Handling machine breakdown for dynamic scheduling by a colony of cognitive agents in a holonic manufacturing framework

Directory of Open Access Journals (Sweden)

T. K. Jana

2015-09-01

Full Text Available There is an ever increasing need of providing quick, yet improved solution to dynamic scheduling by better responsiveness following simple coordination mechanism to better adapt to the changing environments. In this endeavor, a cognitive agent based approach is proposed to deal with machine failure. A Multi Agent based Holonic Adaptive Scheduling (MAHoAS architecture is developed to frame the schedule by explicit communication between the product holons and the resource holons in association with the integrated process planning and scheduling (IPPS holon under normal situation. In the event of breakdown of a resource, the cooperation is sought by implicit communication. Inspired by the cognitive behavior of human being, a cognitive decision making scheme is proposed that reallocates the incomplete task to another resource in the most optimized manner and tries to expedite the processing in view of machine failure. A metamorphic algorithm is developed and implemented in Oracle 9i to identify the best candidate resource for task re-allocation. Integrated approach to process planning and scheduling realized under Multi Agent System (MAS framework facilitates dynamic scheduling with improved performance under such situations. The responsiveness of the resources having cognitive capabilities helps to overcome the adverse consequences of resource failure in a better way.

An Incremental Type-2 Meta-Cognitive Extreme Learning Machine.

Science.gov (United States)

Pratama, Mahardhika; Zhang, Guangquan; Er, Meng Joo; Anavatti, Sreenatha

2017-02-01

Existing extreme learning algorithm have not taken into account four issues: 1) complexity; 2) uncertainty; 3) concept drift; and 4) high dimensionality. A novel incremental type-2 meta-cognitive extreme learning machine (ELM) called evolving type-2 ELM (eT2ELM) is proposed to cope with the four issues in this paper. The eT2ELM presents three main pillars of human meta-cognition: 1) what-to-learn; 2) how-to-learn; and 3) when-to-learn. The what-to-learn component selects important training samples for model updates by virtue of the online certainty-based active learning method, which renders eT2ELM as a semi-supervised classifier. The how-to-learn element develops a synergy between extreme learning theory and the evolving concept, whereby the hidden nodes can be generated and pruned automatically from data streams with no tuning of hidden nodes. The when-to-learn constituent makes use of the standard sample reserved strategy. A generalized interval type-2 fuzzy neural network is also put forward as a cognitive component, in which a hidden node is built upon the interval type-2 multivariate Gaussian function while exploiting a subset of Chebyshev series in the output node. The efficacy of the proposed eT2ELM is numerically validated in 12 data streams containing various concept drifts. The numerical results are confirmed by thorough statistical tests, where the eT2ELM demonstrates the most encouraging numerical results in delivering reliable prediction, while sustaining low complexity.

Les Machines pour le Big Data : Vers une Informatique Quantique et Cognitive.

OpenAIRE

Teboul , Bruno; Amri , Taoufik

2014-01-01

Cet article est une analyse prospective sur les mutations technologiques qui affecteront l’informatique et ses machines dans un avenir proche afin de répondre aux grands défis soulevés par notre société du tout digital. Nous pensons que ces mutations seront à la fois « quantique » et « cognitive ». Nous étayerons notre analyse en revenant sur ce qui fonde encore aujourd’hui nos ordinateurs, à savoir une architecture vieille de plus d’un demi-siècle, qui est responsable des espoirs déchus de l...

Cognitive Machine-Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis From Restrictive Cardiomyopathy.

Science.gov (United States)

Sengupta, Partho P; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

2016-06-01

Associating a patient's profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography data sets derived from patients with known constrictive pericarditis and restrictive cardiomyopathy. Clinical and echocardiographic data of 50 patients with constrictive pericarditis and 44 with restrictive cardiomyopathy were used for developing an associative memory classifier-based machine-learning algorithm. The speckle tracking echocardiography data were normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve of the associative memory classifier was evaluated for differentiating constrictive pericarditis from restrictive cardiomyopathy. Using only speckle tracking echocardiography variables, associative memory classifier achieved a diagnostic area under the curve of 89.2%, which improved to 96.2% with addition of 4 echocardiographic variables. In comparison, the area under the curve of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63.7%, respectively. Furthermore, the associative memory classifier demonstrated greater accuracy and shorter learning curves than other machine-learning approaches, with accuracy asymptotically approaching 90% after a training fraction of 0.3 and remaining flat at higher training fractions. This study demonstrates feasibility of a cognitive machine-learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine-learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. © 2016

A Cognitive Machine Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis from Restrictive Cardiomyopathy

Science.gov (United States)

Sengupta, Partho P.; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

2016-01-01

Background Associating a patient’s profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography (STE) data sets derived from patients with known constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Methods and Results Clinical and echocardiographic data of 50 patients with CP and 44 with RCM were used for developing an associative memory classifier (AMC) based machine learning algorithm. The STE data was normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve (AUC) of the AMC was evaluated for differentiating CP from RCM. Using only STE variables, AMC achieved a diagnostic AUC of 89·2%, which improved to 96·2% with addition of 4 echocardiographic variables. In comparison, the AUC of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63·7%, respectively. Furthermore, AMC demonstrated greater accuracy and shorter learning curves than other machine learning approaches with accuracy asymptotically approaching 90% after a training fraction of 0·3 and remaining flat at higher training fractions. Conclusions This study demonstrates feasibility of a cognitive machine learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. PMID:27266599

Prediction of outcome in internet-delivered cognitive behaviour therapy for paediatric obsessive-compulsive disorder: A machine learning approach.

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Lenhard, Fabian; Sauer, Sebastian; Andersson, Erik; Månsson, Kristoffer Nt; Mataix-Cols, David; Rück, Christian; Serlachius, Eva

2018-03-01

There are no consistent predictors of treatment outcome in paediatric obsessive-compulsive disorder (OCD). One reason for this might be the use of suboptimal statistical methodology. Machine learning is an approach to efficiently analyse complex data. Machine learning has been widely used within other fields, but has rarely been tested in the prediction of paediatric mental health treatment outcomes. To test four different machine learning methods in the prediction of treatment response in a sample of paediatric OCD patients who had received Internet-delivered cognitive behaviour therapy (ICBT). Participants were 61 adolescents (12-17 years) who enrolled in a randomized controlled trial and received ICBT. All clinical baseline variables were used to predict strictly defined treatment response status three months after ICBT. Four machine learning algorithms were implemented. For comparison, we also employed a traditional logistic regression approach. Multivariate logistic regression could not detect any significant predictors. In contrast, all four machine learning algorithms performed well in the prediction of treatment response, with 75 to 83% accuracy. The results suggest that machine learning algorithms can successfully be applied to predict paediatric OCD treatment outcome. Validation studies and studies in other disorders are warranted. Copyright © 2017 John Wiley & Sons, Ltd.

Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

Science.gov (United States)

Zhang, Jianhua; Yin, Zhong; Wang, Rubin

2017-01-01

This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

Selective visual attention to drive cognitive brain machine interfaces: from concepts to neurofeedback and rehabilitation applications

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Elaine eAstrand

2014-08-01

Full Text Available Brain Machine Interfaces (BMI using motor cortical activity to drive an external effector like a screen cursor or a robotic arm have seen enormous success and proven their great rehabilitation potential. An emerging parallel effort is now directed to BMIs controlled by endogenous cognitive activity, also called cognitive BMIs. While more challenging, this approach opens new dimensions to the rehabilitation of cognitive disorders. In the present work, we focus on BMIs driven by visuospatial attention signals and we provide a critical review of these studies in the light of the accumulated knowledge about the psychophysics, anatomy and neurophysiology of visual spatial attention. Importantly, we provide a unique comparative overview of the several studies, ranging from noninvasive to invasive human and non-human primates studies, that decode attention-related information from ongoing neuronal activity. We discuss these studies in the light of the challenges attention-driven cognitive BMIs have to face. In a second part of the review, we discuss past and current attention-based neurofeedback studies, describing both the covert effects of neurofeedback onto neuronal activity and its overt behavioral effects. Importantly, we compare neurofeedback studies based on the amplitude of cortical activity to studies based on the enhancement of cortical information content. Last, we discuss several lines of future research and applications for attention-driven cognitive BCIs, including the rehabilitation of cognitive deficits, restored communication in locked-in patients, and open-field applications for enhanced cognition in normal subjects. The core motivation of this work is the key idea that the improvement of current cognitive BMIs for therapeutic and open field applications needs to be grounded in a proper interdisciplinary understanding of the physiology of the cognitive function of interest, be it spatial attention, working memory or any other

Using a vision cognitive algorithm to schedule virtual machines

OpenAIRE

Zhao Jiaqi; Mhedheb Yousri; Tao Jie; Jrad Foued; Liu Qinghuai; Streit Achim

2014-01-01

Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the...

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

Can machine learning explain human learning?

NARCIS (Netherlands)

Vahdat, M.; Oneto, L.; Anguita, D.; Funk, M.; Rauterberg, G.W.M.

2016-01-01

Learning Analytics (LA) has a major interest in exploring and understanding the learning process of humans and, for this purpose, benefits from both Cognitive Science, which studies how humans learn, and Machine Learning, which studies how algorithms learn from data. Usually, Machine Learning is

A basic experimental study on mental workload for human cognitive work at man-machine interface

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Shimoda, Hiroshi; Wakamori, Osamu; Nagai, Yoshinori

1995-01-01

The nature and measurement methods of mental workload (MWL) for human cognitive activity at man-machine interface (MMI) were firstly discussed from the viewpoint of human information process model. Then, a model VDT experiment which simplifies the actual human-computer-interaction situation at MMI, was conducted for several subjects, where two subjects participated in experiment series and tried to solve the same cognitive task in competition. Adopted experimental parameters were (i)different kinds of cognitive task, and (ii)cycle time of information display, to see the influence on MWL characteristics from psycho-physiological viewpoint. A special processing unit for eye camera was developed and used for measuring subjects' eye movement characteristics. Concerning data analysis, total number of display presentation until problem solving (ie., total information needed for problem solving) was assumed as anchoring objective measure for MWL, and the investigations were conducted from two aspects; (i)global interpretation on MWL characteristics seen in the subjects' behavior from viewpoint of human information process model, and (ii)applicability of MWL by means of biocybernetic method. As regards to applicability of biocybernetic method, the nature of MWL characteristics was first divided into two aspects : (i)efficiency of visual information acquisition, and (ii)difficulty of inner cognitive process to solve problem, both in time pressure situation. Then, the data analysis results for eye movement characteristics were correlated to (i), while for heart rate characteristics, (ii). (author)

Hybrid-augmented intelligence:collaboration and cognition

Institute of Scientific and Technical Information of China (English)

Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

2017-01-01

The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

The Time Machine in Our Mind

Science.gov (United States)

Stocker, Kurt

2012-01-01

This article provides the first comprehensive conceptual account for the imagistic mental machinery that allows us to travel through time--for the time machine in our mind. It is argued that language reveals this imagistic machine and how we use it. Findings from a range of cognitive fields are theoretically unified and a recent proposal about…

Mina: A Sensorimotor Robotic Orthosis for Mobility Assistance

Directory of Open Access Journals (Sweden)

Anil K. Raj

2011-01-01

Full Text Available While most mobility options for persons with paraplegia or paraparesis employ wheeled solutions, significant adverse health, psychological, and social consequences result from wheelchair confinement. Modern robotic exoskeleton devices for gait assistance and rehabilitation, however, can support legged locomotion systems for those with lower extremity weakness or paralysis. The Florida Institute for Human and Machine Cognition (IHMC has developed the Mina, a prototype sensorimotor robotic orthosis for mobility assistance that provides mobility capability for paraplegic and paraparetic users. This paper describes the initial concept, design goals, and methods of this wearable overground robotic mobility device, which uses compliant actuation to power the hip and knee joints. Paralyzed users can balance and walk using the device over level terrain with the assistance of forearm crutches employing a quadrupedal gait. We have initiated sensory substitution feedback mechanisms to augment user sensory perception of his or her lower extremities. Using this sensory feedback, we hypothesize that users will ambulate with a more natural, upright gait and will be able to directly control the gait parameters and respond to perturbations. This may allow bipedal (with minimal support gait in future prototypes.

Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes

Directory of Open Access Journals (Sweden)

Utku Kose

2016-03-01

Full Text Available The definition, diagnosis and classification of Diabetes Mellitus and its complications are very important. First of all, the World Health Organization (WHO and other societies, as well as scientists have done lots of studies regarding this subject. One of the most important research interests of this subject is the computer supported decision systems for diagnosing diabetes. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics to streamline the diagnostic process in daily routine and avoid misdiagnosis. In this study, a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM and Cognitive Development Optimization Algorithm (CoDOA has been proposed. Along the training of SVM, CoDOA was used for determining the sigma parameter of the Gauss (RBF kernel function, and eventually, a classification process was made over the diabetes data set, which is related to Pima Indians. The proposed approach offers an alternative solution to the field of Artificial Intelligence-based diabetes diagnosis, and contributes to the related literature on diagnosis processes.

Visual momentum: an example of cognitive models applied to interface design

International Nuclear Information System (INIS)

Woods, D.D.

1982-01-01

The growth of computer applications has radically changed the nature of the man-machine interface. Through increased automation, the nature of the human's task has shifted from an emphasis on perceptual-motor skills to an emphasis on cognitive activities (e.g., problem solving and decision making). The result is a need to improve the cognitive coupling of person and machine. The goal of this paper is to describe how knowledge from cognitive psychology can be used to provide guidance to display system designers and to solve human performance problems in person-machine systems. The mechanism is to explore one example of a principle of man-machine interaction - visual momentum - that was developed on the basis of a general model of human front-end cognitive processing

Cognitive task analysis of nuclear power plant operators for man-machine interface design

International Nuclear Information System (INIS)

Itoh, J.I.; Yoshimura, S.; Ohtsuka, T.

1990-01-01

This paper aims to ascertain and further develop design guidelines for a man-machine interface compatible with plant operators' problem solving strategies. As the framework for this study, operator's information processing activities were modeled, based on J. Rasmussen's framework for cognitive task analysis. Two experiments were carried out. One was an experiment aimed at gaining an understanding of internal mechanisms involved in mistakes and slips which occurred in operators' responses to incidents and accidents. As a result of fifteen cases of operator performance analysis, sixty one human errors were identified. Further analysis of the errors showed that frequently occurring error mechanisms were absent-mindedness, lack of recognition of patterns in diagnosis and failed procedure formulation due to memory lapses. The other kind of experiment was carried out to identify the envelope of trajectories for the operator's search in the problem space consisting of the two dimensions of means-ends and whole-part relations while dealing with transients. Two cases of experimental sessions were conducted with the thinking-aloud method. From analyses based on verbal protocols, trajectories of operator's search were derived, covering from the whole plant level through the component level in the whole-part dimension and covering from the functional purpose level through the physical form level in the means-ends dimension. The findings obtained from these analyses serve as a basis for developing design guidelines for man-machine interfaces in control rooms of nuclear power plants

Optimizing Neuropsychological Assessments for Cognitive, Behavioral, and Functional Impairment Classification: A Machine Learning Study

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Petronilla Battista

2017-01-01

Full Text Available Subjects with Alzheimer’s disease (AD show loss of cognitive functions and change in behavioral and functional state affecting the quality of their daily life and that of their families and caregivers. A neuropsychological assessment plays a crucial role in detecting such changes from normal conditions. However, despite the existence of clinical measures that are used to classify and diagnose AD, a large amount of subjectivity continues to exist. Our aim was to assess the potential of machine learning in quantifying this process and optimizing or even reducing the amount of neuropsychological tests used to classify AD patients, also at an early stage of impairment. We investigated the role of twelve state-of-the-art neuropsychological tests in the automatic classification of subjects with none, mild, or severe impairment as measured by the clinical dementia rating (CDR. Data were obtained from the ADNI database. In the groups of measures used as features, we included measures of both cognitive domains and subdomains. Our findings show that some tests are more frequently best predictors for the automatic classification, namely, LM, ADAS-Cog, AVLT, and FAQ, with a major role of the ADAS-Cog measures of delayed and immediate memory and the FAQ measure of financial competency.

Ergonomics for enhancing detection of machine abnormalities.

Science.gov (United States)

Illankoon, Prasanna; Abeysekera, John; Singh, Sarbjeet

2016-10-17

Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined. This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections. Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics. As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

Error analysis of nuclear power plant operator cognitive behavior

International Nuclear Information System (INIS)

He Xuhong; Zhao Bingquan; Chen Yulong

2001-01-01

Nuclear power plant is a complex human-machine system integrated with many advanced machines, electron devices and automatic controls. It demands operators to have high cognitive ability and correct analysis skill. The author divides operator's cognitive process into five stages to analysis. With this cognitive model, operator's cognitive error is analysed to get the root causes and stages that error happens. The results of the analysis serve as a basis in design of control rooms and training and evaluation of operators

Neuropsychological Testing and Machine Learning Distinguish Alzheimer’s Disease from Other Causes for Cognitive Impairment

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Helmut Hildebrandt

2017-04-01

Full Text Available With promising results in recent treatment trials for Alzheimer’s disease (AD, it becomes increasingly important to distinguish AD at early stages from other causes for cognitive impairment. However, existing diagnostic methods are either invasive (lumbar punctures, PET or inaccurate Magnetic Resonance Imaging (MRI. This study investigates the potential of neuropsychological testing (NPT to specifically identify those patients with possible AD among a sample of 158 patients with Mild Cognitive Impairment (MCI or dementia for various causes. Patients were divided into an early stage and a late stage group according to their Mini Mental State Examination (MMSE score and labeled as AD or non-AD patients based on a post-mortem validated threshold of the ratio between total tau and beta amyloid in the cerebrospinal fluid (CSF; Total tau/Aβ(1–42 ratio, TB ratio. All patients completed the established Consortium to Establish a Registry for Alzheimer’s Disease—Neuropsychological Assessment Battery (CERAD-NAB test battery and two additional newly-developed neuropsychological tests (recollection and verbal comprehension that aimed at carving out specific Alzheimer-typical deficits. Based on these test results, an underlying AD (pathologically increased TB ratio was predicted with a machine learning algorithm. To this end, the algorithm was trained in each case on all patients except the one to predict (leave-one-out validation. In the total group, 82% of the patients could be correctly identified as AD or non-AD. In the early group with small general cognitive impairment, classification accuracy was increased to 89%. NPT thus seems to be capable of discriminating between AD patients and patients with cognitive impairment due to other neurodegenerative or vascular causes with a high accuracy, and may be used for screening in clinical routine and drug studies, especially in the early course of this disease.

Cognitive technologies

CERN Document Server

Mello, Alan; Figueiredo, Fabrício; Figueiredo, Rafael

2017-01-01

This book focuses on the next generation optical networks as well as mobile communication technologies. The reader will find chapters on Cognitive Optical Network, 5G Cognitive Wireless, LTE, Data Analysis and Natural Language Processing. It also presents a comprehensive view of the enhancements and requirements foreseen for Machine Type Communication. Moreover, some data analysis techniques and Brazilian Portuguese natural language processing technologies are also described here. .

Probabilistic machine learning and artificial intelligence.

Science.gov (United States)

Ghahramani, Zoubin

2015-05-28

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Probabilistic machine learning and artificial intelligence

Science.gov (United States)

Ghahramani, Zoubin

2015-05-01

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Combining human and machine processes (CHAMP)

Science.gov (United States)

Sudit, Moises; Sudit, David; Hirsch, Michael

2015-05-01

Machine Reasoning and Intelligence is usually done in a vacuum, without consultation of the ultimate decision-maker. The late consideration of the human cognitive process causes some major problems in the use of automated systems to provide reliable and actionable information that users can trust and depend to make the best Course-of-Action (COA). On the other hand, if automated systems are created exclusively based on human cognition, then there is a danger of developing systems that don't push the barrier of technology and are mainly done for the comfort level of selected subject matter experts (SMEs). Our approach to combining human and machine processes (CHAMP) is based on the notion of developing optimal strategies for where, when, how, and which human intelligence should be injected within a machine reasoning and intelligence process. This combination is based on the criteria of improving the quality of the output of the automated process while maintaining the required computational efficiency for a COA to be actuated in timely fashion. This research addresses the following problem areas: • Providing consistency within a mission: Injection of human reasoning and intelligence within the reliability and temporal needs of a mission to attain situational awareness, impact assessment, and COA development. • Supporting the incorporation of data that is uncertain, incomplete, imprecise and contradictory (UIIC): Development of mathematical models to suggest the insertion of a cognitive process within a machine reasoning and intelligent system so as to minimize UIIC concerns. • Developing systems that include humans in the loop whose performance can be analyzed and understood to provide feedback to the sensors.

Testing the ghost with the machine

International Nuclear Information System (INIS)

De Zubicaray, G.

2002-01-01

Since its introduction during the 1990s, functional magnetic resonance imaging (fMRI) has been used to investigate brain activity occurring during a bewildering variety of sensory, motor and cognitive tasks. That is, a machine is being used to test 'the ghost in the machine' - the human mind. The use of imaging techniques to investigate these issues has even led to the emergence of a new scientific field called cognitive neuroscience. Currently, there are only a few groups in Australia actively publishing fMRI studies in the international literature, and the majority of these laboratories are clustered on the east coast. My own research with fMRI has focused on areas such as language and memory, with a special interest in how we solve competitive processes in our thinking

Using machine learning to identify air pollution exposure profiles associated with early cognitive skills among U.S. children

International Nuclear Information System (INIS)

Stingone, Jeanette A.; Pandey, Om P.; Claudio, Luz; Pandey, Gaurav

2017-01-01

Data-driven machine learning methods present an opportunity to simultaneously assess the impact of multiple air pollutants on health outcomes. The goal of this study was to apply a two-stage, data-driven approach to identify associations between air pollutant exposure profiles and children's cognitive skills. Data from 6900 children enrolled in the Early Childhood Longitudinal Study, Birth Cohort, a national study of children born in 2001 and followed through kindergarten, were linked to estimated concentrations of 104 ambient air toxics in the 2002 National Air Toxics Assessment using ZIP code of residence at age 9 months. In the first-stage, 100 regression trees were learned to identify ambient air pollutant exposure profiles most closely associated with scores on a standardized mathematics test administered to children in kindergarten. In the second-stage, the exposure profiles frequently predicting lower math scores were included within linear regression models and adjusted for confounders in order to estimate the magnitude of their effect on math scores. This approach was applied to the full population, and then to the populations living in urban and highly-populated urban areas. Our first-stage results in the full population suggested children with low trichloroethylene exposure had significantly lower math scores. This association was not observed for children living in urban communities, suggesting that confounding related to urbanicity needs to be considered within the first-stage. When restricting our analysis to populations living in urban and highly-populated urban areas, high isophorone levels were found to predict lower math scores. Within adjusted regression models of children in highly-populated urban areas, the estimated effect of higher isophorone exposure on math scores was −1.19 points (95% CI −1.94, −0.44). Similar results were observed for the overall population of urban children. This data-driven, two-stage approach can be

Reverse hypothesis machine learning a practitioner's perspective

CERN Document Server

Kulkarni, Parag

2017-01-01

This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as ...

Automated assessment of cognitive health using smart home technologies.

Science.gov (United States)

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2013-01-01

The goal of this work is to develop intelligent systems to monitor the wellbeing of individuals in their home environments. This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve=0.80, g-mean=0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained.

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

Science.gov (United States)

Bini, Stefano A

2018-02-27

This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in the world of health care today. We discuss the origin of AI, progress to machine learning, and then discuss how the limits of machine learning lead data scientists to develop artificial neural networks and deep learning algorithms through biomimicry. We will place all these technologies in the context of practical clinical examples and show how AI can act as a tool to support and amplify human cognitive functions for physicians delivering care to increasingly complex patients. The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it. Copyright © 2018 Elsevier Inc. All rights reserved.

Integrating human factors and artificial intelligence in the development of human-machine cooperation

NARCIS (Netherlands)

Maanen, P.P. van; Lindenberg, J.; Neericx, M.A.

2005-01-01

Increasing machine intelligence leads to a shift from a mere interactive to a much more complex cooperative human-machine relation requiring a multidisciplinary development approach. This paper presents a generic multidisciplinary cognitive engineering method CE+ for the integration of human factors

Multilevel Cognitive Machine-Learning-Based Concept for Artificial Awareness: Application to Humanoid Robot Awareness Using Visual Saliency

Directory of Open Access Journals (Sweden)

Kurosh Madani

2012-01-01

Full Text Available As part of “intelligence,” the “awareness” is the state or ability to perceive, feel, or be mindful of events, objects, or sensory patterns: in other words, to be conscious of the surrounding environment and its interactions. Inspired by early-ages human skills developments and especially by early-ages awareness maturation, the present paper accosts the robots intelligence from a different slant directing the attention to combining both “cognitive” and “perceptual” abilities. Within such a slant, the machine (robot shrewdness is constructed on the basis of a multilevel cognitive concept attempting to handle complex artificial behaviors. The intended complex behavior is the autonomous discovering of objects by robot exploring an unknown environment: in other words, proffering the robot autonomy and awareness in and about unknown backdrop.

The Necessity of Machine Learning and Epistemology in the Development of Categorization Theories: A Case Study in Prototype-Exemplar Debate

Science.gov (United States)

Gagliardi, Francesco

In the present paper we discuss some aspects of the development of categorization theories concerning cognitive psychology and machine learning. We consider the thirty-year debate between prototype-theory and exemplar-theory in the studies of cognitive psychology regarding the categorization processes. We propose this debate is ill-posed, because it neglects some theoretical and empirical results of machine learning about the bias-variance theorem and the existence of some instance-based classifiers which can embed models subsuming both prototype and exemplar theories. Moreover this debate lies on a epistemological error of pursuing a, so called, experimentum crucis. Then we present how an interdisciplinary approach, based on synthetic method for cognitive modelling, can be useful to progress both the fields of cognitive psychology and machine learning.

Resveratrol inhibits the intracellular calcium increase and angiotensin/endothelin system activation induced by soluble uric acid in mesangial cells

Energy Technology Data Exchange (ETDEWEB)

Albertoni, G.; Schor, N. [Divisão de Nefrologia, Departamento de Medicina, Universidade Federal de São Paulo, São Paulo, SP (Brazil)

2014-10-24

Resveratrol (Resv) is natural polyphenol found in grapes. This study evaluated the protective effect of Resv against the effects of uric acid (UA) in immortalized human mesangial cells (ihMCs). ihMCs were preincubated with Resv (12.5 µM) for 1 h and treated with UA (10 mg/dL) for 6 or 12 h. The intracellular calcium concentration [Ca{sup 2+}]i was quantified by fluorescence using flow cytometry. Angiotensinogen (AGT) and pre-pro endothelin-1 (ppET-1) mRNA were assayed by quantitative real-time RT-PCR. Angiotensin II (AII) and endothelin-1 (ET-1) were assayed by ELISA. UA significantly increased [Ca{sup 2+}]i. Pre-incubation with Resv significantly reduced the change in [Ca{sup 2+}]i induced by UA. Incubation with UA for 6 or 12 h also increased AGT mRNA expression and AII protein synthesis. Resv blunted these increases in AGT mRNA expression and AII protein. Incubation with UA in the ihMCs increased ppET-1 expression and ET-1 protein synthesis at 6 and 12 h. When ihMCs were pre-incubated with Resv, UA had a significantly diminished effect on ppET-1 mRNA expression and ET-1 protein synthesis at 6 and 12 h, respectively. Our results suggested that UA triggers reactions including AII and ET-1 production in mesangial cells. The renin-angiotensin system may contribute to the pathogenesis of renal function and chronic kidney disease. Resv can minimize the impact of UA on AII, ET-1 and the increase of [Ca{sup 2+}]i in mesangial cells, suggesting that, at least in part, Resv can prevent the effects of soluble UA in mesangial cells.

Cognitive logical systems with artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Liss, E

1983-09-01

The simulation of cognitive processes for the purpose of the technical development of learning systems with intelligent behavior is a basic object of the young interdisciplinary cognition science which is based upon artificial intelligence, cognitive psychology, computer science, linguistics and pedagogics. Cognitive systems may be described as knowledge-based logical systems. Based on structural and functional principles of intelligent automata and elementary information processing systems with structural learning capability the future process, machine and robot controls, advising units and fifth generation computers may be developed.

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

Science.gov (United States)

Kanchanatawan, Buranee; Sriswasdi, Sira; Thika, Supaksorn; Stoyanov, Drozdstoy; Sirivichayakul, Sunee; Carvalho, André F; Geffard, Michel; Maes, Michael

2018-05-23

Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate classifications should be based on supervised and unsupervised learning rather than on consensus criteria. This study used machine learning as means to provide a more accurate classification of patients with stable phase schizophrenia. We found that using negative symptoms as discriminatory variables, schizophrenia patients may be divided into two distinct classes modelled by (A) impairments in IgA/IgM responses to noxious and generally more protective tryptophan catabolites, (B) impairments in episodic and semantic memory, paired associative learning and false memory creation, and (C) psychotic, excitation, hostility, mannerism, negative, and affective symptoms. The first cluster shows increased negative, psychotic, excitation, hostility, mannerism, depression and anxiety symptoms, and more neuroimmune and cognitive disorders and is therefore called "major neurocognitive psychosis" (MNP). The second cluster, called "simple neurocognitive psychosis" (SNP) is discriminated from normal controls by the same features although the impairments are less well developed than in MNP. The latter is additionally externally validated by lowered quality of life, body mass (reflecting a leptosome body type), and education (reflecting lower cognitive reserve). Previous distinctions including "type 1" (positive)/"type 2" (negative) and DSM-IV-TR (eg, paranoid) schizophrenia could not be validated using machine learning techniques. Previous names of the illness, including schizophrenia, are not very adequate because they do not describe the features of the illness, namely, interrelated neuroimmune, cognitive, and clinical features. Stable-phase schizophrenia consists of 2 relevant qualitatively distinct categories or nosological entities with SNP

Quantum information, cognition, and music

Science.gov (United States)

Dalla Chiara, Maria L.; Giuntini, Roberto; Leporini, Roberto; Negri, Eleonora; Sergioli, Giuseppe

2015-01-01

Parallelism represents an essential aspect of human mind/brain activities. One can recognize some common features between psychological parallelism and the characteristic parallel structures that arise in quantum theory and in quantum computation. The article is devoted to a discussion of the following questions: a comparison between classical probabilistic Turing machines and quantum Turing machines.possible applications of the quantum computational semantics to cognitive problems.parallelism in music. PMID:26539139

Predictors of return rate discrimination in slot machine play.

Science.gov (United States)

Coates, Ewan; Blaszczynski, Alex

2014-09-01

The purpose of this study was to investigate the extent to which accurate estimates of payback percentages and volatility combined with prior learning, enabled players to successfully discriminate between multi-line/multi-credit slot machines that provided differing rates of reinforcement. The aim was to determine if the capacity to discriminate structural characteristics of gaming machines influenced player choices in selecting 'favourite' slot machines. Slot machine gambling history, gambling beliefs and knowledge, impulsivity, illusions of control, and problem solving style were assessed in a sample of 48 first year undergraduate psychology students. Participants were subsequently exposed to a choice paradigm where they could freely select to play either of two concurrently presented PC-simulated slot machines programmed to randomly differ in expected player return rates (payback percentage) and win frequency (volatility). Results suggest that prior learning and cognitions (particularly gambler's fallacy) but not payback, were major contributors to the ability of a player to discriminate volatility between slot machines. Participants displayed a general tendency to discriminate payback, but counter-intuitively placed more bets on the slot machine with lower payback percentage rates.

Quantum information, cognition and music.

Directory of Open Access Journals (Sweden)

Maria Luisa eDalla Chiara

2015-10-01

Full Text Available Parallelism represents an essential aspect of human mind/brain activities. One can recognize some common features between psychological parallelism and the characteristic parallel structures that arise in quantum theory and in quantum computation. The article is devoted to a discussion of the following questions:1 a comparison between classical probabilistic Turing machines and quantum Turing machines;2 possible applications of the quantum computational semantics to cognitive problems;3 parallelism in music.

Developing Preservice Teachers' Understanding of Function Using a Vending Machine Metaphor Applet

Science.gov (United States)

McCulloch, Allison; Lovett, Jennifer; Edgington, Cyndi

2017-01-01

The purpose of this study is to examine the use of a Vending Machine applet as a cognitive root for the development of preservice teachers understanding of function. The applet was designed to purposefully problematize common misconceptions associated with the algebraic nature of typical function machines. Findings indicated affordances and…

Extended Carbon Cognition as a Machine

DEFF Research Database (Denmark)

Lippert, Ingmar

2011-01-01

. Grounded in ethnographic fieldwork at a leading multinational in the financial services sector over a period of more than 12 months, I focus on everyday work practices as taking place in a capitalist context. It is through practical work that the presences of carbon emissions are imagined and brought....... As a result of this analysis carbon accounting emerges as enabled through an extended system of cognition. The paper concludes by tentatively suggesting a view on this machinery as co-constituting a wider -- to borrow Guattari's term -- Universe: A Universe of references to carbon. Following these relations...

An intelligent man-machine system for future nuclear power plants

International Nuclear Information System (INIS)

Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

1994-01-01

The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

Understanding and modelling man-machine interaction

International Nuclear Information System (INIS)

Cacciabue, P.C.

1996-01-01

This paper gives an overview of the current state of the art in man-machine system interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to the design and analysis of man-machine interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans an their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (orig.)

Understanding and modelling Man-Machine Interaction

International Nuclear Information System (INIS)

Cacciabue, P.C.

1991-01-01

This paper gives an overview of the current state of the art in man machine systems interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to design and analysis of Man-Machine Interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans and their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (author)

An intelligent human-machine system based on an ecological interface design concept

International Nuclear Information System (INIS)

Naito, N.

1995-01-01

It seems both necessary and promising to develop an intelligent human-machine system, considering the objective of the human-machine system and the recent advance in cognitive engineering and artificial intelligence together with the ever-increasing importance of human factor issues in nuclear power plant operation and maintenance. It should support human operators in their knowledge-based behaviour and allow them to cope with unanticipated abnormal events, including recovery from erroneous human actions. A top-down design approach has been adopted based on cognitive work analysis, and (1) an ecological interface, (2) a cognitive model-based advisor and (3) a robust automatic sequence controller have been established. These functions have been integrated into an experimental control room. A validation test was carried out by the participation of experienced operators and engineers. The results showed the usefulness of this system in supporting the operator's supervisory plant control tasks. ((orig.))

Cognitive Comparative Advantage and the Organization of Work: Lessons from Herbert Simon's Vision of the Future

OpenAIRE

Richard N. Langlois

2002-01-01

In a marvelous but somewhat neglected paper, 'The Corporation: Will It Be Managed by Machines?' Herbert Simon articulated from the perspective of 1960 his vision of what we now call the New Economy the machine-aided system of production and management of the late twentieth century. Simon's analysis sprang from what I term the principle of cognitive comparative advantage: one has to understand the quite different cognitive structures of humans and machines (including computers) in order to exp...

Man-machine supervision; Supervision homme-machine

Energy Technology Data Exchange (ETDEWEB)

Montmain, J. [CEA Valrho, Dir. de l' Energie Nucleaire (DEN), 30 - Marcoule (France)

2005-05-01

Today's complexity of systems where man is involved has led to the development of more and more sophisticated information processing systems where decision making has become more and more difficult. The operator task has moved from operation to supervision and the production tool has become indissociable from its numerical instrumentation and control system. The integration of more and more numerous and sophisticated control indicators in the control room does not necessary fulfill the expectations of the operation team. It is preferable to develop cooperative information systems which are real situation understanding aids. The stake is not the automation of operators' cognitive tasks but the supply of a reasoning help. One of the challenges of interactive information systems is the selection, organisation and dynamical display of information. The efficiency of the whole man-machine system depends on the communication interface efficiency. This article presents the principles and specificities of man-machine supervision systems: 1 - principle: operator's role in control room, operator and automation, monitoring and diagnosis, characteristics of useful models for supervision; 2 - qualitative reasoning: origin, trends, evolutions; 3 - causal reasoning: causality, causal graph representation, causal and diagnostic graph; 4 - multi-points of view reasoning: multi flow modeling method, Sagace method; 5 - approximate reasoning: the symbolic numerical interface, the multi-criteria decision; 6 - example of application: supervision in a spent-fuel reprocessing facility. (J.S.)

Cognitive environment simulation: An artificial intelligence system for human performance assessment: Cognitive reliability analysis technique: [Technical report, May 1986-June 1987

International Nuclear Information System (INIS)

Woods, D.D.; Roth, E.M.

1987-11-01

This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 34 refs., 7 figs., 1 tab

The East, the West and the universal machine.

Science.gov (United States)

Marchal, Bruno

2017-12-01

After reviewing the basic of theology of Universal Numbers/Machines, as detailed in Marchal (2007), I illustrate how that body of thought might be used to shed some light upon the apparent dichotomy in Eastern/Western spirituality. This paper relies entirely on my previous interdisciplinary work in mathematical logic, computer science and machine's theology, where "theology" is used here in the sense of Plato: it is the truth, or the "truth-theory" (in the sense of logicians) about a machine that the machine can either deduce from some of its primitive beliefs, or can be intuited in some sense that eventually is made clear through the modal logic of machine self-reference. Such a theology appears to be testable, because it has been shown that physics has to be necessarily retrieved from it when we assume the mechanist hypothesis in the cognitive sciences, and this in a unique precise (introspective) way, so that we only need to compare the physics of the introspective machine with the physics inferred from the human observation; and up to now, it is the only theory known to fit both the existence of personal "consciousness" (undoubtable yet unjustifiable truth) and quanta and quantum relationships (Marchal, 1998; Marchal, 2004; Marchal, 2013; Marchal, 2015). Copyright © 2017 Elsevier Ltd. All rights reserved.

Mind, Machine, and Creativity: An Artist's Perspective.

Science.gov (United States)

Sundararajan, Louise

2014-06-01

Harold Cohen is a renowned painter who has developed a computer program, AARON, to create art. While AARON has been hailed as one of the most creative AI programs, Cohen consistently rejects the claims of machine creativity. Questioning the possibility for AI to model human creativity, Cohen suggests in so many words that the human mind takes a different route to creativity, a route that privileges the relational, rather than the computational, dimension of cognition. This unique perspective on the tangled web of mind, machine, and creativity is explored by an application of three relational models of the mind to an analysis of Cohen's talks and writings, which are available on his website: www.aaronshome.com.

Development of realtime cognitive state estimator

International Nuclear Information System (INIS)

Takahashi, Makoto; Kitamura, Masashi; Yoshikaea, Hidekazu

2004-01-01

The realtime cognitive state estimator based on the set of physiological measures has been developed in order to provide valuable information on the human behavior during the interaction through the Man-Machine Interface. The artificial neural network has been adopted to categorize the cognitive states by using the qualitative physiological data pattern as the inputs. The laboratory experiments, in which the subjects' cognitive states were intentionally controlled by the task presented, were performed to obtain training data sets for the neural network. The developed system has been shown to be capable of estimating cognitive state with higher accuracy and realtime estimation capability has also been confirmed through the data processing experiments. (author)

Cognitive distortions and gambling near-misses in Internet Gaming Disorder: A preliminary study.

Directory of Open Access Journals (Sweden)

Yin Wu

Full Text Available Increased cognitive distortions (i.e. biased processing of chance, probability and skill are a key psychopathological process in disordered gambling. The present study investigated state and trait aspects of cognitive distortions in 22 individuals with Internet Gaming Disorder (IGD and 22 healthy controls. Participants completed the Gambling Related Cognitions Scale as a trait measure of cognitive distortions, and played a slot machine task delivering wins, near-misses and full-misses. Ratings of pleasure ("liking" and motivation to play ("wanting" were taken following the different outcomes, and gambling persistence was measured after a mandatory phase. IGD was associated with elevated trait cognitive distortions, in particular skill-oriented cognitions. On the slot machine task, the IGD group showed increased "wanting" ratings compared with control participants, while the two groups did not differ regarding their "liking" of the game. The IGD group displayed increased persistence on the slot machine task. Near-miss outcomes did not elicit stronger motivation to play compared to full-miss outcomes overall, and there was no group difference on this measure. However, a near-miss position effect was observed, such that near-misses stopping before the payline were rated as more motivating than near-misses that stopped after the payline, and this differentiation was attenuated in the IGD group, suggesting possible counterfactual thinking deficits in this group. These data provide preliminary evidence for increased incentive motivation and cognitive distortions in IGD, at least in the context of a chance-based gambling environment.

Cognitive distortions and gambling near-misses in Internet Gaming Disorder: A preliminary study.

Science.gov (United States)

Wu, Yin; Sescousse, Guillaume; Yu, Hongbo; Clark, Luke; Li, Hong

2018-01-01

Increased cognitive distortions (i.e. biased processing of chance, probability and skill) are a key psychopathological process in disordered gambling. The present study investigated state and trait aspects of cognitive distortions in 22 individuals with Internet Gaming Disorder (IGD) and 22 healthy controls. Participants completed the Gambling Related Cognitions Scale as a trait measure of cognitive distortions, and played a slot machine task delivering wins, near-misses and full-misses. Ratings of pleasure ("liking") and motivation to play ("wanting") were taken following the different outcomes, and gambling persistence was measured after a mandatory phase. IGD was associated with elevated trait cognitive distortions, in particular skill-oriented cognitions. On the slot machine task, the IGD group showed increased "wanting" ratings compared with control participants, while the two groups did not differ regarding their "liking" of the game. The IGD group displayed increased persistence on the slot machine task. Near-miss outcomes did not elicit stronger motivation to play compared to full-miss outcomes overall, and there was no group difference on this measure. However, a near-miss position effect was observed, such that near-misses stopping before the payline were rated as more motivating than near-misses that stopped after the payline, and this differentiation was attenuated in the IGD group, suggesting possible counterfactual thinking deficits in this group. These data provide preliminary evidence for increased incentive motivation and cognitive distortions in IGD, at least in the context of a chance-based gambling environment.

Challenges to Cognitive Systems Engineering:Understanding Qualitative Aspects of Control Actions

DEFF Research Database (Denmark)

Lind, Morten

2009-01-01

The paper discusses the future role of Cognitive Systems Engineering (CSE) in contributing to integrated design of process, automation and human machine systems. Existing concepts and methods of Cognitive Systems Engineering do not integrate well with control theory and industrial automation tools...

Enabling Technologies for Cognitive Optical Networks

DEFF Research Database (Denmark)

Borkowski, Robert

Cognition is a new paradigm for optical networking, in which the network has capabilities to observe, plan, decide, and act autonomously in order to optimize the end-to-end performance and minimize the need for human supervision. This PhD thesis expands the state of the art on cognitive optical......, and machine learning algorithms that make cognition possible. Secondly, advanced optical performance monitoring (OPM) capabilities performed via digital signal processing (DSP) that provide CONs with necessary feedback information allowing for autonomous network optimization. The research results presented...... in this thesis were carried out in the framework of the EU project Cognitive Heterogeneous Reconfigurable Optical Network (CHRON), whose aim was to develop an architecture and implement a testbed of a cognitive network able to self-configure and self-optimize to efficiently use available resources. In order...

Humanoid Cognitive Robots That Learn by Imitating: Implications for Consciousness Studies

Directory of Open Access Journals (Sweden)

James A. Reggia

2018-01-01

Full Text Available While the concept of a conscious machine is intriguing, producing such a machine remains controversial and challenging. Here, we describe how our work on creating a humanoid cognitive robot that learns to perform tasks via imitation learning relates to this issue. Our discussion is divided into three parts. First, we summarize our previous framework for advancing the understanding of the nature of phenomenal consciousness. This framework is based on identifying computational correlates of consciousness. Second, we describe a cognitive robotic system that we recently developed that learns to perform tasks by imitating human-provided demonstrations. This humanoid robot uses cause–effect reasoning to infer a demonstrator’s intentions in performing a task, rather than just imitating the observed actions verbatim. In particular, its cognitive components center on top-down control of a working memory that retains the explanatory interpretations that the robot constructs during learning. Finally, we describe our ongoing work that is focused on converting our robot’s imitation learning cognitive system into purely neurocomputational form, including both its low-level cognitive neuromotor components, its use of working memory, and its causal reasoning mechanisms. Based on our initial results, we argue that the top-down cognitive control of working memory, and in particular its gating mechanisms, is an important potential computational correlate of consciousness in humanoid robots. We conclude that developing high-level neurocognitive control systems for cognitive robots and using them to search for computational correlates of consciousness provides an important approach to advancing our understanding of consciousness, and that it provides a credible and achievable route to ultimately developing a phenomenally conscious machine.

Cognitive Architectures and Autonomy: A Comparative Review

Science.gov (United States)

Thórisson, Kristinn; Helgasson, Helgi

2012-05-01

One of the original goals of artificial intelligence (AI) research was to create machines with very general cognitive capabilities and a relatively high level of autonomy. It has taken the field longer than many had expected to achieve even a fraction of this goal; the community has focused on building specific, targeted cognitive processes in isolation, and as of yet no system exists that integrates a broad range of capabilities or presents a general solution to autonomous acquisition of a large set of skills. Among the reasons for this are the highly limited machine learning and adaptation techniques available, and the inherent complexity of integrating numerous cognitive and learning capabilities in a coherent architecture. In this paper we review selected systems and architectures built expressly to address integrated skills. We highlight principles and features of these systems that seem promising for creating generally intelligent systems with some level of autonomy, and discuss them in the context of the development of future cognitive architectures. Autonomy is a key property for any system to be considered generally intelligent, in our view; we use this concept as an organizing principle for comparing the reviewed systems. Features that remain largely unaddressed in present research, but seem nevertheless necessary for such efforts to succeed, are also discussed.

An investigative study towards constructing anthropocentric Man-Machine System design evaluation methodology

International Nuclear Information System (INIS)

Yoshikawa, H.; Gofuku, A.; Itoh, T.; Sasaki, K.

1992-01-01

A methodological investigation has been conducted for evaluating the reliability of man-machine interaction in the total Man-Machine System (MMS) from the view-point of safety maintenance for emergent situations of nuclear power plant. Basic considerations in our study are: (i) what are the MMS design data to be evaluated, (ii) how are those MMS design data should be treated, and (iii) how the introduction effects of various operator support tools can be evaluated. The methods of both qualitative and quantitative MMS design evaluation are summarized in this paper, with the system architecture based on man-machine interaction simulation and the related cognitive human error factor analysis. (author)

Evaluating Effects of Heat Stress on Cognitive Function among Workers in a Hot Industry

OpenAIRE

Adel Mazloumi; Farideh Golbabaei; Somayeh Mahmood Khani; Zeinab Kazemi; Mostafa Hosseini; Marzieh Abbasinia; Somayeh Farhang Dehghan

2014-01-01

Background:Heat stress, as one of the most common occupational health problems, can impair operators' cognitive processes. The aim of this study was to evaluate the impact of thermal stress on cognitive function among workers in a hot industry. Methods: In this cross-sectional study conducted in Malibel Saipa Company in 2013, workers were assigned into two groups: one group were exposed to heat stress (n=35), working in casting unit and the other group working in machin-ing unit (n=35) wit...

Teaching the Teacher: Tutoring SimStudent Leads to More Effective Cognitive Tutor Authoring

Science.gov (United States)

Matsuda, Noboru; Cohen, William W.; Koedinger, Kenneth R.

2015-01-01

SimStudent is a machine-learning agent initially developed to help novice authors to create cognitive tutors without heavy programming. Integrated into an existing suite of software tools called Cognitive Tutor Authoring Tools (CTAT), SimStudent helps authors to create an expert model for a cognitive tutor by tutoring SimStudent on how to solve…

Building machines that learn and think like people.

Science.gov (United States)

Lake, Brenden M; Ullman, Tomer D; Tenenbaum, Joshua B; Gershman, Samuel J

2017-01-01

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.

Analysis of machining and machine tools

CERN Document Server

Liang, Steven Y

2016-01-01

This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

Directory of Open Access Journals (Sweden)

Tiziana Segreto

2017-12-01

Full Text Available Nickel-Titanium (Ni-Ti alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT. The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

Science.gov (United States)

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Effects of digital human-machine interface characteristics on human error in nuclear power plants

International Nuclear Information System (INIS)

Li Pengcheng; Zhang Li; Dai Licao; Huang Weigang

2011-01-01

In order to identify the effects of digital human-machine interface characteristics on human error in nuclear power plants, the new characteristics of digital human-machine interface are identified by comparing with the traditional analog control systems in the aspects of the information display, user interface interaction and management, control systems, alarm systems and procedures system, and the negative effects of digital human-machine interface characteristics on human error are identified by field research and interviewing with operators such as increased cognitive load and workload, mode confusion, loss of situation awareness. As to the adverse effects related above, the corresponding prevention and control measures of human errors are provided to support the prevention and minimization of human errors and the optimization of human-machine interface design. (authors)

Thinking computers and virtual persons essays on the intentionality of machines

CERN Document Server

Dietrich, Eric

1994-01-01

Thinking Computers and Virtual Persons: Essays on the Intentionality of Machines explains how computations are meaningful and how computers can be cognitive agents like humans. This book focuses on the concept that cognition is computation.Organized into four parts encompassing 13 chapters, this book begins with an overview of the analogy between intentionality and phlogiston, the 17th-century principle of burning. This text then examines the objection to computationalism that it cannot prevent arbitrary attributions of content to the various data structures and representations involved in a c

A Cognitive Computing Approach for Classification of Complaints in the Insurance Industry

Science.gov (United States)

Forster, J.; Entrup, B.

2017-10-01

In this paper we present and evaluate a cognitive computing approach for classification of dissatisfaction and four complaint specific complaint classes in correspondence documents between insurance clients and an insurance company. A cognitive computing approach includes the combination classical natural language processing methods, machine learning algorithms and the evaluation of hypothesis. The approach combines a MaxEnt machine learning algorithm with language modelling, tf-idf and sentiment analytics to create a multi-label text classification model. The result is trained and tested with a set of 2500 original insurance communication documents written in German, which have been manually annotated by the partnering insurance company. With a F1-Score of 0.9, a reliable text classification component has been implemented and evaluated. A final outlook towards a cognitive computing insurance assistant is given in the end.

Machine learning in cardiovascular medicine: are we there yet?

Science.gov (United States)

Shameer, Khader; Johnson, Kipp W; Glicksberg, Benjamin S; Dudley, Joel T; Sengupta, Partho P

2018-01-19

Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encompassing several terms like machine learning, cognitive learning, deep learning and reinforcement learning-based methods that can be used to integrate and interpret complex biomedical and healthcare data in scenarios where traditional statistical methods may not be able to perform. In this review article, we discuss the basics of machine learning algorithms and what potential data sources exist; evaluate the need for machine learning; and examine the potential limitations and challenges of implementing machine in the context of cardiovascular medicine. The most promising avenues for AI in medicine are the development of automated risk prediction algorithms which can be used to guide clinical care; use of unsupervised learning techniques to more precisely phenotype complex disease; and the implementation of reinforcement learning algorithms to intelligently augment healthcare providers. The utility of a machine learning-based predictive model will depend on factors including data heterogeneity, data depth, data breadth, nature of modelling task, choice of machine learning and feature selection algorithms, and orthogonal evidence. A critical understanding of the strength and limitations of various methods and tasks amenable to machine learning is vital. By leveraging the growing corpus of big data in medicine, we detail pathways by which machine learning may facilitate optimal development of patient-specific models for improving diagnoses, intervention and outcome in cardiovascular medicine. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

Directory of Open Access Journals (Sweden)

Cai Wingfield

2017-09-01

Full Text Available There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG, generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.

Machine rates for selected forest harvesting machines

Science.gov (United States)

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

Adaptive multi-objective Optimization scheme for cognitive radio resource management

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2014-01-01

configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance

An analysis of switching and non-switching slot machine player behaviour.

Science.gov (United States)

Coates, Ewan; Blaszczynski, Alex

2013-12-01

Learning theory predicts that, given the repeated choice to bet between two concurrently available slot machines, gamblers will learn to bet more money on the machine with higher expected return (payback percentage) or higher win probability per spin (volatility). The purpose of this study was to investigate whether this occurs when the two machines vary orthogonally on payback percentage and volatility. The sample comprised 52 first year psychology students (mean age = 20.3 years, 20 females, 32 males) who had played a gaming machine at least once in the previous 12 months. Participants were administered a battery of questionnaires designed to assess level of knowledge on the characteristics and operation of poker machines, frequency of poker machine play in the past 12 months, personality traits of impulsivity and capacity for cognitive reflection, and gambling beliefs. For the experimental task, participants were instructed to play on two PC-simulated electronic gaming machines (EGMs or slot machines) that differed on payback percentage and volatility, with the option of freely switching between EGMs after a practice phase. Results indicated that participants were able to easily discriminate between machines and manifested a preference to play machines offering higher payback or volatility. These findings diverged from previous findings of no preference for play on higher payback/volatility machines, potentially due to of the current study's absence of the option to make multi-line and multi-credit bets. It was concluded that return rate parameters like payback percentage and volatility strongly influenced slot machine preference in the absence of betting options like multi-line bets, though more research is needed to determine the effects of such betting options on player distribution of money between multiple EGMs.

Development of an evaluation technique for human-machine interface

Energy Technology Data Exchange (ETDEWEB)

Min, Dae Hwan; Koo, Sang Hui; Ahn, Won Yeong; Ryu, Yeong Shin [Korea Univ., Seoul (Korea, Republic of)

1997-07-15

The purpose of this study is two-fold : firstly to establish an evaluation technique for HMI(Human Machine Interface) in NPPs(Nuclear Power Plants) and secondly to develop an architecture of a support system which can be used for the evaluation of HMI. In order to establish an evaluation technique, this study conducted literature review on basic theories of cognitive science studies and summarized the cognitive characteristics of humans. This study also surveyed evaluation techniques of HMI in general, and reviewed studies on the evaluation of HMI in NPPs. On the basis of this survey, the study established a procedure for the evaluation of HMI in NPPs in Korea and laid a foundation for empirical verification.

Development of an evaluation technique for human-machine interface

International Nuclear Information System (INIS)

Min, Dae Hwan; Koo, Sang Hui; Ahn, Won Yeong; Ryu, Yeong Shin

1997-07-01

The purpose of this study is two-fold : firstly to establish an evaluation technique for HMI(Human Machine Interface) in NPPs(Nuclear Power Plants) and secondly to develop an architecture of a support system which can be used for the evaluation of HMI. In order to establish an evaluation technique, this study conducted literature review on basic theories of cognitive science studies and summarized the cognitive characteristics of humans. This study also surveyed evaluation techniques of HMI in general, and reviewed studies on the evaluation of HMI in NPPs. On the basis of this survey, the study established a procedure for the evaluation of HMI in NPPs in Korea and laid a foundation for empirical verification

Validating cognitive support for operators of complex human-machine systems

International Nuclear Information System (INIS)

O'Hara, J.; Wachtel, J.

1995-01-01

Modem nuclear power plants (NPPs) are complex systems whose performance is the result of an intricate interaction of human and system control. A complex system may be defined as one which supports a dynamic process involving a large number of elements that interact in many different ways. Safety is addressed through defense-in-depth design and preplanning; i.e., designers consider the types of failures that are most likely to occur and those of high consequence, and design their solutions in advance. However, complex interactions and their failure modes cannot always be anticipated by the designer and may be unfamiliar to plant personnel. These situations may pose cognitive demands on plant personnel, both individually and as a crew. Other factors may contribute to the cognitive challenges of NPP operation as well, including hierarchal processes, dynamic pace, system redundancy and reliability, and conflicting objectives. These factors are discussed in this paper

JACOS: AI-based simulation system for man-machine system behavior in NPP

International Nuclear Information System (INIS)

Yoshida, Kazuo; Yokobayashi, Masao; Tanabe, Fumiya; Komiya, Akitoshi

2001-08-01

A prototype of a computer simulation system named JACOS (JAERI COgnitive Simulation system) has been developed at JAERI (Japan Atomic Energy Research Institute) to simulate the man-machine system behavior in which both the cognitive behavior of a human operator and the plant behavior affect each other. The objectives of this system development is to provide man-machine system analysts with detailed information on the cognitive process of an operator and the plant behavior affected by operator's actions in accidental situations of a nuclear power plant. The simulation system consists of an operator model and a plant model which are coupled dynamically. The operator model simulates an operator's cognitive behavior in accidental situations based on the decision ladder model of Rasmussen, and is implemented using the AI-techniques of the distributed cooperative inference method with the so-called blackboard architecture. Rule-based behavior is simulated using knowledge representation with If-Then type of rules. Knowledge-based behavior is simulated using knowledge representation with MFM (Multilevel Flow Modeling) and qualitative reasoning method. Cognitive characteristics of attentional narrowing, limitation of short-term memory, and knowledge recalling from long-term memory are also taken into account. The plant model of a 3-loop PWR is also developed using a best estimate thermal-hydraulic analysis code RELAP5/MOD2. This report is prepared as User's Manual for JACOS. The first chapter of this report describes both operator and plant models in detail. The second chapter includes instructive descriptions for program installation, building of a knowledge base for operator model, execution of simulation and analysis of simulation results. The examples of simulation with JACOS are shown in the third chapter. (author)

[A new machinability test machine and the machinability of composite resins for core built-up].

Science.gov (United States)

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

Man-machine supervision

International Nuclear Information System (INIS)

Montmain, J.

2005-01-01

Today's complexity of systems where man is involved has led to the development of more and more sophisticated information processing systems where decision making has become more and more difficult. The operator task has moved from operation to supervision and the production tool has become indissociable from its numerical instrumentation and control system. The integration of more and more numerous and sophisticated control indicators in the control room does not necessary fulfill the expectations of the operation team. It is preferable to develop cooperative information systems which are real situation understanding aids. The stake is not the automation of operators' cognitive tasks but the supply of a reasoning help. One of the challenges of interactive information systems is the selection, organisation and dynamical display of information. The efficiency of the whole man-machine system depends on the communication interface efficiency. This article presents the principles and specificities of man-machine supervision systems: 1 - principle: operator's role in control room, operator and automation, monitoring and diagnosis, characteristics of useful models for supervision; 2 - qualitative reasoning: origin, trends, evolutions; 3 - causal reasoning: causality, causal graph representation, causal and diagnostic graph; 4 - multi-points of view reasoning: multi flow modeling method, Sagace method; 5 - approximate reasoning: the symbolic numerical interface, the multi-criteria decision; 6 - example of application: supervision in a spent-fuel reprocessing facility. (J.S.)

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.

Diagnosis of Dementia by Machine learning methods in Epidemiological studies: a pilot exploratory study from south India.

Science.gov (United States)

Bhagyashree, Sheshadri Iyengar Raghavan; Nagaraj, Kiran; Prince, Martin; Fall, Caroline H D; Krishna, Murali

2018-01-01

There are limited data on the use of artificial intelligence methods for the diagnosis of dementia in epidemiological studies in low- and middle-income country (LMIC) settings. A culture and education fair battery of cognitive tests was developed and validated for population based studies in low- and middle-income countries including India by the 10/66 Dementia Research Group. We explored the machine learning methods based on the 10/66 battery of cognitive tests for the diagnosis of dementia based in a birth cohort study in South India. The data sets for 466 men and women for this study were obtained from the on-going Mysore Studies of Natal effect of Health and Ageing (MYNAH), in south India. The data sets included: demographics, performance on the 10/66 cognitive function tests, the 10/66 diagnosis of mental disorders and population based normative data for the 10/66 battery of cognitive function tests. Diagnosis of dementia from the rule based approach was compared against the 10/66 diagnosis of dementia. We have applied machine learning techniques to identify minimal number of the 10/66 cognitive function tests required for diagnosing dementia and derived an algorithm to improve the accuracy of dementia diagnosis. Of 466 subjects, 27 had 10/66 diagnosis of dementia, 19 of whom were correctly identified as having dementia by Jrip classification with 100% accuracy. This pilot exploratory study indicates that machine learning methods can help identify community dwelling older adults with 10/66 criterion diagnosis of dementia with good accuracy in a LMIC setting such as India. This should reduce the duration of the diagnostic assessment and make the process easier and quicker for clinicians, patients and will be useful for 'case' ascertainment in population based epidemiological studies.

The impact of CmapTools utilization towards students' conceptual change on optics topic

Science.gov (United States)

Rofiuddin, Muhammad Rifqi; Feranie, Selly

2017-05-01

Science teachers need to help students identify their prior ideas and modify them based on scientific knowledge. This process is called as conceptual change. One of essential tools to analyze students' conceptual change is by using concept map. Concept Maps are graphical representations of knowledge that are comprised of concepts and the relationships between them. Constructing concept map is implemented by adapting the role of technology to support learning process, as it is suitable with Educational Ministry Regulation No.68 year 2013. Institute for Human and Machine Cognition (IHMC) has developed CmapTools, a client-server software for easily construct and visualize concept maps. This research aims to investigate secondary students' conceptual change after experiencing five-stage conceptual teaching model by utilizing CmapTools in learning Optics. Weak experimental method through one group pretest-posttest design is implemented in this study to collect preliminary and post concept map as qualitative data. Sample was taken purposively of 8th grade students (n= 22) at one of private schools Bandung, West Java. Conceptual change based on comparison of preliminary and post concept map construction is assessed based on rubric of concept map scoring and structure. Results shows significance conceptual change differences at 50.92 % that is elaborated into concept map element such as prepositions and hierarchical level in high category, cross links in medium category and specific examples in low category. All of the results are supported with the students' positive response towards CmapTools utilization that indicates improvement of motivation, interest, and behavior aspect towards Physics lesson.

Contact-Free Cognitive Load Recognition Based on Eye Movement

Directory of Open Access Journals (Sweden)

Xin Liu

2016-01-01

Full Text Available The cognitive overload not only affects the physical and mental diseases, but also affects the work efficiency and safety. Hence, the research of measuring cognitive load has been an important part of cognitive load theory. In this paper, we proposed a method to identify the state of cognitive load by using eye movement data in a noncontact manner. We designed a visual experiment to elicit human’s cognitive load as high and low state in two light intense environments and recorded the eye movement data in this whole process. Twelve salient features of the eye movement were selected by using statistic test. Algorithms for processing some features are proposed for increasing the recognition rate. Finally we used the support vector machine (SVM to classify high and low cognitive load. The experimental results show that the method can achieve 90.25% accuracy in light controlled condition.

The Machine within the Machine

CERN Multimedia

Katarina Anthony

2014-01-01

Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

Conceptual models in man-machine design verification

International Nuclear Information System (INIS)

Rasmussen, J.

1985-01-01

The need for systematic methods for evaluation of design concepts for new man-machine systems has been rapidly increasing in consequence of the introduction of modern information technology. Direct empirical methods are difficult to apply when functions during rare conditions and support of operator decisions during emergencies are to be evaluated. In this paper, the problems of analytical evaluations based on conceptual models of the man-machine interaction are discussed, and the relations to system design and analytical risk assessment are considered. Finally, a conceptual framework for analytical evaluation is proposed, including several domains of description: 1. The problem space, in the form of a means-end hierarchy; 2. The structure of the decision process; 3. The mental strategies and heuristics used by operators; 4. The levels of cognitive control and the mechanisms related to human errors. Finally, the need for models representing operators' subjective criteria for choosing among available mental strategies and for accepting advice from intelligent interfaces is discussed

JACOS: AI-based simulation system for man-machine system behavior in NPP

Energy Technology Data Exchange (ETDEWEB)

Yoshida, Kazuo; Yokobayashi, Masao; Tanabe, Fumiya [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Kawase, Katsumi [CSK Corp., Tokyo (Japan); Komiya, Akitoshi [Computer Associated Laboratory, Inc., Hitachinaka, Ibaraki (Japan)

2001-08-01

A prototype of a computer simulation system named JACOS (JAERI COgnitive Simulation system) has been developed at JAERI (Japan Atomic Energy Research Institute) to simulate the man-machine system behavior in which both the cognitive behavior of a human operator and the plant behavior affect each other. The objectives of this system development is to provide man-machine system analysts with detailed information on the cognitive process of an operator and the plant behavior affected by operator's actions in accidental situations of a nuclear power plant. The simulation system consists of an operator model and a plant model which are coupled dynamically. The operator model simulates an operator's cognitive behavior in accidental situations based on the decision ladder model of Rasmussen, and is implemented using the AI-techniques of the distributed cooperative inference method with the so-called blackboard architecture. Rule-based behavior is simulated using knowledge representation with If-Then type of rules. Knowledge-based behavior is simulated using knowledge representation with MFM (Multilevel Flow Modeling) and qualitative reasoning method. Cognitive characteristics of attentional narrowing, limitation of short-term memory, and knowledge recalling from long-term memory are also taken into account. The plant model of a 3-loop PWR is also developed using a best estimate thermal-hydraulic analysis code RELAP5/MOD2. This report is prepared as User's Manual for JACOS. The first chapter of this report describes both operator and plant models in detail. The second chapter includes instructive descriptions for program installation, building of a knowledge base for operator model, execution of simulation and analysis of simulation results. The examples of simulation with JACOS are shown in the third chapter. (author)

Effect of Machining Velocity in Nanoscale Machining Operations

International Nuclear Information System (INIS)

Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

2015-01-01

The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

Autonomous unobtrusive detection of mild cognitive impairment in older adults.

Science.gov (United States)

Akl, Ahmad; Taati, Babak; Mihailidis, Alex

2015-05-01

The current diagnosis process of dementia is resulting in a high percentage of cases with delayed detection. To address this problem, in this paper, we explore the feasibility of autonomously detecting mild cognitive impairment (MCI) in the older adult population. We implement a signal processing approach equipped with a machine learning paradigm to process and analyze real-world data acquired using home-based unobtrusive sensing technologies. Using the sensor and clinical data pertaining to 97 subjects, acquired over an average period of three years, a number of measures associated with the subjects' walking speed and general activity in the home were calculated. Different time spans of these measures were used to generate feature vectors to train and test two machine learning algorithms namely support vector machines and random forests. We were able to autonomously detect MCI in older adults with an area under the ROC curve of 0.97 and an area under the precision-recall curve of 0.93 using a time window of 24 weeks. This study is of great significance since it can potentially assist in the early detection of cognitive impairment in older adults.

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Integrated Cognition - A Proposed Definition of Ingredients, A Survey of Systems, and Example Architecture

National Research Council Canada - National Science Library

Rolfe, Robert M; Haugh, Brian A

2004-01-01

Numerous cognitive scientists believe that a human-level thinking machine must be composed of potentially hundreds of distinct subsystems with different structures, reasoning, and learning mechanisms...

Environmentally Friendly Machining

CERN Document Server

Dixit, U S; Davim, J Paulo

2012-01-01

Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

Human friendly man-machine system with advanced media technology

International Nuclear Information System (INIS)

Ogino, Takamichi; Sasaki, Kazunori

1993-01-01

This paper deals with the methodology to implement the man-machine system (MMS) with enhanced human friendliness for nuclear power plants. The relevant technologies are investigated from the two view points: One is integrated multi-media usage for user-computer interface and the other cognitive engineering for user-task interaction. Promising MMS design methodologies, concepts, and their limitations are discussed. To overcome uncertain factors found in human behaviors or individual differences in performance and preference of operators, a design appproach to natural and flexible man-computer interactive environment is proposed by intergrated use of not only cognitive and psychological knowledge but also advanced media technology. Multi-media operator support system under development is shown as an example to evaluate the effectiveness of the new approach and future advancement is prospected. (orig.)

Supervised cognitive system: A new vision for cognitive engine design in wireless networks

KAUST Repository

Alqerm, Ismail

2018-03-19

Cognitive radio attracts researchers\\' attention recently in radio resource management due to its ability to exploit environment awareness in configuring radio system parameters. Cognitive engine (CE) is the structure known for deciding system parameters\\' adaptation using optimization and machine learning techniques. However, these techniques have strengths and weaknesses depending on the experienced network scenario that make one more appropriate than others. In this paper, we propose a novel design for the cognitive system called supervised cognitive system (SCS), which aims to perform radio parameters adaptation with the most appropriate CE learning technique for the encountered network scenario. To realize SCS, it is required to evaluate the performance of different CEs in different network scenarios and according to certain performance objectives. In addition, the ability to select the most appropriate CE learning technique for adaptation in the current network scenario is also a priority in our design. Therefore, SCS investigates the relationship between learning and performance improvement and it employs online learning to classify scenarios and select the most appropriate CE learning technique. The testbed implementation and evaluation results in terms of goodput, packet error rate, and spectral efficiency show that the proposed SCS achieves more than 50% in performance gain compared to the best standalone CE.

Hybrid machining processes perspectives on machining and finishing

CERN Document Server

Gupta, Kapil; Laubscher, R F

2016-01-01

This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

Using support vector machines to identify literacy skills: Evidence from eye movements.

Science.gov (United States)

Lou, Ya; Liu, Yanping; Kaakinen, Johanna K; Li, Xingshan

2017-06-01

Is inferring readers' literacy skills possible by analyzing their eye movements during text reading? This study used Support Vector Machines (SVM) to analyze eye movement data from 61 undergraduate students who read a multiple-paragraph, multiple-topic expository text. Forward fixation time, first-pass rereading time, second-pass fixation time, and regression path reading time on different regions of the text were provided as features. The SVM classification algorithm assisted in distinguishing high-literacy-skilled readers from low-literacy-skilled readers with 80.3 % accuracy. Results demonstrate the effectiveness of combining eye tracking and machine learning techniques to detect readers with low literacy skills, and suggest that such approaches can be potentially used in predicting other cognitive abilities.

Cybernics fusion of human, machine and information systems

CERN Document Server

Suzuki, Kenji; Hasegawa, Yasuhisa

2014-01-01

Cybernics plays a significant role in coping with an aging society using state-of-the-art technologies from engineering, clinical medicine and humanities. This new interdisciplinary field studies technologies that enhance, strengthen, and support physical and cognitive functions of human beings, based on the fusion of human, machine, and information systems. The design of a seamless interface for interaction between the interior and exterior of the human body is described in this book from diverse aspects such as the physical, neurophysiological, and cognitive levels. It is the first book to cover the many aspects of cybernics, allowing readers to understand the life support robotics technology for the elderly, including remote, in-home, hospital, institutional, community medical welfare, and vital-sensing systems. Serving as a valuable resource, this volume will interest not only graduate students, scientists, and engineers but also newcomers to the field of cybernics.

An analysis of a digital variant of the Trail Making Test using machine learning techniques.

Science.gov (United States)

Dahmen, Jessamyn; Cook, Diane; Fellows, Robert; Schmitter-Edgecombe, Maureen

2017-01-01

The goal of this work is to develop a digital version of a standard cognitive assessment, the Trail Making Test (TMT), and assess its utility. This paper introduces a novel digital version of the TMT and introduces a machine learning based approach to assess its capabilities. Using digital Trail Making Test (dTMT) data collected from (N = 54) older adult participants as feature sets, we use machine learning techniques to analyze the utility of the dTMT and evaluate the insights provided by the digital features. Predicted TMT scores correlate well with clinical digital test scores (r = 0.98) and paper time to completion scores (r = 0.65). Predicted TICS exhibited a small correlation with clinically derived TICS scores (r = 0.12 Part A, r = 0.10 Part B). Predicted FAB scores exhibited a small correlation with clinically derived FAB scores (r = 0.13 Part A, r = 0.29 for Part B). Digitally derived features were also used to predict diagnosis (AUC of 0.65). Our findings indicate that the dTMT is capable of measuring the same aspects of cognition as the paper-based TMT. Furthermore, the dTMT's additional data may be able to help monitor other cognitive processes not captured by the paper-based TMT alone.

Learning and Optimization of Cognitive Capabilities. Final Project Report.

Science.gov (United States)

Lumsdaine, A.A.; And Others

The work of a three-year series of experimental studies of human cognition is summarized in this report. Proglem solving and learning in man-machine interaction was investigated, as well as relevant variables and processes. The work included four separate projects: (1) computer-aided problem solving, (2) computer-aided instruction techniques, (3)…

Advanced methods in NDE using machine learning approaches

Science.gov (United States)

Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank

2018-04-01

Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability

The simulation of man-machine interaction in NPPs: the system response analyser project

International Nuclear Information System (INIS)

Cacciabue, P.C.

1990-01-01

In this paper, the ongoing research at Joint Research Centre-Ispra on the simulation of man-machine interaction is reviewed with reference to the past experience of system modelling and to the advances of the technological world. These require the coalescence of mixed disciplines covering the fields of engineering, psychology and sociology. In particular, the complexity of man-machine systems with respect to safety analysis is depicted. The developments and issues in modelling humans and machines are discussed: the possibility of combining them through the System Response Analyser methodology is presented as a balanced to be applied when the objective is the study of safety of systems during abnormal sequences. The three analytical tools which constitute the body of system response analysis namely a quasi-classical simulation of the actual plant, a cognitive model of the operator activities and a driver model, are described. (author)

Humans and Machines in the Evolution of AI in Korea

OpenAIRE

Zhang, Byoung-Tak

2016-01-01

Artificial intelligence in Korea is currently prospering. The media is regularly reporting AI-enabled products such as smart advisors, personal robots, autonomous cars, and human-level intelligence machines. The IT industry is investing in deep learning and AI to maintain the global competitive edge in their services and products. The Ministry of Science, ICT, and Future Planning (MSIP) has launched new funding programs in AI and cognitive science to implement the government’s newly adopted e...

ON THE QUESTION OF THE CONSTRUCTION OF COGNITIVE MAPS FOR DATA MINING

Directory of Open Access Journals (Sweden)

Zhilov R. A.

2016-11-01

Full Text Available A method of constructing an optimal cognitive maps consists in optimizing the input data and the dimension data structure of a cognitive map. Pro-optimization problem occurs when large amounts of input data. Optimization of time-dimension data is clustering the input data and as a method of polarization-clusters using hierarchical agglomerative method. Cluster analysis allows to divide the data set into a finite number of homogeneous groups. Optimization of the structurery cognitive map is automatically tuning the balance of influence on each other concepts of machine learning methods, particularly the method of training the neural network.

A tutorial introduction to Bayesian models of cognitive development.

Science.gov (United States)

Perfors, Amy; Tenenbaum, Joshua B; Griffiths, Thomas L; Xu, Fei

2011-09-01

We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive development. Our goal is to provide an intuitive and accessible guide to the what, the how, and the why of the Bayesian approach: what sorts of problems and data the framework is most relevant for, and how and why it may be useful for developmentalists. We emphasize a qualitative understanding of Bayesian inference, but also include information about additional resources for those interested in the cognitive science applications, mathematical foundations, or machine learning details in more depth. In addition, we discuss some important interpretation issues that often arise when evaluating Bayesian models in cognitive science. Copyright © 2010 Elsevier B.V. All rights reserved.

Machine terms dictionary

Energy Technology Data Exchange (ETDEWEB)

NONE

1979-04-15

This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

Learning Control: Sense-Making, CNC Machines, and Changes in Vocational Training for Industrial Work

Science.gov (United States)

Berner, Boel

2009-01-01

The paper explores how novices in school-based vocational training make sense of computerized numerical control (CNC) machines. Based on two ethnographic studies in Swedish schools, one from the early 1980s and one from 2006, it analyses change and continuity in the cognitive, social, and emotional processes of learning how to become a machine…

Tempo in electronic gaming machines affects behavior among at-risk gamblers.

Science.gov (United States)

Mentzoni, Rune A; Laberg, Jon Christian; Brunborg, Geir Scott; Molde, Helge; Pallesen, Ståle

2012-09-01

Background and aims Electronic gaming machines (EGM) may be a particularly addictive form of gambling, and gambling speed is believed to contribute to the addictive potential of such machines. The aim of the current study was to generate more knowledge concerning speed as a structural characteristic in gambling, by comparing the effects of three different bet-to-outcome intervals (BOI) on gamblers bet-sizes, game evaluations and illusion of control during gambling on a computer simulated slot machine. Furthermore, we investigated whether problem gambling moderates effects of BOI on gambling behavior and cognitions. Methods 62 participants played a computerized slot machine with either fast (400 ms), medium (1700 ms) or slow (3000 ms) BOI. SOGS-R was used to measure pre-existing gambling problems. Mean bet size, game evaluations and illusion of control comprised the dependent variables. Results Gambling speed had no overall effect on either mean bet size, game evaluations or illusion of control, but in the 400 ms condition, at-risk gamblers (SOGS-R score > 0) employed higher bet sizes compared to no-risk (SOGS-R score = 0) gamblers. Conclusions The findings corroborate and elaborate on previous studies and indicate that restrictions on gambling speed may serve as a harm reducing effort for at-risk gamblers.

Some relations between quantum Turing machines and Turing machines

OpenAIRE

Sicard, Andrés; Vélez, Mario

1999-01-01

For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

Support vector machine in machine condition monitoring and fault diagnosis

Science.gov (United States)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

Development of AI (Artificial Intelligence)-based simulation system for man-machine system behavior in accidental situations of nuclear power plant

International Nuclear Information System (INIS)

Yoshida, Kazuo; Yokobayashi, Masao; Tanabe, Fumiya; Kawase, Katumi.

1996-01-01

A prototype version of a computer simulation system named JACOS (JAeri COgnitive Simulation system) has been developed at JAERI (Japan Atomic Energy Research Institute) to simulate the man-machine system behavior in which both the cognitive behavior of a human operator and the plant behavior affect each other. The objectives of this system development is to provide man-machine system analysts with detailed information on the cognitive process of an operator and the plant behavior affected by operator's actions in accidental situations of an NPP (nuclear power plant). The simulation system consists of an operator model and a plant model which are coupled dynamically. The operator model simulates an operator's cognitive behavior in accidental situations based on the decision ladder model of Rasmussen, and is implemented using the AI-techniques of the distributed cooperative inference method with the so-called blackboard architecture. Rule-based behavior is simulated using knowledge representation with If-Then type of rules. Knowledge-based behavior is simulated using knowledge representation with MFM (Multilevel Flow Modeling) and qualitative reasoning method. Cognitive characteristics of attentional narrowing, limitation of short-term memory, and knowledge recalling from long-term memory are also modeled. The plant model of a 3-loop PWR is also developed using a best estimate thermal-hydraulic analysis code RELAP5/MOD2. Some simulations of incidents were performed to verify the human model. It was found that AI-techniques used in the human model are suitable to simulate the operator's cognitive behavior in an NPP accident. The models of cognitive characteristics were investigated in the effects on simulated results of cognitive behaviors. (author)

Multimodality Inferring of Human Cognitive States Based on Integration of Neuro-Fuzzy Network and Information Fusion Techniques

Directory of Open Access Journals (Sweden)

P. Bhattacharya

2007-11-01

Full Text Available To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human's operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressions or cues, the recent trend to infer the human state is to consider multimodality features of the human operator. In this paper, we present a method for multimodality inferring of human cognitive states by integrating neuro-fuzzy network and information fusion techniques. To demonstrate the effectiveness of this method, we take the driver fatigue detection as an example. The proposed method has, in particular, the following new features. First, human expressions are classified into four categories: (i casual or contextual feature, (ii contact feature, (iii contactless feature, and (iv performance feature. Second, the fuzzy neural network technique, in particular Takagi-Sugeno-Kang (TSK model, is employed to cope with uncertain behaviors. Third, the sensor fusion technique, in particular ordered weighted aggregation (OWA, is integrated with the TSK model in such a way that cues are taken as inputs to the TSK model, and then the outputs of the TSK are fused by the OWA which gives outputs corresponding to particular cognitive states under interest (e.g., fatigue. We call this method TSK-OWA. Validation of the TSK-OWA, performed in the Northeastern University vehicle drive simulator, has shown that the proposed method is promising to be a general tool for human cognitive state inferring and a special tool for the driver fatigue detection.

Application of Machine Learning in Postural Control Kinematics for the Diagnosis of Alzheimer’s Disease

Directory of Open Access Journals (Sweden)

Luís Costa

2016-01-01

Full Text Available The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer’s disease (AD. In this paper, we investigate if machine-learning classifiers offer the discriminative power for the diagnosis of AD based on postural control kinematics. We compared Support Vector Machines (SVMs, Multiple Layer Perceptrons (MLPs, Radial Basis Function Neural Networks (RBNs, and Deep Belief Networks (DBNs on 72 participants (36 AD patients and 36 healthy subjects exposed to seven increasingly difficult postural tasks. The decisional space was composed of 18 kinematic variables (adjusted for age, education, height, and weight, with or without neuropsychological evaluation (Montreal cognitive assessment (MoCA score, top ranked in an error incremental analysis. Classification results were based on threefold cross validation of 50 independent and randomized runs sets: training (50%, test (40%, and validation (10%. Having a decisional space relying solely on postural kinematics, accuracy of AD diagnosis ranged from 71.7 to 86.1%. Adding the MoCA variable, the accuracy ranged between 91 and 96.6%. MLP classifier achieved top performance in both decisional spaces. Having comprehended the interdynamic interaction between postural stability and cognitive performance, our results endorse machine-learning models as a useful tool for computer-aided diagnosis of AD based on postural control kinematics.

Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.

Science.gov (United States)

Thabtah, Fadi

2018-02-13

Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of linguistic, communication, cognitive, and social skills and abilities. Despite being diagnosed with ASD, some individuals exhibit outstanding scholastic, non-academic, and artistic capabilities, in such cases posing a challenging task for scientists to provide answers. In the last few years, ASD has been investigated by social and computational intelligence scientists utilizing advanced technologies such as machine learning to improve diagnostic timing, precision, and quality. Machine learning is a multidisciplinary research topic that employs intelligent techniques to discover useful concealed patterns, which are utilized in prediction to improve decision making. Machine learning techniques such as support vector machines, decision trees, logistic regressions, and others, have been applied to datasets related to autism in order to construct predictive models. These models claim to enhance the ability of clinicians to provide robust diagnoses and prognoses of ASD. However, studies concerning the use of machine learning in ASD diagnosis and treatment suffer from conceptual, implementation, and data issues such as the way diagnostic codes are used, the type of feature selection employed, the evaluation measures chosen, and class imbalances in data among others. A more serious claim in recent studies is the development of a new method for ASD diagnoses based on machine learning. This article critically analyses these recent investigative studies on autism, not only articulating the aforementioned issues in these studies but also recommending paths forward that enhance machine learning use in ASD with respect to conceptualization, implementation, and data. Future studies concerning machine learning in autism research are greatly benefitted by such proposals.

Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

OpenAIRE

Qiu, Daowen

2005-01-01

As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing ma...

Optimizing Distributed Machine Learning for Large Scale EEG Data Set

Directory of Open Access Journals (Sweden)

M Bilal Shaikh

2017-06-01

Full Text Available Distributed Machine Learning (DML has gained its importance more than ever in this era of Big Data. There are a lot of challenges to scale machine learning techniques on distributed platforms. When it comes to scalability, improving the processor technology for high level computation of data is at its limit, however increasing machine nodes and distributing data along with computation looks as a viable solution. Different frameworks   and platforms are available to solve DML problems. These platforms provide automated random data distribution of datasets which miss the power of user defined intelligent data partitioning based on domain knowledge. We have conducted an empirical study which uses an EEG Data Set collected through P300 Speller component of an ERP (Event Related Potential which is widely used in BCI problems; it helps in translating the intention of subject w h i l e performing any cognitive task. EEG data contains noise due to waves generated by other activities in the brain which contaminates true P300Speller. Use of Machine Learning techniques could help in detecting errors made by P300 Speller. We are solving this classification problem by partitioning data into different chunks and preparing distributed models using Elastic CV Classifier. To present a case of optimizing distributed machine learning, we propose an intelligent user defined data partitioning approach that could impact on the accuracy of distributed machine learners on average. Our results show better average AUC as compared to average AUC obtained after applying random data partitioning which gives no control to user over data partitioning. It improves the average accuracy of distributed learner due to the domain specific intelligent partitioning by the user. Our customized approach achieves 0.66 AUC on individual sessions and 0.75 AUC on mixed sessions, whereas random / uncontrolled data distribution records 0.63 AUC.

Improved Extreme Learning Machine based on the Sensitivity Analysis

Science.gov (United States)

Cui, Licheng; Zhai, Huawei; Wang, Benchao; Qu, Zengtang

2018-03-01

Extreme learning machine and its improved ones is weak in some points, such as computing complex, learning error and so on. After deeply analyzing, referencing the importance of hidden nodes in SVM, an novel analyzing method of the sensitivity is proposed which meets people’s cognitive habits. Based on these, an improved ELM is proposed, it could remove hidden nodes before meeting the learning error, and it can efficiently manage the number of hidden nodes, so as to improve the its performance. After comparing tests, it is better in learning time, accuracy and so on.

An Analysis of Machine- and Human-Analytics in Classification.

Science.gov (United States)

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

A review of warship man-machine-environment system engineering

Directory of Open Access Journals (Sweden)

ZHANG Yumei

2017-03-01

Full Text Available Warship Man-Machine-Environment System Engineering (MMESE is an integral part of the overall design, and its design principles were proposed according to safety, efficiency, comfort and pleasure. The typical characteristics of MMESE are summarized. The operating environment is extremely terrible on long voyages. High level collaboration is required due to the complex task system and large manpower demand. Owing to the dense computer interface information, the mental cognitive burden on the crew is heavy. The MMESE technology system is divided into four parts:man-machine coordinated, man-environment coordinated, the evaluation of man-machine-environment characteristics and the ergonomic simulation. Based on the MMESE development venation in this paper, the overseas and domestic research statuses are expounded. Interactive optimization can be realized according to the following aspects:researching the basic human characteristics of the crew, applying this to the warship's overall design, and formulating relevant ergonomic standards and norms. Next, Human System Integration (HSI professional engineering was introduced comprehensively into the marines in order to achieve an optimal system. On this basis, we completed the future development trend analysis. All these studies and results have some reference meaning for guiding the integrated optimization of warships as a whole, downsizing the manpower and improving efficiency.

Plant operator performance evaluation based on cognitive process analysis experiment

International Nuclear Information System (INIS)

Ujita, H.; Fukuda, M.

1990-01-01

This paper reports on an experiment to clarify plant operators' cognitive processes that has been performed, to improve the man-machine interface which supports their diagnoses and decisions. The cognitive processes under abnormal conditions were evaluated by protocol analyses interviews, etc. in the experiment using a plant training simulator. A cognitive process model is represented by a stochastic network, based on Rasmussen's decision making model. Each node of the network corresponds to an element of the cognitive process, such as observation, interpretation, execution, etc. Some observations were obtained as follows, by comparison of Monte Carlo simulation results with the experiment results: A process to reconfirm the plant parameters after execution of a task and feedback paths from this process to the observation and the task definition of next task were observed. The feedback probability average and standard deviation should be determined for each incident type to explain correctly the individual differences in the cognitive processes. The tendency for the operator's cognitive level to change from skill-based to knowledge-based via rule-based behavior was observed during the feedback process

Machine tool structures

CERN Document Server

Koenigsberger, F

1970-01-01

Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

Cognitive modelling: a basic complement of human reliability analysis

International Nuclear Information System (INIS)

Bersini, U.; Cacciabue, P.C.; Mancini, G.

1988-01-01

In this paper the issues identified in modelling humans and machines are discussed in the perspective of the consideration of human errors managing complex plants during incidental as well as normal conditions. The dichotomy between the use of a cognitive versus a behaviouristic model approach is discussed and the complementarity aspects rather than the differences of the two methods are identified. A cognitive model based on a hierarchical goal-oriented approach and driven by fuzzy logic methodology is presented as the counterpart to the 'classical' THERP methodology for studying human errors. Such a cognitive model is discussed at length and its fundamental components, i.e. the High Level Decision Making and the Low Level Decision Making models, are reviewed. Finally, the inadequacy of the 'classical' THERP methodology to deal with cognitive errors is discussed on the basis of a simple test case. For the same case the cognitive model is then applied showing the flexibility and adequacy of the model to dynamic configuration with time-dependent failures of components and with consequent need for changing of strategy during the transient itself. (author)

Electricity of machine tool

International Nuclear Information System (INIS)

Gijeon media editorial department

1977-10-01

This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

Machine Learning from Garden Path Sentences: The Application of Computational Linguistics

Directory of Open Access Journals (Sweden)

Jiali Du

2014-12-01

Full Text Available This paper discusses the application of computational linguistics in the machine learning (ML system for the processing of garden path sentences. ML is closely related to artificial intelligence and linguistic cognition. The rapid and efficient processing of the complex structures is an effective method to test the system. By means of parsing the garden path sentence, we draw a conclusion that the integration of theoretical and statistical methods is helpful for the development of ML system.

Machine medical ethics

CERN Document Server

Pontier, Matthijs

2015-01-01

The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

Advances in the development of a cognitive user interface

Directory of Open Access Journals (Sweden)

Jokisch Oliver

2018-01-01

Full Text Available In this contribution, we want to summarize recent development steps of the embedded cognitive user interface UCUI, which enables a user-adaptive scenario in human-machine or even human-robot interactions by considering sophisticated cognitive and semantic modelling. The interface prototype is developed by different German institutes and companies with their steering teams at Fraunhofer IKTS and Brandenburg University of Technology. The interface prototype is able to communicate with users via speech and gesture recognition, speech synthesis and a touch display. The device includes an autarkic semantic processing and beyond a cognitive behavior control, which supports an intuitive interaction to control different kinds of electronic devices, e. g. in a smart home environment or in interactive respectively collaborative robotics. Contrary to available speech assistance systems such as Amazon Echo or Google Home, the introduced cognitive user interface UCUI ensures the user privacy by processing all necessary information without any network access of the interface device.

[Cognitive remediation and cognitive assistive technologies in schizophrenia].

Science.gov (United States)

Sablier, J; Stip, E; Franck, N

2009-04-01

. Finally, we present a review of recent studies testing innovative devices developed to assist schizophrenia patients. First, we found several cognitive programs proven to be effective with schizophrenia patients, but only three were validated in French. It could be useful to adapt other programs for French-speaking populations. Unfortunately, we found that very few of the existing cognitive assistive technologies are proposed to be used with schizophrenia patients. In fact, most of the available cognitive orthoses were tested primarily in people with neurological injuries (for example, various memory impairments caused by traumas), and in elderly illnesses (like Alzheimer disease). Devices for patients with mental deficits (e.g., mental retardation) were developed later, and only very recently explored for use in schizophrenia. As a result of an international collaboration between France and Canada, currently a tool called MOBUS is being tested. This technology aims at improving the autonomy of schizophrenia patients, by helping them plan and remember their daily activities. Furthermore, it encourages patient-caregiver communication, and permits monitoring patients' subjective reports of their symptoms. The use of cognitive assistive technologies is not meant to isolate patients by replacing the human element of relatives and caregivers by a machine. On the contrary, they offer a sense of security and they improve interpersonal relationships by permitting enhanced autonomy and greater self-confidence. Finally, a literature review of cognitive remediation in schizophrenia emphasizes the importance of a structured application of the technique in order for it to succeed. First, it is crucial to detect the impairments that will be targeted in each patient presenting a specific pattern of impairments. For this purpose, validated and customised neuropsychological tests are required. Then, cognitive remediation programs must be customised to each patient's needs in order to

New Perspectives on Computational and Cognitive Strategies for Word Sense Disambiguation

CERN Document Server

Kwong, Oi Yee

2013-01-01

Cognitive and Computational Strategies for Word Sense Disambiguation examines cognitive strategies by humans and computational strategies by machines, for WSD in parallel.  Focusing on a psychologically valid property of words and senses, author Oi Yee Kwong discusses their concreteness or abstractness and draws on psycholinguistic data to examine the extent to which existing lexical resources resemble the mental lexicon as far as the concreteness distinction is concerned. The text also investigates the contribution of different knowledge sources to WSD in relation to this very intrinsic nature of words and senses. 

Machine musicianship

Science.gov (United States)

Rowe, Robert

2002-05-01

The training of musicians begins by teaching basic musical concepts, a collection of knowledge commonly known as musicianship. Computer programs designed to implement musical skills (e.g., to make sense of what they hear, perform music expressively, or compose convincing pieces) can similarly benefit from access to a fundamental level of musicianship. Recent research in music cognition, artificial intelligence, and music theory has produced a repertoire of techniques that can make the behavior of computer programs more musical. Many of these were presented in a recently published book/CD-ROM entitled Machine Musicianship. For use in interactive music systems, we are interested in those which are fast enough to run in real time and that need only make reference to the material as it appears in sequence. This talk will review several applications that are able to identify the tonal center of musical material during performance. Beyond this specific task, the design of real-time algorithmic listening through the concurrent operation of several connected analyzers is examined. The presentation includes discussion of a library of C++ objects that can be combined to perform interactive listening and a demonstration of their capability.

The Importance of the Study of Cognitive Performance Enhancement for U.S. National Security.

Science.gov (United States)

Malish, Richard G

2017-08-01

The American military is embarking on the 'Third Offset'-a strategy designed to produce seismic shifts in the future of warfare. Central to the approach is the conjoining of humans, technology, and machines to deliver a decisive advantage on the battlefield. Because technology will spread rapidly and globally, tactical overmatch will occur when American operators possess a competitive edge in cognition. Investigation of cognitive enhancing therapeutics is not widely articulated as an adjunct to the Third Offset, yet failure to study promising agents could represent a strategic vulnerability. Because of its legacy of research into therapeutic agents to enhance human-machine interplay, the aerospace medical community represents a front-running candidate to perform this work. Notably, there are strong signals emanating from gambling, academic, and video-gaming enterprises that already-developed stimulants and other agents provide cognitive benefits. These agents should be studied not only for reasons of national security, but also because cognitive enhancement may be a necessary step in the evolution of humankind. To illustrate these points, this article will assert that: 1) the need to preserve and enhance physical and cognitive health will become more and more important over the next century; 2) aeromedical specialists are in a position to take the lead in the endeavor to enhance cognition; 3) signals of enhancement of the type useful to both military and medical efforts exist aplenty in today's society; and 4) the aeromedical community should approach human enhancement research deliberately but carefully.Malish RG. The importance of the study of cognitive performance enhancement for U.S. national security. Aerosp Med Hum Perform. 2017; 88(8):773-778.

Code-expanded radio access protocol for machine-to-machine communications

DEFF Research Database (Denmark)

Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

2013-01-01

The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated b...... subframes and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the massive support of Machine-Type Communication users that is beyond the reach of current systems.......The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated...... by the random access method employed in LTE, which significantly increases the amount of contention resources without increasing the system resources, such as contention subframes and preambles. This is accomplished by a logical, rather than physical, extension of the access method in which the available system...

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

Science.gov (United States)

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

Multivariate Cross-Classification: Applying machine learning techniques to characterize abstraction in neural representations

Directory of Open Access Journals (Sweden)

Jonas eKaplan

2015-03-01

Full Text Available Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC, and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application.

Simple machines

CERN Document Server

Graybill, George

2007-01-01

Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

Machine performance assessment and enhancement for a hexapod machine

Energy Technology Data Exchange (ETDEWEB)

Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

1998-03-19

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

Superconducting rotating machines

International Nuclear Information System (INIS)

Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

1975-01-01

The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

Fun cube based brain gym cognitive function assessment system.

Science.gov (United States)

Zhang, Tao; Lin, Chung-Chih; Yu, Tsang-Chu; Sun, Jing; Hsu, Wen-Chuin; Wong, Alice May-Kuen

2017-05-01

The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment. Three kinds of experiments were performed to evaluate the developed FC-based BG cognitive function assessment system. The experimental results showed that the Pearson correlation coefficient between the system's evaluation outcomes and the traditional Montreal Cognitive Assessment scores was 0.83. The average Technology Acceptance Model 2 score was close to six for 31 elderly subjects. Most subjects considered that the brain games are interesting and the FC human-machine interface is easy to learn and operate. The control group and the cognitive impairment group had statistically significant difference with respect to the accuracy of and the time taken for the brain cognitive function assessment games, including Animal Naming, Color Search, Trail Making Test, Change Blindness, and Forward / Backward Digit Span. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative Machine Learning Analysis of Brain MRI Morphology throughout Aging.

Science.gov (United States)

Shamir, Lior; Long, Joe

2016-01-01

While cognition is clearly affected by aging, it is unclear whether the process of brain aging is driven solely by accumulation of environmental damage, or involves biological pathways. We applied quantitative image analysis to profile the alteration of brain tissues during aging. A dataset of 463 brain MRI images taken from a cohort of 416 subjects was analyzed using a large set of low-level numerical image content descriptors computed from the entire brain MRI images. The correlation between the numerical image content descriptors and the age was computed, and the alterations of the brain tissues during aging were quantified and profiled using machine learning. The comprehensive set of global image content descriptors provides high Pearson correlation of ~0.9822 with the chronological age, indicating that the machine learning analysis of global features is sensitive to the age of the subjects. Profiling of the predicted age shows several periods of mild changes, separated by shorter periods of more rapid alterations. The periods with the most rapid changes were around the age of 55, and around the age of 65. The results show that the process of brain aging of is not linear, and exhibit short periods of rapid aging separated by periods of milder change. These results are in agreement with patterns observed in cognitive decline, mental health status, and general human aging, suggesting that brain aging might not be driven solely by accumulation of environmental damage. Code and data used in the experiments are publicly available.

Sustainable machining

CERN Document Server

2017-01-01

This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

Directory of Open Access Journals (Sweden)

Ming Cheng

2015-09-01

Full Text Available The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs. Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG. Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

Asynchronized synchronous machines

CERN Document Server

Botvinnik, M M

1964-01-01

Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

Machine Shop Lathes.

Science.gov (United States)

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

Cognitive computing and big data analytics

CERN Document Server

Hurwitz, Judith; Bowles, Adrian

2015-01-01

MASTER THE ABILITY TO APPLY BIG DATA ANALYTICS TO MASSIVE AMOUNTS OF STRUCTURED AND UNSTRUCTURED DATA Cognitive computing is a technique that allows humans and computers to collaborate in order to gain insights and knowledge from data by uncovering patterns and anomalies. This comprehensive guide explains the underlying technologies, such as artificial intelligence, machine learning, natural language processing, and big data analytics. It then demonstrates how you can use these technologies to transform your organization. You will explore how different vendors and different industries are a

A framework for the analysis of cognitive reliability in complex systems: a recovery centred approach

International Nuclear Information System (INIS)

Kontogiannis, Tom

1997-01-01

Managing complex industrial systems requires reliable performance of cognitive tasks undertaken by operating crews. The infrequent practice of cognitive skills and the reliance on operator performance for novel situations raised cognitive reliability into an urgent and essential aspect in system design and risk analysis. The aim of this article is to contribute to the development of methods for the analysis of cognitive tasks in complex man-machine interactions. A practical framework is proposed for analysing cognitive errors and enhancing error recovery through interface design. Cognitive errors are viewed as failures in problem solving which are difficult to recover under the task constrains imposed by complex systems. In this sense, the interaction between context and cognition, on the one hand, and the process of error recovery, on the other hand, become the focal points of the proposed framework which is illustrated in an analysis of a simulated emergency

Machining of Machine Elements Made of Polymer Composite Materials

Science.gov (United States)

Baurova, N. I.; Makarov, K. A.

2017-12-01

The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

Science.gov (United States)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

The achievements of the Z-machine; Les exploits de la Z-machine

Energy Technology Data Exchange (ETDEWEB)

Larousserie, D

2008-03-15

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Quantum machine learning.

Science.gov (United States)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Machine protection systems

CERN Document Server

Macpherson, A L

2010-01-01

A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

Preliminary Test of Upgraded Conventional Milling Machine into PC Based CNC Milling Machine

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

CNC (Computerized Numerical Control) milling machine yields a challenge to make an innovation in the field of machining. With an action job is machining quality equivalent to CNC milling machine, the conventional milling machine ability was improved to be based on PC CNC milling machine. Mechanically and instrumentally change. As a control replacing was conducted by servo drive and proximity were used. Computer programme was constructed to give instruction into milling machine. The program structure of consists GUI model and ladder diagram. Program was put on programming systems called RTX software. The result of up-grade is computer programming and CNC instruction job. The result was beginning step and it will be continued in next time. With upgrading ability milling machine becomes user can be done safe and optimal from accident risk. By improving performance of milling machine, the user will be more working optimal and safely against accident risk. (author)

A basic experimental study on characteristics of on-line human information processing associated with man-machine interface

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Shimoda, Hiroshi; Nagai, Yoshinori; Kojima, Shin-ichi.

1990-01-01

Regarding human factors research on man-machine interface, a basic psychological experiment was conducted to observe psycho-physiological characteristics of on-line human cognitive behavior when cognitive tasks on learning and pattern classification were given to subjects by personal computer using a simple state transition model. During the experiment, three different types of subjects' data were recorded: (i) eye movement data by eye mark recorder, (ii) physio-electric signals by polygraph and (iii) verbal reports. Those subjects' data were analyzed with respect to: (i) the related human cognitive characteristics concerning problem solving strategy, measures of problem difficulty and mental image effect, (ii) observed eye movement characteristics such as saccade, attention, pupil reaction and blinking, etc., and (iii) obtained characteristics of skin potential response and heart rate. It was found that the application of psycho-physiological measurement would serve to objective and detailed analysis of on-line cognitive process. (author)

The mission execution crew assistant : Improving human-machine team resilience for long duration missions

OpenAIRE

Neerincx, M.A.; Lindenberg, J.; Smets, N.J.J.M.; Bos, A.; Breebaart, L.; Grant, T.; Olmedo-Soler, A.; Brauer, U.; Wolff, M.

2008-01-01

Manned long-duration missions to the Moon and Mars set high operational, human factors and technical demands for a distributed support system, which enhances human-machine teams' capabilities to cope autonomously with unexpected, complex and potentially hazardous situations. Based on a situated Cognitive Engineering (sCE) method, we specified a theoretical and empirical founded Requirements Baseline (RB) for such a system (called Mission Execution Crew Assistant; MECA), and its rational consi...

Study of on-machine error identification and compensation methods for micro machine tools

International Nuclear Information System (INIS)

Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

2016-01-01

Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

Non-conventional electrical machines

CERN Document Server

Rezzoug, Abderrezak

2013-01-01

The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

Imagining the thinking machine: technological myths and the rise of Artificial Intelligence

OpenAIRE

Natale, Simone; Ballatore, Andrea

2017-01-01

This article discusses the role of technological myths in the development of Artificial Intelligence (AI) technologies from 1950s to the early 1970s. It shows how the rise of AI was accompanied by the construction of a powerful cultural myth: the creation of a thinking machine, which would be able to perfectly simulate the cognitive faculties of the human mind. Based on a content analysis of articles on Artificial Intelligence published in two magazines, the Scientific American and the New Sc...

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

2014-08-15

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

International Nuclear Information System (INIS)

Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

2014-01-01

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

Cognitive environment simulation: An artificial intelligence system for human performance assessment: Modeling human intention formation: [Technical report, May 1986-June 1987

International Nuclear Information System (INIS)

Woods, D.D.; Roth, E.M.; Pople, H. Jr.

1987-11-01

This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 43 refs., 20 figs., 1 tab

Enhanced Cognitive Walkthrough: Development of the Cognitive Walkthrough Method to Better Predict, Identify, and Present Usability Problems

Directory of Open Access Journals (Sweden)

Lars-Ola Bligård

2013-01-01

Full Text Available To avoid use errors when handling medical equipment, it is important to develop products with a high degree of usability. This can be achieved by performing usability evaluations in the product development process to detect and mitigate potential usability problems. A commonly used method is cognitive walkthrough (CW, but this method shows three weaknesses: poor high-level perspective, insufficient categorisation of detected usability problems, and difficulties in overviewing the analytical results. This paper presents a further development of CW with the aim of overcoming its weaknesses. The new method is called enhanced cognitive walkthrough (ECW. ECW is a proactive analytical method for analysis of potential usability problems. The ECW method has been employed to evaluate user interface designs of medical equipment such as home-care ventilators, infusion pumps, dialysis machines, and insulin pumps. The method has proved capable of identifying several potential use problems in designs.

Electrical machines & drives

CERN Document Server

Hammond, P

1985-01-01

Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

Machine translation

Energy Technology Data Exchange (ETDEWEB)

Nagao, M

1982-04-01

Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

Induction machine handbook

CERN Document Server

Boldea, Ion

2002-01-01

Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

Chaotic Boltzmann machines

Science.gov (United States)

Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

2013-01-01

The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

Rotating electrical machines

CERN Document Server

Le Doeuff, René

2013-01-01

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

Development of an integrated decision support system to aid cognitive activities of operators

International Nuclear Information System (INIS)

Lee, Seung Jun; Seong, Poong Hyun

2007-01-01

As digital and computer technologies have grown, Human-Machine Interfaces (HMIs) have evolved. In safety-critical systems, especially in Nuclear Power Plants (NPPs), HMIs are important for reducing operational costs, the number of necessary operators, and the probability of accident occurrence. Efforts have been made to improve Main Control Room (MCR) interface design and to develop automated or decision support systems to ensure convenient operation and maintenance. In this paper, an integrated decision support system to aid operator cognitive processes is proposed for advanced MCRs of future NPPs. This work suggests the design concept of a decision support system which accounts for an operator's cognitive processes. The proposed system supports not only a particular task, but also the entire operation process based on a human cognitive process model. In this paper, the operator's operation processes are analyzed according to a human cognitive process model and appropriate support systems that support each cognitive process activity are suggested

Your Sewing Machine.

Science.gov (United States)

Peacock, Marion E.

The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

Investigation of the Machining Stability of a Milling Machine with Hybrid Guideway Systems

Directory of Open Access Journals (Sweden)

Jui-Pin Hung

2016-03-01

Full Text Available This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

Introduction to AC machine design

CERN Document Server

Lipo, Thomas A

2018-01-01

AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

Precision machining commercialization

International Nuclear Information System (INIS)

1978-01-01

To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

Are there intelligent Turing machines?

OpenAIRE

Bátfai, Norbert

2015-01-01

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

Coldness production and heat revalorization: particular machines; Production de froid et revalorisation de la chaleur: machines particulieres

Energy Technology Data Exchange (ETDEWEB)

Feidt, M. [Universite Henri Poincare - Nancy-1, 54 - Nancy (France)

2003-10-01

The machines presented in this article are not the common reverse cycle machines. They use some systems based on different physical principles which have some consequences on the analysis of cycles: 1 - permanent gas machines (thermal separators, pulse gas tube, thermal-acoustic machines); 2 - phase change machines (mechanical vapor compression machines, absorption machines, ejection machines, adsorption machines); 3 - thermoelectric machines (thermoelectric effects, thermodynamic model of a thermoelectric machine). (J.S.)

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

Science.gov (United States)

Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

‘Machinic Trajectories’: Appropriated Devices as Post-Digital Drawing Machines

Directory of Open Access Journals (Sweden)

Andres Wanner

2014-12-01

Full Text Available This article presents a series of works called Machinic Trajectories, consisting of domestic devices appropriated as mechanical drawing machines. These are contextualized within the post-digital discourse, which integrates messy analog conditions into the digital realm. The role of eliciting and examining glitches for investigating a technology is pointed out. Glitches are defined as short-lived, unpremeditated aesthetic results of a failure; they are mostly known as digital phenomena, but I argue that the concept is equally applicable to the output of mechanical machines. Three drawing machines will be presented: The Opener, The Mixer and The Ventilator. In analyzing their drawings, emergent patterns consisting of unpremeditated visual artifacts will be identified and connected to irregularities of the specific technologies. Several other artists who work with mechanical and robotic drawing machines are introduced, to situate the presented works and reflections in a larger context of practice and to investigate how glitch concepts are applicable to such mechanical systems. 

Zooniverse: Combining Human and Machine Classifiers for the Big Survey Era

Science.gov (United States)

Fortson, Lucy; Wright, Darryl; Beck, Melanie; Lintott, Chris; Scarlata, Claudia; Dickinson, Hugh; Trouille, Laura; Willi, Marco; Laraia, Michael; Boyer, Amy; Veldhuis, Marten; Zooniverse

2018-01-01

Many analyses of astronomical data sets, ranging from morphological classification of galaxies to identification of supernova candidates, have relied on humans to classify data into distinct categories. Crowdsourced galaxy classifications via the Galaxy Zoo project provided a solution that scaled visual classification for extant surveys by harnessing the combined power of thousands of volunteers. However, the much larger data sets anticipated from upcoming surveys will require a different approach. Automated classifiers using supervised machine learning have improved considerably over the past decade but their increasing sophistication comes at the expense of needing ever more training data. Crowdsourced classification by human volunteers is a critical technique for obtaining these training data. But several improvements can be made on this zeroth order solution. Efficiency gains can be achieved by implementing a “cascade filtering” approach whereby the task structure is reduced to a set of binary questions that are more suited to simpler machines while demanding lower cognitive loads for humans.Intelligent subject retirement based on quantitative metrics of volunteer skill and subject label reliability also leads to dramatic improvements in efficiency. We note that human and machine classifiers may retire subjects differently leading to trade-offs in performance space. Drawing on work with several Zooniverse projects including Galaxy Zoo and Supernova Hunter, we will present recent findings from experiments that combine cohorts of human and machine classifiers. We show that the most efficient system results when appropriate subsets of the data are intelligently assigned to each group according to their particular capabilities.With sufficient online training, simple machines can quickly classify “easy” subjects, leaving more difficult (and discovery-oriented) tasks for volunteers. We also find humans achieve higher classification purity while samples

Using cognitive modeling to improve the man-machine interface

International Nuclear Information System (INIS)

Newton, R.A.; Zyduck, R.C.; Johnson, D.R.

1982-01-01

A group of utilities from the Westinghouse Owners Group was formed in early 1980 to examine the interface requirements and to determine how they could be implemented. The products available from the major vendors were examined early in 1980 and judged not to be completely applicable. The utility group then decided to develop its own specifications for a Safety Assessment System (SAS) and, later in 1980, contracted with a company to develop the system, prepare the software and demonstrate the system on a simulator. The resulting SAS is a state-of-the-art system targeted for implementation on pressurized water reactor nuclear units. It has been designed to provide control room operators with centralized and easily understandable information from a computer-based data and display system. This paper gives an overview of the SAS plus a detailed description of one of its functional areas - called AIDS. The AIDS portion of SAS is an advanced concept which uses cognitive modeling of the operator as the basis for its design

Self-Improving CNC Milling Machine

OpenAIRE

Spilling, Torjus

2014-01-01

This thesis is a study of the ability of a CNC milling machine to create parts for itself, and an evaluation of whether or not the machine is able to improve itself by creating new machine parts. This will be explored by using off-the-shelf parts to build an initial machine, using 3D printing/rapid prototyping to create any special parts needed for the initial build. After an initial working machine is completed, the design of the machine parts will be adjusted so that the machine can start p...

Machine Learning.

Science.gov (United States)

Kirrane, Diane E.

1990-01-01

As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

Machining of Metal Matrix Composites

CERN Document Server

2012-01-01

Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

Machine technology: a survey

International Nuclear Information System (INIS)

Barbier, M.M.

1981-01-01

An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available

Characteristics of laser assisted machining for silicon nitride ceramic according to machining parameters

International Nuclear Information System (INIS)

Kim, Jong Do; Lee, Su Jin; Suh, Jeong

2011-01-01

This paper describes the Laser Assisted Machining (LAM) that cuts and removes softened parts by locally heating the ceramic with laser. Silicon nitride ceramics can be machined with general machining tools as well, because YSiAlON, which was made up ceramics, is soften at about 1,000 .deg. C. In particular, the laser, which concentrates on highly dense energy, can locally heat materials and very effectively control the temperature of the heated part of specimen. Therefore, this paper intends to propose an efficient machining method of ceramic by deducing the machining governing factors of laser assisted machining and understanding its mechanism. While laser power is the machining factor that controls the temperature, the CBN cutting tool could cut the material more easily as the material gets deteriorated from the temperature increase by increasing the laser power, but excessive oxidation can negatively affect the quality of the material surface after machining. As the feed rate and cutting depth increase, the cutting force increases and tool lifespan decreases, but surface oxidation also decreases. In this experiment, the material can be cut to 3 mm of cutting depth. And based on the results of the experiment, the laser assisted machining mechanism is clarified

Energy-efficient electrical machines by new materials. Superconductivity in large electrical machines

International Nuclear Information System (INIS)

Frauenhofer, Joachim; Arndt, Tabea; Grundmann, Joern

2013-01-01

The implementation of superconducting materials in high-power electrical machines results in significant advantages regarding efficiency, size and dynamic behavior when compared to conventional machines. The application of HTS (high-temperature superconductors) in electrical machines allows significantly higher power densities to be achieved for synchronous machines. In order to gain experience with the new technology, Siemens carried out a series of development projects. A 400 kW model motor for the verification of a concept for the new technology was followed by a 4000 kV A generator as highspeed machine - as well as a low-speed 4000 kW propeller motor with high torque. The 4000 kVA generator is still employed to carry out long-term tests and to check components. Superconducting machines have significantly lower weight and envelope dimensions compared to conventional machines, and for this reason alone, they utilize resources better. At the same time, operating losses are slashed to about half and the efficiency increases. Beyond this, they set themselves apart as a result of their special features in operation, such as high overload capability, stiff alternating load behavior and low noise. HTS machines provide significant advantages where the reduction of footprint, weight and losses or the improved dynamic behavior results in significant improvements of the overall system. Propeller motors and generators,for ships, offshore plants, in wind turbine and hydroelectric plants and in large power stations are just some examples. HTS machines can therefore play a significant role when it comes to efficiently using resources and energy as well as reducing the CO 2 emissions.

VIRTUAL MACHINES IN EDUCATION – CNC MILLING MACHINE WITH SINUMERIK 840D CONTROL SYSTEM

Directory of Open Access Journals (Sweden)

Ireneusz Zagórski

2014-11-01

Full Text Available Machining process nowadays could not be conducted without its inseparable element: cutting edge and frequently numerically controlled milling machines. Milling and lathe machining centres comprise standard equipment in many companies of the machinery industry, e.g. automotive or aircraft. It is for that reason that tertiary education should account for this rising demand. This entails the introduction into the curricula the forms which enable visualisation of machining, milling process and virtual production as well as virtual machining centres simulation. Siemens Virtual Machine (Virtual Workshop sets an example of such software, whose high functionality offers a range of learning experience, such as: learning the design of machine tools, their configuration, basic operation functions as well as basics of CNC.

Analysis and design of machine learning techniques evolutionary solutions for regression, prediction, and control problems

CERN Document Server

Stalph, Patrick

2014-01-01

Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain – at least to some extent. Therefore three suitable machine learning algorithms are selected – algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the...

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

Science.gov (United States)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

Machine-to-machine communications architectures, technology, standards, and applications

CERN Document Server

Misic, Vojislav B

2014-01-01

With the number of machine-to-machine (M2M)-enabled devices projected to reach 20 to 50 billion by 2020, there is a critical need to understand the demands imposed by such systems. Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications offers rigorous treatment of the many facets of M2M communication, including its integration with current technology.Presenting the work of a different group of international experts in each chapter, the book begins by supplying an overview of M2M technology. It considers proposed standards, cutting-edge applications, architectures, and traffic modeling and includes case studies that highlight the differences between traditional and M2M communications technology.Details a practical scheme for the forward error correction code designInvestigates the effectiveness of the IEEE 802.15.4 low data rate wireless personal area network standard for use in M2M communicationsIdentifies algorithms that will ensure functionality, performance, reliability, ...

Nonplanar machines

International Nuclear Information System (INIS)

Ritson, D.

1989-05-01

This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

Investigating gaze-controlled input in a cognitive selection test

OpenAIRE

Gayraud, Katja; Hasse, Catrin; Eißfeldt, Hinnerk; Pannasch, Sebastian

2017-01-01

In the field of aviation, there is a growing interest in developing more natural forms of interaction between operators and systems to enhance safety and efficiency. These efforts also include eye gaze as an input channel for human-machine interaction. The present study investigates the application of gaze-controlled input in a cognitive selection test called Eye Movement Conflict Detection Test. The test enables eye movements to be studied as an indicator for psychological test performance a...

Ultraprecision machining. Cho seimitsu kako

Energy Technology Data Exchange (ETDEWEB)

Suga, T [The Univ. of Tokyo, Tokyo (Japan). Research Center for Advanced Science and Technology

1992-10-05

It is said that the image of ultraprecision improved from 0.1[mu]m to 0.01[mu]m within recent years. Ultraprecision machining is a production technology which forms what is called nanotechnology with ultraprecision measuring and ultraprecision control. Accuracy means average machined sizes close to a required value, namely the deflection errors are small; precision means the scattered errors of machined sizes agree very closely. The errors of machining are related to both of the above errors and ultraprecision means the combined errors are very small. In the present ultraprecision machining, the relative precision to the size of a machined object is said to be in the order of 10[sup -6]. The flatness of silicon wafers is usually less than 0.5[mu]m. It is the fact that the appearance of atomic scale machining is awaited as the limit of ultraprecision machining. The machining of removing and adding atomic units using scanning probe microscopes are expected to reach the limit actually. 2 refs.

Theory and practice in machining systems

CERN Document Server

Ito, Yoshimi

2017-01-01

This book describes machining technology from a wider perspective by considering it within the machining space. Machining technology is one of the metal removal activities that occur at the machining point within the machining space. The machining space consists of structural configuration entities, e.g., the main spindle, the turret head and attachments such the chuck and mandrel, and also the form-generating movement of the machine tool itself. The book describes fundamental topics, including the form-generating movement of the machine tool and the important roles of the attachments, before moving on to consider the supply of raw materials into the machining space, and the discharge of swarf from it, and then machining technology itself. Building on the latest research findings “Theory and Practice in Machining System” discusses current challenges in machining. Thus, with the inclusion of introductory and advanced topics, the book can be used as a guide and survey of machining technology for students an...

Face machines

Energy Technology Data Exchange (ETDEWEB)

Hindle, D.

1999-06-01

The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.

Tattoo machines, needles and utilities.

Science.gov (United States)

Rosenkilde, Frank

2015-01-01

Starting out as a professional tattooist back in 1977 in Copenhagen, Denmark, Frank Rosenkilde has personally experienced the remarkable development of tattoo machines, needles and utilities: all the way from home-made equipment to industrial products of substantially improved quality. Machines can be constructed like the traditional dual-coil and single-coil machines or can be e-coil, rotary and hybrid machines, with the more convenient and precise rotary machines being the recent trend. This development has resulted in disposable needles and utilities. Newer machines are more easily kept clean and protected with foil to prevent crosscontaminations and infections. The machines and the tattooists' knowledge and awareness about prevention of infection have developed hand-in-hand. For decades, Frank Rosenkilde has been collecting tattoo machines. Part of his collection is presented here, supplemented by his personal notes. © 2015 S. Karger AG, Basel.

Design of rotating electrical machines

CERN Document Server

Pyrhonen , Juha; Hrabovcova , Valeria

2013-01-01

In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

Identifying cytokine predictors of cognitive functioning in breast cancer survivors up to 10 years post chemotherapy using machine learning.

Science.gov (United States)

Henneghan, Ashley M; Palesh, Oxana; Harrison, Michelle; Kesler, Shelli R

2018-07-15

The purpose of this study is to explore 13 cytokine predictors of chemotherapy-related cognitive impairment (CRCI) in breast cancer survivors (BCS) 6 months to 10 years after chemotherapy completion using a multivariate, non-parametric approach. Cross sectional data collection included completion of a survey, cognitive testing, and non-fasting blood from 66 participants. Data were analyzed using random forest regression to identify the most significant predictors for each of the cognitive test scores. A different cytokine profile predicted each cognitive test. Adjusted R 2 for each model ranged from 0.71-0.77 (p's < 9.50 -10 ). The relationships between all the cytokine predictors and cognitive test scores were non-linear. Our findings are unique to the field of CRCI and suggest non-linear cytokine specificity to neural networks underlying cognitive functions assessed in this study. Copyright © 2018 Elsevier B.V. All rights reserved.

VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

Directory of Open Access Journals (Sweden)

POPESCU Adrian

2015-11-01

Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

MITS machine operations

International Nuclear Information System (INIS)

Flinchem, J.

1980-01-01

This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility

Coordinate measuring machines

DEFF Research Database (Denmark)

De Chiffre, Leonardo

This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...... and uncertainty during coordinate measurements, 3) Digitalisation and Reverse Engineering. This document contains a short description of each step in the exercise and schemes with room for taking notes of the results.......This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceability...

Electric machine

Science.gov (United States)

El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

2012-07-17

An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

Machine Learning and Radiology

Science.gov (United States)

Wang, Shijun; Summers, Ronald M.

2012-01-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

Tribology in machine design

CERN Document Server

Stolarski, Tadeusz

1999-01-01

""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

Directory of Open Access Journals (Sweden)

Woong-Kirl Choi

2018-01-01

Full Text Available Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks.

A Universal Reactive Machine

DEFF Research Database (Denmark)

Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

1997-01-01

Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...

Consequences of heavy machining vis à vis the machine structure – typical applications

International Nuclear Information System (INIS)

Leuch, M

2011-01-01

StarragHeckert has built 5 axis machines since the middle of the 80s for heavy duty milling. The STC-Centres are predominantly utilised in the aerospace industry, especially for milling structural workpieces, casings or Impellers made out of titanium and steel. StarragHeckert has a history of building machines for high performance milling. The machining of these components includes high forces thus spreading the wheat from the chaff. Although FEM calculations and multi-body simulations are carried out in the early stages of development, this paper will illustrate how the real process stability with modal analysis and cutting trials is determined. The experiment observes chatter stability to identify if the machine devices are adequate for the application or if the design has to be improved. Machining parameters of industrial applications are demonstrating the process stability for five axis heavy duties milling of StarragHeckert machine.

Virtual Machine in Automation Projects

OpenAIRE

Xing, Xiaoyuan

2010-01-01

Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper is to examine how to better utilize virtual machine for the automation projects. This paper designs different project scenarios using virtual machine. It analyzes installability, performance and stability of virtual machine from the test results. Technical solutions concerning virtual machine are discussed such as the conversion with physical...

EFFICIENT SPECTRUM UTILIZATION IN COGNITIVE RADIO THROUGH REINFORCEMENT LEARNING

Directory of Open Access Journals (Sweden)

Dhananjay Kumar

2013-09-01

Full Text Available Machine learning schemes can be employed in cognitive radio systems to intelligently locate the spectrum holes with some knowledge about the operating environment. In this paper, we formulate a variation of Actor Critic Learning algorithm known as Continuous Actor Critic Learning Automaton (CACLA and compare this scheme with Actor Critic Learning scheme and existing Q–learning scheme. Simulation results show that our CACLA scheme has lesser execution time and achieves higher throughput compared to other two schemes.

The Buttonhole Machine. Module 13.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the bottonhole machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers two topics: performing special operations on the buttonhole machine (parts and purpose) and performing special operations on the buttonhole machine (gauged buttonholes). For each topic these components are…

Introduction to machine learning.

Science.gov (United States)

Baştanlar, Yalin; Ozuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

Applied machining technology

CERN Document Server

Tschätsch, Heinz

2010-01-01

Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

Evaluating Effects of Heat Stress on Cognitive Function among Workers in a Hot Industry

Directory of Open Access Journals (Sweden)

Adel Mazloumi

2014-12-01

Full Text Available Background:Heat stress, as one of the most common occupational health problems, can impair operators' cognitive processes. The aim of this study was to evaluate the impact of thermal stress on cognitive function among workers in a hot industry. Methods: In this cross-sectional study conducted in Malibel Saipa Company in 2013, workers were assigned into two groups: one group were exposed to heat stress (n=35, working in casting unit and the other group working in machin-ing unit (n=35 with a normal air conditioning. Wet Bulb Globe Temperature was measured at three heights of ankle, abdomen, and head. In order to evalu-ate the effects of heat stress on attention and reaction time, Stroop tests 1, 2, and 3 were conducted before starting the work and during the work. Results: A significant positive correlation was observed between WBGT and test duration (P=0.01 and reaction time of Stroop test 3 (P=0.047, and be-tween number of errors in Stroop tests 1, 2, and 3, during the work (P= 0.001. Moreover, Stroop test 3 showed a significant higher score for both test dura-tion and reaction time of workers in case group. Conclusion: Results of the present study, conducted in a real work environment, confirmed the impairment of cognitive functions, including selective attention and reaction time, under heat stress conditions.

HUMAN RELIABILITY ANALYSIS DENGAN PENDEKATAN COGNITIVE RELIABILITY AND ERROR ANALYSIS METHOD (CREAM

Directory of Open Access Journals (Sweden)

Zahirah Alifia Maulida

2015-01-01

Full Text Available Kecelakaan kerja pada bidang grinding dan welding menempati urutan tertinggi selama lima tahun terakhir di PT. X. Kecelakaan ini disebabkan oleh human error. Human error terjadi karena pengaruh lingkungan kerja fisik dan non fisik.Penelitian kali menggunakan skenario untuk memprediksi serta mengurangi kemungkinan terjadinya error pada manusia dengan pendekatan CREAM (Cognitive Reliability and Error Analysis Method. CREAM adalah salah satu metode human reliability analysis yang berfungsi untuk mendapatkan nilai Cognitive Failure Probability (CFP yang dapat dilakukan dengan dua cara yaitu basic method dan extended method. Pada basic method hanya akan didapatkan nilai failure probabailty secara umum, sedangkan untuk extended method akan didapatkan CFP untuk setiap task. Hasil penelitian menunjukkan faktor- faktor yang mempengaruhi timbulnya error pada pekerjaan grinding dan welding adalah kecukupan organisasi, kecukupan dari Man Machine Interface (MMI & dukungan operasional, ketersediaan prosedur/ perencanaan, serta kecukupan pelatihan dan pengalaman. Aspek kognitif pada pekerjaan grinding yang memiliki nilai error paling tinggi adalah planning dengan nilai CFP 0.3 dan pada pekerjaan welding yaitu aspek kognitif execution dengan nilai CFP 0.18. Sebagai upaya untuk mengurangi nilai error kognitif pada pekerjaan grinding dan welding rekomendasi yang diberikan adalah memberikan training secara rutin, work instrucstion yang lebih rinci dan memberikan sosialisasi alat. Kata kunci: CREAM (cognitive reliability and error analysis method, HRA (human reliability analysis, cognitive error Abstract The accidents in grinding and welding sectors were the highest cases over the last five years in PT. X and it caused by human error. Human error occurs due to the influence of working environment both physically and non-physically. This study will implement an approaching scenario called CREAM (Cognitive Reliability and Error Analysis Method. CREAM is one of human

Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

2017-04-21

The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

Machine Protection

International Nuclear Information System (INIS)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

Machine Protection

Energy Technology Data Exchange (ETDEWEB)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)

2012-07-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Machine Protection

CERN Document Server

Zerlauth, Markus; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Dictionary of machine terms

International Nuclear Information System (INIS)

1990-06-01

This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.

HTS machine laboratory prototype

DEFF Research Database (Denmark)

machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

2011-01-01

Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

OpenAIRE

Parker, David L.; Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardize...

Machine vision systems using machine learning for industrial product inspection

Science.gov (United States)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Machine Directional Register System Modeling for Shaft-Less Drive Gravure Printing Machines

Directory of Open Access Journals (Sweden)

Shanhui Liu

2013-01-01

Full Text Available In the latest type of gravure printing machines referred to as the shaft-less drive system, each gravure printing roller is driven by an individual servo motor, and all motors are electrically synchronized. The register error is regulated by a speed difference between the adjacent printing rollers. In order to improve the control accuracy of register system, an accurate mathematical model of the register system should be investigated for the latest machines. Therefore, the mathematical model of the machine directional register (MDR system is studied for the multicolor gravure printing machines in this paper. According to the definition of the MDR error, the model is derived, and then it is validated by the numerical simulation and experiments carried out in the experimental setup of the four-color gravure printing machines. The results show that the established MDR system model is accurate and reliable.

Machine learning and radiology.

Science.gov (United States)

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Machining with abrasives

CERN Document Server

Jackson, Mark J

2011-01-01

Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

The Knife Machine. Module 15.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

Restrictions of process machine retooling at machine-building enterprises

Directory of Open Access Journals (Sweden)

Kuznetsova Elena

2017-01-01

Full Text Available The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of up-to-date equipment, and drop in its use efficiency. The article investigates and classifies the main restrictions of the manufacturing equipment renewal process, such as regulatory and legislative, financial, organizational, competency-based. The economic consequences of the revealed restrictions influence on the machine-building enterprises activity are shown.

Cognitive Radio for Smart Grid: Theory, Algorithms, and Security

Directory of Open Access Journals (Sweden)

Raghuram Ranganathan

2011-01-01

Full Text Available Recently, cognitive radio and smart grid are two areas which have received considerable research impetus. Cognitive radios are intelligent software defined radios (SDRs that efficiently utilize the unused regions of the spectrum, to achieve higher data rates. The smart grid is an automated electric power system that monitors and controls grid activities. In this paper, the novel concept of incorporating a cognitive radio network as the communications infrastructure for the smart grid is presented. A brief overview of the cognitive radio, IEEE 802.22 standard and smart grid, is provided. Experimental results obtained by using dimensionality reduction techniques such as principal component analysis (PCA, kernel PCA, and landmark maximum variance unfolding (LMVU on Wi-Fi signal measurements are presented in a spectrum sensing context. Furthermore, compressed sensing algorithms such as Bayesian compressed sensing and the compressed sensing Kalman filter is employed for recovering the sparse smart meter transmissions. From the power system point of view, a supervised learning method called support vector machine (SVM is used for the automated classification of power system disturbances. The impending problem of securing the smart grid is also addressed, in addition to the possibility of applying FPGA-based fuzzy logic intrusion detection for the smart grid.

Eco-Cognitive Computationalism: From Mimetic Minds to Morphology-Based Enhancement of Mimetic Bodies

Directory of Open Access Journals (Sweden)

Lorenzo Magnani

2018-06-01

Full Text Available Eco-cognitive computationalism sees computation in context, exploiting the ideas developed in those projects that have originated the recent views on embodied, situated, and distributed cognition. Turing’s original intellectual perspective has already clearly depicted the evolutionary emergence in humans of information, meaning, and of the first rudimentary forms of cognition, as the result of a complex interplay and simultaneous coevolution, in time, of the states of brain/mind, body, and external environment. This cognitive process played a fundamental heuristic role in Turing’s invention of the universal logical computing machine. It is by extending this eco-cognitive perspective that we can see that the recent emphasis on the simplification of cognitive and motor tasks generated in organic agents by morphological aspects implies the construction of appropriate “mimetic bodies”, able to render the accompanied computation simpler, according to a general appeal to the “simplexity” of animal embodied cognition. I hope it will become clear that eco-cognitive computationalism does not aim at furnishing a final and stable definition of the concept of computation, such as a textbook or a different epistemological approach could provide: I intend to take into account the historical and dynamical character of the concept, to propose an intellectual framework that depicts how we can understand not only the change of its meaning, but also the “emergence” of new forms of computations.

Mechanical design of machine components

CERN Document Server

Ugural, Ansel C

2015-01-01

Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

Soft computing in machine learning

CERN Document Server

Park, Jooyoung; Inoue, Atsushi

2014-01-01

As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

Mankind, machines and people

Energy Technology Data Exchange (ETDEWEB)

Hugli, A

1984-01-01

The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.

A Concrete Framework for Environment Machines

DEFF Research Database (Denmark)

Biernacka, Malgorzata; Danvy, Olivier

2007-01-01

calculus with explicit substitutions), we extend it minimally so that it can also express one-step reduction strategies, and we methodically derive a series of environment machines from the specification of two one-step reduction strategies for the lambda-calculus: normal order and applicative order....... The derivation extends Danvy and Nielsen’s refocusing-based construction of abstract machines with two new steps: one for coalescing two successive transitions into one, and the other for unfolding a closure into a term and an environment in the resulting abstract machine. The resulting environment machines...... include both the Krivine machine and the original version of Krivine’s machine, Felleisen et al.’s CEK machine, and Leroy’s Zinc abstract machine....

A methodology for the characterization and diagnosis of cognitive impairments-Application to specific language impairment.

Science.gov (United States)

Oliva, Jesús; Serrano, J Ignacio; del Castillo, M Dolores; Iglesias, Angel

2014-06-01

The diagnosis of mental disorders is in most cases very difficult because of the high heterogeneity and overlap between associated cognitive impairments. Furthermore, early and individualized diagnosis is crucial. In this paper, we propose a methodology to support the individualized characterization and diagnosis of cognitive impairments. The methodology can also be used as a test platform for existing theories on the causes of the impairments. We use computational cognitive modeling to gather information on the cognitive mechanisms underlying normal and impaired behavior. We then use this information to feed machine-learning algorithms to individually characterize the impairment and to differentiate between normal and impaired behavior. We apply the methodology to the particular case of specific language impairment (SLI) in Spanish-speaking children. The proposed methodology begins by defining a task in which normal and individuals with impairment present behavioral differences. Next we build a computational cognitive model of that task and individualize it: we build a cognitive model for each participant and optimize its parameter values to fit the behavior of each participant. Finally, we use the optimized parameter values to feed different machine learning algorithms. The methodology was applied to an existing database of 48 Spanish-speaking children (24 normal and 24 SLI children) using clustering techniques for the characterization, and different classifier techniques for the diagnosis. The characterization results show three well-differentiated groups that can be associated with the three main theories on SLI. Using a leave-one-subject-out testing methodology, all the classifiers except the DT produced sensitivity, specificity and area under curve values above 90%, reaching 100% in some cases. The results show that our methodology is able to find relevant information on the underlying cognitive mechanisms and to use it appropriately to provide better

Findings From the National Machine Guarding Program-A Small Business Intervention: Machine Safety.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Xi, Min; Brosseau, Lisa M; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2016-09-01

The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P increase in LOTO program scores (P < 0.0001). Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees.

Deciphering CAPTCHAs: what a Turing test reveals about human cognition.

Directory of Open Access Journals (Sweden)

Thomas Hannagan

Full Text Available Turning Turing's logic on its head, we used widespread letter-based Turing Tests found on the internet (CAPTCHAs to shed light on human cognition. We examined the basis of the human ability to solve CAPTCHAs, where machines fail. We asked whether this is due to our use of slow-acting inferential processes that would not be available to machines, or whether fast-acting automatic orthographic processing in humans has superior robustness to shape variations. A masked priming lexical decision experiment revealed efficient processing of CAPTCHA words in conditions that rule out the use of slow inferential processing. This shows that the human superiority in solving CAPTCHAs builds on a high degree of invariance to location and continuous transforms, which is achieved during the very early stages of visual word recognition in skilled readers.

Switching Brains: Cloud-based Intelligent Resources Management for the Internet of Cognitive Things

Directory of Open Access Journals (Sweden)

R. Francisco

2014-05-01

Full Text Available Cognitive technologies can bring important benefits to our everyday life, enabling connected devices to do tasks that in the past only humans could do, leading to the Cognitive Internet of Things. Wireless Sensor and Actuator Networks (WSAN are often employed for communication between Internet objects. However, WSAN face some problems, namely sensors’ energy and CPU load consumption, which are common to other networked devices, such as mobile devices or robotic platforms. Additionally, cognitive functionalities often require large processing power, for running machine learning algorithms, computer vision processing, or behavioral and emotional architectures. Cloud massive storage capacity, large processing speeds and elasticity are appropriate to address these problems. This paper proposes a middleware that transfers flows of execution between devices and the cloud for computationally demanding applications (such as those integrating a robotic brain, to efficiently manage devices’ resources.

Research on the proficient machine system. Theoretical part; Jukutatsu machine system no chosa kenkyu. Rironhen

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-03-01

The basic theory of the proficient machine system to be developed was studied. Important proficient techniques in manufacturing industries are becoming extinct because of insufficient succession to next generation. The proficient machine system was proposed to cope with such situation. This machine system includes the mechanism for progress and evolution of techniques and sensibilities to be adaptable to environmental changes by learning and recognizing various motions such as work and process. Consequently, the basic research fields are composed of thought, learning, perception and action. This machine requires not only deigned fixed functions but also introduction of the same proficient concept as human being to be adaptable to changes in situation, purpose, time and machine`s complexity. This report explains in detail the basic concept, system principle, approaching procedure and practical elemental technologies of the proficient machine system, and also describes the future prospect. 133 refs., 110 figs., 7 tabs.

Machining of uranium and uranium alloys

International Nuclear Information System (INIS)

Morris, T.O.

1981-01-01

Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures

[Comparison of machinability of two types of dental machinable ceramic].

Science.gov (United States)

Fu, Qiang; Zhao, Yunfeng; Li, Yong; Fan, Xinping; Li, Yan; Lin, Xuefeng

2002-11-01

In terms of the problems of now available dental machinable ceramics, a new type of calcium-mica glass-ceramic, PMC-I ceramic, was developed, and its machinability was compared with that of Vita MKII quantitatively. Moreover, the relationship between the strength and the machinability of PMC-I ceramic was studied. Samples of PMC-I ceramic were divided into four groups according to their nucleation procedures. 600-seconds drilling tests were conducted with high-speed steel tools (Phi = 2.3 mm) to measure the drilling depths of Vita MKII ceramic and PMC-I ceramic, while constant drilling speed of 600 rpm and constant axial load of 39.2 N were used. And the 3-point bending strength of the four groups of PMC-I ceramic were recorded. Drilling depth of Vita MKII was 0.71 mm, while the depths of the four groups of PMC-I ceramic were 0.88 mm, 1.40 mm, 0.40 mm and 0.90 mm, respectively. Group B of PMC-I ceramic showed the largest depth of 1.40 mm and was statistically different from other groups and Vita MKII. And the strength of the four groups of PMC-I ceramic were 137.7, 210.2, 118.0 and 106.0 MPa, respectively. The machinability of the new developed dental machinable ceramic of PMC-I could meet the need of the clinic.

Novel Machine Learning-Based Techniques for Efficient Resource Allocation in Next Generation Wireless Networks

KAUST Repository

AlQuerm, Ismail A.

2018-02-21

There is a large demand for applications of high data rates in wireless networks. These networks are becoming more complex and challenging to manage due to the heterogeneity of users and applications specifically in sophisticated networks such as the upcoming 5G. Energy efficiency in the future 5G network is one of the essential problems that needs consideration due to the interference and heterogeneity of the network topology. Smart resource allocation, environmental adaptivity, user-awareness and energy efficiency are essential features in the future networks. It is important to support these features at different networks topologies with various applications. Cognitive radio has been found to be the paradigm that is able to satisfy the above requirements. It is a very interdisciplinary topic that incorporates flexible system architectures, machine learning, context awareness and cooperative networking. Mitola’s vision about cognitive radio intended to build context-sensitive smart radios that are able to adapt to the wireless environment conditions while maintaining quality of service support for different applications. Artificial intelligence techniques including heuristics algorithms and machine learning are the shining tools that are employed to serve the new vision of cognitive radio. In addition, these techniques show a potential to be utilized in an efficient resource allocation for the upcoming 5G networks’ structures such as heterogeneous multi-tier 5G networks and heterogeneous cloud radio access networks due to their capability to allocate resources according to real-time data analytics. In this thesis, we study cognitive radio from a system point of view focusing closely on architectures, artificial intelligence techniques that can enable intelligent radio resource allocation and efficient radio parameters reconfiguration. We propose a modular cognitive resource management architecture, which facilitates a development of flexible control for

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

OpenAIRE

Ming Cheng; Le Sun; Giuseppe Buja; Lihua Song

2015-01-01

The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs). Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator perm...

The First International Workshop on Human and Machine Cognition, Pensacola, Florida. Topic: The Frame Problem

OpenAIRE

Dietrich, Eric

1990-01-01

For some of us, the "Frame Problem Workshop" (as it was called) was an opportunity to discuss a methodological question which has become important in AI and cognitive science: Is the frame problem profound or a mistake?

Findings from the National Machine Guarding Program–A Small Business Intervention: Machine Safety

Science.gov (United States)

Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 – 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of OSHA citations and may result in serious traumatic injury. Methods Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits and a twelve-month follow-up evaluation. Results The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10-percentage point increase in business-level machine scores (p< 0.0001) and a 33-percentage point increase in LOTO program scores (p <0.0001). Conclusions Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:26716850

Machine Tool Software

Science.gov (United States)

1988-01-01

A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

Machine Ethics: Creating an Ethical Intelligent Agent

OpenAIRE

Anderson, Michael; Anderson, Susan Leigh

2007-01-01

The newly emerging field of machine ethics (Anderson and Anderson 2006) is concerned with adding an ethical dimension to machines. Unlike computer ethics -- which has traditionally focused on ethical issues surrounding humans' use of machines -- machine ethics is concerned with ensuring that the behavior of machines toward human users, and perhaps other machines as well, is ethically acceptable. In this article we discuss the importance of machine ethics, the need for machines that represent ...

Nanocomposites for Machining Tools

Directory of Open Access Journals (Sweden)

Daria Sidorenko

2017-10-01

Full Text Available Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

Machine learning with R

CERN Document Server

Lantz, Brett

2013-01-01

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

Restrictions of process machine retooling at machine-building enterprises

OpenAIRE

Kuznetsova Elena; Tipner Ludmila; Ershov Alexey

2017-01-01

The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of...

Pattern recognition & machine learning

CERN Document Server

Anzai, Y

1992-01-01

This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

Parallel-Machine Scheduling with Time-Dependent and Machine Availability Constraints

Directory of Open Access Journals (Sweden)

Cuixia Miao

2015-01-01

Full Text Available We consider the parallel-machine scheduling problem in which the machines have availability constraints and the processing time of each job is simple linear increasing function of its starting times. For the makespan minimization problem, which is NP-hard in the strong sense, we discuss the Longest Deteriorating Rate algorithm and List Scheduling algorithm; we also provide a lower bound of any optimal schedule. For the total completion time minimization problem, we analyze the strong NP-hardness, and we present a dynamic programming algorithm and a fully polynomial time approximation scheme for the two-machine problem. Furthermore, we extended the dynamic programming algorithm to the total weighted completion time minimization problem.

The Hooey Machine.

Science.gov (United States)

Scarnati, James T.; Tice, Craig J.

1992-01-01

Describes how students can make and use Hooey Machines to learn how mechanical energy can be transferred from one object to another within a system. The Hooey Machine is made using a pencil, eight thumbtacks, one pushpin, tape, scissors, graph paper, and a plastic lid. (PR)

Machine Vision Handbook

CERN Document Server

2012-01-01

The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook  equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in insp...

Effect of the Machined Surfaces of AISI 4337 Steel to Cutting Conditions on Dry Machining Lathe

Science.gov (United States)

Rahim, Robbi; Napid, Suhardi; Hasibuan, Abdurrozzaq; Rahmah Sibuea, Siti; Yusmartato, Y.

2018-04-01

The objective of the research is to obtain a cutting condition which has a good chance of realizing dry machining concept on AISI 4337 steel material by studying surface roughness, microstructure and hardness of machining surface. The data generated from the experiment were then processed and analyzed using the standard Taguchi method L9 (34) orthogonal array. Testing of dry and wet machining used surface test and micro hardness test for each of 27 test specimens. The machining results of the experiments showed that average surface roughness (Raavg) was obtained at optimum cutting conditions when VB 0.1 μm, 0.3 μm and 0.6 μm respectively 1.467 μm, 2.133 μm and 2,800 μm fo r dry machining while which was carried out by wet machining the results obtained were 1,833 μm, 2,667 μm and 3,000 μm. It can be concluded that dry machining provides better surface quality of machinery results than wet machining. Therefore, dry machining is a good choice that may be realized in the manufacturing and automotive industries.

Evaluation of machinability and flexural strength of a novel dental machinable glass-ceramic.

Science.gov (United States)

Qin, Feng; Zheng, Shucan; Luo, Zufeng; Li, Yong; Guo, Ling; Zhao, Yunfeng; Fu, Qiang

2009-10-01

To evaluate the machinability and flexural strength of a novel dental machinable glass-ceramic (named PMC), and to compare the machinability property with that of Vita Mark II and human enamel. The raw batch materials were selected and mixed. Four groups of novel glass-ceramics were formed at different nucleation temperatures, and were assigned to Group 1, Group 2, Group 3 and Group 4. The machinability of the four groups of novel glass-ceramics, Vita Mark II ceramic and freshly extracted human premolars were compared by means of drilling depth measurement. A three-point bending test was used to measure the flexural strength of the novel glass-ceramics. The crystalline phases of the group with the best machinability were identified by X-ray diffraction. In terms of the drilling depth, Group 2 of the novel glass-ceramics proves to have the largest drilling depth. There was no statistical difference among Group 1, Group 4 and the natural teeth. The drilling depth of Vita MK II was statistically less than that of Group 1, Group 4 and the natural teeth. Group 3 had the least drilling depth. In respect of the flexural strength, Group 2 exhibited the maximum flexural strength; Group 1 was statistically weaker than Group 2; there was no statistical difference between Group 3 and Group 4, and they were the weakest materials. XRD of Group 2 ceramic showed that a new type of dental machinable glass-ceramic containing calcium-mica had been developed by the present study and was named PMC. PMC is promising for application as a dental machinable ceramic due to its good machinability and relatively high strength.

Adaptive multi-objective Optimization scheme for cognitive radio resource management

KAUST Repository

Alqerm, Ismail

2014-12-01

Cognitive Radio is an intelligent Software Defined Radio that is capable to alter its transmission parameters according to predefined objectives and wireless environment conditions. Cognitive engine is the actuator that performs radio parameters configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance. The optimization relies on adapting radio transmission parameters to environment conditions using constrained optimization modeling called fitness functions in an iterative manner. These functions include minimizing power consumption, Bit Error Rate, delay and interference. On the other hand, maximizing throughput and spectral efficiency. Cross-layer optimization is exploited to access environmental parameters from all TCP/IP stack layers. AMOS uses adaptive Genetic Algorithm in terms of its parameters and objective weights as the vehicle of optimization. The proposed scheme has demonstrated quick response and efficiency in three different scenarios compared to other schemes. In addition, it shows its capability to optimize the performance of TCP/IP layers as whole not only the physical layer.

Machining a glass rod with a lathe-type electro-chemical discharge machine

International Nuclear Information System (INIS)

Furutani, Katsushi; Maeda, Hideaki

2008-01-01

This paper deals with the performance of electro-chemical discharge machining (ECDM) of a revolving glass rod. ECDM has been studied for machining insulating materials such as glass and ceramics. In conventional ECDM, an insulating workpiece is dipped in an electrolyte as a working fluid and a tool electrode is pressed on the surface with a small load. In the experiments, a workpiece was revolved to provide fresh working fluid into a gap between the tool electrode and the workpiece. A soda lime grass rod was machined with a thin tungsten rod in NaCl solution. The applied voltage was changed up to 40 V. The rotation speed was set to 0, 0.3, 3 and 30 min −1 . Discharge was observed over an applied voltage of 30 V. The width and depth of the machined grooves and the surface roughness of their bottom were increased with increase of the applied voltage. Although the depth of machining at 3 min −1 was the same as that at 30 min −1 , the width and roughness at 30 min −1 were smaller than those at 3 min −1 . Moreover, because the thickness of vaporization around the tool electrode was decreased with increase of the rotation speed, the width of the machined groove became smaller

An HTS machine laboratory prototype

DEFF Research Database (Denmark)

Mijatovic, Nenad; Jensen, Bogi Bech; Træholt, Chresten

2012-01-01

This paper describes Superwind HTS machine laboratory setup which is a small scale HTS machine designed and build as a part of the efforts to identify and tackle some of the challenges the HTS machine design may face. One of the challenges of HTS machines is a Torque Transfer Element (TTE) which...... conduction compared to a shaft. The HTS machine was successfully cooled to 77K and tests have been performed. The IV curves of the HTS field winding employing 6 HTS coils indicate that two of the coils had been damaged. The maximal value of the torque during experiments of 78Nm was recorded. Loaded with 33...

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators; Raisonnement causal et modelisation de l`activite cognitive d`operateurs de chaufferie nucleaire navale

Energy Technology Data Exchange (ETDEWEB)

Salazar-Ferrer, P

1995-06-01

In complex industrial process control, causal reasoning appears as a major component in operators` cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs.

LHC Report: machine development

CERN Multimedia

Rogelio Tomás García for the LHC team

2015-01-01

Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

Probability distribution of machining center failures

International Nuclear Information System (INIS)

Jia Yazhou; Wang Molin; Jia Zhixin

1995-01-01

Through field tracing research for 24 Chinese cutter-changeable CNC machine tools (machining centers) over a period of one year, a database of operation and maintenance for machining centers was built, the failure data was fitted to the Weibull distribution and the exponential distribution, the effectiveness was tested, and the failure distribution pattern of machining centers was found. Finally, the reliability characterizations for machining centers are proposed

Student Modeling and Machine Learning

OpenAIRE

Sison , Raymund; Shimura , Masamichi

1998-01-01

After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

The Newest Machine Material

International Nuclear Information System (INIS)

Seo, Yeong Seop; Choe, Byeong Do; Bang, Meong Sung

2005-08-01

This book gives descriptions of machine material with classification of machine material and selection of machine material, structure and connection of material, coagulation of metal and crystal structure, equilibrium diagram, properties of metal material, elasticity and plasticity, biopsy of metal, material test and nondestructive test. It also explains steel material such as heat treatment of steel, cast iron and cast steel, nonferrous metal materials, non metallic materials, and new materials.

Introduction to machine learning

OpenAIRE

Baştanlar, Yalın; Özuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning app...

Support vector machines applications

CERN Document Server

Guo, Guodong

2014-01-01

Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.

Machinability of advanced materials

CERN Document Server

Davim, J Paulo

2014-01-01

Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

Nuclear reactor machine refuelling system

International Nuclear Information System (INIS)

Cashen, W.S.; Erwin, D.

1977-01-01

Part of an on-line fuelling machine for a CANDU pressure-tube reactor is described. The present invention provides a refuelling machine wherein the fuelling components, including the fuel carrier and the closure adapter, are positively positioned and retained within the machine magazine or positively secured to the machine charge tube head, and cannot be accidentally disengaged as in former practice. The positive positioning devices include an arcuate keeper plate. Simplified hooked fingers are used. (NDH)

Machine Translation Effect on Communication

DEFF Research Database (Denmark)

Jensen, Mika Yasuoka; Bjørn, Pernille

2011-01-01

Intercultural collaboration facilitated by machine translation has gradually spread in various settings. Still, little is known as for the practice of machine-translation mediated communication. This paper investigates how machine translation affects intercultural communication in practice. Based...... on communication in which multilingual communication system is applied, we identify four communication types and its’ influences on stakeholders’ communication process, especially focusing on establishment and maintenance of common ground. Different from our expectation that quality of machine translation results...

Machining of Complex Sculptured Surfaces

CERN Document Server

2012-01-01

The machining of complex sculptured surfaces is a global technological topic in modern manufacturing with relevance in both industrialized and emerging in countries particularly within the moulds and dies sector whose applications include highly technological industries such as the automotive and aircraft industry. Machining of Complex Sculptured Surfaces considers new approaches to the manufacture of moulds and dies within these industries. The traditional technology employed in the manufacture of moulds and dies combined conventional milling and electro-discharge machining (EDM) but this has been replaced with  high-speed milling (HSM) which has been applied in roughing, semi-finishing and finishing of moulds and dies with great success. Machining of Complex Sculptured Surfaces provides recent information on machining of complex sculptured surfaces including modern CAM systems and process planning for three and five axis machining as well as explanations of the advantages of HSM over traditional methods ra...

Formal modeling of virtual machines

Science.gov (United States)

Cremers, A. B.; Hibbard, T. N.

1978-01-01

Systematic software design can be based on the development of a 'hierarchy of virtual machines', each representing a 'level of abstraction' of the design process. The reported investigation presents the concept of 'data space' as a formal model for virtual machines. The presented model of a data space combines the notions of data type and mathematical machine to express the close interaction between data and control structures which takes place in a virtual machine. One of the main objectives of the investigation is to show that control-independent data type implementation is only of limited usefulness as an isolated tool of program development, and that the representation of data is generally dictated by the control context of a virtual machine. As a second objective, a better understanding is to be developed of virtual machine state structures than was heretofore provided by the view of the state space as a Cartesian product.

Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

Science.gov (United States)

Pekkala, Timo; Hall, Anette; Lötjönen, Jyrki; Mattila, Jussi; Soininen, Hilkka; Ngandu, Tiia; Laatikainen, Tiina; Kivipelto, Miia; Solomon, Alina

2017-01-01

This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study. The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC). AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype. The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions.

Design Control Systems of Human Machine Interface in the NTVS-2894 Seat Grinder Machine to Increase the Productivity

Science.gov (United States)

Ardi, S.; Ardyansyah, D.

2018-02-01

In the Manufacturing of automotive spare parts, increased sales of vehicles is resulted in increased demand for production of engine valve of the customer. To meet customer demand, we carry out improvement and overhaul of the NTVS-2894 seat grinder machine on a machining line. NTVS-2894 seat grinder machine has been decreased machine productivity, the amount of trouble, and the amount of downtime. To overcome these problems on overhaul the NTVS-2984 seat grinder machine include mechanical and programs, is to do the design and manufacture of HMI (Human Machine Interface) GP-4501T program. Because of the time prior to the overhaul, NTVS-2894 seat grinder machine does not have a backup HMI (Human Machine Interface) program. The goal of the design and manufacture in this program is to improve the achievement of production, and allows an operator to operate beside it easier to troubleshoot the NTVS-2894 seat grinder machine thereby reducing downtime on the NTVS-2894 seat grinder machine. The results after the design are HMI program successfully made it back, machine productivity increased by 34.8%, the amount of trouble, and downtime decreased 40% decrease from 3,160 minutes to 1,700 minutes. The implication of our design, it could facilitate the operator in operating machine and the technician easer to maintain and do the troubleshooting the machine problems.

Permutation parity machines for neural synchronization

International Nuclear Information System (INIS)

Reyes, O M; Kopitzke, I; Zimmermann, K-H

2009-01-01

Synchronization of neural networks has been studied in recent years as an alternative to cryptographic applications such as the realization of symmetric key exchange protocols. This paper presents a first view of the so-called permutation parity machine, an artificial neural network proposed as a binary variant of the tree parity machine. The dynamics of the synchronization process by mutual learning between permutation parity machines is analytically studied and the results are compared with those of tree parity machines. It will turn out that for neural synchronization, permutation parity machines form a viable alternative to tree parity machines

Manipulator for plasma-assisted machining of components made of materials with low machinability

International Nuclear Information System (INIS)

Lyaoshchukov, M.M.; Agadzhanyan, R.A.

1984-01-01

The All-Union Scientific-Research and Technological Institute of Pump Engineering developed, and the ''Uralgidromash'' Production Association has adopted, a manipulator with remote control for the plasma-assisted machining (PAM) of components made of materials with low machinability. The manipulator is distinguished by its universal design and can be used for machining both external and internal surfaces of the bodies of revolution and also end faces and various curvilinear surfaces

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

Science.gov (United States)

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

29 CFR 1910.218 - Forging machines.

Science.gov (United States)

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Forging machines. 1910.218 Section 1910.218 Labor... OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.218 Forging machines. (a... other identifier, for the forging machine which was inspected. (ii) Scheduling and recording the...

The achievements of the Z-machine

International Nuclear Information System (INIS)

Larousserie, D.

2008-01-01

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Vector control of induction machines

CERN Document Server

Robyns, Benoit

2012-01-01

After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, ""Vector Control of Induction Machines"" introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies. The use of causal ordering graphs allows systematization of the design stage, as well as standardization of the structure of control devices. ""Vector Control of Induction Machines"" suggests a unique approach aimed at reducing parameter sensitivity for

Damage to insula abolishes cognitive distortions during simulated gambling.

Science.gov (United States)

Clark, Luke; Studer, Bettina; Bruss, Joel; Tranel, Daniel; Bechara, Antoine

2014-04-22

Gambling is a naturalistic example of risky decision-making. During gambling, players typically display an array of cognitive biases that create a distorted expectancy of winning. This study investigated brain regions underpinning gambling-related cognitive distortions, contrasting patients with focal brain lesions to the ventromedial prefrontal cortex (vmPFC), insula, or amygdala ("target patients") against healthy comparison participants and lesion comparison patients (i.e., with lesions that spare the target regions). A slot machine task was used to deliver near-miss outcomes (i.e., nonwins that fall spatially close to a jackpot), and a roulette game was used to examine the gambler's fallacy (color decisions following outcome runs). Comparison groups displayed a heightened motivation to play following near misses (compared with full misses), and manifested a classic gambler's fallacy effect. Both effects were also observed in patients with vmPFC and amygdala damage, but were absent in patients with insula damage. Our findings indicate that the distorted cognitive processing of near-miss outcomes and event sequences may be ordinarily supported by the recruitment of the insula. Interventions to reduce insula reactivity could show promise in the treatment of disordered gambling.

The Chainstitch Machine. Module 18.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the chainstitch machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the chainstitch machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and…

Machine Shop Fundamentals: Part I.

Science.gov (United States)

Kelly, Michael G.; And Others

These instructional materials were developed and designed for secondary and adult limited English proficient students enrolled in machine tool technology courses. Part 1 includes 24 lessons covering introduction, safety and shop rules, basic machine tools, basic machine operations, measurement, basic blueprint reading, layout, and bench tools.…

Machining dynamics fundamentals, applications and practices

CERN Document Server

Cheng, Kai

2008-01-01

Machining dynamics are vital to the performance of machine tools and machining processes in manufacturing. This book discusses the state-of-the-art applications, practices and research in machining dynamics. It presents basic theory, analysis and control methodology. It is useful for manufacturing engineers, supervisors, engineers and designers.

Investigation of permanent magnet machines for downhole applications: Design, prototype and testing of a flux-switching permanent magnet machine

Energy Technology Data Exchange (ETDEWEB)

Chen, Anyuan

2011-01-15

The current standard electrical downhole machine is the induction machine which is relatively inefficient. Permanent magnet (PM) machines, having higher efficiencies, higher torque densities and smaller volumes, have widely employed in industrial applications to replace conventional machines, but few have been developed for downhole applications due to the high ambient temperatures in deep wells and the low temperature stability of PM materials over time. Today, with the development of variable speed drives and the applications of high temperature magnet materials, it is increasingly interesting for oil and gas industries to develop PM machines for downhole applications. Recently, some PM machines applications have been presented for downhole applications, which are normally addressed on certain specific downhole case. In this thesis the focus has been put on the performance investigation of different PM machines for general downhole cases, in which the machine outer diameter is limited to be small by well size, while the machine axial length may be relatively long. The machine reliability is the most critical requirement while high torque density and high efficiency are also desirable. The purpose is to understand how the special constraints in downhole condition affect the performances of different machines. First of all, three basic machine concepts, which are the radial, axial and transverse flux machines, are studied in details by analytical method. Their torque density, efficiency, power factor and power capability are investigated with respect to the machine axial length and pole number. The presented critical performance comparisons of the machines provide an indication of machines best suitable with respect to performance and size for downhole applications. Conventional radial flux permanent magnet (RFPM) machines with the PMs on the rotor can provide high torque density and high efficiency. This type of machine has been suggested for several different

Electrical machining method of insulating ceramics

International Nuclear Information System (INIS)

Fukuzawa, Y.; Mohri, N.; Tani, T.

1999-01-01

This paper describes a new electrical discharge machining method for insulating ceramics using an assisting electrode with either a sinking electrical discharge machine or a wire electrical discharge machine. In this method, the metal sheet or mesh is attached to the ceramic surface as an assisting material for the discharge generation around the insulator surface. When the machining condition changes from the attached material to the workpiece, a cracked carbon layer is formed on the workpiece surface. As this layer has an electrical conductivity, electrical discharge occurs in working oil between the tool electrode and the surface of the workpiece. The carbon is formed from the working oil during this electrical discharge. Even after the material is machined, an electrical discharge occurs in the gap region between the tool electrode and the ceramic because an electrically conductive layer is generated continuously. Insulating ceramics can be machined by the electrical discharge machining method using the above mentioned surface modification phenomenon. In this paper the authors show a machined example demonstrating that the proposed method is available for machining a complex shape on insulating ceramics. Copyright (1999) AD-TECH - International Foundation for the Advancement of Technology Ltd

Advanced SLARette delivery machine

International Nuclear Information System (INIS)

Bodner, R.R.

1995-01-01

SLARette 1 equipment, comprising of a SLARette Delivery Machine, SLAR Tools, SLAR power supplies and SLAR Inspection Systems was designed, developed and manufactured to service fuel channels of CANDU 6 stations during the regular yearly station outages. The Mark 2 SLARette Delivery Machine uses a Push Tube system to provide the axial and rotary movements of the SLAR Tool. The Push Tubes are operated remotely but must be attached and removed manually. Since this operation is performed at the Reactor face, there is radiation dose involved for the workers. An Advanced SLARette Delivery Machine which incorporates a computer controlled telescoping Ram in the place of the Push Tubes has been recently designed and manufactured. Utilization of the Advanced SLARette Delivery Machine significantly reduces the amount of radiation dose picked up by the workers because the need to have workers at the face of the Reactor during the SLARette operation is greatly reduced. This paper describes the design, development and manufacturing process utilized to produce the Advanced SLARette Delivery Machine and the experience gained during the Gentilly-2 NGS Spring outage. (author)

Modification of structural graphite machining

International Nuclear Information System (INIS)

Lavrenev, M.M.

1979-01-01

Studied are machining procedures for structural graphites (GMZ, MG, MG-1, PPG) most widely used in industry, of the article mass being about 50 kg. Presented are dependences necessary for the calculation of cross sections of chip suction tappers and duster pipelines in machine shops for structural graphite machining

Machines and Metaphors

Directory of Open Access Journals (Sweden)

Ángel Martínez García-Posada

2016-10-01

Full Text Available The edition La ley del reloj. Arquitectura, máquinas y cultura moderna (Cátedra, Madrid, 2016 registers the useful paradox of the analogy between architecture and technique. Its author, the architect Eduardo Prieto, also a philosopher, professor and writer, acknowledges the obvious distance from machines to buildings, so great that it can only be solved using strange comparisons, since architecture does not move nor are the machines habitable, however throughout the book, from the origin of the metaphor of the machine, with clarity in his essay and enlightening erudition, he points out with certainty some concomitances of high interest, drawing throughout history a beautiful cartography of the fruitful encounter between organics and mechanics.

OptiCentric lathe centering machine

Science.gov (United States)

Buß, C.; Heinisch, J.

2013-09-01

High precision optics depend on precisely aligned lenses. The shift and tilt of individual lenses as well as the air gap between elements require accuracies in the single micron regime. These accuracies are hard to meet with traditional assembly methods. Instead, lathe centering can be used to machine the mount with respect to the optical axis. Using a diamond turning process, all relevant errors of single mounted lenses can be corrected in one post-machining step. Building on the OptiCentric® and OptiSurf® measurement systems, Trioptics has developed their first lathe centering machines. The machine and specific design elements of the setup will be shown. For example, the machine can be used to turn optics for i-line steppers with highest precision.

Machine Shop Grinding Machines.

Science.gov (United States)

Dunn, James

This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

''Diagonalization'' of a compound Atwood machine

International Nuclear Information System (INIS)

Crawford, F.S.

1987-01-01

We consider a simple Atwood machine consisting of a massless frictionless pulley no. 0 supporting two masses m 1 and m 2 connected by a massless flexible string. We show that the string that supports massless pulley no. 0 ''thinks'' it is simply supporting a mass m 0 , with m 0 = 4m 1 m 2 /(m 1 +m 2 ). This result, together with Einstein's equivalence principle, allows us to solve easily those compound Atwood machines created by replacing one or both of m 1 and m 2 in machine no. 0 by an Atwood machine. We may then replacing the masses in these new machines by machines, etc. The complete solution can be written down immediately, without solving simultaneous equations. Finally we give the effective mass of an Atwood machine whose pulley has nonzero mass and moment of inertia

Adaptive Machine Aids to Learning.

Science.gov (United States)

Starkweather, John A.

With emphasis on man-machine relationships and on machine evolution, computer-assisted instruction (CAI) is examined in this paper. The discussion includes the background of machine assistance to learning, the current status of CAI, directions of development, the development of criteria for successful instruction, meeting the needs of users,…

Collaborative human-machine analysis using a controlled natural language

Science.gov (United States)

Mott, David H.; Shemanski, Donald R.; Giammanco, Cheryl; Braines, Dave

2015-05-01

A key aspect of an analyst's task in providing relevant information from data is the reasoning about the implications of that data, in order to build a picture of the real world situation. This requires human cognition, based upon domain knowledge about individuals, events and environmental conditions. For a computer system to collaborate with an analyst, it must be capable of following a similar reasoning process to that of the analyst. We describe ITA Controlled English (CE), a subset of English to represent analyst's domain knowledge and reasoning, in a form that it is understandable by both analyst and machine. CE can be used to express domain rules, background data, assumptions and inferred conclusions, thus supporting human-machine interaction. A CE reasoning and modeling system can perform inferences from the data and provide the user with conclusions together with their rationale. We present a logical problem called the "Analysis Game", used for training analysts, which presents "analytic pitfalls" inherent in many problems. We explore an iterative approach to its representation in CE, where a person can develop an understanding of the problem solution by incremental construction of relevant concepts and rules. We discuss how such interactions might occur, and propose that such techniques could lead to better collaborative tools to assist the analyst and avoid the "pitfalls".

Machining of titanium alloys

CERN Document Server

2014-01-01

This book presents a collection of examples illustrating the resent research advances in the machining of titanium alloys. These materials have excellent strength and fracture toughness as well as low density and good corrosion resistance; however, machinability is still poor due to their low thermal conductivity and high chemical reactivity with cutting tool materials. This book presents solutions to enhance machinability in titanium-based alloys and serves as a useful reference to professionals and researchers in aerospace, automotive and biomedical fields.

Bionic machines and systems

Energy Technology Data Exchange (ETDEWEB)

Halme, A.; Paanajaervi, J. (eds.)

2004-07-01

Introduction Biological systems form a versatile and complex entirety on our planet. One evolutionary branch of primates, called humans, has created an extraordinary skill, called technology, by the aid of which it nowadays dominate life on the planet. Humans use technology for producing and harvesting food, healthcare and reproduction, increasing their capability to commute and communicate, defending their territory etc., and to develop more technology. As a result of this, humans have become much technology dependent, so that they have been forced to form a specialized class of humans, called engineers, who take care of the knowledge of technology developing it further and transferring it to later generations. Until now, technology has been relatively independent from biology, although some of its branches, e.g. biotechnology and biomedical engineering, have traditionally been in close contact with it. There exist, however, an increasing interest to expand the interface between technology and biology either by directly utilizing biological processes or materials by combining them with 'dead' technology, or by mimicking in technological solutions the biological innovations created by evolution. The latter theme is in focus of this report, which has been written as the proceeding of the post-graduate seminar 'Bionic Machines and Systems' held at HUT Automation Technology Laboratory in autumn 2003. The underlaying idea of the seminar was to analyze biological species by considering them as 'robotic machines' having various functional subsystems, such as for energy, motion and motion control, perception, navigation, mapping and localization. We were also interested about intelligent capabilities, such as learning and communication, and social structures like swarming behavior and its mechanisms. The word 'bionic machine' comes from the book which was among the initial material when starting our mission to the fascinating world

Brain versus Machine Control.

Directory of Open Access Journals (Sweden)

Jose M Carmena

2004-12-01

Full Text Available Dr. Octopus, the villain of the movie "Spiderman 2", is a fusion of man and machine. Neuroscientist Jose Carmena examines the facts behind this fictional account of a brain- machine interface

The Efficacy of Exergames Played Proximally and over the Internet on Cognitive Functioning for Online Physical Education

Science.gov (United States)

Kooiman, Brian J.; Sheehan, Dwayne P.

2014-01-01

Exergames (active video games that require kinesthetic movement) played in proximity to other players or against a gaming machine have been linked to positive increases in cognitive functioning. This study tested to see if remote exergame play over the Internet had an impact similar to exergames that are played in proximity. The study shows that…

Science knowledge and cognitive strategy use among culturally and linguistically diverse students

Science.gov (United States)

Lee, Okhee; Fradd, Sandra H.; Sutman, Frank X.

Science performance is determined, to a large extent, by what students already know about science (i.e., science knowledge) and what techniques or methods students use in performing science tasks (i.e., cognitive strategies). This study describes and compares science knowledge, science vocabulary, and cognitive strategy use among four diverse groups of elementary students: (a) monolingual English Caucasian, (b) African-American, (c) bilingual Spanish, and (d) bilingual Haitian Creole. To facilitate science performance in culturally and linguistically congruent settings, the study included student dyads and teachers of the same language, culture, and gender. Science performance was observed using three science tasks: weather phenomena, simple machines, and buoyancy. Data analysis involved a range of qualitative methods focusing on major themes and patterns, and quantitative methods using coding systems to summarize frequencies and total scores. The findings reveal distinct patterns of science knowledge, science vocabulary, and cognitive strategy use among the four language and culture groups. The findings also indicate relationships among science knowledge, science vocabulary, and cognitive strategy use. These findings raise important issues about science instruction for culturally and linguistically diverse groups of students.Received: 3 January 1995;

5-axes modular CNC machining center

Directory of Open Access Journals (Sweden)

Breaz Radu-Eugen

2017-01-01

Full Text Available The paper presents the development of a 5-axes CNC machining center. The main goal of the machine was to provide the students a practical layout for training in advanced CAM techniques. The mechanical structure of the machine was built in a modular way by a specialized company, which also implemented the CNC controller. The authors of this paper developed the geometric and kinematic model of the CNC machining center and the post-processor, in order to use the machine in a CAM environment.

15 CFR 5.5 - Vending machines.

Science.gov (United States)

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Vending machines. 5.5 Section 5.5... machines. (a) The income from any vending machines which are located within reasonable proximity to and are... shall be assigned to the operator of such stand. (b) If a vending machine vends articles of a type...

Efficient and robust pupil size and blink estimation from near-field video sequences for human-machine interaction.

Science.gov (United States)

Chen, Siyuan; Epps, Julien

2014-12-01

Monitoring pupil and blink dynamics has applications in cognitive load measurement during human-machine interaction. However, accurate, efficient, and robust pupil size and blink estimation pose significant challenges to the efficacy of real-time applications due to the variability of eye images, hence to date, require manual intervention for fine tuning of parameters. In this paper, a novel self-tuning threshold method, which is applicable to any infrared-illuminated eye images without a tuning parameter, is proposed for segmenting the pupil from the background images recorded by a low cost webcam placed near the eye. A convex hull and a dual-ellipse fitting method are also proposed to select pupil boundary points and to detect the eyelid occlusion state. Experimental results on a realistic video dataset show that the measurement accuracy using the proposed methods is higher than that of widely used manually tuned parameter methods or fixed parameter methods. Importantly, it demonstrates convenience and robustness for an accurate and fast estimate of eye activity in the presence of variations due to different users, task types, load, and environments. Cognitive load measurement in human-machine interaction can benefit from this computationally efficient implementation without requiring a threshold calibration beforehand. Thus, one can envisage a mini IR camera embedded in a lightweight glasses frame, like Google Glass, for convenient applications of real-time adaptive aiding and task management in the future.

An art history of machines?

Directory of Open Access Journals (Sweden)

Daniel Bridgman

2016-12-01

Full Text Available A toast offered in honor of Donald Preziosi on the cusp of his seventy-fifth birthday, this essay considers a range of machine metaphors, their art historical settings, and their implications. Addressing the mythography of Daedalus and his wonder machines in relation to art history’s machinic enterprises, an ancient art-archaeology seminar Preziosi directed at UCLA (in 1988 and the book, Rethinking Art History: Meditations on a Coy Science (1989 form the focus of my thinking about Preziosi’s work. At issue across the essay is the work of recursion, when machines make machines and in so doing create a recessive subjectivity for the maker. The essay ends with the speculation that art history’s disciplinary machinery may owe its generative strength to a perpetual need for replacement parts.

Machinability of Stellite 6 hardfacing

Directory of Open Access Journals (Sweden)

Dudzinski D.

2010-06-01

Full Text Available This paper reports some experimental findings concerning the machinability at high cutting speed of nickel-base weld-deposited hardfacings for the manufacture of hot tooling. The forging work involves extreme impacts, forces, stresses and temperatures. Thus, mould dies must be extremely resistant. The aim of the project is to create a rapid prototyping process answering to forging conditions integrating a Stellite 6 hardfacing deposed PTA process. This study talks about the dry machining of the hardfacing, using a two tips machining tool and a high speed milling machine equipped by a power consumption recorder Wattpilote. The aim is to show the machinability of the hardfacing, measuring the power and the tip wear by optical microscope and white light interferometer, using different strategies and cutting conditions.

Nontraditional machining processes research advances

CERN Document Server

2013-01-01

Nontraditional machining employs processes that remove material by various methods involving thermal, electrical, chemical and mechanical energy or even combinations of these. Nontraditional Machining Processes covers recent research and development in techniques and processes which focus on achieving high accuracies and good surface finishes, parts machined without burrs or residual stresses especially with materials that cannot be machined by conventional methods. With applications to the automotive, aircraft and mould and die industries, Nontraditional Machining Processes explores different aspects and processes through dedicated chapters. The seven chapters explore recent research into a range of topics including laser assisted manufacturing, abrasive water jet milling and hybrid processes. Students and researchers will find the practical examples and new processes useful for both reference and for developing further processes. Industry professionals and materials engineers will also find Nontraditional M...

Toroidal helical quartz forming machine

International Nuclear Information System (INIS)

Hanks, K.W.; Cole, T.R.

1977-01-01

The Scyllac fusion experimental machine used 10 cm diameter smooth bore discharge tubes formed into a simple toroidal shape prior to 1974. At about that time, it was discovered that a discharge tube was required to follow the convoluted shape of the load coil. A machine was designed and built to form a fused quartz tube with a toroidal shape. The machine will accommodate quartz tubes from 5 cm to 20 cm diameter forming it into a 4 m toroidal radius with a 1 to 5 cm helical displacement. The machine will also generate a helical shape on a linear tube. Two sets of tubes with different helical radii and wavelengths have been successfully fabricated. The problems encountered with the design and fabrication of this machine are discussed

Cognitive restructuring of gambling-related thoughts: A systematic review.

Science.gov (United States)

Chrétien, Maxime; Giroux, Isabelle; Goulet, Annie; Jacques, Christian; Bouchard, Stéphane

2017-12-01

Gamblers' thoughts have a fundamental influence on their gambling problem. Cognitive restructuring is the intervention of choice to correct those thoughts. However, certain difficulties are noted in the application of cognitive restructuring techniques and the comprehension of their guidelines. Furthermore, the increase of skill game players (e.g. poker) entering treatment creates a challenge for therapists, as these gamblers present with different thoughts than those of the gamblers usually encountered in treatment (e.g. chance-only games like electronic gambling machines). This systematic review aims to describe how cognitive restructuring is carried out with gamblers based on the evidence available in empirical studies that include cognitive interventions for gambling. Of the 2607 studies collected, 39 were retained. The results highlight exposure as the most frequently used technique to facilitate identification of gambling-related thoughts (imaginal=28.2%; in vivo=10.3%). More than half of the studies (69.2%) clearly reported therapeutic techniques aimed to correct gamblers' thoughts, of which 37% involved visual support to challenge those thoughts (e.g. ABC log). Of the 39 studies retained, 48.7% included skill game players (i.e., poker, blackjack, sports betting) in their sample. However, none of these studies mentioned whether cognitive restructuring had been adapted for these gamblers. Several terms referring to gamblers' thoughts were used interchangeably (e.g. erroneous, dysfunctional or inadequate thoughts), although each of these terms could refer to specific content. Clinical implications of the results are discussed with regard to the needs of therapists. This review also suggests recommendations for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Decomposition of the compound Atwood machine

Science.gov (United States)

Lopes Coelho, R.

2017-11-01

Non-standard solving strategies for the compound Atwood machine problem have been proposed. The present strategy is based on a very simple idea. Taking an Atwood machine and replacing one of its bodies by another Atwood machine, we have a compound machine. As this operation can be repeated, we can construct any compound Atwood machine. This rule of construction is transferred to a mathematical model, whereby the equations of motion are obtained. The only difference between the machine and its model is that instead of pulleys and bodies, we have reference frames that move solidarily with these objects. This model provides us with the accelerations in the non-inertial frames of the bodies, which we will use to obtain the equations of motion. This approach to the problem will be justified by the Lagrange method and exemplified by machines with six and eight bodies.

Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test.

Science.gov (United States)

Souillard-Mandar, William; Davis, Randall; Rudin, Cynthia; Au, Rhoda; Libon, David J; Swenson, Rodney; Price, Catherine C; Lamar, Melissa; Penney, Dana L

2016-03-01

The Clock Drawing Test - a simple pencil and paper test - has been used for more than 50 years as a screening tool to differentiate normal individuals from those with cognitive impairment, and has proven useful in helping to diagnose cognitive dysfunction associated with neurological disorders such as Alzheimer's disease, Parkinson's disease, and other dementias and conditions. We have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject's performance. Using pen stroke data from these drawings categorized by our software, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used manual scoring systems so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and rule lists designed to be as easy to use as scoring systems currently used by clinicians, but more accurate. While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.

Using machine learning to identify air pollution exposure profiles associated with early cognitive skills among U.S. children.

Science.gov (United States)

Stingone, Jeanette A; Pandey, Om P; Claudio, Luz; Pandey, Gaurav

2017-11-01

Data-driven machine learning methods present an opportunity to simultaneously assess the impact of multiple air pollutants on health outcomes. The goal of this study was to apply a two-stage, data-driven approach to identify associations between air pollutant exposure profiles and children's cognitive skills. Data from 6900 children enrolled in the Early Childhood Longitudinal Study, Birth Cohort, a national study of children born in 2001 and followed through kindergarten, were linked to estimated concentrations of 104 ambient air toxics in the 2002 National Air Toxics Assessment using ZIP code of residence at age 9 months. In the first-stage, 100 regression trees were learned to identify ambient air pollutant exposure profiles most closely associated with scores on a standardized mathematics test administered to children in kindergarten. In the second-stage, the exposure profiles frequently predicting lower math scores were included within linear regression models and adjusted for confounders in order to estimate the magnitude of their effect on math scores. This approach was applied to the full population, and then to the populations living in urban and highly-populated urban areas. Our first-stage results in the full population suggested children with low trichloroethylene exposure had significantly lower math scores. This association was not observed for children living in urban communities, suggesting that confounding related to urbanicity needs to be considered within the first-stage. When restricting our analysis to populations living in urban and highly-populated urban areas, high isophorone levels were found to predict lower math scores. Within adjusted regression models of children in highly-populated urban areas, the estimated effect of higher isophorone exposure on math scores was -1.19 points (95% CI -1.94, -0.44). Similar results were observed for the overall population of urban children. This data-driven, two-stage approach can be applied to other

A Peer-Reviewed Journal about Machine Research

OpenAIRE

Cox, G; Ganesh, MI; Gil-Fournier, A; Herrie, MB; Hill, J; House, B; Jones, N; Skinner, S; Young, D; Anon

2017-01-01

Edited by Christian Ulrik Andersen and Geoff Cox This publication is about MACHINE RESEARCH – research on machines, research with machines, and research as a machine. It thus explores machinic perspectives to suggest a situation where the humanities are put into a critical perspective by machine driven ecologies, ontologies and epistemologies of thinking and acting. It aims to engage research and artistic practice that takes into account the new materialist conditions implied by nonhuman t...

Viscoelastic machine elements elastomers and lubricants in machine systems

CERN Document Server

MOORE, D F

2015-01-01

Viscoelastic Machine Elements, which encompass elastomeric elements (rubber-like components), fluidic elements (lubricating squeeze films) and their combinations, are used for absorbing vibration, reducing friction and improving energy use. Examplesinclude pneumatic tyres, oil and lip seals, compliant bearings and races, and thin films. This book sets out to show that these elements can be incorporated in machine analysis, just as in the case of conventional elements (e.g. gears, cogs, chaindrives, bearings). This is achieved by introducing elementary theory and models, by describing new an

Teletherapy machine

International Nuclear Information System (INIS)

Panyam, Vinatha S.; Rakshit, Sougata; Kulkarni, M.S.; Pradeepkumar, K.S.

2017-01-01

Radiation Standards Section (RSS), RSSD, BARC is the national metrology institute for ionizing radiation. RSS develops and maintains radiation standards for X-ray, beta, gamma and neutron radiations. In radiation dosimetry, traceability, accuracy and consistency of radiation measurements is very important especially in radiotherapy where the success of patient treatment is dependent on the accuracy of the dose delivered to the tumour. Cobalt teletherapy machines have been used in the treatment of cancer since the early 1950s and India had its first cobalt teletherapy machine installed at the Cancer Institute, Chennai in 1956

Creativity in Machine Learning

OpenAIRE

Thoma, Martin

2016-01-01

Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as text and as audio. This paper gives a high level overview of how they are created and gives some examples. It is meant to be a summary of the current work and give people who are new to machine learning some starting points.

The Complexity of Abstract Machines

Directory of Open Access Journals (Sweden)

Beniamino Accattoli

2017-01-01

Full Text Available The lambda-calculus is a peculiar computational model whose definition does not come with a notion of machine. Unsurprisingly, implementations of the lambda-calculus have been studied for decades. Abstract machines are implementations schema for fixed evaluation strategies that are a compromise between theory and practice: they are concrete enough to provide a notion of machine and abstract enough to avoid the many intricacies of actual implementations. There is an extensive literature about abstract machines for the lambda-calculus, and yet—quite mysteriously—the efficiency of these machines with respect to the strategy that they implement has almost never been studied. This paper provides an unusual introduction to abstract machines, based on the complexity of their overhead with respect to the length of the implemented strategies. It is conceived to be a tutorial, focusing on the case study of implementing the weak head (call-by-name strategy, and yet it is an original re-elaboration of known results. Moreover, some of the observation contained here never appeared in print before.

On-machine measurement of a slow slide servo diamond-machined 3D microstructure with a curved substrate

International Nuclear Information System (INIS)

Zhu, Wu-Le; Yang, Shunyao; Ju, Bing-Feng; Jiang, Jiacheng; Sun, Anyu

2015-01-01

A scanning tunneling microscope-based multi-axis measuring system is specially developed for the on-machine measurement of three-dimensional (3D) microstructures, to address the quality control difficulty with the traditional off-line measurement process. A typical 3D microstructure of the curved compound eye was diamond-machined by the slow slide servo technique, and then the whole surface was on-machine scanned three-dimensionally based on the tip-tracking strategy by utilizing a spindle, two linear motion stages, and an additional rotary stage. The machined surface profile and its shape deviation were accurately measured on-machine. The distortion of imaged ommatidia on the curved substrate was distinctively evaluated based on the characterized points extracted from the measured surface. Furthermore, the machining errors were investigated in connection with the on-machine measured surface and its characteristic parameters. Through experiments, the proposed measurement system is demonstrated to feature versatile on-machine measurement of 3D microstructures with a curved substrate, which is highly meaningful for quality control in the fabrication field. (paper)

An asymptotical machine

Science.gov (United States)

Cristallini, Achille

2016-07-01

A new and intriguing machine may be obtained replacing the moving pulley of a gun tackle with a fixed point in the rope. Its most important feature is the asymptotic efficiency. Here we obtain a satisfactory description of this machine by means of vector calculus and elementary trigonometry. The mathematical model has been compared with experimental data and briefly discussed.

Apparel Manufacturing (Course Outline), Industrial Single Needle Machines and Machine Practice: 9377.02.

Science.gov (United States)

Dade County Public Schools, Miami, FL.

This course includes a study of the industrial single needle machine, its principal parts, general care, threading, and basic skills in machine practice. Instructional materials include films, illustration, information sheets, and other materials. (CK)

Comparison Between a Reference Torque Standard Machine and a Deadweight Torque Standard Machine to BE Used in Torque Calibration

Science.gov (United States)

Meng, Feng; Zhang, Zhimin; Lin, Jing

The paper describes the reference torque standard machine with high accuracy and multifunction, developed by our institute, and introduces the structure and working principle of this machine. It has three main functions. The first function is the hydraulic torque wrench calibration function. The second function is torque multiply calibration function. The third function is reference torque standard machine function. We can calibrate the torque multipliers, hydraulic wrenches and transducers by this machine. A comparison experiment has been done between this machine and a deadweight torque standard machine. The consistency between the 30 kNm reference torque machine and the 2000 Nm dead-weight torque standard machine under the claimed uncertainties was verified.

Effect of machining fluid on the process performance of wire electrical discharge machining of nanocomposite ceramic

Directory of Open Access Journals (Sweden)

Zhang Chengmao

2015-01-01

Full Text Available Wire electric discharge machining (WEDM promise to be effective and economical techniques for the production of tools and parts from conducting ceramic blanks. However, the manufacturing of nanocomposite ceramics blanks with these processes is a long and costly process. This paper presents a new process of machining nanocomposite ceramics using WEDM. WEDM uses water based emulsion, polyvinyl alcohol and distilled water as the machining fluid. Machining fluid is a primary factor that affects the material removal rate and surface quality of WEDM. The effects of emulsion concentration, polyvinyl alcohol concentration and distilled water of the machining fluid on the process performance have been investigated.

Singer CNC sewing and embroidery machine

Directory of Open Access Journals (Sweden)

Lokodi Zsolt

2011-12-01

Full Text Available This paper presents the adaptation of a classic foot pedal operated Singer sewing machine to a computerized numerical control (CNC sewing and embroidery machine. This machine is composed of a Singer sewing machine and a two-degrees-of-freedom XY stage designed specifically for this application. The whole system is controlled from a PC using adequate CNC control software.

Automating horizontal boring and milling machine

International Nuclear Information System (INIS)

Naqvi, S.A.R.; Mahmood, T.; Choudhry, M.A.; Hanif, A.

2012-01-01

Aiming at the requirements of modification for many old import machine tools in industry, the schemes suited to the renovation are presented in this paper. A horizontal boring and milling machine (HBM) involved in machining of tank Al-Khalid has been modified using Mitsubishi FX-1N and FX-2N PLC. The developed software is for control of all the functions of the said machine. These functions include power on/off oil pump, spindle rotation and machine movement in all axes. All the decisions required by the machine for actuation of instructions are based on the data acquired from the control panel, timers and limit switches. Also the developed software minimize the down time, safety of operator and error free actuation of instructions. (author)

Molecular machines with bio-inspired mechanisms.

Science.gov (United States)

Zhang, Liang; Marcos, Vanesa; Leigh, David A

2018-02-26

The widespread use of molecular-level motion in key natural processes suggests that great rewards could come from bridging the gap between the present generation of synthetic molecular machines-which by and large function as switches-and the machines of the macroscopic world, which utilize the synchronized behavior of integrated components to perform more sophisticated tasks than is possible with any individual switch. Should we try to make molecular machines of greater complexity by trying to mimic machines from the macroscopic world or instead apply unfamiliar (and no doubt have to discover or invent currently unknown) mechanisms utilized by biological machines? Here we try to answer that question by exploring some of the advances made to date using bio-inspired machine mechanisms.

Model-based machine learning.

Science.gov (United States)

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

Reactor refueling machine simulator

International Nuclear Information System (INIS)

Rohosky, T.L.; Swidwa, K.J.

1987-01-01

This patent describes in combination: a nuclear reactor; a refueling machine having a bridge, trolley and hoist each driven by a separate motor having feedback means for generating a feedback signal indicative of movement thereof. The motors are operable to position the refueling machine over the nuclear reactor for refueling the same. The refueling machine also has a removable control console including means for selectively generating separate motor signals for operating the bridge, trolley and hoist motors and for processing the feedback signals to generate an indication of the positions thereof, separate output leads connecting each of the motor signals to the respective refueling machine motor, and separate input leads for connecting each of the feedback means to the console; and a portable simulator unit comprising: a single simulator motor; a single simulator feedback signal generator connected to the simulator motor for generating a simulator feedback signal in response to operation of the simulator motor; means for selectively connecting the output leads of the console to the simulator unit in place of the refueling machine motors, and for connecting the console input leads to the simulator unit in place of the refueling machine motor feedback means; and means for driving the single simulator motor in response to any of the bridge, trolley or hoist motor signals generated by the console and means for applying the simulator feedback signal to the console input lead associated with the motor signal being generated by the control console

The Bearingless Electrical Machine

Science.gov (United States)

Bichsel, J.

1992-01-01

Electromagnetic bearings allow the suspension of solids. For rotary applications, the most important physical effect is the force of a magnetic circuit to a high permeable armature, called the MAXWELL force. Contrary to the commonly used MAXWELL bearings, the bearingless electrical machine will take advantage of the reaction force of a conductor carrying a current in a magnetic field. This kind of force, called Lorentz force, generates the torque in direct current, asynchronous and synchronous machines. The magnetic field, which already exists in electrical machines and helps to build up the torque, can also be used for the suspension of the rotor. Besides the normal winding of the stator, a special winding was added, which generates forces for levitation. So a radial bearing, which is integrated directly in the active part of the machine, and the motor use the laminated core simultaneously. The winding was constructed for the levitating forces in a special way so that commercially available standard ac inverters for drives can be used. Besides wholly magnetic suspended machines, there is a wide range of applications for normal drives with ball bearings. Resonances of the rotor, especially critical speeds, can be damped actively.

Quantum cloning machines and the applications

Energy Technology Data Exchange (ETDEWEB)

Fan, Heng, E-mail: hfan@iphy.ac.cn [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Collaborative Innovation Center of Quantum Matter, Beijing 100190 (China); Wang, Yi-Nan; Jing, Li [School of Physics, Peking University, Beijing 100871 (China); Yue, Jie-Dong [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu [School of Physics, Peking University, Beijing 100871 (China)

2014-11-20

No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results.

Quantum cloning machines and the applications

International Nuclear Information System (INIS)

Fan, Heng; Wang, Yi-Nan; Jing, Li; Yue, Jie-Dong; Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu

2014-01-01

No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results

EDM machinability of SiCw/Al composites

Science.gov (United States)

Ramulu, M.; Taya, M.

1989-01-01

Machinability of high temperature composites was investigated. Target materials, 15 and 25 vol pct SiC whisker-2124 aluminum composites, were machined by electrodischarge sinker machining and diamond saw. The machined surfaces of these metal matrix composites were examined by SEM and profilometry to determine the surface finish. Microhardness measurements were also performed on the as-machined composites.

Machine learning and medical imaging

CERN Document Server

Shen, Dinggang; Sabuncu, Mert

2016-01-01

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, a...

Fundamentals of machine design

CERN Document Server

Karaszewski, Waldemar

2011-01-01

A forum of researchers, educators and engineers involved in various aspects of Machine Design provided the inspiration for this collection of peer-reviewed papers. The resultant dissemination of the latest research results, and the exchange of views concerning the future research directions to be taken in this field will make the work of immense value to all those having an interest in the topics covered. The book reflects the cooperative efforts made in seeking out the best strategies for effecting improvements in the quality and the reliability of machines and machine parts and for extending

Machine Learning for Hackers

CERN Document Server

Conway, Drew

2012-01-01

If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyz

Machine Learning for Medical Imaging.

Science.gov (United States)

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

Failure Identification of Hacksaw Machine REMOR 400

International Nuclear Information System (INIS)

Paidjo; Abdul Hafid; Sagino

2007-01-01

REMOR 400 Hack sawing machine is one of machines type has been old age. For arrange of cutting pressure and repeat lifting load after cutting process by using the hydraulic system. Beside of worn-out of hacksaw blade, failure cutting earn also because of leakage from the hydraulic system of machine. Leakage of hydraulic system occurs because of over load factor using or aging. Base on inspection result, hacksaw machine REMOR 400 fault on hydraulic system in the 2006 year. This matter will be seen from its seal brittle from the machine. For activate to return machine so much replacement repeat the seals used by machine. (author)

Permutation parity machines for neural cryptography.

Science.gov (United States)

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-06-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Permutation parity machines for neural cryptography

International Nuclear Information System (INIS)

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-01-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Cognitive anthropology is a cognitive science.

Science.gov (United States)

Boster, James S

2012-07-01

Cognitive anthropology contributes to cognitive science as a complement to cognitive psychology. The chief threat to its survival has not been rejection by other cognitive scientists but by other cultural anthropologists. It will remain a part of cognitive science as long as cognitive anthropologists research, teach, and publish. Copyright © 2012 Cognitive Science Society, Inc.

Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning.

Science.gov (United States)

Kesler, Shelli R; Rao, Arvind; Blayney, Douglas W; Oakley-Girvan, Ingrid A; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34-65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( p breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.

Machine assembly with a new material handling mechanism in the sewing machine

Directory of Open Access Journals (Sweden)

Umarova Z.M.

2017-05-01

Full Text Available the paper presents the dynamic model of the machine assembly with a recommended mechanism for moving material and the definition of the law of rails motion under various system parameters. The author has suggested the solution implemented by the system of differential equations numerically on the PC and the system describing the motion of the machine set. Recommended values ​​of the parameters of elastic links of material transfer mechanism have been obtained. The researcher has developed the methods of kinematic and dynamic analysis of the material transfer mechanism with elastic elements of the sewing machine and has approved the parameters and development of the design.

Abstract quantum computing machines and quantum computational logics

Science.gov (United States)

Chiara, Maria Luisa Dalla; Giuntini, Roberto; Sergioli, Giuseppe; Leporini, Roberto

2016-06-01

Classical and quantum parallelism are deeply different, although it is sometimes claimed that quantum Turing machines are nothing but special examples of classical probabilistic machines. We introduce the concepts of deterministic state machine, classical probabilistic state machine and quantum state machine. On this basis, we discuss the question: To what extent can quantum state machines be simulated by classical probabilistic state machines? Each state machine is devoted to a single task determined by its program. Real computers, however, behave differently, being able to solve different kinds of problems. This capacity can be modeled, in the quantum case, by the mathematical notion of abstract quantum computing machine, whose different programs determine different quantum state machines. The computations of abstract quantum computing machines can be linguistically described by the formulas of a particular form of quantum logic, termed quantum computational logic.

Nanocomposites for Machining Tools

DEFF Research Database (Denmark)

Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon

2017-01-01

Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials...

Machine intelligence and signal processing

CERN Document Server

Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

2016-01-01

This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

Learning Activity Packets for Milling Machines. Unit I--Introduction to Milling Machines.

Science.gov (United States)

Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This learning activity packet (LAP) outlines the study activities and performance tasks covered in a related curriculum guide on milling machines. The course of study in this LAP is intended to help students learn to identify parts and attachments of vertical and horizontal milling machines, identify work-holding devices, state safety rules, and…

Electrical Discharge Machining (EDM: A Review

Directory of Open Access Journals (Sweden)

Asfana Banu

2016-09-01

Full Text Available Electro discharge machining (EDM process is a non-conventional and non-contact machining operation which is used in industry for high precision products. EDM is known for machining hard and brittle conductivematerials since it can melt any electrically conductive material regardless of its hardness. The workpiece machined by EDM depends on thermal conductivity, electrical resistivity, and melting points of the materials. The tool and the workpiece are adequately both immersed in a dielectric medium, such as, kerosene, deionised water or any other suitable fluid. This paper is reviewed comprehensively on types of EDM operation. A brief discussion is also done on the machining responses and mathematical modelling.

Cognitive Load Measurement in a Virtual Reality-based Driving System for Autism Intervention.

Science.gov (United States)

Zhang, Lian; Wade, Joshua; Bian, Dayi; Fan, Jing; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

2017-01-01

Autism Spectrum Disorder (ASD) is a highly prevalent neurodevelopmental disorder with enormous individual and social cost. In this paper, a novel virtual reality (VR)-based driving system was introduced to teach driving skills to adolescents with ASD. This driving system is capable of gathering eye gaze, electroencephalography, and peripheral physiology data in addition to driving performance data. The objective of this paper is to fuse multimodal information to measure cognitive load during driving such that driving tasks can be individualized for optimal skill learning. Individualization of ASD intervention is an important criterion due to the spectrum nature of the disorder. Twenty adolescents with ASD participated in our study and the data collected were used for systematic feature extraction and classification of cognitive loads based on five well-known machine learning methods. Subsequently, three information fusion schemes-feature level fusion, decision level fusion and hybrid level fusion-were explored. Results indicate that multimodal information fusion can be used to measure cognitive load with high accuracy. Such a mechanism is essential since it will allow individualization of driving skill training based on cognitive load, which will facilitate acceptance of this driving system for clinical use and eventual commercialization.

Cognitive Load Measurement in a Virtual Reality-based Driving System for Autism Intervention

Science.gov (United States)

Zhang, Lian; Wade, Joshua; Bian, Dayi; Fan, Jing; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

2016-01-01

Autism Spectrum Disorder (ASD) is a highly prevalent neurodevelopmental disorder with enormous individual and social cost. In this paper, a novel virtual reality (VR)-based driving system was introduced to teach driving skills to adolescents with ASD. This driving system is capable of gathering eye gaze, electroencephalography, and peripheral physiology data in addition to driving performance data. The objective of this paper is to fuse multimodal information to measure cognitive load during driving such that driving tasks can be individualized for optimal skill learning. Individualization of ASD intervention is an important criterion due to the spectrum nature of the disorder. Twenty adolescents with ASD participated in our study and the data collected were used for systematic feature extraction and classification of cognitive loads based on five well-known machine learning methods. Subsequently, three information fusion schemes—feature level fusion, decision level fusion and hybrid level fusion—were explored. Results indicate that multimodal information fusion can be used to measure cognitive load with high accuracy. Such a mechanism is essential since it will allow individualization of driving skill training based on cognitive load, which will facilitate acceptance of this driving system for clinical use and eventual commercialization. PMID:28966730

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators

International Nuclear Information System (INIS)

Salazar-Ferrer, P.

1995-06-01

In complex industrial process control, causal reasoning appears as a major component in operators' cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs

Human-machine interface upgrade

International Nuclear Information System (INIS)

Kropik, M.; Matejka, K.; Sklenka, L.; Chab, V.

2002-01-01

The article describes a new human-machine interface that was installed at the VR-1 training reactor. The human-machine interface upgrade was completed in the summer 2001. The interface was designed with respect to functional, ergonomic and aesthetic requirements. The interface is based on a personal computer equipped with two displays. One display enables alphanumeric communication between the reactor operator and the nuclear reactor I and C. The second display is a graphical one. It presents the status of the reactor, principal parameters (as power, period), control rods positions, course of the reactor power. Furthermore, it is possible to set parameters, to show the active core configuration, to perform reactivity calculations, etc. The software for the new human-machine interface was produced with the InTouch developing tool of the Wonder-Ware Company. It is possible to switch the language of the interface between Czech and English because of many foreign students and visitors to the reactor. Microcomputer based communication units with proper software were developed to connect the new human-machine interface with the present reactor I and C. The new human-machine interface at the VR-1 training reactor improves the comfort and safety of the reactor utilisation, facilitates experiments and training, and provides better support for foreign visitors. (orig.)

Game-powered machine learning.

Science.gov (United States)

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

X-ray evaluation of residual stress distributions within surface machined layer generated by surface machining and sequential welding

International Nuclear Information System (INIS)

Taniguchi, Yuu; Okano, Shigetaka; Mochizuki, Masahito

2017-01-01

The excessive tensile residual stress generated by welding after surface machining may be an important factor to cause stress corrosion cracking (SCC) in nuclear power plants. Therefore we need to understand and control the residual stress distribution appropriately. In this study, residual stress distributions within surface machined layer generated by surface machining and sequential welding were evaluated by X-ray diffraction method. Depth directional distributions were also investigated by electrolytic polishing. In addition, to consider the effect of work hardened layer on the residual stress distributions, we also measured full width at half maximum (FWHM) obtained from X-ray diffraction. Testing material was a low-carbon austenitic stainless steel type SUS316L. Test specimens were prepared by surface machining with different cutting conditions. Then, bead-on-plate welding under the same welding condition was carried out on the test specimens with different surface machined layer. As a result, the tensile residual stress generated by surface machining increased with increasing cutting speed and showed nearly uniform distributions on the surface. Furthermore, the tensile residual stress drastically decreased with increasing measurement depth within surface machined layer. Then, the residual stress approached 0 MPa after the compressive value showed. FWHM also decreased drastically with increasing measurement depth and almost constant value from a certain depth, which was almost equal regardless of the machining condition, within surface machined layer in all specimens. After welding, the transverse distribution of the longitudinal residual stress varied in the area apart from the weld center according to machining conditions and had a maximum value in heat affected zone. The magnitude of the maximum residual stress was almost equal regardless of the machining condition and decreased with increasing measurement depth within surface machined layer. Finally, the

Electromechanical model of machine for vibroabrasive treatment of machine parts

OpenAIRE

Gorbatiyk, Ruslan; Palamarchuk, Igor; Chubyk, Roman

2015-01-01

A lot of operations on trimming clean and finishing – stripping up treatment, first of all, removing of burrs, rounding and processing of borders, until recently time was carried out by hand, and hardly exposed to automation and became a serious obstacle in subsequent growth of the labor productivity. Machines with free kinematics connection between a tool and the treating parts is provided by the printing-down of all of the surface of the machine parts, that allows us to effectively treat bo...

Toward FRP-Based Brain-Machine Interfaces-Single-Trial Classification of Fixation-Related Potentials.

Directory of Open Access Journals (Sweden)

Andrea Finke

Full Text Available The co-registration of eye tracking and electroencephalography provides a holistic measure of ongoing cognitive processes. Recently, fixation-related potentials have been introduced to quantify the neural activity in such bi-modal recordings. Fixation-related potentials are time-locked to fixation onsets, just like event-related potentials are locked to stimulus onsets. Compared to existing electroencephalography-based brain-machine interfaces that depend on visual stimuli, fixation-related potentials have the advantages that they can be used in free, unconstrained viewing conditions and can also be classified on a single-trial level. Thus, fixation-related potentials have the potential to allow for conceptually different brain-machine interfaces that directly interpret cortical activity related to the visual processing of specific objects. However, existing research has investigated fixation-related potentials only with very restricted and highly unnatural stimuli in simple search tasks while participant's body movements were restricted. We present a study where we relieved many of these restrictions while retaining some control by using a gaze-contingent visual search task. In our study, participants had to find a target object out of 12 complex and everyday objects presented on a screen while the electrical activity of the brain and eye movements were recorded simultaneously. Our results show that our proposed method for the classification of fixation-related potentials can clearly discriminate between fixations on relevant, non-relevant and background areas. Furthermore, we show that our classification approach generalizes not only to different test sets from the same participant, but also across participants. These results promise to open novel avenues for exploiting fixation-related potentials in electroencephalography-based brain-machine interfaces and thus providing a novel means for intuitive human-machine interaction.

Experimental Investigation – Magnetic Assisted Electro Discharge Machining

Science.gov (United States)

Kesava Reddy, Chirra; Manzoor Hussain, M.; Satyanarayana, S.; Krishna, M. V. S. Murali

2018-04-01

Emerging technology needs advanced machined parts with high strength and temperature resistance, high fatigue life at low production cost with good surface quality to fit into various industrial applications. Electro discharge machine is one of the extensively used machines to manufacture advanced machined parts which cannot be machined by other traditional machine with high precision and accuracy. Machining of DIN 17350-1.2080 (High Carbon High Chromium steel), using electro discharge machining has been discussed in this paper. In the present investigation an effort is made to use permanent magnet at various positions near the spark zone to improve surface quality of the machined surface. Taguchi methodology is used to obtain optimal choice for each machining parameter such as peak current, pulse duration, gap voltage and Servo reference voltage etc. Process parameters have significant influence on machining characteristics and surface finish. Improvement in surface finish is observed when process parameters are set at optimum condition under the influence of magnetic field at various positions.

Machine safety: proper safeguarding techniques.

Science.gov (United States)

Martin, K J

1992-06-01

1. OSHA mandates certain safeguarding of machinery to prevent accidents and protect machine operators. OSHA specifies moving parts that must be guarded and sets criteria for the guards. 2. A 1989 OSHA standard for lockout/tagout requires locking the energy source during maintenance, periodically inspecting for power transmission, and training maintenance workers. 3. In an amputation emergency, first aid for cardiopulmonary resuscitation, shock, and bleeding are the first considerations. The amputated part should be wrapped in moist gauze, placed in a sealed plastic bag, and placed in a container of 50% water and 50% ice for transport. 4. The role of the occupational health nurse in machine safety is to conduct worksite analyses to identify proper safeguarding and to communicate deficiencies to appropriate personnel; to train workers in safe work practices and observe compliance in the use of machine guards; to provide care to workers injured by machines; and to reinforce safe work practices among machine operators.

The deleuzian abstract machines

DEFF Research Database (Denmark)

Werner Petersen, Erik

2005-01-01

To most people the concept of abstract machines is connected to the name of Alan Turing and the development of the modern computer. The Turing machine is universal, axiomatic and symbolic (E.g. operating on symbols). Inspired by Foucault, Deleuze and Guattari extended the concept of abstract...

Man-machine interactions 3

CERN Document Server

Czachórski, Tadeusz; Kozielski, Stanisław

2014-01-01

Man-Machine Interaction is an interdisciplinary field of research that covers many aspects of science focused on a human and machine in conjunction.  Basic goal of the study is to improve and invent new ways of communication between users and computers, and many different subjects are involved to reach the long-term research objective of an intuitive, natural and multimodal way of interaction with machines.  The rapid evolution of the methods by which humans interact with computers is observed nowadays and new approaches allow using computing technologies to support people on the daily basis, making computers more usable and receptive to the user's needs.   This monograph is the third edition in the series and presents important ideas, current trends and innovations in  the man-machine interactions area.  The aim of this book is to introduce not only hardware and software interfacing concepts, but also to give insights into the related theoretical background. Reader is provided with a compilation of high...

Hydraulic Power Plant Machine Dynamic Diagnosis

Directory of Open Access Journals (Sweden)

Hans Günther Poll

2006-01-01

Full Text Available A method how to perform an entire structural and hydraulic diagnosis of prototype Francis power machines is presented and discussed in this report. Machine diagnosis of Francis units consists on a proper evaluation of acquired mechanical, thermal and hydraulic data obtained in different operating conditions of several rotary and non rotary machine components. Many different physical quantities of a Francis machine such as pressure, strains, vibration related data, water flow, air flow, position of regulating devices and displacements are measured in a synchronized way so that a relation of cause an effect can be developed for each operating condition and help one to understand all phenomena that are involved with such kind of machine. This amount of data needs to be adequately post processed in order to allow correct interpretation of the machine dynamics and finally these data must be compared with the expected calculated data not only to fine tuning the calculation methods but also to accomplish fully understanding of the influence of the water passages on such machines. The way how the power plant owner has to operate its Francis machines, many times also determined by a central dispatcher, has a high influence on the fatigue life time of the machine components. The diagnostic method presented in this report helps one to understand the importance of adequate operation to allow a low maintenance cost for the entire power plant. The method how to acquire these quantities is discussed in details together with the importance of correct sensor balancing, calibration and adequate correlation with the physical quantities. Typical results of the dynamic machine behavior, with adequate interpretation, obtained in recent measurement campaigns of some important hydraulic turbines were presented. The paper highlights the investigation focus of the hydraulic machine behavior and how to tailor the measurement strategy to accomplish all goals. Finally some

Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.

Science.gov (United States)

Sørensen, Lauge; Nielsen, Mads

2018-05-15

The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), converting MCI (cMCI), and Alzheimer's disease (AD) using brain imaging and general cognition. We proposed to use an ensemble of support vector machines (SVMs) that combined bagging without replacement and feature selection. SVM is the most commonly used algorithm in multivariate classification of dementia, and it was therefore valuable to evaluate the potential benefit of ensembling this type of classifier. The ensemble SVM, using either a linear or a radial basis function (RBF) kernel, achieved multi-class classification accuracies of 55.6% and 55.0% in the challenge test set (60 NC, 60 MCI, 60 cMCI, 60 AD), resulting in a third place in the challenge. Similar feature subset sizes were obtained for both kernels, and the most frequently selected MRI features were the volumes of the two hippocampal subregions left presubiculum and right subiculum. Post-challenge analysis revealed that enforcing a minimum number of selected features and increasing the number of ensemble classifiers improved classification accuracy up to 59.1%. The ensemble SVM outperformed single SVM classifications consistently in the challenge test set. Ensemble methods using bagging and feature selection can improve the performance of the commonly applied SVM classifier in dementia classification. This resulted in competitive classification accuracies in the International Challenge for Automated Prediction of MCI from MRI data. Copyright © 2018 Elsevier B.V. All rights reserved.

Towards Massive Machine Type Cellular Communications

OpenAIRE

Dawy, Zaher; Saad, Walid; Ghosh, Arunabha; Andrews, Jeffrey G.; Yaacoub, Elias

2015-01-01

Cellular networks have been engineered and optimized to carrying ever-increasing amounts of mobile data, but over the last few years, a new class of applications based on machine-centric communications has begun to emerge. Automated devices such as sensors, tracking devices, and meters - often referred to as machine-to-machine (M2M) or machine-type communications (MTC) - introduce an attractive revenue stream for mobile network operators, if a massive number of them can be efficiently support...

Diamond turning machine controller implementation

Energy Technology Data Exchange (ETDEWEB)

Garrard, K.P.; Taylor, L.W.; Knight, B.F.; Fornaro, R.J.

1988-12-01

The standard controller for a Pnuemo ASG 2500 Diamond Turning Machine, an Allen Bradley 8200, has been replaced with a custom high-performance design. This controller consists of four major components. Axis position feedback information is provided by a Zygo Axiom 2/20 laser interferometer with 0.1 micro-inch resolution. Hardware interface logic couples the computers digital and analog I/O channels to the diamond turning machine`s analog motor controllers, the laser interferometer, and other machine status and control information. It also provides front panel switches for operator override of the computer controller and implement the emergency stop sequence. The remaining two components, the control computer hardware and software, are discussed in detail below.

Integrated Inverter For Driving Multiple Electric Machines

Science.gov (United States)

Su, Gui-Jia [Knoxville, TN; Hsu, John S [Oak Ridge, TN

2006-04-04

An electric machine drive (50) has a plurality of inverters (50a, 50b) for controlling respective electric machines (57, 62), which may include a three-phase main traction machine (57) and two-phase accessory machines (62) in a hybrid or electric vehicle. The drive (50) has a common control section (53, 54) for controlling the plurality of inverters (50a, 50b) with only one microelectronic processor (54) for controlling the plurality of inverters (50a, 50b), only one gate driver circuit (53) for controlling conduction of semiconductor switches (S1-S10) in the plurality of inverters (50a, 50b), and also includes a common dc bus (70), a common dc bus filtering capacitor (C1) and a common dc bus voltage sensor (67). The electric machines (57, 62) may be synchronous machines, induction machines, or PM machines and may be operated in a motoring mode or a generating mode.

Choosing between different AI approaches? The scientific benefits of the confrontation, and the new collaborative era between humans and machines

Directory of Open Access Journals (Sweden)

Jordi Vallverdú

2008-07-01

Full Text Available AI is a multidisciplinary activity that involves specialists from several fields, and we can say that the aim of science, and AI science, is solving problems. AI and computer sciences are been creating a new kind of making science, that we can call in silico science. Both models top-eown and bottomup are useful for e-scientific research. There is no a real controversy between them. Besides, the extended mind model of human cognition, involves human-machine interactions. Huge amount of data requires new ways to make and organize scientific practices: supercomputers, grids, distributed computing, specific software and middleware and, basically, more efficient and visual ways to interact with information. This is one of the key points to understand contemporary relationships between humans and machines: usability of scientific data.

Quantum Machine Learning

OpenAIRE

Romero García, Cristian

2017-01-01

[EN] In a world in which accessible information grows exponentially, the selection of the appropriate information turns out to be an extremely relevant problem. In this context, the idea of Machine Learning (ML), a subfield of Artificial Intelligence, emerged to face problems in data mining, pattern recognition, automatic prediction, among others. Quantum Machine Learning is an interdisciplinary research area combining quantum mechanics with methods of ML, in which quantum properties allow fo...

Automatic welding machine for piping

International Nuclear Information System (INIS)

Yoshida, Kazuhiro; Koyama, Takaichi; Iizuka, Tomio; Ito, Yoshitoshi; Takami, Katsumi.

1978-01-01

A remotely controlled automatic special welding machine for piping was developed. This machine is utilized for long distance pipe lines, chemical plants, thermal power generating plants and nuclear power plants effectively from the viewpoint of good quality control, reduction of labor and good controllability. The function of this welding machine is to inspect the shape and dimensions of edge preparation before welding work by the sense of touch, to detect the temperature of melt pool, inspect the bead form by the sense of touch, and check the welding state by ITV during welding work, and to grind the bead surface and inspect the weld metal by ultrasonic test automatically after welding work. The construction of this welding system, the main specification of the apparatus, the welding procedure in detail, the electrical source of this welding machine, the cooling system, the structure and handling of guide ring, the central control system and the operating characteristics are explained. The working procedure and the effect by using this welding machine, and the application to nuclear power plants and the other industrial field are outlined. The HIDIC 08 is used as the controlling computer. This welding machine is useful for welding SUS piping as well as carbon steel piping. (Nakai, Y.)

COGNITIVE COMPETENCE COMPARED TO COGNITIVE INDEPENDENCE AND COGNITIVE ACTIVITY

Directory of Open Access Journals (Sweden)

Irina B. Shmigirilova

2014-01-01

Full Text Available The research is aimed at identifying the essence of the cognitive competence concept in comparison with the concepts of cognitive independence and activity.Methods: The methodology implies a theoretical analysis of psychopedagogical and methodological materials on the cognitive competence formation; generalized teaching experience; empirical methods of direct observations of educational process in the secondary school classrooms; interviews with school teachers and pupils.Results: The research outcomes reveal a semantic intersection between the cognitive competence, independence and activity, and their distinctive features. The paper emphasizes the importance of cognitive competence as an adaptive mechanism in situations of uncertainty and instability.Scientific novelty: The author clarifies the concept of cognitive competence regarding it as a multi-component and systematic characteristic of a personality.Practical significance: The research findings can be used by specialists in didactics developing the teaching techniques of cognitive competence formation for schoolchildren.

49 CFR 173.174 - Refrigerating machines.

Science.gov (United States)

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Refrigerating machines. 173.174 Section 173.174 Transportation Other Regulations Relating to Transportation PIPELINE AND HAZARDOUS MATERIALS SAFETY... Refrigerating machines. A refrigerating machine assembled for shipment and containing 7 kg (15 pounds) or less...

Challenges for coexistence of machine to machine and human to human applications in mobile network

DEFF Research Database (Denmark)

Sanyal, R.; Cianca, E.; Prasad, Ramjee

2012-01-01

A key factor for the evolution of the mobile networks towards 4G is to bring to fruition high bandwidth per mobile node. Eventually, due to the advent of a new class of applications, namely, Machine-to-Machine, we foresee new challenges where bandwidth per user is no more the primal driver...... be evolved to address various nuances of the mobile devices used by man and machines. The bigger question is as follows. Is the state-of-the-art mobile network designed optimally to cater both the Human-to-Human and Machine-to-Machine applications? This paper presents the primary challenges....... As an immediate impact of the high penetration of M2M devices, we envisage a surge in the signaling messages for mobility and location management. The cell size will shrivel due to high tele-density resulting in even more signaling messages related to handoff and location updates. The mobile network should...

Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data.

Science.gov (United States)

Hepworth, Philip J; Nefedov, Alexey V; Muchnik, Ilya B; Morgan, Kenton L

2012-08-07

Machine-learning algorithms pervade our daily lives. In epidemiology, supervised machine learning has the potential for classification, diagnosis and risk factor identification. Here, we report the use of support vector machine learning to identify the features associated with hock burn on commercial broiler farms, using routinely collected farm management data. These data lend themselves to analysis using machine-learning techniques. Hock burn, dermatitis of the skin over the hock, is an important indicator of broiler health and welfare. Remarkably, this classifier can predict the occurrence of high hock burn prevalence with accuracy of 0.78 on unseen data, as measured by the area under the receiver operating characteristic curve. We also compare the results with those obtained by standard multi-variable logistic regression and suggest that this technique provides new insights into the data. This novel application of a machine-learning algorithm, embedded in poultry management systems could offer significant improvements in broiler health and welfare worldwide.

Optimization of pocket machining strategy in HSM

OpenAIRE

Msaddek, El Bechir; Bouaziz, Zoubeir; Dessein, Gilles; Baili, Maher

2012-01-01

International audience; Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the ...

Machine learning with R cookbook

CERN Document Server

Chiu, Yu-Wei

2015-01-01

If you want to learn how to use R for machine learning and gain insights from your data, then this book is ideal for you. Regardless of your level of experience, this book covers the basics of applying R to machine learning through to advanced techniques. While it is helpful if you are familiar with basic programming or machine learning concepts, you do not require prior experience to benefit from this book.

Autocoding State Machine in Erlang

DEFF Research Database (Denmark)

Guo, Yu; Hoffman, Torben; Gunder, Nicholas

2008-01-01

This paper presents an autocoding tool suit, which supports development of state machine in a model-driven fashion, where models are central to all phases of the development process. The tool suit, which is built on the Eclipse platform, provides facilities for the graphical specification...... of a state machine model. Once the state machine is specified, it is used as input to a code generation engine that generates source code in Erlang....

Finite Element Method in Machining Processes

CERN Document Server

Markopoulos, Angelos P

2013-01-01

Finite Element Method in Machining Processes provides a concise study on the way the Finite Element Method (FEM) is used in the case of manufacturing processes, primarily in machining. The basics of this kind of modeling are detailed to create a reference that will provide guidelines for those who start to study this method now, but also for scientists already involved in FEM and want to expand their research. A discussion on FEM, formulations and techniques currently in use is followed up by machining case studies. Orthogonal cutting, oblique cutting, 3D simulations for turning and milling, grinding, and state-of-the-art topics such as high speed machining and micromachining are explained with relevant examples. This is all supported by a literature review and a reference list for further study. As FEM is a key method for researchers in the manufacturing and especially in the machining sector, Finite Element Method in Machining Processes is a key reference for students studying manufacturing processes but al...

Superconducting three element synchronous ac machine

International Nuclear Information System (INIS)

Boyer, L.; Chabrerie, J.P.; Mailfert, A.; Renard, M.

1975-01-01

There is a growing interest in ac superconducting machines. Of several new concepts proposed for these machines in the last years one of the most promising seems to be the ''three elements'' concept which allows the cancellation of the torque acting on the superconducting field winding, thus overcoming some of the major contraints. This concept leads to a device of induction-type generator. A synchronous, three element superconducting ac machine is described, in which a room temperature, dc fed rotating winding is inserted between the superconducting field winding and the ac armature. The steady-state machine theory is developed, the flux linkages are established, and the torque expressions are derived. The condition for zero torque on the field winding, as well as the resulting electrical equations of the machine, are given. The theoretical behavior of the machine is studied, using phasor diagrams and assuming for the superconducting field winding either a constant current or a constant flux condition

Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks.

Science.gov (United States)

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2013-11-01

One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities using smart home technologies. In this paper, we introduce a machine learning-based method for assessing activity quality in smart homes. To validate our approach we quantify activity quality for 179 volunteer participants who performed a complex, interweaved set of activities in our smart home apartment. We observed a statistically significant correlation (r=0.79) between automated assessment of task quality and direct observation scores. Using machine learning techniques to predict the cognitive health of the participants based on task quality is accomplished with an AUC value of 0.64. We believe that this capability is an important step in understanding everyday functional health of individuals in their home environments.

Asymmetric quantum cloning machines

International Nuclear Information System (INIS)

Cerf, N.J.

1998-01-01

A family of asymmetric cloning machines for quantum bits and N-dimensional quantum states is introduced. These machines produce two approximate copies of a single quantum state that emerge from two distinct channels. In particular, an asymmetric Pauli cloning machine is defined that makes two imperfect copies of a quantum bit, while the overall input-to-output operation for each copy is a Pauli channel. A no-cloning inequality is derived, characterizing the impossibility of copying imposed by quantum mechanics. If p and p ' are the probabilities of the depolarizing channels associated with the two outputs, the domain in (√p,√p ' )-space located inside a particular ellipse representing close-to-perfect cloning is forbidden. This ellipse tends to a circle when copying an N-dimensional state with N→∞, which has a simple semi-classical interpretation. The symmetric Pauli cloning machines are then used to provide an upper bound on the quantum capacity of the Pauli channel of probabilities p x , p y and p z . The capacity is proven to be vanishing if (√p x , √p y , √p z ) lies outside an ellipsoid whose pole coincides with the depolarizing channel that underlies the universal cloning machine. Finally, the tradeoff between the quality of the two copies is shown to result from a complementarity akin to Heisenberg uncertainty principle. (author)

Enhancing Human-Machine System Performance by Introducing Artificial Cognition in Vehicle Guidance Work Systems

Science.gov (United States)

2009-10-01

evaluated after each mission using the NASA - TLX method [21]. Moreover, they were interviewed to be able to state problems and suggest system...France, 3 rd -4 th September 2008. [21] Sandra G. Hart & Lowell E. Staveland (1988). Development of NASA - TLX (Task Load Index): Results of...o b s e rv a b le b e h a v io u r o f C P = A C U b e h a v io u r Interpretation Figure 11: The Cognitive Process for generating knowledge

Using theta and alpha band power to assess cognitive workload in multitasking environments.

Science.gov (United States)

Puma, Sébastien; Matton, Nadine; Paubel, Pierre-V; Raufaste, Éric; El-Yagoubi, Radouane

2018-01-01

Cognitive workload is of central importance in the fields of human factors and ergonomics. A reliable measurement of cognitive workload could allow for improvements in human machine interface designs and increase safety in several domains. At present, numerous studies have used electroencephalography (EEG) to assess cognitive workload, reporting the rise in cognitive workload to be associated with increases in theta band power and decreases in alpha band power. However, results have been inconsistent with some failing to reach the required level of significance. We hypothesized that the lack of consistency could be related to individual differences in task performance and/or to the small sample sizes in most EEG studies. In the present study we used EEG to assess the increase in cognitive workload occurring in a multitasking environment while taking into account differences in performance. Twenty participants completed a task commonly used in airline pilot recruitment, which included an increasing number of concurrent sub-tasks to be processed from one to four. Subjective ratings, performances scores, pupil size and EEG signals were recorded. Results showed that increases in EEG alpha and theta band power reflected increases in the involvement of cognitive resources for the completion of one to three subtasks in a multitasking environment. These values reached a ceiling when performances dropped. Consistent differences in levels of alpha and theta band power were associated to levels of task performance: highest performance was related to lowest band power. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of tunnel boring machine performance using machine and rock mass data

International Nuclear Information System (INIS)

Dastgir, G.

2012-01-01

Performance of the tunnel boring machine and its prediction by different methods has been a hot issue since the first TBM came into being. For the sake of safe and sound transport, improvement of hydro-power, mining, civil and many other tunneling projects that cannot be driven efficiently and economically by conventional drill and blast, TBMs are quite frequently used. TBM parameters and rock mass properties, which heavily influence machine performance, should be estimated or known before choice of TBM-type and start of excavation. By applying linear regression analysis (SPSS19), fuzzy logic tools and a special Math-Lab code on actual field data collected from seven TBM driven tunnels (Hieflau expansion, Queen water tunnel, Vereina, Hemerwald, Maen, Pieve and Varzo tunnel), an attempt was made to provide prediction of rock mass class (RMC), rock fracture class (RFC), penetration rate (PR) and advance rate (AR). For detailed analysis of TBM performance, machine parameters (thrust, machine rpm, torque, power etc.), machine types and specification and rock mass properties (UCS, discontinuity in rock mass, RMC, RFC, RMR, etc.) were analyzed by 3-D surface plotting using statistical software R. Correlations between machine parameters and rock mass properties which effectively influence prediction models, are presented as well. In Hieflau expansion tunnel AR linearly decreases with increase of thrust due to high dependence of machine advance rate upon rock strength. For Hieflau expansion tunnel three types of data (TBM, rock mass and seismic data e.g. amplitude, pseudo velocity etc.) were coupled and simultaneously analyzed by plotting 3-D surfaces. No appreciable correlation between seismic data (Amplitude and Pseudo velocity) and rock mass properties and machine parameters could be found. Tool wear as a function of TBM operational parameters was analyzed which revealed that tool wear is minimum if applied thrust is moderate and that tool wear is high when thrust is

48 CFR 908.7103 - Office machines.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Office machines. 908.7103... PLANNING REQUIRED SOURCES OF SUPPLIES AND SERVICES Acquisition of Special Items 908.7103 Office machines. Acquisitions of office machines by DOE offices and its authorized contractors shall be in accordance with FPMR...

20 CFR 368.3 - Vending machines.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Vending machines. 368.3 Section 368.3 Employees' Benefits RAILROAD RETIREMENT BOARD INTERNAL ADMINISTRATION, POLICY AND PROCEDURES PROHIBITION OF CIGARETTE SALES TO MINORS § 368.3 Vending machines. The sale of tobacco products in vending machines is...

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

Non-equilibrium quantum heat machines

Science.gov (United States)

Alicki, Robert; Gelbwaser-Klimovsky, David

2015-11-01

Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound.

Non-equilibrium quantum heat machines

International Nuclear Information System (INIS)

Alicki, Robert; Gelbwaser-Klimovsky, David

2015-01-01

Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound. (paper)

Microsoft Azure machine learning

CERN Document Server

Mund, Sumit

2015-01-01

The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

Coil Optimization for HTS Machines

DEFF Research Database (Denmark)

Mijatovic, Nenad; Jensen, Bogi Bech; Abrahamsen, Asger Bech

An optimization approach of HTS coils in HTS synchronous machines (SM) is presented. The optimization is aimed at high power SM suitable for direct driven wind turbines applications. The optimization process was applied to a general radial flux machine with a peak air gap flux density of ~3T...... is suitable for which coil segment is presented. Thus, the performed study gives valuable input for the coil design of HTS machines ensuring optimal usage of HTS tapes....

vSphere virtual machine management

CERN Document Server

Fitzhugh, Rebecca

2014-01-01

This book follows a step-by-step tutorial approach with some real-world scenarios that vSphere businesses will be required to overcome every day. This book also discusses creating and configuring virtual machines and also covers monitoring virtual machine performance and resource allocation options. This book is for VMware administrators who want to build their knowledge of virtual machine administration and configuration. It's assumed that you have some experience with virtualization administration and vSphere.

An Evaluative Study of Machine Translation in the EFL Scenario of Saudi Arabia

Directory of Open Access Journals (Sweden)

Raneem Khalid Al-Tuwayrish

2016-02-01

Full Text Available Artificial Intelligence or AI as it is popularly known and its corollary, Machine Translation (MT have long engaged scientists, thinkers and linguists alike in the twenty first century. However, the wider question that lies in the relation between technology and translation is, What does technology do to language? This is an important question in the current paradigm because new translation technologies, such as, translation memories, data-based machine translation, and collaborative translation, far from being just additional tools, are changing the very nature of the translators’ cognitive activity, social relations, and professional standing. In fact, in some translation situations such as when translating technical materials or subject matter that are not a specialization with human translators, one potentially needs technology.  The purview of this paper, however, is limited to the role of MT in day to day situations where the generic MT tools like Google Translate or Bing Translator are encouraged. Further, it endeavours to weigh and empirically demonstrate the pros and cons of MT with a view to recommending measures for better communication training in the EFL set up of Saudi Arabia. Keywords: AI, MT, translation, technology, necessity, communication

Technology of magnetic abrasive finishing in machining of difficult-to-machine alloy complex surface

Directory of Open Access Journals (Sweden)

Fujian MA

2016-10-01

Full Text Available The technology of magnetic abrasive finishing is one of the important finishing technologies. Combining with low-frequency vibration and ultrasonic vibration, it can attain higher precision, quality and efficiency. The characteristics and the related current research of magnetic abrasive finishing, vibration assisted magnetic abrasive finishing and ultrasonic assisted magnetic abrasive finishing are introduced. According to the characteristics of the difficult-to-machine alloy's complex surface, the important problems for further study are presented to realize the finishing of complex surface with the technology of magnetic abrasive finishing, such as increasing the machining efficiency by enhancing the magnetic flux density of machining gap and compounding of magnetic energy and others, establishing of the control function during machining and the process planning method for magnetic abrasive finishing of complex surface under the space geometry restraint of complex surface on magnetic pole, etc.

Potential of Cognitive Computing and Cognitive Systems

Science.gov (United States)

Noor, Ahmed K.

2015-01-01

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp

The Button Sew Machine. Module 12.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the button sew machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the button sew machine. These components are provided: an introduction, direction, an objective, learning activities, student information, a student self-check, and a…

The Zig Zag Machine. Module 14.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the zig zag machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the zig zag machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and a…

The Bar Tack Machine. Module 16.

Science.gov (United States)

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the bar tack machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the bar tack machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and a…

Machine function based control code algebras

NARCIS (Netherlands)

Bergstra, J.A.

Machine functions have been introduced by Earley and Sturgis in [6] in order to provide a mathematical foundation of the use of the T-diagrams proposed by Bratman in [5]. Machine functions describe the operation of a machine at a very abstract level. A theory of hardware and software based on

New Applications of Learning Machines

DEFF Research Database (Denmark)

Larsen, Jan

* Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection......* Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection...

Marketing and vending machine; Marketing to jido hanbaiki

Energy Technology Data Exchange (ETDEWEB)

Onzo, N. [Waseda University, Tokyo (Japan)

1999-08-10

Vending machines in Japan have made original progress and have developed into big business. Annual sales by vending machines are 6 trillion 700 billion yen, which exceeds 6 trillion 100 billion yen sales by convenience stores. Research on vending machines may have advanced on the technical side but almost none on the marketing. In a vending machine that made an appearance in 1980 with the feature of a lottery, the winning probability was approximately one in fifty. In addition to a simple vending function, these machines have a promotion function. Some other machines have an electrical display of a commercial for products inside the machine for the purpose of attracting attention of passersby. This is an advertising function of the machines. In other words, one vending machine is capable of various marketing functions. This precisely means the subjects are numerous in the marketing research on vending machines. In contrast to the present century in which technical innovations have been made for vending machines, the coming 21st century may turn out to be the one in which marketing innovations are the mainstream for them. (NEDO)

High pressure water jet mining machine

Science.gov (United States)

Barker, Clark R.

1981-05-05

A high pressure water jet mining machine for the longwall mining of coal is described. The machine is generally in the shape of a plowshare and is advanced in the direction in which the coal is cut. The machine has mounted thereon a plurality of nozzle modules each containing a high pressure water jet nozzle disposed to oscillate in a particular plane. The nozzle modules are oriented to cut in vertical and horizontal planes on the leading edge of the machine and the coal so cut is cleaved off by the wedge-shaped body.

Cognitive allocation and the control room

International Nuclear Information System (INIS)

Paradies, M.W.

1985-01-01

One of the weakest links in the design of nuclear power plants is the inattention to the needs and capabilities of the operators. This flaw causes decreased plant reliability and reduced plant safety. To solve this problem the designer must, in the earliest stages of the design process, consider the operator's abilities. After the system requirements have been established, the designer must consider what functions to allocate to each part of the system. The human must be considered as part of this system. The allocation of functions needs to consider not only the mechanical tasks to be performed, but also the control requirements and the overall control philosophy. In order for the designers to consider the control philosophy, they need to know what control decisions should be automated and what decisions should be made by an operator. They also need to know how these decisions will be implemented: by an operator or by automation. ''Cognitive Allocation'' is the allocation of the decision making process between operators and machines. It defines the operator's role in the system. When designing a power plant, a cognitive allocation starts the process of considering the operator's abilities. This is the first step to correcting the weakest link in the current plant design

DESIGN OF GRASS BRIQUETTE MACHINE

African Journals Online (AJOL)

user

E-mail addresses: 1 mike.ajieh@gmail.com, 2 dracigboanugo@yahoo.com, ... machine design was considered for processing biomass of grass origin. The machine operations include pulverization, compaction and extrusion of the briquettes.

Surface mining machines problems of maintenance and modernization

CERN Document Server

Rusiński, Eugeniusz; Moczko, Przemysław; Pietrusiak, Damian

2017-01-01

This unique volume imparts practical information on the operation, maintenance, and modernization of heavy performance machines such as lignite mine machines, bucket wheel excavators, and spreaders. Problems of large scale machines (mega machines) are highly specific and not well recognized in the common mechanical engineering environment. Prof. Rusiński and his co-authors identify solutions that increase the durability of these machines as well as discuss methods of failure analysis and technical condition assessment procedures. "Surface Mining Machines: Problems in Maintenance and Modernization" stands as a much-needed guidebook for engineers facing the particular challenges of heavy performance machines and offers a distinct and interesting demonstration of scale-up issues for researchers and scientists from across the fields of machine design and mechanical engineering.

Collective cognition in humans: groups outperform their best members in a sentence reconstruction task.

Directory of Open Access Journals (Sweden)

Romain J G Clément

Full Text Available Group-living is widespread among animals and one of the major advantages of group-living is the ability of groups to solve cognitive problems that exceed individual ability. Humans also make use of collective cognition and have simultaneously developed a highly complex language to exchange information. Here we investigated collective cognition of human groups regarding language use in a realistic situation. Individuals listened to a public announcement and had to reconstruct the sentence alone or in groups. This situation is often encountered by humans, for instance at train stations or airports. Using recent developments in machine speech recognition, we analysed how well individuals and groups reconstructed the sentences from a syntactic (i.e., the number of errors and semantic (i.e., the quality of the retrieved information perspective. We show that groups perform better both on a syntactic and semantic level than even their best members. Groups made fewer errors and were able to retrieve more information when reconstructing the sentences, outcompeting even their best group members. Our study takes collective cognition studies to the more complex level of language use in humans.

Unraveling cognitive traits using the Morris water maze unbiased strategy classification (MUST-C) algorithm.

Science.gov (United States)

Illouz, Tomer; Madar, Ravit; Louzon, Yoram; Griffioen, Kathleen J; Okun, Eitan

2016-02-01

The assessment of spatial cognitive learning in rodents is a central approach in neuroscience, as it enables one to assess and quantify the effects of treatments and genetic manipulations from a broad perspective. Although the Morris water maze (MWM) is a well-validated paradigm for testing spatial learning abilities, manual categorization of performance in the MWM into behavioral strategies is subject to individual interpretation, and thus to biases. Here we offer a support vector machine (SVM) - based, automated, MWM unbiased strategy classification (MUST-C) algorithm, as well as a cognitive score scale. This model was examined and validated by analyzing data obtained from five MWM experiments with changing platform sizes, revealing a limitation in the spatial capacity of the hippocampus. We have further employed this algorithm to extract novel mechanistic insights on the impact of members of the Toll-like receptor pathway on cognitive spatial learning and memory. The MUST-C algorithm can greatly benefit MWM users as it provides a standardized method of strategy classification as well as a cognitive scoring scale, which cannot be derived from typical analysis of MWM data. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Cognitive Connected Vehicle Information System Design Requirement for Safety: Role of Bayesian Artificial Intelligence

Directory of Open Access Journals (Sweden)

Ata Khan

2013-04-01

Full Text Available Intelligent transportation systems (ITS are gaining acceptance around the world and the connected vehicle component of ITS is recognized as a high priority research and development area in many technologically advanced countries. Connected vehicles are expected to have the capability of safe, efficient and eco-driving operations whether these are under human control or in the adaptive machine control mode of operations. The race is on to design the capability to operate in connected traffic environment. The operational requirements can be met with cognitive vehicle design features made possible by advances in artificial intelligence-supported methodology, improved understanding of human factors, and advances in communication technology. This paper describes cognitive features and their information system requirements. The architecture of an information system is presented that supports the features of the cognitive connected vehicle. For better focus, information processing capabilities are specified and the role of Bayesian artificial intelligence is defined for data fusion. Example applications illustrate the role of information systems in integrating intelligent technology, Bayesian artificial intelligence, and abstracted human factors. Concluding remarks highlight the role of the information system and Bayesian artificial intelligence in the design of a new generation of cognitive connected vehicle.

Power training using pneumatic machines vs. plate-loaded machines to improve muscle power in older adults.

Science.gov (United States)

Balachandran, Anoop T; Gandia, Kristine; Jacobs, Kevin A; Streiner, David L; Eltoukhy, Moataz; Signorile, Joseph F

2017-11-01

Power training has been shown to be more effective than conventional resistance training for improving physical function in older adults; however, most trials have used pneumatic machines during training. Considering that the general public typically has access to plate-loaded machines, the effectiveness and safety of power training using plate-loaded machines compared to pneumatic machines is an important consideration. The purpose of this investigation was to compare the effects of high-velocity training using pneumatic machines (Pn) versus standard plate-loaded machines (PL). Independently-living older adults, 60years or older were randomized into two groups: pneumatic machine (Pn, n=19) and plate-loaded machine (PL, n=17). After 12weeks of high-velocity training twice per week, groups were analyzed using an intention-to-treat approach. Primary outcomes were lower body power measured using a linear transducer and upper body power using medicine ball throw. Secondary outcomes included lower and upper body muscle muscle strength, the Physical Performance Battery (PPB), gallon jug test, the timed up-and-go test, and self-reported function using the Patient Reported Outcomes Measurement Information System (PROMIS) and an online video questionnaire. Outcome assessors were blinded to group membership. Lower body power significantly improved in both groups (Pn: 19%, PL: 31%), with no significant difference between the groups (Cohen's d=0.4, 95% CI (-1.1, 0.3)). Upper body power significantly improved only in the PL group, but showed no significant difference between the groups (Pn: 3%, PL: 6%). For balance, there was a significant difference between the groups favoring the Pn group (d=0.7, 95% CI (0.1, 1.4)); however, there were no statistically significant differences between groups for PPB, gallon jug transfer, muscle muscle strength, timed up-and-go or self-reported function. No serious adverse events were reported in either of the groups. Pneumatic and plate

Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

OpenAIRE

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

2014-01-01

Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

OpenAIRE

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

2016-01-01

Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

Functional Correspondence between Evaluators and Abstract Machines

DEFF Research Database (Denmark)

Ager, Mads Stig; Biernacki, Dariusz; Danvy, Olivier

2003-01-01

We bridge the gap between functional evaluators and abstract machines for the λ-calculus, using closure conversion, transformation into continuation-passing style, and defunctionalization.We illustrate this approach by deriving Krivine's abstract machine from an ordinary call-by-name evaluator...... and by deriving an ordinary call-by-value evaluator from Felleisen et al.'s CEK machine. The first derivation is strikingly simpler than what can be found in the literature. The second one is new. Together, they show that Krivine's abstract machine and the CEK machine correspond to the call-by-name and call...

Machine learning in healthcare informatics

CERN Document Server

Acharya, U; Dua, Prerna

2014-01-01

The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.

Historical and Epistemological Reflections on the Culture of Machines around the Renaissance: Machines, Machineries and Perpetual Motion

Directory of Open Access Journals (Sweden)

Raffaele Pisano

2015-05-01

Full Text Available This paper is the second part of our recent paper ‘Historical and Epistemological Reflections on the Culture of Machines around the Renaissance: How Science and Technique Work’ (Pisano & Bussotti 2014a. In the first paper—which discussed some aspects of the relations between science and technology from Antiquity to the Renaissance—we highlighted the differences between the Aristotelian/Euclidean tradition and the Archimedean tradition. We also pointed out the way in which the two traditions were perceived around the Renaissance. The Archimedean tradition is connected with machines: its relationship with science and construction of machines should be made clear. It is enough to think that Archimedes mainly dealt with three machines: lever, pulley and screw (and a correlated principle of mechanical advantage. As underlined in the first part, our thesis is that many machines were constructed by people who ignored theory, even though, in other cases, the knowledge of the Archimedean tradition was a precious help in order to build machines. Hence, an a priori idea as to the relations between the Archimedean tradition and construction of machines cannot exist. In this second part we offer some examples of functioning machines constructed by people who ignored any physical theory, whereas, in other cases, the ignorance of some principles—such as the impossibility of a perpetuum mobile—induced the attempt to construct impossible machines. What is very interesting is that these machines did not function, of course, as a perpetuum mobile, but anyway had their functioning and were useful for certain aims, although they were constructed on an idea which is completely wrong from a theoretical point of view. We mainly focus on the Renaissance and early modern period, but we also provide examples of machines built before and after this period. We have followed a chronological order in both parts, starting from the analysis of the situation in

QCD machines - present and future

International Nuclear Information System (INIS)

Christ, N.H.

1991-01-01

The present status of the currently working and nearly working dedicated QCD machines is reviewed and proposals for future machines are discussed with particular emphasis on the QCD Teraflop Project in the US. (orig.)

Cosimo: a cognitive simulation model of human decision making and behaviour in complex work environments

International Nuclear Information System (INIS)

Cacciabue, P.C.; Decortis, F.; Nordvik, J.P.; Drozdowicz, B.; Masson, M.

1992-01-01

In this paper the Cognitive Simulation Model (COSIMO), currently implemented at the Ispra JRC, is described, with particular emphasis on its theoretical foundations, on its computational implementation and on a number of simulations cases of man-machine system interactions. COSIMO runs on a lisp machine and it interacts with the simulation of the physical system implemented on a Sun computer. In our case the physical system is a typical Nuclear Power Plant subsystem - the Auxiliary Feed-Water System (AFWS). One basic application is to explore human behaviour in simulated accident situations in order to identify suitable safety recommendations. To be more specific, COSIMO can be used to: - analyse how operators are likely to act given a particular context, - identify difficult problem solving situations, given problem solving resources and constraints (operator knowledge, man-machine interfaces, procedures), - identify situations that can lead to human errors and evaluate their consequences, - identify and test conditions for error recovery, - investigate the effects of changes in the man-machine system. Since the modelling of the AFWS, its control system and procedures have also been the object of a detailed description (Cacciabue et al., 1990a), the objective of this paper is the presentation of the state of the art of the COSIMO simulation

Metal release from coffee machines and electric kettles.

Science.gov (United States)

Müller, Frederic D; Hackethal, Christin; Schmidt, Roman; Kappenstein, Oliver; Pfaff, Karla; Luch, Andreas

2015-01-01

The release of elemental ions from 8 coffee machines and 11 electric kettles into food simulants was investigated. Three different types of coffee machines were tested: portafilter espresso machines, pod machines and capsule machines. All machines were tested subsequently on 3 days before and on 3 days after decalcification. Decalcification of the machines was performed with agents according to procedures as specified in the respective manufacturer's manuals. The electric kettles showed only a low release of the elements analysed. For the coffee machines decreasing concentrations of elements were found from the first to the last sample taken in the course of 1 day. Metal release on consecutive days showed a decreasing trend as well. After decalcification a large increase in the amounts of elements released was encountered. In addition, the different machine types investigated clearly differed in their extent of element release. By far the highest leaching, both quantitatively and qualitatively, was found for the portafilter machines. With these products releases of Pb, Ni, Mn, Cr and Zn were in the range and beyond the release limits as proposed by the Council of Europe. Therefore, a careful rinsing routine, especially after decalcification, is recommended for these machines. The comparably lower extent of release of one particular portafilter machine demonstrates that metal release at levels above the threshold that triggers health concerns are technically avoidable.

Modularity Design Approach for Preventive Machine Maintenance

Science.gov (United States)

Ernawati, D.; Pudji, E.; Ngatilah, Y.; Handoyo, R.

2018-01-01

In a company, machine maintenance system will be very influential in production process activity. The company should have a scheduled engine maintenance system that does not require high costs when repairing and replacing machine parts. Modularity Design method is able to provide solutions to the engine maintenance scheduling system and can prevent fatal damage to the engine components. It can minimize the cost of repair and replacement of these machine components.The paper provides a solution to machine maintenance problems. The paper is also completed with case study of milling machines. That case studies can give us a real description about impact implementation of modularity design to prevent fatal damage to components and minimize the cost of repair and replacement of components of the machine.

Machine learning with R

CERN Document Server

Lantz, Brett

2015-01-01

Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

Human Machine Learning Symbiosis

Science.gov (United States)

Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

2017-01-01

Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

Human-Machine Communication

International Nuclear Information System (INIS)

Farbrot, J.E.; Nihlwing, Ch.; Svengren, H.

2005-01-01

New requirements for enhanced safety and design changes in process systems often leads to a step-wise installation of new information and control equipment in the control room of older nuclear power plants, where nowadays modern digital I and C solutions with screen-based human-machine interfaces (HMI) most often are introduced. Human factors (HF) expertise is then required to assist in specifying a unified, integrated HMI, where the entire integration of information is addressed to ensure an optimal and effective interplay between human (operators) and machine (process). Following a controlled design process is the best insurance for ending up with good solutions. This paper addresses the approach taken when introducing modern human-machine communication in the Oskarshamn 1 NPP, the results, and the lessons learned from this work with high operator involvement seen from an HF point of view. Examples of possibilities modern technology might offer for the operators are also addressed. (orig.)

Behind the machines

CERN Multimedia

Laëtitia Pedroso

2010-01-01

One of the first things we think about when someone mentions physics is the machines. But behind the machines, there are the men and women who design, build and operate them. In an exhibition at the Thinktank planetarium’s art gallery in Birmingham (UK), Claudia Marcelloni and her husband Neal Hartman—she is a photographer and Outreach Officer for ATLAS, while he is an engineer working on the ATLAS pixel detector—explore the human side of scientists.   The exhibition at the Thinktank Planetarium art gallery, Birmingham (UK). It all began two years ago with the publication of Exploring the mystery of matter, a book about ATLAS. “A Norwegian physicist friend, Heidi Sandaker, saw my photographs and suggested that I display them in a museum. I thought this was an interesting idea, except that the photos consisted entirely of depictions of machinery, with human beings completely absent. For me, showing the people who are behind the machines and the fascination ...

Gram staining with an automatic machine.

Science.gov (United States)

Felek, S; Arslan, A

1999-01-01

This study was undertaken to develop a new Gram-staining machine controlled by a micro-controller and to investigate the quality of slides that were stained in the machine. The machine was designed and produced by the authors. It uses standard 220 V AC. Staining, washing, and drying periods are controlled by a timer built in the micro-controller. A software was made that contains a certain algorithm and time intervals for the staining mode. One-hundred and forty smears were prepared from Escherichia coli, Staphylococcus aureus, Neisseria sp., blood culture, trypticase soy broth, direct pus and sputum smears for comparison studies. Half of the slides in each group were stained with the machine, the other half by hand and then examined by four different microbiologists. Machine-stained slides had a higher clarity and less debris than the hand-stained slides (p stained slides, some Gram-positive organisms showed poor Gram-positive staining features (p Gram staining with the automatic machine increases the staining quality and helps to decrease the work load in a busy diagnostic laboratory.

Addressing uncertainty in atomistic machine learning

DEFF Research Database (Denmark)

Peterson, Andrew A.; Christensen, Rune; Khorshidi, Alireza

2017-01-01

Machine-learning regression has been demonstrated to precisely emulate the potential energy and forces that are output from more expensive electronic-structure calculations. However, to predict new regions of the potential energy surface, an assessment must be made of the credibility of the predi......Machine-learning regression has been demonstrated to precisely emulate the potential energy and forces that are output from more expensive electronic-structure calculations. However, to predict new regions of the potential energy surface, an assessment must be made of the credibility...... of the predictions. In this perspective, we address the types of errors that might arise in atomistic machine learning, the unique aspects of atomistic simulations that make machine-learning challenging, and highlight how uncertainty analysis can be used to assess the validity of machine-learning predictions. We...... suggest this will allow researchers to more fully use machine learning for the routine acceleration of large, high-accuracy, or extended-time simulations. In our demonstrations, we use a bootstrap ensemble of neural network-based calculators, and show that the width of the ensemble can provide an estimate...

Diamond machining of micro-optical components and structures

Science.gov (United States)

Gläbe, Ralf; Riemer, Oltmann

2010-05-01

Diamond machining originates from the 1950s to 1970s in the USA. This technology was originally designed for machining of metal optics at macroscopic dimensions with so far unreached tolerances. During the following decades the machine tools, the monocrystalline diamond cutting tools, the workpiece materials and the machining processes advanced to even higher precision and flexibility. For this reason also the fabrication of small functional components like micro optics at a large spectrum of geometries became technologically and economically feasible. Today, several kinds of fast tool machining and multi axis machining operations can be applied for diamond machining of micro optical components as well as diffractive optical elements. These parts can either be machined directly as single or individual component or as mold insert for mass production by plastic replication. Examples are multi lens arrays, micro mirror arrays and fiber coupling lenses. This paper will give an overview about the potentials and limits of the current diamond machining technology with respect to micro optical components.

Machining of Fibre Reinforced Plastic Composite Materials

Science.gov (United States)

2018-01-01

Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented. PMID:29562635

Machining of Fibre Reinforced Plastic Composite Materials

Directory of Open Access Journals (Sweden)

Alessandra Caggiano

2018-03-01

Full Text Available Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented.

Superconducting magnetic systems and electrical machines

International Nuclear Information System (INIS)

Glebov, I.A.

1975-01-01

The use of superconductors for magnets and electrical machines attracts close attention of designers and scientists. A description is given of an ongoing research program to create superconductive magnetic systems, commutator motors, homopolar machines, topological generators and turbogenerators with superconductive field windings. All the machines are tentative experimental models and serve as a basis for further developments

Advanced Machining Toolpath for Low Distortion

Science.gov (United States)

2017-02-28

Advanced Machining Toolpath for Low Distortion FINAL STATUS REPORT Prepared by Brian Becker R&D Technology Manager Third Wave Systems, Inc... Machining Toolpath for Low Distortion December 2016 Contract No.: W911W6-16-P-0044 2 Table of Contents 1.0 EXECUTIVE SUMMARY...2 2.1 Task 1: Collect Details of Machining Lab to Support

Mini lathe machine converted to CNC

Directory of Open Access Journals (Sweden)

Alexandru Morar

2012-06-01

Full Text Available This paper presents the adaptation of a mechanical mini-lathing machine to a computerized numerical control (CNC lathing machine. This machine is composed of a ASIST mini-lathe and a two-degrees-of-freedom XZ stage designed specifically for this application. The whole system is controlled from a PC using adequate CNC control software.

Magnetic field-assisted electrochemical discharge machining

International Nuclear Information System (INIS)

Cheng, Chih-Ping; Mai, Chao-Chuang; Wu, Kun-Ling; Hsu, Yu-Shan; Yan, Biing-Hwa

2010-01-01

Electrochemical discharge machining (ECDM) is an effective unconventional method for micromachining in non-conducting materials, such as glass, quartz and some ceramics. However, since the spark discharge performance becomes unpredictable as the machining depth increases, it is hard to achieve precision geometry and efficient machining rate in ECDM drilling. One of the main factors for this is the lack of sufficient electrolyte flow in the narrow gap between the tool and the workpiece. In this study a magnetohydrodynamic (MHD) convection, which enhances electrolyte circulation has been applied to the ECDM process in order to upgrade the machining accuracy and efficiency. During electrolysis in the presence of a magnetic field, the Lorenz force induces the charged ions to form a MHD convection. The MHD convection then forces the electrolyte into movement, thus enhancing circulation of electrolyte. Experimental results show that the MHD convection induced by the magnetic field can effectively enhance electrolyte circulation in the micro-hole, which contributes to higher machining efficiency. Micro-holes in glass with a depth of 450 µm are drilled in less than 20 s. At the same time, better electrolyte circulation can prevent deterioration of gas film quality with increasing machining depth, while ensuring stable electrochemical discharge. The improvement in the entrance diameter thus achieved was 23.8% while that in machining time reached 57.4%. The magnetic field-assisted approach proposed in the research does not require changes in the machining setup or electrolyte but has proved to achieve significant enhancement in both accuracy and efficiency of ECDM.

On the importance of a rich embodiment in the grounding of concepts: perspectives from embodied cognitive science and computational linguistics.

Science.gov (United States)

Thill, Serge; Padó, Sebastian; Ziemke, Tom

2014-07-01

The recent trend in cognitive robotics experiments on language learning, symbol grounding, and related issues necessarily entails a reduction of sensorimotor aspects from those provided by a human body to those that can be realized in machines, limiting robotic models of symbol grounding in this respect. Here, we argue that there is a need for modeling work in this domain to explicitly take into account the richer human embodiment even for concrete concepts that prima facie relate merely to simple actions, and illustrate this using distributional methods from computational linguistics which allow us to investigate grounding of concepts based on their actual usage. We also argue that these techniques have applications in theories and models of grounding, particularly in machine implementations thereof. Similarly, considering the grounding of concepts in human terms may be of benefit to future work in computational linguistics, in particular in going beyond "grounding" concepts in the textual modality alone. Overall, we highlight the overall potential for a mutually beneficial relationship between the two fields. Copyright © 2014 Cognitive Science Society, Inc.

Machining refractory alloys: an overview

International Nuclear Information System (INIS)

Christopher, J.D.

1984-01-01

Nontraditional machining is a generic term for those material removal processes that differ drastically from the historic operations such as turning, milling, drilling, tapping, and grinding. The use of primary energy modes other than mechanical, such as thermal, electrical, and chemical, sets these operations apart and reinforces their nontraditional label. Several of these newer processes have been very successful in machining close tolerance parts from refractory materials. This paper provides a general overview of both traditional and nontraditional aspects of machining refractory materials. 11 figures, 7 tables

Structural dynamics of turbo-machines

CERN Document Server

Rangwala, AS

2009-01-01

The book presents a detailed and comprehensive treatment of structural vibration evaluation of turbo-machines. Starting with the fundamentals of the theory of vibration as related to various aspects of rotating machines, the dynamic analysis procedures of a broad spectrum of turbo-machines is covered. An in-depth procedure for analyzing the torsional and flexural oscillations of the components and of the rotor-bearing system is presented. The latest trends in design and analysis are presented, chief among them: Blade and coupled disk-blade mod

Sixth international conference on electrical machines and drives

International Nuclear Information System (INIS)

1993-01-01

This volume contains 111 papers presented at the Sixth International Conference on Electrical Machines and Drives. The topics covered include: miniature and micro motors; induction motors; DC machines; reluctance motors; condition monitoring; synchronous machines and drives; induction machines; induction generators; simulation; design; and operating experience; linear machines; noise and vibration; special machines. Separate abstracts have been prepared for a paper on linear step motors for control rod drives and for a paper on a motor drive for gas filtration in gas-cooled reactors. (UK)

Man - Machine Communication

CERN Document Server

Petersen, Peter; Nielsen, Henning

1984-01-01

This report describes a Man-to-Machine Communication module which together with a STAC can take care of all operator inputs from the touch-screen, tracker balls and mechanical buttons. The MMC module can also contain a G64 card which could be a GPIB driver but many other G64 cards could be used. The soft-ware services the input devices and makes the results accessible from the CAMAC bus. NODAL functions for the Man Machine Communication is implemented in the STAC and in the ICC.

Application of Machine Learning Techniques in Aquaculture

OpenAIRE

Rahman, Akhlaqur; Tasnim, Sumaira

2014-01-01

In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.

Machinability of IPS Empress 2 framework ceramic.

Science.gov (United States)

Schmidt, C; Weigl, P

2000-01-01

Using ceramic materials for an automatic production of ceramic dentures by CAD/CAM is a challenge, because many technological, medical, and optical demands must be considered. The IPS Empress 2 framework ceramic meets most of them. This study shows the possibilities for machining this ceramic with economical parameters. The long life-time requirement for ceramic dentures requires a ductile machined surface to avoid the well-known subsurface damages of brittle materials caused by machining. Slow and rapid damage propagation begins at break outs and cracks, and limits life-time significantly. Therefore, ductile machined surfaces are an important demand for machine dental ceramics. The machining tests were performed with various parameters such as tool grain size and feed speed. Denture ceramics were machined by jig grinding on a 5-axis CNC milling machine (Maho HGF 500) with a high-speed spindle up to 120,000 rpm. The results of the wear test indicate low tool wear. With one tool, you can machine eight occlusal surfaces including roughing and finishing. One occlusal surface takes about 60 min machining time. Recommended parameters for roughing are middle diamond grain size (D107), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 1000 mm/min, depth of cut a(e) = 0.06 mm, width of contact a(p) = 0.8 mm, and for finishing ultra fine diamond grain size (D46), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 100 mm/min, depth of cut a(e) = 0.02 mm, width of contact a(p) = 0.8 mm. The results of the machining tests give a reference for using IPS Empress(R) 2 framework ceramic in CAD/CAM systems. Copyright 2000 John Wiley & Sons, Inc.

An approach to modeling operator's cognitive behavior using artificial intelligence techniques in emergency operating event sequences

International Nuclear Information System (INIS)

Cheon, Se Woo; Sur, Sang Moon; Lee, Yong Hee; Park, Young Taeck; Moon, Sang Joon

1994-01-01

Computer modeling of an operator's cognitive behavior is a promising approach for the purpose of human factors study and man-machine systems assessment. In this paper, the states of the art in modeling operator behavior and the current status in developing an operator's model (MINERVA - NPP) are presented. The model is constructed as a knowledge-based system of a blackboard framework and is simulated based on emergency operating procedures

Nano Mechanical Machining Using AFM Probe

Science.gov (United States)

Mostofa, Md. Golam

Complex miniaturized components with high form accuracy will play key roles in the future development of many products, as they provide portability, disposability, lower material consumption in production, low power consumption during operation, lower sample requirements for testing, and higher heat transfer due to their very high surface-to-volume ratio. Given the high market demand for such micro and nano featured components, different manufacturing methods have been developed for their fabrication. Some of the common technologies in micro/nano fabrication are photolithography, electron beam lithography, X-ray lithography and other semiconductor processing techniques. Although these methods are capable of fabricating micro/nano structures with a resolution of less than a few nanometers, some of the shortcomings associated with these methods, such as high production costs for customized products, limited material choices, necessitate the development of other fabricating techniques. Micro/nano mechanical machining, such an atomic force microscope (AFM) probe based nano fabrication, has, therefore, been used to overcome some the major restrictions of the traditional processes. This technique removes material from the workpiece by engaging micro/nano size cutting tool (i.e. AFM probe) and is applicable on a wider range of materials compared to the photolithographic process. In spite of the unique benefits of nano mechanical machining, there are also some challenges with this technique, since the scale is reduced, such as size effects, burr formations, chip adhesions, fragility of tools and tool wear. Moreover, AFM based machining does not have any rotational movement, which makes fabrication of 3D features more difficult. Thus, vibration-assisted machining is introduced into AFM probe based nano mechanical machining to overcome the limitations associated with the conventional AFM probe based scratching method. Vibration-assisted machining reduced the cutting forces

High speed operation of permanent magnet machines

Science.gov (United States)

El-Refaie, Ayman M.

This work proposes methods to extend the high-speed operating capabilities of both the interior PM (IPM) and surface PM (SPM) machines. For interior PM machines, this research has developed and presented the first thorough analysis of how a new bi-state magnetic material can be usefully applied to the design of IPM machines. Key elements of this contribution include identifying how the unique properties of the bi-state magnetic material can be applied most effectively in the rotor design of an IPM machine by "unmagnetizing" the magnet cavity center posts rather than the outer bridges. The importance of elevated rotor speed in making the best use of the bi-state magnetic material while recognizing its limitations has been identified. For surface PM machines, this research has provided, for the first time, a clear explanation of how fractional-slot concentrated windings can be applied to SPM machines in order to achieve the necessary conditions for optimal flux weakening. A closed-form analytical procedure for analyzing SPM machines designed with concentrated windings has been developed. Guidelines for designing SPM machines using concentrated windings in order to achieve optimum flux weakening are provided. Analytical and numerical finite element analysis (FEA) results have provided promising evidence of the scalability of the concentrated winding technique with respect to the number of poles, machine aspect ratio, and output power rating. Useful comparisons between the predicted performance characteristics of SPM machines equipped with concentrated windings and both SPM and IPM machines designed with distributed windings are included. Analytical techniques have been used to evaluate the impact of the high pole number on various converter performance metrics. Both analytical techniques and FEA have been used for evaluating the eddy-current losses in the surface magnets due to the stator winding subharmonics. Techniques for reducing these losses have been

Remote filter handling machine for Sizewell B

International Nuclear Information System (INIS)

Barker, D.

1993-01-01

Two Filter Handling machines (FHM) have been supplied to Nuclear Electric plc for use at Sizewell B Power Station. These machines have been designed and built following ALARP principles with the functional objective being to remove radioactive filter cartridges from a filter housing and replace them with clean filter cartridges. Operation of the machine is achieved by the prompt of each distinct task via an industrial computer or the prompt of a full cycle using the automatic mode. The design of the machine features many aspects demonstrating ALARP while keeping the machine simple, robust and easy to maintain. (author)

EXPERIMENTAL EVALUATION OF WEDM MACHINED SURFACE WAVINESS

Directory of Open Access Journals (Sweden)

Katerina Mouralova

2016-10-01

Full Text Available Wire Electrical Discharge Machining (WEDM an unconventional machining technology which has become indispensable in many industries. The typical morphology of a surface machined using the electrical discharge technology is characterized with a large number of craters caused by electro-spark discharges produced during the machining process. The study deals with an evaluation of the machine parameter setting on the profile parameters of surface waviness on samples made of two metal materials Al 99.5 and Ti-6Al-4V. Attention was also paid to an evaluation of the surface morphology using 3D colour filtered and non-filtered images.

Machinability of experimental Ti-Ag alloys.

Science.gov (United States)

Kikuchi, Masafumi; Takahashi, Masatoshi; Okuno, Osamu

2008-03-01

This study investigated the machinability of experimental Ti-Ag alloys (5, 10, 20, and 30 mass% Ag) as a new dental titanium alloy candidate for CAD/CAM use. The alloys were slotted with a vertical milling machine and carbide square end mills under two cutting conditions. Machinability was evaluated through cutting force using a three-component force transducer fixed on the table of the milling machine. The horizontal cutting force of the Ti-Ag alloys tended to decrease as the concentration of silver increased. Values of the component of the horizontal cutting force perpendicular to the feed direction for Ti-20% Ag and Ti-30% Ag were more than 20% lower than those for titanium under both cutting conditions. Alloying with silver significantly improved the machinability of titanium in terms of cutting force under the present cutting conditions.

Machine learning for adaptive many-core machines a practical approach

CERN Document Server

Lopes, Noel

2015-01-01

The overwhelming data produced everyday and the increasing performance and cost requirements of applications?are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data.This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind.

Gaussian processes for machine learning.

Science.gov (United States)

Seeger, Matthias

2004-04-01

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.

Mechanical design of walking machines.

Science.gov (United States)

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.

A nucleonic weighing machine

International Nuclear Information System (INIS)

Anon.

1978-01-01

The design and operation of a nucleonic weighing machine fabricated for continuous weighing of material over conveyor belt are described. The machine uses a 40 mCi cesium-137 line source and a 10 litre capacity ionization chamber. It is easy to maintain as there are no moving parts. It can also be easily removed and reinstalled. (M.G.B.)

Chatter and machine tools

CERN Document Server

Stone, Brian

2014-01-01

Focussing on occurrences of unstable vibrations, or Chatter, in machine tools, this book gives important insights into how to eliminate chatter with associated improvements in product quality, surface finish and tool wear. Covering a wide range of machining processes, including turning, drilling, milling and grinding, the author uses his research expertise and practical knowledge of vibration problems to provide solutions supported by experimental evidence of their effectiveness. In addition, this book contains links to supplementary animation programs that help readers to visualise the ideas detailed in the text. Advancing knowledge in chatter avoidance and suggesting areas for new innovations, Chatter and Machine Tools serves as a handbook for those desiring to achieve significant reductions in noise, longer tool and grinding wheel life and improved product finish.

GPK heading machine

Energy Technology Data Exchange (ETDEWEB)

Krmasek, J.; Novosad, K.

1981-01-01

This article evaluates performance tests of the Soviet made GPK heading machine carried out in 4 coal mines in Czechoslovakia (Ostrava-Karvina region and Kladno mines). GPK works in coal seams and rocks with compression strength of 40 to 50 MPa. Dimensions of the tunnel are height 1.8 to 3.8 m and width 2.6 to 4.7 m, tunnel gradient plus to minus 10 degrees. GPK weighs 16 t, its conical shaped cutting head equipped with RKS-1 cutting tools is driven by an electric motor with 55 kW capacity. Undercarriage of the GPK, gathering-arm loader, hydraulic system, electric system and dust supression system (water spraying or pneumatic section) are characterized. Specifications of GPK heading machines are compared with PK-3r and F8 heading machines. Reliability, number of failures, dust level, noise, productivity depending on compression strength of rocks, heading rate in coal and in rocks, energy consumption, performance in inclined tunnels, and cutting tool wear are evaluated. Tests show that GPK can be used to drive tunnels in coal with rock constituting up to 50% of the tunnel crosscut, as long as rock compression strength does not exceed 50 MPa. In rocks characterized by higher compression strength cutting tool wear sharply increases. GPK is characterized by higher productivity than that of the PK-3r heading machine. Among the weak points of the GPK are: unsatisfactory reliability and excessive wear of its elements. (4 refs.) (In Czech)

Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence.

Science.gov (United States)

Ahn, Woo-Young; Vassileva, Jasmin

2016-04-01

Recent animal and human studies reveal distinct cognitive and neurobiological differences between opiate and stimulant addictions; however, our understanding of the common and specific effects of these two classes of drugs remains limited due to the high rates of polysubstance-dependence among drug users. The goal of the current study was to identify multivariate substance-specific markers classifying heroin dependence (HD) and amphetamine dependence (AD), by using machine-learning approaches. Participants included 39 amphetamine mono-dependent, 44 heroin mono-dependent, 58 polysubstance dependent, and 81 non-substance dependent individuals. The majority of substance dependent participants were in protracted abstinence. We used demographic, personality (trait impulsivity, trait psychopathy, aggression, sensation seeking), psychiatric (attention deficit hyperactivity disorder, conduct disorder, antisocial personality disorder, psychopathy, anxiety, depression), and neurocognitive impulsivity measures (Delay Discounting, Go/No-Go, Stop Signal, Immediate Memory, Balloon Analogue Risk, Cambridge Gambling, and Iowa Gambling tasks) as predictors in a machine-learning algorithm. The machine-learning approach revealed substance-specific multivariate profiles that classified HD and AD in new samples with high degree of accuracy. Out of 54 predictors, psychopathy was the only classifier common to both types of addiction. Important dissociations emerged between factors classifying HD and AD, which often showed opposite patterns among individuals with HD and AD. These results suggest that different mechanisms may underlie HD and AD, challenging the unitary account of drug addiction. This line of work may shed light on the development of standardized and cost-efficient clinical diagnostic tests and facilitate the development of individualized prevention and intervention programs for HD and AD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Philips high tension generator (x-ray machine) testing for baby ebm (electron beam machine) project

International Nuclear Information System (INIS)