperability, and reusability(FAIR) for data and artificial intelligence (AI) models . This article provides a domain-agnostic, step-by-step assessment guide to evaluate whether or not agiven dataset meets each FAIR principle .…