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The building thermodynamics model, which predicts real-time indoor temperature changes under potential HVAC (Heating, Ventilation, and Air Conditioning) control operations, is crucial for optimizing HVAC control in buildings. While pioneering studies have attempted to develop such models for various building environme... |
This paper explores the role and challenges of Artificial Intelligence (AI) algorithms, specifically AI-based software elements, in autonomous driving systems. These AI systems are fundamental in executing real-time critical functions in complex and high-dimensional environments. |
Knowledge Base Completion (KBC), which aims at determining the missing relations between entity pairs, has received increasing attention in recent years. Most existing KBC methods focus on either embedding the Knowledge Base (KB) into a specific semantic space or leveraging the joint probability of Random Walks (RWs) ... |
This paper builds upon recent work in the declarative design of dialogue agents and proposes an exciting new tool -- D3BA -- Declarative Design for Digital Business Automation, built to optimize business processes using the power of AI planning. The tool provides a powerful framework to build, optimize, and maintain c... |
With the technology development, the need of analyze and extraction of useful information is increasing. Bayesian networks contain knowledge from data and experts that could be used for decision making processes But they are not easily understandable thus the rule extraction methods have been used but they have high c... |
Exact algorithms for learning Bayesian networks guarantee to find provably optimal networks. However, they may fail in difficult learning tasks due to limited time or memory. |
We address the problem of identifying dynamic sequential plans in the framework of causal Bayesian networks, and show that the problem is reduced to identifying causal effects, for which there are complete identi cation algorithms available in the literature. |
The k-SERVER problem is one of the most prominent problems in online algorithms with several variants and extensions. However, simplifying assumptions like instantaneous server movements and zero service time has hitherto limited its applicability to real-world problems. |
Humans are capable of abstracting away irrelevant details when studying problems. This is especially noticeable for problems over grid-cells, as humans are able to disregard certain parts of the grid and focus on the key elements important for the problem. |
This paper describes a problem arising in sea exploration, where the aim is to schedule the expedition of a ship for collecting information about the resources on the seafloor. The aim is to collect data by probing on a set of carefully chosen locations, so that the information available is optimally enriched. |
Traffic simulators act as an essential component in the operating and planning of transportation systems. Conventional traffic simulators usually employ a calibrated physical car-following model to describe vehicles' behaviors and their interactions with traffic environment. |
This paper presents a fuzzy inference system for integrated volt/var control (VVC) in distribution substations. The purpose is go forward to automation distribution applying conservation voltage reduction (CVR) in isolated power systems where control capabilities are limited. |
Next Point-of-Interest (POI) recommendation is a research hotspot in business intelligence, where users' spatial-temporal transitions and social relationships play key roles. However, most existing works model spatial and temporal transitions separately, leading to misaligned representations of the same spatial-te... |
Intermediate token generation (ITG), where a model produces output before the solution, has been proposed as a method to improve the performance of language models on reasoning tasks. While these reasoning traces or Chain of Thoughts (CoTs) are correlated with performance gains, the mechanisms underlying them remain u... |
In this paper we apply computer learning methods to diagnosing ovarian cancer using the level of the standard biomarker CA125 in conjunction with information provided by mass-spectrometry. We are working with a new data set collected over a period of 7 years. |
We consider the problem of computing a lightest derivation of a global structure using a set of weighted rules. A large variety of inference problems in AI can be formulated in this framework. |
Decision lists are one of the most easily explainable machine learning models. Given the renewed emphasis on explainable machine learning decisions, this machine learning model is increasingly attractive, combining small size and clear explainability. |
Data originating from the Web, sensor readings and social media result in increasingly huge datasets. The so called Big Data comes with new scientific and technological challenges while creating new opportunities, hence the increasing interest in academia and industry. |
Memory-based meta-learning is a powerful technique to build agents that adapt fast to any task within a target distribution. A previous theoretical study has argued that this remarkable performance is because the meta-training protocol incentivises agents to behave Bayes-optimally. |
Large artificial intelligence (AI) models exhibit remarkable capabilities in various application scenarios, but deploying them at the network edge poses significant challenges due to issues such as data privacy, computational resources, and latency. In this paper, we explore federated fine-tuning and collaborative rea... |
This research paper delves into the integration of OpenAI's ChatGPT into embodied agent systems, evaluating its influence on interactive decision-making benchmark. Drawing a parallel to the concept of people assuming roles according to their unique strengths, we introduce InterAct. |
The manuscript presented an analysis of the work in the field of eye-tracking over the past ten years in the low-cost filed. We researched in detail the methods, algorithms, and developed hardware. |
Concepts, which represent a group of different instances sharing common properties, are essential information in knowledge representation. Most conventional knowledge embedding methods encode both entities (concepts and instances) and relations as vectors in a low dimensional semantic space equally, ignoring the diffe... |
This paper presents a novel approach to aligning large language models (LLMs) with individual human preferences, sometimes referred to as Reinforcement Learning from \textit{Personalized} Human Feedback (RLPHF). Given stated preferences along multiple dimensions, such as helpfulness, conciseness, or humor, the goal is... |
We present a convenient notation for positive/negative-conditional equations. The idea is to merge rules specifying the same function by using case-, if-, match-, and let-expressions. |
Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning and reasoning. However, measuring agent performance in realistic environments remains a challenge since: |
AI systems have been known to amplify biases in real-world data. Explanations may help human-AI teams address these biases for fairer decision-making. |
The reasoning processes of large language models often lack faithfulness; a model may generate a correct answer while relying on a flawed or irrelevant reasoning trace. This behavior, a direct consequence of training objectives that solely reward final-answer correctness, severely undermines the trustworthiness of the... |
Attempts to import dual-system descriptions of System-1 and System-2 into AI have been hindered by a lack of clarity over their distinction. We address this and other issues by situating System-1 and System-2 within the Common Model of Cognition. |
State-of-the-art approaches for integrating symbolic knowledge with deep learning architectures have demonstrated promising results in static domains. However, methods to handle temporal logic specifications remain underexplored. |
Knowledge-driven autonomous driving systems(ADs) offer powerful reasoning capabilities, but face two critical challenges: limited perception due to the short-sightedness of single-vehicle sensors, and hallucination arising from the lack of real-time environmental grounding. To address these issues, this paper introduc... |
Data science tasks involving tabular data present complex challenges that require sophisticated problem-solving approaches. We propose AutoKaggle, a powerful and user-centric framework that assists data scientists in completing daily data pipelines through a collaborative multi-agent system. |
The no-wait flowshop scheduling problem is a variant of the classical permutation flowshop problem, with the additional constraint that jobs have to be processed by the successive machines without waiting time. To efficiently address this NP-hard combinatorial optimization problem we conduct an analysis of the structu... |
United Nations set Sustainable Development Goals and this paper focuses on 7th (Affordable and Clean Energy), 9th (Industries, Innovation and Infrastructure), and 13th (Climate Action) goals. Climate change is a major concern in our society; for this reason, a current global objective is to reduce energy waste. |
Training agents to act in embodied environments typically requires vast training data or access to accurate simulation, neither of which exists for many cases in the real world. Instead, world models are emerging as an alternative leveraging offline, passively collected data, they make it possible to generate diverse ... |
One goal of Artificial Intelligence is to learn meaningful representations for natural language expressions, but what this entails is not always clear. A variety of new linguistic behaviours present themselves embodied as computers, enhanced humans, and collectives with various kinds of integration and communication. |
Predicting contextualised engagement in videos is a long-standing problem that has been popularly attempted by exploiting the number of views or the associated likes using different computational methods. The recent decade has seen a boom in online learning resources, and during the pandemic, there has been an exponen... |
Recently, digital music libraries have been developed and can be plainly accessed. Latest research showed that current organization and retrieval of music tracks based on album information are inefficient. |
The rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. This study delves into university instructors' experiences and attitudes toward AI language models, filling a gap in the literature by anal... |
Vision-language models (VLMs) have tremendous potential for grounding language, and thus enabling language-conditioned agents (LCAs) to perform diverse tasks specified with text. This has motivated the study of LCAs based on reinforcement learning (RL) with rewards given by rendering images of an environment and evalu... |
This work presents six structural quality metrics that can measure the quality of knowledge graphs and analyzes five cross-domain knowledge graphs on the web (Wikidata, DBpedia, YAGO, Google Knowledge Graph, Freebase) as well as 'Raftel', Naver's integrated knowledge graph. The 'Good Knowledge Graph... |
We study the problem of off-policy evaluation (OPE) in reinforcement learning (RL), where the goal is to estimate the performance of a policy from the data generated by another policy(ies). In particular, we focus on the doubly robust (DR) estimators that consist of an importance sampling (IS) component and a performa... |
Agricultural production requires careful management of inputs such as fungicides, insecticides, and herbicides to ensure a successful crop that is high-yielding, profitable, and of superior seed quality. Current state-of-the-art field crop management relies on coarse-scale crop management strategies, where entire fiel... |
Stochastic Constraint Programming (SCP) is an extension of Constraint Programming (CP) used for modelling and solving problems involving constraints and uncertainty. SCP inherits excellent modelling abilities and filtering algorithms from CP, but so far it has not been applied to large problems. |
Metaheuristics are general methods that guide application of concrete heuristic(s) to problems that are too hard to solve using exact algorithms. However, even though a growing body of literature has been devoted to their statistical evaluation, the approaches proposed so far are able to assess only coupled effects of... |
The high-dimesionality, non-linearity and emergent properties of complex systems pose a challenge to identifying general laws in the same manner that has been so successful in simpler physical systems. In Anderson's seminal work on why "more is different" he pointed to how emergent, macroscale patterns bre... |
The expected value of information (EVI) is the most powerful measure of sensitivity to uncertainty in a decision model: it measures the potential of information to improve the decision, and hence measures the expected value of outcome. Standard methods for computing EVI use discrete variables and are computationally i... |
We present chemlambda (or the chemical concrete machine), an artificial chemistry with the following properties: (a) is Turing complete, |
Evaluating the safety of AI Systems is a pressing concern for organizations deploying them. In addition to the societal damage done by the lack of fairness of those systems, deployers are concerned about the legal repercussions and the reputational damage incurred by the use of models that are unsafe. |
The devastating 6.8-magnitude earthquake in Al Haouz, Morocco in 2023 prompted critical reflections on global disaster management strategies, resulting in a post-disaster hackathon, using artificial intelligence (AI) to improve disaster preparedness, response, and recovery. This paper provides |
Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and ge... |
In this technical report, we investigate the predictive performance differences of a rule-based approach and the GNN architectures NBFNet and A*Net with respect to knowledge graph completion. For the two most common benchmarks, we find that a substantial fraction of the performance difference can be explained by one u... |
Large Multimodal Models (LMMs) often rely on in-context learning (ICL) to perform new tasks with minimal supervision. However, ICL performance, especially in smaller LMMs, is inconsistent and does not always improve monotonically with increasing examples. |
In this work we study how to learn good algorithms for selecting reasoning steps in theorem proving. We explore this in the connection tableau calculus implemented by leanCoP where the partial tableau provides a clean and compact notion of a state to which a limited number of inferences can be applied. |
Machine learning (ML) approaches have demonstrated promising results in a wide range of healthcare applications. Data plays a crucial role in developing ML-based healthcare systems that directly affect people's lives. |
Multiclass learning problems involve finding a definition for an unknown function f(x) whose range is a discrete set containing k &gt 2 values (i.e., k ``classes''). The definition is acquired by studying collections of training examples of the form [x_i, f (x_i)]. |
We are interested in creating an automated or semi-automated system with the capability of taking a set of radar imagery, collection parameters and a priori map and other tactical data, and producing likely interpretations of the possible military situations given the available evidence. This paper is concerned with t... |
Continuous optimization is an important problem in many areas of AI, including vision, robotics, probabilistic inference, and machine learning. Unfortunately, most real-world optimization problems are nonconvex, causing standard convex techniques to find only local optima, even with extensions like random restarts and... |
We analyze the dependence of the membership probabilities obtained from kinematical variables on the radius of the field of view around open clusters (the sampling radius, Rs). From simulated data, we show that the best discrimination between cluster members and non-members is obtained when the sampling radius is very... |
The nuclear stellar disc (NSD) is a flat and dense stellar structure at the centre of the Milky Way. Previous work has identified the presence of metal-rich and metal-poor stars in the NSD, suggesting that they have different origins. |
It is now established that the faint radio population is a mixture of star-forming galaxies and faint active galactic nuclei (AGNs), with the former dominating below S(1.4GHz) \sim 100 muJy and the latter at larger flux densities. The faint radio AGN component can itself be separated into two main classes, mainly base... |
Using the astrometry from the ESA's Gaia mission, previous works have shown that the Milky Way stellar halo is dominated by metal-rich stars on highly eccentric orbits. To shed light on the nature of this prominent halo component, we have analysed 28 Galaxy analogues in the Auriga suite of cosmological hydrodynami... |
We take advantage of exquisitely deep optical imaging data from HST/ACS in the F475W ($g_{F475W}$) and F606W ($V_{F606W}$) bands, to study the properties of the globular cluster (GC) population in the intermediate mass lenticular galaxy PGC 087327, in the Hydra I galaxy cluster. We inspect the photometric (magnitudes ... |
We study the redshift evolution of the dynamical properties of ~180,000 massive galaxies from SDSS-III/BOSS combined with a local early-type galaxy sample from SDSS-II in the redshift range 0.1<z< 0.6. The typical stellar mass of this sample is Mstar~2x10^{11} Msun. |
We present an analysis of the cluster X-ray morphology and active galactic nucleus (AGN) activity in nine $z\sim1$ galaxy clusters from the Massive and Distant Clusters of $WISE$ Survey (MaDCoWS) observed with $Chandra$. Using photon asymmetry ($A_{\text{phot}}$) to quantify X-ray morphologies, we find evidence that t... |
We present a possible identification strategy for first hydrostatic core (FHSC) candidates and make predictions of ALMA dust continuum emission maps from these objects. We analyze the results given by the different bands and array configurations and identify which combinations of the two represent our best chance of s... |
Triangulum, M33, is a low mass, relatively undisturbed spiral galaxy that offers a new regime in which to test models of dynamical heating. In spite of its proximity, the dynamical heating history of M33 has not yet been well constrained. |
Observations show that the ISM contains sub-structure on scales less than 1 pc, detected in the form of spatial and temporal variations in column densities or optical depth. Despite the number of detections, the nature and ubiquity of the small-scale structure in the ISM is not yet fully understood. |
The isocyanic acid (HNCO) presents an extended distribution in the centers of the Milky Way and the spiral galaxy IC342. Based on the morphology of the emission and the HNCO abundance with respect to H2, several authors made the hypothesis that HNCO could be a good tracer of interstellar shocks. |
As some of the only Lyman continuum (LyC) emitters at z~0, Green Pea (GP) galaxies are possible analogs of the sources that reionized the universe. We present HST COS spectra of 13 of the most highly ionized GPs, with [O III]/[O II]=6-35, and investigate correlations between Ly-alpha, galaxy properties, and low-ioniza... |
Mapping star-formation rates (SFR) within galaxies is key to unveiling their assembly and evolution. Calibrations exist for computing SFR from a combination of ultraviolet and infrared bands for galaxies as integrated systems, but their applicability to sub-galactic (kpc) scales remains largely untested. |
We investigated the connection between the mid-infrared (MIR) and optical spectral characteristics in a sample of 82 Type 1 active galactic nuclei (AGNs), observed with Infrared Spectrometer on Spitzer (IRS) and Sloan Digital Sky Survey (SDSS, DR12). We found several interesting correlations between optical and MIR sp... |
ALMA-IMF is a large program of the Atacama Large Millimeter/submillimeter Array (ALMA) that aims to determine the origin of the core mass function (CMF) of 15 massive Galactic protoclusters (~ 1.0-25.0 x 10^3 solar mass within ~ 2.5 x 2.5 pc^2 ) located towards the Galactic plane. In addition, the objective of the pro... |
We show that the James Webb Space Telescope will be able to detect dwarf satellites of high-$z$ Lyman Break Galaxies (LBGs). To this aim, we use cosmological simulations following the evolution of a typical $M_\star\simeq10^{10}\rm M_\odot$ LBG up to $z\simeq6$, and analyse the observational properties of its five sat... |
We use galaxies from the Herschel Reference Survey to evaluate commonly used indirect predictors of cold gas masses. We calibrate predictions for cold neutral atomic and molecular gas using infrared dust emission and gas depletion time methods which are self-consistent and have ~20% accuracy (with the highest accuracy... |
Supermassive black holes at the centre of galactic nuclei mostly grow in mass through gas accretion over cosmic time. This process also modifies the angular momentum (or spin) of black holes, both in magnitude and in orientation. |
The internal kinematics of the Large Magellanic Cloud (LMC) disk have been modeled by several studies using different tracers with varying coverage, resulting in a range of parameters. Here, we modeled the LMC disk using 1705 star clusters and field stars, based on a robust Markov Chain Monte Carlo (MCMC) method, usin... |
We present first results from the SXDF-ALMA 1.5 arcmin^2 deep survey at 1.1 mm using Atacama Large Millimeter Array (ALMA). The map reaches a 1sigma depth of 55 uJy/beam and covers 12 Halpha-selected star-forming galaxies at z = 2.19 or z=2.53. |
We propose a Machian model of gravitational interaction at galactic scales to explain the rotation curves of these large structures without the need for dark matter or MOND. |
We analyze the properties of the circumgalactic gas (CGM) around 120 galaxies with stellar and dark matter halo masses similar to that of the Milky Way. We focus on the morphology and kinematics of the neutral hydrogen and how this depends on f_g, the ratio of gas-to-stellar mass within the optical radius. |
In the nearby universe jets from AGN are observed to have a dramatic impact on their surrounding extragalactic environment. Their effect at the `cosmic noon' (z>1.5), the epoch when star formation and AGN activity peak, is instead much less constrained. |
We report the discovery of spiral galaxies that are as optically luminous as elliptical brightest cluster galaxies, with r-band monochromatic luminosity L_r=8-14L* (4.3-7.5E44 erg/s). These super spiral galaxies are also giant and massive, with diameter D=57-134 kpc and stellar mass M_stars=0.3-3.4E11 M_sun. |
Past studies have long emphasised the key role played by galactic stellar bars in the context of disc secular evolution, via the redistribution of gas and stars, the triggering of star formation, and the formation of prominent structures such as rings and central mass concentrations. However, the exact physical proces... |
Galaxy mergers are crucial to understanding galaxy evolution, therefore we must determine their observational signatures to select them from large IFU galaxy samples such as MUSE and SAMI. We employ 24 high-resolution idealised hydrodynamical galaxy merger simulations based on the "Feedback In Realistic Environmen... |
Statistical studies of X-ray selected Active Galactic Nuclei (AGN) indicate that the fraction of obscured AGN increases with increasing redshift, and the results suggest that a significant part of the accretion growth occurs behind obscuring material in the early universe. We investigate the obscured fraction of highl... |
We report the detection of multiple faint radio sources, that we identify as AGN-jets, within CLJ1449+0856 at z=2 using 3 GHz VLA observations. We study the effects of radio-jet based kinetic feedback at high redshifts, which has been found to be crucial in low redshift clusters to explain the observed thermodynamic p... |
We present multiline CO observations of the complex submillimeter galaxy SMM J00266+1708. Using the Zpectrometer on the Green Bank Telescope, we provide the first precise spectroscopic measurement of its redshift (z=2.742). |
It is well known that the dust properties of the diffuse interstellar medium exhibit variations towards different sight-lines on a large scale. We have investigated the variability of the dust characteristics on a small scale, and from cloud-to-cloud. |
The COSMOS-Web survey is the largest JWST Cycle 1 General Observer program covering a contiguous ~0.54 deg$^2$ area with NIRCam imaging in four broad-band filters and a non-contiguous ~0.2 deg$^2$ with parallel MIRI imaging in a single broad-band filter, F770W. Here we present a comprehensive overview of the MIRI imag... |
We present the results of ALMA observations of dust continuum emission and molecular rotational lines toward a dense core MC27 (aka L1521F) in Taurus, which is considered to be at a very early stage of star formation. The detailed column density distribution on size scales from a few tens AU to ~10,000 AU scale are re... |
Previous studies have shown that star formation depends on the driving of molecular cloud turbulence, and differences in the driving can produce an order of magnitude difference in the star formation rate. The turbulent driving is characterised by the parameter $\zeta$, with $\zeta=0$ for compressive, curl-free drivin... |
We report the discovery of 10-kpc scale [CII] 158um halos surrounding star-forming galaxies in the early Universe. We choose deep ALMA data of 18 galaxies each with a star-formation rate of ~ 10-70 Msun with no signature of AGN whose [CII] lines are individually detected at z=5.153-7.142, and conduct stacking of the [... |
We measured the $12.8\mu$m [NeII] line in the dwarf starburst galaxy He 2-10 with the high-resolution spectrometer TeXeS on the NASA IRTF. The data cube has diffraction-limited spatial resolution $\sim1^{\prime\prime}$ and total velocity resolution including thermal broadening of $\sim5$km/s. |
The observational constraints on the baryon content of the WHIM rely almost entirely on FUV measurements. However, cosmological, hydrodynamical simulations predict strong correlations between the spatial distributions of FUV and X-ray absorbing WHIM. |
Understanding the numerical dependencies that act on the galactic dynamo is a crucial step in determining what resolution and what conditions are required to properly capture the magnetic fields observed in galaxies. Here, we present an extensive study on the numerical dependencies of the galactic dynamo in isolated s... |
Magnetic fields are widely observed in the Universe in virtually all astrophysical objects, from individual stars to entire galaxies, even in the intergalactic medium, but their specific generation has long been debated. Due to the development of more realistic models of galaxy formation, viable scenarios are emerging... |
We report the discovery of 28 candidate high-velocity stars (HVSs) at heliocentric distances of less than 3 kpc, based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 1. Our sample of HVS candidates covers a much broader color range than the equivalent ranges discussed in previou... |
We report on the presence of 6.7-GHz methanol masers, known tracers of high-mass star formation, in the 3-kpc arms of the inner Galaxy. We present 49 detections from the Methanol Multibeam Survey, the largest Galactic plane survey for 6.7-GHz methanol masers, which coincide in longitude, latitude and velocity with the... |
Supermassive black holes (SMBHs) are fundamental keys to understand the formation and evolution of their host galaxies. However, the formation and growth of SMBHs are not yet well understood. |
We use three different techniques to identify hundreds of white dwarf (WD) candidates in the Next Generation Virgo Cluster Survey (NGVS) based on photometry from the NGVS and GUViCS, and proper motions derived from the NGVS and the Sloan Digital Sky Survey (SDSS). Photometric distances for these candidates are calcula... |
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