Search results for "artificial intelligence"

The perception loop in CiceRobot, a museum guide robot

2009

The paper discusses a model of robot perception based on a comparison loop process between the actual and the expected robot input sensory data generated by a 3D robot/environment simulator. The perception loop process is operating in CiceRobot, a functional robot architecture implemented on an autonomous robot RWI B21 offering guided tours at the Archaeological Museum of Agrigento, Italy.

Pettis integrability of fuzzy mappings with values in arbitrary Banach spaces

2017

Abstract In this paper we study the Pettis integral of fuzzy mappings in arbitrary Banach spaces. We present some properties of the Pettis integral of fuzzy mappings and we give conditions under which a scalarly integrable fuzzy mapping is Pettis integrable.

COVID-19 … What are drugs and strategies now?

2020

From February 2019 the World faces the Covid19 pandemic. The data in our possession are still insufficient to effectively combat this pathology. The gold standard for diagnosis remains molecular testing, while clinical and instrumental and serological diagnostics are highly nonspecific leading to a slowdown in the battle against covid19.[3] Can Artificial Intelligence (AI) and Machine Learning (ML) help us? The use of large databases to cross-reference data to stratify the diagnostic scores, to quickly differentiate a critical Covid-19 patient from a non-critical one is the challenge of the future. All to achieve better management of resources in the field and a more effective therapeutic a…

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives.

2021

Abstract Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era…

Multivariate equivalence tests for use in pharmaceutical development.

2014

Statistical equivalence analyses are well-established parts of many studies in the biomedical sciences. Also in pharmaceutical development and manufacturing equivalence testing methods are required in order to statistically establish similarities between machines, process components, or complete processes. This article presents a choice of multivariate equivalence testing procedures for normally distributed data as generalizations of existing univariate methods. In all derived methods, variability is interpreted as nuisance parameter. The use of the proposed methods in pharmaceutical development is demonstrated with a comparative analysis of dissolution profiles.

Introduction to molecular topology: basic concepts and application to drug design.

2012

In this review it is dealt the use of molecular topology (MT) in the selection and design of new drugs. After an introduction of the actual methods used for drug design, the basic concepts of MT are defined, including examples of calculation of topological indices, which are numerical descriptors of molecular structures. The goal is making this calculation familiar to the potential students and allowing a straightforward comprehension of the topic. Finally, the achievements obtained in this field are detailed, so that the reader can figure out the great interest of this approach.

The Prediction of Human Intestinal Absorption Based on the Molecular Structure

2014

Human Intestinal Absorption (HIA) has been modeled many times by using classification models. However, regression models are scarce. Here, Artificial Neural Networks (ANNs) are implemented for this purpose. A dataset of structurally diverse chemicals with their respective experimental HIA were used to design robust, true predictive and widespread applicable ANN models. An input variables pool was made up of structural invariants calculated by using either Dragon or our software Desmol 1. The selection of best variables was performed following three steps using the entire dataset of molecules. Firstly, variables poorly correlated with the experimental data were eliminated. Secondly, input va…

Classical and Connectionist Models: Levels of Description

1993

To begin, I introduce an analysis of interlevel relations that allows us to offer an initial characterization of the debate about the way classical and connectionist models relate. Subsequently, I examine a compatibility thesis and a conditional claim on this issue. With respect to the compatibility thesis, I argue that, even if classical and connectionist models are not necessarily incompatible, the emergence of the latter seems to undermine the best arguments for the Language of Thought Hypothesis, which is essential to the former. I attack the conditional claim of connectionism to eliminativism, presented by Ramsey et al. (1990), by discrediting their discrete characterization of common-…

Truth and Ontology

2010

Paraconsistent logics, conventionalism and ontology

2004

Paraconsistent logics may be viewed as one of the last elements in a series of rapid developments in science in the 19th and early 20th c., triggered by the appearance of non-Euclidean geometries. The philosophy of conventionalism, which gave a metatheoretical framework to the basic changes involved, may also help in evaluating the truth import of (paraconsistent) logic and in determining its relation to ontology.