General Knapsack Problems in a Dynamic Setting

The world is dynamic and changes over time, so any optimization problems must address this dynamic nature . In the multistage model we are given aseries of instance of an optimization problem, and a solution is provided foreach instance . The strive for continuous and similar solutions over time are quantified and integrated into the objective function .…

Tamper Detection against Unitary Operators

Quantum tamper-detection codes are quantum generalizations of classical tamper detection codes studied by Jafargholi et al. They must detect that tampering occurred with high probability. In case there was no tampering, we would like to output the message $m$ with a probability of$1 .…

Optimal heating of an indoor swimming pool

This work presents the derivation of a model for the heating process of the air of a glass dome, where an indoor swimming pool is located in the bottom of the dome . The problem can be reduced from a three-dimensional to a twodimensional one .…

UniGNN a Unified Framework for Graph and Hypergraph Neural Networks

UniGNN is a unified framework for interpreting the messagepassing process in graph and hypergraph neural networks, which can generalize general GNN models into hypergraphs . Extensive experiments have been conducted to demonstratethe effectiveness of UniGnn on multiple real-world datasets, which outperform the state-of-the-art approaches with a large margin .…

Reversible cellular automata in presence of noise rapidly forget everything

We consider reversible and surjective cellular automata perturbed with noise . We show that in the presence of positive additive noise, the cellularautomaton forgets all the information regarding its initial configurationexponentially fast . In particular, the state of a finite collection of cellswith diameter n becomes indistinguishable from pure noise after O(log n) timesteps .…

Metaphor Research in the 21st Century A Bibliographic Analysis

This paperexamines the advancements in metaphor research from 2000 to 2017 . Using dataretrieved from Microsoft Academic Graph and Web of Science, this paper makes amacro analysis of metaphor research, and expounds the underlying patterns ofits development . This paper provides novel insights into the current state of the art ofmetaphor research as well as future trends in this field, which may spark new research interests in metaphor from both linguistic and interdisciplinaryperspectives .…

A Machine Learning Based Ensemble Method for Automatic Multiclass Classification of Decisions

Stakeholders make various types of decisions with respect to requirements, design, management, and so on during the software development life cycle . These decisions are typically not well documented and classified due to limited human resources, time, and budget . In this paper, we aimed at automaticallyclassifying decisions into five types to help stakeholders better document and understand decisions .…

High order space time finite element methods for the Poisson Nernst Planck equations Positivity and unconditional energy stability

We present a novel class of high-order space-time finite element schemes for the Poisson-Nernst-Planck (PNP) equations . We prove that our schemes are massconservative, positivity preserving, and unconditionally energy stable for any order of approximation . This is the first class of (arbitrarily) high order accurate schemes for PNP equations that simultaneously achieve all these three properties .…

Explaining how your AI system is fair

To implement fair machine learning in a sustainable way, choosing the rightfairness objective is key . The most appropriate fairness definition for an artificial intelligence system is a matter of ethical standards and legal requirements . In thisposition paper, we propose to use a decision tree as means to explain andjustify the implemented kind of fairness to the end users .…

Multi agent consensus with heterogeneous time varying input and communication delays in digraphs

This paper investigates the distributed consensus tracking control problem for general linear multi-agent systems (MASs) with external disturbances andheterogeneous time-varying input and communication delays . An extended LMI is proposed which, in conjunction with the rest of the LMIs, results in a solution with a larger upper bound on delays than what would befeasible without it .…

An Efficient and Secure Location based Alert Protocol using Searchable Encryption and Huffman Codes

Location data are widely used in mobile apps, ranging from location-basedrecommendations, to social media and navigation . But serious privacy concerns arise if users share their locationhistory with the service provider in plaintext . The underlying searchable encryption primitives required to perform the matching on ciphertexts are expensive, and without a proper encoding oflocations and search predicates, the performance can degrade a lot .…

Formalizing the Four layer Metamodeling Stack Potential and Benefits

Enterprise modeling deals with the increasing complexity of processes and systems by operationalizing model content and by linking complementary modelsand languages . To enable this amplification and turn models intocomputer-processable structures a comprehensive formalization is needed . Thispaper presents a generic formalism based on typed first-order logic and provides a perspective on the potential and benefits arising for a variety of research issues in conceptual modeling .…

Abstract clones for abstract syntax

Abstract clonestraditionally describe first-order structures, but by equipping them with algebraic structure, one can further axiomatize second-order, variable-binding operators . We give a construction of free algebras and derive acorresponding induction principle . This provides a syntax-independent representation of simple type theories, such as the simply-typed $\lambda$-calculus, using the framework of abstract clones .…

Tubal Matrix Analysis

The $2$-norm of a tubal matrix is equal to its largest T-singular value, multiplied with a coefficient, which is $1$ in the case of matrices . Further study on tubal matrices may reveal more links between matrix theory and tensor theory .…

Security Properties for Stack Safety

“stack safety” is associated with avariety of compiler, run-time, and hardware mechanisms for protecting stackmemory . We propose a formal characterization of stack safety, formulated with concepts from language-based security . We use these properties to validatethe stack-safety “micro-policies” proposed by Roessler and DeHon [2018].…

Cross Modal Self Attention with Multi Task Pre Training for Medical Visual Question Answering

Existing methods of medical visual question answering usually rely on transfer learning to obtain effective image feature representation . We introduce a cross-modal self-attention module to capture the long-range contextual relevance for more effectivefusion of visual and linguistic features . Experimental results demonstrate that the proposed method outperforms existing state-of-the-art methods .…

QDOT Quantized Dot Product Kernel for Approximate High Performance Computing

Error sensitive applications in high-performance computing are unable to benefit from existing approximatecomputing strategies that are not developed with guaranteed error bounds . Using qdot for the dot products in CG can result in amajority of components being perforated or quantized to half precision withoutincreasing the iteration count required for convergence to the same solution as CG using a double precision dot product .…

CARL DTN Context Adaptive Reinforcement Learning based Routing Algorithm in Delay Tolerant Network

Delay/Disruption-Tolerant Networks (DTN) invented to describe and cover all types of long-delay, disconnected, intermittently connected networks . The term is characterized by frequent network partitioning, intermittentconnectivity, large or variable delay, asymmetric data rate, and low transmission reliability . In DTNthere is a trade-off off between delivery ratio and overhead .…

Model Checking Quantum Continuous Time Markov Chains

A real-time system, we specify the temporal properties on QCTMC by signal temporal logic (STL) To effectivelycheck the atomic propositions in STL, we develop a state-of-art real rootisolation algorithm under Schanuel’s conjecture . Further, we check the generalSTL formula by interval operations with a bottom-up fashion, whose querycomplexity turns out to be linear in the size of the input formula by calling the real root isolation algorithm .…

Lecture Notes on Voting Theory

Lectures were developed for the course Computational SocialChoice of the Artificial Intelligence MSc programme at the University of Groningen . They cover mathematical and algorithmic aspects of voting theory .…

AI Assisted MAC for Reconfigurable Intelligent Surface Aided Wireless Networks Challenges and Opportunities

Recently, significant research attention has been devoted to the study ofreconfigurable intelligent surfaces (RISs) RISs are capable of reconfiguring the wireless propagation environment by exploiting the unique properties ofmetamaterials-based integrated large arrays of inexpensive antennas . The medium access control (MAC) of multiple usersaccessing an RIS-enabled channel is still in its infancy, while many open issues remain to be addressed .…

OR Net Pointwise Relational Inference for Data Completion under Partial Observation

Current methods fail to perceive datarelativity under partial observation . Omni-Relational Network (OR-Net) to model the pointwise relativity in two aspects . It is demonstrated that the proposed OR-Net can be wellgeneralized for data completion tasks of various modalities, including functionregression, image completion on MNIST and CelebA datasets, and also sequentialmotion generation conditioned on the observed poses .…

GODSAC Graph Optimized DSAC for Robot Relocalization

Deep learning based camera pose estimation from monocular camera images has a recent uptake in Visual SLAM research . GODSAC* outperforms the state-of-the-artapproaches in pose estimation accuracy, as we demonstrate in our experiments . The approach augments posepredictions from a trained neural network with noisy odometry data through theoptimization of a pose graph .…

Dialectica models of type theory

We present two Dialectica-like constructions for models of intensionalMartin-L\”of type theory . We propose a new semantic notion of finite sum for dependent types, generalizingfinitely-complete extensive categories . The second avoids extensivityassumptions using biproducts in a Kleisli category for a fibred additive monad .…

Paradiseo From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics 22 Years of Paradiseo

ParadisEO is a comprehensive C++ freesoftware which targets the development of modular metaheuristics . It is of prior importance to have access to mature and flexible software frameworks which allow for an efficient exploration of the algorithm design space . This articlesummarizes the features of the framework, a highly modular architecture, a large set of components, speed of execution and automated algorithm design features, which are key to modern approaches to metaheiristics development .…

Data Driven Model Order Reduction for Problems with Parameter Dependent Jump Discontinuities

We propose a data-driven model order reduction (MOR) technique for partial differential equations that exhibit parameter-dependentjump-discontinuities . We build upon themethodology of approximating the map between the parameter domain and theexpansion coefficients of the reduced basis via regression . The online stagequeries the regression model for the expansion coefficients and recovers areduced approximation for the solution .…

Synthesizing Abstract Transformers

This paper addresses the problem of creating abstract transformersautomatically . The method we present provides the basis for creating a tool toautomate the construction of program analyzers in a fashion similar to the wayyacc automates parsers . We used it to create a set of replacement abstracttransformers for those used in an existing analyzer, and obtained essentially identical performance .…

Probabilistic Analysis of Operating Modes in Cache Enabled Full Duplex D2D Networks

Cache-enabled Device-to-Device (D2D) communication is one of the key enablers of the fifth generation (5G) cellular network . But conventional half-duplex(HD) communication may not be sufficient to provide fast enough content delivery over D2D links . In-band full-duple (FD) can provide more content deliveryopportunities, thus resulting improved spectral efficiency and latency reduction .…