Read by QxMD icon Read

artificial general intelligence

M Vadiati, A Asghari-Moghaddam, M Nakhaei, J Adamowski, A H Akbarzadeh
Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI)...
October 6, 2016: Journal of Environmental Management
Vedran Dunjko, Jacob M Taylor, Hans J Briegel
The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention...
September 23, 2016: Physical Review Letters
Alessio Bottrighi, Paolo Terenziani
CONTEXT: Several different computer-assisted management systems of computer interpretable guidelines (CIGs) have been developed by the Artificial Intelligence in Medicine community. Each CIG system is characterized by a specific formalism to represent CIGs, and usually provides a manager to acquire, consult and execute them. Though there are several commonalities between most formalisms in the literature, each formalism has its own peculiarities. OBJECTIVE: The goal of our work is to provide a flexible support to the extension or definition of CIGs formalisms, and of their acquisition and execution engines...
September 2016: Artificial Intelligence in Medicine
Giorgio Gemignani, Alessandro Rozza
Motion detection in video streams is a challenging task for several computer vision applications. Indeed, segmentation of moving and static elements in the scene allows to increase the efficiency of several challenging tasks, such as human-computer interface, robot visions, and intelligent surveillance systems. In this paper, we approach motion detection through a multi-layered artificial neural network, which is able to build for each background pixel a multi-modal color distribution evolving over time through self-organization...
November 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Christopher Stanton, Jeff Clune
Natural animals are renowned for their ability to acquire a diverse and general skill set over the course of their lifetime. However, research in artificial intelligence has yet to produce agents that acquire all or even most of the available skills in non-trivial environments. One candidate algorithm for encouraging the production of such individuals is Novelty Search, which pressures organisms to exhibit different behaviors from other individuals. However, we hypothesized that Novelty Search would produce sub-populations of specialists, in which each individual possesses a subset of skills, but no one organism acquires all or most of the skills...
2016: PloS One
Henrik Erikson, Martin Salzmann-Erikson
It is highly likely that artificial intelligence (AI) will be implemented in nursing robotics in various forms, both in medical and surgical robotic instruments, but also as different types of droids and humanoids, physical reinforcements, and also animal/pet robots. Exploring and discussing AI and robotics in nursing and health care before these tools become commonplace is of great importance. We propose that monsters in popular culture might be studied with the hope of learning about situations and relationships that generate empathic capacities in their monstrous existences...
2016: Permanente Journal
Dharshan Kumaran, Demis Hassabis, James L McClelland
We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure...
July 2016: Trends in Cognitive Sciences
Hossam M Zawbaa, Jakub Szlȩk, Crina Grosan, Renata Jachowicz, Aleksander Mendyk
Poly-lactide-co-glycolide (PLGA) is a copolymer of lactic and glycolic acid. Drug release from PLGA microspheres depends not only on polymer properties but also on drug type, particle size, morphology of microspheres, release conditions, etc. Selecting a subset of relevant properties for PLGA is a challenging machine learning task as there are over three hundred features to consider. In this work, we formulate the selection of critical attributes for PLGA as a multiobjective optimization problem with the aim of minimizing the error of predicting the dissolution profile while reducing the number of attributes selected...
2016: PloS One
Michael S C Thomas
Twin studies indicate that the heritability of general cognitive ability - the genetic contribution to individual differences - increases with age. Brant et al. (2013) reported that this increase in heritability occurs earlier in development for low ability children than high ability children. Allied with structural brain imaging results that indicate faster thickening and thinning of cortex for high ability children (Shaw et al., 2006), Brant and colleagues argued higher cognitive ability represents an extended sensitive period for brain development...
June 2016: Developmental Cognitive Neuroscience
A M Corrêa, P E Teodoro, M C Gonçalves, L M A Barroso, M Nascimento, A Santos, F E Torres
Artificial neural networks have been used for various purposes in plant breeding, including use in the investigation of genotype x environment interactions. The aim of this study was to use artificial neural networks in the selection of common bean genotypes with high phenotypic adaptability and stability, and to verify their consistency with the Eberhart and Russell method. Six trials were conducted using 13 genotypes of common bean between 2002 and 2006 in the municipalities of Aquidauana and Dourados. The experimental design was a randomized block with three replicates...
2016: Genetics and Molecular Research: GMR
Randal S Olson, David B Knoester, Christoph Adami
Animal grouping behaviors have been widely studied due to their implications for understanding social intelligence, collective cognition, and potential applications in engineering, artificial intelligence, and robotics. An important biological aspect of these studies is discerning which selection pressures favor the evolution of grouping behavior. In the past decade, researchers have begun using evolutionary computation to study the evolutionary effects of these selection pressures in predator-prey models. The selfish herd hypothesis states that concentrated groups arise because prey selfishly attempt to place their conspecifics between themselves and the predator, thus causing an endless cycle of movement toward the center of the group...
2016: Artificial Life
Thomas B Sheridan
OBJECTIVE: The current status of human-robot interaction (HRI) is reviewed, and key current research challenges for the human factors community are described. BACKGROUND: Robots have evolved from continuous human-controlled master-slave servomechanisms for handling nuclear waste to a broad range of robots incorporating artificial intelligence for many applications and under human supervisory control. METHODS: This mini-review describes HRI developments in four application areas and what are the challenges for human factors research...
June 2016: Human Factors
Halis Simsek
Wastewater-derived dissolved organic nitrogen (DON) typically constitutes the majority of total dissolved nitrogen (TDN) discharged to surface waters from advanced wastewater treatment plants (WWTPs). When considering the stringent regulations on nitrogen discharge limits in sensitive receiving waters, DON becomes problematic and needs to be reduced. Biodegradable DON (BDON) is a portion of DON that is biologically degradable by bacteria when the optimum environmental conditions are met. BDON in a two-stage trickling filter WWTP was estimated using artificial intelligence techniques, such as adaptive neuro-fuzzy inference systems, multilayer perceptron, radial basis neural networks (RBNN), and generalized regression neural networks...
November 2016: Environmental Technology
Nina C Franklin, Ross Arena
Obesity is an independent contributor to cardiovascular disease (CVD) and a major driving force behind racial/ethnic and gender disparities in risk. Due to a multitude of interrelating factors (i.e., personal, social, cultural, economic and environmental), African-American (AA) women are disproportionately obese and twice as likely to succumb to CVD, yet they are significantly underrepresented in behavioral weight management interventions. In this selective review we highlight components of the limited interventions shown to enhance weight loss outcomes in this population and make a case for leveraging Web-based technology and artificial intelligence techniques to deliver personalized programs aimed at obesity treatment and CVD risk reduction...
May 2016: Progress in Cardiovascular Diseases
Jianjun Ni, Liuying Wu, Xinnan Fan, Simon X Yang
Bioinspired intelligent algorithm (BIA) is a kind of intelligent computing method, which is with a more lifelike biological working mechanism than other types. BIAs have made significant progress in both understanding of the neuroscience and biological systems and applying to various fields. Mobile robot control is one of the main application fields of BIAs which has attracted more and more attention, because mobile robots can be used widely and general artificial intelligent algorithms meet a development bottleneck in this field, such as complex computing and the dependence on high-precision sensors...
2016: Computational Intelligence and Neuroscience
Gabriel Oltean, Laura-Nicoleta Ivanciu
The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system...
2016: PloS One
Seok-Ki Jung, Tae-Woo Kim
INTRODUCTION: The decision to extract teeth for orthodontic treatment is important and difficult because it tends to be based on the practitioner's experiences. The purposes of this study were to construct an artificial intelligence expert system for the diagnosis of extractions using neural network machine learning and to evaluate the performance of this model. METHODS: The subjects included 156 patients. Input data consisted of 12 cephalometric variables and an additional 6 indexes...
January 2016: American Journal of Orthodontics and Dentofacial Orthopedics
Karl Gustafson
Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof) in artificial, human and quantum cognition and decision-making processes. Then I will look in more detail at some of the 'engineering details' of its implementation (or lack thereof) in each of these settings. In other words, the question posed is: What is actually happening? For example, we previously found that humans overwhelmingly seek, create or imagine context in order to provide meaning when presented with abstract, apparently incomplete, contradictory or otherwise untenable decision-making situations...
January 13, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
Tansel Ozyer, Serkan Ucer, Taylan Iyidogan
Detection of disease biomarkers in general and cancer biomarkers in particular is an important task which has received considerable attention in the area of in silico genomic experiments. We describe a new approach for detecting cancer biomarkers based on genomic microarray data; it is characterised by employing Social Network Analysis (SNA) techniques. Through social interaction perspective, we can have genes as actors in a social network, where similarities between genes can be described as connections between these actors...
2015: International Journal of Data Mining and Bioinformatics
Purva Goel, Sanket Bapat, Renu Vyas, Amruta Tambe, Sanjeev S Tambe
The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI)...
November 13, 2015: Journal of Chromatography. A
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"