Who Owns the Data A Systematic Review at the Boundary of Information Systems and Marketing

This paper gives a systematic research review at the boundary of theinformation systems (IS) and marketing disciplines . The citation asymmetries between IS and marketing are noted and an overall conceptual model is created . Forwardlooking suggestions are made on how academic researchers can better interfacewith industry and how academic research at the boundaries of IS can be further developed .…

Resilience of Well structured Graph Transformation Systems

Resilience is a concept of rising interest in computer science and software engineering . For systems in which correctness w.r.t. a safety condition is impossible, fast recovery is demanded . We investigate resilience problems ofgraph transformation systems . Our main contribution is the decidability of tworesilience problems for well-structured graph transformation systems (withstrong compatibility)…

Who Owns the Data A Systematic Review at the Boundary of Information Systems and Marketing

This paper gives a systematic research review at the boundary of theinformation systems (IS) and marketing disciplines . The citation asymmetries between IS and marketing are noted and an overall conceptual model is created . Forwardlooking suggestions are made on how academic researchers can better interfacewith industry and how academic research at the boundaries of IS can be further developed .…

Who Owns the Data A Systematic Review at the Boundary of Information Systems and Marketing

This paper gives a systematic research review at the boundary of theinformation systems (IS) and marketing disciplines . The citation asymmetries between IS and marketing are noted and an overall conceptual model is created . Forwardlooking suggestions are made on how academic researchers can better interfacewith industry and how academic research at the boundaries of IS can be further developed .…

Towards Semantic Interoperability in Historical Research Documenting Research Data and Knowledge with Synthesis

A vast area of research in historical science concerns the documentation and study of artefacts and related evidence . Current practice mostly usesspreadsheets or simple relational databases to organise the information as rowswith multiple columns of related attributes . Synthesis documentationsystem is Web-based andcollaborative, and makes use of existing standards for informationdocumentation and publication (CIDOC-CRM, RDF), focusing on semanticinteroperability and the production of data of high value and long-termvalidity .…

Rate Independent Computation in Continuous Chemical Reaction Networks

Chemical reaction networks are formalized as chemical reaction networks (CRNs) Despite widespread use of CRNs in the natural sciences, the range of computational behavior exhibited by CRNs is not well understood . Understanding the algorithmic behaviors that are *in principle* realizable in a chemical system is necessary for a rigorous understanding of the designprinciples of biological regulatory networks .…

Counterexample Classification

In model checking, when a given model fails to satisfy the desiredspecification, a typical model checker provides a counterexample that shows how the violation occurs . In general, there exist many diversecounterexamples that exhibit distinct violating behaviors . The goal of classification is to partition thespace of all countereXamples into a finite set of classes, each of which describes a distinct type of violating behavior for the givenspecification .…

Quantum Annealing Algorithms for Boolean Tensor Networks

Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality solutions of NP-hard problems . In this contribution, we explore the potential and effectiveness of such quantumanneals for computing Boolean tensor networks . We show that tensor with up to millions of elements can bedecomposed efficiently using a DWave 2000Q adiabatic quantum annealer .…

Bottom Up Derivatives of Tree Expressions

In this paper, we extend the notion of (word) derivatives and partialderivatives due to (respectively) Brzozowski and Antimirov to tree derivatives . We define a new family of extended regular tree expressions (using negationor intersection operators) We show how to compute a Brozozowski-likeinductive tree automaton .…

Accelerated Multiple Precision Direct Method and Mixed Precision Iterative Refinement on Python Programming Environment

Current Python programming environment does not have any reliable and efficient multiple precision floating-point arithmetic . MPF library can be utilized for middlelength precision arithmetic under 200 bits, but they are not widely used on Python . In this paper, we describe our accelerated MPF direct method withAVX2 techniques and its application to mixed precision iterative refinement combined with mpmath, and demonstrate their efficiency on x86\_64 computational environments .…

Accelerated Multiple Precision Direct Method and Mixed Precision Iterative Refinement on Python Programming Environment

Current Python programming environment does not have any reliable and efficient multiple precision floating-point arithmetic . MPF library can be utilized for middlelength precision arithmetic under 200 bits, but they are not widely used on Python . In this paper, we describe our accelerated MPF direct method withAVX2 techniques and its application to mixed precision iterative refinement combined with mpmath, and demonstrate their efficiency on x86\_64 computational environments .…

Bibliometric Profile of Nursing Research in Ex Yugoslavian Countries

Slovenia was the most productive country, followed byCroatia and Serbia . Nursing research in ex-Yugoslavian countries is growing both in scope and number of publications . A substantial part of the research is published in national journalsin national languages . The study also revealed substantial international cooperation among ex-yugoslavians and European Union.…

MLDev Data Science Experiment Automation and Reproducibility Software

In this paper we explore the challenges of automating experiments in datascience . We propose an extensible experiment model as a foundation forintegration of different open source tools for running research experiments . Weimplement our approach in a prototype open source MLDev software package andevaluate it in a series of experiments yielding promising results .…

Logics Meet 2 Way 1 Clock Alternating Timed Automata

In this paper, we study the extension of 1-clock Alternating Timed Automata(1-ATA) with the ability to read in both forward and backward direction . We propose a “non-punctuality” like restriction,called non-adjacency, for 2-Way 1-ATA-rfl, and also for GQMSO, for which theemptiness (respectively, satisfiability) checking becomes decidable, in general .…

MLDev Data Science Experiment Automation and Reproducibility Software

In this paper we explore the challenges of automating experiments in datascience . We propose an extensible experiment model as a foundation forintegration of different open source tools for running research experiments . Weimplement our approach in a prototype open source MLDev software package andevaluate it in a series of experiments yielding promising results .…

Reradiation and Scattering from a Reconfigurable Intelligent Surface A General Macroscopic Model

Reconfigurable Intelligent Surfaces (RISs) have attracted attention in the last year for their characteristics of nearly-passive, thin structures that candynamically change their reflection or refraction behaviour . In this paper, we introduce a general macroscopic model for therealistic evaluation of RIS scattering, based on its decomposition intomultiple scattering mechanisms and aimed at being embedded into ray models .…

Hyperbolic Diffusion in Flux Reconstruction Optimisation through Kernel Fusion within Tensor Product Elements

Novel methods are presented for the fusion of GPU kernels in the artificialcompressibility method (ACM) The fused kernels are able to achieve 3-4 times speedup, which compares favourably with atheoretical maximum speedup of 4.3 times . In three dimensional test cases, thegenerated fused kernels were found to reduce total runtime by ${\sim}25\%$, and,when compared to the standard ACM formulation, simulations demonstrate that aspeedup of $2.3$ times can be achieved .…

Hyperbolic Diffusion in Flux Reconstruction Optimisation through Kernel Fusion within Tensor Product Elements

Novel methods are presented for the fusion of GPU kernels in the artificialcompressibility method (ACM) The fused kernels are able to achieve 3-4 times speedup, which compares favourably with atheoretical maximum speedup of 4.3 times . In three dimensional test cases, thegenerated fused kernels were found to reduce total runtime by ${\sim}25\%$, and,when compared to the standard ACM formulation, simulations demonstrate that aspeedup of $2.3$ times can be achieved .…

Logical Characterization of Coherent Uninterpreted Programs

An uninterpreted program (UP) is a program whose semantics is defined over the theory of uninterpretated functions . This is a common abstraction used inequivalence checking, compiler optimization, and program verification . Recently, a class of UP programs, called coherent, has been proposed and shown to be decidable .…

A 51 3 TOPS W 134 4 GOPS In memory Binary Image Filtering in 65nm CMOS

Neuromorphic vision sensors (NVS) can enable energy savings due to theirevent-driven that exploits the temporal redundancy in video streams from astationary camera . Noise-driven events lead to the false triggering of the object recognition processor . Image denoise operations require memoryintensive processing leading to a bottleneck in energy and latency .…

Caveats for the use of Web of Science Core Collection in old literature retrieval and historical bibliometric analysis

This research note tries to uncover the 1991 phenomenon from theperspective of database limitation by probing the limitations of search inabstract/author keywords/keywords plus fields of Web of Science Core Collection . The lowavailability rates of abstract/author keyword searches in WoSCC found in this study can explain the “watershed” phenomenon of AIscholarship in 1991 to a large extent .…

Score Based Point Cloud Denoising

Point clouds acquired from scanning devices are often perturbed by noise, which affects downstream tasks such as surface reconstruction and analysis . To denoise a noisy point cloud, we propose to increase the log-likelihood of each point from $p *n$ via gradient ascent .…

MCDAL Maximum Classifier Discrepancy for Active Learning

Recent state-of-the-art active learning methods have mostly leveragedGenerative Adversarial Networks (GAN) for sample acquisition . However, GAN isusually known to suffer from instability and sensitivity to hyper-parameters . In contrast to these methods, we propose in this paper a novel active learningframework that we call Maximum Classifier Discrepancy for Active Learning(MCDAL) which takes the prediction discrepancies between multiple classifiers .…

Dynamic Proximal Unrolling Network for Compressive Sensing Imaging

CompressiveSensing Imaging (CSI) is a challenging problem and has many practical applications . Deep neural networks have been applied to this problem with promising results . But existing neural network approaches require separate models for each imaging parameter like sampling ratios, leading totraining difficulties and overfitting to specific settings .…

Pruning Ternary Quantization

The method significantly compressesneural network weights to a sparse ternary of [-1,0,1 . It can compress aResNet-18 model from 46 MB to 955KB and a ResNet-50 model from 99 MB to 3.3MB (~30x) The top-1 accuracy on ImageNet drops slightly from 69.7% to65.3% and from 76.15% to 74.47% .…

Domain Adaptive Video Segmentation via Temporal Consistency Regularization

DA-VSN is a domain adaptive video segmentation network that addresses domain gaps in videos by temporal consistency regularization (TCR) for consecutive frames of target-domain videos . The network is based on cross-domain TCR that guides the prediction of target frames to have similar temporal consistency as that of source frames (learnt from annotated source data) viaadversarial learning .…

Detail Preserving Residual Feature Pyramid Modules for Optical Flow

Feature pyramids and iterative refinement have recently led to great progress in optical flow estimation . However, downsampling in feature pyramids can cause blending of foreground objects with background . We propose anovel Residual Feature Pyramid Module (RFPM) which retains important details inthe feature map without changing the overall design of the overall iterative .…

Resource Efficient Mountainous Skyline Extraction using Shallow Learning

Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented realityapplications . We present a novel mountainous skyline detection approach wherewe adapt a shallow learning approach to learn a set of filters to discriminate between edges belonging to sky-mountain boundary and others coming from different regions .…

Photon Starved Scene Inference using Single Photon Cameras

Single-photon cameras (SPCs) are an emergingsensing modality that are capable of capturing images with high sensitivity . Despite having minimal read-noise, images captured by SPCs in photon-starved conditions still suffer from strong shot noise . We propose photon scale-space a collection of high-SNR imagesspanning a wide range of photons-per-pixel (PPP) levels as guides to train inference model on low photon flux images .…