Artificial intelligence approaches in statistics

International Nuclear Information System (INIS)

Phelps, R.I.; Musgrove, P.B.

1986-01-01

The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed

Biology and fertility life table of Agrotis ipsilon on artificial diet

International Nuclear Information System (INIS)

Bento, Flavia de Moura Manoel; Fortes, Priscila; Zerio, Neide Graciano; Parra, Jose Roberto Postali

2007-01-01

The objective of this work was to develop an artificial diet to rear Agrotis ipsilon in laboratory using biological parameters and fertility life table. The artificial diet was prepared with bean, casein, soybean protein, yeast and wheat germ as protein sources. The biological aspects duration and viability of larval and pupal stages, pupal weight, sex ratio, life span of adults, preoviposition period, egg laying capacity and fertility life table were evaluated. Six larval instars were observed comprising larval duration of 28,4 days and 93% of viability mean pupal duration of 12,4 days and viability of 96%. The total viability of the life cycle was 72%. The pupae weight was 387 mg for males and 484 mg for females. The sex ratio was 0,46 and the preoviposition period lasted one day and egg laying was 1,806 eggs per female. The net reproductive rate per generation and increase finite rate were 616,9 and 1,14, respectively. Artificial diet is adequate for rearing A. ipsilon in laboratory. (author)

Recent Theoretical Approaches to Minimal Artificial Cells

Directory of Open Access Journals (Sweden)

Fabio Mavelli

2014-05-01

Full Text Available Minimal artificial cells (MACs are self-assembled chemical systems able to mimic the behavior of living cells at a minimal level, i.e. to exhibit self-maintenance, self-reproduction and the capability of evolution. The bottom-up approach to the construction of MACs is mainly based on the encapsulation of chemical reacting systems inside lipid vesicles, i.e. chemical systems enclosed (compartmentalized by a double-layered lipid membrane. Several researchers are currently interested in synthesizing such simple cellular models for biotechnological purposes or for investigating origin of life scenarios. Within this context, the properties of lipid vesicles (e.g., their stability, permeability, growth dynamics, potential to host reactions or undergo division processes… play a central role, in combination with the dynamics of the encapsulated chemical or biochemical networks. Thus, from a theoretical standpoint, it is very important to develop kinetic equations in order to explore first—and specify later—the conditions that allow the robust implementation of these complex chemically reacting systems, as well as their controlled reproduction. Due to being compartmentalized in small volumes, the population of reacting molecules can be very low in terms of the number of molecules and therefore their behavior becomes highly affected by stochastic effects both in the time course of reactions and in occupancy distribution among the vesicle population. In this short review we report our mathematical approaches to model artificial cell systems in this complex scenario by giving a summary of three recent simulations studies on the topic of primitive cell (protocell systems.

Integrated Artificial Intelligence Approaches for Disease Diagnostics.

Science.gov (United States)

Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

2018-06-01

Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.

Forecasting daily lake levels using artificial intelligence approaches

Science.gov (United States)

Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

2012-04-01

Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

Transport modeling: An artificial immune system approach

Directory of Open Access Journals (Sweden)

Teodorović Dušan

2006-01-01

Full Text Available This paper describes an artificial immune system approach (AIS to modeling time-dependent (dynamic, real time transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies for different antigens (different traffic "scenarios". This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

Machine learning an artificial intelligence approach

CERN Document Server

Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

1983-01-01

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

Artificial Life as an Aid to Astrobiology: Testing Life Seeking Techniques

OpenAIRE

Centler, F.; Dittrich, P.; Ku, L.; Matsumaru, N.; Pfaffmann, J.; Zauner, K.-P.

2003-01-01

Searching for signatures of fossil or present life in our solar system requires autonomous devices capable of investigating remote locations with limited assistance from earth. Here, we use an artificial chemistry model to create spatially complex chemical environments. An autonomous experimentation technique based on evolutionary computation is then employed to explore these environments with the aim of discovering the chemical signature of small patches of biota present in the simulation sp...

Natural - synthetic - artificial!

DEFF Research Database (Denmark)

Nielsen, Peter E

2010-01-01

The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

A comprehensive overview of the applications of artificial life.

Science.gov (United States)

Kim, Kyung-Joong; Cho, Sung-Bae

2006-01-01

We review the applications of artificial life (ALife), the creation of synthetic life on computers to study, simulate, and understand living systems. The definition and features of ALife are shown by application studies. ALife application fields treated include robot control, robot manufacturing, practical robots, computer graphics, natural phenomenon modeling, entertainment, games, music, economics, Internet, information processing, industrial design, simulation software, electronics, security, data mining, and telecommunications. In order to show the status of ALife application research, this review primarily features a survey of about 180 ALife application articles rather than a selected representation of a few articles. Evolutionary computation is the most popular method for designing such applications, but recently swarm intelligence, artificial immune network, and agent-based modeling have also produced results. Applications were initially restricted to the robotics and computer graphics, but presently, many different applications in engineering areas are of interest.

Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

Directory of Open Access Journals (Sweden)

Ye Tian

2014-01-01

Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

Artificial-life researchers try to create social reality.

Science.gov (United States)

Flam, F

1994-08-12

Some scientists, among them cosmologist Stephen Hawking, argue that computer viruses are alive. A better case might be made for many of the self-replicating silicon-based creatures featured at the fourth Conference on Artificial Life, held on 5 to 8 July in Boston. Researchers from computer science, biology, and other disciplines presented computer programs that, among other things, evolved cooperative strategies in a selfish world and recreated themselves in ever more complex forms.

Biology and fertility life table of Agrotis ipsilon on artificial diet; Biologia e tabela de vida de fertilidade de Agrotis ipsilon em dieta artificial

Energy Technology Data Exchange (ETDEWEB)

Bento, Flavia de Moura Manoel; Fortes, Priscila; Zerio, Neide Graciano; Parra, Jose Roberto Postali [Universidade de Sao Paulo (USP), Piracicaba, SP (Brazil). Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Dept. Entomologia, Fitopatologia e Zoologia Agricola]. E-mail: flaviam@esalq.usp.br, pfortes@esalq.usp.br, ngzerio@esalq.usp.br, jrpparra@esalq.usp.br; Magro, Sandra Regina [Universidade Camilo Castelo Branco, Fernandopolis, SP (Brazil)]. E-mail: sandra.magro@gmail.com

2007-10-15

The objective of this work was to develop an artificial diet to rear Agrotis ipsilon in laboratory using biological parameters and fertility life table. The artificial diet was prepared with bean, casein, soybean protein, yeast and wheat germ as protein sources. The biological aspects duration and viability of larval and pupal stages, pupal weight, sex ratio, life span of adults, preoviposition period, egg laying capacity and fertility life table were evaluated. Six larval instars were observed comprising larval duration of 28,4 days and 93% of viability mean pupal duration of 12,4 days and viability of 96%. The total viability of the life cycle was 72%. The pupae weight was 387 mg for males and 484 mg for females. The sex ratio was 0,46 and the preoviposition period lasted one day and egg laying was 1,806 eggs per female. The net reproductive rate per generation and increase finite rate were 616,9 and 1,14, respectively. Artificial diet is adequate for rearing A. ipsilon in laboratory. (author)

Ethical Analysis of Withdrawing Total Artificial Heart Support.

Science.gov (United States)

DeMartino, Erin S; Wordingham, Sara E; Stulak, John M; Boilson, Barry A; Fuechtmann, Kayla R; Singh, Nausheen; Sulmasy, Daniel P; Pajaro, Octavio E; Mueller, Paul S

2017-05-01

To describe the characteristics of patients who undergo withdrawal of total artificial heart support and to explore the ethical aspects of withdrawing this life-sustaining treatment. We retrospectively reviewed the medical records of all adult recipients of a total artificial heart at Mayo Clinic from the program's inception in 2007 through June 30, 2015. Management of other life-sustaining therapies, approach to end-of-life decision making, engagement of ethics and palliative care consultation, and causes of death were analyzed. Of 47 total artificial heart recipients, 14 patients or their surrogates (30%) requested withdrawal of total artificial heart support. No request was denied by treatment teams. All 14 patients were supported with at least 1 other life-sustaining therapy. Only 1 patient was able to participate in decision making. It is widely held to be ethically permissible to withdraw a life-sustaining treatment when the treatment no longer meets the patient's health care-related goals (ie, the burdens outweigh the benefits). These data suggest that some patients, surrogates, physicians, and other care providers believe that this principle extends to the withdrawal of total artificial heart support. Copyright © 2017 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

The essential Turing Seminal writings in computing, logic, philosophy, artificial intelligence, and artificial life plus the secrets of enigma

CERN Document Server

2004-01-01

The ideas that gave birth to the computer age. Alan Turing, pioneer of computing and WWII codebreaker, was one of the most important and influential thinkers of the twentieth century. In this volume for the first time his key writings are made available to a broad, non-specialist readership. They make fascinating reading both in their own right and for their historic significance: contemporary computational theory, cognitive science, artificial intelligence, and artificial life all spring from this ground-breaking work, which is also rich. in philosophical and logical insight. An introduction

A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

Directory of Open Access Journals (Sweden)

Ali Akbar Ziaee

2012-02-01

Full Text Available Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important challenges will be the quality of representing the Islamic values like piety, obedience, Halal and Haram, and etc in the form of semantics. In this paper, I want to emphasize on the role of Divine Islamic values in the application of AI and discuss it according to philosophy of AI and Islamic perspective.Keywords- Value, expert, Community Development, Artificial Intelligence, Superintelligence, Friendly Artificial Intelligence

Artificial neuron-glia networks learning approach based on cooperative coevolution.

Science.gov (United States)

Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

2015-06-01

Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

WebAL Comes of Age: A review of the first 21 years of Artificial Life on the Web

DEFF Research Database (Denmark)

Taylor, Tim; Auerbach, Joshua E; Bongard, Josh

2016-01-01

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994—when the first WebAL work appeared...

Risk prediction model: Statistical and artificial neural network approach

Science.gov (United States)

Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

2017-04-01

Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

Science.gov (United States)

Broderick, Ron

1997-01-01

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

Life Span Developmental Approach

Directory of Open Access Journals (Sweden)

Ali Eryilmaz

2011-03-01

Full Text Available The Life Span Developmental Approach examines development of individuals which occurs from birth to death. Life span developmental approach is a multi-disciplinary approach related with disciplines like psychology, psychiatry, sociology, anthropology and geriatrics that indicates the fact that development is not completed in adulthood, it continues during the life course. Development is a complex process that consists of dying and death. This approach carefully investigates the development of individuals with respect to developmental stages. This developmental approach suggests that scientific disciplines should not explain developmental facts only with age changes. Along with aging, cognitive, biological, and socioemotional development throughout life should also be considered to provide a reasonable and acceptable context, guideposts, and reasonable expectations for the person. There are three important subjects whom life span developmental approach deals with. These are nature vs nurture, continuity vs discontinuity, and change vs stability. Researchers using life span developmental approach gather and produce knowledge on these three most important domains of individual development with their unique scientific methodology.

An artificial intelligence approach to well log correlation

International Nuclear Information System (INIS)

Startzman, R.A.; Kuo, T.B.

1986-01-01

This paper shows how an expert computer system was developed to correlate two well logs in at least moderately difficult situations. A four step process was devised to process log trace information and apply a set of rules to identify zonal correlations. Some of the advantages and problems with the artificial intelligence approach are shown using field logs. The approach is useful and, if properly and systematically applied, it can result in good correlations

Life History Approach

DEFF Research Database (Denmark)

Olesen, Henning Salling

2015-01-01

as in everyday life. Life histories represent lived lives past, present and anticipated future. As such they are interpretations of individuals’ experiences of the way in which societal dynamics take place in the individual body and mind, either by the individual him/herself or by another biographer. The Life...... History approach was developing from interpreting autobiographical and later certain other forms of language interactive material as moments of life history, i.e. it is basically a hermeneutic approach. Talking about a psycho-societal approach indicates the ambition of attacking the dichotomy...... of the social and the psychic, both in the interpretation procedure and in some main theoretical understandings of language, body and mind. My article will present the reflections on the use of life history based methodology in learning and education research as a kind of learning story of research work....

Life Span Developmental Approach

OpenAIRE

Ali Eryilmaz

2011-01-01

The Life Span Developmental Approach examines development of individuals which occurs from birth to death. Life span developmental approach is a multi-disciplinary approach related with disciplines like psychology, psychiatry, sociology, anthropology and geriatrics that indicates the fact that development is not completed in adulthood, it continues during the life course. Development is a complex process that consists of dying and death. This approach carefully investigates the development of...

An Artificial Intelligence Approach to Transient Stability Assessment

OpenAIRE

Akella, Vijay Ahaskar; Khincha, HP; Kumar, Sreerama R

1991-01-01

An artificial intelligence approach to online transient stability assessment is briefly discussed, and some crucial requirements for this algorithm are identified. Solutions to these are proposed. Some new attributes are suggested so as to reflect machine dynamics and changes in the network. Also a new representative learning set algorithm has been developed.

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

Science.gov (United States)

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

An artificial neural network approach and sensitivity analysis in predicting skeletal muscle forces.

Science.gov (United States)

Vilimek, Miloslav

2014-01-01

This paper presents the use of an artificial neural network (NN) approach for predicting the muscle forces around the elbow joint. The main goal was to create an artificial NN which could predict the musculotendon forces for any general muscle without significant errors. The input parameters for the network were morphological and anatomical musculotendon parameters, plus an activation level experimentally measured during a flexion/extension movement in the elbow. The muscle forces calculated by the 'Virtual Muscle System' provide the output. The cross-correlation coefficient expressing the ability of an artificial NN to predict the "true" force was in the range 0.97-0.98. A sensitivity analysis was used to eliminate the less sensitive inputs, and the final number of inputs for a sufficient prediction was nine. A variant of an artificial NN for a single specific muscle was also studied. The artificial NN for one specific muscle gives better results than a network for general muscles. This method is a good alternative to other approaches to calculation of muscle force.

A Flexible Approach for Human Activity Recognition Using Artificial Hydrocarbon Networks.

Science.gov (United States)

Ponce, Hiram; Miralles-Pechuán, Luis; Martínez-Villaseñor, María de Lourdes

2016-10-25

Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior in order to deliver proactive and personalized services. Although many activity recognition systems have been developed for more than two decades, there are still open issues to be tackled with new techniques. We address in this paper one of the main challenges of human activity recognition: Flexibility. Our goal in this work is to present artificial hydrocarbon networks as a novel flexible approach in a human activity recognition system. In order to evaluate the performance of artificial hydrocarbon networks based classifier, experimentation was designed for user-independent, and also for user-dependent case scenarios. Our results demonstrate that artificial hydrocarbon networks classifier is flexible enough to be used when building a human activity recognition system with either user-dependent or user-independent approaches.

Discrepancies in the use of chemotherapy and artificial nutrition near the end of life for hospitalised patients with metastatic gastric or oesophageal cancer. A countrywide, register-based study.

Science.gov (United States)

Kempf, Emmanuelle; Tournigand, Christophe; Rochigneux, Philippe; Aubry, Régis; Morin, Lucas

2017-07-01

To evaluate the frequency and the factors associated with the use of chemotherapy and artificial nutrition near the end of life in hospitalised patients with metastatic oesophageal or gastric cancer. Nationwide, register-based study, including all hospitalised adults (≥20 years) who died with metastatic oesophageal or gastric cancer between 2010 and 2013, in France. Chemotherapy and artificial nutrition during the final weeks of life were considered as primary outcomes. A total of 4031 patients with oesophageal cancer and 10,423 patients with gastric cancer were included. While the proportion of patients receiving chemotherapy decreased from 35.9% during the 3rd month before death to 7.9% in the final week (p nutrition rose from 9.6% to 16.0% of patients. During the last week before death, patients with stomach cancer were more likely to receive chemotherapy (adjusted odds ratio (aOR) = 1.35, 95% CI = 1.17-1.56) but less likely to receive artificial nutrition (aOR = 0.80, 95%CI = 0.73-0.88) than patients with cancer of the oesophagus. The adjusted rates of chemotherapy use during the last week of life varied from 1.6% in rural hospitals to 11.2% in comprehensive cancer centres, while the adjusted probability to receive artificial nutrition varied from 12.1% in private for-profit clinics up to 19.9% in rehabilitation care facilities (p gastric cancer, the use of chemotherapy decreases while the use of artificial nutrition increases as death approaches. This raises important questions, as clinical guidelines clearly recommend to limit the use of artificial nutrition in contexts of limited life expectancy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Control approach development for variable recruitment artificial muscles

Science.gov (United States)

Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

2016-04-01

This study characterizes hybrid control approaches for the variable recruitment of fluidic artificial muscles with double acting (antagonistic) actuation. Fluidic artificial muscle actuators have been explored by researchers due to their natural compliance, high force-to-weight ratio, and low cost of fabrication. Previous studies have attempted to improve system efficiency of the actuators through variable recruitment, i.e. using discrete changes in the number of active actuators. While current variable recruitment research utilizes manual valve switching, this paper details the current development of an online variable recruitment control scheme. By continuously controlling applied pressure and discretely controlling the number of active actuators, operation in the lowest possible recruitment state is ensured and working fluid consumption is minimized. Results provide insight into switching control scheme effects on working fluids, fabrication material choices, actuator modeling, and controller development decisions.

Biologia e tabela de vida de fertilidade de Agrotis ipsilon em dieta artificial Biology and fertility life table of Agrotis ipsilon on artificial diet

Directory of Open Access Journals (Sweden)

Flavia de Moura Manoel Bento

2007-10-01

Full Text Available O objetivo deste trabalho foi desenvolver uma dieta artificial para criação de Agrotis ipsilon em laboratório com base em parâmetros biológicos e na tabela de vida de fertilidade. A dieta artificial utilizada continha feijão, caseína, proteína de soja, levedura e germe de trigo como fontes protéicas. Os parâmetros biológicos duração e viabilidade das fases larval e pupal, peso de pupas, de ambos os sexos, com 24 horas de idade, razão sexual, longevidade dos adultos, período de pré-oviposição e número de ovos produzidos por fêmea e a tabela de vida de fertilidade foram avaliados. Foram observados seis ínstares larvais com duração de 25,4 dias e viabilidade de 93%. A duração da fase pupal foi de 12,4 dias e viabilidade de 96%. A viabilidade de ciclo total foi 72%. O peso de pupas foi 387 mg (machos e 484 mg (fêmeas. A razão sexual foi 0,46. O período de pré-oviposição foi de um dia, com 1.806 ovos por fêmea. Na tabela de vida verificou-se que a taxa líquida de reprodução e a razão finita de aumento foram 616,9 e 1,14, respectivamente. A dieta artificial é adequada à manutenção da criação de A. ipsilon, em laboratório.The objective of this work was to develop an artificial diet to rear Agrotis ipsilon in laboratory using biological parameters and fertility life table. The artificial diet was prepared with bean, casein, soybean protein, yeast and wheat germ as protein sources. The biological aspects duration and viability of larval and pupal stages, pupal weight, sex ratio, life span of adults, preoviposition period, egg laying capacity and fertility life table were evaluated. Six larval instars were observed comprising larval duration of 28,4 days and 93% of viability mean pupal duration of 12,4 days and viability of 96%. The total viability of the life cycle was 72%. The pupae weight was 387 mg for males and 484 mg for females. The sex ratio was 0,46 and the preoviposition period lasted one day and egg

Application of artificial tactile sensing approach in kidney-stone-removal laparoscopy.

Science.gov (United States)

Afshari, Elnaz; Najarian, Siamak; Simforoosh, Nasser

2010-01-01

Artificial tactile sensing is a novel method for obtaining different characteristics of a hard object embedded in a soft tissue. In this regard, artificial palpation is one of the most valuable achievements of artificial tactile sensing that can be used in various fields of medicine and more specifically in surgery. In this study, considering the present problems and limitations in kidney-stone-removal laparoscopy, a new application will be presented for artificial tactile sensing approach. Having imitated surgeon's palpation during open surgery and modeled it conceptually, indications of stone existence that appear on the surface of kidney (due to exerting mechanical load) were determined. A number of different cases were created and solved by the software. Using stress distribution contours and stress graphs, it is illustrated that the created stress patterns on the surface of kidney not only show the existence of stone inside, but also its exact location. In fact, the reliability and accuracy of artificial tactile sensing method in detection of kidney stone during laparoscopy is demonstrated by means of finite element analysis. Also, in this paper, the functional principles of tactile system capable of determining the exact location of stone during laparoscopy will be presented.

Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches

OpenAIRE

Lehký , David; Slowik , Ondřej; Novák , Drahomír

2014-01-01

Part 7: Genetic Algorithms; International audience; The paper presents two alternative approaches to solve inverse reliability task – to determine the design parameters to achieve desired target reliabilities. The first approach is based on utilization of artificial neural networks and small-sample simulation Latin hypercube sampling. The second approach considers inverse reliability task as reliability-based optimization task using double-loop method and also small-sample simulation. Efficie...

Artificial intelligence approach to interwell log correlation

Energy Technology Data Exchange (ETDEWEB)

Lim, Jong-Se [Korea Maritime University, Pusan(Korea); Kang, Joo Myung [Seoul National University, Seoul(Korea); Kim, Jung Whan [Korea National Oil Corp., Anyang(Korea)

2000-04-30

This paper describes a new approach to automated interwell log correlation using artificial intelligence and principal component analysis. The approach to correlate wire line logging data is on the basis of a large set of subjective rules that are intended to represent human logical processes. The data processed are mainly the qualitative information such as the characteristics of the shapes extracted along log traces. The apparent geologic zones are identified by pattern recognition for the specific characteristics of log trace collected as a set of objects by object oriented programming. The correlation of zones between wells is made by rule-based inference program. The reliable correlation can be established from the first principal component logs derived from both the important information around well bore and the largest common part of variances of all available well log data. Correlation with field log data shows that this approach can make interwell log correlation more reliable and accurate. (author). 6 refs., 7 figs.

Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units

International Nuclear Information System (INIS)

Santos Coelho, Leandro dos; Mariani, Viviana Cocco

2009-01-01

The economic dispatch problem (EDP) is an optimization problem useful in power systems operation. The objective of the EDP of electric power generation, whose characteristics are complex and highly non-linear, is to schedule the committed generating unit outputs so as to meet the required load demand at minimum operating cost while satisfying system constraints. Recently, as an alternative to the conventional mathematical approaches, modern heuristic optimization techniques have been given much attention by many researchers due to their ability to find an almost global optimal solution in EDPs. As special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used as optimization technique in EDPs. Based on the chaos theory, this paper discusses the design and validation of an optimization procedure based on a chaotic artificial immune network approach based on Zaslavsky's map. The optimization approach based on chaotic artificial immune network is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. Simulation results and comparisons show that the chaotic artificial immune network approach is competitive in performance with other optimization approaches presented in literature and is also an attractive tool to be used on applications in the power systems field.

Artificial Consciousness or Artificial Intelligence

Directory of Open Access Journals (Sweden)

Spanache Florin

2017-05-01

Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web.

Science.gov (United States)

Taylor, Tim; Auerbach, Joshua E; Bongard, Josh; Clune, Jeff; Hickinbotham, Simon; Ofria, Charles; Oka, Mizuki; Risi, Sebastian; Stanley, Kenneth O; Yosinski, Jason

2016-01-01

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994-when the first WebAL work appeared-up to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010-2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area.

Artificial intelligence

CERN Document Server

Hunt, Earl B

1975-01-01

Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

Application of life cycle assessment to production processes of environmentally sustainable concrete, prepared with artificial aggregates

International Nuclear Information System (INIS)

Vaccaro, R.; Colangelo, F.; Palumbo, M.; Cioffi, R.

2005-01-01

This paper is about the application of Life Cycle Assessment (L.C.A.) on environmentally sustainable concrete production processes. The goal of this experimentations is to assess environmental impact and energy demand related to concrete production, by using, in different admixtures, natural and artificial aggregates, belonging from treatments of different kind of industrial wastes characterized by very small particle sizes. Particular attention was concentrated on the utilization of fine fraction since it is difficult to recover in usual fields of recycling (i.e. aggers, crowl spaces, etc.). This study follows the approach from cradle to cradle. This experimentation was conducted in relation to four concrete admixtures produced, one of them containing only natural aggregate, and the other ones obtained by substituting the 10% of aggregate respectively with inert wastes as construction and demolition waste (CeD waste). cement kiln dust (CKD) and marble sludge. For all admixtures six different end-life scenarios have been proposed, one of them considers all materials transported in landfill while the other ones consider a partial transportation on landfill (15%) and a recycle of the 85% of wastes obtained after demolition of structures [it

Artificial hydration and alimentation at the end of life: a reply to Craig.

Science.gov (United States)

Ashby, M; Stoffell, B

1995-06-01

Dr Gillian Craig (1) has argued that palliative medicine services have tended to adopt a policy of sedation without hydration, which under certain circumstances may be medically inappropriate, causative of death and distressing to family and friends. We welcome this opportunity to defend, with an important modification, the approach we proposed without substantive background argument in our original article (2). We maintain that slowing and eventual cessation of oral intake is a normal part of a natural dying process, that artificial hydration and alimentation (AHA) are not justified unless thirst or hunger are present and cannot be relieved by other means, but food and fluids for (natural) oral consumption should never be 'withdrawn'. The intention of this practice is not to alter the timing of an inevitable death, and sedation is not used, as has been alleged, to mask the effects of dehydration or starvation. The artificial provision of hydration and alimentation is now widely accepted as medical treatment. We believe that arguments that it is not have led to confusion as to whether or not non-provision or withdrawal of AHA constitutes a cause of death in law. Arguments that it is such a cause appear to be tenuously based on an extraordinary/ordinary categorisation of treatments by Kelly (3) which has subsequently been interpreted as prescriptive in a way quite inconsistent with the Catholic moral theological tradition from which the distinction is derived. The focus of ethical discourse on decisions at the end of life should be shifted to an analysis of care, needs, proportionality of medical interventions, and processes of communication.

Reactively and Anticipatory Behaving Agents for Artificial Life Simulations

Science.gov (United States)

Kohout, Karel; Nahodil, Pavel

2010-11-01

Reactive behavior is still considered and the exact opposite for the anticipatory one. Despite the advances on the field of anticipation there are little thoughts on relation with the reactive behavior, the similarities and where the boundary is. In this article we will present our viewpoint and we will try to show that reactive and anticipatory behavior can be combined. This is the basic ground of our unified theory for anticipatory behavior architecture. We still miss such compact theory, which would integrate multiple aspects of anticipation. My multi-level anticipatory behavior approach is based on the current understanding of anticipation from both the artificial intelligence and biology point of view. As part of the explanation we will also elaborate on the topic of weak and strong artificial life. Anticipation is not matter of a single mechanism in a living organism. It was noted already that it happens on many different levels even in the very simple creatures. What we consider to be important for our work and what is our original though is that it happens even without voluntary control. We believe that this is novelty though for the anticipation theory. Naturally research of anticipation was in the beginning of this decade focused on the anticipatory principles bringing advances on the field itself. This allowed us to build on those, look at them from higher perspective, and use not one but multiple levels of anticipation in a creature design. This presents second original though and that is composition of the agent architecture that has anticipation built in almost every function. In this article we will focus only on first two levels within the 8-factor anticipation framework. We will introduce them as defined categories of anticipation and describe them from theory and implementation algorithm point of view. We will also present an experiment conducted, however this experiment serves more as explanatory example. These first two levels may seem trivial

Automation of seismic network signal interpolation: an artificial intelligence approach

International Nuclear Information System (INIS)

Chiaruttini, C.; Roberto, V.

1988-01-01

After discussing the current status of the automation in signal interpretation from seismic networks, a new approach, based on artificial-intelligence tecniques, is proposed. The knowledge of the human expert analyst is examined, with emphasis on its objects, strategies and reasoning techniques. It is argued that knowledge-based systems (or expert systems) provide the most appropriate tools for designing an automatic system, modelled on the expert behaviour

[Artificial organs].

Science.gov (United States)

Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

2017-01-01

Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

Artificial intelligence and synthetic biology: A tri-temporal contribution.

Science.gov (United States)

Bianchini, Francesco

2016-10-01

Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The prediction of the residual life of electromechanical equipment based on the artificial neural network

Science.gov (United States)

Zhukovskiy, Yu L.; Korolev, N. A.; Babanova, I. S.; Boikov, A. V.

2017-10-01

This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

Science.gov (United States)

Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

2018-02-01

Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising

A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

OpenAIRE

Xiangyu He; Shanghong He

2014-01-01

Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then served as the fault determinant to diagnose test faults and the work condition of the hydraulic system was identified. Several typical faults of the hydraulic system were used to verify the fault diagnosis approach. Experiment re...

Biology and fertility life table of Hypercompe indecisa on artificial diet

International Nuclear Information System (INIS)

Nava, Dori Edson; Diez-Rodriguez, Gabriela Ines; Melo, Mirtes; Afonso, Ana Paula Schneid

2008-01-01

The objective of this work was to study the biology of Hypercompe indecisa and construct a life table of fertility on an artificial diet, aiming at insect rearing in the laboratory. The following variables were determined: duration and survival of egg, larval and pupal phases; number of larval stages; sexual ratio; pupal weight; longevity; fecundity; and the period of pre-oviposition and oviposition. The embrionary, larval and pupal phases were 6, 25.4 and 64.3 days, with survival of 92.7, 92 and 71.9%, respectively. Six larval stages with variable durations were observed. Pupal weight was 1.04 g for females and 0.726 g for males. The biological cycle was 95.6 days, with 61.3% total survival. Females laid in average 1,531 eggs, during 8.3 days, with a pre-oviposition period of two days. The average longevity of males and females was 21.9 and 21.8 days, respectively, and the sexual ratio of males to females was 0.54. Increase of H. indecisa was 283 times through each generation, with the generation average duration of 98 days, and the fi nite ratio of increase of 1.0593. The used artificial diet was adequate for rearing H. indecisa, in the laboratory. (author)

APPROACHES TO QUALITY OF LIFE ANALYSISQUANTICATION

Directory of Open Access Journals (Sweden)

Larisa E. Danilina

2015-01-01

Full Text Available The paper reviews different approaches to quality of life measurement used in Russian and international statistics. It outlines the essence of J. Stiglitz’s recommendations on development of quality of life statistical indicators, analyses proposals and practical application of innovative approaches of quality of life measurement by the French National Institute for Statistics and Economic Studies (INSEE. The paper reviews Rosstat’s (Russian Federal State Statistics Service new research as well as an independent research in the area of quality of life research. The authors make proposals to extend the list of aspects analyzed an quality of life research and underline the importance of such a review through regional specifics. They suggest extending the system of quality of life statistical indicators by certain coefficients characterizing economic development disparity and its influence on the quality of life.

Impact of Artificial Intelligence on Economic Theory

OpenAIRE

Tshilidzi Marwala

2015-01-01

Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

Artificial Reefs

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

Influence of adjustments to amputation and artificial limb on quality of life in patients following lower limb amputation

NARCIS (Netherlands)

Sinha, Richa; van den Heuvel, Wim J. A.; Arokiasamy, Perianayagam; van Dijk, Jitse P.

The objectives of this study are to investigate the relationship between adjustments to amputation and artificial limb, and quality of life (QoL), and to analyse the influence of sociodemographic, medical and amputation-related factors on this relationship. Patients with unilateral and noncongenital

Investigating Membranes: Using Artificial Membranes to Convey Chemistry and Biology Concepts

Science.gov (United States)

Zrelak, Yoshi; McCallister, Gary

2009-01-01

While not organic in nature, quick-"growing" artificial membranes can be a profound visual aid when teaching students about cellular processes and the chemical nature of membranes. Students are often intrigued when they see biological and chemical concepts come to life before their eyes. In this article, the authors share their approach to growing…

A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

Directory of Open Access Journals (Sweden)

Fernando Sánchez Lasheras

2015-03-01

Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

AP@home: a novel European approach to bring the artificial pancreas home.

Science.gov (United States)

Heinemann, Lutz; Benesch, Carsten; DeVries, J Hans

2011-11-01

The development of an artificial pancreas (AP) made huge strides from 2006 to 2008 and a large number of activities are going on in this area of research. Until now, most AP systems under development were tested only under highly controlled conditions. The aim of our project, funded by the European Union, is to develop an AP system to such a level that it can be studied under daily life conditions at the home of patients with diabetes (hence AP@home). Based on a subcutaneous-subcutaneous closed-loop strategy (i.e., glucose sensing and insulin infusion in the subcutaneous tissue), two different approaches will be taken to achieve this aim: a two-port AP system and a single-port AP system. The two-port AP system will use off-the-shelf-components for the glucose sensor and insulin pump in combination with closed-loop algorithms generated in Europe. As to the single-port AP system, two different innovative single-port systems will be developed; in this case, continuous glucose monitoring and insulin infusion will take place via a single catheter. The first clinical trials with the two-port AP system under controlled clinical conditions have started and good progress has been made in the development of the single-port AP systems. We believe that our consortium of 12 European partners, which builds on existing achievements and close cooperation between academic centers and industry, can contribute substantially to the development of an AP system that can be used by patients in daily life. © 2011 Diabetes Technology Society.

A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

Directory of Open Access Journals (Sweden)

Wen-An Yang

2016-01-01

Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

Wirklich wie im wirklichen Leben. Sarah Kember untersucht die (Re-Produktion des kleinen Unterschieds und seiner großen Folgen in Theorie und Praxis von Artificial Life Real as in real life. Sarah Kember examines the (reproduction of ‘the small difference and its big consequences’ in the theory and practice of artificial life.

Directory of Open Access Journals (Sweden)

Verena Kuni

2004-03-01

Full Text Available Wie greifen diese ‚virtuellen Realitäten‘ in unsere Körper- und Identitätskonzepte, unsere Subjekt- und Geschlechtervorstellungen ein? Sarah Kembers Buch verspricht, erhellende Schneisen durch das Dickicht der definitionsmächtigen Diskurse, Konzepte und Konstruktionen zu schlagen und neue Wege für feministische Interventionen in die Auseinandersetzungen um ‚Artificial Life‘ aufzuzeigen.ow a way through the labyrinth of discourse, concepts and constructions, and to open the door for feminist interpretations in debates about artificial life.

Quality by design approach: application of artificial intelligence techniques of tablets manufactured by direct compression.

Science.gov (United States)

Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Ozer, Ozgen; Güneri, Tamer; York, Peter

2012-12-01

The publication of the International Conference of Harmonization (ICH) Q8, Q9, and Q10 guidelines paved the way for the standardization of quality after the Food and Drug Administration issued current Good Manufacturing Practices guidelines in 2003. "Quality by Design", mentioned in the ICH Q8 guideline, offers a better scientific understanding of critical process and product qualities using knowledge obtained during the life cycle of a product. In this scope, the "knowledge space" is a summary of all process knowledge obtained during product development, and the "design space" is the area in which a product can be manufactured within acceptable limits. To create the spaces, artificial neural networks (ANNs) can be used to emphasize the multidimensional interactions of input variables and to closely bind these variables to a design space. This helps guide the experimental design process to include interactions among the input variables, along with modeling and optimization of pharmaceutical formulations. The objective of this study was to develop an integrated multivariate approach to obtain a quality product based on an understanding of the cause-effect relationships between formulation ingredients and product properties with ANNs and genetic programming on the ramipril tablets prepared by the direct compression method. In this study, the data are generated through the systematic application of the design of experiments (DoE) principles and optimization studies using artificial neural networks and neurofuzzy logic programs.

An integrated artificial neural networks approach for predicting global radiation

International Nuclear Information System (INIS)

Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

2009-01-01

This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

A classical Master equation approach to modeling an artificial protein motor

International Nuclear Information System (INIS)

Kuwada, Nathan J.; Blab, Gerhard A.; Linke, Heiner

2010-01-01

Inspired by biomolecular motors, as well as by theoretical concepts for chemically driven nanomotors, there is significant interest in constructing artificial molecular motors. One driving force is the opportunity to create well-controlled model systems that are simple enough to be modeled in detail. A remaining challenge is the fact that such models need to take into account processes on many different time scales. Here we describe use of a classical Master equation approach, integrated with input from Langevin and molecular dynamics modeling, to stochastically model an existing artificial molecular motor concept, the Tumbleweed, across many time scales. This enables us to study how interdependencies between motor processes, such as center-of-mass diffusion and track binding/unbinding, affect motor performance. Results from our model help guide the experimental realization of the proposed motor, and potentially lead to insights that apply to a wider class of molecular motors.

Artificial intelligence approaches to astronomical observation scheduling

Science.gov (United States)

Johnston, Mark D.; Miller, Glenn

1988-01-01

Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

Artificial intelligence approach to legal reasoning

International Nuclear Information System (INIS)

Gardner, A.V.D.L.

1984-01-01

For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about legal problems must be able to distinguish between questions it is competent to answer and questions that human lawyers could seriously argue either way. In addition, a program for analyzing legal problems should be able to use both general legal rules and decisions in past cases; and it should be able to work with technical concepts that are only partly defined and subject to shifts of meaning. Each of these requirements has wider applications in artificial intelligence, beyond the legal domain. This dissertation presents a computational framework for legal reasoning, within which such requirements can be accommodated. The development of the framework draws significantly on the philosophy of law, in which the elucidation of legal reasoning is an important topic. A key element of the framework is the legal distinction between hard cases and clear cases. In legal writing, this distinction has been taken for granted more often than it has been explored. Here, some initial heuristics are proposed by which a program might make the distinction

Reinforcement Learning Based Artificial Immune Classifier

Directory of Open Access Journals (Sweden)

Mehmet Karakose

2013-01-01

Full Text Available One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.

Reasoning methods in medical consultation systems: artificial intelligence approaches.

Science.gov (United States)

Shortliffe, E H

1984-01-01

It has been argued that the problem of medical diagnosis is fundamentally ill-structured, particularly during the early stages when the number of possible explanations for presenting complaints can be immense. This paper discusses the process of clinical hypothesis evocation, contrasts it with the structured decision making approaches used in traditional computer-based diagnostic systems, and briefly surveys the more open-ended reasoning methods that have been used in medical artificial intelligence (AI) programs. The additional complexity introduced when an advice system is designed to suggest management instead of (or in addition to) diagnosis is also emphasized. Example systems are discussed to illustrate the key concepts.

Artificial Neural Network Approach to Predict Biodiesel Production in Supercritical tert-Butyl Methyl Ether

Directory of Open Access Journals (Sweden)

Obie Farobie

2016-05-01

Full Text Available In this study, for the first time artificial neural network was used to predict biodiesel yield in supercritical tert-butyl methyl ether (MTBE. The experimental data of biodiesel yield conducted by varying four input factors (i.e. temperature, pressure, oil-to-MTBE molar ratio, and reaction time were used to elucidate artificial neural network model in order to predict biodiesel yield. The main goal of this study was to assess how accurately this artificial neural network model to predict biodiesel yield conducted under supercritical MTBE condition. The result shows that artificial neural network is a powerful tool for modeling and predicting biodiesel yield conducted under supercritical MTBE condition that was proven by a high value of coefficient of determination (R of 0.9969, 0.9899, and 0.9658 for training, validation, and testing, respectively. Using this approach, the highest biodiesel yield was determined of 0.93 mol/mol (corresponding to the actual biodiesel yield of 0.94 mol/mol that was achieved at 400 °C, under the reactor pressure of 10 MPa, oil-to-MTBE molar ratio of 1:40 within 15 min of reaction time.

Artificial intelligence and the future.

Science.gov (United States)

Clocksin, William F

2003-08-15

We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

An artificial ecosystem model used in the study of social, economic and technological dynamics: An artificial electrical energy market

International Nuclear Information System (INIS)

Arjona, D.

1998-01-01

This paper will present the artificial ecosystem as a tool, in the development of multi agent models for the simulation of economic and technological dynamics (as well as other possible applications). This tool is based on the mechanics of an artificial society and consists of autonomous artificial agents that interact with individuals that have different characteristics and behavior and other that have a similar conduct to their own. Initial conditions are assumed not to be controllable, however they can be influenced. The importance of the concept of the ecosystem is in understanding great units in the light of their own components which are relevant for the analysis and become interdependent among themselves and with other essential components that hold the total operation of the system. Ideas for the development of a simulation model based on autonomous intelligent agents are presented. These agents will have a brain that is based on artificial intelligence technologies. The Sand Kings Simulation Model, an artificial ecosystem model developed by the author, is described as well as the application of artificial intelligence to this artificial life model. An application to a real life problem is also offered as an artificial energy market that is currently being developed by the author is described

The artificial neural networks: An approach to artificial intelligence; Un approccio ``biologico`` all`intelligenza artificiale

Energy Technology Data Exchange (ETDEWEB)

Taraglio, Sergio; Zanela, Andrea [ENEA, Casaccia (Italy). Dipt. Innovazione

1997-05-01

The artificial neural networks try to simulate the functionalities of the nervous system through a complex network of simple computing elements. In this work is presented an introduction to the neural networks and some of their possible applications, especially in the field of Artificial Intelligence.

Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

CERN Document Server

Wenger, Etienne

2014-01-01

Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

Knowledge representation an approach to artificial intelligence

CERN Document Server

Bench-Capon, TJM

1990-01-01

Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the ch

Artificial Evolution for the Detection of Group Identities in Complex Artificial Societies

DEFF Research Database (Denmark)

Grappiolo, Corrado; Togelius, Julian; Yannakakis, Georgios N.

2013-01-01

This paper aims at detecting the presence of group structures in complex artificial societies by solely observing and analysing the interactions occurring among the artificial agents. Our approach combines: (1) an unsupervised method for clustering interactions into two possible classes, namely in...

Parallel artificial liquid membrane extraction

DEFF Research Database (Denmark)

Gjelstad, Astrid; Rasmussen, Knut Einar; Parmer, Marthe Petrine

2013-01-01

This paper reports development of a new approach towards analytical liquid-liquid-liquid membrane extraction termed parallel artificial liquid membrane extraction. A donor plate and acceptor plate create a sandwich, in which each sample (human plasma) and acceptor solution is separated by an arti......This paper reports development of a new approach towards analytical liquid-liquid-liquid membrane extraction termed parallel artificial liquid membrane extraction. A donor plate and acceptor plate create a sandwich, in which each sample (human plasma) and acceptor solution is separated...... by an artificial liquid membrane. Parallel artificial liquid membrane extraction is a modification of hollow-fiber liquid-phase microextraction, where the hollow fibers are replaced by flat membranes in a 96-well plate format....

Artificial Intelligence in Astronomy

Science.gov (United States)

Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

2010-12-01

From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

Material and Non-material Determinants of European Youth's Life Quality

OpenAIRE

Gawlik, Remigiusz

2013-01-01

The paper confronts chosen approaches to quality of life studies with recent changes in post-crisis socio-economic environment. The focus is on European Youth at verge of entry into adult life. Presented research is a preliminary study for “The Application of Artificial Intelligence Methods for Analyzing Material and Non-material Determinants of Life Satisfaction between Young People from Developing Countries” project. Identifying and grouping the determinants of their life satisfaction could...

A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

DEFF Research Database (Denmark)

Lynggaard, Per

2013-01-01

A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

Engineering of metabolic pathways by artificial enzyme channels

Directory of Open Access Journals (Sweden)

Marlene ePröschel

2015-10-01

Full Text Available Application of industrial enzymes for production of valuable chemical compounds has greatly benefited from recent developments in Systems and Synthetic Biology. Both, in vivo and in vitro systems have been established, allowing conversion of simple into complex compounds. Metabolic engineering in living cells needs to be balanced which is achieved by controlling gene expression levels, translation, scaffolding, compartmentation and flux control. In vitro applications are often hampered by limited protein stability/half-life and insufficient rates of substrate conversion. To improve stability and catalytic activity, proteins are post-translationally modified and arranged in artificial metabolic channels. Within the review article we will first discuss the supramolecular organization of enzymes in living systems and secondly summarize current and future approaches to design artificial metabolic channels by additive manufacturing for the efficient production of desired products.

The Nexus Between Artificial Intellgence and Economics

NARCIS (Netherlands)

van de Gevel, A.J.W.; Noussair, C.N.

2013-01-01

The manuscript reviews some key ideas about artificial intelligence, and relates them to economics. These include its relation to robotics, and the concepts of synthetic emotions, consciousness, and life. The economic implications of the advent of artificial intelligence, such as its effect on

The general entity of life: a cybernetic approach.

Science.gov (United States)

Bielecki, Andrzej

2015-06-01

Life, not only in the well-known context of biochemical metabolism but also in the context of hypothetical life synthesized laboratorially or possibly found on other planets, is considered in this paper. The three-component information-energetic-structural irreducible processing in autonomous systems is the core of the proposed approach. The cybernetic organization of a general entity of life--the alivon--is postulated. The crucial properties of life and evolution are derived from the proposed approach. Information encoded in biological structures is also studied.

Artificial intelligence approach to accelerator control systems

International Nuclear Information System (INIS)

Schultz, D.E.; Hurd, J.W.; Brown, S.K.

1987-01-01

An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

Ethico-epistemological implications of artificial intelligence for ...

African Journals Online (AJOL)

We argued for a re-direction of AI. research and suggested a humanization of Artificial Intelligence that cloaks technoscientific innovations with humanistic life jackets for man‟s preservation. The textual analysis method is adopted for this research. Key words: Ethics, Epistemology, Artificial Intelligence, Humanity.

Could a functional artificial skeletal muscle be useful in muscle wasting?

Science.gov (United States)

Fuoco, Claudia; Cannata, Stefano; Gargioli, Cesare

2016-05-01

Regardless of the underlying cause, skeletal muscle wasting is detrimental for a person's life quality, leading to impaired strength, locomotion, and physiological activity. Here, we propose a series of studies presenting tissue engineering-based approaches to reconstruct artificial muscle in vitro and in vivo. Skeletal muscle tissue engineering is attracting more and more attention from scientists, clinicians, patients, and media, thanks to the promising results obtained in the last decade with animal models of muscle wasting. The use of novel and refined biomimetic scaffolds mimicking three-dimensional muscle environment, thus supporting cell survival and differentiation, in combination with well characterized myogenic stem/progenitor cells, revealed the noteworthy potential of these technologies for creating artificial skeletal muscle tissue. In vitro, the production of three-dimensional muscle structures offer the possibility to generate a drug-screening platform for patient-specific pharmacological treatment, opening new frontiers in the development of new compounds with specific therapeutic actions. In vivo, three-dimensional artificial muscle biomimetic constructs offer the possibility to replace, in part or entirely, wasted muscle by means of straight reconstruction and/or by enhancing endogenous regeneration. Reports of tissue engineering approaches for artificial muscle building appeared in large numbers in the specialized press lately, advocating the suitability of this technology for human application upon scaling up and a near future applicability for medical care of muscle wasting. http://links.lww.com/COCN/A9

EVALUATION AND RANKING OF ARTIFICIAL HIP PROSTHESIS SUPPLIERS BY USING A FUZZY TOPSIS METHODOLOGY

Directory of Open Access Journals (Sweden)

Marija Zahar Djordjevic

2014-06-01

Full Text Available The aim of this study is to propose a fuzzy multi-criteria decision-making approach (MCDM to evaluate the artificial hip prosthesis suppliers with respect to numerous criteria, simultaneously, taking into account the type of each criteria and its relative importance. The fuzzy of the Technique for Order Preference by Similarity to Ideal Solution (FTOSISis applied in order to rank the artificial hip prosthesis suppliers. The rank is obtained using the process of fuzzy number comparison. Software solution based on suggested method is also presented. A real-life example with real data is presented to clarify the proposed method.

Suitability of an artificial diet for rape aphid, Brevicoryne brassicae ...

African Journals Online (AJOL)

STORAGESEVER

2009-09-15

Sep 15, 2009 ... Brevicoryne brassicae, using life table parameters. A. Balvasi1* ... In this work, suitability of an artificial diet was studied through age-specific life tables. Development ... In large measure, the success of entomology over the past century is ..... balance on the improvement of an artificial diet for a biotype of.

ARTIFICIAL AND NATURAL INTELLIGENCE IN ANTHROPOGENIC EDUCATIONAL ENVIRONMENTS

Directory of Open Access Journals (Sweden)

Sergey F. Sergeev

2013-01-01

Full Text Available In the present article we show the link between both artificial and natural intelligence and the system’s complexity during the life-cycle. Autopoetic’s type of living systems determines the differences between natural and artificial intelligence; artificial environments have an influence to the intelligence abilities development. We present the «diffusion intellect» concept where the diffusion intellect is considered as a synergistic unity of natural and artificial intellect in organized environments. 

An activated energy approach for accelerated testing of the deformation of UHMWPE in artificial joints.

Science.gov (United States)

Galetz, Mathias Christian; Glatzel, Uwe

2010-05-01

The deformation behavior of ultrahigh molecular polyethylene (UHMWPE) is studied in the temperature range of 23-80 degrees C. Samples are examined in quasi-static compression, tensile and creep tests to determine the accelerated deformation of UHMWPE at elevated temperatures. The deformation mechanisms under compression load can be described by one strain rate and temperature dependent Eyring process. The activation energy and volume of that process do not change between 23 degrees C and 50 degrees C. This suggests that the deformation mechanism under compression remains stable within this temperature range. Tribological tests are conducted to transfer this activated energy approach to the deformation behavior under loading typical for artificial knee joints. While this approach does not cover the wear mechanisms close to the surface, testing at higher temperatures is shown to have a significant potential to reduce the testing time for lifetime predictions in terms of the macroscopic creep and deformation behavior of artificial joints. Copyright 2010. Published by Elsevier Ltd.

Artificial organ engineering

CERN Document Server

Annesini, Maria Cristina; Piemonte, Vincenzo; Turchetti, Luca

2017-01-01

Artificial organs may be considered as small-scale process plants, in which heat, mass and momentum transfer operations and, possibly, chemical transformations are carried out. This book proposes a novel analysis of artificial organs based on the typical bottom-up approach used in process engineering. Starting from a description of the fundamental physico-chemical phenomena involved in the process, the whole system is rebuilt as an interconnected ensemble of elemental unit operations. Each artificial organ is presented with a short introduction provided by expert clinicians. Devices commonly used in clinical practice are reviewed and their performance is assessed and compared by using a mathematical model based approach. Whilst mathematical modelling is a fundamental tool for quantitative descriptions of clinical devices, models are kept simple to remain focused on the essential features of each process. Postgraduate students and researchers in the field of chemical and biomedical engineering will find that t...

Life-oriented approach for urban policy decision-making: Surveys and applications

OpenAIRE

Junyi Zhang; Yubing Xiong; Minh Tu Tran

2014-01-01

In this study, we propose an additional approach, called life-oriented approach, for supporting urban policy decisions. The life-oriented approach argues that people's decisions on various life choices are not independent of each other and that an understanding of life choices should not be constrained by the boundary of any single discipline. People's life choices are closely linked with the quality of life (QOL), which can be roughly captured from the perspective of life domains such as res...

Artificial limb representation in amputees

OpenAIRE

van den Heiligenberg, FMZ; Orlov, T; Macdonald, SN; Duff, EP; Henderson Slater, JDE; Beckmann, CF; Johansen-Berg, H; Culham, JC; Makin, TR

2018-01-01

The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral o...

Two approaches to the study of the origin of life

NARCIS (Netherlands)

Hengeveld, R.

2007-01-01

This paper compares two approaches that attempt to explain the origin of life, or biogenesis. The more established approach is one based on chemical principles, whereas a new, yet not widely known approach begins from a physical perspective. According to the first approach, life would have begun

Two approaches to the study of the origin of life.

NARCIS (Netherlands)

Hengeveld, R.

2007-01-01

This paper compares two approaches that attempt to explain the origin of life, or biogenesis. The more established approach is one based on chemical principles, whereas a new, yet not widely known approach begins from a physical perspective. According to the first approach, life would have begun

Improvisation of Real-Life Scenarios through Intercultural Competence

Science.gov (United States)

Okten, Celile Eren; Griffin, Banu Ozer

2016-01-01

This paper describes tasks based on real-life scenarios, which triggered reflective thinking, verbalization, and writing, leading to the creation of natural dialogues rather than artificial, dull monologues. One of the main aims of this approach is to engage students in a dynamic process of both learning about multicultural participants and…

A Hybrid Fuzzy Time Series Approach Based on Fuzzy Clustering and Artificial Neural Network with Single Multiplicative Neuron Model

Directory of Open Access Journals (Sweden)

Ozge Cagcag Yolcu

2013-01-01

Full Text Available Particularly in recent years, artificial intelligence optimization techniques have been used to make fuzzy time series approaches more systematic and improve forecasting performance. Besides, some fuzzy clustering methods and artificial neural networks with different structures are used in the fuzzification of observations and determination of fuzzy relationships, respectively. In approaches considering the membership values, the membership values are determined subjectively or fuzzy outputs of the system are obtained by considering that there is a relation between membership values in identification of relation. This necessitates defuzzification step and increases the model error. In this study, membership values were obtained more systematically by using Gustafson-Kessel fuzzy clustering technique. The use of artificial neural network with single multiplicative neuron model in identification of fuzzy relation eliminated the architecture selection problem as well as the necessity for defuzzification step by constituting target values from real observations of time series. The training of artificial neural network with single multiplicative neuron model which is used for identification of fuzzy relation step is carried out with particle swarm optimization. The proposed method is implemented using various time series and the results are compared with those of previous studies to demonstrate the performance of the proposed method.

Relationship between mediation analysis and the structured life course approach

Science.gov (United States)

Howe, Laura D; Smith, Andrew D; Macdonald-Wallis, Corrie; Anderson, Emma L; Galobardes, Bruna; Lawlor, Debbie A; Ben-Shlomo, Yoav; Hardy, Rebecca; Cooper, Rachel; Tilling, Kate; Fraser, Abigail

2016-01-01

Abstract Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond to different combinations of mediation and interaction parameters. For example, an early life critical period model corresponds to a direct effect of the early life exposure, but no indirect effect via the mediator and no interaction between the early life exposure and the mediator. We also compare these methods using an illustrative real-data example using data on parental occupational social class (early life exposure), own adult occupational social class (mediator) and physical capability (outcome). PMID:27681097

A Novel Wearable Sensor-Based Human Activity Recognition Approach Using Artificial Hydrocarbon Networks.

Science.gov (United States)

Ponce, Hiram; Martínez-Villaseñor, María de Lourdes; Miralles-Pechuán, Luis

2016-07-05

Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by human activity recognition. Nevertheless, the human activity recognition classification process is not an easy task. Different types of noise in wearable sensors data frequently hamper the human activity recognition classification process. In order to develop a successful activity recognition system, it is necessary to use stable and robust machine learning techniques capable of dealing with noisy data. In this paper, we presented the artificial hydrocarbon networks (AHN) technique to the human activity recognition community. Our artificial hydrocarbon networks novel approach is suitable for physical activity recognition, noise tolerance of corrupted data sensors and robust in terms of different issues on data sensors. We proved that the AHN classifier is very competitive for physical activity recognition and is very robust in comparison with other well-known machine learning methods.

Relationship between mediation analysis and the structured life course approach.

Science.gov (United States)

Howe, Laura D; Smith, Andrew D; Macdonald-Wallis, Corrie; Anderson, Emma L; Galobardes, Bruna; Lawlor, Debbie A; Ben-Shlomo, Yoav; Hardy, Rebecca; Cooper, Rachel; Tilling, Kate; Fraser, Abigail

2016-08-01

Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond to different combinations of mediation and interaction parameters. For example, an early life critical period model corresponds to a direct effect of the early life exposure, but no indirect effect via the mediator and no interaction between the early life exposure and the mediator. We also compare these methods using an illustrative real-data example using data on parental occupational social class (early life exposure), own adult occupational social class (mediator) and physical capability (outcome). © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Artificial intelligence tools decision support systems in condition monitoring and diagnosis

CERN Document Server

Galar Pascual, Diego

2015-01-01

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

An artificial intelligence approach to accelerator control systems

International Nuclear Information System (INIS)

Schultz, D.E.; Hurd, J.W.; Brown, S.K.

1987-01-01

An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

New twist on artificial muscles.

Science.gov (United States)

Haines, Carter S; Li, Na; Spinks, Geoffrey M; Aliev, Ali E; Di, Jiangtao; Baughman, Ray H

2016-10-18

Lightweight artificial muscle fibers that can match the large tensile stroke of natural muscles have been elusive. In particular, low stroke, limited cycle life, and inefficient energy conversion have combined with high cost and hysteretic performance to restrict practical use. In recent years, a new class of artificial muscles, based on highly twisted fibers, has emerged that can deliver more than 2,000 J/kg of specific work during muscle contraction, compared with just 40 J/kg for natural muscle. Thermally actuated muscles made from ordinary polymer fibers can deliver long-life, hysteresis-free tensile strokes of more than 30% and torsional actuation capable of spinning a paddle at speeds of more than 100,000 rpm. In this perspective, we explore the mechanisms and potential applications of present twisted fiber muscles and the future opportunities and challenges for developing twisted muscles having improved cycle rates, efficiencies, and functionality. We also demonstrate artificial muscle sewing threads and textiles and coiled structures that exhibit nearly unlimited actuation strokes. In addition to robotics and prosthetics, future applications include smart textiles that change breathability in response to temperature and moisture and window shutters that automatically open and close to conserve energy.

Brain Intelligence: Go Beyond Artificial Intelligence

OpenAIRE

Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

2017-01-01

Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

Identification of time-varying structural dynamic systems - An artificial intelligence approach

Science.gov (United States)

Glass, B. J.; Hanagud, S.

1992-01-01

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

How to teach artificial organs.

Science.gov (United States)

Zapanta, Conrad M; Borovetz, Harvey S; Lysaght, Michael J; Manning, Keefe B

2011-01-01

Artificial organs education is often an overlooked field for many bioengineering and biomedical engineering students. The purpose of this article is to describe three different approaches to teaching artificial organs. This article can serve as a reference for those who wish to offer a similar course at their own institutions or incorporate these ideas into existing courses. Artificial organ classes typically fulfill several ABET (Accreditation Board for Engineering and Technology) criteria, including those specific to bioengineering and biomedical engineering programs.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

Science.gov (United States)

Contreras, Ivan; Vehi, Josep

2018-05-30

Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life. ©Ivan Contreras, Josep Vehi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition

Directory of Open Access Journals (Sweden)

Adam Linson

2018-03-01

Full Text Available The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness.

Synthetic and Bio-Artificial Tactile Sensing: A Review

Directory of Open Access Journals (Sweden)

Maria Chiara Carrozza

2013-01-01

Full Text Available This paper reviews the state of the art of artificial tactile sensing, with a particular focus on bio-hybrid and fully-biological approaches. To this aim, the study of physiology of the human sense of touch and of the coding mechanisms of tactile information is a significant starting point, which is briefly explored in this review. Then, the progress towards the development of an artificial sense of touch are investigated. Artificial tactile sensing is analysed with respect to the possible approaches to fabricate the outer interface layer: synthetic skin versus bio-artificial skin. With particular respect to the synthetic skin approach, a brief overview is provided on various technologies and transduction principles that can be integrated beneath the skin layer. Then, the main focus moves to approaches characterized by the use of bio-artificial skin as an outer layer of the artificial sensory system. Within this design solution for the skin, bio-hybrid and fully-biological tactile sensing systems are thoroughly presented: while significant results have been reported for the development of tissue engineered skins, the development of mechanotransduction units and their integration is a recent trend that is still lagging behind, therefore requiring research efforts and investments. In the last part of the paper, application domains and perspectives of the reviewed tactile sensing technologies are discussed.

Effects of artificial gravity on the cardiovascular system: Computational approach

Science.gov (United States)

Diaz Artiles, Ana; Heldt, Thomas; Young, Laurence R.

2016-09-01

Artificial gravity has been suggested as a multisystem countermeasure against the negative effects of weightlessness. However, many questions regarding the appropriate configuration are still unanswered, including optimal g-level, angular velocity, gravity gradient, and exercise protocol. Mathematical models can provide unique insight into these questions, particularly when experimental data is very expensive or difficult to obtain. In this research effort, a cardiovascular lumped-parameter model is developed to simulate the short-term transient hemodynamic response to artificial gravity exposure combined with ergometer exercise, using a bicycle mounted on a short-radius centrifuge. The model is thoroughly described and preliminary simulations are conducted to show the model capabilities and potential applications. The model consists of 21 compartments (including systemic circulation, pulmonary circulation, and a cardiac model), and it also includes the rapid cardiovascular control systems (arterial baroreflex and cardiopulmonary reflex). In addition, the pressure gradient resulting from short-radius centrifugation is captured in the model using hydrostatic pressure sources located at each compartment. The model also includes the cardiovascular effects resulting from exercise such as the muscle pump effect. An initial set of artificial gravity simulations were implemented using the Massachusetts Institute of Technology (MIT) Compact-Radius Centrifuge (CRC) configuration. Three centripetal acceleration (artificial gravity) levels were chosen: 1 g, 1.2 g, and 1.4 g, referenced to the subject's feet. Each simulation lasted 15.5 minutes and included a baseline period, the spin-up process, the ergometer exercise period (5 minutes of ergometer exercise at 30 W with a simulated pedal cadence of 60 RPM), and the spin-down process. Results showed that the cardiovascular model is able to predict the cardiovascular dynamics during gravity changes, as well as the expected

A psycho-societal approach to life histories

DEFF Research Database (Denmark)

Olesen, Henning Salling

2016-01-01

Life histories represent lived lives past, present and anticipated future. As such they are interpretations of individuals’ experiences of the way in which societal dynamics take place in the individual body and mind, either by the individual him/herself or by another biographer. I have been...... particularly interested in the relations between the culturally mediated and the sensory/bodily aspects of experience processes because this is the boundary zones of knowledge and seat of the dynamics of learning. My psycho-societal approach was developing from interpreting autobiographical and later certain...... other forms of language interactive material as moments of life history, i.e. it is basically a hermeneutic approach. Talking about a psycho-societal approach indicates the ambition of attacking the dichotomy of the social and the psychic, both in the interpretation procedure and in some main...

Telomerase-mediated life-span extension of human primary fibroblasts by human artificial chromosome (HAC) vector

International Nuclear Information System (INIS)

Shitara, Shingo; Kakeda, Minoru; Nagata, Keiko; Hiratsuka, Masaharu; Sano, Akiko; Osawa, Kanako; Okazaki, Akiyo; Katoh, Motonobu; Kazuki, Yasuhiro; Oshimura, Mitsuo; Tomizuka, Kazuma

2008-01-01

Telomerase-mediated life-span extension enables the expansion of normal cells without malignant transformation, and thus has been thought to be useful in cell therapies. Currently, integrating vectors including the retrovirus are used for human telomerase reverse transcriptase (hTERT)-mediated expansion of normal cells; however, the use of these vectors potentially causes unexpected insertional mutagenesis and/or activation of oncogenes. Here, we established normal human fibroblast (hPF) clones retaining non-integrating human artificial chromosome (HAC) vectors harboring the hTERT expression cassette. In hTERT-HAC/hPF clones, we observed the telomerase activity and the suppression of senescent-associated SA-β-galactosidase activity. Furthermore, the hTERT-HAC/hPF clones continued growing beyond 120 days after cloning, whereas the hPF clones retaining the silent hTERT-HAC senesced within 70 days. Thus, hTERT-HAC-mediated episomal expression of hTERT allows the extension of the life-span of human primary cells, implying that gene delivery by non-integrating HAC vectors can be used to control cellular proliferative capacity of primary cultured cells

A Dynamic Health Assessment Approach for Shearer Based on Artificial Immune Algorithm

Directory of Open Access Journals (Sweden)

Zhongbin Wang

2016-01-01

Full Text Available In order to accurately identify the dynamic health of shearer, reducing operating trouble and production accident of shearer and improving coal production efficiency further, a dynamic health assessment approach for shearer based on artificial immune algorithm was proposed. The key technologies such as system framework, selecting the indicators for shearer dynamic health assessment, and health assessment model were provided, and the flowchart of the proposed approach was designed. A simulation example, with an accuracy of 96%, based on the collected data from industrial production scene was provided. Furthermore, the comparison demonstrated that the proposed method exhibited higher classification accuracy than the classifiers based on back propagation-neural network (BP-NN and support vector machine (SVM methods. Finally, the proposed approach was applied in an engineering problem of shearer dynamic health assessment. The industrial application results showed that the paper research achievements could be used combining with shearer automation control system in fully mechanized coal face. The simulation and the application results indicated that the proposed method was feasible and outperforming others.

BioArtificial polymers

Science.gov (United States)

Szałata, Kamila; Gumi, Tania

2017-07-01

Nowadays, the polymer science has impact in practically all life areas. Countless benefits coming from the usage of materials with high mechanical and chemical resistance, variety of functionalities and potentiality of modification drive to the development of new application fields. Novel approaches of combining these synthetic substances with biomolecules lead to obtain multifunctional hybrid conjugates which merge the bioactivity of natural component with outstanding properties of artificial polymer. Over the decades, an immense progress in bioartificial composites domain allowed to reach a high level of knowledge in terms of natural-like systems engineering, leading to diverse strategies of biomolecule immobilization. Together with different available options, including covalent and noncovalent attachment, come various challenges, related mainly with maintaining the biological activity of fixed molecules. Even though the amount of applications that achieve commercial status is still not substantial, and is expanding continuously in the disciplines like "smart materials," biosensors, delivery systems, nanoreactors and many others. A huge number of remarkable developments reported in the literature present a potential of bioartificial conjugates as a fabrics with highly controllable structure and multiple functionalities, serving as a powerful nanotechnological tool. This novel approach brings closer biologists, chemists and engineers, who sharing their effort and complementing the knowledge can revolutionize the field of bioartificial polymer science.

Modelling fuel cell performance using artificial intelligence

Science.gov (United States)

Ogaji, S. O. T.; Singh, R.; Pilidis, P.; Diacakis, M.

Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed.

Modelling fuel cell performance using artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Ogaji, S.O.T.; Singh, R.; Pilidis, P.; Diacakis, M. [Power Propulsion and Aerospace Engineering Department, Centre for Diagnostics and Life Cycle Costs, Cranfield University (United Kingdom)

2006-03-09

Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed. (author)

Polymeric membrane materials for artificial organs.

Science.gov (United States)

Kawakami, Hiroyoshi

2008-01-01

Many polymeric materials have already been used in the field of artificial organs. However, the materials used in artificial organs are not necessarily created with the best material selectivity and materials design; therefore, the development of synthesized polymeric membrane materials for artificial organs based on well-defined designs is required. The approaches to the development of biocompatible polymeric materials fall into three categories: (1) control of physicochemical characteristics on material surfaces, (2) modification of material surfaces using biomolecules, and (3) construction of biomimetic membrane surfaces. This review will describe current issues regarding polymeric membrane materials for use in artificial organs.

[An artificial heart: bridge to transplantation or permanent?].

Science.gov (United States)

de Mol, Bas A J M; Lahpor, Jaap

2013-01-01

An artificial heart is a continuous-flow pump device with a constant output, which usually supports the left ventricle. Over the past five years, survival rates with an artificial heart have increased dramatically, but with an annual mortality of 10% per year compared with 6% for heart transplantation the artificial heart is mainly a 'bridge to transplantation' or an alternative for those patients who are not suitable for heart transplant, 'destination therapy'. It is anticipated that the number and severity of complications will decrease as a result of technological progress. The artificial heart could then become a long-term treatment option providing a good quality of life and thus become equivalent to a heart transplant.

Artificial intelligence approach with the use of artificial neural networks for the creation of a forecasting model of Plasmopara viticola infection.

Science.gov (United States)

Bugliosi, R; Spera, G; La Torre, A; Campoli, L; Scaglione, M

2006-01-01

Most of the forecasting models of Plasmopara viticola infections are based upon empiric correlations between meteorological/environmental data and pathogen outbreak. These models generally overestimate the risk of infections and induce to treat the vineyard even if it should be not necessary. In rare cases they underrate the risk of infection leaving the pathogen to breakout. Starting from these considerations we have decided to approach the problem from another point of view utilizing Artificial Intelligence techniques for data elaboration and analysis. Meanwhile the same data have been studied with a more classic approach with statistical tools to verify the impact of a large data collection on the standard data analysis methods. A network of RTUs (Remote Terminal Units) distributed all over the Italian national territory transmits 12 environmental parameters every 15 minutes via radio or via GPRS to a centralized Data Base. Other pedologic data is collected directly from the field and sent via Internet to the centralized data base utilizing Personal Digital Assistants (PDAs) running a specific software. Data is stored after having been preprocessed, to guarantee the quality of the information. The subsequent analysis has been realized mostly with Artificial Neural Networks (ANNs). Collecting and analizing data in this way will probably bring us to the possibility of preventing Plasmospara viticola infection starting from the environmental conditions in this very complex context. The aim of this work is to forecast the infection avoiding the ineffective use of the plant protection products in agriculture. Applying different analysis models we will try to find the best ANN capable of forecasting with an high level of affordability.

AN ARTIFICIAL INTELLIGENCE APPROACH FOR THE PREDICTION OF SURFACE ROUGHNESS IN CO2 LASER CUTTING

Directory of Open Access Journals (Sweden)

MILOŠ MADIĆ

2012-12-01

Full Text Available In laser cutting, the cut quality is of great importance. Multiple non-linear effects of process parameters and their interactions make very difficult to predict cut quality. In this paper, artificial intelligence (AI approach was applied to predict the surface roughness in CO2 laser cutting. To this aim, artificial neural network (ANN model of surface roughness was developed in terms of cutting speed, laser power and assist gas pressure. The experimental results obtained from Taguchi’s L25 orthogonal array were used to develop ANN model. The ANN mathematical model of surface roughness was expressed as explicit nonlinear function of the selected input parameters. Statistical results indicate that the ANN model can predict the surface roughness with good accuracy. It was showed that ANNs may be used as a good alternative in analyzing the effects of cutting parameters on the surface roughness.

Life cycle management and assessment: approaches and visions towards sustainable manufacturing

DEFF Research Database (Denmark)

Westkämper, Engelbert; Alting, Leo; Arndt, Günther

2000-01-01

. The goal of this approach is to protect resources and maximize effectiveness by means of life cycle assessment, product data management, technical support and, last but not least, life cycle costing. This paper shows the existing approaches of LCM and discusses their prospects and further development....... concepts are required, new regulations have been passed or consumer values are changing, the differences between business areas are disappearing. Life cycle management (LCM) considers the product life cycle as a whole and optimizes the interaction of product design, manufacturing and life cycle activities...

Artificial Lipid Membranes: Past, Present, and Future.

Science.gov (United States)

Siontorou, Christina G; Nikoleli, Georgia-Paraskevi; Nikolelis, Dimitrios P; Karapetis, Stefanos K

2017-07-26

The multifaceted role of biological membranes prompted early the development of artificial lipid-based models with a primary view of reconstituting the natural functions in vitro so as to study and exploit chemoreception for sensor engineering. Over the years, a fair amount of knowledge on the artificial lipid membranes, as both, suspended or supported lipid films and liposomes, has been disseminated and has helped to diversify and expand initial scopes. Artificial lipid membranes can be constructed by several methods, stabilized by various means, functionalized in a variety of ways, experimented upon intensively, and broadly utilized in sensor development, drug testing, drug discovery or as molecular tools and research probes for elucidating the mechanics and the mechanisms of biological membranes. This paper reviews the state-of-the-art, discusses the diversity of applications, and presents future perspectives. The newly-introduced field of artificial cells further broadens the applicability of artificial membranes in studying the evolution of life.

Implanted artificial heart with radioisotope power source

Energy Technology Data Exchange (ETDEWEB)

Shumakov, V I; Griaznov, G M; Zhemchuzhnikov, G N; Kiselev, I M; Osipov, A P

1983-02-01

An atomic artificial heart for orthotopic implantation was developed with the following characteristics: volume, 1.2 L; weight, 1.5 kg; radioisotope power, 45 W; operating life, up to 5 years; hemodynamics, similar to natural hemodynamics. The artificial heart includes a thermal drive with systems for regulating power, feeding steam into the cylinders, return of the condensate to the steam generator, and delivery of power to the ventricles and heat container. The artificial heart is placed in an artificial pericardium partially filled with physiologic solution. It uses a steam engine with two operating cylinders that separately drive the left and right ventricles. There is no electronic control system in the proposed design. The operation of the heat engine is controlled, with preservation of autoregulation by the vascular system of the body. The separate drives for the ventricles is of primary importance as it provides for operation of the artificial heart through control of cardiac activity by venous return. Experimental testing on a hydromechanical bench demonstrated effective autoregulation.

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242

Directory of Open Access Journals (Sweden)

Ahmed R. J. Almusawi

2016-01-01

Full Text Available This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot’s joint angles.

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)

Science.gov (United States)

Dülger, L. Canan; Kapucu, Sadettin

2016-01-01

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles. PMID:27610129

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242).

Science.gov (United States)

Almusawi, Ahmed R J; Dülger, L Canan; Kapucu, Sadettin

2016-01-01

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles.

An artificial neural network approach to laser-induced breakdown spectroscopy quantitative analysis

International Nuclear Information System (INIS)

D’Andrea, Eleonora; Pagnotta, Stefano; Grifoni, Emanuela; Lorenzetti, Giulia; Legnaioli, Stefano; Palleschi, Vincenzo; Lazzerini, Beatrice

2014-01-01

The usual approach to laser-induced breakdown spectroscopy (LIBS) quantitative analysis is based on the use of calibration curves, suitably built using appropriate reference standards. More recently, statistical methods relying on the principles of artificial neural networks (ANN) are increasingly used. However, ANN analysis is often used as a ‘black box’ system and the peculiarities of the LIBS spectra are not exploited fully. An a priori exploration of the raw data contained in the LIBS spectra, carried out by a neural network to learn what are the significant areas of the spectrum to be used for a subsequent neural network delegated to the calibration, is able to throw light upon important information initially unknown, although already contained within the spectrum. This communication will demonstrate that an approach based on neural networks specially taylored for dealing with LIBS spectra would provide a viable, fast and robust method for LIBS quantitative analysis. This would allow the use of a relatively limited number of reference samples for the training of the network, with respect to the current approaches, and provide a fully automatizable approach for the analysis of a large number of samples. - Highlights: • A methodological approach to neural network analysis of LIBS spectra is proposed. • The architecture of the network and the number of inputs are optimized. • The method is tested on bronze samples already analyzed using a calibration-free LIBS approach. • The results are validated, compared and discussed

Artificial Intelligence (AI) Studies in Water Resources

OpenAIRE

Ay, Murat; Özyıldırım, Serhat

2018-01-01

Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

From Suns to Life: A Chronological Approach to the History of Life on Earth

CERN Document Server

Gargaud, Muriel; López-García, Purificación; Martin, Hervé; Montmerle, Thierry; Pascal, Robert; Reisse, Jacques

2006-01-01

This review emerged from several interdisciplinary meetings and schools gathering a group of astronomers, geologists, biologists, and chemists, attempting to share their specialized knowledge around a common question: how did life emerge on Earth? Their ultimate goal was to provide some kind of answer as a prerequisite to an even more demanding question: is life universal? The resulting state-of-the-art articles were written by twenty-five scientists telling a not-so linear story, but on the contrary, highlighting problems, gaps, and controversies. Needless to say, this approach yielded no definitive answers to both questions. However, by adopting a chronological approach to the question of the emergence of life on Earth, the only place where we know for sure that life exists; it was possible to break down this question into several sub-topics that can be addressed by the different disciplines. The main chapters of this review present the formation and evolution of the solar system (3); the building of a habi...

A new collaborative recommendation approach based on users clustering using artificial bee colony algorithm.

Science.gov (United States)

Ju, Chunhua; Xu, Chonghuan

2013-01-01

Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Chunhua Ju

2013-01-01

Full Text Available Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users’ preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods.

Nasogastric feeding at the end of life: a virtue ethics approach.

Science.gov (United States)

Krishna, Lalit

2011-07-01

The use of Nasogastric (NG) feeding in the provision of artificial nutrition and hydration at the end of life has, for the most part, been regarded as futile by the medical community. This position has been led chiefly by prevailing medical data. In Singapore, however, there has been an increase in its utilization supported primarily by social, religious and cultural factors expressly to prolong life of the terminally ill patient. Here this article will seek to review the ethical and clinical impact of this treatment and provide some understanding for such decisions in the light of the Duty of Palliative Care [DoPC]. Complemented by virtue ethics theory, the DoPC highlights and seeks to realize the individual case specific goals of care that maximize comfort and quality of life of the patient in the face of rapid attenuation of treatment options and the eminence of the final outcome by considering each of these factors individually in order to provide the best outcome for the patient and the family.

Life cycle management and assessment: approaches and visions towards sustainable manufacturing

DEFF Research Database (Denmark)

Westkämper, Engelbert; Alting, Leo; Arndt, Günther

2001-01-01

and optimizes the interaction of product design, manufacturing and life cycle activities. The goal of this approach is to protect resources and maximize effectiveness by means of life cycle assessment, product data management, technical support and, last but not least, life cycle costing. This paper shows....... Economically successful business areas can also be explored. Whether new service concepts are required, new regulations have been passed or consumer values are changing, the differences between business areas are disappearing. Life cycle management (LCM) considers the product life cycle as a whole...... the existing approaches of LCM and discusses their prospects and further development....

Artificial organs and transplantation.

Science.gov (United States)

Splendiani, G; Cipriani, S; Vega, A; Casciani, C U

2003-05-01

Nowadays artificial devices are not able to totally and undefinitely replace the loss of function of all vital organs and artificial organs can be used only to bridge the time to transplantation, which must be considered the first choice in the therapeutical approach for many chronic diseases. Since general population aging process is leading to an increase of organ demand, the gap between performed and requested transplantation is hard to fill. Xenotransplantation is nowadays only an experimental alternative solution and we have to do our best using available artificial organs to increase and improve the survival of patients waiting for transplantation. In this meeting we particularly dealt about organ function replacing therapy, especially regarding the kidney, heart, liver, pancreas and ear.

An Artificial Intelligence-Based Environment Quality Analysis System

OpenAIRE

Oprea , Mihaela; Iliadis , Lazaros

2011-01-01

Part 20: Informatics and Intelligent Systems Applications for Quality of Life information Services (ISQLIS) Workshop; International audience; The paper describes an environment quality analysis system based on a combination of some artificial intelligence techniques, artificial neural networks and rule-based expert systems. Two case studies of the system use are discussed: air pollution analysis and flood forecasting with their impact on the environment and on the population health. The syste...

Artificial intelligence applications in information and communication technologies

CERN Document Server

Bouguila, Nizar

2015-01-01

This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

Integration of Artificial Neural Network Modeling and Genetic Algorithm Approach for Enrichment of Laccase Production in Solid State Fermentation by Pleurotus ostreatus

OpenAIRE

Potu Venkata Chiranjeevi; Moses Rajasekara Pandian; Sathish Thadikamala

2014-01-01

Black gram husk was used as a solid substrate for laccase production by Pleurotus ostreatus, and various fermentation conditions were optimized based on an artificial intelligence method. A total of six parameters, i.e., temperature, inoculum concentration, moisture content, CuSO4, glucose, and peptone concentrations, were optimized. A total of 50 experiments were conducted, and the obtained data were modeled by a hybrid of artificial neural network (ANN) and genetic algorithm (GA) approaches...

Application of algorithms and artificial-intelligence approach for locating multiple harmonics in distribution systems

Energy Technology Data Exchange (ETDEWEB)

Hong, Y.-Y.; Chen, Y.-C. [Chung Yuan University (China). Dept. of Electrical Engineering

1999-05-01

A new method is proposed for locating multiple harmonic sources in distribution systems. The proposed method first determines the proper locations for metering measurement using fuzzy clustering. Next, an artificial neural network based on the back-propagation approach is used to identify the most likely location for multiple harmonic sources. A set of systematic algorithmic steps is developed until all harmonic locations are identified. The simulation results for an 18-busbar system show that the proposed method is very efficient in locating the multiple harmonics in a distribution system. (author)

Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

Science.gov (United States)

Ladstätter, Felix; Garrosa, Eva; Moreno-Jiménez, Bernardo; Ponsoda, Vicente; Reales Aviles, José Manuel; Dai, Junming

2016-01-01

Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling non-linearities in the hardiness-modulated burnout process with a neural network. Specifically, two multi-layer feed-forward artificial neural networks are concatenated in an attempt to model the composite non-linear burnout process. Sensitivity analysis, a Monte Carlo-based global simulation technique, is then utilised to examine the first-order effects of the predictor variables on the burnout sub-dimensions and consequences. Results show that (1) this concatenated artificial neural network approach is feasible to model the burnout process, (2) sensitivity analysis is a prolific method to study the relative importance of predictor variables and (3) the relationships among variables involved in the development of burnout and its consequences are to different degrees non-linear. Many relationships among variables (e.g., stressors and strains) are not linear, yet researchers use linear methods such as Pearson correlation or linear regression to analyse these relationships. Artificial neural network analysis is an innovative method to analyse non-linear relationships and in combination with sensitivity analysis superior to linear methods.

CANDU plant life management - An integrated approach

International Nuclear Information System (INIS)

Charlebois, P.; Hart, R.S.; Hopkins, J.R.

1998-01-01

Commercial versions of CANDU reactors were put into service starting more than 25 years ago. The first unit of Ontario Hydro's Pickering A station was put into service in 1971, and Bruce A in 1977. Most CANDU reactors, however, are only now approaching their mid-life of 15 to 20 years of operation. In particular, the first series of CANDU 6 plants which entered service in the early 1980's were designed for a 30 year life and are now approaching mid life. The current CANDU 6 design is based on a 40 year life as a result of advancement in design and materials through research and development. In order to assure safe and economic operation of these reactors, a comprehensive CANDU Plant Life Management (PLIM) program is being developed from the knowledge gained during the operation of Ontario Hydro's Pickering, Bruce, and Darlington stations, worldwide information from CANDU 6 stations, CANDU research and development programs, and other national and international sources. This integration began its first phase in 1994, with the identification of most of the critical systems structures and components in these stations, and a preliminary assessment of degradation and mechanisms that could affect their fitness for service for their planned life. Most of these preliminary assessments are now complete, together with the production of the first iteration of Life Management Plans for several of the systems and components. The Generic CANDU 6 PLIM program is now reaching its maturity, with formal processes to systematically identify and evaluate the major CSSCs in the station, and a plan to ensure that the plant surveillance, operation, and maintenance programs monitor and control component degradation well within the original design specifications essential for the plant life attainment. A Technology Watch program is being established to ensure that degradation mechanisms which could impact on plant life are promptly investigated and mitigating programs established. The

Life cycle reliability assessment of new products—A Bayesian model updating approach

International Nuclear Information System (INIS)

Peng, Weiwen; Huang, Hong-Zhong; Li, Yanfeng; Zuo, Ming J.; Xie, Min

2013-01-01

The rapidly increasing pace and continuously evolving reliability requirements of new products have made life cycle reliability assessment of new products an imperative yet difficult work. While much work has been done to separately estimate reliability of new products in specific stages, a gap exists in carrying out life cycle reliability assessment throughout all life cycle stages. We present a Bayesian model updating approach (BMUA) for life cycle reliability assessment of new products. Novel features of this approach are the development of Bayesian information toolkits by separately including “reliability improvement factor” and “information fusion factor”, which allow the integration of subjective information in a specific life cycle stage and the transition of integrated information between adjacent life cycle stages. They lead to the unique characteristics of the BMUA in which information generated throughout life cycle stages are integrated coherently. To illustrate the approach, an application to the life cycle reliability assessment of a newly developed Gantry Machining Center is shown

HYBRID HUMAN-ARTIFICIAL INTELLIGENCE APPROACH FOR PAVEMENT DISTRESS ASSESSMENT (PICUCHA

Directory of Open Access Journals (Sweden)

Reus Salini

2017-07-01

Full Text Available The pavement surface condition assessment is a critical component for a proper pavement management system as well as for pavement rehabilitation design. A number of devices were developed to automatically record surface distresses in a continuous survey mode, but the software required for automatic distress identification remains a big challenge. In this study, a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA is proposed to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence. It was designed from scratch to be capable to identify sealed and unsealed cracks, potholes, patches, different types of pavements and others. The self-learning algorithms do not use any distresses predefinition and can process images taken by cameras with different brands, technologies and resolution. This study describes some key aspects of the new method and provides examples in which PICUCHA was tested in real conditions showing accuracy up to 96.9% in image pattern detection and classification.

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

Science.gov (United States)

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

A life-course approach to health: synergy with sustainable development goals.

Science.gov (United States)

Kuruvilla, Shyama; Sadana, Ritu; Montesinos, Eugenio Villar; Beard, John; Vasdeki, Jennifer Franz; Araujo de Carvalho, Islene; Thomas, Rebekah Bosco; Drisse, Marie-Noel Brunne; Daelmans, Bernadette; Goodman, Tracey; Koller, Theadora; Officer, Alana; Vogel, Joanna; Valentine, Nicole; Wootton, Emily; Banerjee, Anshu; Magar, Veronica; Neira, Maria; Bele, Jean Marie Okwo; Worning, Anne Marie; Bustreo, Flavia

2018-01-01

A life-course approach to health encompasses strategies across individuals' lives that optimize their functional ability (taking into account the interdependence of individual, social, environmental, temporal and intergenerational factors), thereby enabling well-being and the realization of rights. The approach is a perfect fit with efforts to achieve universal health coverage and meet the sustainable development goals (SDGs). Properly applied, a life-course approach can increase the effectiveness of the former and help realize the vision of the latter, especially in ensuring health and well-being for all at all ages. Its implementation requires a shared understanding by individuals and societies of how health is shaped by multiple factors throughout life and across generations. Most studies have focused on noncommunicable disease and ageing populations in high-income countries and on epidemiological, theoretical and clinical issues. The aim of this article is to show how the life-course approach to health can be extended to all age groups, health topics and countries by building on a synthesis of existing scientific evidence, experience in different countries and advances in health strategies and programmes. A conceptual framework for the approach is presented along with implications for implementation in the areas of: (i) policy and investment; (ii) health services and systems; (iii) local, multisectoral and multistakeholder action; and (iv) measurement, monitoring and research. The SDGs provide a unique context for applying a holistic, multisectoral approach to achieving transformative outcomes for people, prosperity and the environment. A life-course approach can reinforce these efforts, particularly given its emphasis on rights and equity.

Artificial intelligence in nanotechnology.

Science.gov (United States)

Sacha, G M; Varona, P

2013-11-15

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

Artificial intelligence in nanotechnology

Science.gov (United States)

Sacha, G. M.; Varona, P.

2013-11-01

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

Artificial intelligence in nanotechnology

International Nuclear Information System (INIS)

Sacha, G M; Varona, P

2013-01-01

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

An effective hierarchical model for the biomolecular covalent bond: an approach integrating artificial chemistry and an actual terrestrial life system.

Science.gov (United States)

Oohashi, Tsutomu; Ueno, Osamu; Maekawa, Tadao; Kawai, Norie; Nishina, Emi; Honda, Manabu

2009-01-01

Under the AChem paradigm and the programmed self-decomposition (PSD) model, we propose a hierarchical model for the biomolecular covalent bond (HBCB model). This model assumes that terrestrial organisms arrange their biomolecules in a hierarchical structure according to the energy strength of their covalent bonds. It also assumes that they have evolutionarily selected the PSD mechanism of turning biological polymers (BPs) into biological monomers (BMs) as an efficient biomolecular recycling strategy We have examined the validity and effectiveness of the HBCB model by coordinating two complementary approaches: biological experiments using existent terrestrial life, and simulation experiments using an AChem system. Biological experiments have shown that terrestrial life possesses a PSD mechanism as an endergonic, genetically regulated process and that hydrolysis, which decomposes a BP into BMs, is one of the main processes of such a mechanism. In simulation experiments, we compared different virtual self-decomposition processes. The virtual species in which the self-decomposition process mainly involved covalent bond cleavage from a BP to BMs showed evolutionary superiority over other species in which the self-decomposition process involved cleavage from BP to classes lower than BM. These converging findings strongly support the existence of PSD and the validity and effectiveness of the HBCB model.

Quality of life among lower limb prosthesis users attending Artificial Limb Center of Fauji Foundation Hospital Rawalpindi

International Nuclear Information System (INIS)

Kalsoom, U.; Bairam, S.

2018-01-01

To assess quality of life and the influencing factors as perceived by lower limb prosthesis users. Study Design: Cross sectional study. Place and Duration of Study: Artificial Limb Centre, Fauji Foundation Hospital Rawalpindi, 11 months (Jan to Nov 2014). Material and Methods: A sample of 50 patients with lower limb amputations and using lower limb prosthesis were recruited by applying inclusion criteria. Responses were recorded on demographic variables, reasons for amputation, time of provision of prosthesis, employment status etc. by the investigator on a structured pretested questionnaire after their consent. A p-value of <0.05 was taken as significant. Quality of life was interpreted on 5 point Likert scale. Data was analyzed in SPSS version 21. Result: Majority of respondents i.e. 17 (34%) were in 51-60 years age group with mean age 46 +- 14 years while 33 (66%) were males and 27 (54%) illiterate, 33 (66%) could afford a prosthesis. Trauma 28 (56%) was the most prevalent cause of lower limb amputation and among them 15 (53%) had road accident injuries. Various factors influenced quality of life as perceived by the respondents and in 10 (20%), 16 (32%), 25 (50%) social, family life and emotional status was affected respectively, while 14 (28%) of the prosthesis user were unemployed. Prosthesis were provided after 2 years in 18 (36%) and in 37 (74%) prosthesis were provided by the health care facility. Good quality of life was perceived in 40 (80%) respondents. Conclusion: Perceived Quality of life was good in majority of the prosthesis users but others can't be ignored. It can be improved by early provision of prosthesis which can help in better employment opportunities. (author)

Life support approaches for Mars missions

Science.gov (United States)

Drysdale, A. E.; Ewert, M. K.; Hanford, A. J.

Life support approaches for Mars missions are evaluated using an equivalent system mass (ESM) approach, in which all significant costs are converted into mass units. The best approach, as defined by the lowest mission ESM, depends on several mission parameters, notably duration, environment and consequent infrastructure costs, and crew size, as well as the characteristics of the technologies which are available. Generally, for the missions under consideration, physicochemical regeneration is most cost effective. However, bioregeneration is likely to be of use for producing salad crops for any mission, for producing staple crops for medium duration missions, and for most food, air and water regeneration for long missions (durations of a decade). Potential applications of in situ resource utilization need to be considered further.

Design Of the Approximation Function of a Pedometer based on Artificial Neural Network for the Healthy Life Style Promotion in Diabetic Patients

OpenAIRE

Vega Corona, Antonio; Zárate Banda, Magdalena; Barron Adame, Jose Miguel; Martínez Celorio, René Alfredo; Andina de la Fuente, Diego

2008-01-01

The present study describes the design of an Artificial Neural Network to synthesize the Approximation Function of a Pedometer for the Healthy Life Style Promotion. Experimentally, the approximation function is synthesized using three basic digital pedometers of low cost, these pedometers were calibrated with an advanced pedometer that calculates calories consumed and computes distance travelled with personal stride input. The synthesized approximation function by means of the designed neural...

Modular Extended-Stay HyperGravity Facility Design Concept: An Artificial-Gravity Space-Settlement Ground Analogue

Science.gov (United States)

Dorais, Gregory A.

2015-01-01

This document defines the design concept for a ground-based, extended-stay hypergravity facility as a precursor for space-based artificial-gravity facilities that extend the permanent presence of both human and non-human life beyond Earth in artificial-gravity settlements. Since the Earth's current human population is stressing the environment and the resources off-Earth are relatively unlimited, by as soon as 2040 more than one thousand people could be living in Earthorbiting artificial-gravity habitats. Eventually, the majority of humanity may live in artificialgravity habitats throughout this solar system as well as others, but little is known about the longterm (multi-generational) effects of artificial-gravity habitats on people, animals, and plants. In order to extend life permanently beyond Earth, it would be useful to create an orbiting space facility that generates 1g as well as other gravity levels to rigorously address the numerous challenges of such an endeavor. Before doing so, developing a ground-based artificial-gravity facility is a reasonable next step. Just as the International Space Station is a microgravity research facility, at a small fraction of the cost and risk a ground-based artificial-gravity facility can begin to address a wide-variety of the artificial-gravity life-science questions and engineering challenges requiring long-term research to enable people, animals, and plants to live off-Earth indefinitely.

Folding pathways explored with artificial potential functions

International Nuclear Information System (INIS)

Ulutaş, B; Bozma, I; Haliloglu, T

2009-01-01

This paper considers the generation of trajectories to a given protein conformation and presents a novel approach based on artificial potential functions—originally proposed for multi-robot navigation. The artificial potential function corresponds to a simplified energy model, but with the novelty that—motivated by work on robotic navigation—a nonlinear compositional scheme of constructing the energy model is adapted instead of an additive formulation. The artificial potential naturally gives rise to a dynamic system for the protein structure that ensures collision-free motion to an equilibrium point. In cases where the equilibrium point is the native conformation, the motion trajectory corresponds to the folding pathway. This framework is used to investigate folding in a variety of protein structures, and the results are compared with those of other approaches including experimental studies

Goles en césped artificial: más duradero y sostenible

OpenAIRE

Sanchís Almenara, Mercedes; Rosa Mañez, David; Magraner Llavador, Laura; Pellicer Chenoll, Maria Teresa; GARCIA BELENGUER, ANA CRUZ; Ballester Fernandez, Alfredo; Chirivella Moreno, Carlos; Garcés Pérez, Luis

2012-01-01

[EN] Currently there are installed approximately 25 millions of square meters of artificial turf for contact sports use in Europe (football, rugby, etc.). It means that at the end of their cycle of life 400.000 tones of non-dangerous materials will be placed in controlled landfills. The first aim of this project is to increase the useful life of artificial turf pitches in good conditions of use; and the second objective is to reuse and/or recycle the materi...

Artificial companions as personal coach for children: The Interactive Drums Teacher

OpenAIRE

Courgeon , Matthieu; Duhaut , Dominique

2015-01-01

International audience; The MOCA Project that aims at designing and studying the interaction and relationship between artificial companions and children in everyday life at home activities. Artificial companions are digital embodied entities that can be either robotic or virtual. In this paper, we focus on a single activity, subpart of the whole project: a coaching application that uses two artificial companions to teach the basics of drums to children. One device is a Nao robot, the other is...

A multiscale approach for modeling actuation response of polymeric artificial muscles.

Science.gov (United States)

Sharafi, Soodabeh; Li, Guoqiang

2015-05-21

Artificial muscles are emerging materials in the field of smart materials with applications in aerospace, robotic, and biomedical industries. Despite extensive experimental investigations in this field, there is a need for numerical modeling techniques that facilitate cutting edge research and development. This work aims at studying an artificial muscle made of twisted Nylon 6.6 fibers that are highly cold-drawn. A computationally efficient phenomenological thermo-mechanical constitutive model is developed in which several physical properties of the artificial muscles are incorporated to minimize the trial-and-error numerical curve fitting processes. Two types of molecular chains are considered at the micro-scale level that control training and actuation processes viz. (a) helically oriented chains which are structural switches that store a twisted shape in their low temperature phase and restore their random configuration during the thermal actuation process, and (b) entropic chains which are highly drawn chains that could actuate as soon as the muscle heats up, and saturates when coil contact temperature is reached. The thermal actuation response of the muscle over working temperatures has been elaborated in the Modeling section. The performance of the model is validated by available experiments in the literature. The model may provide a design platform for future artificial muscle developments.

Surgery-first orthognathic approach vs traditional orthognathic approach: Oral health-related quality of life assessed with 2 questionnaires.

Science.gov (United States)

Pelo, Sandro; Gasparini, Giulio; Garagiola, Umberto; Cordaro, Massimo; Di Nardo, Francesco; Staderini, Edoardo; Patini, Romeo; de Angelis, Paolo; D'Amato, Giuseppe; Saponaro, Gianmarco; Moro, Alessandro

2017-08-01

The purposes of the study were to investigate and evaluate the differences detected by the patients between the traditional orthognathic approach and the surgery-first one in terms of level of satisfaction and quality of life. A total of 30 patients who underwent orthognathic surgery for correction of malocclusions were selected and included in this study. Fifteen patients were treated with the conventional orthognathic surgery approach, and 15 patients with the surgery-first approach. Variables were assessed through the Orthognathic Quality of Life Questionnaire and the Oral Health Impact Profile questionnaire and analyzed with 2-way repeated-measures analysis of variance. The results showed significant differences in terms of the Orthognathic Quality of Life Questionnaire (P surgery in the surgery-first group and an initial worsening during orthodontic treatment in the traditional approach group followed by postoperative improvement. This study showed that the worsening of the facial profile during the traditional orthognathic surgery approach decompensation phase has a negative impact on the perception of patients' quality of life. Surgeons should consider the possibility of a surgery-first approach to prevent this occurrence. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

Science.gov (United States)

Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

2007-12-01

The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

Exergy analysis of an ejector-absorption heat transformer using artificial neural network approach

International Nuclear Information System (INIS)

Soezen, Adnan; Arcaklioglu, Erol

2007-01-01

This paper proposes artificial neural networks (ANNs) technique as a new approach to determine the exergy losses of an ejector-absorption heat transformer (EAHT). Thermodynamic analysis of the EAHT is too complex due to complex differential equations and complex simulations programs. ANN technique facilitates these complicated situations. This study is considered to be helpful in predicting the exergetic performance of components of an EAHT prior to its setting up in a thermal system where the working temperatures are known. The best approach was investigated using different algorithms with developed software. The best statistical coefficient of multiple determinations (R 2 -value) for training data equals to 0.999715, 0.995627, 0.999497, and 0.997648 obtained by different algorithms with seven neurons for the non-dimensional exergy losses of evaporator, generator, absorber and condenser, respectively. Similarly these values for testing data are 0.999774, 0.994039, 0.999613 and 0.99938, respectively. The results show that this approach has the advantages of computational speed, low cost for feasibility, rapid turnaround, which is especially important during iterative design phases, and easy of design by operators with little technical experience

Artificial Intelligence Approach to the Determination of Physical Properties of Eclipsing Binaries. I. The EBAI Project

Science.gov (United States)

Prša, A.; Guinan, E. F.; Devinney, E. J.; DeGeorge, M.; Bradstreet, D. H.; Giammarco, J. M.; Alcock, C. R.; Engle, S. G.

2008-11-01

Achieving maximum scientific results from the overwhelming volume of astronomical data to be acquired over the next few decades demands novel, fully automatic methods of data analysis. Here we concentrate on eclipsing binary (EB) stars, a prime source of astrophysical information, of which only some hundreds have been rigorously analyzed, but whose numbers will reach millions in a decade. We describe the artificial neural network (ANN) approach which is able to surmount the human bottleneck and permit EB-based scientific yield to keep pace with future data rates. The ANN, following training on a sample of 33,235 model light curves, outputs a set of approximate model parameters [T2/T1, (R1 + R2)/a, esin ω , ecos ω , and sin i] for each input light curve data set. The obtained parameters can then be readily passed to sophisticated modeling engines. We also describe a novel method polyfit for preprocessing observational light curves before inputting their data to the ANN and present the results and analysis of testing the approach on synthetic data and on real data including 50 binaries from the Catalog and Atlas of Eclipsing Binaries (CALEB) database and 2580 light curves from OGLE survey data. The success rate, defined by less than a 10% error in the network output parameter values, is approximately 90% for the OGLE sample and close to 100% for the CALEB sample—sufficient for a reliable statistical analysis. The code is made available to the public. Our approach is applicable to EB light curves of all classes; this first paper in the eclipsing binaries via artificial intelligence (EBAI) series focuses on detached EBs, which is the class most challenging for this approach.

Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

Science.gov (United States)

Chen, Chau-Kuang

2010-01-01

Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

Artificial hammerhead ribozymes: engineering and applications

International Nuclear Information System (INIS)

Vorobjeva, M A; Davydova, A S; Venyaminova, Aliya G

2011-01-01

The properties of hammerhead ribozymes are described. Various hammerhead ribozyme constructs for target RNA cleavage were considered. Approaches to enhancement of the stability of artificial ribozymes in biological media and to regulation of the catalytic activity of hammerhead ribozymes using effector molecules are described. The effect of ribozymes on extended structured natural RNAs is discussed. Applications of artificial hammerhead ribozymes as inhibitors of gene expression at matrix RNA level were considered.

Ethical Issues of Artificial Biomedical Applications

OpenAIRE

Alexiou , Athanasios; Psixa , Maria; Vlamos , Panagiotis

2011-01-01

Part 12: Medical Applications of ANN and Ethics of AI; International audience; While the plethora of artificial biomedical applications is enriched and combined with the possibilities of artificial intelligence, bioinformatics and nanotechnology, the variability in the ideological use of such concepts is associated with bioethical issues and several legal aspects. The convergence of bioethics and computer ethics, attempts to illustrate and approach problems, occurring by the fusion of human a...

Parental perceptions of forgoing artificial nutrition and hydration during end-of-life care.

Science.gov (United States)

Rapoport, Adam; Shaheed, Jenny; Newman, Christine; Rugg, Maria; Steele, Rose

2013-05-01

Forgoing artificial nutrition and hydration (FANH) in children at the end of life (EOL) is a medically, legally, and ethically acceptable practice under specific circumstances. However, most of the evidence on FANH involves dying adults. There is a paucity of pediatric evidence to guide health care providers' and parents' decision-making around this practice. Objectives were (1) to explore the experiences of bereaved parents when a decision had been made to FANH during EOL care for their child and (2) to describe the perceived quality of death in these children, as reported by their parents. This was a qualitative study using in-depth interviews with parents whose children died after a decision to FANH. Parental perceptions about the experience and their child's quality of death were explored. Interviews were audiotaped and transcribed, then data were analyzed by using interpretive description methodology. All parents were satisfied with their decision to FANH and believed that their child's death was generally peaceful and comfortable. The child's perceived poor quality of life was central to the decision to FANH, with feeding intolerance often contributing to this perception. Despite overall satisfaction, all parents had doubts and questions about the decision and benefited from ongoing assurances from the clinical team. FANH in children at the EOL is an acceptable form of palliation for some parents and may contribute to a death that is perceived to be peaceful and comfortable. In situations in which FANH may be a reasonable possibility, physicians should be prepared to introduce the option.

Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

Directory of Open Access Journals (Sweden)

Karin Kandananond

2011-08-01

Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

Artificial organs 2011: a year in review.

Science.gov (United States)

Malchesky, Paul S

2012-03-01

In this Editor's Review, articles published in 2011 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal would not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely well-received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. We look forward to recording further advances in the coming years. © 2012, Copyright the Author. Artificial Organs © 2012, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Artificial Organs 2012: a year in review.

Science.gov (United States)

Malchesky, Paul S

2013-03-01

In this editor's review, articles published in 2012 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. As the official journal of the International Federation for Artificial Organs, the International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide such meaningful suggestions to the author's work whether eventually accepted or rejected, and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our publisher, Wiley Periodicals, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to recording further advances in the coming years. © 2013, Copyright the Author. Artificial Organs © 2013, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

An artificial neural network approach for aerodynamic performance retention in airframe noise reduction design of a 3D swept wing model

Directory of Open Access Journals (Sweden)

Tao Jun

2016-10-01

Full Text Available With the progress of high-bypass turbofan and the innovation of silencing nacelle in engine noise reduction, airframe noise has now become another important sound source besides the engine noise. Thus, reducing airframe noise makes a great contribution to the overall noise reduction of a civil aircraft. However, reducing airframe noise often leads to aerodynamic performance loss in the meantime. In this case, an approach based on artificial neural network is introduced. An established database serves as a basis and the training sample of a back propagation (BP artificial neural network, which uses confidence coefficient reasoning method for optimization later on. Then the most satisfactory configuration is selected for validating computations through the trained BP network. On the basis of the artificial neural network approach, an optimization process of slat cove filler (SCF for high lift devices (HLD on the Trap Wing is presented. Aerodynamic performance of both the baseline and optimized configurations is investigated through unsteady detached eddy simulations (DES, and a hybrid method, which combines unsteady DES method with acoustic analogy theory, is employed to validate the noise reduction effect. The numerical results indicate not merely a significant airframe noise reduction effect but also excellent aerodynamic performance retention simultaneously.

Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Fei Song

2014-01-01

Full Text Available This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

Integrated NPP life cycle management - Agency's approach

International Nuclear Information System (INIS)

Gueorguiev, B.

2002-01-01

Full text: The number of nuclear power plants (NPPs) operating in the world has been roughly constant for the past seven years. There are 438 reactors of 353,489 MW(e) capacity in the world and they generated 2448.9 TWh in 2001 giving a total world operating experience with nuclear power of 10,363 years. About 230 units have reached already over 15 years of operation and significant number of these plants are fully depreciated. Share of nuclear power in electricity production sector in Member States utilising nuclear power plants represents a meaningful amount and in 14 countries it exceeds 30%. Therefore, a loss of this share should be covered by new installed capacities either from conventional or alternative sources of electricity generation. Recent forecasts, for nuclear power use over the next two decades range from ∼350 to ∼500 GW(e) worldwide. While assessing the need for any nuclear power related programmes there are several important factors that must be considered since even 350 GW(e) is a very large programme requiring several hundred thousand highly qualified personnel and a substantial infrastructure to assure its continued safe, reliable and cost-effective operation. It is important to assure reliable, safe and economic beneficial performance of the plant, which requires in turn an appropriated management of any activity connected with any taken period of a plant life starting from design and ending by the decided mode of decommissioning. The period between the first and the last payment for the activities connected with the existence of a plant could be defined as a life cycle of the plant. Such integrated approach requires considering the life cycle of the plant in a much broader sense than just operational life and is characterized by the variety of activities and their management represents in a whole a plant life management programme (PLIM). Therefore PLIM could be defined as an aggregate (totality) of technical, financial, economical and

Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

Science.gov (United States)

Srimani, P. K.; Parimala, Y. G.

2011-12-01

A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.

A genetic-neural artificial intelligence approach to resins optimization

International Nuclear Information System (INIS)

Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A.

2005-01-01

This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

An approach to incorporate risks into a product's life-cycle assessment

International Nuclear Information System (INIS)

Pirhonen, P.

1995-01-01

Life-cycle assessment is usually based on regular discharges that occur at a more or less constant rate. Nevertheless, the more factors that are taken into account in the LCA the better picture it gives on the environmental aspects of a product. In this study an approach to incorporate accidental releases into a products' life-cycle assessment was developed. In this approach accidental releases are divided into two categories. The first category consists of those unplanned releases which occur with a predicted level and frequency. Due to the high frequency and small release size at a time, these accidental releases can be compared to continuous emissions. Their global impacts are studied in this approach. Accidental releases of the second category are sudden, unplanned releases caused by exceptional situations, e.g. technical failure, action error or disturbances in process conditions. These releases have a singular character and local impacts are typical of them. As far as the accidental releases of the second category are concerned, the approach introduced in this study results in a risk value for every stage of a life-cycle, the sum of which is a risk value for the whole life-cycle. Risk value is based on occurrence frequencies of incidents and potential environmental damage caused by releases. Risk value illustrates the level of potential damage caused by accidental releases related to the system under study and is meant to be used for comparison of these levels of two different products. It can also be used to compare the risk levels of different stages of the life-cycle. An approach was illustrated using petrol as an example product. The whole life-cycle of petrol from crude oil production to the consumption of petrol was studied

Patterns recognition of electric brain activity using artificial neural networks

Science.gov (United States)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Predicting concrete corrosion of sewers using artificial neural network.

Science.gov (United States)

Jiang, Guangming; Keller, Jurg; Bond, Philip L; Yuan, Zhiguo

2016-04-01

Corrosion is often a major failure mechanism for concrete sewers and under such circumstances the sewer service life is largely determined by the progression of microbially induced concrete corrosion. The modelling of sewer processes has become possible due to the improved understanding of in-sewer transformation. Recent systematic studies about the correlation between the corrosion processes and sewer environment factors should be utilized to improve the prediction capability of service life by sewer models. This paper presents an artificial neural network (ANN)-based approach for modelling the concrete corrosion processes in sewers. The approach included predicting the time for the corrosion to initiate and then predicting the corrosion rate after the initiation period. The ANN model was trained and validated with long-term (4.5 years) corrosion data obtained in laboratory corrosion chambers, and further verified with field measurements in real sewers across Australia. The trained model estimated the corrosion initiation time and corrosion rates very close to those measured in Australian sewers. The ANN model performed better than a multiple regression model also developed on the same dataset. Additionally, the ANN model can serve as a prediction framework for sewer service life, which can be progressively improved and expanded by including corrosion rates measured in different sewer conditions. Furthermore, the proposed methodology holds promise to facilitate the construction of analytical models associated with corrosion processes of concrete sewers. Copyright © 2016 Elsevier Ltd. All rights reserved.

A biomimetic approach toward artificial bone-like materials

OpenAIRE

Bertozzi, Carolyn R.

2001-01-01

Bone consists of microcrystalline hydroxyapatite and collagen, an elastic protein matrix that is decorated with mineral-nucleating phosphoproteins. Our rational design of artificial bone-like material uses natural bone as a guide. Hydrogel and self-assembling polymers that possess anionic groups suitably positioned for nucleating biominerals, and therefore mimic the natural function of the collagen-phosphoprotein matrix in bone, were designed to direct template-driven biomimetic mineralizatio...

HUMAN EXPOSURE TO THE ARTIFICIAL RADIONUCLIDES IN ENVIRONMENT

Directory of Open Access Journals (Sweden)

Ivana Vukanac

2012-09-01

Full Text Available Artificial radionuclides are product of different human activities and their presence in the environment is negative side effect of civilization progress. They have been spread in the environment by events such as nuclear weapon tests, nuclear accidents and by deliberate and negligent discharge of radioactive waste from nuclear and other installation. Once released in to the nature, the artificial radionuclides start to circle in the same manner as naturally occurring ones, and finally they fall out from air and water onto the ground and build into the foodstuff and drinking water resulting in radiation doses to human beings. The short overview of presence of artificial radioactivity in human environment and its impact on human life is presented in this paper.

HUMAN EXPOSURE TO THE ARTIFICIAL RADIONUCLIDES IN ENVIRONMENT

Directory of Open Access Journals (Sweden)

Ivana Vukanac

2012-09-01

Full Text Available Artificial radionuclides are product of different human activities and their presence in the environment is negative side effect of civilization progress. They have been spread in the environment by events such as nuclear weapon tests, nuclear accidents and by deliberate and negligent discharge of radioactive waste from nuclear and other installation. Once released in to the nature, the artificial radionuclides start to circle in the same manner as naturally occurring ones, and finally they fall out from air and water onto the ground and build into the foodstuff and drinking water resulting in radiation doses to human beings. The short overview of presence of artificial radioactivity in human environment and its impact on human life is presented in this paper

Biologically inspired technologies using artificial muscles

Science.gov (United States)

Bar-Cohen, Yoseph

2005-01-01

After billions of years of evolution, nature developed inventions that work, which are appropriate for the intended tasks and that last. The evolution of nature led to the introduction of highly effective and power efficient biological mechanisms that are scalable from micron to many meters in size. Imitating these mechanisms offers enormous potentials for the improvement of our life and the tools we use. Humans have always made efforts to imitate nature and we are increasingly reaching levels of advancement where it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. Some of the biomimetic technologies that have emerged include artificial muscles, artificial intelligence, and artificial vision to which significant advances in materials science, mechanics, electronics, and computer science have contributed greatly. One of the newest fields of biomimetics is the electroactive polymers (EAP) that are also known as artificial muscles. To take advantage of these materials, efforts are made worldwide to establish a strong infrastructure addressing the need for comprehensive analytical modeling of their operation mechanism and develop effective processing and characterization techniques. The field is still in its emerging state and robust materials are not readily available however in recent years significant progress has been made and commercial products have already started to appear. This paper covers the state-of-the-art and challenges to making artificial muscles and their potential biomimetic applications.

Artificial organs 2010: a year in review.

Science.gov (United States)

Malchesky, Paul S

2011-03-01

In this Editor's Review, articles published in 2010 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide such meaningful suggestions to the author's work whether eventually accepted or rejected and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. We look forward to recording further advances in the coming years. © 2011, Copyright the Author. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Artificial neural network based approach to transmission lines protection

International Nuclear Information System (INIS)

Joorabian, M.

1999-05-01

The aim of this paper is to present and accurate fault detection technique for high speed distance protection using artificial neural networks. The feed-forward multi-layer neural network with the use of supervised learning and the common training rule of error back-propagation is chosen for this study. Information available locally at the relay point is passed to a neural network in order for an assessment of the fault location to be made. However in practice there is a large amount of information available, and a feature extraction process is required to reduce the dimensionality of the pattern vectors, whilst retaining important information that distinguishes the fault point. The choice of features is critical to the performance of the neural networks learning and operation. A significant feature in this paper is that an artificial neural network has been designed and tested to enhance the precision of the adaptive capabilities for distance protection

Artificial Consciousness or Artificial Intelligence

OpenAIRE

Spanache Florin

2017-01-01

Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

Safe-life and damage-tolerant design approaches for helicopter structures

Science.gov (United States)

Reddick, H. K., Jr.

1983-01-01

The safe-life and damage-tolerant design approaches discussed apply to both metallic and fibrous composite helicopter structures. The application of these design approaches to fibrous composite structures is emphasized. Safe-life and damage-tolerant criteria are applied to all helicopter flight critical components, which are generally categorized as: dynamic components with a main and tail rotor system, which includes blades, hub and rotating controls, and drive train which includes transmission, and main and interconnecting rotor shafts; and the airframe, composed of the fuselage, aerodynamic surfaces, and landing gear.

Artificial Organs 2015: A Year in Review.

Science.gov (United States)

Malchesky, Paul S

2016-03-01

In this Editor's Review, articles published in 2015 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for providing their work to this journal. We offer our very special thanks to our reviewers who give so generously of their time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. Copyright © 2016 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Artificial Organs 2013: a year in review.

Science.gov (United States)

Malchesky, Paul S

2014-03-01

In this Editor's Review, articles published in 2013 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level". Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide so meaningful suggestions to the author's work whether eventually accepted or rejected and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, Wiley Periodicals, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to recording further advances in the coming years. © 2014 Wiley Periodicals, Inc. and International Center for Artificial Organs and Transplantation.

Life course approach in social epidemiology: an overview, application and future implications.

Science.gov (United States)

Cable, Noriko

2014-01-01

The application of the life course approach to social epidemiology has helped epidemiologists theoretically examine social gradients in population health. Longitudinal data with rich contextual information collected repeatedly and advanced statistical approaches have made this challenging task easier. This review paper provides an overview of the life course approach in epidemiology, its research application, and future challenges. In summary, a systematic approach to methods, including theoretically guided measurement of socioeconomic position, would assist researchers in gathering evidence for reducing social gradients in health, and collaboration across individual disciplines will make this task achievable.

Artificial Aging as a Predictor of Paper's Future Useful Life.

Science.gov (United States)

Bansa, Helmut; Hofer, Hans-H.

1989-01-01

An experiment with the artificial aging of paper which--in contrast with the usual practice--was carried out at relatively low temperatures (i.e., 50-95 degrees Celsius), and not on laboratory handsheets, but on naturally aged paper from the commercial production of four centuries, produced results justifying the thesis that there may be at best…

Update on Renal Replacement Therapy: Implantable Artificial Devices and Bioengineered Organs.

Science.gov (United States)

Attanasio, Chiara; Latancia, Marcela T; Otterbein, Leo E; Netti, Paolo A

2016-08-01

Recent advances in the fields of artificial organs and regenerative medicine are now joining forces in the areas of organ transplantation and bioengineering to solve continued challenges for patients with end-stage renal disease. The waiting lists for those needing a transplant continue to exceed demand. Dialysis, while effective, brings different challenges, including quality of life and susceptibility to infection. Unfortunately, the majority of research outputs are far from delivering satisfactory solutions. Current efforts are focused on providing a self-standing device able to recapitulate kidney function. In this review, we focus on two remarkable innovations that may offer significant clinical impact in the field of renal replacement therapy: the implantable artificial renal assist device (RAD) and the transplantable bioengineered kidney. The artificial RAD strategy utilizes micromachining techniques to fabricate a biohybrid system able to mimic renal morphology and function. The current trend in kidney bioengineering exploits the structure of the native organ to produce a kidney that is ready to be transplanted. Although these two systems stem from different technological approaches, they are both designed to be implantable, long lasting, and free standing to allow patients with kidney failure to be autonomous. However, for both of them, there are relevant issues that must be addressed before translation into clinical use and these are discussed in this review.

Optimizing radiologic workup: An artificial intelligence approach

International Nuclear Information System (INIS)

Swett, H.A.; Rothschild, M.; Weltin, G.G.; Fisher, P.R.; Miller, P.L.

1987-01-01

The increasing complexity of diagnostic imaging is presenting an ever-expanding variety of radiologic test options to referring clinicians, making it more difficult for them to plan efficient workup. Diagnosis-oriented reimbursement systems are providing new incentives for hospitals and radiologists to use imaging modalities judiciously. This paper describes DxCON, a developmental artificial intelligence-based computer system, which gives advice to physicians about the optimum sequencing of radiologic tests. DxCON analyzes a physician's proposed workup plan and discusses its strengths and weaknesses. The domain chosen for this research is the imaging workup of obstructive jaundice

Origin of life. The role of experiments, basic beliefs, and social authorities in the controversies about the spontaneous generation of life and the subsequent debates about synthesizing life in the laboratory.

Science.gov (United States)

Deichmann, Ute

2012-01-01

For centuries the question of the origin of life had focused on the question of the spontaneous generation of life, at least primitive forms of life, from inanimate matter, an idea that had been promoted most prominently by Aristotle. The widespread belief in spontaneous generation, which had been adopted by the Church, too, was finally abandoned at the beginning of the twentieth century, when the question of the origin of life became related to that of the artificial generation of life in the laboratory. This paper examines the role of social authorities, researchers' basic beliefs, crucial experiments, and scientific advance in the controversies about spontaneous generation from the seventeenth to the nineteenth centuries and analyzes the subsequent debates about the synthesis of artificial life in the changing scientific contexts of the nineteenth and early-twentieth centuries. It shows that despite the importance of social authorities, basic beliefs, and crucial experiments scientific advances, especially those in microbiology, were the single most important factor in the stepwise abandoning of the doctrine of spontaneous generation. Research on the origin of life and the artificial synthesis of life became scientifically addressed only when it got rid of the idea of constant smooth transitions between inanimate matter and life and explored possible chemical and physical mechanisms of the specificity of basic molecules and processes of life.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

International Nuclear Information System (INIS)

Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

2011-01-01

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives.

Science.gov (United States)

Cordier, Marie-Odile; Dague, Philippe; Lévy, François; Montmain, Jacky; Staroswiecki, Marcel; Travé-Massuyès, Louise

2004-10-01

Two distinct and parallel research communities have been working along the lines of the model-based diagnosis approach: the fault detection and isolation (FDI) community and the diagnostic (DX) community that have evolved in the fields of automatic control and artificial intelligence, respectively. This paper clarifies and links the concepts and assumptions that underlie the FDI analytical redundancy approach and the DX consistency-based logical approach. A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.

Perspectives for the information approach application to natural and artificial ecosystems investigation

Science.gov (United States)

Lankin, Yuliy

As a methodological matter, all modern conceptions of life development can be subdivided into the substrate (S), the energetic (E) and the informational (I). The S-conception is based on biochemical, genetic and morphological ideas. The E-conception deals with an idea of development of complicated open systems (COS) which are characterized by energy getting constantly from the outside, by improvement of substance cycles and as speeding-up and increasing of "power" of them as well, and by increasing of energy intensity transformation by the each structure of COS. The I-conception has been developing so far in the main within the frameworks of the traditional both cybernetic ideas and information theory that are convenient for many technical applications but are deficient for investigation of ecoand bio-systems. Situation was changed when the conception of adaptive systems (CAS) based on the ideas of ecology, biology and neurocybernetic (neuroinforamtic) had offered. As a consequence of this, the I-conception based on the CAS well accords with the S- and the E-conceptions and allows to hope to their combine into one the S + E + I conception that will include all virtues of the S-, the E-, and the I-conceptions and eliminate of their limitations. Thanks to relative easiness of hierarchic adaptive nonlinear models making using of the CAS, it is possible overcome effectively both of the problems as the "dimensionality problem" and the "loss of stability" as well for complicated models of ecosystems (CME). Optimization of energy and substance consumption process and adaptation of the CME to changes of current conditions are well realized in ranges given by goal function. A use adaptive networks (including neural nets) in frames of the CAS allows to realize any continuous function in control loops and at information processing. The considered features of the S + E + I proposed approach based on the CAS make it perspective for construction as biosphere models and

Cognitive reasoning a formal approach

CERN Document Server

Anshakov, Oleg M

2010-01-01

Dealing with uncertainty, moving from ignorance to knowledge, is the focus of cognitive processes. Understanding these processes and modelling, designing, and building artificial cognitive systems have long been challenging research problems. This book describes the theory and methodology of a new, scientifically well-founded general approach, and its realization in the form of intelligent systems applicable in disciplines ranging from social sciences, such as cognitive science and sociology, through natural sciences, such as life sciences and chemistry, to applied sciences, such as medicine,

Artificial neural networks application for horizontal and vertical forecasting radionuclides transport

International Nuclear Information System (INIS)

Khil'ko, O.S.; Kovalenko, V.I.; Kundas, S.P.

2010-01-01

Artificial neural networks approach for horizontal and vertical radionuclide transport forecasting was proposed. Runoff factors analysis was considered. Additional artificial neural network structures for physical-chemical properties recognition were used. (authors)

USE OF ARTIFICIAL LIGHT IN MUSHROOM CULTIVATION

Directory of Open Access Journals (Sweden)

N. L. Poyedinok

2013-12-01

Full Text Available Artificial light is used in greenhouses to increase productivity and quality of agricultural and ornamental plants. Despite the awareness of the fact that light also plays important role in the life of nonhotosynthetic organisms, such as fungi, its using in their biotechnology cultivation is currently limited. Science has quite a large amount information about the influence of artificial light of different nature on morphogenesis, metabolic processes and productivity of more than 100 species of fungi, many of which are valuable producers of biologically active compounds. Themechanisms of photoreactions of various fungi, which is an integral part of a purposeful photoregulation their activity in biotechnological processes are described. The analysis of the researches and of the experience of their practical application allows predicting potential of using artificial light in mushroom growing industry, as well as in creating highly productive, environmentally clean technologies of targeted synthesis of the final product.

Artificial heart

Energy Technology Data Exchange (ETDEWEB)

1984-10-18

Super-pure plutonium-238 could use heat produced during fission to power an implanted artificial heart. Three model hearts have worked for some time. Concern that excess heat would make the procedure unsafe for humans has broadened the search for another energy source, such as electrohydraulic drive or an external power battery. A back pack approach may provide an interim solution until materials are developed which can withstand heart activity and be small enough for implantation.

A novel artificial bee colony approach of live virtual machine migration policy using Bayes theorem.

Science.gov (United States)

Xu, Gaochao; Ding, Yan; Zhao, Jia; Hu, Liang; Fu, Xiaodong

2013-01-01

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

Philosophical Approaches towards Sciences of Life in Early Cybernetics

Science.gov (United States)

Montagnini, Leone

2008-07-01

The article focuses on the different conceptual and philosophical approaches towards the sciences of life operating in the backstage of Early Cybernetics. After a short reconstruction of the main steps characterizing the origins of Cybernetics, from 1940 until 1948, the paper examines the complementary conceptual views between Norbert Wiener and John von Neumann, as a "fuzzy thinking" versus a "logical thinking", and the marked difference between the "methodological individualism" shared by both of them versus the "methodological collectivism" of most of the numerous scientists of life and society attending the Macy Conferences on Cybernetics. The main thesis sustained here is that these different approaches, quite invisible to the participants, were different, maybe even opposite, but they could provoke clashes, as well as cooperate in a synergic way.

Artificial Organs 2017: A Year in Review.

Science.gov (United States)

Malchesky, Paul S

2018-03-01

In this Editor's Review, articles published in 2017 are organized by category and summarized. We provide a brief reflection of the research and progress in artificial organs intended to advance and better human life while providing insight for continued application of these technologies and methods. Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. Peer-reviewed Special Issues this year included contributions from the 12th International Conference on Pediatric Mechanical Circulatory Support Systems and Pediatric Cardiopulmonary Perfusion edited by Dr. Akif Undar, Artificial Oxygen Carriers edited by Drs. Akira Kawaguchi and Jan Simoni, the 24th Congress of the International Society for Mechanical Circulatory Support edited by Dr. Toru Masuzawa, Challenges in the Field of Biomedical Devices: A Multidisciplinary Perspective edited by Dr. Vincenzo Piemonte and colleagues and Functional Electrical Stimulation edited by Dr. Winfried Mayr and colleagues. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. © 2018 International Center for

Computational Simulation on Facial Expressions and Experimental Tensile Strength for Silicone Rubber as Artificial Skin

Science.gov (United States)

Amijoyo Mochtar, Andi

2018-02-01

Applications of robotics have become important for human life in recent years. There are many specification of robots that have been improved and encriched with the technology advances. One of them are humanoid robot with facial expression which closer with the human facial expression naturally. The purpose of this research is to make computation on facial expressions and conduct the tensile strength for silicone rubber as artificial skin. Facial expressions were calculated by determining dimension, material properties, number of node elements, boundary condition, force condition, and analysis type. A Facial expression robot is determined by the direction and the magnitude external force on the driven point. The expression face of robot is identical with the human facial expression where the muscle structure in face according to the human face anatomy. For developing facial expression robots, facial action coding system (FACS) in approached due to follow expression human. The tensile strength is conducting due to check the proportional force of artificial skin that can be applied on the future of robot facial expression. Combining of calculated and experimental results can generate reliable and sustainable robot facial expression that using silicone rubber as artificial skin.

An artificial intelligence approach towards disturbance analysis

International Nuclear Information System (INIS)

Fiedler, U.; Lindner, A.; Baldeweg, F.; Klebau, J.

1986-01-01

Scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in well-known situations. But in cases of emergencies, the operator needs more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence (AI) methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application to nuclear power plants. Problems related to man-machine communication will be gone into more detail, because their solution will influence end-user acceptance considerably. (author)

Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Rasoul Sali

2013-01-01

Full Text Available Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12. A hybrid model of genetic algorithm (GA and artificial neural networks (ANNs was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale and the GHQ score as a response variable. In this model, GA is used in order to set some parameter of ANN for achieving more accurate results. Results. For each stressful life event, the number is defined as weight. Among all stressful life events, death of parents, spouse, or siblings is the most important and impactful stressor in the studied population. Sensitivity of 83% and specificity of 81% were obtained for the cut point 100. Conclusion. The SLE-revised (SLE-R questionnaire despite simplicity is a high-performance screening tool for investigating the stress level of life events and its management in both community and primary care settings. The SLE-R questionnaire is user-friendly and easy to be self-administered. This questionnaire allows the individuals to be aware of their own health status.

Individual aircraft life monitoring: An engineering approach for fatigue damage evaluation

Directory of Open Access Journals (Sweden)

Rui JIAO

2018-04-01

Full Text Available Individual aircraft life monitoring is required to ensure safety and economy of aircraft structure, and fatigue damage evaluation based on collected operational data of aircraft is an integral part of it. To improve the accuracy and facilitate the application, this paper proposes an engineering approach to evaluate fatigue damage and predict fatigue life for critical structures in fatigue monitoring. In this approach, traditional nominal stress method is applied to back calculate the S-N curve parameters of the realistic structure details based on full-scale fatigue test data. Then the S-N curve and Miner’s rule are adopted in damage estimation and fatigue life analysis for critical locations under individual load spectra. The relationship between relative small crack length and fatigue life can also be predicted with this approach. Specimens of 7B04-T74 aluminum alloy and TA15M titanium alloy are fatigue tested under two types of load spectra, and there is a good agreement between the experimental results and analysis results. Furthermore, the issue concerning scatter factor in individual aircraft damage estimation is also discussed. Keywords: Fatigue damage, Fatigue monitoring, Fatigue test, Scatter factor, S-N curve

Artificial Promoters for Metabolic Optimization

DEFF Research Database (Denmark)

Jensen, Peter Ruhdal; Hammer, Karin

1998-01-01

In this article, we review some of the expression systems that are available for Metabolic Control Analysis and Metabolic Engineering, and examine their advantages and disadvantages in different contexts. In a recent approach, artificial promoters for modulating gene expression in micro-organisms...

Knowledge in Artificial Intelligence Systems: Searching the Strategies for Application

OpenAIRE

Kornienko, Alla A.; Kornienko, Anatoly V.; Fofanov, Oleg B.; Chubik, Maxim P.

2015-01-01

The studies based on auto-epistemic logic are pointed out as an advanced direction for development of artificial intelligence (AI). Artificial intelligence is taken as a system that imitates the solution of complicated problems by human during the course of life. The structure of symbols and operations, by which intellectual solution is performed, as well as searching the strategic reference points for those solutions, which are caused by certain structures of symbols and operations, – are co...

Artificial neural networks and the effects of loading conditions on fatigue life of carbon and low-alloy steels

International Nuclear Information System (INIS)

Pleune, T.T.

1996-11-01

The ASME Boiler and Pressure Vessel Code contains rules for the construction of nuclear power plant components. Figure 1-90 of Appendix I to Section III of the Code specifies fatigue design curves for structural materials. However, the effects of light water reactor (LWR) coolant environments are not explicitly addressed by the Code design curves. Recent test data indicate significant decreases in the fatigue lives of carbon and low-alloy steels in LWR environments when five conditions are satisfied simultaneously. When applied strain range, temperature, dissolved oxygen in the water, and sulfur content of the steel are above a minimum threshold level, and the loading strain rate is below a threshold value, environmentally assisted fatigue occurs. For this study, a data base of 1036 fatigue tests was used to train an artificial neural network (ANN). Once the optimal ANN was designed, ANN were trained and used to predict fatigue life for specified sets of loading and environmental conditions. By finding patterns and trends in the data, the ANN can find the fatigue lifetime for any set of conditions. Artificial neural networks show great potential for predicting environmentally assisted corrosion. Their main benefits are that the fit of the data is based purely on data and not on preconceptions and that the network can interpolate effects by learning trends and patterns when data are not available

Principle of natural and artificial radioactive series equivalency

International Nuclear Information System (INIS)

Vasilyeva, A.N.; Starkov, O.V.

2001-01-01

In the present paper one approach used under development of radioactive waste management conception is under consideration. This approach is based on the principle of natural and artificial radioactive series radiotoxic equivalency. The radioactivity of natural and artificial radioactive series has been calculated for 10 9 - years period. The toxicity evaluation for natural and artificial series has also been made. The correlation between natural radioactive series and their predecessors - actinides produced in thermal and fast reactors - has been considered. It has been shown that systematized reactor series data had great scientific significance and the principle of differential calculation of radiotoxicity was necessary to realize long-lived radioactive waste and uranium and thorium ore radiotoxicity equivalency conception. The calculations show that the execution of equivalency principle is possible for uranium series (4n+2, 4n+1). It is a problem for thorium. series. This principle is impracticable for neptunium series. (author)

Inteligência artificial aplicada à Zootecnia Artificial intelligence in Animal Science

Directory of Open Access Journals (Sweden)

Ernane José Xavier Costa

2009-07-01

Full Text Available Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11 neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.Biological systems are surprising flexible in processing information in the real world. Some biological organisms have a central unit processing named brain. The human's brain, consisting of 10(11 neurons, realizes intelligent information processing based on exact and commonsense reasoning. Artificial intelligence (AI has been trying to implement biological intelligence in computers in various ways, but is still far from real one. Therefore, there are approaches like Symbolic AI, Artificial Neural Network and Fuzzy system that partially successful in implementing heuristic from biological intelligence. Many recent applications of these approaches show an increased interest in animal science research. The main goal of this article is to explain the principles of heuristic problem-solving approach and to demonstrate how they can be applied to building knowledge-based systems for animal science problem solving.

Artificial neural network approach to spatial estimation of wind velocity data

International Nuclear Information System (INIS)

Oztopal, Ahmet

2006-01-01

In any regional wind energy assessment, equal wind velocity or energy lines provide a common basis for meaningful interpretations that furnish essential information for proper design purposes. In order to achieve regional variation descriptions, there are methods of optimum interpolation with classical weighting functions or variogram methods in Kriging methodology. Generally, the weighting functions are logically and geometrically deduced in a deterministic manner, and hence, they are imaginary first approximations for regional variability assessments, such as wind velocity. Geometrical weighting functions are necessary for regional estimation of the regional variable at a location with no measurement, which is referred to as the pivot station from the measurements of a set of surrounding stations. In this paper, weighting factors of surrounding stations necessary for the prediction of a pivot station are presented by an artificial neural network (ANN) technique. The wind speed prediction results are compared with measured values at a pivot station. Daily wind velocity measurements in the Marmara region from 1993 to 1997 are considered for application of the ANN methodology. The model is more appropriate for winter period daily wind velocities, which are significant for energy generation in the study area. Trigonometric point cumulative semivariogram (TPCSV) approach results are compared with the ANN estimations for the same set of data by considering the correlation coefficient (R). Under and over estimation problems in objective analysis can be avoided by the ANN approach

Comparison of Plant Life Management Approaches for Long Term Operations

International Nuclear Information System (INIS)

Kang, Kisig

2012-01-01

Plant life management can be defined as the integration of ageing and economic planning to maintain a high level of safety and optimize operations. Many Member States have given high priority to long term operation of nuclear power plants beyond the time frame originally anticipated (e. g. 30 or 40 years). Out of a total of 445 (369 GWe) operating nuclear power plants, 349 units (297 GWe) have been in operation for more than 20 years (as of November 2011). The need for engineering support to operation, maintenance, safety review and life management for long term operation as well as education and training in the field is increasingly evident. In addition the Fukushima accident has rendered all stake holders even more attentive to safety concerns and to the provision of beyond safety measures in the preparation and scrutiny of applications for operational design life extensions. In many countries, the safety performance of NPPs is periodically followed and characterized via the periodic safety review (PSR) approach. The regulatory The regulatory review and acceptance of the PSR gives the licensee the permission to operate the plant for up to the end of the next PSR cycle (usually 10 years). In the USA and other countries operating US designed plants, the license renewal application is based on the five pre-requisite requirements and ageing management programme for passive long life system structure and components(SSCs) and active systems is adequately addressed by the maintenance rule (MR) requirements and other established regulatory processes. Other Member States have adopted a combined approach that incorporates elements of both PSR and additional LRA specific requirements primarily focused on time limited ageing analysis. Taking into account this variety of approaches, the international atomic energy agency (IAEA) initiated work for collecting and sharing information among Member States about good practices on plant life management for long term operation in

Constructing a Life That Works: Part 2, An Approach to Practice

Science.gov (United States)

Campbell, Cathy; Ungar, Michael

2004-01-01

The 1st article (C. Campbell & M. Ungar, 2004) of this 2-part exploration of postmodern approaches to family therapy and narrative approaches to career counseling explored the differences between traditional trait and factor counseling models and postmodern approaches using life narratives and social constructionism. In this 2nd article, the…

Artificial limb representation in amputees.

Science.gov (United States)

van den Heiligenberg, Fiona M Z; Orlov, Tanya; Macdonald, Scott N; Duff, Eugene P; Henderson Slater, David; Beckmann, Christian F; Johansen-Berg, Heidi; Culham, Jody C; Makin, Tamar R

2018-05-01

The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral occipitotemporal cortex respond to prosthesis images. This was found even when one-handers were presented with images of active prostheses that share the functionality of the hand but not necessarily its visual features (e.g. a 'hook' prosthesis). Further, we show that daily prosthesis usage determines large-scale inter-network communication across hand-selective areas. This was demonstrated by increased resting state functional connectivity between visual and sensorimotor hand-selective areas, proportional to the intensiveness of everyday prosthesis usage. Further analysis revealed a 3-fold coupling between prosthesis activity, visuomotor connectivity and usage, suggesting a possible role for the motor system in shaping use-dependent representation in visual hand-selective areas, and/or vice versa. Moreover, able-bodied control participants who routinely observe prosthesis usage (albeit less intensively than the prosthesis users) showed significantly weaker associations between degree of prosthesis observation and visual cortex activity or connectivity. Together, our findings suggest that altered daily motor behaviour facilitates prosthesis-related visual processing and shapes communication across hand-selective areas. This neurophysiological substrate for prosthesis embodiment may inspire rehabilitation approaches to improve usage of existing substitutionary devices and aid implementation of future assistive and augmentative technologies.

Towards sustainability: artificial intelligent based approach for soil stabilization using various pozzolans

KAUST Repository

Ouf, M. S.

2012-07-03

Due to the gradual depletion in the conventional resources, searching for a more rational road construction approach aimed at reducing the dependence on imported materials while improving the quality and durability of the roads is necessary. A previous study carried out on a sample of Egyptian soil aimed at reducing the road construction cost, protect the environment and achieving sustainability. RoadCem, ground granulated blast furnace slag (GGBS), lime and ordinary Portland cement (OPC) were employed to stabilise the Egyptian clayey soil. The results revealed that the unconfined compressive strength (UCS) of the test soil increased while the free swelling percent (FSP) decreased with an increase in the total stabiliser and the curing period. This paper discusses attempts to reach optimum stabilization through: (1) Recognizing the relationship between the UCS/FSP of stabilized soil and the stabilization parameters using artificial neural network (ANN); and (2) Performing a backward optimization on the developed (ANN) model using general algorithm (GA) to meet practical design preferences. © 2012 WIT Press.

Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach).

Science.gov (United States)

Ikehara, Kenji

2016-01-26

It is no doubt quite difficult to solve the riddle of the origin of life. So, firstly, I would like to point out the kinds of obstacles there are in solving this riddle and how we should tackle these difficult problems, reviewing the studies that have been conducted so far. After that, I will propose that the consecutive evolutionary steps in a timeline can be rationally deduced by using a common event as a juncture, which is obtained by two counter-directional approaches: one is the bottom-up approach through which many researchers have studied the origin of life, and the other is the top-down approach, through which I established the [GADV]-protein world hypothesis or GADV hypothesis on the origin of life starting from a study on the formation of entirely new genes in extant microorganisms. Last, I will describe the probable evolutionary process from the formation of Earth to the emergence of life, which was deduced by using a common event-the establishment of the first genetic code encoding [GADV]-amino acids-as a juncture for the results obtained from the two approaches.

Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach

Directory of Open Access Journals (Sweden)

Kenji Ikehara

2016-01-01

Full Text Available It is no doubt quite difficult to solve the riddle of the origin of life. So, firstly, I would like to point out the kinds of obstacles there are in solving this riddle and how we should tackle these difficult problems, reviewing the studies that have been conducted so far. After that, I will propose that the consecutive evolutionary steps in a timeline can be rationally deduced by using a common event as a juncture, which is obtained by two counter-directional approaches: one is the bottom-up approach through which many researchers have studied the origin of life, and the other is the top-down approach, through which I established the [GADV]-protein world hypothesis or GADV hypothesis on the origin of life starting from a study on the formation of entirely new genes in extant microorganisms. Last, I will describe the probable evolutionary process from the formation of Earth to the emergence of life, which was deduced by using a common event—the establishment of the first genetic code encoding [GADV]-amino acids—as a juncture for the results obtained from the two approaches.

The work environment disability-adjusted life year for use with life cycle assessment: a methodological approach.

Science.gov (United States)

Scanlon, Kelly A; Gray, George M; Francis, Royce A; Lloyd, Shannon M; LaPuma, Peter

2013-03-06

Life cycle assessment (LCA) is a systems-based method used to determine potential impacts to the environment associated with a product throughout its life cycle. Conclusions from LCA studies can be applied to support decisions regarding product design or public policy, therefore, all relevant inputs (e.g., raw materials, energy) and outputs (e.g., emissions, waste) to the product system should be evaluated to estimate impacts. Currently, work-related impacts are not routinely considered in LCA. The objectives of this paper are: 1) introduce the work environment disability-adjusted life year (WE-DALY), one portion of a characterization factor used to express the magnitude of impacts to human health attributable to work-related exposures to workplace hazards; 2) outline the methods for calculating the WE-DALY; 3) demonstrate the calculation; and 4) highlight strengths and weaknesses of the methodological approach. The concept of the WE-DALY and the methodological approach to its calculation is grounded in the World Health Organization's disability-adjusted life year (DALY). Like the DALY, the WE-DALY equation considers the years of life lost due to premature mortality and the years of life lived with disability outcomes to estimate the total number of years of healthy life lost in a population. The equation requires input in the form of the number of fatal and nonfatal injuries and illnesses that occur in the industries relevant to the product system evaluated in the LCA study, the age of the worker at the time of the fatal or nonfatal injury or illness, the severity of the injury or illness, and the duration of time lived with the outcomes of the injury or illness. The methodological approach for the WE-DALY requires data from various sources, multi-step instructions to determine each variable used in the WE-DALY equation, and assumptions based on professional opinion. Results support the use of the WE-DALY in a characterization factor in LCA. Integrating

A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

Directory of Open Access Journals (Sweden)

Jeremy Straub

2013-05-01

Full Text Available An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response, this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

Computational Approaches to Modeling Artificial Emotion -– An overview of the Proposed Solutions

Directory of Open Access Journals (Sweden)

Zdzislaw eKOWALCZUK

2016-04-01

Full Text Available Cybernetic approach to modeling artificial emotion through the use of different theories of psychology is considered in this paper, presenting a review of twelve proposed solutions: ActAffAct, FLAME, EMA, ParleE, FearNot!, FAtiMA, WASABI, Cathexis, KARO, MAMID, FCM, and xEmotion. The main motivation for this study is founded on the hypothesis that emotions can play a definite utility role of scheduling variables in the construction of intelligent autonomous systems, agents and mobile robots. In this review we also include an innovative and panoptical, comprehensive system, referred to as the Intelligent System of Decision-making (ISD, which has been employed in practical applications of various autonomous units, and which applies as its part the xEmotion, taking into consideration the personal aspects of emotions, affects (short term emotions and mood (principally, long term emotions.

Whispering galleries and the control of artificial atoms.

Science.gov (United States)

Forrester, Derek Michael; Kusmartsev, Feodor V

2016-04-28

Quantum computation using artificial-atoms, such as novel superconducting circuits, can be sensitively controlled by external electromagnetic fields. These fields and the self-fields attributable to the coupled artificial-atoms influence the amount of quantum correlation in the system. However, control elements that can operate without complete destruction of the entanglement of the quantum-bits are difficult to engineer. Here we investigate the possibility of using closely-spaced-linear arrays of metallic-elliptical discs as whispering gallery waveguides to control artificial-atoms. The discs confine and guide radiation through the array with small notches etched into their sides that act as scatterers. We focus on π-ring artificial-atoms, which can generate their own spontaneous fluxes. We find that the micro-discs of the waveguides can be excited by terahertz frequency fields to exhibit whispering-modes and that a quantum-phase-gate composed of π-rings can be operated under their influence. Furthermore, we gauge the level of entanglement through the concurrence measure and show that under certain magnetic conditions a series of entanglement sudden-deaths and revivals occur between the two qubits. This is important for understanding the stability and life-time of qubit operations using, for example, a phase gate in a hybrid of quantum technologies composed of control elements and artificial-atoms.

From Welfare to Well-being: new approaches for a good life

Directory of Open Access Journals (Sweden)

Maria Antonietta Selvaggio

2016-01-01

Full Text Available In this paper we reflect on some analysis conducted by researchers as Laura Balbo, Mary Catherine Bateson and Martha Nussbaum who, although having not had direct relations among them or specific partnerships, have greatly contributed to elaborate concepts and categories regarding our new vision of the well-being. This concept, so dear to the economist Amartya Sen, draws nourishment from thoughts and lived belonging to women’s life experience, particularly as concerning their capacity to organize their daily and family life, taking care of others, shouldering the vulnerabilities and building their biographical paths with creativity and adaptation. So we can understand what is a good life through the realization of our abilities, that is of each person, and not using a utility calculation. This involves a new approach to life quality and human development, that is exactly the capabilities approach described by Sen, rehashed by Nussbaum but, for some aspects, it was already present into the studies which characterize the gender prospective.

CANDU plant life management - An integrated approach

International Nuclear Information System (INIS)

Hopkins, J.R.

1998-01-01

An integrated approach to plant life management has been developed for CANDU reactors. Strategies, methods, and procedures have been developed for assessment of critical systems structures and components and for implementing a reliability centred maintenance program. A Technology Watch program is being implemented to eliminate 'surprises'. Specific work has been identified for 1998. AECL is working on the integrated program with CANDU owners and seeks participation from other CANDU owners

An artificial neural network approach to reconstruct the source term of a nuclear accident

International Nuclear Information System (INIS)

Giles, J.; Palma, C. R.; Weller, P.

1997-01-01

This work makes use of one of the main features of artificial neural networks, which is their ability to 'learn' from sets of known input and output data. Indeed, a trained artificial neural network can be used to make predictions on the input data when the output is known, and this feedback process enables one to reconstruct the source term from field observations. With this aim, an artificial neural networks has been trained, using the projections of a segmented plume atmospheric dispersion model at fixed points, simulating a set of gamma detectors located outside the perimeter of a nuclear facility. The resulting set of artificial neural networks was used to determine the release fraction and rate for each of the noble gases, iodines and particulate fission products that could originate from a nuclear accident. Model projections were made using a large data set consisting of effective release height, release fraction of noble gases, iodines and particulate fission products, atmospheric stability, wind speed and wind direction. The model computed nuclide-specific gamma dose rates. The locations of the detectors were chosen taking into account both building shine and wake effects, and varied in distance between 800 and 1200 m from the reactor.The inputs to the artificial neural networks consisted of the measurements from the detector array, atmospheric stability, wind speed and wind direction; the outputs comprised a set of release fractions and heights. Once trained, the artificial neural networks was used to reconstruct the source term from the detector responses for data sets not used in training. The preliminary results are encouraging and show that the noble gases and particulate fission product release fractions are well determined

Neuro-Based Artificial Intelligence Model for Loan Decisions

OpenAIRE

Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

2010-01-01

Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpr...

A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

Directory of Open Access Journals (Sweden)

Gaochao Xu

2013-01-01

Full Text Available Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration’s ability and local exploitation’s ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas.

Directory of Open Access Journals (Sweden)

Jing Shao

Full Text Available China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining "replace" and "alter" operations, and the third is a "swap" strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China, and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures.

Artificial gravity - The evolution of variable gravity research

Science.gov (United States)

Fuller, Charles A.; Sulzman, Frank M.; Keefe, J. Richard

1987-01-01

The development of a space life science research program based on the use of rotational facilities is described. In-flight and ground centrifuges can be used as artificial gravity environments to study the following: nongravitational biological factors; the effects of 0, 1, and hyper G on man; counter measures for deconditioning astronauts in weightlessness; and the development of suitable artificial gravity for long-term residence in space. The use of inertial fields as a substitute for gravity, and the relations between the radius of the centrifuge and rotation rate and specimen height and rotation radius are examined. An example of a centrifuge study involving squirrel monkeys is presented.

Environmental education - an approach based on the concept of life

Directory of Open Access Journals (Sweden)

J. Fourie

1990-10-01

Full Text Available Environmental education is described as an enterprise aiming at a philosophy of life and therefore as a matter of life. This suggests the concept of life as a natural foundation for an approach to environmental education. Therefore a reflection on the phenomenon of life is offered in which the 'philosophy of life' or vitalist philosophy is reviewed. It is argued that life is a multi-levelled phenomenon and that a monolithic view of life is inadequate. A functional definition of life is proposed in which the microbiological description of life, its link with the abiotic aspect of reality, its other relationships and its spiritual potential are respected. This is used as the ground for an exemplary discussion of life at the levels suggested by the philosophical reflection, viz. life and the individual (which concentrates mainly on the biological aspect, life and the community (concentrating on the social aspect, life and the ecosystem (concentrating primarily on the relationship between abiotic and biotic, and life and the cosmos (which reaches the limit of the authors' task. The need for an ethic is related to these levels and the idea of responsibility is developed with recourse to ancient texts in which comparable ethical implications for the environment are contained. Finally, some practical suggestions are made for implementing the results of the argument in environmental education.

Life cycle costing of food waste: A review of methodological approaches.

Science.gov (United States)

De Menna, Fabio; Dietershagen, Jana; Loubiere, Marion; Vittuari, Matteo

2018-03-01

Food waste (FW) is a global problem that is receiving increasing attention due to its environmental and economic impacts. Appropriate FW prevention, valorization, and management routes could mitigate or avoid these effects. Life cycle thinking and approaches, such as life cycle costing (LCC), may represent suitable tools to assess the sustainability of these routes. This study analyzes different LCC methodological aspects and approaches to evaluate FW management and valorization routes. A systematic literature review was carried out with a focus on different LCC approaches, their application to food, FW, and waste systems, as well as on specific methodological aspects. The review consisted of three phases: a collection phase, an iterative phase with experts' consultation, and a final literature classification. Journal papers and reports were retrieved from selected databases and search engines. The standardization of LCC methodologies is still in its infancy due to a lack of consensus over definitions and approaches. Research on the life cycle cost of FW is limited and generally focused on FW management, rather than prevention or valorization of specific flows. FW prevention, valorization, and management require a consistent integration of LCC and Life Cycle Assessment (LCA) to avoid tradeoffs between environmental and economic impacts. This entails a proper investigation of methodological differences between attributional and consequential modelling in LCC, especially with regard to functional unit, system boundaries, multi-functionality, included cost, and assessed impacts. Further efforts could also aim at finding the most effective and transparent categorization of costs, in particular when dealing with multiple stakeholders sustaining costs of FW. Interpretation of results from LCC of FW should take into account the effect on larger economic systems. Additional key performance indicators and analytical tools could be included in consequential approaches

Determination of the synthetic hydroxyapatite life circle used in dental practice

Directory of Open Access Journals (Sweden)

Teodorović Nevenka

2012-01-01

Full Text Available Dental materials are specific materials that were developed as a general materials for specific aplication in oral environment. To determinate the functional properties of this materials, we are obligated to use nonstandard approach and specific methods. In this study, two methodologies of material testing-artificial agging and quantification of visual informations for life circle assessment of hydroxyapatite (Hap based materials, were used. Hap was chemically synthetized which produced the material with high purity and crystallinity. Artificially produced Hap is used in stomatology for repair of bone tissue, as a filling for periodontal defects, and as a preservative augmentation for alveolar ridges. In the mean time those materials are used for definitive root canal obturation in endodontic therapy procedure as an apical plug or as complete filling material. This research was focused on the analysis of the bonding properties of the Hap based materials to the root canal walls. The methodology of artificial agging was used together with the quantification of visual informations in purpose to quantify the Hap bonding properties and bonding quality. Experiments were done in-vitro, with the artificia saliva as the agressive agent. The experimental tooths were analyzed by the high resolution optical microscope for the morphological characterisation of the bonding layer. The model for the bond life circle assessment was developed. Hap based materials proved that has favorable properties for the dental use. The presented results proved that the combination of two methodologies (artificial agging and quantification of visual informations could be used as the tool for analyzing the material-dentine interaction.

A New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network

Directory of Open Access Journals (Sweden)

Ummuhan Basaran Filik

2016-01-01

Full Text Available A new hybrid wind speed prediction approach, which uses fast block least mean square (FBLMS algorithm and artificial neural network (ANN method, is proposed. FBLMS is an adaptive algorithm which has reduced complexity with a very fast convergence rate. A hybrid approach is proposed which uses two powerful methods: FBLMS and ANN method. In order to show the efficiency and accuracy of the proposed approach, seven-year real hourly collected wind speed data sets belonging to Turkish State Meteorological Service of Bozcaada and Eskisehir regions are used. Two different ANN structures are used to compare with this approach. The first six-year data is handled as a train set; the remaining one-year hourly data is handled as test data. Mean absolute error (MAE and root mean square error (RMSE are used for performance evaluations. It is shown for various cases that the performance of the new hybrid approach gives better results than the different conventional ANN structure.

Autonomy: Life and Being

Science.gov (United States)

Williams, Mary-Anne

This paper uses robot experience to explore key concepts of autonomy, life and being. Unfortunately, there are no widely accepted definitions of autonomy, life or being. Using a new cognitive agent architecture we argue that autonomy is a key ingredient for both life and being, and set about exploring autonomy as a concept and a capability. Some schools of thought regard autonomy as the key characteristic that distinguishes a system from an agent; agents are systems with autonomy, but rarely is a definition of autonomy provided. Living entities are autonomous systems, and autonomy is vital to life. Intelligence presupposes autonomy too; what would it mean for a system to be intelligent but not exhibit any form of genuine autonomy. Our philosophical, scientific and legal understanding of autonomy and its implications is immature and as a result progress towards designing, building, managing, exploiting and regulating autonomous systems is retarded. In response we put forward a framework for exploring autonomy as a concept and capability based on a new cognitive architecture. Using this architecture tools and benchmarks can be developed to analyze and study autonomy in its own right as a means to further our understanding of autonomous systems, life and being. This endeavor would lead to important practical benefits for autonomous systems design and help determine the legal status of autonomous systems. It is only with a new enabling understanding of autonomy that the dream of Artificial Intelligence and Artificial Life can be realized. We argue that designing systems with genuine autonomy capabilities can be achieved by focusing on agent experiences of being rather than attempting to encode human experiences as symbolic knowledge and know-how in the artificial agents we build.

Stirling engine with hydraulic power output for powering artificial hearts

International Nuclear Information System (INIS)

Johnston, R.P.; Noble, J.E.; Emigh, S.G.; White, M.A.; Griffith, W.R.; Perrone, R.E.

1975-01-01

The DWDL heart power source combines the high efficiency of Stirling engines with the reliability, efficiency, and flexibility of hydraulic power transfer and control to ensure long system life and physiological effectiveness. Extended life testing has already been achieved with an engine module; animal in-vivo tests with an assist heart have consistently demonstrated required performance by biological synchronization and effective ventricle relief. The present System 5 can reliably meet near-term thousand-hour animal in-vivo test goals as far as the durability and efficacy of the power source are concerned. Carefully planned development of System 6 has produced major reductions in size and required input power. Research engine tests have provided the basis for achieving performance goals and the approach for further improvement is well established. The near term goal is 33 W heat input with 16 W input projected for normal physical activity. The goal of reduction of engine module volume to 0.9 liter has been achieved. Demonstrated reliability of 292 d for the engine and 35 d for the full system, as well as effectiveness of the artificial heart power source in short-term in-vivo tests indicate that life-limiting problems are now blood pump reliability and the machine-animal interface

An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes

DEFF Research Database (Denmark)

Schmidt, Signe; Boiroux, Dimitri; Ranjan, Ajenthen

2015-01-01

Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications...... and markedly improve patient quality of life. An artificial pancreas consists of portable devices for glucose sensing and insulin delivery which are controlled by an algorithm residing on a computer. The technology is still under development and currently no artificial pancreas is commercially available....... This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research....

[The artificial sphincter: therapy for faecal incontinence].

Science.gov (United States)

Baumgartner, U

2012-08-01

Faecal incontinence (FI) challenges a patient's professional, social and sexual life. Often the patient becomes depressive and socially isolated. If able to break open for therapy the patient should receive as first line a conservative treatment (like dietary measures, pelvic re-education, biofeedback, bulking agents, irrigation). When is the time to implant an artificial anal sphincter? If conservative therapy fails as well as surgical options (like a sphincteroplasty - if indicated a reconstruction of the pelvic floor if insufficient, or a sacral nerve stimulation) an ultimo surgical procedure should be offered to appropriate and compliant patients: an artificial anal sphincter. Worldwide, there are two established devices on the market: the artificial bowel sphincter® (ABS) from A. M. S. (Minnetonka, MN, USA) and the soft anal band® from A. M. I. (Feldkirch, Austria). How to implant the artificial anal sphincter? Both devices consist of a silicon cuff which can be filled with fluid. Under absolute aseptic conditions this cuff is placed in the lithotomy position by perianal incisions around the anal canal below the pelvic floor. A silicon tube connects the anal cuff with a reservoir (containing fluid) which is placed either behind the pubis bone in front of the bladder (ABS) or below the costal arch (anal band). With a pump placed in the scrotum/labia (ABS) or by pressing the balloon (anal band) in both types operated by the patient the fluid is shifted forth and back between the anal cuff and the reservoir closing or opening the anal canal. Both systems are placed completely subcutaneously. Both devices improve significantly the anal continence. Both systems have a high rate of reoperations. However, the causes for the redos are different. The ABS is associated with high infection and anal penetration rates of the cuff leading to an explantation rate to up to 60 % of the implants. This kind of complication seems to be much lower with the anal band. The major

Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

Energy Technology Data Exchange (ETDEWEB)

Yildiz, Sayiter [Engineering Faculty, Cumhuriyet University, Sivas (Turkmenistan)

2017-09-15

Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R{sup 2} value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R{sup 2} values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

International Nuclear Information System (INIS)

Yildiz, Sayiter

2017-01-01

Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R"2 value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R"2 values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

An applied artificial intelligence approach towards assessing building performance simulation tools

Energy Technology Data Exchange (ETDEWEB)

Yezioro, Abraham [Faculty of Architecture and Town Planning, Technion IIT (Israel); Dong, Bing [Center for Building Performance and Diagnostics, School of Architecture, Carnegie Mellon University (United States); Leite, Fernanda [Department of Civil and Environmental Engineering, Carnegie Mellon University (United States)

2008-07-01

With the development of modern computer technology, a large amount of building energy simulation tools is available in the market. When choosing which simulation tool to use in a project, the user must consider the tool's accuracy and reliability, considering the building information they have at hand, which will serve as input for the tool. This paper presents an approach towards assessing building performance simulation results to actual measurements, using artificial neural networks (ANN) for predicting building energy performance. Training and testing of the ANN were carried out with energy consumption data acquired for 1 week in the case building called the Solar House. The predicted results show a good fitness with the mathematical model with a mean absolute error of 0.9%. Moreover, four building simulation tools were selected in this study in order to compare their results with the ANN predicted energy consumption: Energy{sub 1}0, Green Building Studio web tool, eQuest and EnergyPlus. The results showed that the more detailed simulation tools have the best simulation performance in terms of heating and cooling electricity consumption within 3% of mean absolute error. (author)

A novel artificial bee colony based clustering algorithm for categorical data.

Science.gov (United States)

Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

2015-01-01

Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data.

Probabilistic Wind Power Forecasting with Hybrid Artificial Neural Networks

DEFF Research Database (Denmark)

Wan, Can; Song, Yonghua; Xu, Zhao

2016-01-01

probabilities of prediction errors provide an alternative yet effective solution. This article proposes a hybrid artificial neural network approach to generate prediction intervals of wind power. An extreme learning machine is applied to conduct point prediction of wind power and estimate model uncertainties...... via a bootstrap technique. Subsequently, the maximum likelihood estimation method is employed to construct a distinct neural network to estimate the noise variance of forecasting results. The proposed approach has been tested on multi-step forecasting of high-resolution (10-min) wind power using...... actual wind power data from Denmark. The numerical results demonstrate that the proposed hybrid artificial neural network approach is effective and efficient for probabilistic forecasting of wind power and has high potential in practical applications....

Mars extant-life campaign using an approach based on Earth-analog habitats

Science.gov (United States)

Palkovic, Lawrence A.; Wilson, Thomas J.

2005-01-01

The Mars Robotic Outpost group at JPL has identified sixteen potential momentous discoveries that if found on Mars would alter planning for the future Mars exploration program. This paper details one possible approach to the discovery of and response to the 'momentous discovery'' of extant life on Mars. The approach detailed in this paper, the Mars Extant-Life (MEL) campaign, is a comprehensive and flexible program to find living organisms on Mars by studying Earth-analog habitats of extremophile communities.

Distributed computing and artificial intelligence : 10th International Conference

CERN Document Server

Neves, José; Rodriguez, Juan; Santana, Juan; Gonzalez, Sara

2013-01-01

The International Symposium on Distributed Computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. This conference is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry se...

A Review of Safety and Design Requirements of the Artificial Pancreas.

Science.gov (United States)

Blauw, Helga; Keith-Hynes, Patrick; Koops, Robin; DeVries, J Hans

2016-11-01

As clinical studies with artificial pancreas systems for automated blood glucose control in patients with type 1 diabetes move to unsupervised real-life settings, product development will be a focus of companies over the coming years. Directions or requirements regarding safety in the design of an artificial pancreas are, however, lacking. This review aims to provide an overview and discussion of safety and design requirements of the artificial pancreas. We performed a structured literature search based on three search components-type 1 diabetes, artificial pancreas, and safety or design-and extended the discussion with our own experiences in developing artificial pancreas systems. The main hazards of the artificial pancreas are over- and under-dosing of insulin and, in case of a bi-hormonal system, of glucagon or other hormones. For each component of an artificial pancreas and for the complete system we identified safety issues related to these hazards and proposed control measures. Prerequisites that enable the control algorithms to provide safe closed-loop control are accurate and reliable input of glucose values, assured hormone delivery and an efficient user interface. In addition, the system configuration has important implications for safety, as close cooperation and data exchange between the different components is essential.

An active artificial cornea with the function of inducing new corneal tissue generation in vivo-a new approach to corneal tissue engineering

International Nuclear Information System (INIS)

Huang Yaoxiong; Li Qinhua

2007-01-01

An active artificial cornea which can perform the function of inducing new cornea generation in vivo but does not need culture cells in vitro and which has similar optical and mechanical properties to those of the human cornea was constructed. An animal keratoplasty experiment using the artificial cornea as the implant showed that the animals' corneas could keep smooth surface and clear stroma postoperatively, and that the repopulation of the host's keratocytes, the degradation of the implant and new corneal tissue generation were completed at 5-6 months after surgery. Such an artificial cornea has several advantages over other corneal equivalents constructed in the typical way of tissue engineering: in having similar mechanical and optical properties to those of the human cornea and with no exogenetic cells, it can be used universally in different implantation surgeries without immunoreaction; it is easy to prepare and process into different shapes and sizes on a large scale, and suitable for long-distance transportation and long-term storage. All these characteristics make it a new approach to cornea tissue engineering having potential in many clinical applications

APPLYING TEACHING-LEARNING TO ARTIFICIAL BEE COLONY FOR PARAMETER OPTIMIZATION OF SOFTWARE EFFORT ESTIMATION MODEL

Directory of Open Access Journals (Sweden)

THANH TUNG KHUAT

2017-05-01

Full Text Available Artificial Bee Colony inspired by the foraging behaviour of honey bees is a novel meta-heuristic optimization algorithm in the community of swarm intelligence algorithms. Nevertheless, it is still insufficient in the speed of convergence and the quality of solutions. This paper proposes an approach in order to tackle these downsides by combining the positive aspects of TeachingLearning based optimization and Artificial Bee Colony. The performance of the proposed method is assessed on the software effort estimation problem, which is the complex and important issue in the project management. Software developers often carry out the software estimation in the early stages of the software development life cycle to derive the required cost and schedule for a project. There are a large number of methods for effort estimation in which COCOMO II is one of the most widely used models. However, this model has some restricts because its parameters have not been optimized yet. In this work, therefore, we will present the approach to overcome this limitation of COCOMO II model. The experiments have been conducted on NASA software project dataset and the obtained results indicated that the improvement of parameters provided better estimation capabilities compared to the original COCOMO II model.

Maximizing performance of fuel cell using artificial neural network approach for smart grid applications

International Nuclear Information System (INIS)

Bicer, Y.; Dincer, I.; Aydin, M.

2016-01-01

This paper presents an artificial neural network (ANN) approach of a smart grid integrated proton exchange membrane (PEM) fuel cell and proposes a neural network model of a 6 kW PEM fuel cell. The data required to train the neural network model are generated by a model of 6 kW PEM fuel cell. After the model is trained and validated, it is used to analyze the dynamic behavior of the PEM fuel cell. The study results demonstrate that the model based on neural network approach is appropriate for predicting the outlet parameters. Various types of training methods, sample numbers and sample distribution methods are utilized to compare the results. The fuel cell stack efficiency considerably varies between 20% and 60%, according to input variables and models. The rapid changes in the input variables can be recovered within a short time period, such as 10 s. The obtained response graphs point out the load tracking features of ANN model and the projected changes in the input variables are controlled quickly in the study. - Highlights: • An ANN approach of a proton exchange membrane (PEM) fuel cell is proposed. • Dynamic behavior of the PEM fuel cell is analyzed. • The effects of various variables on model accuracy are investigated. • Response curves indicate the load following characteristics of the model.

Environmental and economic analysis of end of life management options for an HDPE product using a life cycle thinking approach.

Science.gov (United States)

Simões, Carla L; Pinto, Lígia M Costa; Bernardo, C A

2014-05-01

Manufacturers have been increasingly considering the implication of materials used in commercial products and the management of such products at the end of their useful lives (as waste or as post-consumer secondary materials). The present work describes the application of the life cycle thinking approach to a plastic product, specifically an anti-glare lamellae (used for road safety applications) made with high-density polyethylene (HDPE). This study shows that optimal environmental and economic outcomes associated with this product can be realized by recovering the material at the end of its useful life (end of life, EoL) and by using the recycled HDPE as a raw material in the production of new similar products. The study confirmed the applicability of the life cycle thinking approach by industry in sustainable products development, supporting the development of robust environmental and economic guidelines.

Can interbreeding of wild and artificially propagated animals be prevented by using broodstock selected for a divergent life history?

Science.gov (United States)

Seamons, Todd R; Hauser, Lorenz; Naish, Kerry A; Quinn, Thomas P

2012-01-01

Two strategies have been proposed to avoid negative genetic effects of artificially propagated individuals on wild populations: (i) integration of wild and captive populations to minimize domestication selection and (ii) segregation of released individuals from the wild population to minimize interbreeding. We tested the efficacy of the strategy of segregation by divergent life history in a steelhead trout, Oncorhynchus mykiss, system, where hatchery fish were selected to spawn months earlier than the indigenous wild population. The proportion of wild ancestry smolts and adults declined by 10–20% over the three generations since the hatchery program began. Up to 80% of the naturally produced steelhead in any given year were hatchery/wild hybrids. Regression model selection analysis showed that the proportion of hatchery ancestry smolts was lower in years when stream discharge was high, suggesting a negative effect of flow on reproductive success of early-spawning hatchery fish. Furthermore, proportions of hybrid smolts and adults were higher in years when the number of naturally spawning hatchery-produced adults was higher. Divergent life history failed to prevent interbreeding when physical isolation was ineffective, an inadequacy that is likely to prevail in many other situations. PMID:23144657

Recent Progress in Micro/Nanoreactors toward the Creation of Artificial Organelles

DEFF Research Database (Denmark)

Gallardo, Maria Godoy; York-Durán, María José; Hosta-Rigau, Leticia

2018-01-01

Artificial organelles created from a bottom up approach are a new type of engineered materials, which are not designed to be living but, instead, to mimic some specific functions inside cells. By doing so, artificial organelles are expected to become a powerful tool in biomedicine. They can act a...

Artificial intelligence as a means to moral enhancement

OpenAIRE

Klincewicz, Michał

2016-01-01

This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artificial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative t...

Artificial Intelligence and the 'Good Society': the US, EU, and UK approach.

Science.gov (United States)

Cath, Corinne; Wachter, Sandra; Mittelstadt, Brent; Taddeo, Mariarosaria; Floridi, Luciano

2018-04-01

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence (AI). In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a 'good AI society'. To do so, we examine how each report addresses the following three topics: (a) the development of a 'good AI society'; (b) the role and responsibility of the government, the private sector, and the research community (including academia) in pursuing such a development; and (c) where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a 'good AI society'. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach.

CONCEPTUAL APPROACHES TO THE EDUCATION OF LIFE-MEANINGFUL VALUES OF TEENAGERS AND EARLY ADOLESCENCE IN UKRAINE

Directory of Open Access Journals (Sweden)

Katherinа Zhurba

2015-04-01

Full Text Available The article presents the conceptual approaches to the upbringing in the education of life-meaningful values of teenagers and early adolescence in Ukraine. The definition of life-meaningful values has been given up. The major problems and contradictions in the upbringing of the Ukrainian children were paid attention to. The dependence of the result of upbringing, from the desire and the participation of all actors: children, parents, teachers is pointed out. Conceptual approaches to education of life values meaning are analyzed on the methodological, theoretical and practical levels. The aspects of the previous researches have been underlined. In this context, a systematic approach determines the integrity of the educational process in primary and high school. Synergetic approach combines the organization and self-organization of the growing personality. Humanistic approach recognizes each child's highest value at school, family, and society. Personal-centered approach provides individual attention to him, to free choice of that or other life-meaningful values. Activity approach provides practice and deed activity of children and shows how the value of the meaning of life affects the behavior of the individual. The theoretical level of substantiation of the concept of education of children of teenagers and early youth gives ability to define key points and concepts. Practical level implies the corresponding experimental activity, the determination of propriate pedagogical conditions, the selection of content, forms and methods of education of teenagers and early adolescence. Conceptual approaches offer the opportunity to develop a modern system of education of the values of the meaning of life of teenagers and early adolescence in Ukraine. Implementation of conceptual approaches aimed at qualitative changes in the education of life-meaningful values among of teenagers and early adolescence.

Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks

DEFF Research Database (Denmark)

Chon, K H; Hoyer, D; Armoundas, A A

1999-01-01

In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic...... part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction...... error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate...

Artificial intelligence in hematology.

Science.gov (United States)

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Cotton genotypes selection through artificial neural networks.

Science.gov (United States)

Júnior, E G Silva; Cardoso, D B O; Reis, M C; Nascimento, A F O; Bortolin, D I; Martins, M R; Sousa, L B

2017-09-27

Breeding programs currently use statistical analysis to assist in the identification of superior genotypes at various stages of a cultivar's development. Differently from these analyses, the computational intelligence approach has been little explored in genetic improvement of cotton. Thus, this study was carried out with the objective of presenting the use of artificial neural networks as auxiliary tools in the improvement of the cotton to improve fiber quality. To demonstrate the applicability of this approach, this research was carried out using the evaluation data of 40 genotypes. In order to classify the genotypes for fiber quality, the artificial neural networks were trained with replicate data of 20 genotypes of cotton evaluated in the harvests of 2013/14 and 2014/15, regarding fiber length, uniformity of length, fiber strength, micronaire index, elongation, short fiber index, maturity index, reflectance degree, and fiber quality index. This quality index was estimated by means of a weighted average on the determined score (1 to 5) of each characteristic of the HVI evaluated, according to its industry standards. The artificial neural networks presented a high capacity of correct classification of the 20 selected genotypes based on the fiber quality index, so that when using fiber length associated with the short fiber index, fiber maturation, and micronaire index, the artificial neural networks presented better results than using only fiber length and previous associations. It was also observed that to submit data of means of new genotypes to the neural networks trained with data of repetition, provides better results of classification of the genotypes. When observing the results obtained in the present study, it was verified that the artificial neural networks present great potential to be used in the different stages of a genetic improvement program of the cotton, aiming at the improvement of the fiber quality of the future cultivars.

AP@home: The Artificial Pancreas Is Now at Home

NARCIS (Netherlands)

Heinemann, Lutz; Benesch, Carsten; DeVries, J. Hans

2016-01-01

In the past years the development of an artificial pancreas (AP) has made great progress and many activities are ongoing in this area of research. The major step forward made in the last years was moving the evaluation of AP systems from highly controlled experimental conditions to daily life

Reliability studies for the nuclear-powered artificial heart program

International Nuclear Information System (INIS)

Horita, M.; Zeigler, R.K.

1976-04-01

By assuming that the failures of an artificial heart system with a mean life of 10 y can be modeled by a particular probability distribution, both the probability of a failure in the system within t years and the reliability required of each subsystem and component were investigated

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

Energy Technology Data Exchange (ETDEWEB)

El Hariri, Mohamad [Florida Intl Univ., Miami, FL (United States); Faddel, Samy [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States)

2017-11-01

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted to verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.

Fatigue life prediction for pressure cast transmission housings using the strain life approach

Energy Technology Data Exchange (ETDEWEB)

Varenkamp, M. [ZF Friedrichshafen AG, Abteilung TB-1, 88038 Friedrichshafen (Germany); Schoen, M.

2011-04-15

Pressure cast transmission housings are structural components of complex shape, which have to fulfil, amongst others, the requirements of structural durability, saving as much weight as possible. The numerical proof of structural durability is carried out using the local strain approach. One challenge is to consider the inhomogeneous material properties, as a consequence of the casting process. It shows, that local porosity is the determining factor for the components fatigue life. Coming from the experiences made using the basic version of the local strain approach the methods used to successfully adjust the procedure for calculating pressure cast components under constant and variable amplitudes are described. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

Science.gov (United States)

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-04-12

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

An Artificial Intelligence Approach for Gears Diagnostics in AUVs

Directory of Open Access Journals (Sweden)

Graciliano Nicolás Marichal

2016-04-01

Full Text Available In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles, where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

OpenAIRE

Jerzy Balicki

2015-01-01

The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to p...

Internet of Things and Artificial Vision, Performance and Applications: Literature Review

Directory of Open Access Journals (Sweden)

Vanessa Alvear-Puertas

2017-02-01

Full Text Available Internet of Things (or also known as IoT is one of the technologies most named today because of the ability it envisages to connect all kinds of devices to the Internet. If to the potentialities of IoT we add another technology of high impact as It is the Artificial Vision we have a wide field of innovative applications, where the processing of images and video in real time allow the visualization of large amounts of data on the Internet. The main applications developed with IoT and Artificial Vision can be implemented in education, medicine, intelligent buildings, surveillance systems of people and vehicles, among others. This type of applications improves the quality of life of users, however, for their development an infrastructure is required that allows the convergence of different protocols and devices, but in a special way that can handle the different phases of the acquisition of images. In this work, a review of the beginnings, concepts, technologies and applications related to the Artificial Vision with the Internet of Things has been carried out to be able to understand in a precise way the impact of its application in daily life.

Fatigue life evaluation of 42CrMo4 nitrided steel by local approach: Equivalent strain-life-time

International Nuclear Information System (INIS)

Terres, Mohamed Ali; Sidhom, Habib

2012-01-01

Highlights: → Ion nitriding treatment of 42CrMo4 steel improves their fatigue strength by 32% as compared with the untreated state. → This improvement is the result of the beneficial effects of the superficial work- hardening and of the stabilized compressive residual stress. → The notch region is found to be the fatigue crack nucleation site resulting from a stress concentration (Kt = 1.6). → The local equivalent strain-fatigue life method was found to be an interesting predictive fatigue life method for nitrided parts. -- Abstract: In this paper, the fatigue resistance of 42CrMo4 steel in his untreated and nitrided state was evaluated, using both experimental and numerical approaches. The experimental assessment was conducted using three points fatigue flexion tests on notched specimens at R = 0.1. Microstructure analysis, micro-Vickers hardness test, and scanning electron microscope observation were carried out for evaluating experiments. In results, the fatigue cracks of nitrided specimens were initiated at the surface. The fatigue life of nitrided specimens was prolonged compared to that of the untreated. The numerical method used in this study to predict the nucleation fatigue life was developed on the basis of a local approach, which took into account the applied stresses and stabilized residual stresses during the cyclic loading and the low cyclic fatigue characteristics. The propagation fatigue life was calculated using fracture mechanics concepts. It was found that the numerical results were well correlated with the experimental ones.

Computer automation and artificial intelligence

International Nuclear Information System (INIS)

Hasnain, S.B.

1992-01-01

Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

A genetic-neural artificial intelligence approach to resins optimization; Uma metodologia baseada em inteligencia artificial para otimizacao de resinas

Energy Technology Data Exchange (ETDEWEB)

Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: lapa@ien.gov.br; mbarros@ien.gov.br

2005-07-01

This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

End of Life Care

Science.gov (United States)

... Related Topics Choosing Wisely Join our e-newsletter! Aging & Health A to Z End of Life Care ... be used. Ice chips, popsicles, moist swabs, or artificial saliva can help prevent the mouth from becoming ...

Adenomyosis: a life-cycle approach.

Science.gov (United States)

Benagiano, Giuseppe; Brosens, Ivo; Habiba, Marwan

2015-03-01

The life-cycle approach to endometriosis highlighted unexpected features of the condition; the same approach was therefore applied to gain insight into the clinical features of adenomyosis and to draw a comparison with endometriosis. This is possible today thanks to new imaging techniques enabling non-invasive diagnosis of adenomyosis. The specificity and sensitivity of magnetic resonance imaging and transvaginal ultrasound remain uncertain. Unlike endometriosis, little information is available on the presence of classic adenomyosis in adolescents, except for rare cystic forms that may not represent the true disease. Adenomyosis is most likely to affect adult women, although most reported incidences are still based on post-hysterectomy studies, and are affected by diligence in histopathologic diagnosis and the adopted cut-off point. The traditionally accepted associations of adult adenomyosis, such as multiparity, a link to infertility and its effect on pregnancy are uncertain. Active adenomyosis has been found in pre- and peri-menopausal women and in postmenopausal women receiving tamoxifen. In conclusion, major diagnostic limitations and the systematic bias of hysterectomy make it difficult to draw firm conclusions from existing evidence. In addition, no information is available on the natural history of adenomyosis and no study has systematically evaluated its existence in adolescents. Copyright © 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Metacognition: towards a new approach to quality of life.

Science.gov (United States)

Blanc, Julien; Boyer, Laurent; Le Coz, Pierre; Auquier, Pascal

2014-03-01

Recent studies have demonstrated that various diseases states (e.g., schizophrenia, Alzheimer's disease) and events (e.g., a stroke) alter a person's perception of their physical and mental status. Most often this involves alterations in a person's metacognitive capabilities, and this can question the conceptual model of quality of life (QoL) based on a "perspectivist" approach. Using the example of schizophrenia, we applied a philosophical model, developed by Griffin, to deal with this potential threat to the validity of QoL assessment. Patients with schizophrenia are at risk for being impaired in their ability to assess their QoL. We hypothesise that metacognition (i.e., the ability to attribute mental states in terms of beliefs and goals to one's self and others) is a formal condition to assess QoL. This particular skill is important because self-reflection is necessary for making a qualitative judgment. A link between this psychological concept and the philosophical concept of reflexivity may be established. We propose a conceptual approach to QoL that takes into account the patient's reflexivity. This approach is derived from Griffin's theory based on the list of "prudential values" and the satisfaction of the informed desires of the individual. The ability of patients to evaluate and value their life should be considered to enrich the concept of QoL. The approach derived from Griffin's theory might constitute a new avenue for QoL research.

Artificial Organs 2016: A Year in Review.

Science.gov (United States)

Hadsell, Angela T; Malchesky, Paul S

2017-03-01

In this Editor's Review, articles published in 2016 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Mechanical Circulatory Support, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We were pleased to publish our second Virtual Issue in April 2016 on "Tissue Engineering in Bone" by Professor Tsuyoshi Takato. Our first was published in 2011 titled "Intra-Aortic Balloon Pumping" by Dr. Ashraf Khir. Other peer-reviewed Special Issues this year included contributions from the 11th International Conference on Pediatric Mechanical Circulatory Support Systems and Pediatric Cardiopulmonary Perfusion edited by Dr. Akif Ündar and selections from the 23rd Congress of the International Society for Rotary Blood Pumps edited by Dr. Bojan Biocina. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and

Artificial skin and patient simulator comprising the artificial skin

NARCIS (Netherlands)

2011-01-01

The invention relates to an artificial skin (10, 12, 14), and relates to a patient simulator (100) comprising the artificial skin. The artificial skin is a layered structure comprising a translucent cover layer (20) configured for imitating human or animal skin, and comprising a light emitting layer

Groundhog Day for Medical Artificial Intelligence.

Science.gov (United States)

London, Alex John

2018-05-01

Following a boom in investment and overinflated expectations in the 1980s, artificial intelligence entered a period of retrenchment known as the "AI winter." With advances in the field of machine learning and the availability of large datasets for training various types of artificial neural networks, AI is in another cycle of halcyon days. Although medicine is particularly recalcitrant to change, applications of AI in health care have professionals in fields like radiology worried about the future of their careers and have the public tittering about the prospect of soulless machines making life-and-death decisions. Medicine thus appears to be at an inflection point-a kind of Groundhog Day on which either AI will bring a springtime of improved diagnostic and predictive practices or the shadow of public and professional fear will lead to six more metaphorical weeks of winter in medical AI. © 2018 The Hastings Center.

Living technology: exploiting life's principles in technology.

Science.gov (United States)

Bedau, Mark A; McCaskill, John S; Packard, Norman H; Rasmussen, Steen

2010-01-01

The concept of living technology-that is, technology that is based on the powerful core features of life-is explained and illustrated with examples from artificial life software, reconfigurable and evolvable hardware, autonomously self-reproducing robots, chemical protocells, and hybrid electronic-chemical systems. We define primary (secondary) living technology according as key material components and core systems are not (are) derived from living organisms. Primary living technology is currently emerging, distinctive, and potentially powerful, motivating this review. We trace living technology's connections with artificial life (soft, hard, and wet), synthetic biology (top-down and bottom-up), and the convergence of nano-, bio-, information, and cognitive (NBIC) technologies. We end with a brief look at the social and ethical questions generated by the prospect of living technology.

Investigating the effect of clamping force on the fatigue life of bolted plates using volumetric approach

International Nuclear Information System (INIS)

Esmaeili, F.; Chakherlou, T. N.; Zehsaz, M.; Hasanifard, S.

2013-01-01

In this paper, the effects of bolt clamping force on the fatigue life for bolted plates made from Al7075-T6 have been studied on the values of notch strength reduction factor obtained by volumetric approach. To attain stress distribution around the notch (hole) which is required for volumetric approach, nonlinear finite element simulations were carried out. To estimate the fatigue life, the available smooth S-N curve of Al7075-T6 and the notch strength reduction factor obtained from volumetric method were used. The estimated fatigue life was compared with the available experimental test results. The investigation shows that there is a good agreement between the life predicted by the volumetric approach and the experimental results for various specimens with different amount of clamping forces. Volumetric approach and experimental results showed that the fatigue life of bolted plates improves because of the compressive stresses created around the plate hole due to clamping force.

Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

International Nuclear Information System (INIS)

Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

2016-01-01

Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

Artificial Intelligence.

Science.gov (United States)

Information Technology Quarterly, 1985

1985-01-01

This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

Artificial organs: recent progress in artificial hearing and vision.

Science.gov (United States)

Ifukube, Tohru

2009-01-01

Artificial sensory organs are a prosthetic means of sending visual or auditory information to the brain by electrical stimulation of the optic or auditory nerves to assist visually impaired or hearing-impaired people. However, clinical application of artificial sensory organs, except for cochlear implants, is still a trial-and-error process. This is because how and where the information transmitted to the brain is processed is still unknown, and also because changes in brain function (plasticity) remain unknown, even though brain plasticity plays an important role in meaningful interpretation of new sensory stimuli. This article discusses some basic unresolved issues and potential solutions in the development of artificial sensory organs such as cochlear implants, brainstem implants, artificial vision, and artificial retinas.

Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Narayanan Manikandan

2016-01-01

Full Text Available Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.

Comparison of beta-binomial regression model approaches to analyze health-related quality of life data.

Science.gov (United States)

Najera-Zuloaga, Josu; Lee, Dae-Jin; Arostegui, Inmaculada

2017-01-01

Health-related quality of life has become an increasingly important indicator of health status in clinical trials and epidemiological research. Moreover, the study of the relationship of health-related quality of life with patients and disease characteristics has become one of the primary aims of many health-related quality of life studies. Health-related quality of life scores are usually assumed to be distributed as binomial random variables and often highly skewed. The use of the beta-binomial distribution in the regression context has been proposed to model such data; however, the beta-binomial regression has been performed by means of two different approaches in the literature: (i) beta-binomial distribution with a logistic link; and (ii) hierarchical generalized linear models. None of the existing literature in the analysis of health-related quality of life survey data has performed a comparison of both approaches in terms of adequacy and regression parameter interpretation context. This paper is motivated by the analysis of a real data application of health-related quality of life outcomes in patients with Chronic Obstructive Pulmonary Disease, where the use of both approaches yields to contradictory results in terms of covariate effects significance and consequently the interpretation of the most relevant factors in health-related quality of life. We present an explanation of the results in both methodologies through a simulation study and address the need to apply the proper approach in the analysis of health-related quality of life survey data for practitioners, providing an R package.

9th International conference on distributed computing and artificial intelligence

CERN Document Server

Santana, Juan; González, Sara; Molina, Jose; Bernardos, Ana; Rodríguez, Juan; DCAI 2012; International Symposium on Distributed Computing and Artificial Intelligence 2012

2012-01-01

The International Symposium on Distributed Computing and Artificial Intelligence 2012 (DCAI 2012) is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. This conference is a forum in which  applications of innovative techniques for solving complex problems will be presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and indus...

ARTIFICIAL INTELLIGENCE: APPLICATIONS AND FUTURE

OpenAIRE

Ellur Anand; S. G. Varun Kumar

2017-01-01

Artificial Intelligence (AI) or Augmented Intelligence happens to be the most talked about technology that would have a major impact on the way the current day world functions. The next step in evolution of digital world is AI. The safety of the world with more and more use of AI also becomes necessity. Safety rules and regulations of the digital world need to be drafted and redrafted as AI evolves and becomes a new normal in every one’s life just as mobile phone has become in the current sce...

Providing Language Instructor with Artificial Intelligence Assistant

OpenAIRE

K. Pietroszek

2007-01-01

Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot), a voice (text-to-speech engine interface) andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual wor...

Artificial Immune Ecosystems: the role of expert-based learning in artificial cognition

Directory of Open Access Journals (Sweden)

Pierre Parrend

2018-03-01

Full Text Available The rapid evolution of IT ecosystems significantly challenges the security models our infrastructures rely on. Beyond the old dichotomy between open and closed systems, it is now necessary to handle securely the interaction between heterogeneous devices building dynamic ecosystems. To this regard, bio-inspired approaches provide a rich set of conceptual tools, but they have failed to lay the basis for robust and efficient solutions. Our research effort intends to revisit the contribution of artificial immune system research to bring immune properties: security, resilience, distribution, memory, into IT infrastructures. Artificial immune ecosystems support a comprehensive model for anomaly detection and characterization, but their cognitive capacity are limited by the state of the art in machine learning and the rapid evolution of cybersecurity threats so far. We therefore propose to enrich the cognitive process with expert-based learning for reinforcement, classification and investigation. Application to system supervision using system logs and supervision time series confirms the relevance and performance of this model.

ENVIRONMENTAL ASSESSMENT OF ROAD TRANSPORT IN A PASSENGER CAR USING THE LIFE CYCLE APPROACH

Directory of Open Access Journals (Sweden)

Piotr FOLĘGA

2017-06-01

Full Text Available Environmental issues are an increasingly important aspect of management in the transport sector; new methods have been developed for assessment of the environment in the transport sector using the life cycle approach. The paper presents the application of Well to Wheel (WTW and Life Cycle Assessment (LCA in the transport sector. The WTW method focuses on energy analysis and greenhouse gas emissions during the life cycle of fuels. WTW is used to support decision-making on the environmental aspects of transport, particularly with regard to fuel life cycle management, but this method omits important stages in the life cycle, particularly the ones regarding important circular economy guidelines such as reduction of natural resource consumption, impact on human health, etc. The LCA method provides a much broader approach to environmental assessment than WTW. LCA takes into consideration environmental impact in the whole life cycle of the vehicle, from the stage of production, through the period of exploitation, and finally its disposal.

A Pathway to Artificial Metalloenzymes

KAUST Repository

Fischer, Johannes

2015-12-01

The advancement of catalytic systems and the application thereof has proven to be the key to overcome traditional limitations of industrial-scale synthetic processes. Converging organometallic and biocatalytic principles lead to the development of Artificial Metalloenzymes (ArMs) that comprise a synthetic metal catalyst embedded in a protein scaffold, thereby combining the reactivity of the former with the versatility of the latter. This synergistic approach introduces rationally designed building blocks for the catalytic site and the host protein to assemble enzyme-like structures that follow regio-, chemo-, enantio- and substrate-selective principles. Yet, the identification of suitable protein scaffolds has thus far been challenging. Herein we report a rationally optimized fluorescent protein host, mTFP*, that was engineered to have no intrinsic metal binding capability and, owing to its robust nature, can act as scaffold for the design of novel ArMs. We demonstrate the potential of site-specific modifications within the protein host, use protein X-Ray analysis to validate the respective scaffolds and show how artificial mutant binding sites can be introduced. Transition metal Förster Resonance Energy transfer (tmFRET) methodologies help to evaluate micromolar dissociation constants and reveal structural rearrangements upon coordination of the metal centers. In conjunction with molecular insights from X-Ray crystallographic structure determination, dynamics of the binding pocket can be inferred. The versatile subset of different binding motifs paired with transition metal catalysts create artificial metalloenzymes that provide reactivities which otherwise do not exist in nature. As a proof of concept, Diels-Alder cycloadditions highlight the potential of the present mTFP* based catalysts by stereoselectively converting azachalcone and cyclopentadiene substrates. Screens indicate an enantiomeric excess of up to 60% and provide insights into the electronic and

Engineering considerations in the use of artificial filter beds

International Nuclear Information System (INIS)

Richards, R.T.

1978-01-01

Artificial filter bed intakes utilize a prepared granular filter material to prevent entrance of debris and aquatic life into a water withdrawal facility. The relatively large quantities of water and the service reliability required for power plant cooling water systems present major engineering problems for the artificial filter concept, many of which have not been resolved. These problems include development of a suitable and stable filter medium; design of a reliable backwash system which is both effective and environmentally acceptable; meeting of all site-imposed restrictions relating to natural river turbidity, flooding characteristics, channel stability, and ice loads; and provision of the complex civil and mechanical engineering design inherent in such a system. Extensive model testing may be required for further engineering development of this system. The preliminary engineering for an artificial filter system is discussed in connection with a proposed 1.6-m 3 /s-capacity (25,000-gpm capacity) filter in the Columbia River

Impacts of Artificial Reefs and Diving Tourism

Directory of Open Access Journals (Sweden)

Sandra Jakšić

2013-10-01

Full Text Available Coral reefs are currently endangered throughout the world. One of the main activities responsible for this is scuba-diving. Scuba-diving on coral reefs was not problematic in the begging, but due to popularization of the new sport, more and more tourists desired to participate in the activity. Mass tourism, direct contact of the tourists with the coral reefs and unprofessional behavior underwater has a negative effect on the coral reefs. The conflict between nature preservation and economy benefits related to scuba-diving tourism resulted in the creation of artificial reefs, used both to promote marine life and as tourists attractions, thereby taking the pressure off the natural coral reefs. Ships, vehicles and other large structures can be found on the coastal sea floor in North America, Australia, Japan and Europe. The concept of artificial reefs as a scuba-diving attraction was developed in Florida. The main goal was to promote aquaculture, with the popularization of scuba-diving attractions being a secondary effect. The aim of this paper is to determine the effects of artificial reefs on scuba-diving tourism, while taking into account the questionnaire carried out among 18 divers

Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

International Nuclear Information System (INIS)

Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

2003-01-01

Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

Artificial organs 2014: a year in review.

Science.gov (United States)

Malchesky, Paul S

2015-03-01

In this Editor's Review, articles published in 2014 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of the International Federation for Artificial Organs, the International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Artificial immune system applications in computer security

CERN Document Server

Tan, Ying

2016-01-01

This book provides state-of-the-art information on the use, design, and development of the Artificial Immune System (AIS) and AIS-based solutions to computer security issues. Artificial Immune System: Applications in Computer Security focuses on the technologies and applications of AIS in malware detection proposed in recent years by the Computational Intelligence Laboratory of Peking University (CIL@PKU). It offers a theoretical perspective as well as practical solutions for readers interested in AIS, machine learning, pattern recognition and computer security. The book begins by introducing the basic concepts, typical algorithms, important features, and some applications of AIS. The second chapter introduces malware and its detection methods, especially for immune-based malware detection approaches. Successive chapters present a variety of advanced detection approaches for malware, including Virus Detection System, K-Nearest Neighbour (KNN), RBF networ s, and Support Vector Machines (SVM), Danger theory, ...

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

Science.gov (United States)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

Directory of Open Access Journals (Sweden)

Jerzy Balicki

2015-12-01

Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

The Third Age of Artificial Intelligence

OpenAIRE

Miailhe, Nicolas; Hodes, Cyrus

2018-01-01

If the definitional boundaries of Artificial Intelligence (AI) remains contested, experts agree that we are witnessing a revolution. “Is this time different?” is the question that they worryingly argue over when they analyze the socio-economic impact of the AI revolution as compared with the other industrial revolutions of the 19th and 20th centuries. This Schumpeterian wave may prove to be a creative destruction raising incomes, enhancing quality of life for all and generating previously uni...

In-plant natural versus artificial aging study

International Nuclear Information System (INIS)

Shaw, M.

1989-01-01

A few years ago, cable specimens and small electrical components were placed in the reactor buildings of several operating nuclear plants in the United States. Temperature and radiation at the specimen locations are being monitored during the life of the plants. Measured physical properties of materials removed periodically during planned outages over the next 10 to 30 years will be compared with properties of artificially aged materials in identical specimens to assess artificial aging practice. This will also lead to improved lifetime predictions for cables and equipment. The study is being performed by the University of Connecticut's Institute for Materials Science in collaboration with U. S. utilities under the sponsorship of the Electric Power Research Institute (EPRI). Cofunding is being provided by Northeast Utilities and Detroit Edison. This paper gives the status of the study, along with some preliminary results

International Conference on Artificial Neural Networks (ICANN)

CERN Document Server

Mladenov, Valeri; Kasabov, Nikola; Artificial Neural Networks : Methods and Applications in Bio-/Neuroinformatics

2015-01-01

The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new al...

Kant, Xunzi and the Artificiality of Manners

Directory of Open Access Journals (Sweden)

Anja BERNINGER

2017-01-01

Full Text Available Both Chinese and Western philosophers have argued for the ethical importance of manners. Their approaches are sometimes criticized on the grounds that manners are artificial. I compare Xunzi’s and Kant’s responses to this claim, and discuss the relevance of both positions for the development of a theory of manners. I show that there is no single artificiality claim, but rather four different claims: the claim that polite behavior lacks spontaneity, the claim that it is insincere, the claim that it goes against human nature, and the claim that it is arbitrary. While Kant is mainly concerned with the insincerity claim, Xunzi focusses on the claim that manners are arbitrary rules. Because of their different understandings of the function of manners both authors only provide a partial answer to the artificiality claim. To arrive at a full account of manners both perspectives must be combined.

Perception of artificial conspecifics by bearded dragons (Pogona vitticeps).

Science.gov (United States)

Frohnwieser, Anna; Pike, Thomas W; Murray, John C; Wilkinson, Anna

2018-01-09

Artificial animals are increasingly used as conspecific stimuli in animal behavior research. However, researchers often have an incomplete understanding of how the species under study perceives conspecifics, and hence which features needed for a stimulus to be perceived appropriately. To investigate the features to which bearded dragons (Pogona vitticeps) attend, we measured their lateralized eye use when assessing a successive range of stimuli. These ranged through several stages of realism in artificial conspecifics, to see how features such as color, the presence of eyes, body shape and motion influence behavior. We found differences in lateralized eye use depending on the sex of the observing bearded dragon and the artificial conspecific, as well as the artificial conspecific's behavior. Therefore, this approach can inform the design of robotic animals that elicit biologically-meaningful responses in live animals. This article is protected by copyright. All rights reserved.

Artificial Sight Basic Research, Biomedical Engineering, and Clinical Advances

CERN Document Server

Humayun, Mark S; Chader, Gerald; Greenbaum, Elias

2008-01-01

Artificial sight is a frontier area of modern ophthalmology combining the multidisciplinary skills of surgical ophthalmology, biomedical engineering, biological physics, and psychophysical testing. Many scientific, engineering, and surgical challenges must be surmounted before widespread practical applications can be realized. The goal of Artificial Sight is to summarize the state-of-the-art research in this exciting area, and to describe some of the current approaches and initiatives that may help patients in a clinical setting. The Editors are active researchers in the fields of artificial sight, biomedical engineering and biological physics. They have received numerous professional awards and recognition for their work. The artificial sight team at the Doheny Eye Institute, led by Dr. Mark Humayun, is a world leader in this area of biomedical engineering and clinical research. Key Features Introduces and assesses the state of the art for a broad audience of biomedical engineers, biophysicists, and clinical...

Statistical Classification for Cognitive Diagnostic Assessment: An Artificial Neural Network Approach

Science.gov (United States)

Cui, Ying; Gierl, Mark; Guo, Qi

2016-01-01

The purpose of the current investigation was to describe how the artificial neural networks (ANNs) can be used to interpret student performance on cognitive diagnostic assessments (CDAs) and evaluate the performances of ANNs using simulation results. CDAs are designed to measure student performance on problem-solving tasks and provide useful…

Towards sustainability: artificial intelligent based approach for soil stabilization using various pozzolans

KAUST Repository

Ouf, M. S.

2012-01-01

. This paper discusses attempts to reach optimum stabilization through: (1) Recognizing the relationship between the UCS/FSP of stabilized soil and the stabilization parameters using artificial neural network (ANN); and (2) Performing a backward optimization

Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information

OpenAIRE

Kinch, Martin W.; Melis, Wim J.C.; Keates, Simeon

2017-01-01

This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context in comparison to what currently happens in human life, while it would benefit from improvements in this area. Additionally, the process of transferring knowledge between application domains is another important area where artificial system can imp...

Semen parameters can be predicted from environmental factors and lifestyle using artificial intelligence methods.

Science.gov (United States)

Girela, Jose L; Gil, David; Johnsson, Magnus; Gomez-Torres, María José; De Juan, Joaquín

2013-04-01

Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors as well as life habits may affect semen quality. In this paper we use artificial intelligence techniques in order to predict semen characteristics resulting from environmental factors, life habits, and health status, with these techniques constituting a possible decision support system that can help in the study of male fertility potential. A total of 123 young, healthy volunteers provided a semen sample that was analyzed according to the World Health Organization 2010 criteria. They also were asked to complete a validated questionnaire about life habits and health status. Sperm concentration and percentage of motile sperm were related to sociodemographic data, environmental factors, health status, and life habits in order to determine the predictive accuracy of a multilayer perceptron network, a type of artificial neural network. In conclusion, we have developed an artificial neural network that can predict the results of the semen analysis based on the data collected by the questionnaire. The semen parameter that is best predicted using this methodology is the sperm concentration. Although the accuracy for motility is slightly lower than that for concentration, it is possible to predict it with a significant degree of accuracy. This methodology can be a useful tool in early diagnosis of patients with seminal disorders or in the selection of candidates to become semen donors.

Artificial neural network applications in ionospheric studies

Directory of Open Access Journals (Sweden)

L. R. Cander

1998-06-01

Full Text Available The ionosphere of Earth exhibits considerable spatial changes and has large temporal variability of various timescales related to the mechanisms of creation, decay and transport of space ionospheric plasma. Many techniques for modelling electron density profiles through entire ionosphere have been developed in order to solve the "age-old problem" of ionospheric physics which has not yet been fully solved. A new way to address this problem is by applying artificial intelligence methodologies to current large amounts of solar-terrestrial and ionospheric data. It is the aim of this paper to show by the most recent examples that modern development of numerical models for ionospheric monthly median long-term prediction and daily hourly short-term forecasting may proceed successfully applying the artificial neural networks. The performance of these techniques is illustrated with different artificial neural networks developed to model and predict the temporal and spatial variations of ionospheric critical frequency, f0F2 and Total Electron Content (TEC. Comparisons between results obtained by the proposed approaches and measured f0F2 and TEC data provide prospects for future applications of the artificial neural networks in ionospheric studies.

Integrated approach for stress based lifing of aero gas turbine blades

Science.gov (United States)

Abu, Abdullahi Obonyegba

In order to analyse the turbine blade life, the damage due to the combined thermal and mechanical loads should be adequately accounted for. This is more challenging when detailed component geometry is limited. Therefore, a compromise between the level of geometric detail and the complexity of the lifing method to be implemented would be necessary. This research focuses on how the life assessment of aero engine turbine blades can be done, considering the balance between available design inputs and adequate level of fidelity. Accordingly, the thesis contributes to developing a generic turbine blade lifing method that is based on the engine thermodynamic cycle; as well as integrating critical design/technological factors and operational parameters that influence the aero engine blade life. To this end, thermo-mechanical fatigue was identified as the critical damage phenomenon driving the life of the turbine blade.. The developed approach integrates software tools and numerical models created using the minimum design information typically available at the early design stages. Using finite element analysis of an idealised blade geometry, the approach captures relevant impacts of thermal gradients and thermal stresses that contribute to the thermo-mechanical fatigue damage on the gas turbine blade. The blade life is evaluated using the Neu/Sehitoglu thermo-mechanical fatigue model that considers damage accumulation due to fatigue, oxidation, and creep. The leading edge is examined as a critical part of the blade to estimate the damage severity for different design factors and operational parameters. The outputs of the research can be used to better understand how the environment and the operating conditions of the aircraft affect the blade life consumption and therefore what is the impact on the maintenance cost and the availability of the propulsion system. This research also finds that the environmental (oxidation) effect drives the blade life and the blade coolant

A Semiotic Approach to Food and Ethics in Everyday Life

DEFF Research Database (Denmark)

Coff, Christian

2013-01-01

The aim of this paper is to explore how food can be analysed in terms of signs and codes of everyday life, and especially how food can be used to express ethical concerns. The paper investigates the potential of a semiotic conceptual analysis: How can the semiotic approach be used to analyse...... expressions of ethics and food ethics in everyday life? The intention is to explore from a theoretical point of view and with constructed cases, how semiotics can be used to analyse the role of food as an expression of ethics in everyday life among families, friends and colleagues: How do foodstuffs function...... as signs of ethics in everyday life? How is food used to send signals about care and concern? How are the signs of food ethics perceived? It is concluded that analysing ethical considerations with respect to food with the help of the semiotic model can show us perspectives that otherwise would be difficult...

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

Science.gov (United States)

Gevarter, W. B.

1983-01-01

Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

Leaching of zinc from rubber infill on artificial turf (football pitches)

NARCIS (Netherlands)

Verschoor AJ; LER

2007-01-01

Many artificial football pitches are treated with a rubber infill made of recycled tyres. From this material zinc leaches to the soil, groundwater and surface water. [This can present significant environmental risks, particularly for aquatic life.] Human health risks posed by leaching of zinc are

Psychological approach to successful ageing predicts future quality of life in older adults

Directory of Open Access Journals (Sweden)

Iliffe Steve

2011-03-01

Full Text Available Abstract Background Public policies aim to promote well-being, and ultimately the quality of later life. Positive perspectives of ageing are underpinned by a range of appraoches to successful ageing. This study aimed to investigate whether baseline biological, psychological and social aproaches to successful ageing predicted future QoL. Methods Postal follow-up in 2007/8 of a national random sample of 999 people aged 65 and over in 1999/2000. Of 496 valid addresses of survivors at follow-up, the follow-up response rate was 58% (287. Measures of the different concepts of successful ageing were constructed using baseline indicators. They were assessed for their ability to independently predict quality of life at follow-up. Results Few respondents achieved all good scores within each of the approaches to successful ageing. Each approach was associated with follow-up QoL when their scores were analysed continuously. The biomedical (health approach failed to achieve significance when the traditional dichotomous cut-off point for successfully aged (full health, or not (less than full health, was used. In multiple regression analyses of the relative predictive ability of each approach, only the psychological approach (perceived self-efficacy and optimism retained significance. Conclusion Only the psychological approach to successful ageing independently predicted QoL at follow-up. Successful ageing is not only about the maintenance of health, but about maximising one's psychological resources, namely self-efficacy and resilience. Increasing use of preventive care, better medical management of morbidity, and changing lifestyles in older people may have beneficial effects on health and longevity, but may not improve their QoL. Adding years to life and life to years may require two distinct and different approaches, one physical and the other psychological. Follow-up health status, number of supporters and social activities, and self-rated active ageing

Inteligência biológica versus inteligência artificial: uma abordagem crítica Biologic intelligence versus artificial intelligence: a critical approach

Directory of Open Access Journals (Sweden)

Wilson Luiz Sanvito

1995-09-01

Full Text Available Após considerações iniciais sobre inteligência, um estudo comparativo entre inteligência biológica e inteligência artificial é feito. Os especialistas em Inteligência Artificial são de opinião que inteligência é simplesmente uma matéria de manipulação de símbolos físicos. Neste sentido, o objetivo da Inteligência Artificial é entender como a inteligência cerebral funciona em termos de conceitos e técnicas de engenharia. De modo diverso os filósofos da ciência acreditam que os computadores podem ter uma sintaxe, porém não têm uma semântica. No presente trabalho é ressaltado que o complexo cérebro/mente constitui um sistema monolítico, que funciona com funções emergentes em vários níveis de organização hierárquica. Esses níveis hierárquicos não são redutíveis um ao outro. Eles são, no mínimo, três (neuronal, funcional e semântico e funcionam dentro de um plano interacional. Do ponto de vista epistemológico, o complexo cérebro/mente se utiliza de mecanismos lógicos e não-lógicos para lidar com os problemas do dia-a-dia. A lógica é necessária para o processo do pensamento, porém não é suficiente. Ênfase é dada aos mecanismos não-lógicos (lógica nebulosa, heurística, raciocínio intuitivo, os quais permitem à mente desenvolver estratégias para encontrar soluções.After brief considerations about intelligence, a comparative study between biologic and artificial intelligence is made. The specialists in Artificial Intelligence found that intelligence is purely a matter of physical symbol manipulation. The enterprise of Artificial Intelligence aims to understand what we might call Brain Intelligence in terms of concepts and techniques of engineering. However the philosophers believed that computer-machine can have syntax, but can never have semantics. In other words, that they can follow rules, such as those of arithmetic or grammar, but not understand what to us are meanings of symbols

ICON: An artificial intelligence approach to radiologic differential diagnosis

International Nuclear Information System (INIS)

Swett, H.A.; Miller, P.L.

1986-01-01

ICON is a computer system, developed using artificial intelligence techniques, that is designed to help radiologists manage the large body of knowledge needed to perform differential diagnosis in radiology. The system's domain is lung disease in patients with lymphoproliferative disorders. The radiologist proposes a diagnostic hypothesis which he or she thinks explains the known clinical and chest radiographic findings. ICON responds with an English-language prose critique that discusses how and why the proposed diagnosis is or is not supported by the clinical literature and suggests further findings or clinical information that might make the diagnosis more secure

Artificial intelligence in robot control systems

Science.gov (United States)

Korikov, A.

2018-05-01

This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

High voltage transmission lines studies with the use of artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Ekonomou, L. [A.S.PE.T.E. - School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece)

2009-12-15

The paper presents an alternative approach for the studies of high voltage transmission lines based on artificial intelligence and more specifically artificial neural networks (ANNs). In contrast to the existing conventional-analytical techniques and simulations which are using in the calculations empirical and/or approximating equations, this approach is based only on actual field data and actual measurements. The proposed approach is applied on high voltage transmission lines in order to calculate the lightning outages, on grounding systems in order to assess the grounding resistance and on high voltage transmission lines' polluted insulators in order to estimate the critical flashover voltage. The obtained results are very close to the actual ones for all three case studies, something which clearly implies that the ANN approach is well working and has an acceptable accuracy, constituting an additional tool of electric engineers. (author)

Alternative Approaches to the Family Life Cycle in the Analysis of Housing Consumption.

Science.gov (United States)

McLeod, P. B.; Ellis, J. R.

1983-01-01

Used loan-approval data to analyze the effects of life-cycle stage on housing consumption. The detailed typologies were not generally superior to the more simplified approaches, except for per capita consumption. For per capita consumption, price, and quality, clear evidence is found for structural nonhomogeneity across life-cycle stages. (JAC)

A Review of Safety and Design Requirements of the Artificial Pancreas

NARCIS (Netherlands)

Blauw, Helga; Keith-Hynes, Patrick; Koops, Robin; DeVries, J. Hans

2016-01-01

As clinical studies with artificial pancreas systems for automated blood glucose control in patients with type 1 diabetes move to unsupervised real-life settings, product development will be a focus of companies over the coming years. Directions or requirements regarding safety in the design of an

Control Systems for Hyper-Redundant Robots Based on Artificial Potential Method

Directory of Open Access Journals (Sweden)

Mihaela Florescu

2015-06-01

Full Text Available This paper presents the control method of hyper-redundant robots based on the artificial potential approach. The principles of this method are shown and a suggestive example is offered. Then, the artificial potential method is applied to the case of a tentacle robot starting from the dynamic model of the robot. In addition, a series of results that are obtained through simulation is presented.

Hybrid intelligence systems and artificial neural network (ANN approach for modeling of surface roughness in drilling

Directory of Open Access Journals (Sweden)

Ch. Sanjay

2014-12-01

Full Text Available In machining processes, drilling operation is material removal process that has been widely used in manufacturing since industrial revolution. The useful life of cutting tool and its operating conditions largely controls the economics of machining operations. Drilling is most frequently performed material removing process and is used as a preliminary step for many operations, such as reaming, tapping, and boring. Drill wear has a bad effect on the surface finish and dimensional accuracy of the work piece. The surface finish of a machined part is one of the most important quality characteristics in manufacturing industries. The primary objective of this research is the prediction of suitable parameters for surface roughness in drilling. Cutting speed, cutting force, and machining time were given as inputs to the adaptive fuzzy neural network and neuro-fuzzy analysis for estimating the values of surface roughness by using 2, 3, 4, and 5 membership functions. The best structures were selected based on minimum of summation of square with the actual values with the estimated values by artificial neural fuzzy inference system (ANFIS and neuro-fuzzy systems. For artificial neural network (ANN analysis, the number of neurons was selected from 1, 2, 3, … , 20. The learning rate was selected as .5 and .5 smoothing factor was used. The inputs were selected as cutting speed, feed, machining time, and thrust force. The best structures of neural networks were selected based on the criteria as the minimum of summation of square with the actual value of surface roughness. Drilling experiments with 10 mm size were performed at two cutting speeds and feeds. Comparative analysis has been done between the actual values and the estimated values obtained by ANFIS, neuro-fuzzy, and ANN analysis.

Influence of artificial saliva in biofilm formation of Candida albicans in vitro

Directory of Open Access Journals (Sweden)

Michelle Peneluppi Silva

2012-02-01

Full Text Available Due to the increase in life expectancy, new treatments have emerged which, although palliative, provide individuals with a better quality of life. Artificial saliva is a solution that contains substances that moisten a dry mouth, thus mimicking the role of saliva in lubricating the oral cavity and controlling the existing normal oral microbiota. This study aimed to assess the influence of commercially available artificial saliva on biofilm formation by Candida albicans. Artificial saliva I consists of carboxymethylcellulose, while artificial saliva II is composed of glucose oxidase, lactoferrin, lysozyme and lactoperoxidase. A control group used sterile distilled water. Microorganisms from the oral cavity were transferred to Sabouraud Dextrose Agar and incubated at 37°C for 24 hours. Colonies of Candida albicans were suspended in a sterile solution of NaCl 0.9%, and standardisation of the suspension to 106 cells/mL was achieved. The acrylic discs, immersed in artificial saliva and sterile distilled water, were placed in a 24-well plate containing 2 mL of Sabouraud Dextrose Broth plus 5% sucrose and 0.1 mL aliquot of the Candida albicans suspension. The plates were incubated at 37°C for 5 days, the discs were washed in 2 mL of 0.9% NaCl and placed into a tube containing 10 mL of 0.9% NaCl. After decimal dilutions, aliquots of 0.1 mL were seeded on Sabouraud Dextrose Agar and incubated at 37°C for 48 hours. Counts were reported as CFU/mL (Log10. A statistically significant reduction of 29.89% (1.45 CFU/mL of Candida albicans was observed in saliva I when compared to saliva II (p = 0.002, considering p≤0.05.

Automated Scheduling Via Artificial Intelligence

Science.gov (United States)

Biefeld, Eric W.; Cooper, Lynne P.

1991-01-01

Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

ANOMALY DETECTION IN NETWORKING USING HYBRID ARTIFICIAL IMMUNE ALGORITHM

Directory of Open Access Journals (Sweden)

D. Amutha Guka

2012-01-01

Full Text Available Especially in today’s network scenario, when computers are interconnected through internet, security of an information system is very important issue. Because no system can be absolutely secure, the timely and accurate detection of anomalies is necessary. The main aim of this research paper is to improve the anomaly detection by using Hybrid Artificial Immune Algorithm (HAIA which is based on Artificial Immune Systems (AIS and Genetic Algorithm (GA. In this research work, HAIA approach is used to develop Network Anomaly Detection System (NADS. The detector set is generated by using GA and the anomalies are identified using Negative Selection Algorithm (NSA which is based on AIS. The HAIA algorithm is tested with KDD Cup 99 benchmark dataset. The detection rate is used to measure the effectiveness of the NADS. The results and consistency of the HAIA are compared with earlier approaches and the results are presented. The proposed algorithm gives best results when compared to the earlier approaches.

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

Science.gov (United States)

Abbasi, Maryam; El Hanandeh, Ali

2016-10-01

Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Human technology after cardiac epigenesis. Artificial heart versus cardiac transplantation.

Science.gov (United States)

Losman, J G

1977-09-24

Cardiovascular disease is the chief cause of death in technologically advanced countries and accounts for more than 50% of all deaths in the USA. For a patient with end-stage cardiac failure the only treatment presently available is organ replacement, either by transplantation or by the use of a mechanical heart. Transplantation has demonstrated its value: survival of more than 8 years and restoration of a normal quality of life to patients who were in end-stage cardiac decompensation. However, the prospect of routine clinical application of an artificial heart remains distant. The development of a totally implantable artificial heart still presents a series of challenging engineering problems with regard to strict constraints of size, weight, blood-material compatibility, adaptability of output to demand, efficiency and reliability of the power supply, and safety if nuclear fuel is used. The totally artificial heart is presently not an alternative to the cardiac allograft, but could provide short-term support for patients awaiting cardiac transplantation.

Three-dimensional hysteresis compensation enhances accuracy of robotic artificial muscles

Science.gov (United States)

Zhang, Jun; Simeonov, Anthony; Yip, Michael C.

2018-03-01

Robotic artificial muscles are compliant and can generate straight contractions. They are increasingly popular as driving mechanisms for robotic systems. However, their strain and tension force often vary simultaneously under varying loads and inputs, resulting in three-dimensional hysteretic relationships. The three-dimensional hysteresis in robotic artificial muscles poses difficulties in estimating how they work and how to make them perform designed motions. This study proposes an approach to driving robotic artificial muscles to generate designed motions and forces by modeling and compensating for their three-dimensional hysteresis. The proposed scheme captures the nonlinearity by embedding two hysteresis models. The effectiveness of the model is confirmed by testing three popular robotic artificial muscles. Inverting the proposed model allows us to compensate for the hysteresis among temperature surrogate, contraction length, and tension force of a shape memory alloy (SMA) actuator. Feedforward control of an SMA-actuated robotic bicep is demonstrated. This study can be generalized to other robotic artificial muscles, thus enabling muscle-powered machines to generate desired motions.

Efficacy of an artificial neural network-based approach to endoscopic ultrasound elastography in diagnosis of focal pancreatic masses.

Science.gov (United States)

Săftoiu, Adrian; Vilmann, Peter; Gorunescu, Florin; Janssen, Jan; Hocke, Michael; Larsen, Michael; Iglesias-Garcia, Julio; Arcidiacono, Paolo; Will, Uwe; Giovannini, Marc; Dietrich, Cristoph F; Havre, Roald; Gheorghe, Cristian; McKay, Colin; Gheonea, Dan Ionuţ; Ciurea, Tudorel

2012-01-01

By using strain assessment, real-time endoscopic ultrasound (EUS) elastography provides additional information about a lesion's characteristics in the pancreas. We assessed the accuracy of real-time EUS elastography in focal pancreatic lesions using computer-aided diagnosis by artificial neural network analysis. We performed a prospective, blinded, multicentric study at of 258 patients (774 recordings from EUS elastography) who were diagnosed with chronic pancreatitis (n = 47) or pancreatic adenocarcinoma (n = 211) from 13 tertiary academic medical centers in Europe (the European EUS Elastography Multicentric Study Group). We used postprocessing software analysis to compute individual frames of elastography movies recorded by retrieving hue histogram data from a dynamic sequence of EUS elastography into a numeric matrix. The data then were analyzed in an extended neural network analysis, to automatically differentiate benign from malignant patterns. The neural computing approach had 91.14% training accuracy (95% confidence interval [CI], 89.87%-92.42%) and 84.27% testing accuracy (95% CI, 83.09%-85.44%). These results were obtained using the 10-fold cross-validation technique. The statistical analysis of the classification process showed a sensitivity of 87.59%, a specificity of 82.94%, a positive predictive value of 96.25%, and a negative predictive value of 57.22%. Moreover, the corresponding area under the receiver operating characteristic curve was 0.94 (95% CI, 0.91%-0.97%), which was significantly higher than the values obtained by simple mean hue histogram analysis, for which the area under the receiver operating characteristic was 0.85. Use of the artificial intelligence methodology via artificial neural networks supports the medical decision process, providing fast and accurate diagnoses. Copyright © 2012 AGA Institute. Published by Elsevier Inc. All rights reserved.

ECO INVESTMENT PROJECT MANAGEMENT THROUGH TIME APPLYING ARTIFICIAL NEURAL NETWORKS

Directory of Open Access Journals (Sweden)

Tamara Gvozdenović

2007-06-01

Full Text Available he concept of project management expresses an indispensable approach to investment projects. Time is often the most important factor in these projects. The artificial neural network is the paradigm of data processing, which is inspired by the one used by the biological brain, and it is used in numerous, different fields, among which is the project management. This research is oriented to application of artificial neural networks in managing time of investment project. The artificial neural networks are used to define the optimistic, the most probable and the pessimistic time in PERT method. The program package Matlab: Neural Network Toolbox is used in data simulation. The feed-forward back propagation network is chosen.

A Life Course Approach to High-skilled Migration : Lived Experiences of Indians in the Netherlands

NARCIS (Netherlands)

Kou, Anu; van Wissen, Leo; van Dijk, Jouke; Bailey, Ajay

2015-01-01

This article presents a framework which applies life course approach to high-skilled migration. By using the lens of the life course, migration behaviour is viewed not only in response to labour market triggers, but also in relation to other life domains such as education, employment and household.

Enhancing Safety of Artificially Ventilated Patients Using Ambient Process Analysis.

Science.gov (United States)

Lins, Christian; Gerka, Alexander; Lüpkes, Christian; Röhrig, Rainer; Hein, Andreas

2018-01-01

In this paper, we present an approach for enhancing the safety of artificially ventilated patients using ambient process analysis. We propose to use an analysis system consisting of low-cost ambient sensors such as power sensor, RGB-D sensor, passage detector, and matrix infrared temperature sensor to reduce risks for artificially ventilated patients in both home and clinical environments. We describe the system concept and our implementation and show how the system can contribute to patient safety.

Analysis of Computer-Aided and Artificial Intelligence Technologies and Solutions in Service Industries in Russia

OpenAIRE

Rezanov, Vladislav

2013-01-01

The primary objective of this research study was to investigate the relationship between Computer-Aided and Artificial Intelligence Technologies and customer satisfaction in the context of businesses in Russia. The research focuses on methods of Artificial Intelligence technology application in business and its effect on customer satisfaction. The researcher introduces Artificial Intelligence and studies the forecasting approaches in relation to business operations. The rese...

Artificial intelligence and finite element modelling for monitoring flood defence structures

NARCIS (Netherlands)

Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

2011-01-01

We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

Imitative and Direct Learning as Interacting Factors in Life History Evolution.

Science.gov (United States)

Bullinaria, John A

2017-01-01

The idea that lifetime learning can have a significant effect on life history evolution has recently been explored using a series of artificial life simulations. These involved populations of competing individuals evolving by natural selection to learn to perform well on simplified abstract tasks, with the learning consisting of identifying regularities in their environment. In reality, there is more to learning than that type of direct individual experience, because it often includes a substantial degree of social learning that involves various forms of imitation of what other individuals have learned before them. This article rectifies that omission by incorporating memes and imitative learning into revised versions of the previous approach. To do this reliably requires formulating and testing a general framework for meme-based simulations that will enable more complete investigations of learning as a factor in any life history evolution scenarios. It does that by simulating imitative information transfer in terms of memes being passed between individuals, and developing a process for merging that information with the (possibly inconsistent) information acquired by direct experience, leading to a consistent overall body of learning. The proposed framework is tested on a range of learning variations and a representative set of life history factors to confirm the robustness of the approach. The simulations presented illustrate the types of interactions and tradeoffs that can emerge, and indicate the kinds of species-specific models that could be developed with this approach in the future.

Advanced intelligence and mechanism approach

Institute of Scientific and Technical Information of China (English)

ZHONG Yixin

2007-01-01

Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

Science.gov (United States)

Becker, Lee A.

1987-01-01

Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

Death with dignity and euthanasia: comparative European approaches.

Science.gov (United States)

Byk, Christian

2007-09-01

From 1800 to 1960, the average life expectancy doubled making medical activities a fight against death. In doing so, the dying process became medicalized. Some infectious diseases clearly disappeared while new surgical interventions, such as organ transplants, may be viewed as some kinds of human resuscitation. Sociologically, medicine has replaced religion and doctors are the new priests of our techno society. Paradoxically this has created a new fear The artificial process of dying is replacing death but it is transforming the individuals into artificially supported and suffering bodies relying on medical supervision while the family is left away, making social solidarity and compassion a relic of the past. There comes the wish to re appropriate our own death, to give a true meaning to the dying process by making it peaceful and respectful of our human dignity. This evolution takes place in a very controversial context because it is founded on various and contradictory attitudes. A rights based approach will support both the termination of futile treatment and active euthanasia while a duty-based approach will allow the physicians to accept responding positively to death claims that follow some predetermined criteria and refused others.

Development of a nuclear-powered artificial heart

International Nuclear Information System (INIS)

Mott, W.E.; Cole, D.W. Jr.

1972-01-01

Of the few known methods of furnishing power for a completely implantable artificial heart one of the most promising involves the conversion of the thermal energy from the decay of man-made radioisotopes. Serious consideration of radioisotopic, or nuclear, heat sources for implantable power supplies began in early 1964. Since then there have been some notable accomplishments on the road to a nuclear-powered system but a large number of important and difficult problems remain to be clarified. The overall objective of the Atomic Energy Commission's current program is to examine critically these problems and to provide information so that the reasonableness and practicability of the nuclear approach can be assessed at an early date. Research and development projects are underway on radioisotope heat source fuel and containment materials, on a highly reliable, long-life thermal energy conversion system and its requisite high performance thermal insulation package, on the coupling of the converter output power to the diaphragm of a suitable blood pump in such a manner that the system is fully responsive to the needs of the body, and on the radiobiological implications of large-scale heat source implantation. (auth)

Artificial Intelligence (AI techniques to analyze the determinants attributes in housing prices

Directory of Open Access Journals (Sweden)

Julia M. Núñez Tabale

2016-12-01

Full Text Available The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI techniques, such as artificial neural networks (ANN, these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain.

Epistasis analysis using artificial intelligence.

Science.gov (United States)

Moore, Jason H; Hill, Doug P

2015-01-01

Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

Providing Language Instructor with Artificial Intelligence Assistant

Directory of Open Access Journals (Sweden)

K. Pietroszek

2007-12-01

Full Text Available Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot, a voice (text-to-speech engine interface andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual world isproposed. We will discuss technical challenges and possiblefuture work directions.

An Examination of Application of Artificial Neural Network in Cognitive Radios

International Nuclear Information System (INIS)

Salau, H Bello; Onwuka, E N; Aibinu, A M

2013-01-01

Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined

An Examination of Application of Artificial Neural Network in Cognitive Radios

Science.gov (United States)

Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.

2013-12-01

Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.

A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.

Science.gov (United States)

1986-06-01

example, Duda and others translated production rules into a partitioned semantic network (73). Representations were also translated into production...153. Berlin: Springer-Verlag, 1982. 38. Blikle, Andrzej . "Equational Languages," Information and Control, 21: 134-147 (September 1972). 285 39. Ezawa...Conference on Artificial Intelligence, IJCAI-75. 115-121. William Kaufmann, Inc., Los Altos CA, 1975. 73. Duda , Richard 0. and others. "Semantic

Artificial intelligence

CERN Document Server

Ennals, J R

1987-01-01

Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

Artificial Intelligence as a Means to Moral Enhancement

Directory of Open Access Journals (Sweden)

Klincewicz Michał

2016-12-01

Full Text Available This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015. The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artificial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism or utilitarianism, that reason-responsive people can be persuaded by. This proposal can play a normative role and it is also a more promising avenue towards moral enhancement. It is more promising because such a system can be designed to take advantage of the sometimes undue trust that people put in automated technologies. We could therefore expect a well-designed moral reasoner system to be able to persuade people that may not be persuaded by similar arguments from other people. So, all things considered, there is hope in artificial intelligence for moral enhancement, but not in artificial intelligence that relies solely on ambient intelligence technologies.

A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network

Science.gov (United States)

Marto, Aminaton; Jahed Armaghani, Danial; Tonnizam Mohamad, Edy; Makhtar, Ahmad Mahir

2014-01-01

Flyrock is one of the major disturbances induced by blasting which may cause severe damage to nearby structures. This phenomenon has to be precisely predicted and subsequently controlled through the changing in the blast design to minimize potential risk of blasting. The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). For this purpose, the parameters of 113 blasting operations were accurately recorded and flyrock distances were measured for each operation. By applying the sensitivity analysis, maximum charge per delay and powder factor were determined as the most influential parameters on flyrock. In the light of this analysis, two new empirical predictors were developed to predict flyrock distance. For a comparison purpose, a predeveloped backpropagation (BP) ANN was developed and the results were compared with those of the proposed ICA-ANN model and empirical predictors. The results clearly showed the superiority of the proposed ICA-ANN model in comparison with the proposed BP-ANN model and empirical approaches. PMID:25147856

A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network

Directory of Open Access Journals (Sweden)

Aminaton Marto

2014-01-01

Full Text Available Flyrock is one of the major disturbances induced by blasting which may cause severe damage to nearby structures. This phenomenon has to be precisely predicted and subsequently controlled through the changing in the blast design to minimize potential risk of blasting. The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA and artificial neural network (ANN. For this purpose, the parameters of 113 blasting operations were accurately recorded and flyrock distances were measured for each operation. By applying the sensitivity analysis, maximum charge per delay and powder factor were determined as the most influential parameters on flyrock. In the light of this analysis, two new empirical predictors were developed to predict flyrock distance. For a comparison purpose, a predeveloped backpropagation (BP ANN was developed and the results were compared with those of the proposed ICA-ANN model and empirical predictors. The results clearly showed the superiority of the proposed ICA-ANN model in comparison with the proposed BP-ANN model and empirical approaches.

Beyond AI: Interdisciplinary Aspects of Artificial Intelligence

CERN Document Server

Romportl, Jan; Zackova, Eva; Beyond Artificial Intelligence : Contemplations, Expectations, Applications

2013-01-01

Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world.   The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011.   From its very definition, the reflection of the phenomena that lie beyond AI must be i...

AN INTRODUCTION TO KNOWLEDGE-GROWING SYSTEM: A NOVEL FIELD IN ARTIFICIAL INTELLIGENCE

Directory of Open Access Journals (Sweden)

Arwin Datumaya Wahyudi Sumari

2010-07-01

Full Text Available The essential matter of Artificial Intelligence (AI is how to build an entity that mimics human intelligence in the way of learning of a phenomenon in a real life to gain knowledge of it and uses the knowledge to solve problems related to it. Based on the findings of intelligenct characteristic displayed by the human brain in growing and generating new knowledge by fusing information perceived by sensory organs, we develop brain-inspired Knowledge-Growing System (KGS that is, a system that is capable of growing its knowledge along with the accretion of information as the time passes. The essential matter of KGS is knowledge-growing method which is based on a new algorithm called Observation Multi-time A3S (OMA3S information-inferencing fusion method. In this paper we deliver the development of KGS along with some examples of KGS application to a real-life problem. Based on the state-of-the-art of AI and approaches to construct OMA3S method as KG method as well as validations to assess the system performance, we state that brain-inspired KGS is a novel field in AI.

The Artificial, the Accidental, the Aesthetic…

Directory of Open Access Journals (Sweden)

Nicole Koltick

2015-11-01

Full Text Available How do we define, discuss or assess aesthetics within a contemporary philosophical framework? The indefiniteness that accompanies attempts to formalize a definition of the aesthetic is a primary focus of this paper. This lack of a definition has occupied philosophers for hundreds of years in attempts to delineate the boundaries of an elusively formless concept. This formlessness speaks to the incredibly evasive character of such a pervasive feature recognized in both natural and artificial systems, agents and artefacts. With the rapid growth of artificially intelligent systems and an astounding diversity in computational creativity, in what ways may we approach aesthetics? How is the aesthetic recognized, determined and produced? This paper seeks to critically engage issues of non-human agency, inter-object relations, and aesthetic theory in relation to computational entities and autonomous systems. The ability of these systems to operate outside of human cognitive limitations including thought patterns and constructions which may preclude alternative aesthetic outcomes, afford them in some ways limitless potential in relation to aesthetics. The designation of the accidental or provisional is utilized as an alternative approach to the production and assessment of aesthetic occurrences of the non-human.

Fatigue life analysis of unexpected failure in a lamellar TiAl alloy

Energy Technology Data Exchange (ETDEWEB)

Chan, K.S.

1999-07-01

Unexpected catastrophic failure occurred in specimens of a lamellar TiAl alloy tested by axial fatigue. The failure initiated at locations away from artificial defects introduced to the specimens as crack starters. Fractographic examination of the fracture surface revealed the presence of featureless, low-energy facets that suggested the catastrophic crack may have initiated in one or more large grains that cleaved on a cleavage plane or an interface. A crack growth analysis of fatigue life of the test specimens suggested that the catastrophic crack propagated at stress intensity levels below the large crack threshold. Furthermore, the catastrophic crack propagated at rates that were higher than the average rates exhibited by small cracks, as well as by the large crack under equivalent stress intensity ranges. Because of this, the conventional life prediction approach based on the large crack growth data grossly overpredicted the fatigue life.

A Multidisciplinary Artificial Intelligence Model of an Affective Robot

Directory of Open Access Journals (Sweden)

Hooman Aghaebrahimi Samani

2012-03-01

Full Text Available A multidisciplinary approach to a novel artificial intelligence system for an affective robot is presented in this paper. The general objective of the system is to develop a robotic system which strives to achieve a high level of emotional bond between humans and robot by exploring human love. Such a relationship is a contingent process of attraction, affection and attachment from humans towards robots, and the belief of the vice versa from robots to humans. The advanced artificial intelligence of the system includes three modules, namely Probabilistic Love Assembly (PLA, based on the psychology of love, Artificial Endocrine System (AES, based on the physiology of love, and Affective State Transition (AST, based on emotions. The PLA module employs a Bayesian network to incorporate psychological parameters of affection in the robot. The AES module employs artificial emotional and biological hormones via a Dynamic Bayesian Network (DBN. The AST module uses a novel transition method for handling affective states of the robot. These three modules work together to manage emotional behaviours of the robot.

An experimental biomimetic platform for artificial olfaction.

Directory of Open Access Journals (Sweden)

Corrado Di Natale

Full Text Available Artificial olfactory systems have been studied for the last two decades mainly from the point of view of the features of olfactory neuron receptor fields. Other fundamental olfaction properties have only been episodically considered in artificial systems. As a result, current artificial olfactory systems are mostly intended as instruments and are of poor benefit for biologists who may need tools to model and test olfactory models. Herewith, we show how a simple experimental approach can be used to account for several phenomena observed in olfaction. An artificial epithelium is formed as a disordered distributed layer of broadly selective color indicators dispersed in a transparent polymer layer. The whole epithelium is probed with colored light, imaged with a digital camera and the olfactory response upon exposure to an odor is the change of the multispectral image. The pixels are treated as olfactory receptor neurons, whose optical properties are used to build a convergence classifier into a number of mathematically defined artificial glomeruli. A non-homogenous exposure of the test structure to the odours gives rise to a time and spatial dependence of the response of the different glomeruli strikingly similar to patterns observed in the olfactory bulb. The model seems to mimic both the formation of glomeruli, the zonal nature of olfactory epithelium, and the spatio-temporal signal patterns at the glomeruli level. This platform is able to provide a readily available test vehicle for chemists developing optical indicators for chemical sensing purposes and for biologists to test models of olfactory system organization.

How long will my mouse live? Machine learning approaches for prediction of mouse life span.

Science.gov (United States)

Swindell, William R; Harper, James M; Miller, Richard A

2008-09-01

Prediction of individual life span based on characteristics evaluated at middle-age represents a challenging objective for aging research. In this study, we used machine learning algorithms to construct models that predict life span in a stock of genetically heterogeneous mice. Life-span prediction accuracy of 22 algorithms was evaluated using a cross-validation approach, in which models were trained and tested with distinct subsets of data. Using a combination of body weight and T-cell subset measures evaluated before 2 years of age, we show that the life-span quartile to which an individual mouse belongs can be predicted with an accuracy of 35.3% (+/-0.10%). This result provides a new benchmark for the development of life-span-predictive models, but improvement can be expected through identification of new predictor variables and development of computational approaches. Future work in this direction can provide tools for aging research and will shed light on associations between phenotypic traits and longevity.

Biological life-support systems for Mars mission.

Science.gov (United States)

Gitelson, J I

1992-01-01

Mars mission like the Lunar base is the first venture to maintain human life beyond earth biosphere. So far, all manned space missions including the longest ones used stocked reserves and can not be considered egress from biosphere. Conventional path proposed by technology for Martian mission LSS is to use physical-chemical approaches proved by the experience of astronautics. But the problem of man living beyond the limits of the earth biosphere can be fundamentally solved by making a closed ecosystem for him. The choice optimum for a Mars mission LSS can be substantiated by comparing the merits and demerits of physical-chemical and biological principles without ruling out possible compromise between them. The work gives comparative analysis of ecological and physical-chemical principles for LSS. Taking into consideration universal significance of ecological problems with artificial LSS as a particular case of their solution, complexity and high cost of large-scale experiments with manned LSS, it would be expedient for these works to have the status of an International Program open to be joined. A program of making artificial biospheres based on preceding experience and analysis of current situation is proposed.

Impacts of Artificial Reefs on Surrounding Ecosystems

Science.gov (United States)

Manoukian, Sarine

Artificial reefs are becoming a popular biological and management component in shallow water environments characterized by soft seabed, representing both important marine habitats and tools to manage coastal fisheries and resources. An artificial reef in the marine environment acts as an open system with exchange of material and energy, altering the physical and biological characteristics of the surrounding area. Reef stability will depend on the balance of scour, settlement, and burial resulting from ocean conditions over time. Because of the unstable nature of sediments, they require a detailed and systematic investigation. Acoustic systems like high-frequency multibeam sonar are efficient tools in monitoring the environmental evolution around artificial reefs, whereas water turbidity can limit visual dive and ROV inspections. A high-frequency multibeam echo sounder offers the potential of detecting fine-scale distribution of reef units, providing an unprecedented level of resolution, coverage, and spatial definition. How do artificial reefs change over time in relation to the coastal processes? How accurately does multibeam technology map different typologies of artificial modules of known size and shape? How do artificial reefs affect fish school behavior? What are the limitations of multibeam technology for investigating fish school distribution as well as spatial and temporal changes? This study addresses the above questions and presents results of a new approach for artificial reef seafloor mapping over time, based upon an integrated analysis of multibeam swath bathymetry data and geoscientific information (backscatter data analysis, SCUBA observations, physical oceanographic data, and previous findings on the geology and sedimentation processes, integrated with unpublished data) from Senigallia artificial reef, northwestern Adriatic Sea (Italy) and St. Petersburg Beach Reef, west-central Florida continental shelf. A new approach for observation of fish

A modified artificial immune system based pattern recognition approach -- an application to clinic diagnostics

Science.gov (United States)

Zhao, Weixiang; Davis, Cristina E.

2011-01-01

Objective This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis. Methods and materials Conventionally, the AIS approach is often coupled with the k nearest neighbor (k-NN) algorithm to form a classification method called AIS-kNN. In this paper we discuss the basic principle and possible problems of this conventional approach, and propose a new approach where AIS is integrated with the radial basis function – partial least square regression (AIS-RBFPLS). Additionally, both the two AIS-based approaches are compared with two classical and powerful machine learning methods, back-propagation neural network (BPNN) and orthogonal radial basis function network (Ortho-RBF network). Results The diagnosis results show that: (1) both the AIS-kNN and the AIS-RBFPLS proved to be a good machine leaning method for clinical diagnosis, but the proposed AIS-RBFPLS generated an even lower misclassification ratio, especially in the cases where the conventional AIS-kNN approach generated poor classification results because of possible improper AIS parameters. For example, based upon the AIS memory cells of “replacement threshold = 0.3”, the average misclassification ratios of two approaches for study 1 are 3.36% (AIS-RBFPLS) and 9.07% (AIS-kNN), and the misclassification ratios for study 2 are 19.18% (AIS-RBFPLS) and 28.36% (AIS-kNN); (2) the proposed AIS-RBFPLS presented its robustness in terms of the AIS-created memory cells, showing a smaller standard deviation of the results from the multiple trials than AIS-kNN. For example, using the result from the first set of AIS memory cells as an example, the standard deviations of the misclassification ratios for study 1 are 0.45% (AIS-RBFPLS) and 8.71% (AIS-kNN) and those for

Temporal anomaly detection: an artificial immune approach based on T cell activation, clonal size regulation and homeostasis.

Science.gov (United States)

Antunes, Mário J; Correia, Manuel E

2010-01-01

This paper presents an artificial immune system (AIS) based on Grossman's tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous. We conclude by discussing results obtained thus far with artificially generated data sets.

Regulation Of Hydraulic Fracturing In South Africa: A Project Life-Cycle Approach?

Directory of Open Access Journals (Sweden)

Willemien du Plessis

2015-12-01

Full Text Available This note deals with the 2015 regulations pertaining to hydraulic fracturing in South Africa from a project life-cycle approach. A brief history of the fragmentation of the regulation of environmental and mining related matters is provided, followed by a discussion of the application of the 2015 regulations during the project life cycle, ie the pre-commencement phase, the design and authorisation phase, the testing phase, the operational phase and the decommissioning and closure phase.

Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.

Science.gov (United States)

Aliabadi, Mohsen; Farhadian, Maryam; Darvishi, Ebrahim

2015-08-01

Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using artificial neural networks, this study aims to present an empirical model for the prediction of the hearing loss threshold among noise-exposed workers. Two hundred and ten workers employed in a steel factory were chosen, and their occupational exposure histories were collected. To determine the hearing loss threshold, the audiometric test was carried out using a calibrated audiometer. The personal noise exposure was also measured using a noise dosimeter in the workstations of workers. Finally, data obtained five variables, which can influence the hearing loss, were used for the development of the prediction model. Multilayer feed-forward neural networks with different structures were developed using MATLAB software. Neural network structures had one hidden layer with the number of neurons being approximately between 5 and 15 neurons. The best developed neural networks with one hidden layer and ten neurons could accurately predict the hearing loss threshold with RMSE = 2.6 dB and R(2) = 0.89. The results also confirmed that neural networks could provide more accurate predictions than multiple regressions. Since occupational hearing loss is frequently non-curable, results of accurate prediction can be used by occupational health experts to modify and improve noise exposure conditions.

Liquefaction Microzonation of Babol City Using Artificial Neural Network

DEFF Research Database (Denmark)

Farrokhzad, F.; Choobbasti, A.J.; Barari, Amin

2012-01-01

that will be less susceptible to damage during earthquakes. The scope of present study is to prepare the liquefaction microzonation map for the Babol city based on Seed and Idriss (1983) method using artificial neural network. Artificial neural network (ANN) is one of the artificial intelligence (AI) approaches...... microzonation map is produced for research area. Based on the obtained results, it can be stated that the trained neural network is capable in prediction of liquefaction potential with an acceptable level of confidence. At the end, zoning of the city is carried out based on the prediction of liquefaction...... that can be classified as machine learning. Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. In order to address the collective knowledge built-up in conventional liquefaction engineering, an alternative general regression neural network model...

Artificial intelligence in cardiology

Directory of Open Access Journals (Sweden)

Srishti Sharma

2017-01-01

Full Text Available Artificial intelligence (AI provides machines with the ability to learn and respond the way humans do and is also referred to as machine learning. The step to building an AI system is to provide the data to learn from so that it can map relations between inputs and outputs and set up parameters such as “weights”/decision boundaries to predict responses for inputs in the future. Then, the model is tested on a second data set. This article outlines the promise this analytic approach has in medicine and cardiology.

Credit Risk Evaluation System For Nigerian Banks Using Artificial Ne

African Journals Online (AJOL)

MANKABS

CREDIT RISK EVALUATION SYSTEM: AN ARTIFICIAL NEURAL NETWORK APPROACH of their own experiential .... limitations concern the high computational ... Number of existing credits at this bank. 7. Personal status and sex. 14. Job. 17.

Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production

Science.gov (United States)

2017-06-30

collect light energy and separate charge for developing new types of nanobiodevices to construct ”artificial leaf” from solar to fuel. or Concept of...AFRL-AFOSR-JP-TR-2017-0054 Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production Mamoru Nango NAGOYA INSTITUTE OF TECHNOLOGY...display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-06-2017 2

Biofluid lubrication for artificial joints

Science.gov (United States)

Pendleton, Alice Mae

This research investigated biofluid lubrication related to artificial joints using tribological and rheological approaches. Biofluids studied here represent two categories of fluids, base fluids and nanostructured biofluids. Base fluids were studied through comparison of synthetic fluids (simulated body fluid and hyaluronic acid) as well as natural biofluids (from dogs, horses, and humans) in terms of viscosity and fluid shear stress. The nano-structured biofluids were formed using molecules having well-defined shapes. Understanding nano-structured biofluids leads to new ways of design and synthesis of biofluids that are beneficial for artificial joint performance. Experimental approaches were utilized in the present research. This includes basic analysis of biofluids' property, such as viscosity, fluid shear stress, and shear rate using rheological experiments. Tribological investigation and surface characterization were conducted in order to understand effects of molecular and nanostructures on fluid lubrication. Workpiece surface structure and wear mechanisms were investigated using a scanning electron microscope and a transmission electron microscope. The surface topography was examined using a profilometer. The results demonstrated that with the adding of solid additives, such as crown ether or fullerene acted as rough as the other solids in the 3-body wear systems. In addition, the fullerene supplied low friction and low wear, which designates the lubrication purpose of this particular particle system. This dissertation is constructed of six chapters. The first chapter is an introduction to body fluids, as mentioned earlier. After Chapter II, it examines the motivation and approach of the present research, Chapter III discusses the experimental approaches, including materials, experimental setup, and conditions. In Chapter IV, lubrication properties of various fluids are discussed. The tribological properties and performance nanostructured biofluids are

Life Span Approach to Growth and Human Development: A Broad ...

African Journals Online (AJOL)

The traditional approach to the study of development emphasizes extensive change in childhood. ... the paper draws the reader's attention to the fact that by adopting the life-span perspective, we gain insights into what our lives will be like as we grow into middle age or old age, who we are, how we came to be this way and ...

Towards artificial tissue models: past, present, and future of 3D bioprinting.

Science.gov (United States)

Arslan-Yildiz, Ahu; El Assal, Rami; Chen, Pu; Guven, Sinan; Inci, Fatih; Demirci, Utkan

2016-03-01

Regenerative medicine and tissue engineering have seen unprecedented growth in the past decade, driving the field of artificial tissue models towards a revolution in future medicine. Major progress has been achieved through the development of innovative biomanufacturing strategies to pattern and assemble cells and extracellular matrix (ECM) in three-dimensions (3D) to create functional tissue constructs. Bioprinting has emerged as a promising 3D biomanufacturing technology, enabling precise control over spatial and temporal distribution of cells and ECM. Bioprinting technology can be used to engineer artificial tissues and organs by producing scaffolds with controlled spatial heterogeneity of physical properties, cellular composition, and ECM organization. This innovative approach is increasingly utilized in biomedicine, and has potential to create artificial functional constructs for drug screening and toxicology research, as well as tissue and organ transplantation. Herein, we review the recent advances in bioprinting technologies and discuss current markets, approaches, and biomedical applications. We also present current challenges and provide future directions for bioprinting research.

How to Improve Artificial Intelligence through Web

Directory of Open Access Journals (Sweden)

Adrian LUPASC

2005-10-01

Full Text Available Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers maymake their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced intoWeb Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logiclayer. The Intelligent Wireless Web’s significant potential for rapidly completing information transactions may take an important contribution toglobal worker productivity. Artificial intelligence can be defined as the study of the ways in which computers can be made to perform cognitivetasks. Examples of such tasks include understanding natural language statements, recognizing visual patterns or scenes, diagnosing diseases orillnesses, solving mathematical problems, performing financial analyses, learning new procedures for solving problems. The term expert system canbe considered to be a particular type of knowledge-based system. An expert system is a system in which the knowledge is deliberately represented“as it is”. Expert systems are applications that make decisions in real-life situations that would otherwise be performed by a human expert. They areprograms designed to mimic human performance at specialized, constrained problem-solving tasks. They are constructed as a collection of IF-THENproduction rules combined with a reasoning engine that applies those rules, either in a forward or backward direction, to specific problems.

Preterm children quality of life evaluation: a qualitative study to approach physicians’ perception

Directory of Open Access Journals (Sweden)

Einaudi Marie-Ange

2012-09-01

Full Text Available Abstract Background While data for preterm children health-related quality of life are available, there are little data on the perception of health-related quality of life evaluation by physicians who manage preterm children, or its use in real life and decision making. The aim of this qualitative study is to highlight among physicians, themes of reflection about health-related quality of life in extremely preterm children (less than 28 weeks’ gestation. Methods Focus groups at a French University Hospital with physicians who manage extremely preterm children: obstetricians, intensive care physicians, neonatal physicians and paediatric neurologists. The focus groups allowed the participants to discuss (drawing on their personal experience, three principal topics regarding the health-related quality of life of preterm children: representation, expectations in daily practice and evaluation method. Results We included fourteen participants in the three focus groups. Many themes emerged from the focus groups: approaches for defining health-related quality of life and difficulties of utilization, the role that health-related quality of life should have in the system of care, the problem of standards and evidence-based decision making. Physicians had difficulties with taking positions regarding this concept. There were no differences by gender, age or seniority, but points of view varied by specialty and type of practice. Physicians who had longer specialized care for extremely preterm children were more sensitive to the impact of preterm complications on health-related quality of life. Conclusions This study provides preliminary results about physicians’ perspective on the health-related quality of life of extremely preterm children. The themes emerged from the focus groups are classically described in other domains but not all in so clear a way (definition, interests and limits, ethical reflection. This approach was never developed in the field

Holistic approach to education and upbringing: Contradictory to the general assumption of life

Directory of Open Access Journals (Sweden)

Mihajlović Ljubiša M.

2014-01-01

Full Text Available Holistic education is a compprehensive view of education based on the assumption that each individual finds his own identity, meaning and objective in life through the connection with the community, nature and human values such as compassion and peace. Within holistic education the teacher is viewed not as an authority figure who guides and controls, but rather as a 'friend', a facilitator of learning: a guide and a companion in gaining experience. The norm is cooperation rather than competition. However, is this possible in real life? The answer is simple - it is not. Why? The reason why lies in the foundation of life itself: a molecule built in such a way that it does not permit such an idealistic approach to life, and therefore, to education. It is a DNK molecule: the molecule of life exhibiting, among other, the following characteristics: it seeks procreation, and exhibits the tendency of eternal struggle, competition. This is in stark opposition to holistic approach to education which does not recognize competition, struggle, gradation and rivalry. The development of an advanced and socially responsible society demands partial, measured application of holism. This needs to be reflected in education as well: approved competition, clear and fair gradation, the best in certain areas become the elite, with the rest following or to be found solutions in accordance with their abilities.

Evaluating the attractiveness and effectiveness of artificial coral reefs as a recreational ecosystem service.

Science.gov (United States)

Belhassen, Yaniv; Rousseau, Meghan; Tynyakov, Jenny; Shashar, Nadav

2017-12-01

Artificial reefs are increasingly being used around the globe to attract recreational divers, for both environmental and commercial reasons. This paper examines artificial coral reefs as recreational ecosystem services (RES) by evaluating their attractiveness and effectiveness and by examining divers' attitudes toward them. An online survey targeted at divers in Israel (n = 263) indicated that 35% of the dives in Eilat (a resort city on the shore of the Red Sea) take place at artificial reefs. A second study monitored divers' behavior around the Tamar artificial reef, one of the most popular submerged artificial reefs in Eilat, and juxtaposed it with divers' activities around two adjacent natural reefs. Findings show that the average diver density at the artificial reef was higher than at the two nearby natural knolls and that the artificial reef effectively diverts divers from natural knolls. A third study that examined the attitudes towards natural vs. artificial reefs found that the artificial reefs are considered more appropriate for training, but that divers feel less relaxed around them. By utilizing the RES approach as a framework, the study offers a comprehensive methodology that brings together the aesthetic, behavioral, and attitudinal aspects in terms of which artificial reefs can be evaluated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Artificial intelligence and process management

International Nuclear Information System (INIS)

Epton, J.B.A.

1989-01-01

Techniques derived from work in artificial intelligence over the past few decades are beginning to change the approach in applying computers to process management. To explore this new approach and gain real practical experience of its potential a programme of experimental applications was initiated by Sira in collaboration with the process industry. This programme encompassed a family of experimental applications ranging from process monitoring, through supervisory control and troubleshooting to planning and scheduling. The experience gained has led to a number of conclusions regarding the present level of maturity of the technology, the potential for further developments and the measures required to secure the levels of system integrity necessary in on-line applications to critical processes. (author)

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

Science.gov (United States)

Gevarter, W. B.

1983-01-01

Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm

International Nuclear Information System (INIS)

Sencan Sahin, Arzu; Kilic, Bayram; Kilic, Ulas

2011-01-01

Highlights: → Artificial Bee Colony for shell and tube heat exchanger optimization is used. → The total cost is minimized by varying design variables. → This new approach can be applied for optimization of heat exchangers. - Abstract: In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.

Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm

Energy Technology Data Exchange (ETDEWEB)

Sencan Sahin, Arzu, E-mail: sencan@tef.sdu.edu.tr [Department of Mechanical Education, Technical Education Faculty, Sueleyman Demirel University, 32260 Isparta (Turkey); Kilic, Bayram, E-mail: bayramkilic@hotmail.com [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey); Kilic, Ulas, E-mail: ulaskilic@mehmetakif.edu.tr [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey)

2011-10-15

Highlights: {yields} Artificial Bee Colony for shell and tube heat exchanger optimization is used. {yields} The total cost is minimized by varying design variables. {yields} This new approach can be applied for optimization of heat exchangers. - Abstract: In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.

Artificial Intelligence Software Engineering (AISE) model

Science.gov (United States)

Kiss, Peter A.

1990-01-01

The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

Strontium-doped calcium polyphosphate/ultrahigh molecular weight polyethylene composites: A new class of artificial joint components with enhanced biological efficacy to aseptic loosening

International Nuclear Information System (INIS)

Gu, Zhipeng; Huang, Bingxue; Li, Yiwen; Tian, Meng; Li, Li; Yu, Xixun

2016-01-01

To enhance implant stability and prolong the service life of artificial joint component, a new approach was proposed to improve the wear resistance of artificial joint component and endow artificial joint component with the biological efficacy of resistance to aseptic loosening. Strontium calcium polyphosphate (SCPP) were interfused in ultrahigh molecular weight polyethylene (UHMWPE) by a combination of liquid nitrogen ball-milling and flat-panel curing process to prepare the SCPP/UHMWPE composites. The micro-structure, mechanical characterization, tribological characterization and bioactivities of various SCPP/UHMWPE composites were investigated. The results suggested that this method could statistically improve the wear resistance of UHMWPE resulting from a good SCPP particle dispersion. Moreover, it is also observed that the SCPP/UHMWPE composites-wear particles could promote the production of OPG by osteoblasts and decrease the production of RANKL by osteoblasts, and then increase the OPG/RANKL ratio. This indicated that the SCPP/UHMWPE composites had potential efficacy to prevent and treat aseptic loosening. Above all, the SCPP/UHMWPE composites with a suitable SCPP content would be the promising materials for fabricating artificial joint component with ability to resist aseptic loosening. - Highlights: • SCPP/UHMWPE composites could enhance biological efficacy of resistance to aseptic loosening. • SCPP would improve biological efficacy with a few sacrifice of wear resistance. • The results might provide a promising wear-resistant material for fabricating acetabular cup.

Strontium-doped calcium polyphosphate/ultrahigh molecular weight polyethylene composites: A new class of artificial joint components with enhanced biological efficacy to aseptic loosening

Energy Technology Data Exchange (ETDEWEB)

Gu, Zhipeng [College of Polymer Science and Engineering, Sichuan University, Chengdu 610065 (China); Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610041 (China); Huang, Bingxue; Li, Yiwen [College of Polymer Science and Engineering, Sichuan University, Chengdu 610065 (China); Tian, Meng [Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610041 (China); Li, Li [Department of Oncology, the 452 Hospital of Chinese PLA, Chengdu 610021 (China); Yu, Xixun, E-mail: yuxixun@163.com [College of Polymer Science and Engineering, Sichuan University, Chengdu 610065 (China)

2016-04-01

To enhance implant stability and prolong the service life of artificial joint component, a new approach was proposed to improve the wear resistance of artificial joint component and endow artificial joint component with the biological efficacy of resistance to aseptic loosening. Strontium calcium polyphosphate (SCPP) were interfused in ultrahigh molecular weight polyethylene (UHMWPE) by a combination of liquid nitrogen ball-milling and flat-panel curing process to prepare the SCPP/UHMWPE composites. The micro-structure, mechanical characterization, tribological characterization and bioactivities of various SCPP/UHMWPE composites were investigated. The results suggested that this method could statistically improve the wear resistance of UHMWPE resulting from a good SCPP particle dispersion. Moreover, it is also observed that the SCPP/UHMWPE composites-wear particles could promote the production of OPG by osteoblasts and decrease the production of RANKL by osteoblasts, and then increase the OPG/RANKL ratio. This indicated that the SCPP/UHMWPE composites had potential efficacy to prevent and treat aseptic loosening. Above all, the SCPP/UHMWPE composites with a suitable SCPP content would be the promising materials for fabricating artificial joint component with ability to resist aseptic loosening. - Highlights: • SCPP/UHMWPE composites could enhance biological efficacy of resistance to aseptic loosening. • SCPP would improve biological efficacy with a few sacrifice of wear resistance. • The results might provide a promising wear-resistant material for fabricating acetabular cup.

Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

NARCIS (Netherlands)

van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

2013-01-01

The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

Application of Artificial Neural Network to Predict the use of Runway at Juanda International Airport

Science.gov (United States)

Putra, J. C. P.; Safrilah

2017-06-01

Artificial neural network approaches are useful to solve many complicated problems. It solves a number of problems in various areas such as engineering, medicine, business, manufacturing, etc. This paper presents an application of artificial neural network to predict a runway capacity at Juanda International Airport. An artificial neural network model of backpropagation and multi-layer perceptron is adopted to this research to learning process of runway capacity at Juanda International Airport. The results indicate that the training data is successfully recognizing the certain pattern of runway use at Juanda International Airport. Whereas, testing data indicate vice versa. Finally, it can be concluded that the approach of uniformity data and network architecture is the critical part to determine the accuracy of prediction results.

Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

Science.gov (United States)

Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

2018-08-01

Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

Evolvable mathematical models: A new artificial Intelligence paradigm

Science.gov (United States)

Grouchy, Paul

We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

A study of fatigue life prediction for automotive spot weldment using local strain approach

International Nuclear Information System (INIS)

Lee, Song In; Yu, Hyo Sun; Na, Sung Hun; Na, Eui Gyun

2000-01-01

The fatigue crack initiation life is studied on automotive spot weldment made from cold rolled carbon steel(SPC) sheet by using DCPDM and local strain approach. It can be found that the fatigue crack initiation behavior in spot weldment can be definitely detected by DCPDM system. The local stresses and strains are estimated by elastic-plastic FEM analysis and the alternative approximate method based on Neuber's rule were applied to predict the fatigue life of spot weldment. A satisfactory correlation between the predicted life and experimental life can be found in spot weldment within a factor of 4

Artificial-neural-network-based failure detection and isolation

Science.gov (United States)

Sadok, Mokhtar; Gharsalli, Imed; Alouani, Ali T.

1998-03-01

This paper presents the design of a systematic failure detection and isolation system that uses the concept of failure sensitive variables (FSV) and artificial neural networks (ANN). The proposed approach was applied to tube leak detection in a utility boiler system. Results of the experimental testing are presented in the paper.

Nano-Launcher Technologies, Approaches, and Life Cycle Assessment. Phase II

Science.gov (United States)

Zapata, Edgar

2014-01-01

Assist in understanding NASA technology and investment approaches, and other driving factors, necessary for enabling dedicated nano-launchers by industry at a cost and flight rate that (1) could support and be supported by an emerging nano-satellite market and (2) would benefit NASAs needs. Develop life-cycle cost, performance and other NASA analysis tools or models required to understand issues, drivers and challenges.

Using cohort change ratios to estimate life expectancy in populations with negligible migration: A new approach

Directory of Open Access Journals (Sweden)

David A. Swanson

2012-07-01

Full Text Available Census survival methods are the oldest and most widely applicable methods of estimating adult mortality, and for populations with negligible migration they can provide excellent results. The reason for this ubiquity is threefold: (1 their data requirements are minimal in that only two successive age distributions are needed; (2 the two successive age distributions are usually easily obtained from census counts; and (3 the method is straightforward in that it requires neither a great deal of judgment nor “data-fitting” techniques to implement. This ubiquity is in contrast to other methods, which require more data, as well as judgment and, often, data fitting. In this short note, the new approach we demonstrate is that life expectancy at birth can be computed by using census survival rates in combination with an identity whereby the radix of a life table is equal to 1 (l0 = 1.00. We point out that our suggested method is less involved than the existing approach. We compare estimates using our approach against other estimates, and find it works reasonably well. As well as some nuances and cautions, we discuss the benefits of using this approach to estimate life expectancy, including the ability to develop estimates of average remaining life at any age. We believe that the technique is worthy of consideration for use in estimating life expectancy in populations that experience negligible migration.

Using cohort change ratios to estimate life expectancy in populations with negligible migration: A new approach

Directory of Open Access Journals (Sweden)

Lucky Tedrow

2012-01-01

Full Text Available Census survival methods are the oldest and most widely applicable methods of estimating adult mortality, and for populations with negligible migration they can provide excellent results. The reason for this ubiquity is threefold: (1 their data requirements are minimal in that only two successive age distributions are needed; (2 the two successive age distributions are usually easily obtained from census counts; and (3 the method is straightforward in that it requires neither a great deal of judgment nor “data-fitting” techniques to implement. This ubiquity is in contrast to other methods, which require more data, as well as judgment and, often, data fitting. In this short note, the new approach we demonstrate is that life expectancy at birth can be computed by using census survival rates in combination with an identity whereby the radix of a life table is equal to 1 (l0 = 1.00. We point out that our suggested method is less involved than the existing approach. We compare estimates using our approach against other estimates, and find it works reasonably well. As well as some nuances and cautions, we discuss the benefits of using this approach to estimate life expectancy, including the ability to develop estimates of average remaining life at any age. We believe that the technique is worthy of consideration for use in estimating life expectancy in populations that experience negligible migration.

Interaction modifiers in artificial spin ices

Science.gov (United States)

Ã-stman, Erik; Stopfel, Henry; Chioar, Ioan-Augustin; Arnalds, Unnar B.; Stein, Aaron; Kapaklis, Vassilios; Hjörvarsson, Björgvin

2018-04-01

The modification of geometry and interactions in two-dimensional magnetic nanosystems has enabled a range of studies addressing the magnetic order1-6, collective low-energy dynamics7,8 and emergent magnetic properties5, 9,10 in, for example, artificial spin-ice structures. The common denominator of all these investigations is the use of Ising-like mesospins as building blocks, in the form of elongated magnetic islands. Here, we introduce a new approach: single interaction modifiers, using slave mesospins in the form of discs, within which the mesospin is free to rotate in the disc plane11. We show that by placing these on the vertices of square artificial spin-ice arrays and varying their diameter, it is possible to tailor the strength and the ratio of the interaction energies. We demonstrate the existence of degenerate ice-rule-obeying states in square artificial spin-ice structures, enabling the exploration of thermal dynamics in a spin-liquid manifold. Furthermore, we even observe the emergence of flux lattices on larger length scales, when the energy landscape of the vertices is reversed. The work highlights the potential of a design strategy for two-dimensional magnetic nano-architectures, through which mixed dimensionality of mesospins can be used to promote thermally emergent mesoscale magnetic states.

Towards a Hierarchical Definition of Life, the Organism, and Death

NARCIS (Netherlands)

Jagers Op Akkerhuis, G.A.J.M.

2010-01-01

Despite hundreds of definitions, no consensus exists on a definition of life or on the closely related and problematic definitions of the organism and death. These problems retard practical and theoretical development in, for example, exobiology, artificial life, biology and evolution. This paper

Application of the artificial bee colony algorithm for solving the set covering problem.

Science.gov (United States)

Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

2014-01-01

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem.

Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

NARCIS (Netherlands)

E.H. Gerding (Enrico); D.D.B. van Bragt; J.A. La Poutré (Han)

2000-01-01

textabstractDue to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI).

ESPEN guideline on ethical aspects of artificial nutrition and hydration.

Science.gov (United States)

Druml, Christiane; Ballmer, Peter E; Druml, Wilfred; Oehmichen, Frank; Shenkin, Alan; Singer, Pierre; Soeters, Peter; Weimann, Arved; Bischoff, Stephan C

2016-06-01

The worldwide debate over the use of artificial nutrition and hydration remains controversial although the scientific and medical facts are unequivocal. Artificial nutrition and hydration are a medical intervention, requiring an indication, a therapeutic goal and the will (consent) of the competent patient. The guideline was developed by an international multidisciplinary working group based on the main aspects of the Guideline on "Ethical and Legal Aspects of Artificial Nutrition" published 2013 by the German Society for Nutritional Medicine (DGEM) after conducting a review of specific current literature. The text was extended and introduced a broader view in particular on the impact of culture and religion. The results were discussed at the ESPEN Congress in Lisbon 2015 and accepted in an online survey among ESPEN members. The ESPEN Guideline on Ethical Aspects of Artificial Nutrition and Hydration is focused on the adult patient and provides a critical summary for physicians and caregivers. Special consideration is given to end of life issues and palliative medicine; to dementia and to specific situations like nursing care or the intensive care unit. The respect for autonomy is an important focus of the guideline as well as the careful wording to be used in the communication with patients and families. The other principles of Bioethics like beneficence, non-maleficence and justice are presented in the context of artificial nutrition and hydration. In this respect the withholding and withdrawing of artificial nutrition and/or hydration is discussed. Due to increasingly multicultural societies and the need for awareness of different values and beliefs an elaborated chapter is dedicated to cultural and religious issues and nutrition. Last but not least topics like voluntary refusal of nutrition and fluids, and forced feeding of competent persons (persons on hunger strike) is included in the guideline. Copyright © 2016 Elsevier Ltd and European Society for Clinical

Single molecule detection, thermal fluctuation and life

Science.gov (United States)

YANAGIDA, Toshio; ISHII, Yoshiharu

2017-01-01

Single molecule detection has contributed to our understanding of the unique mechanisms of life. Unlike artificial man-made machines, biological molecular machines integrate thermal noises rather than avoid them. For example, single molecule detection has demonstrated that myosin motors undergo biased Brownian motion for stepwise movement and that single protein molecules spontaneously change their conformation, for switching to interactions with other proteins, in response to thermal fluctuation. Thus, molecular machines have flexibility and efficiency not seen in artificial machines. PMID:28190869

Artificial sweeteners

DEFF Research Database (Denmark)

Raben, Anne Birgitte; Richelsen, Bjørn

2012-01-01

Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie-containin......Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie......-containing sweeteners. The purpose of this review is to summarize the current evidence on the effect of artificial sweeteners on body weight, appetite, and risk markers for diabetes and CVD in humans....

The use of theory in qualitative approaches to research: application in end-of-life studies.

Science.gov (United States)

Wu, Hung-Lan; Volker, Deborah L

2009-12-01

This paper is a report of an analysis of the use of theory in qualitative approaches to research as exemplified in qualitative end-of-life studies. Nurses researchers turn to theory to conceptualize research problems and guide investigations. However, researchers using qualitative approaches do not consistently articulate how theory has been applied, and no clear consensus exists regarding the appropriate application of theory in qualitative studies. A review of qualitative, end-of-life studies is used to illustrate application of theory to study design and findings. A review of theoretical literature was carried out, focusing on definitions and use of theory in qualitative end-of-life studies published in English between 1990 and 2008. The term 'theory' continues to be used in a variety of ways by theorists and researchers. Within the reviewed end-of-life studies, the use of theory included theory creation or provision of a comparative framework for data analysis and interpretation. Implications for nursing. Nurses who conduct qualitative studies should examine the philosophical and theoretical bases of their selected methodological approach, articulate a theoretical framework that fits the phenomenon being studied, and adopt a critical, flexible and creative attitude when applying theory to a study. Theory can be put to several uses in qualitative inquiry and should guide nurse researchers as they develop and implement their studies. Nurse educators who teach qualitative approaches to research should emphasize a variety of ways to incorporate theory in qualitative designs.

Artificial Neural Network Approach in Laboratory Test Reporting:  Learning Algorithms.

Science.gov (United States)

Demirci, Ferhat; Akan, Pinar; Kume, Tuncay; Sisman, Ali Riza; Erbayraktar, Zubeyde; Sevinc, Suleyman

2016-08-01

In the field of laboratory medicine, minimizing errors and establishing standardization is only possible by predefined processes. The aim of this study was to build an experimental decision algorithm model open to improvement that would efficiently and rapidly evaluate the results of biochemical tests with critical values by evaluating multiple factors concurrently. The experimental model was built by Weka software (Weka, Waikato, New Zealand) based on the artificial neural network method. Data were received from Dokuz Eylül University Central Laboratory. "Training sets" were developed for our experimental model to teach the evaluation criteria. After training the system, "test sets" developed for different conditions were used to statistically assess the validity of the model. After developing the decision algorithm with three iterations of training, no result was verified that was refused by the laboratory specialist. The sensitivity of the model was 91% and specificity was 100%. The estimated κ score was 0.950. This is the first study based on an artificial neural network to build an experimental assessment and decision algorithm model. By integrating our trained algorithm model into a laboratory information system, it may be possible to reduce employees' workload without compromising patient safety. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Securing Relay Networks with Artificial Noise: An Error Performance-Based Approach

Directory of Open Access Journals (Sweden)

Ying Liu

2017-07-01

Full Text Available We apply the concept of artificial and controlled interference in a two-hop relay network with an untrusted relay, aiming at enhancing the wireless communication secrecy between the source and the destination node. In order to shield the square quadrature amplitude-modulated (QAM signals transmitted from the source node to the relay, the destination node designs and transmits artificial noise (AN symbols to jam the relay reception. The objective of our considered AN design is to degrade the error probability performance at the untrusted relay, for different types of channel state information (CSI at the destination. By considering perfect knowledge of the instantaneous CSI of the source-to-relay and relay-to-destination links, we first present an analytical expression for the symbol error rate (SER performance at the relay. Based on the assumption of an average power constraint at the destination node, we then derive the optimal phase and power distribution of the AN that maximizes the SER at the relay. Furthermore, we obtain the optimal AN design for the case where only statistical CSI is available at the destination node. For both cases, our study reveals that the Gaussian distribution is generally not optimal to generate AN symbols. The presented AN design takes into account practical parameters for the communication links, such as QAM signaling and maximum likelihood decoding.

Artificial cognition architectures

CERN Document Server

Crowder, James A; Friess, Shelli A

2013-01-01

The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution

The systems approach for applying artificial intelligence to space station automation (Invited Paper)

Science.gov (United States)

Grose, Vernon L.

1985-12-01

The progress of technology is marked by fragmentation -- dividing research and development into ever narrower fields of specialization. Ultimately, specialists know everything about nothing. And hope for integrating those slender slivers of specialty into a whole fades. Without an integrated, all-encompassing perspective, technology becomes applied in a lopsided and often inefficient manner. A decisionary model, developed and applied for NASA's Chief Engineer toward establishment of commercial space operations, can be adapted to the identification, evaluation, and selection of optimum application of artificial intelligence for space station automation -- restoring wholeness to a situation that is otherwise chaotic due to increasing subdivision of effort. Issues such as functional assignments for space station task, domain, and symptom modules can be resolved in a manner understood by all parties rather than just the person with assigned responsibility -- and ranked by overall significance to mission accomplishment. Ranking is based on the three basic parameters of cost, performance, and schedule. This approach has successfully integrated many diverse specialties in situations like worldwide terrorism control, coal mining safety, medical malpractice risk, grain elevator explosion prevention, offshore drilling hazards, and criminal justice resource allocation -- all of which would have otherwise been subject to "squeaky wheel" emphasis and support of decision-makers.

Stability of Bifurcating Stationary Solutions of the Artificial Compressible System

Science.gov (United States)

Teramoto, Yuka

2018-02-01

The artificial compressible system gives a compressible approximation of the incompressible Navier-Stokes system. The latter system is obtained from the former one in the zero limit of the artificial Mach number ɛ which is a singular limit. The sets of stationary solutions of both systems coincide with each other. It is known that if a stationary solution of the incompressible system is asymptotically stable and the velocity field of the stationary solution satisfies an energy-type stability criterion, then it is also stable as a solution of the artificial compressible one for sufficiently small ɛ . In general, the range of ɛ shrinks when the spectrum of the linearized operator for the incompressible system approaches to the imaginary axis. This can happen when a stationary bifurcation occurs. It is proved that when a stationary bifurcation from a simple eigenvalue occurs, the range of ɛ can be taken uniformly near the bifurcation point to conclude the stability of the bifurcating solution as a solution of the artificial compressible system.

Understanding of xerostomia and strategies for the development of artificial saliva.

Science.gov (United States)

Kho, Hong-Seop

2014-01-01

Xerostomia is becoming a major issue in dental and medical clinics with an increase of aged population. Medication is the most common etiology of xerostomia, while the most severe xerostomia generally occurs in patients with a history of head and neck radiotherapy. Xerostomic patients usually suffer from diminished quality of life due to various symptoms and complications. Decreased salivary output is a definite objective sign, but oral mucosal wetness is a more reliable factor for the evaluation of xerostomia. At present there are no effective therapeutic methods for the treatment of xerostomia. Sialogogues may have problematic side effects and their therapeutic effects last only brief duration. Artificial saliva typically does not produce satisfactory results in therapeutic efficacy. Therefore, further research and development of better therapeutic modalities are necessary. The basic concept for the development of ideal and functional artificial saliva is the mimicry of natural human saliva. We need proper candidate molecules and antimicrobial supplements to simulate the rheological and biological properties of human saliva. We also need better understanding of the interactions between the ingredients of artificial saliva themselves and between the ingredients and components of human saliva both in solution and on surface phases. In addition, we need accepted measures to evaluate the efficacy of artificial saliva. In conclusion, for the development of ideal artificial saliva, research based on the understanding of pathophysiology of xerostomia and knowledge about rheological and biological functions of human saliva are necessary.

Disruption of behavior and brain metabolism in artificially reared rats.

Science.gov (United States)

Aguirre-Benítez, Elsa L; Porras, Mercedes G; Parra, Leticia; González-Ríos, Jacquelina; Garduño-Torres, Dafne F; Albores-García, Damaris; Avendaño, Arturo; Ávila-Rodríguez, Miguel A; Melo, Angel I; Jiménez-Estrada, Ismael; Mendoza-Garrido, Ma Eugenia; Toriz, César; Diaz, Daniel; Ibarra-Coronado, Elizabeth; Mendoza-Ángeles, Karina; Hernández-Falcón, Jesús

2017-12-01

Early adverse life stress has been associated to behavioral disorders that can manifest as inappropriate or aggressive responses to social challenges. In this study, we analyzed the effects of artificial rearing on the open field and burial behavioral tests and on GFAP, c-Fos immunoreactivity, and glucose metabolism measured in anxiety-related brain areas. Artificial rearing of male rats was performed by supplying artificial milk through a cheek cannula and tactile stimulation, mimicking the mother's licking to rat pups from the fourth postnatal day until weaning. Tactile stimulation was applied twice a day, at morning and at night, by means of a camel brush on the rat anogenital area. As compared to mother reared rats, greater aggressiveness, and boldness, stereotyped behavior (burial conduct) was observed in artificially reared rats which occurred in parallel to a reduction of GFAP immunoreactivity in somatosensory cortex, c-Fos immunoreactivity at the amygdala and primary somatosensory cortex, and lower metabolism in amygdala (as measured by 2-deoxi-2-[ 18 fluoro]-d-glucose uptake, assessed by microPET imaging). These results could suggest that tactile and/or chemical stimuli from the mother and littermates carry relevant information for the proper development of the central nervous system, particularly in brain areas involved with emotions and social relationships of the rat. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 77: 1413-1429, 2017. © 2017 Wiley Periodicals, Inc.

A relational ethical approach to end-of-life delirium.

Science.gov (United States)

Wright, David Kenneth; Brajtman, Susan; Macdonald, Mary Ellen

2014-08-01

Delirium is a condition of acute onset and fluctuating course in which a person's level of consciousness and cognition become disturbed. Delirium is a common and distressing phenomenon in end-of-life care, yet it is underrecognized and undertreated. In this article, we review qualitative descriptions of the delirium experience in end-of-life care, found through a systematic search of academic databases, to generate insight into the intersubjective nature of the delirium experience. Our analysis of retrieved studies advances an understanding of the relational ethical dimensions of this phenomenon, that is, how delirium is lived by patients, families, and health care providers and how it affects the relationships and values at stake. We propose three themes that explain the distressing nature of delirium in palliative care: 1) experiences of relational tension; 2) challenges in recognizing the delirious person; and 3) struggles to interpret the meaning of delirious behaviors. By approaching end-of-life delirium from a perspective of relational ethics, attention is focused on the implications for the therapeutic relationship with patients and families when delirium becomes part of the dying trajectory. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Design of Multithreaded Software The Entity-Life Modeling Approach

CERN Document Server

Sandén, Bo I

2011-01-01

This book assumes familiarity with threads (in a language such as Ada, C#, or Java) and introduces the entity-life modeling (ELM) design approach for certain kinds of multithreaded software. ELM focuses on "reactive systems," which continuously interact with the problem environment. These "reactive systems" include embedded systems, as well as such interactive systems as cruise controllers and automated teller machines.Part I covers two fundamentals: program-language thread support and state diagramming. These are necessary for understanding ELM and are provided primarily for reference. P

Artificial Disc Replacement

Science.gov (United States)

... Spondylolisthesis BLOG FIND A SPECIALIST Treatments Artificial Disc Replacement (ADR) Patient Education Committee Jamie Baisden The disc ... Disc An artificial disc (also called a disc replacement, disc prosthesis or spine arthroplasty device) is a ...

Artificial Intelligence, Evolutionary Computing and Metaheuristics In the Footsteps of Alan Turing

CERN Document Server

2013-01-01

Alan Turing pioneered many research areas such as artificial intelligence, computability, heuristics and pattern formation.  Nowadays at the information age, it is hard to imagine how the world would be without computers and the Internet. Without Turing's work, especially the core concept of Turing Machine at the heart of every computer, mobile phone and microchip today, so many things on which we are so dependent would be impossible. 2012 is the Alan Turing year -- a centenary celebration of the life and work of Alan Turing. To celebrate Turing's legacy and follow the footsteps of this brilliant mind, we take this golden opportunity to review the latest developments in areas of artificial intelligence, evolutionary computation and metaheuristics, and all these areas can be traced back to Turing's pioneer work. Topics include Turing test, Turing machine, artificial intelligence, cryptography, software testing, image processing, neural networks, nature-inspired algorithms such as bat algorithm and cuckoo sear...

Nonthrombotic artificial mass in right ventricle and pulmonary circulation as a sequence of vertebroplasty

International Nuclear Information System (INIS)

Monovska, T.; Kirova, G.; Bojinov, D.; Kichukov, K.

2013-01-01

Full text: Introduction: Percutaneous vertebroplasty for the treatment of the vertebral body fractures is considered to be relatively safe therapeutic procedure. Nevertheless there is a potential risk of spread of emboli from artificial material through external vertebral venous plexus. What you will learn: This is a 60 -year-old patient with primary diagnosis of multiple myeloma and conducted vertebroplasty due to the vertebral bodies fractures. Accompanying symptoms are: coughing up blood and pain in the right the chest with medication for micro thromboembolism form of Pulmonary thromboembolism (PTE). There are echocardiographic data on hospitalization for a formation in the right ventricle. Based on additionally performed CT study, a ‘foreign body’ - artificial material in right ventricle and subsegmentary branches of the pulmonary arteries as a complication of previous vertebroplasty has been recorded. Paravertebral venous vessels in the area of the thoracic section filled with cement have been noticed. Discussion: non-thrombotic embolism of artificial material prior vertebroplasty can be asymptomatic, or condition may be associated with life-threatening symptoms - compression of the spinal cord resulting in paraplegia, emboli in the cerebral vessels, right ventricle, kidney arteries. The frequency of the topical flowing of the used material is relatively high (80-90 %) to the para-vertebral vein (over 24%), with subsequent pulmonary emboli (4.6 to 6.8 %). The path of the embolization material dissemination is in the course of the para-vertebral veins, v. azygos and v. cafa inf., with the end goal pulmonary circulation. Conclusion: Follow-up of patients after the therapeutic vertebroplasty and integrated diagnostic approach with appropriate imaging methods allow timely diagnosis and treatment of this unusual form of non-thrombotic embolism

On the synergy of network science and artificial intelligence

NARCIS (Netherlands)

Mocanu, D.C.

2016-01-01

Traditionally science is done using the reductionism paradigm. Artificial intelligence does not make an exception and it follows the same strategy. At the same time, network science tries to study complex systems as a whole. This Ph.D. research takes an alternative approach to the reductionism

Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

Prediction of hydrate formation temperature by both statistical models and artificial neural network approaches

International Nuclear Information System (INIS)

Zahedi, Gholamreza; Karami, Zohre; Yaghoobi, Hamed

2009-01-01

In this study, various estimation methods have been reviewed for hydrate formation temperature (HFT) and two procedures have been presented. In the first method, two general correlations have been proposed for HFT. One of the correlations has 11 parameters, and the second one has 18 parameters. In order to obtain constants in proposed equations, 203 experimental data points have been collected from literatures. The Engineering Equation Solver (EES) and Statistical Package for the Social Sciences (SPSS) soft wares have been employed for statistical analysis of the data. Accuracy of the obtained correlations also has been declared by comparison with experimental data and some recent common used correlations. In the second method, HFT is estimated by artificial neural network (ANN) approach. In this case, various architectures have been checked using 70% of experimental data for training of ANN. Among the various architectures multi layer perceptron (MLP) network with trainlm training algorithm was found as the best architecture. Comparing the obtained ANN model results with 30% of unseen data confirms ANN excellent estimation performance. It was found that ANN is more accurate than traditional methods and even our two proposed correlations for HFT estimation.

Artificial Intelligence and Semantics through the Prism of Structural, Post-Structural and Transcendental Approaches.

Science.gov (United States)

Gasparyan, Diana

2016-12-01

There is a problem associated with contemporary studies of philosophy of mind, which focuses on the identification and convergence of human and machine intelligence. This is the problem of machine emulation of sense. In the present study, analysis of this problem is carried out based on concepts from structural and post-structural approaches that have been almost entirely overlooked by contemporary philosophy of mind. If we refer to the basic definitions of "sign" and "meaning" found in structuralism and post-structuralism, we see a fundamental difference between the capabilities of a machine and the human brain engaged in the processing of a sign. This research will exemplify and provide additional evidence to support distinctions between syntactic and semantic aspects of intelligence, an issue widely discussed by adepts of contemporary philosophy of mind. The research will demonstrate that some aspect of a number of ideas proposed in relation to semantics and semiosis in structuralism and post-structuralism are similar to those we find in contemporary analytical studies related to the theory and philosophy of artificial intelligence. The concluding part of the paper offers an interpretation of the problem of formalization of sense, connected to its metaphysical (transcendental) properties.

Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

Science.gov (United States)

Mishra, D.; Goyal, P.

2014-12-01

Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

The application of hybrid artificial intelligence systems for forecasting

Science.gov (United States)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

The origami of life

Energy Technology Data Exchange (ETDEWEB)

Lezon, Timothy R [Department of Physics, 104 Davey Laboratory, Pennsylvania State University, University Park, PA 16802 (United States); Banavar, Jayanth R [Department of Physics, 104 Davey Laboratory, Pennsylvania State University, University Park, PA 16802 (United States); Maritan, Amos [Dipartimento di Fisica ' G Galilei' and INFN, Universita di Padova, Via Marzolo 8, 35131 Padova (Italy)

2006-01-25

All living organisms rely upon networks of molecular interactions to carry out their vital processes. In order for a molecular system to display the properties of life, its constituent molecules must themselves be endowed with several features: stability, specificity, self-organization, functionality, sensitivity, robustness, diversity and adaptability. We argue that these are the emergent properties of a unique phase of matter, and we demonstrate that proteins, the functional molecules of terrestrial life, are perfectly suited to this phase. We explore, through an understanding of this phase of matter, the physical principles that govern the operation of living matter. Our work has implications for the design of functionally useful nanoscale devices and the ultimate development of physically based artificial life.

The origami of life

International Nuclear Information System (INIS)

Lezon, Timothy R; Banavar, Jayanth R; Maritan, Amos

2006-01-01

All living organisms rely upon networks of molecular interactions to carry out their vital processes. In order for a molecular system to display the properties of life, its constituent molecules must themselves be endowed with several features: stability, specificity, self-organization, functionality, sensitivity, robustness, diversity and adaptability. We argue that these are the emergent properties of a unique phase of matter, and we demonstrate that proteins, the functional molecules of terrestrial life, are perfectly suited to this phase. We explore, through an understanding of this phase of matter, the physical principles that govern the operation of living matter. Our work has implications for the design of functionally useful nanoscale devices and the ultimate development of physically based artificial life

Fluid propulsion using magnetically-actuated artificial cilia : Experiments and simulations

NARCIS (Netherlands)

Khaderi, Syed; Hussong, Jeanette; Westerweel, Jerry; den Toonder, Jaap; Onck, Patrick

2013-01-01

We conducted a combined modelling and experimental approach to explore the underlying physical mechanisms responsible for fluid flow caused by magnetically-actuated plate-like artificial cilia. After independently calibrating the elastic and magnetic properties of the cilia, the model predictions

Fluid propulsion using magnetically-actuated artificial cilia : experiments and simulations

NARCIS (Netherlands)

Khaderi, S.N.; Hussong, J.; Westerweel, J.; Toonder, den J.M.J.; Onck, P.R.

2013-01-01

We conducted a combined modelling and experimental approach to explore the underlying physical mechanisms responsible for fluid flow caused by magnetically-actuated plate-like artificial cilia. After independently calibrating the elastic and magnetic properties of the cilia, the model predictions

Examination of Relationship between Self-esteem, Life Satisfaction of Riot Policemen and Their Approach to Dealing with Stress

OpenAIRE

Ruhi YİĞİT

2012-01-01

Main objective of this study is to examinate of relationship between self-esteem, life satisfaction of riot police and their approach to dealing with stress. Research data has been obtained through using self-esteem scale and inventory of approach to dealing with stress. The first finding is that there is a positive and meaningful relationship between self-esteem of riot police and their life satisfaction. As the self-esteem increases, so the life satisfaction does. The second finding is that...

Nondestructive pavement evaluation using ILLI-PAVE based artificial neural network models.

Science.gov (United States)

2008-09-01

The overall objective in this research project is to develop advanced pavement structural analysis models for more accurate solutions with fast computation schemes. Soft computing and modeling approaches, specifically the Artificial Neural Network (A...

Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

Directory of Open Access Journals (Sweden)

Mustafa Serter Uzer

2013-01-01

Full Text Available This paper offers a hybrid approach that uses the artificial bee colony (ABC algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.

Changes in genetic architecture during relaxation in Drosophila melanogaster selected on divergent virgin life span

NARCIS (Netherlands)

Vermeulen, CJ; Bijlsma, R

Artificial selection experiments often confer important information on the genetic correlations constraining the evolution of life history. After artificial selection has ceased however, selection pressures in the culture environment can change the correlation matrix again. Here, we reinvestigate

Advanced solutions in power systems HVDC, facts, and artificial intelligence

CERN Document Server

Liu, Chen-Ching; Edris, Abdel-Aty

2016-01-01

Provides insight on both classical means and new trends in the application of power electronic and artificial intelligence techniques in power system operation and control This book presents advanced solutions for power system controllability improvement, transmission capability enhancement and operation planning. The book is organized into three parts. The first part describes the CSC-HVDC and VSC-HVDC technologies, the second part presents the FACTS devices, and the third part refers to the artificial intelligence techniques. All technologies and tools approached in this book are essential for power system development to comply with the smart grid requirements.

Co je na životě tak zvláštního? Příklad redukcionismu René Descarta (What is so special about life? The example of René Descartes‘ reductionism

Directory of Open Access Journals (Sweden)

Vladimír Vodička

2017-03-01

Full Text Available History of philosophy offers many examples capable of informing discussions related to questions, topics and problems, which are actual for both philosophy and particular scientific fields. Explanation of the nature of life is such a topic. Although current debates have been paying attention to the impact of scientific findings on our understanding of the phenomenon of life, the very definition of life falls in to the continuum between philosophy and science, the endeavor to capture origin of life and possibilities of creating artificial life bring up both theoretical and practical questions alike. In this paper we approach to the analysis of the standpoint of one of the most important philosophical authorities of modern philosophy, René Descartes. By the analysis of his approach to the nature of life we try to amend his reception and intellectual legacy of not so well appreciated part of his works.

The New Genetics and Natural versus Artificial Genetic Modification

Directory of Open Access Journals (Sweden)

Mae-Wan Ho

2013-11-01

Full Text Available The original rationale and impetus for artificial genetic modification was the “central dogma” of molecular biology that assumed DNA carries all the instructions for making an organism, which are transmitted via RNA to protein to biological function in linear causal chains. This is contrary to the reality of the “fluid genome” that has emerged since the mid-1970s. In order to survive, the organism needs to engage in natural genetic modification in real time, an exquisitely precise molecular dance of life with RNA and DNA responding to and participating in “downstream” biological functions. Artificial genetic modification, in contrast, is crude, imprecise, and interferes with the natural process. It drives natural systems towards maximum biosemiotic entropy as the perturbations are propagated and amplified through the complex cascades of interactions between subsystems that are essential for health and longevity.

An Approach to Object Recognition: Aligning Pictorial Descriptions.

Science.gov (United States)

1986-12-01

PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

Implementation of science process skills using ICT-based approach to facilitate student life skills

Science.gov (United States)

Rahayu, Y. S.; Yuliani; Wijaya, B. R.

2018-01-01

The purpose of this study is to describe the results of the implementation of a teaching-learning package in Plant Physiology courses to improve the student’s life skills using the science process skills-based approach ICT. This research used 15 students of Biology Education of Undergraduate International Class who are in the Plant Physiology course. This study consists of two phases items, namely the development phase and implementation phase by using a one-shot case study design. Research parameters were the feasibility of lesson plans, student achievement, Including academic skills, thinking skills, and social skills. Data were descriptively Analyzed According to the characteristics of the existing data. The result shows that the feasibility of a lesson plan is very satisfied and can be improvements in student’s life skills, especially with regards to student’s thinking skills and scientific thinking skills. The results indicate that the science process skills using ICT-based approach can be effective methods to improve student’s life skills.

Emergent Properties in Natural and Artificial Dynamical Systems

CERN Document Server

Aziz-Alaoui, M.A

2006-01-01

An important part of the science of complexity is the study of emergent properties arising through dynamical processes in various types of natural and artificial systems. This is the aim of this book, which is the outcome of a discussion meeting within the first European conference on complex systems. It presents multidisciplinary approaches for getting representations of complex systems and using different methods to extract emergent structures. This carefully edited book studies emergent features such as self organization, synchronization, opening on stability and robustness properties. Invariant techniques are presented which can express global emergent properties in dynamical and in temporal evolution systems. This book demonstrates how artificial systems such as a distributed platform can be used for simulation used to search emergent placement during simulation execution.

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

Science.gov (United States)

Enshaei, A; Robson, C N; Edmondson, R J

2015-11-01

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.

The Life-course Approach in Assessment of Dental Health: A Cross Sectional Study among Finnish and Turkish Pre-adolescents

DEFF Research Database (Denmark)

Cinar, Ayse Basak; Murtomaa, Heikki; Tseveenjav, Battsetseg

2008-01-01

Interest is growing on conceptualizing dental disease aetiology under the life-course approach. The aim of this study was to assess the association of dental caries experience with the major components of life-course approach, health- and behavioral capital, among Turkish and Finnish pre-adolesce...

The Quality of Life and relevant Approaches based on Capabilities and Functionalities

Directory of Open Access Journals (Sweden)

Matei Șimandan

2014-12-01

Full Text Available Recent research regarding the quality of life developed different approaches concerning the use of objective and subjective indicators, as well as the relevance of hypotheses, propositions and methods of analysis or of evaluation. Starting from the conceptual difficulties regarding the term of ‘quality of life’, this article focuses upon the contributions of Amartya Sen on the relationships between resources, liberties, capabilities, functionalities and human development. A separate section attempts to capture the shift of accent from the approaches of a quantitative type towards those of a qualitative type, founded on capabilities, functionalities, and the factors of conversion of resources into elements of quality of subjective life. The following sections are consecrated to the contributions to the development of the model proposed by Amartya Sen and to the reception of this model by a few specialists in the field, as well as to its relevance within scientific research and the foundation of public policies.

Predicting asthma exacerbations using artificial intelligence.

Science.gov (United States)

Finkelstein, Joseph; Wood, Jeffrey

2013-01-01

Modern telemonitoring systems identify a serious patient deterioration when it already occurred. It would be much more beneficial if the upcoming clinical deterioration were identified ahead of time even before a patient actually experiences it. The goal of this study was to assess artificial intelligence approaches which potentially can be used in telemonitoring systems for advance prediction of changes in disease severity before they actually occur. The study dataset was based on daily self-reports submitted by 26 adult asthma patients during home telemonitoring consisting of 7001 records. Two classification algorithms were employed for building predictive models: naïve Bayesian classifier and support vector machines. Using a 7-day window, a support vector machine was able to predict asthma exacerbation to occur on the day 8 with the accuracy of 0.80, sensitivity of 0.84 and specificity of 0.80. Our study showed that methods of artificial intelligence have significant potential in developing individualized decision support for chronic disease telemonitoring systems.

Wet-Spun Biofiber for Torsional Artificial Muscles.

Science.gov (United States)

Mirabedini, Azadeh; Aziz, Shazed; Spinks, Geoffrey M; Foroughi, Javad

2017-12-01

The demands for new types of artificial muscles continue to grow and novel approaches are being enabled by the advent of new materials and novel fabrication strategies. Self-powered actuators have attracted significant attention due to their ability to be driven by elements in the ambient environment such as moisture. In this study, we demonstrate the use of twisted and coiled wet-spun hygroscopic chitosan fibers to achieve a novel torsional artificial muscle. The coiled fibers exhibited significant torsional actuation where the free end of the coiled fiber rotated up to 1155 degrees per mm of coil length when hydrated. This value is 96%, 362%, and 2210% higher than twisted graphene fiber, carbon nanotube torsional actuators, and coiled nylon muscles, respectively. A model based on a single helix was used to evaluate the torsional actuation behavior of these coiled chitosan fibers.

An artificial intelligence approach towards disturbance analysis in nuclear power plants

International Nuclear Information System (INIS)

Lindner, A.; Klebau, J.; Fielder, U.; Baldeweg, F.

1987-01-01

The scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in wellknown situations. But in cases of emergencies, the operator staff needs a more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application in nuclear power plants. 9 refs. (author)

Thermal responses of shape memory alloy artificial anal sphincters

Science.gov (United States)

Luo, Yun; Takagi, Toshiyuki; Matsuzawa, Kenichi

2003-08-01

This paper presents a numerical investigation of the thermal behavior of an artificial anal sphincter using shape memory alloys (SMAs) proposed by the authors. The SMA artificial anal sphincter has the function of occlusion at body temperature and can be opened with a thermal transformation induced deformation of SMAs to solve the problem of severe fecal incontinence. The investigation of its thermal behavior is of great importance in terms of practical use in living bodies as a prosthesis. In this work, a previously proposed phenomenological model was applied to simulate the thermal responses of SMA plates that had undergone thermally induced transformation. The numerical approach for considering the thermal interaction between the prosthesis and surrounding tissues was discussed based on the classical bio-heat equation. Numerical predictions on both in vitro and in vivo cases were verified by experiments with acceptable agreements. The thermal responses of the SMA artificial anal sphincter were discussed based on the simulation results, with the values of the applied power and the geometric configuration of thermal insulation as parameters. The results obtained in the present work provided a framework for the further design of SMA artificial sphincters to meet demands from the viewpoint of thermal compatibility as prostheses.

Natural vs. artificial groundwater recharge, quantification through inverse modeling

Directory of Open Access Journals (Sweden)

H. Hashemi

2013-02-01

Full Text Available Estimating the change in groundwater recharge from an introduced artificial recharge system is important in order to evaluate future water availability. This paper presents an inverse modeling approach to quantify the recharge contribution from both an ephemeral river channel and an introduced artificial recharge system based on floodwater spreading in arid Iran. The study used the MODFLOW-2000 to estimate recharge for both steady- and unsteady-state conditions. The model was calibrated and verified based on the observed hydraulic head in observation wells and model precision, uncertainty, and model sensitivity were analyzed in all modeling steps. The results showed that in a normal year without extreme events, the floodwater spreading system is the main contributor to recharge with 80% and the ephemeral river channel with 20% of total recharge in the studied area. Uncertainty analysis revealed that the river channel recharge estimation represents relatively more uncertainty in comparison to the artificial recharge zones. The model is also less sensitive to the river channel. The results show that by expanding the artificial recharge system, the recharge volume can be increased even for small flood events, while the recharge through the river channel increases only for major flood events.

[Evaluation of the Function and Quality of Life after Total Hip Arthroplasty by Different Approaches].

Science.gov (United States)

Araújo, Paulo; Machado, Luís; Cadavez, Duarte; Mónaco, Lisete; Januário, Filipa; Luís, Lisete; Bártolo, Mafalda

2017-09-29

To assess the function and quality of life in patients undergoing total hip arthroplasty distinguishing two surgical approaches (posterior / anterolateral) used by the Orthopedics department of Centro Hospitalar de Leiria. Retrospective study of 94 patients subject to unilateral hip replacement surgery, using the 'Hip Osteoarthritis Outcome Score' (HOOS LK 2.0) questionnaire, the Trendelenburg test and evaluation of muscle strength of the hip abductor muscles with dynamometer. Patients were evaluated at six months, 12 months, 18 months and 24 months after surgery. The study revealed that 97.9% patients completed the rehabilitation program. The postoperative evolution (six to 24 months) does not appear to have any differences in results when comparing both approaches. At six months the patient operated by the anterolateral approach showed worse results when compared with the posterior approach, in particular in Hip Osteoarthritis Outcome Score pain, in Hip Osteoarthritis Outcome Score symptoms and Hip Osteoarthritis Outcome Score activities of daily living. After 24 months, no differences between the two surgical approaches were found. Of the 94 patients evaluated, the Trendelenburg test was positive in 31% of patients of which 81.9% corresponds to patients operated by the anterolateral approach. Muscle strength of the abductors of the operated hip was clearly lower in the anterolateral approach at six months, 12 months, and 24 months. This study showed that, in the first six months after total hip arthroplasty, the patients operated by the posterior approach were, according to the HOOS questionnaire, less symptomatic, and presented with better quality of life and less impact on activities of daily living and in sport and leisure when compared with the patients operated by the anterolateral approach. However, these differences were matched over the 24 months. Moreover, the results of muscle strength of the abductor muscles of the hip were clearly superior in

Evaluation of the Function and Quality of Life after Total Hip Arthroplasty by Different Approaches

Directory of Open Access Journals (Sweden)

Paulo Araújo

2017-09-01

Conclusion: After 24 months post total hip arthroplasty there are no differences between the two approaches with regard to function or quality of life. However, the patients operated by the anterolateral approach had greater muscle strength deficits and higher percentage of positive Trendelenburg test.

Re-conceptualising prenatal life stressors in predicting post-partum depression: cumulative-, specific-, and domain-specific approaches to calculating risk.

Science.gov (United States)

Liu, Cindy H; Tronick, Ed

2013-09-01

Prenatal life stress predicts post-partum depression (PPD); however, studies generally examine individual stressors (a specific approach) or the summation of such exposure (a cumulative approach) and their associations with PPD. Such approaches may oversimplify prenatal life stress as a risk factor for PPD. We evaluated approaches in assessing prenatal life stress as a predictor of PPD diagnosis, including a domain-specific approach that captures cumulative life stress while accounting for stress across different life stress domains: financial, relational, and physical health. The Pregnancy Risk Assessment Monitoring System, a population-based survey, was used to analyse the association of prenatal life stressors with PPD diagnoses among 3566 New York City post-partum women. Specific stressors were not associated with PPD diagnosis after controlling for sociodemographic variables. Exposure to a greater number of stressors was associated with PPD diagnosis, even after adjusting for both sociodemographic variables and specific stressors [odds ratio (OR) = 3.1, 95% confidence interval (CI) = 1.5, 6.7]. Individuals reporting a moderate-to-high number of financial problems along with a moderate-to-high number of physical problems were at greater odds of PPD (OR = 4.2, 95% CI = 1.2, 15.3); those with a moderate-to-high number of problems in all three domains were at over fivefold increased odds of PPD (OR = 5.5, CI = 1.1, 28.5). In assessing prenatal stress, clinicians should consider the extent to which stressors occur across different life domains; this association appears stronger with PPD diagnosis than simple assessments of individual stressors, which typically overestimate risk or cumulative exposures. © 2013 John Wiley & Sons Ltd.

Degree of Biomimicry of Artificial Spider Silk Spinning Assessed by NMR Spectroscopy.

Science.gov (United States)

Otikovs, Martins; Andersson, Marlene; Jia, Qiupin; Nordling, Kerstin; Meng, Qing; Andreas, Loren B; Pintacuda, Guido; Johansson, Jan; Rising, Anna; Jaudzems, Kristaps

2017-10-02

Biomimetic spinning of artificial spider silk requires that the terminal domains of designed minispidroins undergo specific structural changes in concert with the β-sheet conversion of the repetitive region. Herein, we combine solution and solid-state NMR methods to probe domain-specific structural changes in the NT2RepCT minispidroin, which allows us to assess the degree of biomimicry of artificial silk spinning. In addition, we show that the structural effects of post-spinning procedures can be examined. By studying the impact of NT2RepCT fiber drying, we observed a reversible beta-to-alpha conversion. We think that this approach will be useful for guiding the optimization of artificial spider silk fibers. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Total artificial heart].

Science.gov (United States)

Antretter, H; Dumfarth, J; Höfer, D

2015-09-01

To date the CardioWest™ total artificial heart is the only clinically available implantable biventricular mechanical replacement for irreversible cardiac failure. This article presents the indications, contraindications, implantation procedere and postoperative treatment. In addition to a overview of the applications of the total artificial heart this article gives a brief presentation of the two patients treated in our department with the CardioWest™. The clinical course, postoperative rehabilitation, device-related complications and control mechanisms are presented. The total artificial heart is a reliable implant for treating critically ill patients with irreversible cardiogenic shock. A bridge to transplantation is feasible with excellent results.

Securing Digital Images Integrity using Artificial Neural Networks

Science.gov (United States)

Hajji, Tarik; Itahriouan, Zakaria; Ouazzani Jamil, Mohammed

2018-05-01

Digital image signature is a technique used to protect the image integrity. The application of this technique can serve several areas of imaging applied to smart cities. The objective of this work is to propose two methods to protect digital image integrity. We present a description of two approaches using artificial neural networks (ANN) to digitally sign an image. The first one is “Direct Signature without learning” and the second is “Direct Signature with learning”. This paper presents the theory of proposed approaches and an experimental study to test their effectiveness.

Gene- and cell-based bio-artificial pacemaker: what basic and translational lessons have we learned?

Science.gov (United States)

Li, R A

2012-06-01

Normal rhythms originate in the sino-atrial node, a specialized cardiac tissue consisting of only a few thousands of nodal pacemaker cells. Malfunction of pacemaker cells due to diseases or aging leads to rhythm generation disorders (for example, bradycardias and sick-sinus syndrome (SSS)), which often necessitate the implantation of electronic pacemakers. Although effective, electronic devices are associated with such shortcomings as limited battery life, permanent implantation of leads, lead dislodging, the lack of autonomic responses and so on. Here, various gene- and cell-based approaches, with a particular emphasis placed on the use of pluripotent stem cells and the hyperpolarization-activated cyclic nucleotide-gated-encoded pacemaker gene family, that have been pursued in the past decade to reconstruct bio-artificial pacemakers as alternatives will be discussed in relation to the basic biological insights and translational regenerative potential.

[Preparation of nano-nacre artificial bone].

Science.gov (United States)

Chen, Jian-ting; Tang, Yong-zhi; Zhang, Jian-gang; Wang, Jian-jun; Xiao, Ying

2008-12-01

To assess the improvements in the properties of nano-nacre artificial bone prepared on the basis of nacre/polylactide acid composite artificial bone and its potential for clinical use. The compound of nano-scale nacre powder and poly-D, L-lactide acid (PDLLA) was used to prepare the cylindrical hollow artificial bone, whose properties including raw material powder scale, pore size, porosity and biomechanical characteristics were compared with another artificial bone made of micron-scale nacre powder and PDLLA. Scanning electron microscope showed that the average particle size of the nano-nacre powder was 50.4-/+12.4 nm, and the average pore size of the artificial bone prepared using nano-nacre powder was 215.7-/+77.5 microm, as compared with the particle size of the micron-scale nacre powder of 5.0-/+3.0 microm and the pore size of the resultant artificial bone of 205.1-/+72.0 microm. The porosities of nano-nacre artificial bone and the micron-nacre artificial bone were (65.4-/+2.9)% and (53.4-/+2.2)%, respectively, and the two artificial bones had comparable compressive strength and Young's modulus, but the flexural strength of the nano-nacre artificial bone was lower than that of the micro-nacre artificial bone. The nano-nacre artificial bone allows better biodegradability and possesses appropriate pore size, porosity and biomechanical properties for use as a promising material in bone tissue engineering.

Reflections on using biographical approaches in end-of-life care: dignity therapy as example.

Science.gov (United States)

Lindqvist, Olav; Threlkeld, Guinever; Street, Annette F; Tishelman, Carol

2015-01-01

The therapeutic potential of nonpharmacologic interventions using biographical approaches at the end of life (EoL) is being increasingly recognized, but less attention is paid to processes impeding realization of this potential. In this article, Swedish and Australian researchers reflect on and problematize experiences using one biographical approach, dignity therapy (DT), in EoL care in Sweden. We use this as an example, focusing on critical examination of the process of applying DT in practice, examining frictions experienced in recruiting participants, collecting the data, and creating a biography. We discuss issues regarding agency, which became evident in the recruitment process and choices made about participation, and the power differentials manifested in the interactive process of eliciting stories and crafting them into a final product. We also raise salient questions about how research and practice with biographical approaches in EoL care might better build on and further existing knowledge to better reflect the complexities of everyday life. © The Author(s) 2014.

Superhydrophobic Natural and Artificial Surfaces—A Structural Approach

Science.gov (United States)

Avrămescu, Roxana-Elena; Ghica, Mihaela Violeta; Dinu-Pîrvu, Cristina; Prisada, Răzvan; Popa, Lăcrămioara

2018-01-01

Since ancient times humans observed animal and plants features and tried to adapt them according to their own needs. Biomimetics represents the foundation of many inventions from various fields: From transportation devices (helicopter, airplane, submarine) and flying techniques, to sports’ wear industry (swimming suits, scuba diving gear, Velcro closure system), bullet proof vests made from Kevlar etc. It is true that nature provides numerous noteworthy models (shark skin, spider web, lotus leaves), referring both to the plant and animal kingdom. This review paper summarizes a few of “nature’s interventions” in human evolution, regarding understanding of surface wettability and development of innovative special surfaces. Empirical models are described in order to reveal the science behind special wettable surfaces (superhydrophobic /superhydrophilic). Materials and methods used in order to artificially obtain special wettable surfaces are described in correlation with plants’ and animals’ unique features. Emphasis is placed on joining superhydrophobic and superhydrophilic surfaces, with important applications in cell culturing, microorganism isolation/separation and molecule screening techniques. Bio-inspired wettability is presented as a constitutive part of traditional devices/systems, intended to improve their characteristics and extend performances. PMID:29789488

Superhydrophobic Natural and Artificial Surfaces—A Structural Approach

Directory of Open Access Journals (Sweden)

Roxana-Elena Avrămescu

2018-05-01

Full Text Available Since ancient times humans observed animal and plants features and tried to adapt them according to their own needs. Biomimetics represents the foundation of many inventions from various fields: From transportation devices (helicopter, airplane, submarine and flying techniques, to sports’ wear industry (swimming suits, scuba diving gear, Velcro closure system, bullet proof vests made from Kevlar etc. It is true that nature provides numerous noteworthy models (shark skin, spider web, lotus leaves, referring both to the plant and animal kingdom. This review paper summarizes a few of “nature’s interventions” in human evolution, regarding understanding of surface wettability and development of innovative special surfaces. Empirical models are described in order to reveal the science behind special wettable surfaces (superhydrophobic /superhydrophilic. Materials and methods used in order to artificially obtain special wettable surfaces are described in correlation with plants’ and animals’ unique features. Emphasis is placed on joining superhydrophobic and superhydrophilic surfaces, with important applications in cell culturing, microorganism isolation/separation and molecule screening techniques. Bio-inspired wettability is presented as a constitutive part of traditional devices/systems, intended to improve their characteristics and extend performances.

Superhydrophobic Natural and Artificial Surfaces-A Structural Approach.

Science.gov (United States)

Avrămescu, Roxana-Elena; Ghica, Mihaela Violeta; Dinu-Pîrvu, Cristina; Prisada, Răzvan; Popa, Lăcrămioara

2018-05-22

Since ancient times humans observed animal and plants features and tried to adapt them according to their own needs. Biomimetics represents the foundation of many inventions from various fields: From transportation devices (helicopter, airplane, submarine) and flying techniques, to sports' wear industry (swimming suits, scuba diving gear, Velcro closure system), bullet proof vests made from Kevlar etc. It is true that nature provides numerous noteworthy models (shark skin, spider web, lotus leaves), referring both to the plant and animal kingdom. This review paper summarizes a few of "nature's interventions" in human evolution, regarding understanding of surface wettability and development of innovative special surfaces. Empirical models are described in order to reveal the science behind special wettable surfaces (superhydrophobic /superhydrophilic). Materials and methods used in order to artificially obtain special wettable surfaces are described in correlation with plants' and animals' unique features. Emphasis is placed on joining superhydrophobic and superhydrophilic surfaces, with important applications in cell culturing, microorganism isolation/separation and molecule screening techniques. Bio-inspired wettability is presented as a constitutive part of traditional devices/systems, intended to improve their characteristics and extend performances.

A Simple and Efficient Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Yunfeng Xu

2013-01-01

Full Text Available Artificial bee colony (ABC is a new population-based stochastic algorithm which has shown good search abilities on many optimization problems. However, the original ABC shows slow convergence speed during the search process. In order to enhance the performance of ABC, this paper proposes a new artificial bee colony (NABC algorithm, which modifies the search pattern of both employed and onlooker bees. A solution pool is constructed by storing some best solutions of the current swarm. New candidate solutions are generated by searching the neighborhood of solutions randomly chosen from the solution pool. Experiments are conducted on a set of twelve benchmark functions. Simulation results show that our approach is significantly better or at least comparable to the original ABC and seven other stochastic algorithms.

Artificial Intelligence Study (AIS).

Science.gov (United States)

1987-02-01

ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

A Model of Artificial Genotype and Norm of Reaction in a Robotic System

OpenAIRE

Durán Bosch, Ángel Juan; Pascual del Pobil Ferré, Ángel

2016-01-01

The genes of living organisms serve as large stores of information for replicating their behavior and morphology over generations. The evolutionary view of genetics that has inspired artificial systems with a Mendelian approach does not take into account the interaction between species and with the environment to generate a particular phenotype. In this paper, a genotype model is suggested to shape the relationship with the phenotype and the environment in an artificial system. A method to ob...