Transfer Learning for Human & AI

We conducted a field study at a K-12 private school in the suburbs of Melbourne, Australia . The data capture contained two elements: a 5-monthlongitudinal field study In-Gauge using two outdoor weather stations, as well as indoor weather stations in 17 classrooms .…

Language-queried video actor segmentation aims to predict the pixel-levelmask of the actor which performs the actions described by a natural language query in the target frames . We propose a collaborativespatial-temporal encoder-decoder framework which contains a 3D temporal encoder over the video clip to recognize the queried actions .…

This paper introduces reproducible research, and explains its importance,benefits and challenges . Some important tools for conducting reproducibleresearch in Transportation Research are also introduced . The sourcecode for generating this paper has been designed in a way so that it can be used as a template for researchers to write their future journal papers .…

Learning analytics (LA) is argued to be able to improve learning outcomes,learner support and teaching . However, despite an expanding amount of student (digital) data, there is still little empirical evidence of impact on practice that shows the effectiveness of LA in education settings .…

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 .…

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 .…

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 .…

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 .…

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 .…

The benefits of deep neural networks (DNNs) have become of interest for safety critical applications like medical ones or automated driving . Such can be sub-objects like human body parts that are valuable forvalidation of pedestrian detection . To our knowledge, concept analysis has notyet been applied to large object detectors, specifically not for sub-parts .…

Bibliometric studies are a rare undertaking in the field of English languageteaching, especially at a journal level . To celebrate the 30th anniversary ofTEFLIN Journal, this study exhibits a bibliometric portrait of its publication, indexation, and citation from 1990 to 2019 .…

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 .…

Stencil computations are widely used to simulate the change of state of physical systems across a multidimensional grid over multiple timesteps . Current direct solvers in this domain arecomputationally inefficient, and Krylov methods require manual labor and training . We solve these problems for linear stencils by using DFTpreconditioning on a Krylov method to achieve a direct solver which is bothfast and general .…

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 .…

A large portion of mobile data traffic is consumed behind theshielding walls of buildings or in the Faraday cage of trains . Indoor small cells and distributed antennas along train tracks are often considered as a solution . This concept does not require fiber deployment, provides backward compatibility to equipment already in use, and additional indoor capacity is gained while outdoor networks are offloaded .…

Wireless indoor coverage and data capacity are important aspects of cellularnetworks . With the ever-increasing data traffic, demand for more data capacityindoors is also growing . Newfrequencies foreseen for the 5th generation (5G) of mobile communications inthe millimeter wave (mmWave) spectrum penetrate very poorly into buildings .…

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 .…

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.…

The more one publishes and the higher their impact, the larger their collaboration network . International academic migrants are better at growing their networks than those that only migrate within the same country . High academic mobility does not appear to translate into better academic performance or larger collaboration networks, say the authors .…

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 .…

In this position paper, we argue for the need to investigate if and how gender stereotypes manifest in search and recommender systems . We focus on how these systems may propagate and reinforce gender stereotypes through their results in learning environments .…

Self-adjusting computation is an approach for automatically producing dynamical algorithms from static ones . The approach works by tracking control and datadependencies, and propagating changes through the dependencies when making an update . The main innovation in the paper is in using Series-Paralleltrees (SP trees) to track sequential and parallel control dependencies to allow the application of changes to be applied safely in parallel .…

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 .…

A smart microgrid implemented in Paracas, Ica, Peru, provides electricity to a rural community of 40 families . Real data of solarirradiance, wind speed, energy demand, and voltage of the battery bank from 2periods of operation were studied to find patterns, seasonality, and existingrelations between the analyzed data .…

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 .…

A widely used standard for portable multilingual data analysis pipelines would enable considerable benefits to scholarly publication reuse, research/industry collaboration, regulatory cost control, and to the environment . Researchers would be able to easier collaborate and reuse these pipelines, adding or exchanging components regardless of programming language used .…

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.…

Spiking neural networks (SNNs) communicate through the all-or-none spikingactivity of neurons . But fitting the large number of SNN model parameters remains a challenge . Previous work using genetic algorithm (GA) optimisation on a specific efficient model was limited to a single parameter and objective .…

We consider the problem of estimating quantum observables on a collection of qubits . We introduce estimators based on randomised measurements . They use decision diagrams to sample from probability distributions on measurement bases . This approach generalises previously knownuniform and locally-biased randomised estimators .…

A key way to construct complex distributed systems is through modularcomposition of linearizable concurrent objects . A strengthening of linearizability has been shown to preserve probabilistic behavior, as well as other hypersafety properties . This paper answers the question in the negative: there are nostrongly-linearizable fault-tolerant message-passing implementations of multi-writer registers, max-registers, snapshots or counters .…

The performance of distributed and data-centric applications often critically depends on the interconnecting network . Applications are modeled as virtual networks, also accounting for resource demands on links . At the heart of provisioning such virtual networks lies the NP-hard Virtual NetworkEmbedding Problem .…

We show that plane bipolar posets (i.e., plane bipolar orientations with notransitive edge) and transversal structures can be set in correspondence to certain (weighted) models of quadrant walks . We then derive exact andasymptotic counting results, and in particular we prove (computationally andthen bijectively) that the number of plane bipolar .…

Multi-thread applications commonly utilize condition variables for communication between threads . Condition variables allow threads to block andwait until a certain condition holds, and also enable threads to wake up their blocked peers notifying them about a change to the state of shared data .…

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 .…

Information compression is essential to reduce communication cost indistributed optimization over peer-to-peer networks . This paper proposes acommunication-efficient linearly convergent distributed (COLD) algorithm to solve strongly convex optimization problems . By compressing innovation vectors, which are the differences between decision vectors and their estimates, COLD isable to achieve linear convergence for a class of $\delta$-contractedcompressors .…

In the (fully) dynamic set cover problem, we have a collection of $m$ sets from a universe of size $n$ that undergo element insertions and deletions . The goal is to maintain an approximate set cover of the universe after each update .…

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 .…

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 .…

Constraint handling is one of the most influential aspects of applying metaheuristics to real-world applications . In this work, we focus on a particular case – the boxconstraints, for which many boundary constraint handling methods (BCHMs) have been proposed . We call for the necessity of studying the impact of BCHMs on performance and behavior, which receives seemingly little attention in the field .…

Spiking Neural Networks (SNN) are the so-called third generation of neuralnetworks which attempt to more closely match the functioning of the biological brain . They inherently encode temporal data, allowing for training with less energy usage and can be extremely energy efficient when coded on neuromorphichardware .…

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.…

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 .…

The proposed Heuristically-Assisted DRL (HA-DRL)allows to accelerate the learning process and gain in resource usage . The DRL algorithm uses the so-calledAsynchronous Advantage Actor Critic (A3C) algorithm for fast learning, andGraph Convolutional Networks (GCN) to automate feature extraction from the physical substrate network .…

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 .…

Edge intelligence leverages computing resources on network edge to provide artificial intelligence (AI) services close to network users . Edge intelligence is envisioned to bean important component of 6G networks . We propose a novel resource pooling method to jointly manage service data and network resources for AI services .…

This article proposes a hybrid device-to-device (D2D) and D2V network for collecting and transmitting emergency information . We establish the D2Dnetwork from the perspective of complex networks by jointly determining theoptimal network partition (ONP) and the temporary data caching centers (TDCC) First, we establish the .…

NVIDIA’s BlueField-2 SmartNIC can be used to offload data to the edge of the network . HPC researchers have long envisioned scenarios where application workflows could be improved through the use of programmable elements embedded in the network fabric . While the host can easily saturate thenetwork link, the embedded processors may not have enough computingresources to sustain more than half the expected bandwidth when using kernel-space packet processing .…

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 .…

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 .…

Modern rock music proved to bedifficult to estimate tempo and chord recognition did not work . Using a neural network has been one of the simplest ways of dealing with it . The recognition process is time-consuming centred centred on onextremely complicated and memory-intensive methods .…