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Mobile messaging apps offer an increasing range of emotional expressions, such as emojis to help users manually augment their texting experiences. Accessibility of such augmentations is limited in voice messaging. With the term "speejis" we refer to accessible emojis and other visual speech emotion cues that are created automatically from speech input alone. The paper presents an implementation of speejis and reports on a user study (N=12) comparing the UX of voice messaging with and without speejis. Results show significant differences in measures such as attractiveness and stimulation and a clear preference of all participants for messaging with speejis. We highlight the benefits of using paralinguistic speech processing and continuous emotion models to enable finer grained augmentations of emotion changes and transitions within a single message in addition to augmentations of the overall tone of the message., Comment: 20 pages, 9 figures

Human cognitive performance is an underlying factor in most of our daily lives, and numerous factors influence cognitive performance. In this work, we investigate how changes in sleep quality influence cognitive performance, measured from a dataset collected during a 2-month field study. We collected cognitive performance data (alertness) with the Psychomotor Vigilance Task (PVT), mobile keyboard typing metrics from participants' smartphones, and sleep quality metrics through a wearable sleep tracking ring. Our findings highlight that specific sleep metrics like night-time heart rate, sleep latency, sleep timing, sleep restfulness, and overall sleep quantity significantly influence cognitive performance. To strengthen the current research on cognitive measurements, we introduce smartphone typing metrics as a proxy or a complementary method for continuous passive measurement of cognitive performance. Together, our findings contribute to ubiquitous computing via a longitudinal case study with a novel wearable device, the resulting findings on the association between sleep and cognitive function, and the introduction of smartphone keyboard typing as a proxy of cognitive function., Comment: 27 pages, 6 figures. Submitted to Pervasive and Ubiquitous Computing

Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires significant effort because users must carefully organize and articulate their thoughts. This may discourage users from leaving comprehensive and high-quality reviews, especially when they are on the go. To address this challenge, we developed Vocalizer, a mobile application that enables users to provide reviews through voice input, with enhancements from a large language model (LLM). In a longitudinal study, we analysed user interactions with the app, focusing on AI-driven features that help refine and improve reviews. Our findings show that users frequently utilized the AI agent to add more detailed information to their reviews. We also show how interactive AI features can improve users self-efficacy and willingness to share reviews online. Finally, we discuss the opportunities and challenges of integrating AI assistance into review-writing systems., Comment: \c{opyright} Kavindu Ravishan | ACM 2024. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in the Proceedings of the ACM Conference on Mobile and Ubiquitous Multimedia (MUM '24), http://dx.doi.org/10.1145/3701571.3701593

Nuclear fusion could offer clean, abundant energy. However, managing the immense power exhausted from the core fusion plasma towards the divertor remains a major challenge. This is compounded in emerging compact reactor designs which promise more cost-effective pathways towards commercial fusion energy. Alternative divertor configurations (ADCs) are a potential solution to this challenge. In this work, we demonstrate exhaust control in ADCs for the first time, on MAST-U. We employ a novel diagnostic strategy for the neutral gas buffer which shields the target. Our work shows that ADCs tackle key risks and uncertainties in realising fusion energy: 1) an enlarged operating window which 2) improves exhaust control through the absorption of transients which can remove the neutral shield and damage the divertor, 3) isolation of each divertor from other reactor regions, enabling combined control. This showcases real-world benefits of alternative divertors for effective heat load management and control in reactors.

We propose a class of cellular automata for the Hamiltonian of a free particle. It is based on a two-step unitary evolution operator in discrete time and space. Various experiments with one and two-dimensional cellular automata are used to analyze 1) phase velocities of plane waves, 2) dispersion and group velocities of wavepackets, 3) energy levels of infinite potential wells and harmonic oscillators, and 4) interference from double-slit diffraction. Some of the differences between their known (analytical) results and the cellular-automata approximations are intriguing.

We report measurements characterizing the performance of a kinetic inductance detector array designed for a wavelength of 25 microns and very low optical background level suitable for applications such as a far-infrared instrument on a cryogenically cooled space telescope. In a pulse counting mode of operation at low optical flux, the detectors can resolve individual 25-micron photons. In an integrating mode, the detectors remain photon noise limited over more than six orders of magnitude in absorbed power from 70 zW to 200 fW, with a limiting NEP of 4.6 x 10^-20 W/rtHz at 1 Hz. In addition, the detectors are highly stable with flat power spectra under optical load down to 1 mHz. Operational parameters of the detector are determined including the efficiency of conversion of the incident optical power into quasiparticles in the aluminum absorbing element and the quasiparticle self-recombination constant., Comment: 35 pages, 18 figures

This paper provides a set of cut-free complete sequent-style calculi for deontic STIT ('See To It That') logics used to formally reason about choice-making, obligations, and norms in a multi-agent setting. We leverage these calculi to write a proof-search algorithm deciding deontic, multi-agent STIT logics with (un)limited choice and introduce a loop-checking mechanism to ensure the termination of the algorithm. Despite the acknowledged potential for deontic reasoning in the context of autonomous, multi-agent scenarios, this work is the first to provide a syntactic decision procedure for this class of logics. Our proof-search procedure is designed to provide verifiable witnesses/certificates of the (in)validity of formulae, which permits an analysis of the (non)theoremhood of formulae and act as explanations thereof. We show how the proof system and decision algorithm can be used to automate normative reasoning tasks such as duty checking (viz. determining an agent's obligations relative to a given knowledge base), compliance checking (viz. determining if a choice, considered by an agent as potential conduct, complies with the given knowledge base), and joint fulfillment checking (viz. determining whether under a specified factual context an agent can jointly fulfill all their duties)., Comment: Preprint; published in the Journal of Artificial Intelligence Research 2024

The PRobe far-Infrared Mission for Astrophysics (PRIMA) is under study as a potential far-IR space mission, featuring actively cooled optics, and both imaging and spectroscopic instrumentation. To fully take advantage of the low background afforded by a cold telescope, spectroscopy with PRIMA requires detectors with a noise equivalent power (NEP) better than $1 \times 10^{-19}$ W Hz$^{-1/2}$. To meet this goal we are developing large format arrays of kinetic inductance detectors (KIDs) to work across the $25-250$ micron range. Here we present the design and characterization of a single pixel prototype detector optimized for $210$ micron. The KID consists of a lens-coupled aluminum inductor-absorber connected to a niobium interdigitated capacitor to form a 2 GHz resonator. We have fabricated a small array with 28 KIDs, and we measure the performance of one of these detectors with an optical loading in the $0.01 - 300$ aW range. At low loading the detector achieves an NEP of $9\times10^{-20}$ W Hz$^{-1/2}$ at a 10 Hz readout frequency, and the lens-absorber system achieves a good optical efficiency. An extrapolation of these measurements suggest this detector may remain photon noise limited at up to 20 fW of loading, offering a high dynamic range for PRIMA observations of bright astronomical sources., Comment: revised submission to IEEE Transactions on Terahertz Science and Technology

This paper addresses the challenge of boosting the precision of multi-path long-term vessel trajectory forecasting on engineered sequences of Automatic Identification System (AIS) data using feature fusion for problem shifting. We have developed a deep auto-encoder model and a phased framework approach to predict the next 12 hours of vessel trajectories using 1 to 3 hours of AIS data as input. To this end, we fuse the spatiotemporal features from the AIS messages with probabilistic features engineered from historical AIS data referring to potential routes and destinations. As a result, we reduce the forecasting uncertainty by shifting the problem into a trajectory reconstruction problem. The probabilistic features have an F1-Score of approximately 85% and 75% for the vessel route and destination prediction, respectively. Under such circumstances, we achieved an R2 Score of over 98% with different layer structures and varying feature combinations; the high R2 Score is a natural outcome of the well-defined shipping lanes in the study region. However, our proposal stands out among competing approaches as it demonstrates the capability of complex decision-making during turnings and route selection. Furthermore, we have shown that our model achieves more accurate forecasting with average and median errors of 11km and 6km, respectively, a 25% improvement from the current state-of-the-art approaches. The resulting model from this proposal is deployed as part of a broader Decision Support System to safeguard whales by preventing the risk of vessel-whale collisions under the smartWhales initiative and acting on the Gulf of St. Lawrence in Atlantic Canada.

Future generation of astronomical imaging spectrometers are targeting the far infrared wavelengths to close the THz astronomy gap. Similar to lens antenna coupled Microwave Kinetic Inductance Detectors (MKIDs), lens absorber coupled MKIDs are a candidate for highly sensitive large format detector arrays. However, the latter is more robust to misalignment and assembly issues at THz frequencies due to its incoherent detection mechanism while requiring a less complex fabrication process. In this work, the performance of such detectors is investigated. The fabrication and sensitivity measurement of several lens absorber coupled MKID array prototypes operating at 6.98 and 12 THz central frequencies is on-going., Comment: 2 pages, 2 figures, IRMMW-THz conference paper

How can we ensure that Ubiquitous Computing (UbiComp) research outcomes are both ethical and fair? While fairness in machine learning (ML) has gained traction in recent years, fairness in UbiComp remains unexplored. This workshop aims to discuss fairness in UbiComp research and its social, technical, and legal implications. From a social perspective, we will examine the relationship between fairness and UbiComp research and identify pathways to ensure that ubiquitous technologies do not cause harm or infringe on individual rights. From a technical perspective, we will initiate a discussion on data practices to develop bias mitigation approaches tailored to UbiComp research. From a legal perspective, we will examine how new policies shape our community's work and future research. We aim to foster a vibrant community centered around the topic of responsible UbiComp, while also charting a clear path for future research endeavours in this field.

Model predictive control (MPC) is promising for fueling and core density feedback control in nuclear fusion tokamaks, where the primary actuators, frozen hydrogen fuel pellets fired into the plasma, are discrete. Previous density feedback control approaches have only approximated pellet injection as a continuous input due to the complexity that it introduces. In this letter, we model plasma density and pellet injection as a hybrid system and propose two MPC strategies for density control: mixed-integer (MI) MPC using a conventional mixed-integer programming (MIP) solver and MPC utilizing our novel modification of the penalty term homotopy (PTH) algorithm. By relaxing the integer requirements, the PTH algorithm transforms the MIP problem into a series of continuous optimization problems, reducing computational complexity. Our novel modification to the PTH algorithm ensures that it can handle path constraints, making it viable for constrained hybrid MPC in general. Both strategies perform well with regards to reference tracking without violating path constraints and satisfy the computation time limit for real-time control of the pellet injection system. However, the computation time of the PTH-based MPC strategy consistently outpaces the conventional MI-MPC strategy.

Clinical needs and technological advances have resulted in increased use of Artificial Intelligence (AI) in clinical decision support. However, such support can introduce new and amplify existing cognitive biases. Through contextual inquiry and interviews, we set out to understand the use of an existing AI support system by ophthalmologists. We identified concerns regarding anchoring bias and a misunderstanding of the AI's capabilities. Following, we evaluated clinicians' perceptions of three bias mitigation strategies as integrated into their existing decision support system. While clinicians recognised the danger of anchoring bias, we identified a concern around the impact of bias mitigation on procedure time. Our participants were divided in their expectations of any positive impact on diagnostic accuracy, stemming from varying reliance on the decision support. Our results provide insights into the challenges of integrating bias mitigation into AI decision support., Comment: CHI '23

The Bell inequality constrains the outcomes of measurements on pairs of distant entangled particles. The Bell contradiction states that the Bell inequality is inconsistent with the calculated outcomes of these quantum experiments. This contradiction led many to question the underlying assumptions, viz. so-called realism and locality. This paper proposes an appropriate probability model for the Bell experiment. This model has only two simultaneously observable detector settings per measurement, and therefore does not assume realism. It is in full agreement with both quantum mechanics and experiments. In this model the expectation for a particular pair of observations is partial to the selected detector settings. This leads to a slightly different variant of the Bell inequality, one that is consistent with both quantum mechanics and measurements. In this model there is no Bell contradiction. Furthermore, the proposed probability model is statistically local, is not factorizable, and is not Bell-separable. The latter implies that either hidden variables must be ruled out, or that locality must be violated. Thus, our conclusion agrees with Bell's conclusion.

Artificial Intelligence (AI) systems have been increasingly used to make decision-making processes faster, more accurate, and more efficient. However, such systems are also at constant risk of being attacked. While the majority of attacks targeting AI-based applications aim to manipulate classifiers or training data and alter the output of an AI model, recently proposed Sponge Attacks against AI models aim to impede the classifier's execution by consuming substantial resources. In this work, we propose \textit{Dual Denial of Decision (DDoD) attacks against collaborative Human-AI teams}. We discuss how such attacks aim to deplete \textit{both computational and human} resources, and significantly impair decision-making capabilities. We describe DDoD on human and computational resources and present potential risk scenarios in a series of exemplary domains., Comment: 10 pages, 1 figure, IEEE Pervasive Computing, IEEE Special Issue on Human-Centered AI

This article proposes the use of temporal logic for an analysis of instrumentality inspired by the work of G.H. von Wright. The first part of the article contains the philosophical foundations. We discuss von Wright's general theory of agency and his account of instrumentality. Moreover, we propose several refinements to this framework via rigorous definitions of the core notions involved. In the second part, we develop a logical system called Temporal Logic of Action and Expectations (TLAE). The logic is inspired by a fragment of propositional dynamic logic based on indeterministic time. The system is proven to be weakly complete relative to its given semantics. We then employ TLAE to formalise and analyse the instrumentality relations defined in the first part of the paper. Last, we point out philosophical implications and possible extensions of our work.

Theoretical work in morphological typology offers the possibility of measuring morphological diversity on a continuous scale. However, literature in Natural Language Processing (NLP) typically labels a whole language with a strict type of morphology, e.g. fusional or agglutinative. In this work, we propose to reduce the rigidity of such claims, by quantifying morphological typology at the word and segment level. We consider Payne (2017)'s approach to classify morphology using two indices: synthesis (e.g. analytic to polysynthetic) and fusion (agglutinative to fusional). For computing synthesis, we test unsupervised and supervised morphological segmentation methods for English, German and Turkish, whereas for fusion, we propose a semi-automatic method using Spanish as a case study. Then, we analyse the relationship between machine translation quality and the degree of synthesis and fusion at word (nouns and verbs for English-Turkish, and verbs in English-Spanish) and segment level (previous language pairs plus English-German in both directions). We complement the word-level analysis with human evaluation, and overall, we observe a consistent impact of both indexes on machine translation quality., Comment: Accepted at NAACL 2022