Content Analysis Application in Nursing A Synthetic Knowledge Synthesis Meta Study

Synthetic content analysis is frequently used in nursing research in a wide spectrum of applications . The trend of its use is positive and it is used globally in a variety of research settings . The synthetic content analysis used in our study showed to be a very helpful toolin performing knowledge synthesis, replacing many of the routine activities of conventional synthesis with automated activities this making such studies more economically viable and easier to perform .…

Multi Link and AUV aided Energy Efficient Underwater Emergency Response

The recent development of wireless communication has provided many promisingsolutions to emergency response . This article proposes an underwateremergency communication network (UECN) aided by multiple UCLs and autonomousunderwater vehicles to collect underwater emergency data . Simulation results show that the proposed system significantlyimproves the response efficiency and overcomes the limitations of existingworks, which makes contributions to emergency decision-making .…

XAI Handbook Towards a Unified Framework for Explainable AI

The field of explainable AI (XAI) has quickly become a thriving and prolific community . A silent, recurrent and acknowledged issue in this area is the lack of consensus regarding its terminology . We propose atheoretical framework that not only provides concrete definitions for theseterms, but it also outlines all steps necessary to produce explanations andinterpretations .…

SAT Based Rigorous Explanations for Decision Lists

Decision lists (DLs) find a wide range of uses for classification problems inMachine Learning (ML) This paper shows that computing explanations for DLs is computationallyhard . It proposes propositional encodings for computing abductive explanations (AXps) and contrastive explanations of DLs .…

Merit and Blame Assignment with Kind 2

Open-source model checker Kind 2 can identify Minimal Inductive Validity Cores and Minimal Cut Sets . It can also identify minimal sets of design elements that are sufficient to prove a given set of safety properties . The computed information can be used for several purposes, including assessing the quality of a system specification, tracking the safety impact of model changes .…

Generalized LR drawings of trees

LR-drawing-method is a method of drawing an ordered rooted binary tree . It is based on drawing one root-to-leaf path on a vertical line and attachingrecursively obtained drawings of the subtrees on the left and right . In this paper, we study how to generalize this drawing-method to trees of higher arity.…

Meta Inductive Node Classification across Graphs

Recent graph neural networks integrate node features with network structures, thus enabling inductive node classification models that can be applied to new nodes or even new graphs in the same feature space . Inter-graph differences still exist across graphs within the same domain .…

A Separator Theorem for Hypergraphs and a CSP SAT Algorithm

We show that for every $r$-uniform hypergraph on $m$ edges has a set of atmost $m/2$ edges . We use this to give an algorithm running in time $d^{(1 – \epsilon_r)m}$ that decidessatisfiability of $m-variable $(d, k)$-CSPs can be refuted intree-like resolution in size $2(1)m) The algorithm solves the corresponding #CSP-SAT andMax CSPs .…

The Greedy Algorithm is emph not Optimal for On Line Edge Coloring

Bar-Noy, Motwani and Naor showed that no onlineedge-coloring algorithm can edge color a graph optimally . Their lower bound required bounded-degree graphs, which prompted them to conjecture that better bounds are possible for higher degree graphs . We resolve this thirty-year-old conjecture in the affirmative, presenting a $(1.9+o(1)$-competitive online edge coloring algorithm for general graphs of degree $\Delta = \omega(\log n)$ under vertex arrivals .…

3 5 GHz Coverage Assessment with a 5G Testbed

5th generation (5G) mobile networks target the 3.5\,GHz band (3.4 to 3.8GHz) Despite its expected wide usage, there islittle empirical path loss data and mobile radio network planning experience . This paper presents the results of rural,suburban, and urban measurement campaigns using a pre-standard 5G prototypetestbed .…

Delivering Gigabit Capacities to Passenger Trains Tales from an Operator on the Road to 5G

Modern railway cars act as Faraday cages and atypical train consist comprises several hundreds of users moving at highvelocity . User expectations have dramatically increased: it isexpected to be online anytime and anywhere . Demand for mobile high-capacity is driven by video and music streaming services, for lower latency and availability by gaming, and for more reliability and even uplinkcapacity by mission critical applications .…

QAConv Question Answering on Informative Conversations

This paper introduces QAConv, a new question answering (QA) dataset that uses conversations as a knowledge source . We focus on informative conversations including business emails, panel discussions, and work channels . We collect 34,204 QA pairs, including span-based, free-form, and unanswerable questions, from 10,259 selected conversations with both human-written and machine-generated questions .…

Hybrid Schrödinger Feynman Simulation of Quantum Circuits With Decision Diagrams

Classical simulations of quantum computations are vital for the futuredevelopment of this emerging technology . Decision diagrams have been proposed as a complementary technique which frequently allows to tackle the inherent exponential complexity of these simulations . In this work, we show that both problems can be tackled together by employing a hybrid Schrodinger-Feynman scheme for the simulation.…

Sofically presented dynamical systems

We show that M-subshift/SFT systems are precisely the expansive dynamical dynamical M-systems . We also study theautomorphism groups and periodic points of sofically presented systems . A keyidea is the introduction of so-called automatic spaces . We show any finite connected simplicial complex is aconnected component of a finitely presented system, and prove that conjugacy of one-dimensional dynamical systems is undecidable.…

Editing Conditional Radiance Fields

A neural radiance field (NeRF) is a scene model supporting high-quality viewsynthesis, optimized per scene . In this paper, we explore enabling user editing of a category-level NeRF . We introduce a method for propagating coarse2D user scribbles to the 3D space, to modify the color or shape of a local region .…

Budget based real time Executor for Micro ROS

Robot Operating System (ROS) is a popular robotics middleware framework . It underwent a redesign and reimplementation under the nameROS~2 . It now features QoS-configurable communication and a flexible layeredarchitecture . Micro-ROS is a variant developed specifically for resource-constrained microcontrollers (MCU) Such MCUs are commonly used inrobotics for sensors and actuators, for time-critical control functions, and for safety .…

On Bisimilarities for Closure Spaces Preliminary Version

Closure spaces are a generalisation of topological spaces obtained by removing idempotence requirement on the closure operator . We adapt the notion of bisimilarity for topological models, namelyTopo-bisimilarity, to closure models . We also address the issue of (space) minimisation via the three equivalences .…

Emergent Prosociality in Multi Agent Games Through Gifting

Coordination is often critical to forming prosocial behaviors . State of the art reinforcement learning algorithmsoften suffer from converging to socially less desirable equilibria . We propose using a less restrictive peer-rewarding mechanism,gifting . Gifting allows each agent to give some of their reward to other agents .…

Hierarchical Architectures in Reservoir Computing Systems

Reservoir computing (RC) offers efficient temporal data processing with a low training cost by separating recurrent neural networks into a fixed network with recurrent connections and a trainable linear network . The quality of the fixed network, called reservoir, is the most important factor that determines the performance of the RC system .…

Risk Model of German Corona Warning App Reloaded

In this paper we discuss the risk model of the German Corona Warning App(CWA) in two versions . Both are based on a general semi-quantitative risk approach that is not state of the art anymore . However, it turns out that the CWA uses a much more limited model, that does not even assess risk, but relies only on one parameter, aweighted exposure time .…

Urban Analytics History Trajectory and Critique

This chapter reflects on the history and trajectory of urban analytics as a scholarly and professional discipline . It argues that privacy and ethical concerns are toooften ignored as ubiquitous monitoring and analytics can empower socialrepression . It concludes with a call for a more critical urban analytics that emphasizes human dignity and learns from and supports marginalized communities in the field of data analysis .…

Lessons Learned Addressing Dataset Bias in Model Based Candidate Generation at Twitter

Traditionally, heuristic methods are used to generate candidates for largescale recommender systems . Model-based candidate generation promises multiplepotential advantages, primarily that we can explicitly optimize the same objective as the downstream ranking model . We first explore theynamics of the dataset bias problem and then demonstrate how to use randomsampling techniques to mitigate it .…

Bounded Reachability Problems are Decidable in FIFO Machines

The undecidability of basic decision problems for general FIFO machines such as reachability and unboundedness is well-known . In this paper, we provide anunderapproximation for the general model by considering only runs that are input-bounded . We prove, by reducing this model to acounter machine with restricted zero tests, that the rational-reachabilityproblem is decidable .…

Towards Equity and Algorithmic Fairness in Student Grade Prediction

Equity of educational outcome and fairness of AI with respect to race have been topics of increasing importance in education . We find that an adversarial learning approach, combined with grade label balancing,achieved by far the fairest results . With AI-infused technology supportsincreasingly prevalent on campuses, our methodologies fill a need forframeworks to consider performance trade-offs withrespect to sensitive studentattributes and allow institutions to instrument their AI resources in ways that are attentive to equity and fairness .…

Learning Unknown from Correlations Graph Neural Network for Inter novel protein Interaction Prediction

Study of multi-type Protein-Protein Interaction (PPI) is fundamental for understanding biological processes from a systematic perspective and revealing disease mechanisms . Existing methods suffer from significant performancedegradation when tested in unseen dataset . We propose a graph neural network based method for better inter-novel-protein interaction prediction .…

Minimal Cycle Representatives in Persistent Homology using Linear Programming an Empirical Study with User s Guide

Cycle representatives of persistent homology classes can be used to provide descriptions of topological features in data . The non-uniqueness of these representatives creates ambiguity and can lead to many differentinterpretations of the same set of classes . We conduct theseoptimizations via standard linear programming methods, applying general-purposesolvers to optimize over column bases of simplicial boundary matrices .…

Butterfly Core Community Search over Labeled Graphs

Community search aims at finding densely connected subgraphs for queryvertices in a graph . We theoretically prove this problem is NP-hard and analyze its non-approximability . To efficiently tackle the problem, we develop a heuristic algorithm, which first finds a BCCcontaining the query vertices, then removes the farthest verticesto those vertices from the graph .…

Partitioned Deep Learning of Fluid Structure Interaction

We present a partitioned neural network-based framework for learning offluid-structure interaction (FSI) problems . We decompose the simulation domain into two smaller sub-domains, i.e., fluid and solid domains, and incorporate an independent neural network for each . Aquasi-Newton method is used to accelerate the FSI coupling convergence .…

Streaming Transformer for Hardware Efficient Voice Trigger Detection and False Trigger Mitigation

We present a unified and hardware efficient architecture for two stage voicetrigger detection (VTD) and false trigger mitigation (FTM) tasks . We propose a streaming transformer (TF) encoder architecture, which progressively processes incoming audio chunks and maintains audio context . The proposed model yields an average 18% relative reduction in false reject rate (FRR) for the VTD task at a given false alarm rate .…

Keep Your Distance Land Division With Separation

This paper is part of an ongoing endeavor to bring the theory of fairdivision closer to practice by handling requirements from real-life applications . We prove upper and lower boundson achievable maximin share guarantees when the usable shapes are squares, fatrectangles, or arbitrary axes-aligned rectangles .…