96 research outputs found
A Model of Attention and Interest Using Gaze Behavior
No full textOne of the major problems of user’s interaction with Embodied Conversational Agents (ECAs) is to have the conversation last more than few second:after being amused and intrigued by the ECAs, users may find rapidly the restrictions and limitations of the dialog systems, they may perceive the repetition of the ECAs animation, they may find the behaviors of ECAs to be inconsistent and implausible, etc. We believe that some special links, or bonds, have to be established between users and ECAs during interaction. It is our view that showing and/or perceiving interest is the necessary premise to establish a relationship. In this paper we present a model of an ECA able to establish, maintain and end the conversation based on its perception of the level of interest of its interlocutor
Emerging applications of machine learning in genomic medicine and healthcare
No full textThe integration of artificial intelligence technologies has propelled the progress of clinical and genomic medicine in recent years. The significant increase in computing power has facilitated the ability of artificial intelligence models to analyze and extract features from extensive medical data and images, thereby contributing to the advancement of intelligent diagnostic tools. Artificial intelligence (AI) models have been utilized in the field of personalized medicine to integrate clinical data and genomic information of patients. This integration allows for the identification of customized treatment recommendations, ultimately leading to enhanced patient outcomes. Notwithstanding the notable advancements, the application of artificial intelligence (AI) in the field of medicine is impeded by various obstacles such as the limited availability of clinical and genomic data, the diversity of datasets, ethical implications, and the inconclusive interpretation of AI models' results. In this review, a comprehensive evaluation of multiple machine learning algorithms utilized in the fields of clinical and genomic medicine is conducted. Furthermore, we present an overview of the implementation of artificial intelligence (AI) in the fields of clinical medicine, drug discovery, and genomic medicine. Finally, a number of constraints pertaining to the implementation of artificial intelligence within the healthcare industry are examined
The Behavior Markup Language: Recent Developments and Challenges
No full textVilhjalmsson H, Cantelmo N, Cassell J, Chafai NE, Kipp M, Kopp S. The Behavior Markup Language: Recent Developments and Challenges. In: Proc. of Intelligent Virtual Agents (IVA 2007). LNAI. Vol 4722. Berlin, Heidelberg: Springer; 2007: 99-111.Since the beginning of the SAIBA effort to unify key interfaces in the multi-modal behavior generation process, the Behavior Markup Language (BML) has both gained ground as an important component in many projects worldwide, and continues to undergo further refinement. This paper reports on the progress made in the last year in further developing BML. It discusses some of the key challenges identified that the effort is facing, and reviews a number of projects that already are making use of BML or support its use
Experimental and detailed DFT/MD simulation of α-aminophosphonates as promising corrosion inhibitor for XC48 carbon steel in HCl environment
No full textBackground: Corrosion is a pervasive issue in several industries, causing safety hazards and substantial economic losses. α-aminophosphonate substances have recently garnered attention for their ability to inhibit corrosion. In this study, two specific α-aminophosphonate molecules, namely diethyl(furan-2-yl(phenylamino)methyl) phosphonate (AMP1) and diethyl((2methoxyphenyl) amino) (thiophene-2-methyl) phosphonate (AMP2) were evaluated for their potential as anticorrosion agents for XC48 carbon steel under acidic conditions. Methods: Their corrosion inhibition was examined towards XC48 carbon steel under 1.0 M HCl solution utilizing the electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP), atomic force microscope (AFM), scanning electron microscope (SEM), contact angle, Density functional theory (DFT), molecular dynamics (MD), and atoms in molecule (AIM). Significant findings: Results showed that AMP1 and AMP2 had inhibition efficiencies of 83.34% and 63.82% for EIS and 82.70% and 74.57% for PDP, respectively. The inhibition mechanism involved adsorption of the additives onto the metal surface via Langmuir isotherm. The study also demonstrated the influence of temperature on inhibition efficiency, with nearly 70% inhibition observed at 298 to 323 K. AFM and SEM analyses revealed chemisorption coating formation inhibiting acid attack, and contact angle analyses showed the surface to be hydrophobic. Theoretical analyses using DFT, MD, and AIM were used to clarify the inhibitors' adsorption effect on XC48 steel, showing a high agreement with experimental findings
Circular law for non-central random matrices
No full textaccepted in Journal of Theoretical ProbabilityInternational audienceLet be an infinite array of i.i.d. complex random variables, with mean and variance . Let \la_{n,1},\ldots,\la_{n,n} be the eigenvalues of . The strong circular law theorem states that with probability one, the empirical spectral distribution \frac{1}{n}(\de_{\la_{n,1}}+\cdots+\de_{\la_{n,n}}) converges weakly as to the uniform law over the unit disc \{z\in\dC;|z|\leq1\}. In this short note, we provide an elementary argument that allows to add a deterministic matrix to provided that and \mathrm{rank}(M)=O(n^\al) with \al<1. Conveniently, the argument is similar to the one used for the non-central version of Wigner's and Marchenko-Pastur theorems
Confidence Regions for the Multinomial Parameter With Small Sample Size
No full textConsider the observation of n iid realizations of an experiment with d >= 2 possible outcomes, which corresponds to a single observation of a multinomial distribution M_d(n; p) where p is an unknown discrete distribution on \{1,...,d\}. In many applications, the construction of a confidence region for p when n is small is crucial. This
concrete challenging problem has a long history. It is well known that the confidence regions built from asymptotic statistics do not have good coverage when n is small.
On the other hand, most available methods providing non-asymptotic regions with controlled coverage are limited to the binomial case d = 2. In the present work, we
propose a new method valid for any d >= 2. This method provides condence regions with controlled coverage and small volume, and consists in the inversion of the "cover-
ing collection" associated to level-sets of the likelihood. The behavior when d=n tends to infinity remains an interesting open problem beyond the scope of this work
Circular law for random matrices with unconditional log-concave distribution
No full textWe explore the validity of the circular law for random matrices with non-i.i.d. entries. Let M be an n × n random real matrix obeying, as a real random vector, a log-concave isotropic (up to normalization) unconditional law, with mean squared norm equal to n. The entries are uncorrelated and obey a symmetric law of zero mean and variance 1/n. This model allows some dependence and non-equidistribution among the entries, while keeping the special case of i.i.d. standard Gaussian entries, known as the real Ginibre Ensemble. Our main result states that as the dimension n goes to infinity, the empirical spectral distribution of M tends to the uniform law on the unit disc of the complex plane
Large squirrel cage induction motor reliability modelling
No full textIn this study a simplified reliability model is developed on the basis of knowledge, from field data, of the dominating failure modes and mechanisms of large power squirrel cage induction motors operating at constant speed and fed from a conventional 3 phase sinusoidal supply voltage. Field data failures distribution indicates a dominance of failure modes pertaining to machine bearings and stator winding insulation. The motor system can be regarded as a complex combination of three fundamental parts: The stator, the rotor and the bearings which are respectively electrical, electromechanical and mechanical in nature. On this basis, the motor system reliability block diagram is modelled in a series configuration comprising the above mentioned parts. The individual reliability functions developed for each part will yield together the overall motor system reliabilit
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