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Sample records for machine cognition ihmc

  1. The cognitive approach to conscious machines

    CERN Document Server

    Haikonen, Pentti O

    2003-01-01

    Could a machine have an immaterial mind? The author argues that true conscious machines can be built, but rejects artificial intelligence and classical neural networks in favour of the emulation of the cognitive processes of the brain-the flow of inner speech, inner imagery and emotions. This results in a non-numeric meaning-processing machine with distributed information representation and system reactions. It is argued that this machine would be conscious; it would be aware of its own existence and its mental content and perceive this as immaterial. Novel views on consciousness and the mind-

  2. Spectrum Assignment Algorithm for Cognitive Machine-to-Machine Networks

    Directory of Open Access Journals (Sweden)

    Soheil Rostami

    2016-01-01

    Full Text Available A novel aggregation-based spectrum assignment algorithm for Cognitive Machine-To-Machine (CM2M networks is proposed. The introduced algorithm takes practical constraints including interference to the Licensed Users (LUs, co-channel interference (CCI among CM2M devices, and Maximum Aggregation Span (MAS into consideration. Simulation results show clearly that the proposed algorithm outperforms State-Of-The-Art (SOTA algorithms in terms of spectrum utilisation and network capacity. Furthermore, the convergence analysis of the proposed algorithm verifies its high convergence rate.

  3. Machine Cognition Models: EPAM and GPS

    CERN Document Server

    Elouafiq, Ali

    2012-01-01

    Through history, the human being tried to relay its daily tasks to other creatures, which was the main reason behind the rise of civilizations. It started with deploying animals to automate tasks in the field of agriculture(bulls), transportation (e.g. horses and donkeys), and even communication (pigeons). Millenniums after, come the Golden age with "Al-jazari" and other Muslim inventors, which were the pioneers of automation, this has given birth to industrial revolution in Europe, centuries after. At the end of the nineteenth century, a new era was to begin, the computational era, the most advanced technological and scientific development that is driving the mankind and the reason behind all the evolutions of science; such as medicine, communication, education, and physics. At this edge of technology engineers and scientists are trying to model a machine that behaves the same as they do, which pushed us to think about designing and implementing "Things that-Thinks", then artificial intelligence was. In this...

  4. Machine learning based Intelligent cognitive network using fog computing

    Science.gov (United States)

    Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

    2017-05-01

    In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

  5. Classifying cognitive profiles using machine learning with privileged information in Mild Cognitive Impairment

    Directory of Open Access Journals (Sweden)

    Hanin Hamdan Alahmadi

    2016-11-01

    Full Text Available Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalised Matrix Learning Vector Quantization (GMLVQ classifiers to discriminate patients with Mild Cognitive Impairment (MCI from healthy controls based on their cognitive skills. Further, we adopted a ``Learning with privileged information'' approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants.MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls based on the learning performance and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on the learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1 when overall fMRI signal for structured stimuli is

  6. Classifying Cognitive Profiles Using Machine Learning with Privileged Information in Mild Cognitive Impairment

    Science.gov (United States)

    Alahmadi, Hanin H.; Shen, Yuan; Fouad, Shereen; Luft, Caroline Di B.; Bentham, Peter; Kourtzi, Zoe; Tino, Peter

    2016-01-01

    Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalized Matrix Learning Vector Quantization (GMLVQ) classifiers to discriminate patients with Mild Cognitive Impairment (MCI) from healthy controls based on their cognitive skills. Further, we adopted a “Learning with privileged information” approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI) during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants. MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on a probabilistic sequence learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1) when overall fMRI signal is used as inputs to the classifier, the post

  7. Classifying Cognitive Profiles Using Machine Learning with Privileged Information in Mild Cognitive Impairment.

    Science.gov (United States)

    Alahmadi, Hanin H; Shen, Yuan; Fouad, Shereen; Luft, Caroline Di B; Bentham, Peter; Kourtzi, Zoe; Tino, Peter

    2016-01-01

    Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalized Matrix Learning Vector Quantization (GMLVQ) classifiers to discriminate patients with Mild Cognitive Impairment (MCI) from healthy controls based on their cognitive skills. Further, we adopted a "Learning with privileged information" approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI) during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants. MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on a probabilistic sequence learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1) when overall fMRI signal is used as inputs to the classifier, the post

  8. Cognitive engineering for long duration missions: Human-machine collaboration on the moon and mars

    NARCIS (Netherlands)

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

    2006-01-01

    For manned long-duration missions to the Moon and Mars, there is a need for a Mission Execution Crew Assistant (MECA) that empowers the cognitive capacities of human-machine teams during planetary exploration missions in order to cope autonomously with unexpected, complex and potentially hazardous s

  9. Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    M. T. Mushtaq

    2015-04-01

    Full Text Available Cognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying based signals propagating through an AWGN (Additive White Gaussian Noise channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR values up to -50 dB.

  10. Discriminating cognitive status in Parkinson’s disease through functional connectomics and machine learning

    Science.gov (United States)

    Abós, Alexandra; Baggio, Hugo C.; Segura, Bàrbara; García-Díaz, Anna I.; Compta, Yaroslau; Martí, Maria José; Valldeoriola, Francesc; Junqué, Carme

    2017-01-01

    There is growing interest in the potential of neuroimaging to help develop non-invasive biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of functional connectivity were used to distinguish Parkinson’s disease patients according to cognitive status using machine learning. Two independent subject samples were assessed with resting-state fMRI. The first (training) sample comprised 38 healthy controls and 70 Parkinson’s disease patients (27 with mild cognitive impairment). The second (validation) sample included 25 patients (8 with mild cognitive impairment). The Brainnetome atlas was used to reconstruct the functional connectomes. Using a support vector machine trained on features selected through randomized logistic regression with leave-one-out cross-validation, a mean accuracy of 82.6% (p < 0.002) was achieved in separating patients with mild cognitive impairment from those without it in the training sample. The model trained on the whole training sample achieved an accuracy of 80.0% when used to classify the validation sample (p = 0.006). Correlation analyses showed that the connectivity level in the edges most consistently selected as features was associated with memory and executive function performance in the patient group. Our results demonstrate that connection-wise patterns of functional connectivity may be useful for discriminating Parkinson’s disease patients according to the presence of cognitive deficits. PMID:28349948

  11. Optimizing Spectrum Trading in Cognitive Mesh Network Using Machine Learning

    Directory of Open Access Journals (Sweden)

    Ayoub Alsarhan

    2012-01-01

    Full Text Available In a cognitive wireless mesh network, licensed users (primary users, PUs may rent surplus spectrum to unlicensed users (secondary users, SUs for getting some revenue. For such spectrum sharing paradigm, maximizing the revenue is the key objective of the PUs while that of the SUs is to meet their requirements. These complex contradicting objectives are embedded in our reinforcement learning (RL model that is developed and implemented as shown in this paper. The objective function is defined as the net revenue gained by PUs from renting some of their spectrum. RL is used to extract the optimal control policy that maximizes the PUs’ profit continuously over time. The extracted policy is used by PUs to manage renting the spectrum to SUs and it helps PUs to adapt to the changing network conditions. Performance evaluation of the proposed spectrum trading approach shows that it is able to find the optimal size and price of spectrum for each primary user under different conditions. Moreover, the approach constitutes a framework for studying, synthesizing and optimizing other schemes. Another contribution is proposing a new distributed algorithm to manage spectrum sharing among PUs. In our scheme, PUs exchange channels dynamically based on the availability of neighbor’s idle channels. In our cooperative scheme, the objective of spectrum sharing is to maximize the total revenue and utilize spectrum efficiently. Compared to the poverty-line heuristic that does not consider the availability of unused spectrum, our scheme has the advantage of utilizing spectrum efficiently.

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

    Directory of Open Access Journals (Sweden)

    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

  13. Neuropsychological test selection for cognitive impairment classification: A machine learning approach.

    Science.gov (United States)

    Weakley, Alyssa; Williams, Jennifer A; Schmitter-Edgecombe, Maureen; Cook, Diane J

    2015-01-01

    Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI), or dementia using a suite of classification techniques. Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis; Clinical Dementia Rating, CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals with CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. A total of 27 demographic, psychological, and neuropsychological variables were available for variable selection. No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0-99.1%), geometric mean (60.9-98.1%), sensitivity (44.2-100%), and specificity (52.7-100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2-9 variables were required for classification and varied between datasets in a clinically meaningful way. The current study results reveal that machine learning techniques can accurately classify cognitive impairment and reduce the number of measures required for diagnosis.

  14. Distinguishing age-related cognitive decline from dementias: A study based on machine learning algorithms.

    Science.gov (United States)

    Er, Füsun; Iscen, Pınar; Sahin, Sevki; Çinar, Nilgun; Karsidag, Sibel; Goularas, Dionysis

    2017-08-01

    This study aims to examine the distinguishability of age-related cognitive decline (ARCD) from dementias based on some neurocognitive tests using machine learning. 106 subjects were divided into four groups: ARCD (n=30), probable Alzheimer's disease (AD) (n=20), vascular dementia (VD) (n=21) and amnestic mild cognitive impairment (MCI) (n=35). The following tests were applied to all subjects: The Wechsler memory scale-revised, a clock-drawing, the dual similarities, interpretation of proverbs, word fluency, the Stroop, the Boston naming (BNT), the Benton face recognition, a copying-drawings and Öktem verbal memory processes (Ö-VMPT) tests. A multilayer perceptron, a support vector machine and a classification via regression with M5-model trees were employed for classification. The pairwise classification results show that ARCD is completely separable from AD with a success rate of 100% and highly separable from MCI and VD with success rates of 95.4% and 86.30%, respectively. The neurocognitive tests with the higher merit values were Ö-VMPT recognition (ARCD vs. AD), Ö-VMPT total learning (ARCD vs. MCI) and semantic fluency, proverbs, Stroop interference and naming BNT (ARCD vs. VD). The findings show that machine learning can be successfully utilized for distinguishing ARCD from dementias based on neurocognitive tests. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. 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...

  16. Meta-cognitive online sequential extreme learning machine for imbalanced and concept-drifting data classification.

    Science.gov (United States)

    Mirza, Bilal; Lin, Zhiping

    2016-08-01

    In this paper, a meta-cognitive online sequential extreme learning machine (MOS-ELM) is proposed for class imbalance and concept drift learning. In MOS-ELM, meta-cognition is used to self-regulate the learning by selecting suitable learning strategies for class imbalance and concept drift problems. MOS-ELM is the first sequential learning method to alleviate the imbalance problem for both binary class and multi-class data streams with concept drift. In MOS-ELM, a new adaptive window approach is proposed for concept drift learning. A single output update equation is also proposed which unifies various application specific OS-ELM methods. The performance of MOS-ELM is evaluated under different conditions and compared with methods each specific to some of the conditions. On most of the datasets in comparison, MOS-ELM outperforms the competing methods.

  17. Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

    Science.gov (United States)

    Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.

    2016-01-01

    Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171

  18. Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

    Science.gov (United States)

    Deng, Li; Wang, Guohua; Yu, Suihuai

    2016-01-01

    In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

  19. Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

    Directory of Open Access Journals (Sweden)

    Li Deng

    2016-01-01

    Full Text Available In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

  20. Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

    Science.gov (United States)

    Deng, Li; Wang, Guohua; Yu, Suihuai

    2016-01-01

    In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

  1. A Simple ERP Method for Quantitative Analysis of Cognitive Workload in Myoelectric Prosthesis Control and Human-Machine Interaction

    OpenAIRE

    Sean Deeny; Caitlin Chicoine; Levi Hargrove; Todd Parrish; Arun Jayaraman

    2014-01-01

    Common goals in the development of human-machine interface (HMI) technology are to reduce cognitive workload and increase function. However, objective and quantitative outcome measures assessing cognitive workload have not been standardized for HMI research. The present study examines the efficacy of a simple event-related potential (ERP) measure of cortical effort during myoelectric control of a virtual limb for use as an outcome tool. Participants trained and tested on two methods of contro...

  2. 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.

  3. Neuropsychological Testing and Machine Learning Distinguish Alzheimer's Disease from Other Causes for Cognitive Impairment.

    Science.gov (United States)

    Gurevich, Pavel; Stuke, Hannes; Kastrup, Andreas; Stuke, Heiner; Hildebrandt, Helmut

    2017-01-01

    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.

  4. Predictive modeling of human operator cognitive state via sparse and robust support vector machines.

    Science.gov (United States)

    Zhang, Jian-Hua; Qin, Pan-Pan; Raisch, Jörg; Wang, Ru-Bin

    2013-10-01

    The accurate prediction of the temporal variations in human operator cognitive state (HCS) is of great practical importance in many real-world safety-critical situations. However, since the relationship between the HCS and electrophysiological responses of the operator is basically unknown, complicated and uncertain, only data-based modeling method can be employed. This paper is aimed at constructing a data-driven computationally intelligent model, based on multiple psychophysiological and performance measures, to accurately estimate the HCS in the context of a safety-critical human-machine system. The advanced least squares support vector machines (LS-SVM), whose parameters are optimized by grid search and cross-validation techniques, are adopted for the purpose of predictive modeling of the HCS. The sparse and weighted LS-SVM (WLS-SVM) were proposed by Suykens et al. to overcome the deficiency of the standard LS-SVM in lacking sparseness and robustness. This paper adopted those two improved LS-SVM algorithms to model the HCS based solely on a set of physiological and operator performance data. The results showed that the sparse LS-SVM can obtain HCS models with sparseness with almost no loss of modeling accuracy, while the WLS-SVM leads to models which are robust in case of noisy training data. Both intelligent system modeling approaches are shown to be capable of capturing the temporal fluctuation trends of the HCS because of their superior generalization performance.

  5. Identification of Conversion from Normal Elderly Cognition to Alzheimer's Disease using Multimodal Support Vector Machine.

    Science.gov (United States)

    Zhan, Ye; Chen, Kewei; Wu, Xia; Zhang, Daoqiang; Zhang, Jiacai; Yao, Li; Guo, Xiaojuan

    2015-01-01

    Alzheimer's disease (AD) is one of the most serious progressive neurodegenerative diseases among the elderly, therefore the identification of conversion to AD at the earlier stage has become a crucial issue. In this study, we applied multimodal support vector machine to identify the conversion from normal elderly cognition to mild cognitive impairment (MCI) or AD based on magnetic resonance imaging and positron emission tomography data. The participants included two independent cohorts (Training set: 121 AD patients and 120 normal controls (NC); Testing set: 20 NC converters and 20 NC non-converters) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The multimodal results showed that the accuracy, sensitivity, and specificity of the classification between NC converters and NC non-converters were 67.5% , 73.33% , and 64% , respectively. Furthermore, the classification results with feature selection increased to 70% accuracy, 75% sensitivity, and 66.67% specificity. The classification results using multimodal data are markedly superior to that using a single modality when we identified the conversion from NC to MCI or AD. The model built in this study of identifying the risk of normal elderly converting to MCI or AD will be helpful in clinical diagnosis and pathological research.

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

    Science.gov (United States)

    Battista, Petronilla; Salvatore, Christian; Castiglioni, Isabella

    2017-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2017-07-28

    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.

  9. 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.

  10. 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.

  11. 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.

  12. A simple ERP method for quantitative analysis of cognitive workload in myoelectric prosthesis control and human-machine interaction.

    Directory of Open Access Journals (Sweden)

    Sean Deeny

    Full Text Available Common goals in the development of human-machine interface (HMI technology are to reduce cognitive workload and increase function. However, objective and quantitative outcome measures assessing cognitive workload have not been standardized for HMI research. The present study examines the efficacy of a simple event-related potential (ERP measure of cortical effort during myoelectric control of a virtual limb for use as an outcome tool. Participants trained and tested on two methods of control, direct control (DC and pattern recognition control (PRC, while electroencephalographic (EEG activity was recorded. Eighteen healthy participants with intact limbs were tested using DC and PRC under three conditions: passive viewing, easy, and hard. Novel auditory probes were presented at random intervals during testing, and significant task-difficulty effects were observed in the P200, P300, and a late positive potential (LPP, supporting the efficacy of ERPs as a cognitive workload measure in HMI tasks. LPP amplitude distinguished DC from PRC in the hard condition with higher amplitude in PRC, consistent with lower cognitive workload in PRC relative to DC for complex movements. Participants completed trials faster in the easy condition using DC relative to PRC, but completed trials more slowly using DC relative to PRC in the hard condition. The results provide promising support for ERPs as an outcome measure for cognitive workload in HMI research such as prosthetics, exoskeletons, and other assistive devices, and can be used to evaluate and guide new technologies for more intuitive HMI control.

  13. A simple ERP method for quantitative analysis of cognitive workload in myoelectric prosthesis control and human-machine interaction.

    Science.gov (United States)

    Deeny, Sean; Chicoine, Caitlin; Hargrove, Levi; Parrish, Todd; Jayaraman, Arun

    2014-01-01

    Common goals in the development of human-machine interface (HMI) technology are to reduce cognitive workload and increase function. However, objective and quantitative outcome measures assessing cognitive workload have not been standardized for HMI research. The present study examines the efficacy of a simple event-related potential (ERP) measure of cortical effort during myoelectric control of a virtual limb for use as an outcome tool. Participants trained and tested on two methods of control, direct control (DC) and pattern recognition control (PRC), while electroencephalographic (EEG) activity was recorded. Eighteen healthy participants with intact limbs were tested using DC and PRC under three conditions: passive viewing, easy, and hard. Novel auditory probes were presented at random intervals during testing, and significant task-difficulty effects were observed in the P200, P300, and a late positive potential (LPP), supporting the efficacy of ERPs as a cognitive workload measure in HMI tasks. LPP amplitude distinguished DC from PRC in the hard condition with higher amplitude in PRC, consistent with lower cognitive workload in PRC relative to DC for complex movements. Participants completed trials faster in the easy condition using DC relative to PRC, but completed trials more slowly using DC relative to PRC in the hard condition. The results provide promising support for ERPs as an outcome measure for cognitive workload in HMI research such as prosthetics, exoskeletons, and other assistive devices, and can be used to evaluate and guide new technologies for more intuitive HMI control.

  14. 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. PMID:28367110

  15. 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

  16. VHDL-based system design of a cognitive sensorimotor loop (CSL) for haptic Human-Machine Interaction (HMI)

    OpenAIRE

    Miguel Morales, Pablo de

    2015-01-01

    This document is a summary of the Bachelor thesis titled “VHDL-Based System Design of a Cognitive Sensorimotor Loop (CSL) for Haptic Human-Machine Interaction (HMI)” written by Pablo de Miguel Morales, Electronics Engineering student at the Universidad Politécnica de Madrid (UPM Madrid, Spain) during an Erasmus+ Exchange Program at the Beuth Hochschule für Technik (BHT Berlin, Germany). The tutor of this project is Dr. Prof. Hild. This project has been developed inside the Neurobotics Researc...

  17. Cognitive adaptive man machine interfaces for the firefighter commander: design framework and research methodology

    NARCIS (Netherlands)

    de Graaf, Maurits; Varkevisser, Michel; Kempen, Masja; Jourden, Nicolas; Schmorrow, Dylan D.; Fidopiastis, Cali M.

    2011-01-01

    The ARTEMIS CAMMI project aims at developing a joint-cognitive system to optimise human operator’s performance under demanding labour conditions. The CAMMI domain applications concern avionics, automotive, and civil emergencies. In this paper we address the development of a joint cognitive system

  18. Cognitive adaptive man machine interfaces for the firefighter commander: design framework and research methodology

    NARCIS (Netherlands)

    Graaf, de Maurits; Varkevisser, Michel; Kempen, Masja; Jourden, Nicolas; Schmorrow, Dylan D.; Fidopiastis, Cali M.

    2011-01-01

    The ARTEMIS CAMMI project aims at developing a joint-cognitive system to optimise human operator’s performance under demanding labour conditions. The CAMMI domain applications concern avionics, automotive, and civil emergencies. In this paper we address the development of a joint cognitive system fo

  19. Pattern Recognition in Collective Cognitive Systems: Hybrid Human-Machine Learning (HHML) By Heterogeneous Ensembles

    CERN Document Server

    Dashti, Hesam T; Siahpirani, Alireza F; Tonejc, Jernej; Uilecan, Ioan V; Simas, Tiago; Miranda, Bruno; Ribeiro, Rita; Wang, Liya; Assadi, Amir H

    2010-01-01

    The ubiquitous role of the cyber-infrastructures, such as the WWW, provides myriad opportunities for machine learning and its broad spectrum of application domains taking advantage of digital communication. Pattern classification and feature extraction are among the first applications of machine learning that have received extensive attention. The most remarkable achievements have addressed data sets of moderate-to-large size. The 'data deluge' in the last decade or two has posed new challenges for AI researchers to design new, effective and accurate algorithms for similar tasks using ultra-massive data sets and complex (natural or synthetic) dynamical systems. We propose a novel principled approach to feature extraction in hybrid architectures comprised of humans and machines in networked communication, who collaborate to solve a pre-assigned pattern recognition (feature extraction) task. There are two practical considerations addressed below: (1) Human experts, such as plant biologists or astronomers, often...

  20. 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.

  1. A Cognitive Systems Engineering Approach to Developing Human Machine Interface Requirements for New Technologies

    Science.gov (United States)

    Fern, Lisa Carolynn

    This dissertation examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will be deployed into complex systems. A key question for new technologies with increasingly capable automation, is how work will be accomplished by human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by designers. The human machine interface (HMI), which is intended to facilitate human-machine interaction and cooperation, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the predicted performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements for a detect and avoid (DAA) system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned in order

  2. Machine Learning Aided Efficient and Robust Algorithms for Spectrum Knowledge Acquisition in Wideband Autonomous Cognitive Radios

    Science.gov (United States)

    2016-08-01

    WIDEBAND AUTONOMOUS COGNITIVE RADIOS Sudharman Jayaweera Department of Electrical and Computer Engineering University of New Mexico Albuquerque, NM...of Electrical and Computer Engineering 8. PERFORMING ORGANIZATION REPORT NUMBER University of New Mexico Albuquerque, NM 87131 9. SPONSORING...1, is the wideband spectrum scanning [1,8]. Hardware constraints limit the instantaneous sensing bandwidth of most state-of-the- art software

  3. Validating cognitive support for operators of complex human-machine systems

    Energy Technology Data Exchange (ETDEWEB)

    O`Hara, J. [Brookhaven National Lab., Upton, NY (United States); Wachtel, J. [US Nuclear Regulatory Commission, Washington, DC (United States)

    1995-10-01

    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.

  4. Social Robots, Brain Machine Interfaces and Neuro/Cognitive Enhancers: Three Emerging Science and Technology Products through the Lens of Technology Acceptance Theories, Models and Frameworks

    Directory of Open Access Journals (Sweden)

    Gregor Wolbring

    2013-06-01

    Full Text Available Social robotics, brain machine interfaces and neuro and cognitive enhancement products are three emerging science and technology products with wide-reaching impact for disabled and non-disabled people. Acceptance of ideas and products depend on multiple parameters and many models have been developed to predict product acceptance. We investigated which frequently employed technology acceptance models (consumer theory, innovation diffusion model, theory of reasoned action, theory of planned behaviour, social cognitive theory, self-determination theory, technology of acceptance model, Unified Theory of Acceptance and Use of Technology UTAUT and UTAUT2 are employed in the social robotics, brain machine interfaces and neuro and cognitive enhancement product literature and which of the core measures used in the technology acceptance models are implicit or explicit engaged with in the literature.

  5. Classification of frontal cortex haemodynamic responses during cognitive tasks using wavelet transforms and machine learning algorithms.

    Science.gov (United States)

    Abibullaev, Berdakh; An, Jinung

    2012-12-01

    Recent advances in neuroimaging demonstrate the potential of functional near-infrared spectroscopy (fNIRS) for use in brain-computer interfaces (BCIs). fNIRS uses light in the near-infrared range to measure brain surface haemoglobin concentrations and thus determine human neural activity. Our primary goal in this study is to analyse brain haemodynamic responses for application in a BCI. Specifically, we develop an efficient signal processing algorithm to extract important mental-task-relevant neural features and obtain the best possible classification performance. We recorded brain haemodynamic responses due to frontal cortex brain activity from nine subjects using a 19-channel fNIRS system. Our algorithm is based on continuous wavelet transforms (CWTs) for multi-scale decomposition and a soft thresholding algorithm for de-noising. We adopted three machine learning algorithms and compared their performance. Good performance can be achieved by using the de-noised wavelet coefficients as input features for the classifier. Moreover, the classifier performance varied depending on the type of mother wavelet used for wavelet decomposition. Our quantitative results showed that CWTs can be used efficiently to extract important brain haemodynamic features at multiple frequencies if an appropriate mother wavelet function is chosen. The best classification results were obtained by a specific combination of input feature type and classifier.

  6. Social Robots, Brain Machine Interfaces and Neuro/Cognitive Enhancers: Three Emerging Science and Technology Products through the Lens of Technology Acceptance Theories, Models and Frameworks

    OpenAIRE

    Gregor Wolbring; Lucy Diep; Sophya Yumakulov; Natalie Ball; Dean Yergens

    2013-01-01

    Social robotics, brain machine interfaces and neuro and cognitive enhancement products are three emerging science and technology products with wide-reaching impact for disabled and non-disabled people. Acceptance of ideas and products depend on multiple parameters and many models have been developed to predict product acceptance. We investigated which frequently employed technology acceptance models (consumer theory, innovation diffusion model, theory of reasoned action, theory of planned beh...

  7. Human-machine interactions

    Science.gov (United States)

    Forsythe, J. Chris; Xavier, Patrick G.; Abbott, Robert G.; Brannon, Nathan G.; Bernard, Michael L.; Speed, Ann E.

    2009-04-28

    Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

  8. Cognitive signals for brain-machine interfaces in posterior parietal cortex include continuous 3D trajectory commands.

    Science.gov (United States)

    Hauschild, Markus; Mulliken, Grant H; Fineman, Igor; Loeb, Gerald E; Andersen, Richard A

    2012-10-16

    Cortical neural prosthetics extract command signals from the brain with the goal to restore function in paralyzed or amputated patients. Continuous control signals can be extracted from the motor cortical areas, whereas neural activity from posterior parietal cortex (PPC) can be used to decode cognitive variables related to the goals of movement. Because typical activities of daily living comprise both continuous control tasks such as reaching, and tasks benefiting from discrete control such as typing on a keyboard, availability of both signals simultaneously would promise significant increases in performance and versatility. Here, we show that PPC can provide 3D hand trajectory information under natural conditions that would be encountered for prosthetic applications, thus allowing simultaneous extraction of continuous and discrete signals without requiring multisite surgical implants. We found that limb movements can be decoded robustly and with high accuracy from a small population of neural units under free gaze in a complex 3D point-to-point reaching task. Both animals' brain-control performance improved rapidly with practice, resulting in faster target acquisition and increasing accuracy. These findings disprove the notion that the motor cortical areas are the only candidate areas for continuous prosthetic command signals and, rather, suggests that PPC can provide equally useful trajectory signals in addition to discrete, cognitive variables. Hybrid use of continuous and discrete signals from PPC may enable a new generation of neural prostheses providing superior performance and additional flexibility in addressing individual patient needs.

  9. Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer's disease.

    Science.gov (United States)

    Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas

    2016-09-01

    The study of brain networks by resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method for identifying patients with dementia from healthy controls (HC). Using graph theory, different aspects of the brain network can be efficiently characterized by calculating measures of integration and segregation. In this study, we combined a graph theoretical approach with advanced machine learning methods to study the brain network in 89 patients with mild cognitive impairment (MCI), 34 patients with Alzheimer's disease (AD), and 45 age-matched HC. The rs-fMRI connectivity matrix was constructed using a brain parcellation based on a 264 putative functional areas. Using the optimal features extracted from the graph measures, we were able to accurately classify three groups (i.e., HC, MCI, and AD) with accuracy of 88.4 %. We also investigated performance of our proposed method for a binary classification of a group (e.g., MCI) from two other groups (e.g., HC and AD). The classification accuracies for identifying HC from AD and MCI, AD from HC and MCI, and MCI from HC and AD, were 87.3, 97.5, and 72.0 %, respectively. In addition, results based on the parcellation of 264 regions were compared to that of the automated anatomical labeling atlas (AAL), consisted of 90 regions. The accuracy of classification of three groups using AAL was degraded to 83.2 %. Our results show that combining the graph measures with the machine learning approach, on the basis of the rs-fMRI connectivity analysis, may assist in diagnosis of AD and MCI.

  10. Perception and estimation challenges for humanoid robotics: DARPA Robotics Challenge and NASA Valkyrie

    Science.gov (United States)

    Fallon, Maurice

    2016-10-01

    This paper describes ongoing work at the University of Edinburgh's Humanoid Robotics Project. University of Edinburgh have formed a collaboration with the United States' National Aeronautics and Space Administration (NASA) around their R5 humanoid robot commonly known as Valkyrie. Also involved are MIT, Northeastern University and the Florida Institute for Human and Machine Cognition (IHMC) as part of NASA's Space Robotics Challenge. We will outline the development of state estimation and localization algorithms being developed for Valkyrie.

  11. Cognitive Systems

    DEFF Research Database (Denmark)

    and its relation and potential over current artificial intelligence architectures. Machine learning models that learn from data and previous knowledge will play an increasingly important role in all levels of cognition as large real world digital environments (such as the Internet) usually are too complex...... to be modeled within a limited set of predefined specifications. There will inevitably be a need for robust decisions and behaviors in novel situations that include handling of conflicts and ambiguities based on the capability and knowledge of the artificial cognitive system. Further, there is a need......, cognitive psychology, and semantics. However, machine learning for signal processing plays a key role at all the levels of the cognitive processes, and we expect this to be a new emerging trend in our community in the coming years. Current examples of the use of machine learning for signal processing...

  12. When Machines Design Machines!

    DEFF Research Database (Denmark)

    2011-01-01

    Until recently we were the sole designers, alone in the driving seat making all the decisions. But, we have created a world of complexity way beyond human ability to understand, control, and govern. Machines now do more trades than humans on stock markets, they control our power, water, gas...... and food supplies, manage our elevators, microclimates, automobiles and transport systems, and manufacture almost everything. It should come as no surprise that machines are now designing machines. The chips that power our computers and mobile phones, the robots and commercial processing plants on which we...... depend, all are now largely designed by machines. So what of us - will be totally usurped, or are we looking at a new symbiosis with human and artificial intelligences combined to realise the best outcomes possible. In most respects we have no choice! Human abilities alone cannot solve any of the major...

  13. Early identification of mild cognitive impairment using incomplete random forest-robust support vector machine and FDG-PET imaging.

    Science.gov (United States)

    Lu, Shen; Xia, Yong; Cai, Weidong; Fulham, Michael; Feng, David Dagan

    2017-09-01

    Alzheimer's disease (AD) is the most common type of dementia and will be an increasing health problem in society as the population ages. Mild cognitive impairment (MCI) is considered to be a prodromal stage of AD. The ability to identify subjects with MCI will be increasingly important as disease modifying therapies for AD are developed. We propose a semi-supervised learning method based on robust optimization for the identification of MCI from [18F]Fluorodeoxyglucose PET scans. We extracted three groups of spatial features from the cortical and subcortical regions of each FDG-PET image volume. We measured the statistical uncertainty related to these spatial features via transformation using an incomplete random forest and formulated the MCI identification problem under a robust optimization framework. We compared our approach to other state-of-the-art methods in different learning schemas. Our method outperformed the other techniques in the ability to separate MCI from normal controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

    Science.gov (United States)

    Dyrba, Martin; Barkhof, Frederik; Fellgiebel, Andreas; Filippi, Massimo; Hausner, Lucrezia; Hauenstein, Karlheinz; Kirste, Thomas; Teipel, Stefan J

    2015-01-01

    Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI). We applied a Support Vector Machine (SVM) classifier to DTI and volumetric magnetic resonance imaging data from 35 amyloid-β42 negative MCI subjects (MCI-Aβ42-), 35 positive MCI subjects (MCI-Aβ42+), and 25 healthy controls (HC) retrieved from the European DTI Study on Dementia. The SVM was applied to DTI-derived fractional anisotropy, mean diffusivity (MD), and mode of anisotropy (MO) maps. For comparison, we studied classification based on gray matter (GM) and WM volume. We obtained accuracies of up to 68% for MO and 63% for GM volume when it came to distinguishing between MCI-Aβ42- and MCI-Aβ42+. When it came to separating MCI-Aβ42+ from HC we achieved an accuracy of up to 77% for MD and a significantly lower accuracy of 68% for GM volume. The accuracy of multimodal classification was not higher than the accuracy of the best single modality. Our results suggest that DTI data provide better prediction accuracy than GM volume in predementia AD. Copyright © 2015 by the American Society of Neuroimaging.

  15. Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia

    Directory of Open Access Journals (Sweden)

    Benedikt Sundermann

    2017-06-01

    Full Text Available BackgroundThe approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT in PD/AG.MethodsThis analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30 or non-responders (n = 29 based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50% after 6 weeks of CBT (2 h/week. fMRI parametric maps were used as features for response classification with linear support vector machines (SVM with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated.ResultsSVM did not reach sufficient overall predictive accuracies (38.0–54.2% for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7% were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons.ConclusionIn contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique.

  16. Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia.

    Science.gov (United States)

    Sundermann, Benedikt; Bode, Jens; Lueken, Ulrike; Westphal, Dorte; Gerlach, Alexander L; Straube, Benjamin; Wittchen, Hans-Ulrich; Ströhle, Andreas; Wittmann, André; Konrad, Carsten; Kircher, Tilo; Arolt, Volker; Pfleiderer, Bettina

    2017-01-01

    The approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG) often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI) interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT) in PD/AG. This analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30) or non-responders (n = 29) based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50%) after 6 weeks of CBT (2 h/week). fMRI parametric maps were used as features for response classification with linear support vector machines (SVM) with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated. SVM did not reach sufficient overall predictive accuracies (38.0-54.2%) for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7%) were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons. In contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique.

  17. 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. .

  18. 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.

  19. Machine Translation

    Institute of Scientific and Technical Information of China (English)

    张严心

    2015-01-01

    As a kind of ancillary translation tool, Machine Translation has been paid increasing attention to and received different kinds of study by a great deal of researchers and scholars for a long time. To know the definition of Machine Translation and to analyse its benefits and problems are significant for translators in order to make good use of Machine Translation, and helpful to develop and consummate Machine Translation Systems in the future.

  20. 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.

  1. Robot phototaxis control based on Boltzmann machine neural network cognitive mechanism%基于Boltzmann机神经网络认知机制的机器人趋光控制

    Institute of Scientific and Technical Information of China (English)

    阮晓钢; 庞涛; 于建均

    2014-01-01

    For mobile robot phototaxis control problems, the human or animal“perception-action”cognitive mechanism is simulated. The structure of mobile robot is designed and the method of phototaxis control is proposed based on the Boltzmann machine neural network. The Boltzmann machine neural network is trained by the knowledge set. The phototaxis control method is implemented by using the Boltzmann machine neural network operation mechanism. Simulation results show that the proposed method can improve the control accuracy and the success rate of robot learning.%针对移动机器人未知环境下的趋光控制问题,模拟人或动物“感知-行动”认知机制,对具有趋光特性的移动机器人进行设计,提出一种基于Boltzmann机神经网络的趋光控制方法。该方法首先应用知识集对机器人趋光控制器的Boltzmann机神经网络进行趋光训练;然后应用Boltzmann机神经网络的运行机制实现趋光控制。仿真实验表明,该方法能够提高机器人学习的控制精度。

  2. 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

  3. 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.

  4. 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 ...

  5. Cognitive Fingerprints

    Science.gov (United States)

    2015-03-25

    approaches vary but most involve machine learning and data mining techniques and specific computational methods will be highlighted. Digital traces from...dynamics (which are a behavioral biometric) with linguistic features (Juola et al. 2013). Linguistic features include lexical statis- tics (e.g., word...concerning aggregated features suggesting the possibility of similar computational approaches in cap- turing a cognitive fingerprint. Prior work in Web

  6. 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…

  7. 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…

  8. Machine Learning

    CERN Document Server

    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.

  9. 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.

  10. Machine testning

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo

    This document is used in connection with a laboratory exercise of 3 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercise includes a series of tests carried out by the student on a conventional and a numerically controled lathe, respectively. This document...

  11. Representational Machines

    DEFF Research Database (Denmark)

    Petersson, Dag; Dahlgren, Anna; Vestberg, Nina Lager

    to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...

  12. 计算主义纲领与机器博弈的认知意蕴%The Calculated Doctrine Program and the Cognitive Implication of the Machine Game

    Institute of Scientific and Technical Information of China (English)

    谷飙

    2011-01-01

    In the flood of the second- generation cognitive science, computing platform still leads to the field of traditional knowledge and emerging branch of cognitive development while facing the challenges of the theory of behaviorism, and connectionism. Machin%在第二代认知科学的潮涌中,计算主义纲领虽然面临心灵实在论、行为主义、联结主义的挑战,但仍然引导着传统认知领域和新兴认知分支的发展。机器博弈是认知科学与博弈论互动的产物,在计算主义纲领启发下,理性人之间的博弈被视为人一机智能体间的策略性互动,互动认知、博弈学习、演化博弈等理论成为智能体感知环境、处理信息、控制行为、交流互动的分析基础。自动机在重复博弈中显示出的长远眼光、威胁和承诺能力,提供了解决计算主义纲领主要难题——意向性之谜的思路:意向性并不是孤独的心灵与外部世界的关系,而是通过智能体互动实现的自我指涉

  13. Adding machine and calculating machine

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In 1642 the French mathematician Blaise Pascal(1623-1662) invented a machine;.that could add and subtract. It had.wheels that each had: 1 to 10 marked off along its circumference. When the wheel at the right, representing units, made one complete circle, it engaged the wheel to its left, represents tens, and moved it forward one notch.

  14. Genesis machines

    CERN Document Server

    Amos, Martyn

    2014-01-01

    Silicon chips are out. Today's scientists are using real, wet, squishy, living biology to build the next generation of computers. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Much smaller and more intelligent, these organic computers open up revolutionary possibilities. Tracing the history of computing and revealing a brave new world to come, Genesis Machines describes how this new technology will change the way we think not just about computers - but about life itself.

  15. Cognition: Human Information Processing. Introduction.

    Science.gov (United States)

    Griffith, Belver C.

    1981-01-01

    Summarizes the key research issues and developments in cognitive science, especially with respect to the similarities, differences, and interrelationships between human and machine information processing. Nine references are listed. (JL)

  16. Simulating Turing machines on Maurer machines

    NARCIS (Netherlands)

    Bergstra, J.A.; Middelburg, C.A.

    2008-01-01

    In a previous paper, we used Maurer machines to model and analyse micro-architectures. In the current paper, we investigate the connections between Turing machines and Maurer machines with the purpose to gain an insight into computability issues relating to Maurer machines. We introduce ways to

  17. 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.

  18. Machine Transliteration

    CERN Document Server

    Knight, K; Knight, Kevin; Graehl, Jonathan

    1997-01-01

    It is challenging to translate names and technical terms across languages with different alphabets and sound inventories. These items are commonly transliterated, i.e., replaced with approximate phonetic equivalents. For example, "computer" in English comes out as "konpyuutaa" in Japanese. Translating such items from Japanese back to English is even more challenging, and of practical interest, as transliterated items make up the bulk of text phrases not found in bilingual dictionaries. We describe and evaluate a method for performing backwards transliterations by machine. This method uses a generative model, incorporating several distinct stages in the transliteration process.

  19. Machine Protection

    CERN Document Server

    Schmidt, R

    2014-01-01

    The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an ...

  20. The Application of Man-Machine System Theory in Information System%人机系统理论在情报系统中的应用

    Institute of Scientific and Technical Information of China (English)

    王以群; 张力; 张中会

    2000-01-01

    In the light of cognitive science and man-machine system theory, users' information cognitive behavior models are studied. Three experiments are carried out to study how machine factors influence the cognitive abilities of users. Finally, man and machine problems with information automation system management are discussed.

  1. 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...

  2. Interaction with Machine Improvisation

    Science.gov (United States)

    Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

    We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

  3. 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.

  4. 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.

  5. 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 ...

  6. 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.

  7. Automation of printing machine

    OpenAIRE

    Sušil, David

    2016-01-01

    Bachelor thesis is focused on the automation of the printing machine and comparing the two types of printing machines. The first chapter deals with the history of printing, typesettings, printing techniques and various kinds of bookbinding. The second chapter describes the difference between sheet-fed printing machines and offset printing machines, the difference between two representatives of rotary machines, technological process of the products on these machines, the description of the mac...

  8. Extended Carbon Cognition as a Machine

    DEFF Research Database (Denmark)

    Lippert, Ingmar

    2011-01-01

    By way of exploring ethnographic data on carbon construction practices by agents of ecological modernisation in a multinational corporation, this paper seeks to problematise the distributed and heterogeneous intelligence assembled by human and non-humans to make intelligible their carbon footprin...

  9. Extended Carbon Cognition as a Machine

    DEFF Research Database (Denmark)

    Lippert, Ingmar

    2011-01-01

    of thinking allows to question the conceptualisa- tions of the actors involved and how their practical interactions render carbon, nature and our society (un)sustainable. This, I hope, provides a chance to better conceptualise individuals, their social and material contexts, and through that, corresponding...... into being. Thus, carbon emerges as co-constituted by thought. I will focus on instances in which the corporate machinery, i.e. automated thought, had to be supplemented by immediate human practices of 1) thinking themselves, 2) organising materials to think through and 3) ordering others to think...

  10. Electrical machines mathematical fundamentals of machine topologies

    CERN Document Server

    Gerling, Dieter

    2015-01-01

    Electrical Machines and Drives play a powerful role in industry with an ever increasing importance. This fact requires the understanding of machine and drive principles by engineers of many different disciplines. Therefore, this book is intended to give a comprehensive deduction of these principles. Special attention is given to the precise mathematical derivation of the necessary formulae to calculate machines and drives and to the discussion of simplifications (if applied) with the associated limits. The book shows how the different machine topologies can be deduced from general fundamentals, and how they are linked together. This book addresses graduate students, researchers, and developers of Electrical Machines and Drives, who are interested in getting knowledge about the principles of machine and drive operation and in detecting the mathematical and engineering specialties of the different machine and drive topologies together with their mutual links. The detailed - but nevertheless compact - mat...

  11. Laser machining of advanced materials

    CERN Document Server

    Dahotre, Narendra B

    2011-01-01

    Advanced materialsIntroductionApplicationsStructural ceramicsBiomaterials CompositesIntermetallicsMachining of advanced materials IntroductionFabrication techniquesMechanical machiningChemical Machining (CM)Electrical machiningRadiation machining Hybrid machiningLaser machiningIntroductionAbsorption of laser energy and multiple reflectionsThermal effectsLaser machining of structural ceramicsIntrodu

  12. The deleuzian abstract machines

    DEFF Research Database (Denmark)

    Werner Petersen, Erik

    2005-01-01

    production. In Kafka: Toward a Minor Literature, Deleuze and Guatari gave the most comprehensive explanation to the abstract machine in the work of art. Like the war-machines of Virilio, the Kafka-machine operates in three gears or speeds. Furthermore, the machine is connected to spatial diagrams...

  13. 基于支持向量机的遗忘型轻度认知障碍个体识别研究%Individual identification research of amnestic mild cognitive impairment based on support vector machine

    Institute of Scientific and Technical Information of China (English)

    张忠敏; 崔再续; 郭艳芹; 李坤成; 贾建平; 韩璎

    2014-01-01

    Objective In recent years , multivariate pattern analysis ( MVPA) method was proposed and considered to be a promising tool for automated identification of various neuropsychiatric populations .Support vector machine ( SVM) is one of the most widely used methods of MVPA .Using SVM classifier for MVPA of amnestic mild cognitive impairment (aMCI) and normal control (NC) group, the present study aims to build an individual diagnostic model with significant discriminative power and investigate the gray matter abnor-malities of aMCI patients . Methods Fifty-one aMCI patients and 68 normal controls were scanned on the 3-Tesla magnetic resonance imaging (MRI) for high-resolution T1-weighted images.Gray matter volume map was calculated for each subject and used as features for subsequent discriminative analysis .We first applied feature selection to remove redundant information and reduce feature dimension , and then trained an SVM classifier . Leave-one-out cross validation ( LOOCV) was used to estimate the performance of the classifier , and finally the most discriminative features were identified . Results The proposed classifier achieved a classification accuracy of 83.19%with a sensitivity of 76.47%and a specificity of 88.24%.In ad-dition, the area under the receiver operating characteristic (ROC) curve was 0.8368.Further analysis revealed that the most discrimi-native features for classification included bilateral parahippocampal gyri , bilateral hippocampi , bilateral amygdala , bilateral thalamus , right cingulate , right precuneus , left caudate , left superior temporal gyrus , left middle temporal gyrus , left insula and left orbitofrontal cortex. Conclusion The proposed classification model has achieved significant accuracy for aMCI prediction , and it also displayed the whole brain gray matter atrophy pattern in aMCI patients .It suggests that the proposed method may have important implications for early clinical diagnosis of aMCI patients .%目的:

  14. 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

  15. 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

  16. Design of Demining Machines

    CERN Document Server

    Mikulic, Dinko

    2013-01-01

    In constant effort to eliminate mine danger, international mine action community has been developing safety, efficiency and cost-effectiveness of clearance methods. Demining machines have become necessary when conducting humanitarian demining where the mechanization of demining provides greater safety and productivity. Design of Demining Machines describes the development and testing of modern demining machines in humanitarian demining.   Relevant data for design of demining machines are included to explain the machinery implemented and some innovative and inspiring development solutions. Development technologies, companies and projects are discussed to provide a comprehensive estimate of the effects of various design factors and to proper selection of optimal parameters for designing the demining machines.   Covering the dynamic processes occurring in machine assemblies and their components to a broader understanding of demining machine as a whole, Design of Demining Machines is primarily tailored as a tex...

  17. 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.

  18. 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.

  19. Women, Men, and Machines.

    Science.gov (United States)

    Form, William; McMillen, David Byron

    1983-01-01

    Data from the first national study of technological change show that proportionately more women than men operate machines, are more exposed to machines that have alienating effects, and suffer more from the negative effects of technological change. (Author/SSH)

  20. 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...

  1. 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

  2. Cooperative Human-Machine Fault Diagnosis

    Science.gov (United States)

    Remington, Roger; Palmer, Everett

    1987-02-01

    Current expert system technology does not permit complete automatic fault diagnosis; significant levels of human intervention are still required. This requirement dictates a need for a division of labor that recognizes the strengths and weaknesses of both human and machine diagnostic skills. Relevant findings from the literature on human cognition are combined with the results of reviews of aircrew performance with highly automated systems to suggest how the interface of a fault diagnostic expert system can be designed to assist human operators in verifying machine diagnoses and guiding interactive fault diagnosis. It is argued that the needs of the human operator should play an important role in the design of the knowledge base.

  3. 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...

  4. 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

  5. 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.

  6. Precision machine design

    CERN Document Server

    Slocum, Alexander H

    1992-01-01

    This book is a comprehensive engineering exploration of all the aspects of precision machine design - both component and system design considerations for precision machines. It addresses both theoretical analysis and practical implementation providing many real-world design case studies as well as numerous examples of existing components and their characteristics. Fast becoming a classic, this book includes examples of analysis techniques, along with the philosophy of the solution method. It explores the physics of errors in machines and how such knowledge can be used to build an error budget for a machine, how error budgets can be used to design more accurate machines.

  7. 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

  8. Perspex machine: VII. The universal perspex machine

    Science.gov (United States)

    Anderson, James A. D. W.

    2006-01-01

    The perspex machine arose from the unification of projective geometry with the Turing machine. It uses a total arithmetic, called transreal arithmetic, that contains real arithmetic and allows division by zero. Transreal arithmetic is redefined here. The new arithmetic has both a positive and a negative infinity which lie at the extremes of the number line, and a number nullity that lies off the number line. We prove that nullity, 0/0, is a number. Hence a number may have one of four signs: negative, zero, positive, or nullity. It is, therefore, impossible to encode the sign of a number in one bit, as floating-point arithmetic attempts to do, resulting in the difficulty of having both positive and negative zeros and NaNs. Transrational arithmetic is consistent with Cantor arithmetic. In an extension to real arithmetic, the product of zero, an infinity, or nullity with its reciprocal is nullity, not unity. This avoids the usual contradictions that follow from allowing division by zero. Transreal arithmetic has a fixed algebraic structure and does not admit options as IEEE, floating-point arithmetic does. Most significantly, nullity has a simple semantics that is related to zero. Zero means "no value" and nullity means "no information." We argue that nullity is as useful to a manufactured computer as zero is to a human computer. The perspex machine is intended to offer one solution to the mind-body problem by showing how the computable aspects of mind and, perhaps, the whole of mind relates to the geometrical aspects of body and, perhaps, the whole of body. We review some of Turing's writings and show that he held the view that his machine has spatial properties. In particular, that it has the property of being a 7D lattice of compact spaces. Thus, we read Turing as believing that his machine relates computation to geometrical bodies. We simplify the perspex machine by substituting an augmented Euclidean geometry for projective geometry. This leads to a general

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. Debugging the virtual machine

    Energy Technology Data Exchange (ETDEWEB)

    Miller, P.; Pizzi, R.

    1994-09-02

    A computer program is really nothing more than a virtual machine built to perform a task. The program`s source code expresses abstract constructs using low level language features. When a virtual machine breaks, it can be very difficult to debug because typical debuggers provide only low level machine implementation in formation to the software engineer. We believe that the debugging task can be simplified by introducing aspects of the abstract design into the source code. We introduce OODIE, an object-oriented language extension that allows programmers to specify a virtual debugging environment which includes the design and abstract data types of the virtual machine.

  17. 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

  18. 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

  19. 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

  20. Perpetual Self-Aware Cognitive Agents

    OpenAIRE

    2007-01-01

    To construct a perpetual self-aware cognitive agent that can continuously operate with independence, an introspective machine must be produced. To assemble such an agent, it is necessary to perform a full integration of cognition (planning, understanding, and learning) and metacognition (control and monitoring of cognition) with intelligent behaviors. The failure to do this completely is why similar, more limited efforts have not succeeded in the past. I outline some key computational require...

  1. Virtual machine vs Real Machine: Security Systems

    Directory of Open Access Journals (Sweden)

    Dr. C. Suresh Gnana Das

    2009-08-01

    Full Text Available This paper argues that the operating system and applications currently running on a real machine should relocate into a virtual machine. This structure enables services to be added below the operating system and to do so without trusting or modifying the operating system or applications. To demonstrate the usefulness of this structure, we describe three services that take advantage of it: secure logging, intrusion prevention and detection, and environment migration. In particular, we can provide services below the guest operating system without trusting or modifying it. We believe providing services at this layer are especially useful for enhancing security and mobility. This position paper describes the general benefits and challenges that arise from running most applications in a virtual machine, and then describes some example services and alternative ways to provide those services.

  2. Automatic Evaluation of Machine Translation

    DEFF Research Database (Denmark)

    Martinez, Mercedes Garcia; Koglin, Arlene; Mesa-Lao, Bartolomé

    2015-01-01

    The availability of systems capable of producing fairly accurate translations has increased the popularity of machine translation (MT). The translation industry is steadily incorporating MT in their workflows engaging the human translator to post-edit the raw MT output in order to comply with a set...... of post-editing effort, namely i) temporal (time), ii) cognitive (mental processes) and iii) technical (keyboard activity). For the purposes of this research, TER scores were correlated with two different indicators of post-editing effort as computed in the CRITT Translation Process Database (TPR......-DB) *. On the one hand, post-editing temporal effort was measured using FDur values (duration of segment production time excluding keystroke pauses >_ 200 seconds) and KDur values (duration of coherent keyboard activity excluding keystroke pauses >_ 5 seconds). On the other hand, post-editing technical effort...

  3. Checking the STEP-Associated Trafficking and Internalization of Glutamate Receptors for Reduced Cognitive Deficits: A Machine Learning Approach-Based Cheminformatics Study and Its Application for Drug Repurposing.

    Science.gov (United States)

    Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav

    2015-01-01

    Alzheimer's disease, a lethal neurodegenerative disorder that leads to progressive memory loss, is the most common form of dementia. Owing to the complexity of the disease, its root cause still remains unclear. The existing anti-Alzheimer's drugs are unable to cure the disease while the current therapeutic options have provided only limited help in restoring moderate memory and remain ineffective at restricting the disease's progression. The striatal-enriched protein tyrosine phosphatase (STEP) has been shown to be involved in the internalization of the receptor, N-methyl D-aspartate (NMDR) and thus is associated with the disease. The present study was performed using machine learning algorithms, docking protocol and molecular dynamics (MD) simulations to develop STEP inhibitors, which could be novel anti-Alzheimer's molecules. The present study deals with the generation of computational predictive models based on chemical descriptors of compounds using machine learning approaches followed by substructure fragment analysis. To perform this analysis, the 2D molecular descriptors were generated and machine learning algorithms (Naïve Bayes, Random Forest and Sequential Minimization Optimization) were utilized. The binding mechanisms and the molecular interactions between the predicted active compounds and the target protein were modelled using docking methods. Further, the stability of the protein-ligand complex was evaluated using MD simulation studies. The substructure fragment analysis was performed using Substructure fingerprint (SubFp), which was further explored using a predefined dictionary. The present study demonstrates that the computational methodology used can be employed to examine the biological activities of small molecules and prioritize them for experimental screening. Large unscreened chemical libraries can be screened to identify potential novel hits and accelerate the drug discovery process. Additionally, the chemical libraries can be searched for

  4. Checking the STEP-Associated Trafficking and Internalization of Glutamate Receptors for Reduced Cognitive Deficits: A Machine Learning Approach-Based Cheminformatics Study and Its Application for Drug Repurposing.

    Directory of Open Access Journals (Sweden)

    Salma Jamal

    Full Text Available Alzheimer's disease, a lethal neurodegenerative disorder that leads to progressive memory loss, is the most common form of dementia. Owing to the complexity of the disease, its root cause still remains unclear. The existing anti-Alzheimer's drugs are unable to cure the disease while the current therapeutic options have provided only limited help in restoring moderate memory and remain ineffective at restricting the disease's progression. The striatal-enriched protein tyrosine phosphatase (STEP has been shown to be involved in the internalization of the receptor, N-methyl D-aspartate (NMDR and thus is associated with the disease. The present study was performed using machine learning algorithms, docking protocol and molecular dynamics (MD simulations to develop STEP inhibitors, which could be novel anti-Alzheimer's molecules.The present study deals with the generation of computational predictive models based on chemical descriptors of compounds using machine learning approaches followed by substructure fragment analysis. To perform this analysis, the 2D molecular descriptors were generated and machine learning algorithms (Naïve Bayes, Random Forest and Sequential Minimization Optimization were utilized. The binding mechanisms and the molecular interactions between the predicted active compounds and the target protein were modelled using docking methods. Further, the stability of the protein-ligand complex was evaluated using MD simulation studies. The substructure fragment analysis was performed using Substructure fingerprint (SubFp, which was further explored using a predefined dictionary.The present study demonstrates that the computational methodology used can be employed to examine the biological activities of small molecules and prioritize them for experimental screening. Large unscreened chemical libraries can be screened to identify potential novel hits and accelerate the drug discovery process. Additionally, the chemical libraries can be

  5. Stirling machine operating experience

    Energy Technology Data Exchange (ETDEWEB)

    Ross, B. [Stirling Technology Co., Richland, WA (United States); Dudenhoefer, J.E. [Lewis Research Center, Cleveland, OH (United States)

    1994-09-01

    Numerous Stirling machines have been built and operated, but the operating experience of these machines is not well known. It is important to examine this operating experience in detail, because it largely substantiates the claim that stirling machines are capable of reliable and lengthy operating lives. The amount of data that exists is impressive, considering that many of the machines that have been built are developmental machines intended to show proof of concept, and are not expected to operate for lengthy periods of time. Some Stirling machines (typically free-piston machines) achieve long life through non-contact bearings, while other Stirling machines (typically kinematic) have achieved long operating lives through regular seal and bearing replacements. In addition to engine and system testing, life testing of critical components is also considered. The record in this paper is not complete, due to the reluctance of some organizations to release operational data and because several organizations were not contacted. The authors intend to repeat this assessment in three years, hoping for even greater participation.

  6. Perpetual Motion Machine

    Directory of Open Access Journals (Sweden)

    D. Tsaousis

    2008-01-01

    Full Text Available Ever since the first century A.D. there have been relative descriptions of known devices as well as manufactures for the creation of perpetual motion machines. Although physics has led, with two thermodynamic laws, to the opinion that a perpetual motion machine is impossible to be manufactured, inventors of every age and educational level appear to claim that they have invented something «entirely new» or they have improved somebody else’s invention, which «will function henceforth perpetually»! However the fact of the failure in manufacturing a perpetual motion machine till now, it does not mean that countless historical elements for these fictional machines become indifferent. The discussion on every version of a perpetual motion machine on the one hand gives the chance to comprehend the inventor’s of each period level of knowledge and his way of thinking, and on the other hand, to locate the points where this «perpetual motion machine» clashes with the laws of nature and that’s why it is impossible to have been manufactured or have functioned. The presentation of a new «perpetual motion machine» has excited our interest to locate its weak points. According to the designer of it the machine functions with the work produced by the buoyant force

  7. Machine Intelligence and Explication

    NARCIS (Netherlands)

    Wieringa, Roelf J.

    1987-01-01

    This report is an MA ("doctoraal") thesis submitted to the department of philosophy, university of Amsterdam. It attempts to answer the question whether machines can think by conceptual analysis. Ideally. a conceptual analysis should give plausible explications of the concepts of "machine" and "inte

  8. 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.

  9. Reactive Turing machines

    NARCIS (Netherlands)

    Baeten, J.C.M.; Luttik, B.; Tilburg, P.J.A. van

    2013-01-01

    We propose reactive Turing machines (RTMs), extending classical Turing machines with a process-theoretical notion of interaction, and use it to define a notion of executable transition system. We show that every computable transition system with a bounded branching degree is simulated modulo diverge

  10. Machine Intelligence and Explication

    NARCIS (Netherlands)

    Wieringa, Roel

    1987-01-01

    This report is an MA ("doctoraal") thesis submitted to the department of philosophy, university of Amsterdam. It attempts to answer the question whether machines can think by conceptual analysis. Ideally. a conceptual analysis should give plausible explications of the concepts of "machine" and "inte

  11. 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) Traceability...

  12. Simple Machine Junk Cars

    Science.gov (United States)

    Herald, Christine

    2010-01-01

    During the month of May, the author's eighth-grade physical science students study the six simple machines through hands-on activities, reading assignments, videos, and notes. At the end of the month, they can easily identify the six types of simple machine: inclined plane, wheel and axle, pulley, screw, wedge, and lever. To conclude this unit,…

  13. 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…

  14. 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.

  15. 15 CFR 700.31 - Metalworking machines.

    Science.gov (United States)

    2010-01-01

    ... Drilling and tapping machines Electrical discharge, ultrasonic and chemical erosion machines Forging..., power driven Machining centers and way-type machines Manual presses Mechanical presses, power...

  16. 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 –...

  17. Micro-machining.

    Science.gov (United States)

    Brinksmeier, Ekkard; Preuss, Werner

    2012-08-28

    Manipulating bulk material at the atomic level is considered to be the domain of physics, chemistry and nanotechnology. However, precision engineering, especially micro-machining, has become a powerful tool for controlling the surface properties and sub-surface integrity of the optical, electronic and mechanical functional parts in a regime where continuum mechanics is left behind and the quantum nature of matter comes into play. The surprising subtlety of micro-machining results from the extraordinary precision of tools, machines and controls expanding into the nanometre range-a hundred times more precise than the wavelength of light. In this paper, we will outline the development of precision engineering, highlight modern achievements of ultra-precision machining and discuss the necessity of a deeper physical understanding of micro-machining.

  18. 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.

  19. 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.

  20. Grounded cognition.

    Science.gov (United States)

    Barsalou, Lawrence W

    2008-01-01

    Grounded cognition rejects traditional views that cognition is computation on amodal symbols in a modular system, independent of the brain's modal systems for perception, action, and introspection. Instead, grounded cognition proposes that modal simulations, bodily states, and situated action underlie cognition. Accumulating behavioral and neural evidence supporting this view is reviewed from research on perception, memory, knowledge, language, thought, social cognition, and development. Theories of grounded cognition are also reviewed, as are origins of the area and common misperceptions of it. Theoretical, empirical, and methodological issues are raised whose future treatment is likely to affect the growth and impact of grounded cognition.

  1. Improving air traffic control: Proving new tools or approving the joint human-machine system?

    Science.gov (United States)

    Gaillard, Irene; Leroux, Marcel

    1994-01-01

    From the description of a field problem (i.e., designing decision aids for air traffic controllers), this paper points out how a cognitive engineering approach provides the milestones for the evaluation of future joint human-machine systems.

  2. 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

  3. The basic anaesthesia machine.

    Science.gov (United States)

    Gurudatt, Cl

    2013-09-01

    After WTG Morton's first public demonstration in 1846 of use of ether as an anaesthetic agent, for many years anaesthesiologists did not require a machine to deliver anaesthesia to the patients. After the introduction of oxygen and nitrous oxide in the form of compressed gases in cylinders, there was a necessity for mounting these cylinders on a metal frame. This stimulated many people to attempt to construct the anaesthesia machine. HEG Boyle in the year 1917 modified the Gwathmey's machine and this became popular as Boyle anaesthesia machine. Though a lot of changes have been made for the original Boyle machine still the basic structure remains the same. All the subsequent changes which have been brought are mainly to improve the safety of the patients. Knowing the details of the basic machine will make the trainee to understand the additional improvements. It is also important for every practicing anaesthesiologist to have a thorough knowledge of the basic anaesthesia machine for safe conduct of anaesthesia.

  4. The basic anaesthesia machine

    Directory of Open Access Journals (Sweden)

    C L Gurudatt

    2013-01-01

    Full Text Available After WTG Morton′s first public demonstration in 1846 of use of ether as an anaesthetic agent, for many years anaesthesiologists did not require a machine to deliver anaesthesia to the patients. After the introduction of oxygen and nitrous oxide in the form of compressed gases in cylinders, there was a necessity for mounting these cylinders on a metal frame. This stimulated many people to attempt to construct the anaesthesia machine. HEG Boyle in the year 1917 modified the Gwathmey′s machine and this became popular as Boyle anaesthesia machine. Though a lot of changes have been made for the original Boyle machine still the basic structure remains the same. All the subsequent changes which have been brought are mainly to improve the safety of the patients. Knowing the details of the basic machine will make the trainee to understand the additional improvements. It is also important for every practicing anaesthesiologist to have a thorough knowledge of the basic anaesthesia machine for safe conduct of anaesthesia.

  5. Part Machinability Evaluation System

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    In the early design period, estimation of the part or the whole product machinability is useful to consider the function and process request of the product at the same time so as to globally optimize the design decision. This paper presents a part machinability evaluation system, discusses the general restrictions of part machinability, and realizes the inspection of these restrictions with the relation between tool scan space and part model. During the system development, the expansibility and understandability were considered, and an independent restriction algorithm library and a general function library were set up. Additionally, the system has an interpreter and a knowledge manager.

  6. 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

  7. 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.

  8. Analysis of synchronous machines

    CERN Document Server

    Lipo, TA

    2012-01-01

    Analysis of Synchronous Machines, Second Edition is a thoroughly modern treatment of an old subject. Courses generally teach about synchronous machines by introducing the steady-state per phase equivalent circuit without a clear, thorough presentation of the source of this circuit representation, which is a crucial aspect. Taking a different approach, this book provides a deeper understanding of complex electromechanical drives. Focusing on the terminal rather than on the internal characteristics of machines, the book begins with the general concept of winding functions, describing the placeme

  9. Database machine performance

    Energy Technology Data Exchange (ETDEWEB)

    Cesarini, F.; Salza, S.

    1987-01-01

    This book is devoted to the important problem of database machine performance evaluation. The book presents several methodological proposals and case studies, that have been developed within an international project supported by the European Economic Community on Database Machine Evaluation Techniques and Tools in the Context of the Real Time Processing. The book gives an overall view of the modeling methodologies and the evaluation strategies that can be adopted to analyze the performance of the database machine. Moreover, it includes interesting case studies and an extensive bibliography.

  10. Virtual Machine Introspection

    Directory of Open Access Journals (Sweden)

    S C Rachana

    2014-06-01

    Full Text Available Cloud computing is an Internet-based computing solution which provides the resources in an effective manner. A very serious issue in cloud computing is security which is a major obstacle for the adoption of cloud. The most important threats of cloud computing are Multitenancy, Availability, Loss of control, Loss of Data, outside attacks, DOS attacks, malicious insiders, etc. Among many security issues in cloud, the Virtual Machine Security is one of the very serious issues. Thus, monitoring of virtual machine is essential. The paper proposes a Virtual Network Introspection [VMI] System to secure the Virtual machines from Distributed Denial of Service [DDOS] and Zombie attacks.

  11. Virtual Machine Introspection

    Directory of Open Access Journals (Sweden)

    S C Rachana

    2015-11-01

    Full Text Available Cloud computing is an Internet-based computing solution which provides the resources in an effective manner. A very serious issue in cloud computing is security which is a major obstacle for the adoption of cloud. The most important threats of cloud computing are Multitenancy, Availability, Loss of control, Loss of Data, outside attacks, DOS attacks, malicious insiders, etc. Among many security issues in cloud, the Virtual Machine Security is one of the very serious issues. Thus, monitoring of virtual machine is essential. The paper proposes a Virtual Network Introspection [VMI] System to secure the Virtual machines from Distributed Denial of Service [DDOS] and Zombie attacks.

  12. 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

  13. 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

  14. Some relations between quantum Turing machines and Turing machines

    CERN Document Server

    Sicard, A; 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 deterministic Turing machines, the time evolution operator is related with reversible Turing machines and the local transition function is related with probabilistic and reversible Turing machines.

  15. Machining of hard-to-machine materials

    OpenAIRE

    2016-01-01

    Bakalářská práce se zabývá studiem obrábění těžkoobrobitelných materiálů. V první části jsou rozděleny těžkoobrobitelné materiály a následuje jejich analýza. V další části se práce zaměřuje na problematiku obrobitelnosti jednotlivých slitin. Závěrečná část práce je věnovaná experimentu, jeho statistickému zpracování a nakonec následnému vyhodnocení. This bachelor thesis studies the machining of hard-to-machine materials. The first part of the thesis considers hard-to-machine materials and ...

  16. Machine (bulk) harvest

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This is a summary of machine harvesting activities on Neal Smith National Wildlife Refuge between 1991 and 2008. Information is provided for each year about...

  17. 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...

  18. Tests of Machine Intelligence

    CERN Document Server

    Legg, Shane

    2007-01-01

    Although the definition and measurement of intelligence is clearly of fundamental importance to the field of artificial intelligence, no general survey of definitions and tests of machine intelligence exists. Indeed few researchers are even aware of alternatives to the Turing test and its many derivatives. In this paper we fill this gap by providing a short survey of the many tests of machine intelligence that have been proposed.

  19. Metalworking and machining fluids

    Science.gov (United States)

    Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

    2010-10-12

    Improved boron-based metal working and machining fluids. Boric acid and boron-based additives that, when mixed with certain carrier fluids, such as water, cellulose and/or cellulose derivatives, polyhydric alcohol, polyalkylene glycol, polyvinyl alcohol, starch, dextrin, in solid and/or solvated forms result in improved metalworking and machining of metallic work pieces. Fluids manufactured with boric acid or boron-based additives effectively reduce friction, prevent galling and severe wear problems on cutting and forming tools.

  20. mlpy: Machine Learning Python

    CERN Document Server

    Albanese, Davide; Merler, Stefano; Riccadonna, Samantha; Jurman, Giuseppe; Furlanello, Cesare

    2012-01-01

    mlpy is a Python Open Source Machine Learning library built on top of NumPy/SciPy and the GNU Scientific Libraries. mlpy provides a wide range of state-of-the-art machine learning methods for supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and efficiency. mlpy is multiplatform, it works with Python 2 and 3 and it is distributed under GPL3 at the website http://mlpy.fbk.eu.

  1. Machine Learning with Distances

    Science.gov (United States)

    2015-02-16

    and demonstrated their usefulness in experiments. 1 Introduction The goal of machine learning is to find useful knowledge behind data. Many machine...212, 172]. However, direct divergence approximators still suffer from the curse of dimensionality. A possible cure for this problem is to combine them...obtain the global optimal solution or even a good local solution without any prior knowledge . For this reason, we decided to introduce the unit-norm

  2. mlpy: Machine Learning Python

    OpenAIRE

    Albanese, Davide; Visintainer, Roberto; Merler, Stefano; Riccadonna, Samantha; Jurman, Giuseppe; Furlanello, Cesare

    2012-01-01

    mlpy is a Python Open Source Machine Learning library built on top of NumPy/SciPy and the GNU Scientific Libraries. mlpy provides a wide range of state-of-the-art machine learning methods for supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and efficiency. mlpy is multiplatform, it works with Python 2 and 3 and it is distributed under GPL3 at the website http://mlpy.fbk.eu.

  3. The Relevance of Peirce's Semiotic for Cognitive Science

    OpenAIRE

    Tiercelin, Claudine

    1995-01-01

    The aim of the text is to present Peirce's relevance for cognitive science,especially in terms of his views in semiotic (i.e, for him : logic), logical machines, and the psychology of iconic reasoning.

  4. EVALUATION OF MACHINE TOOL QUALITY

    Directory of Open Access Journals (Sweden)

    Ivan Kuric

    2011-12-01

    Full Text Available Paper deals with aspects of quality and accuracy of machine tools. As the accuracy of machine tools has key factor for product quality, it is important to know the methods for evaluation of quality and accuracy of machine tools. Several aspects of diagnostics of machine tools are described, such as aspects of reliability.

  5. 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...

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

    Science.gov (United States)

    Sundararajan, Louise

    2014-01-01

    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. PMID:25541564

  7. 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.

  8. Machining of fiber reinforced composites

    Science.gov (United States)

    Komanduri, Ranga; Zhang, Bi; Vissa, Chandra M.

    Factors involved in machining of fiber-reinforced composites are reviewed. Consideration is given to properties of composites reinforced with boron filaments, glass fibers, aramid fibers, carbon fibers, and silicon carbide fibers and to polymer (organic) matrix composites, metal matrix composites, and ceramic matrix composites, as well as to the processes used in conventional machining of boron-titanium composites and of composites reinforced by each of these fibers. Particular attention is given to the methods of nonconventional machining, such as laser machining, water jet cutting, electrical discharge machining, and ultrasonic assisted machining. Also discussed are safety precautions which must be taken during machining of fiber-containing composites.

  9. 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...

  10. Cognitive ecology.

    Science.gov (United States)

    Hutchins, Edwin

    2010-10-01

    Cognitive ecology is the study of cognitive phenomena in context. In particular, it points to the web of mutual dependence among the elements of a cognitive ecosystem. At least three fields were taking a deeply ecological approach to cognition 30 years ago: Gibson's ecological psychology, Bateson's ecology of mind, and Soviet cultural-historical activity theory. The ideas developed in those projects have now found a place in modern views of embodied, situated, distributed cognition. As cognitive theory continues to shift from units of analysis defined by inherent properties of the elements to units defined in terms of dynamic patterns of correlation across elements, the study of cognitive ecosystems will become an increasingly important part of cognitive science.

  11. 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.

  12. Cognitive and Neural Correlates of Aging in Autism Spectrum Disorder

    Science.gov (United States)

    2016-07-01

    Bayesian networks, machine learning 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON...methods, we will use innovative machine learning and sparse Bayesian networks to combine structure, function, cognition, and symptom profiles to...and will contribute to the establishment of a core set of cognitive tests and other data that can be collated across studies from around the world

  13. Machinability evaluation of machinable ceramics with fuzzy theory

    Institute of Scientific and Technical Information of China (English)

    YU Ai-bing; ZHONG Li-jun; TAN Ye-fa

    2005-01-01

    The property parameters and machining output parameters were selected for machinability evaluation of machinable ceramics. Based on fuzzy evaluation theory, two-stage fuzzy evaluation approach was applied to consider these parameters. Two-stage fuzzy comprehensive evaluation model was proposed to evaluate machinability of machinable ceramic materials. Ce-ZrO2/CePO4 composites were fabricated and machined for evaluation of machinable ceramics. Material removal rates and specific normal grinding forces were measured. The parameters concerned with machinability were selected as alternative set. Five grades were chosen for the machinability evaluation of machnable ceramics. Machinability grades of machinable ceramics were determined through fuzzy operation. Ductile marks are observed on Ce-ZrO2/CePO4 machined surface. Five prepared Ce-ZrO2/CePO4 composites are classified as three machinability grades according to the fuzzy comprehensive evaluation results. The machinability grades of Ce-ZrO2/CePO4 composites are concerned with CePO4 content.

  14. MACHINE MOTION EQUATIONS

    Directory of Open Access Journals (Sweden)

    Florian Ion Tiberiu Petrescu

    2015-09-01

    Full Text Available This paper presents the dynamic, original, machine motion equations. The equation of motion of the machine that generates angular speed of the shaft (which varies with position and rotation speed is deduced by conservation kinetic energy of the machine. An additional variation of angular speed is added by multiplying by the coefficient dynamic D (generated by the forces out of mechanism and or by the forces generated by the elasticity of the system. Kinetic energy conservation shows angular speed variation (from the shaft with inertial masses, while the dynamic coefficient introduces the variation of w with forces acting in the mechanism. Deriving the first equation of motion of the machine one can obtain the second equation of motion dynamic. From the second equation of motion of the machine it determines the angular acceleration of the shaft. It shows the distribution of the forces on the mechanism to the internal combustion heat engines. Dynamic, the velocities can be distributed in the same way as forces. Practically, in the dynamic regimes, the velocities have the same timing as the forces. Calculations should be made for an engine with a single cylinder. Originally exemplification is done for a classic distribution mechanism, and then even the module B distribution mechanism of an Otto engine type.

  15. Dynamics of cyclic machines

    CERN Document Server

    Vulfson, Iosif

    2015-01-01

    This book focuses on modern methods of oscillation analysis in machines, including cyclic action mechanisms (linkages, cams, steppers, etc.). It presents schematization techniques and mathematical descriptions of oscillating systems, taking into account the variability of the parameters and nonlinearities, engineering evaluations of dynamic errors, and oscillation suppression methods. The majority of the book is devoted to the development of new methods of dynamic analysis and synthesis for cyclic machines that form regular oscillatory systems with multiple duplicate modules.  There are also sections examining aspects of general engineering interest (nonlinear dissipative forces, systems with non-stationary constraints, impacts and pseudo-impacts in clearances, etc.)  The examples in the book are based on the widely used results of theoretical and experimental studies as well as engineering calculations carried out in relation to machines used in the textile, light, polygraphic and other industries. Particu...

  16. 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.

  17. 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.

  18. Machine Learning Markets

    CERN Document Server

    Storkey, Amos

    2011-01-01

    Prediction markets show considerable promise for developing flexible mechanisms for machine learning. Here, machine learning markets for multivariate systems are defined, and a utility-based framework is established for their analysis. This differs from the usual approach of defining static betting functions. It is shown that such markets can implement model combination methods used in machine learning, such as product of expert and mixture of expert approaches as equilibrium pricing models, by varying agent utility functions. They can also implement models composed of local potentials, and message passing methods. Prediction markets also allow for more flexible combinations, by combining multiple different utility functions. Conversely, the market mechanisms implement inference in the relevant probabilistic models. This means that market mechanism can be utilized for implementing parallelized model building and inference for probabilistic modelling.

  19. Machine Learning for Security

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Applied statistics, aka ‘Machine Learning’, offers a wealth of techniques for answering security questions. It’s a much hyped topic in the big data world, with many companies now providing machine learning as a service. This talk will demystify these techniques, explain the math, and demonstrate their application to security problems. The presentation will include how-to’s on classifying malware, looking into encrypted tunnels, and finding botnets in DNS data. About the speaker Josiah is a security researcher with HP TippingPoint DVLabs Research Group. He has over 15 years of professional software development experience. Josiah used to do AI, with work focused on graph theory, search, and deductive inference on large knowledge bases. As rules only get you so far, he moved from AI to using machine learning techniques identifying failure modes in email traffic. There followed digressions into clustered data storage and later integrated control systems. Current ...

  20. Advanced Analysis of Nontraditional Machining

    CERN Document Server

    Tsai, Hung-Yin

    2013-01-01

    Nontraditional machining utilizes thermal, chemical, electrical, mechanical and optical sources of energy to form and cut materials. Advanced Analysis of Nontraditional Machining explains in-depth how each of these advanced machining processes work, their machining system components, and process variables and industrial applications, thereby offering advanced knowledge and scientific insight. This book also documents the latest and frequently cited research results of a few key nonconventional machining processes for the most concerned topics in industrial applications, such as laser machining, electrical discharge machining, electropolishing of die and mold, and wafer processing for integrated circuit manufacturing. This book also: Fills the gap of the advanced knowledge of nonconventional machining between industry and research Documents latest and frequently cited research of key nonconventional machining processes for the most sought after topics in industrial applications Demonstrates advanced multidisci...

  1. Machining strategy choice: performance VIEWER

    CERN Document Server

    Tapie, Laurent; Anselmetti, Bernard

    2009-01-01

    Nowadays high speed machining (HSM) machine tool combines productivity and part quality. So mould and die maker invested in HSM. Die and mould features are more and more complex shaped. Thus, it is difficult to choose the best machining strategy according to part shape. Geometrical analysis of machining features is not sufficient to make an optimal choice. Some research show that security, technical, functional and economical constrains must be taken into account to elaborate a machining strategy. During complex shape machining, production system limits induce feed rate decreases, thus loss of productivity, in some part areas. In this paper we propose to analyse these areas by estimating tool path quality. First we perform experiments on HSM machine tool to determine trajectory impact on machine tool behaviour. Then, we extract critical criteria and establish models of performance loss. Our work is focused on machine tool kinematical performance and numerical controller unit calculation capacity. We implement...

  2. Electrical machines diagnosis

    CERN Document Server

    Trigeassou, Jean-Claude

    2013-01-01

    Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives.This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit.Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is perf

  3. Refrigerating machine oil

    Energy Technology Data Exchange (ETDEWEB)

    Nozawa, K.

    1981-03-17

    Refrigerating machine oil to be filled in a sealed motorcompressor unit constituting a refrigerating cycle system including an electric refrigerator, an electric cold-storage box, a small-scaled electric refrigerating show-case, a small-scaled electric cold-storage show-case and the like, is arranged to have a specifically enhanced property, in which smaller initial driving power consumption of the sealed motor-compressor and easier supply of the predetermined amount of the refrigerating machine oil to the refrigerating system are both guaranteed even in a rather low environmental temperature condition.

  4. Machine shop basics

    CERN Document Server

    Miller, Rex

    2004-01-01

    Use the right tool the right wayHere, fully updated to include new machines and electronic/digital controls, is the ultimate guide to basic machine shop equipment and how to use it. Whether you're a professional machinist, an apprentice, a trade student, or a handy homeowner, this fully illustrated volume helps you define tools and use them properly and safely. It's packed with review questions for students, and loaded with answers you need on the job.Mark Richard Miller is a Professor and Chairman of the Industrial Technology Department at Texas A&M University in Kingsville, T

  5. Electrical machines & their applications

    CERN Document Server

    Hindmarsh, J

    1984-01-01

    A self-contained, comprehensive and unified treatment of electrical machines, including consideration of their control characteristics in both conventional and semiconductor switched circuits. This new edition has been expanded and updated to include material which reflects current thinking and practice. All references have been updated to conform to the latest national (BS) and international (IEC) recommendations and a new appendix has been added which deals more fully with the theory of permanent-magnets, recognising the growing importance of permanent-magnet machines. The text is so arra

  6. Clojure for machine learning

    CERN Document Server

    Wali, Akhil

    2014-01-01

    A book that brings out the strengths of Clojure programming that have to facilitate machine learning. Each topic is described in substantial detail, and examples and libraries in Clojure are also demonstrated.This book is intended for Clojure developers who want to explore the area of machine learning. Basic understanding of the Clojure programming language is required, but thorough acquaintance with the standard Clojure library or any libraries are not required. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage.

  7. Perpetual Motion Machine

    OpenAIRE

    D. Tsaousis

    2008-01-01

    Ever since the first century A.D. there have been relative descriptions of known devices as well as manufactures for the creation of perpetual motion machines. Although physics has led, with two thermodynamic laws, to the opinion that a perpetual motion machine is impossible to be manufactured, inventors of every age and educational level appear to claim that they have invented something «entirely new» or they have improved somebody else’s invention, which «will function henceforth perpetuall...

  8. 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.

  9. Machine Fault Signature Analysis

    Directory of Open Access Journals (Sweden)

    Pratesh Jayaswal

    2008-01-01

    Full Text Available The objective of this paper is to present recent developments in the field of machine fault signature analysis with particular regard to vibration analysis. The different types of faults that can be identified from the vibration signature analysis are, for example, gear fault, rolling contact bearing fault, journal bearing fault, flexible coupling faults, and electrical machine fault. It is not the intention of the authors to attempt to provide a detailed coverage of all the faults while detailed consideration is given to the subject of the rolling element bearing fault signature analysis.

  10. 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

  11. Cognitive optical networks: architectures and techniques

    Science.gov (United States)

    Grebeshkov, Alexander Y.

    2017-04-01

    This article analyzes architectures and techniques of the optical networks with taking into account the cognitive methodology based on continuous cycle "Observe-Orient-Plan-Decide-Act-Learn" and the ability of the cognitive systems adjust itself through an adaptive process by responding to new changes in the environment. Cognitive optical network architecture includes cognitive control layer with knowledge base for control of software-configurable devices as reconfigurable optical add-drop multiplexers, flexible optical transceivers, software-defined receivers. Some techniques for cognitive optical networks as flexible-grid technology, broker-oriented technique, machine learning are examined. Software defined optical network and integration of wireless and optical networks with radio over fiber technique and fiber-wireless technique in the context of cognitive technologies are discussed.

  12. Machine speech and speaking about machines

    Energy Technology Data Exchange (ETDEWEB)

    Nye, A. [Univ. of Wisconsin, Whitewater, WI (United States)

    1996-12-31

    Current philosophy of language prides itself on scientific status. It boasts of being no longer contaminated with queer mental entities or idealist essences. It theorizes language as programmable variants of formal semantic systems, reimaginable either as the properly epiphenomenal machine functions of computer science or the properly material neural networks of physiology. Whether or not such models properly capture the physical workings of a living human brain is a question that scientists will have to answer. I, as a philosopher, come at the problem from another direction. Does contemporary philosophical semantics, in its dominant truth-theoretic and related versions, capture actual living human thought as it is experienced, or does it instead reflect, regardless of (perhaps dubious) scientific credentials, pathology of thought, a pathology with a disturbing social history.

  13. 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.

  14. Cybernetic anthropomorphic machine systems

    Science.gov (United States)

    Gray, W. E.

    1974-01-01

    Functional descriptions are provided for a number of cybernetic man machine systems that augment the capacity of normal human beings in the areas of strength, reach or physical size, and environmental interaction, and that are also applicable to aiding the neurologically handicapped. Teleoperators, computer control, exoskeletal devices, quadruped vehicles, space maintenance systems, and communications equipment are considered.

  15. ARM : abstract rewriting machine

    NARCIS (Netherlands)

    J.F.T. Kamperman; H.R. Walters (Pum)

    1993-01-01

    textabstractTerm rewriting is frequently used as implementation technique for algebraic specifications. In this paper we present the abstract term rewriting machine (ARM), which has an extremely compact instruction set and imposes no restrictions on the implemented TRSs. Apart from standard

  16. A "Living" Machine

    Institute of Scientific and Technical Information of China (English)

    N.R.Bogatyrev

    2004-01-01

    Biomimetics (or bionics) is the engineering discipline that constructs artificial systems using biological principles. The ideal final result in biomimetics is to create a living machine. But what are the desirable and non-desirable properties of biomimetic product? Where can natural prototypes be found? How can technical solutions be transferred from nature to technology? Can we use living nature like LEGO bricks for construction our machines? How can biology help us? What is a living machine? In biomimetic practice only some "part" (organ, part of organ, tissue) of the observed whole organism is utilized. A possible template for future super-organism extension for biomimetic methods might be drawn from experiments in holistic ecological agriculture (ecological design, permaculture, ecological engineering, etc. ). The necessary translation of these rules to practical action can be achieved with the Russian Theory of Inventive Problem Solving (TRIZ), specifically adjusted to biology. Thus, permaculture, reinforced by a TRIZ conceptual framework, might provide the basis for Super-Organismic Bionics, which is hypothesized as necessary for effective ecological engineering. This hypothesis is supported by a case study-the design of a sustainable artificial nature reserve for wild pollinators as a living machine.

  17. Of machines and men ...

    CERN Multimedia

    CERN; Daniel Boileau

    1990-01-01

    Engineering and construction at LEP. Committed work and physicists motivation to work on this type of machine. With Guido Altarelli Theory Division Physicist, Ugo Amaldi Delphi Experiment Spokesman, Oscar Barbalat Head of Industry and Technology Liaison Office, Jonathan Ellis Head of Theory Division.

  18. Technology Time Machine 2012

    DEFF Research Database (Denmark)

    Lehner, Wolfgang; Fettweis, Gerhard; Fitzek, Frank

    2013-01-01

    The IEEE Technology Time Machine (TTM) is a unique event for industry leaders, academics, and decision making government officials who direct R&D activities, plan research programs or manage portfolios of research activities. This report covers the main topics of the 2nd Symposium of future...

  19. Training Restricted Boltzmann Machines

    DEFF Research Database (Denmark)

    Fischer, Asja

    Restricted Boltzmann machines (RBMs) are probabilistic graphical models that can also be interpreted as stochastic neural networks. Training RBMs is known to be challenging. Computing the likelihood of the model parameters or its gradient is in general computationally intensive. Thus, training...

  20. Laser machining of explosives

    Science.gov (United States)

    Perry, Michael D.; Stuart, Brent C.; Banks, Paul S.; Myers, Booth R.; Sefcik, Joseph A.

    2000-01-01

    The invention consists of a method for machining (cutting, drilling, sculpting) of explosives (e.g., TNT, TATB, PETN, RDX, etc.). By using pulses of a duration in the range of 5 femtoseconds to 50 picoseconds, extremely precise and rapid machining can be achieved with essentially no heat or shock affected zone. In this method, material is removed by a nonthermal mechanism. A combination of multiphoton and collisional ionization creates a critical density plasma in a time scale much shorter than electron kinetic energy is transferred to the lattice. The resulting plasma is far from thermal equilibrium. The material is in essence converted from its initial solid-state directly into a fully ionized plasma on a time scale too short for thermal equilibrium to be established with the lattice. As a result, there is negligible heat conduction beyond the region removed resulting in negligible thermal stress or shock to the material beyond a few microns from the laser machined surface. Hydrodynamic expansion of the plasma eliminates the need for any ancillary techniques to remove material and produces extremely high quality machined surfaces. There is no detonation or deflagration of the explosive in the process and the material which is removed is rendered inert.

  1. Electrical Discharge Machining.

    Science.gov (United States)

    Montgomery, C. M.

    The manual is for use by students learning electrical discharge machining (EDM). It consists of eight units divided into several lessons, each designed to meet one of the stated objectives for the unit. The units deal with: introduction to and advantages of EDM, the EDM process, basic components of EDM, reaction between forming tool and workpiece,…

  2. The Answer Machine.

    Science.gov (United States)

    Feldman, Susan

    2000-01-01

    Discusses information retrieval systems and the need to have them adapt to user needs, integrate information in any format, reveal patterns and trends in information, and answer questions. Topics include statistics and probability; natural language processing; intelligent agents; concept mapping; machine-aided indexing; text mining; filtering;…

  3. Massively collaborative machine learning

    NARCIS (Netherlands)

    Rijn, van J.N.

    2016-01-01

    Many scientists are focussed on building models. We nearly process all information we perceive to a model. There are many techniques that enable computers to build models as well. The field of research that develops such techniques is called Machine Learning. Many research is devoted to develop comp

  4. Recent Advances on Permanent Magnet Machines

    Institute of Scientific and Technical Information of China (English)

    诸自强

    2012-01-01

    This paper overviews advances on permanent magnet(PM) brushless machines over last 30 years,with particular reference to new and novel machine topologies.These include current states and trends for surface-mounted and interior PM machines,electrically and mechanically adjusted variable flux PM machines including memory machine,hybrid PM machines which uniquely integrate PM technology into induction machines,switched and synchronous reluctance machines and wound field machines,Halbach PM machines,dual-rotor PM machines,and magnetically geared PM machines,etc.The paper highlights their features and applications to various market sectors.

  5. Motherhood and the Machine

    Directory of Open Access Journals (Sweden)

    Miglena Nikolchina

    2014-12-01

    Full Text Available In her conceptualization of the human as defined by the capacity for revolt Kristeva unavoidably touches upon issues of robotization, technology, and the virtual. The concepts of animal and machine, however, although they do appear occasionally and in important ways, are never at the focus of her inquiries and are absent in her “New Forms of Revolt.” Yet these two concepts to a large extent define the field of contemporary philosophical debates of the human giving rise to three major theoretical orientations. On the one hand, there is the trend which tries to come to terms with technological novelties and the merging of human and machine that they imply. This trend unfolds under the rubric of “transhuman” or “posthuman” and of the “enhancement” of man. The second trend predominates in animal studies. Mostly in an ethical perspective but also ontologically, this trend, to which Derrida’s later writing made a significant contribution, questions the idea of the “human exception” and the rigorous distinction between man and animal on which this exception rests. While apparently antagonistic, both trends align the human with the animal and oppose it to technology. The third trend collapses the distinctions on which the previous two rely through the lens of biopolitics: drawing on Heidegger, Kojève, and Foucault, it regards contemporary technological transformations as amounting to the animalization of man.  The human disappears in the animal, in the machine, or in the indistinguishability of the two, confirming what Agamben has described as the inoperativeness of the anthropological machine. The present text turns to Kristeva’s conceptions of motherhood and revolt as introducing a powerful inflection in this tripartite field. Remarkably, it is precisely new sagas of rebellious machines like Battlestar “Galactica” that foreground the relevance of Kristeva’s approach.

  6. CENTEC: Center for Excellence in Neuroergonomics, Technology, and Cognition

    Science.gov (United States)

    2016-10-26

    Hamilton, G. Ascoli, et al. (2013). Machine-readable hippocampal neuron properties. Neuroinformatics Conf., Stockholm, Sweden . D. Hamilton, G. Ascoli...Romigh, G., Baldwin, C. L. & Simpson, B. (2013). Spatial attention in an auditory dual task. (June, 2013: Sweden ). Proceedings of the Cognitive...task. Published Abstract in the Proceedings of the Cognitive Hearing Sciences Conference. (June, 2013: Sweden ). Kennedy, W. G. (2010). Towards

  7. Machine learning in image steganalysis

    CERN Document Server

    Schaathun, Hans Georg

    2012-01-01

    "The only book to look at steganalysis from the perspective of machine learning theory, and to apply the common technique of machine learning to the particular field of steganalysis; ideal for people working in both disciplines"--

  8. 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...

  9. 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...

  10. Hinged Shields for Machine Tools

    Science.gov (United States)

    Lallande, J. B.; Poland, W. W.; Tull, S.

    1985-01-01

    Flaps guard against flying chips, but fold away for tool setup. Clear plastic shield in position to intercept flying chips from machine tool and retracted to give operator access to workpiece. Machine shops readily make such shields for own use.

  11. Visual cognition

    Energy Technology Data Exchange (ETDEWEB)

    Pinker, S.

    1985-01-01

    This book consists of essays covering issues in visual cognition presenting experimental techniques from cognitive psychology, methods of modeling cognitive processes on computers from artificial intelligence, and methods of studying brain organization from neuropsychology. Topics considered include: parts of recognition; visual routines; upward direction; mental rotation, and discrimination of left and right turns in maps; individual differences in mental imagery, computational analysis and the neurological basis of mental imagery: componental analysis.

  12. Knowledge in formation: The machine-modeled frame of mind

    Energy Technology Data Exchange (ETDEWEB)

    Shore, B.

    1996-12-31

    Artificial Intelligence researchers have used the digital computer as a model for the human mind in two different ways. Most obviously, the computer has been used as a tool on which simulations of thinking-as-programs are developed and tested. Less obvious, but of great significance, is the use of the computer as a conceptual model for the human mind. This essay traces the sources of this machine-modeled conception of cognition in a great variety of social institutions and everyday experienced treating them as {open_quotes}cultural models{close_quotes} which have contributed to the naturalness of The mine-as-machine paradigm for many Americans. The roots of these models antedate the actual development of modern computers, and take the form of a {open_quotes}modularity schema{close_quotes} that has shaped the cultural and cognitive landscape of modernity. The essay concludes with a consideration of some of the cognitive consequences of this extension of machine logic into modern life, and proposes an important distinction between information processing models of thought and meaning-making in how human cognition is conceptualized.

  13. COGNITIVE ECONOMICS

    Science.gov (United States)

    KIMBALL, MILES

    2017-01-01

    Cognitive economics is the economics of what is in people’s minds. It is a vibrant area of research (much of it within behavioural economics, labour economics and the economics of education) that brings into play novel types of data, especially novel types of survey data. Such data highlight the importance of heterogeneity across individuals and highlight thorny issues for welfare economics. A key theme of cognitive economics is finite cognition (often misleadingly called “bounded rationality”), which poses theoretical challenges that call for versatile approaches. Cognitive economics brings a rich toolbox to the task of understanding a complex world. PMID:28149186

  14. Design of Sugarcane Peeling Machine

    Directory of Open Access Journals (Sweden)

    Ge Xinfeng

    2015-02-01

    Full Text Available In order to solve the problem that appeared in hand peeling sugarcane, the sugarcane peeling machine is designed, the sugarcane peeling machine includes motor, groove wheel, cutting room, slider crank mechanism, reducer (including belt drive, chain drive and so on. The designed sugarcane peeling machine is simulated, the results show that the sugarcane peeling machine can peel sugarcane successfully with convenient, fast and uniform.

  15. Automatically-Programed Machine Tools

    Science.gov (United States)

    Purves, L.; Clerman, N.

    1985-01-01

    Software produces cutter location files for numerically-controlled machine tools. APT, acronym for Automatically Programed Tools, is among most widely used software systems for computerized machine tools. APT developed for explicit purpose of providing effective software system for programing NC machine tools. APT system includes specification of APT programing language and language processor, which executes APT statements and generates NC machine-tool motions specified by APT statements.

  16. Automatically-Programed Machine Tools

    Science.gov (United States)

    Purves, L.; Clerman, N.

    1985-01-01

    Software produces cutter location files for numerically-controlled machine tools. APT, acronym for Automatically Programed Tools, is among most widely used software systems for computerized machine tools. APT developed for explicit purpose of providing effective software system for programing NC machine tools. APT system includes specification of APT programing language and language processor, which executes APT statements and generates NC machine-tool motions specified by APT statements.

  17. Feature Recognition for Virtual Machining

    OpenAIRE

    Xú, Shixin; Anwer, Nabil; Qiao, Lihong

    2014-01-01

    International audience; Virtual machining uses software tools to simulate machining processes in virtual environments ahead of actual production. This paper proposes that feature recognition techniques can be applied in the course of virtual machining, such as identifying some process problems, and presenting corresponding correcting advices. By comparing with the original CAD model, form errors of the machining features can be found. And then corrections are suggested to process designers. T...

  18. The Neural Support Vector Machine

    NARCIS (Netherlands)

    Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus

    2013-01-01

    This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a

  19. The Neural Support Vector Machine

    NARCIS (Netherlands)

    Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus

    2013-01-01

    This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a centr

  20. Prediction of Machine Tool Condition Using Support Vector Machine

    Science.gov (United States)

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

    2011-07-01

    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.

  1. Capturing Cognitive Processing Time for Active Authentication

    Science.gov (United States)

    2014-02-01

    Description Physical biometrics relies on physical characteristics, such as fingerprints or retinal patterns. The behavioral biometric of keystroke...cognitive fingerprint for continuous authentication. Its effectiveness has been verified through a campus-wide experiment at Iowa State University...typing rhythm (CTR), Support Vector Machine (SVM), Behavioral Biometrics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF

  2. A Boltzmann machine for the organization of intelligent machines

    Science.gov (United States)

    Moed, Michael C.; Saridis, George N.

    1989-01-01

    In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved

  3. Engineering molecular machines

    Science.gov (United States)

    Erman, Burak

    2016-04-01

    Biological molecular motors use chemical energy, mostly in the form of ATP hydrolysis, and convert it to mechanical energy. Correlated thermal fluctuations are essential for the function of a molecular machine and it is the hydrolysis of ATP that modifies the correlated fluctuations of the system. Correlations are consequences of the molecular architecture of the protein. The idea that synthetic molecular machines may be constructed by designing the proper molecular architecture is challenging. In their paper, Sarkar et al (2016 New J. Phys. 18 043006) propose a synthetic molecular motor based on the coarse grained elastic network model of proteins and show by numerical simulations that motor function is realized, ranging from deterministic to thermal, depending on temperature. This work opens up a new range of possibilities of molecular architecture based engine design.

  4. Boosting Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Elkin Eduardo García Díaz

    2006-11-01

    Full Text Available En este artículo, se presenta un algoritmo de clasificación binaria basado en Support Vector Machines (Máquinas de Vectores de Soporte que combinado apropiadamente con técnicas de Boosting consigue un mejor desempeño en cuanto a tiempo de entrenamiento y conserva características similares de generalización con un modelo de igual complejidad pero de representación más compacta./ In this paper we present an algorithm of binary classification based on Support Vector Machines. It is combined with a modified Boosting algorithm. It run faster than the original SVM algorithm with a similar generalization error and equal complexity model but it has more compact representation.

  5. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  6. Introduction to Machine Protection

    CERN Document Server

    Schmidt, R

    2016-01-01

    Protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent, although there was one paper that discussed beam-induced damage for the SLAC linac (Stanford Linear Accelerator Center) as early as in 1967. It is related to the increasing beam power of high-power proton accelerators, to the emission of synchrotron light by electron-positron accelerators and to the increase of energy stored in the beam. Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping ...

  7. Technological requirements of profile machining

    Institute of Scientific and Technical Information of China (English)

    PARK Sangchul; CHUNG Yunchan

    2006-01-01

    The term ‘profile machining’is used to refer to the milling of vertical surfaces described by profile curves. Profile machining requires higher precision (1/1000 mm) than regular 3D machining (1/100 mm) with the erosion of sharp vertices should being especially avoided. Although, profile machining is very essential for making trimming and flangedies, it seldom brought into focus. This paper addresses the technological requirements of profile machining including machining width and depth control,minimizing toolware, and protecting sharp vertices. Issues of controller alarms are also addressed.

  8. Machining fiber-reinforced composites

    Science.gov (United States)

    Komanduri, Ranga

    1993-04-01

    Compared to high tool wear and high costs of tooling of fiber-reinforced composites (FRCs), noncontact material-removal processes offer attractive alternative. Noncontact machining methods can also minimize dust, noise, and extensive plastic deformation and consequent heat generation associated with conventional machining of FRCs, espacially those with an epoxy matrix. The paper describes the principles involved in and the details of machining of FRCs by laser machining, water jet-cutting and abrasive water jet-cutting, and electrical discharge machining of composites, as well as the limitations of each method.

  9. Future database machine architectures

    OpenAIRE

    Hsiao, David K.

    1984-01-01

    There are many software database management systems available on many general-purpose computers ranging from micros to super-mainframes. Database machines as backened computers can offload the database management work from the mainframe so that we can retain the same mainframe longer. However, the database backend must also demonstrate lower cost, higher performance, and newer functionality. Some of the fundamental architecture issues in the design of high-performance and great-capacity datab...

  10. Machine Learning at Scale

    OpenAIRE

    Izrailev, Sergei; Stanley, Jeremy M.

    2014-01-01

    It takes skill to build a meaningful predictive model even with the abundance of implementations of modern machine learning algorithms and readily available computing resources. Building a model becomes challenging if hundreds of terabytes of data need to be processed to produce the training data set. In a digital advertising technology setting, we are faced with the need to build thousands of such models that predict user behavior and power advertising campaigns in a 24/7 chaotic real-time p...

  11. Cost of photochemical machining

    OpenAIRE

    Roy, Rajkumar; Allen, David; Zamora, Oscar

    2004-01-01

    Photochemical machining (PCM), also known as photoetching, photofabrication or photochemical milling, is a non-traditional manufacturing method based on the combination of photoresist imaging and chemical etching. PCM uses techniques similar to those employed for the production of printed circuit boards and silicon integrated circuits. The PCM industry plays a valuable worldwide role in the production of metal precision parts and decorative items. Parts produced by PCM are t...

  12. Austempered Ductile Iron Machining

    Science.gov (United States)

    Pilc, Jozef; Šajgalík, Michal; Holubják, Jozef; Piešová, Marianna; Zaušková, Lucia; Babík, Ondrej; Kuždák, Viktor; Rákoci, Jozef

    2015-12-01

    This article deals with the machining of cast iron. In industrial practice, Austempered Ductile Iron began to be used relatively recently. ADI is ductile iron that has gone through austempering to get improved properties, among which we can include strength, wear resistance or noise damping. This specific material is defined also by other properties, such as high elasticity, ductility and endurance against tenigue, which are the properties, that considerably make the tooling characteristic worse.

  13. Quantum Virtual Machine (QVM)

    Energy Technology Data Exchange (ETDEWEB)

    2016-11-18

    There is a lack of state-of-the-art HPC simulation tools for simulating general quantum computing. Furthermore, there are no real software tools that integrate current quantum computers into existing classical HPC workflows. This product, the Quantum Virtual Machine (QVM), solves this problem by providing an extensible framework for pluggable virtual, or physical, quantum processing units (QPUs). It enables the execution of low level quantum assembly codes and returns the results of such executions.

  14. Agent Based Computing Machine

    Science.gov (United States)

    2005-12-09

    be used in Phase 2 to accomplish the following enhancements. Due to the speed and support of MPI for C/C++ on Beowulf clusters , these languages could...1.7 ABC Machine Formal Definition 24 1.8 Computational Analysis 31 1.9 Programming Concepts 34 1.10 Cluster Mapping 38 1.11 Phase 1 Results 43 2...options for hardware implementation are explored including an emulation with a high performance cluster , a high performance silicon chip and the

  15. Magnetic Electrochemical Finishing Machining

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    How to improve the finishing efficiency and surface roughness have been all along the objective of research in electrochemical polishing. However, the research activity, i.e. during electrochemical polishing, directly introduce the magnetic field to study how the magnetic field influences on the finishing efficiency, quality and the electrochemical process in the field of finishing machining technology, is insufficient. When introducing additional magnetic field in the traditional electrochemical pol...

  16. FMS precision machining

    Energy Technology Data Exchange (ETDEWEB)

    Burnham, M.W.

    1980-01-01

    In evaluating the technical obstacles and accuracy limits to producing a Precision Flexible Manufacturing System, a current system is subjected to an error budget analysis. It is noted that to make complex part geometries with tolerances in the lower thousandths range, machining to tenths is required for process control. Actual parts made to tenths are illustrated, along with a discussion of the requirements for automation and for process control.

  17. Machine on Trial

    Science.gov (United States)

    2012-06-01

    front of the Judge, how did we come to justify the ethical use of such a machine? The Judge called for a recess so that he could further educate ...commerce, where money would change hands, or for the purposes of controlling critical systems.”29 The initial group that set up the ARPANET did not... EBook of Fundamental Principals of the Metaphysic of Morals, May, 2004 [ EBook #5682 translated by Thomas Kingsmill Abbott, 12. http://manybooks.net

  18. Visual cognition

    Energy Technology Data Exchange (ETDEWEB)

    Pinker, S.

    1985-01-01

    This collection of research papers on visual cognition first appeared as a special issue of Cognition: International Journal of Cognitive Science. The study of visual cognition has seen enormous progress in the past decade, bringing important advances in our understanding of shape perception, visual imagery, and mental maps. Many of these discoveries are the result of converging investigations in different areas, such as cognitive and perceptual psychology, artificial intelligence, and neuropsychology. This volume is intended to highlight a sample of work at the cutting edge of this research area for the benefit of students and researchers in a variety of disciplines. The tutorial introduction that begins the volume is designed to help the nonspecialist reader bridge the gap between the contemporary research reported here and earlier textbook introductions or literature reviews.

  19. Electrochemical Discharge Machining Process

    Directory of Open Access Journals (Sweden)

    Anjali V. Kulkarni

    2007-09-01

    Full Text Available Electrochemical discharge machining process is evolving as a promising micromachiningprocess. The experimental investigations in the present work substantiate this trend. In the presentwork, in situ, synchronised, transient temperature and current measurements have been carriedout. The need for the transient measurements arose due to the time-varying nature of the dischargeformation and time varying circuit current. Synchronised and transient measurements revealedthe discrete nature of the process. It also helped in formulating the basic mechanism for thedischarge formation and the material removal in the process. Temperature profile on workpieceand in electrochemical discharge machining cell is experimentally measured using pyrometer,and two varieties of K-type thermocouples. Surface topography of the discharge-affected zoneson the workpiece has been carried out using scanning electron microscope. Measurements andsurface topographical studies reveal the potential use of this process for machining in micronregime. With careful experimental set-up design, suitable supply voltage and its polarity, theprocess can be applied for both micromachining and micro-deposition. It can be extended formachining and or deposition of wide range of materials.

  20. Introduction: Minds, Bodies, Machines

    Directory of Open Access Journals (Sweden)

    Deirdre Coleman

    2008-10-01

    Full Text Available This issue of 19 brings together a selection of essays from an interdisciplinary conference on 'Minds, Bodies, Machines' convened last year by Birkbeck's Centre for Nineteenth-Century Studies, University of London, in partnership with the English programme, University of Melbourne and software developers Constraint Technologies International (CTI. The conference explored the relationship between minds, bodies and machines in the long nineteenth century, with a view to understanding the history of our technology-driven, post-human visions. It is in the nineteenth century that the relationship between the human and the machine under post-industrial capitalism becomes a pervasive theme. From Blake on the mills of the mind by which we are enslaved, to Carlyle's and Arnold's denunciation of the machinery of modern life, from Dickens's sooty fictional locomotive Mr Pancks, who 'snorted and sniffed and puffed and blew, like a little labouring steam-engine', and 'shot out […]cinders of principles, as if it were done by mechanical revolvency', to the alienated historical body of the late-nineteenth-century factory worker under Taylorization, whose movements and gestures were timed, regulated and rationalised to maximize efficiency; we find a cultural preoccupation with the mechanisation of the nineteenth-century human body that uncannily resonates with modern dreams and anxieties around technologies of the human.

  1. Machine Learning in Medicine.

    Science.gov (United States)

    Deo, Rahul C

    2015-11-17

    Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games - tasks that would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in health care. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades, and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus, part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome.

  2. Behind the machines

    CERN Document Server

    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 ...

  3. The Use of Machine Aids in Dynamic Multi-Task Environments: A Comparison of an Optimal Model to Human Behavior.

    Science.gov (United States)

    1982-06-01

    advantage . Unproductive machines, however, were used far more frequently than indicated by the optimal model. Increasing the cost of using machines was...found to have a greater inhibiting effect on their use than did de-creasing machine productivity. SECURITY CLASSIFICATION OF THIS PAQE(Vhm’ Date Bnb .,e@V...and the method used to deal with it. The cognitive interface is like the storm front between a warm air mass and a cold air mass. Both are described as

  4. 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...

  5. 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...... determines communication process largely, our data indicates communication relies more on a dynamic process where participants establish common ground than on reproducibility and grammatical accuracy.......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...

  6. Cognitive Performance and Cognitive Style.

    Science.gov (United States)

    International Journal of Behavioral Development, 1985

    1985-01-01

    Investigates (1) the relationships between cognitive performance and cognitive styles and predictive possibilities and (2) performance differences by sex, school, grade, and income in 92 Indian adolescents. Assessment measures included Liquid Conservation, Islands, Goat-Lion, Hanoi-Tower, Rabbits (Piagetian); Block Design (WISC-R); Paper Cutting…

  7. Enabling Technologies for Cognitive Optical Networks

    DEFF Research Database (Denmark)

    Borkowski, Robert

    to technologies required for their implementation. Operation of CON-enabling machine learning methods is tested experimentally and DSP-based OPM techniques for software-defined receivers are introduced and verified. The presented set of technologies forms a foundation, upon which next generation fiber-optic data......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...

  8. Cognitive Neuropsychology

    DEFF Research Database (Denmark)

    Starrfelt, Randi

    2012-01-01

    Traditionally, studies in cognitive neuropsychology have reported single cases or small groups of patients with seemingly selective impairments of specific cognitive processes or modules. Many studies, particularly older ones, have used simple and coarse tasks to show that patients are disproport......Traditionally, studies in cognitive neuropsychology have reported single cases or small groups of patients with seemingly selective impairments of specific cognitive processes or modules. Many studies, particularly older ones, have used simple and coarse tasks to show that patients...... for cognitive neuropsychology are opened up. The questions addressed in this symposium is whether the questions posed by cognitive neuropsychology are still relevant, and whether new methods can spark a new interest in the field, or if the time has passed when the observation of single and double dissociations...... in patients’ test performance can inform theories of (normal) cognitive function. In four talks, this symposium will present and discuss methods for investigating impairment patterns in neuropsychological patients: 1) a talk on basic assumptions and statistical methods in single case methodology; 2) a talk...

  9. 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.

  10. Humans and Machines in the Evolution of AI in Korea

    OpenAIRE

    Zhang, Byoung-Tak; Seoul National University

    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...

  11. Mineral mining machines

    Energy Technology Data Exchange (ETDEWEB)

    Mc Gaw, B.H.

    1984-01-01

    A machine for mining minerals is patented. It is a cutter loader with a drum actuating element of the worm type equipped with a multitude of cutting teeth reinforced with tungsten carbide. A feature of the patented machine is that all of the cutting teeth and holders on the drum have the identical design. This is achieved through selecting a slant angle for the cutting teeth which is the mean between the slant angle of the conventional radial teeth and the slant angle of the advance teeth. This, in turn, is provided thanks to the corresponding slant of the holders relative to the drum and (or) the slant of the cutting part of the teeth relative to their stems. Thus, the advance teeth projecting beyond the surface of the drum on the face side and providing upper and lateral clearances have the same angle of attack as the radial teeth, that is, from 20 to 35 degrees. A series of modifications of the cutting teeth is patented. One of the designs allows the cutting tooth to occupy a varying position relative to the drum, from the conventional vertical to an inverted, axially projecting position. In the last case the tooth in the extraction process provides the upper and lateral clearances for the drum on the face side. Among the different modifications of the cutting teeth, a design is proposed which provides for the presence of a stem which is shaped like a truncated cone. This particular stem is designed for use jointly with a wedge which unfastens the teeth and is placed in a holder. The latter is completed in a transverse slot thanks to which the rear end of the stem is compressed, which simplifies replacement of a tooth. Channels are provided in the patented machine for feeding water to the worm spiral, the holders and the cutting teeth themselves in order to deal with dust.

  12. 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.

  13. Embodying cognition

    DEFF Research Database (Denmark)

    Martiny, Kristian Møller Moltke; Aggerholm, Kenneth

    2016-01-01

    During the last decades, research on cognition has undergone a reformation, which is necessary to take into account when evaluating the cognitive and behavioural aspects of therapy. This reformation is due to the research programme called Embodied Cognition (EC). Although EC may have become...... the theoretical authority in current cognitive science, there are only sporadic examples of EC-based therapy, and no established framework. We aim to build such a framework on the aims, methods and techniques of the current third-wave of CBT. There appears to be a possibility for cross-fertilization between EC...... and CBT that could contribute to the development of theory and practice for both of them. We present a case-study of an EC-based model of intervention for working with self-control in cerebral palsy.We centre the results of the study and its discussion on how we should understand and work with self...

  14. Spatial cognition

    Science.gov (United States)

    Kaiser, Mary Kister; Remington, Roger

    1988-01-01

    Spatial cognition is the ability to reason about geometric relationships in the real (or a metaphorical) world based on one or more internal representations of those relationships. The study of spatial cognition is concerned with the representation of spatial knowledge, and our ability to manipulate these representations to solve spatial problems. Spatial cognition is utilized most critically when direct perceptual cues are absent or impoverished. Examples are provided of how human spatial cognitive abilities impact on three areas of space station operator performance: orientation, path planning, and data base management. A videotape provides demonstrations of relevant phenomena (e.g., the importance of orientation for recognition of complex, configural forms). The presentation is represented by abstract and overhead visuals only.

  15. Cognitive Changes

    Science.gov (United States)

    ... decline tend to occur in parallel as the disease progresses. Significant cognitive impairment in PD is often associated with: Caregiver distress Worse day-to-day function Diminished quality of life Poorer treatment outcomes Greater medical costs due to ...

  16. Cognitive remission

    DEFF Research Database (Denmark)

    Bortolato, Beatrice; Miskowiak, Kamilla W; Köhler, Cristiano A

    2016-01-01

    dysfunction in MDD. Several other novel agents may be repurposed as cognitive enhancers for MDD treatment, including minocycline, insulin, antidiabetic agents, angiotensin-converting enzyme inhibitors, S-adenosyl methionine, acetyl-L-carnitine, alpha lipoic acid, omega-3 fatty acids, melatonin, modafinil......BACKGROUND: Cognitive dysfunction in major depressive disorder (MDD) encompasses several domains, including but not limited to executive function, verbal memory, and attention. Furthermore, cognitive dysfunction is a frequent residual manifestation in depression and may persist during the remitted...... phase. Cognitive deficits may also impede functional recovery, including workforce performance, in patients with MDD. The overarching aims of this opinion article are to critically evaluate the effects of available antidepressants as well as novel therapeutic targets on neurocognitive dysfunction in MDD...

  17. Diamond Measuring Machine

    Energy Technology Data Exchange (ETDEWEB)

    Krstulic, J.F.

    2000-01-27

    The fundamental goal of this project was to develop additional capabilities to the diamond measuring prototype, work out technical difficulties associated with the original device, and perform automated measurements which are accurate and repeatable. For this project, FM and T was responsible for the overall system design, edge extraction, and defect extraction and identification. AccuGem provided a lab and computer equipment in Lawrence, 3D modeling, industry expertise, and sets of diamonds for testing. The system executive software which controls stone positioning, lighting, focusing, report generation, and data acquisition was written in Microsoft Visual Basic 6, while data analysis and modeling were compiled in C/C++ DLLs. All scanning parameters and extracted data are stored in a central database and available for automated analysis and reporting. The Phase 1 study showed that data can be extracted and measured from diamond scans, but most of the information had to be manually extracted. In this Phase 2 project, all data required for geometric modeling and defect identification were automatically extracted and passed to a 3D modeling module for analysis. Algorithms were developed which automatically adjusted both light levels and stone focus positioning for each diamond-under-test. After a diamond is analyzed and measurements are completed, a report is printed for the customer which shows carat weight, summarizes stone geometry information, lists defects and their size, displays a picture of the diamond, and shows a plot of defects on a top view drawing of the stone. Initial emphasis of defect extraction was on identification of feathers, pinpoints, and crystals. Defects were plotted color-coded by industry standards for inclusions (red), blemishes (green), and unknown defects (blue). Diamonds with a wide variety of cut quality, size, and number of defects were tested in the machine. Edge extraction, defect extraction, and modeling code were tested for

  18. Tribology in machine design

    CERN Document Server

    Stolarski, T A

    1990-01-01

    Tribology in Machine Design aims to promote a better appreciation of the increasingly important role played by tribology at the design stage in engineering. This book shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications. The concept of tribodesign is introduced in Chapter 1. Chapter 2 is devoted to a brief discussion of the basic principles of tribology, including some concepts and models of lubricated wear and friction under complex kinematic conditions. Elements of contact mechanics, presented in Chapter 3, are confined to the

  19. Quantum adiabatic machine learning

    CERN Document Server

    Pudenz, Kristen L

    2011-01-01

    We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we adiabatically evolve one or more strong classifiers on a superposition of inputs in order to find certain anomalous elements in the classification space. Both the training and testing phases are executed via quantum adiabatic evolution. We apply and illustrate this approach in detail to the problem of software verification and validation.

  20. Daphne machine project

    Energy Technology Data Exchange (ETDEWEB)

    Vignola, G. and Daphne Project Team [Istituto Nazionale di Fisica Nucleare, Frascati (Italy)

    1996-07-01

    Daphne, a high luminosity e{sup +}/e{sup -} {Phi} factory, is presently under construction in Frascati. The beginning of the collider commissioning is scheduled by winter 1997, with a short term luminosity goal L=1.3 10{sup 32} cm{sup -2} sec{sup -1}. Daphne shall be the first of the new generation of very high luminosity colliders, called factories, to come in operation. Other factories under construction are PEP-II and KEK-B: first collision, for both machines, is planned for 1998.

  1. CENTRIFUGAL CASTING MACHINE

    Science.gov (United States)

    Shuck, A.B.

    1958-04-01

    A device is described that is specifically designed to cast uraniumn fuel rods in a vacuunn, in order to obtain flawless, nonoxidized castings which subsequently require a maximum of machining or wastage of the expensive processed material. A chamber surrounded with heating elements is connected to the molds, and the entire apparatus is housed in an airtight container. A charge of uranium is placed in the chamber, heated, then is allowed to flow into the molds While being rotated. Water circulating through passages in the molds chills the casting to form a fine grained fuel rod in nearly finished form.

  2. Electrical machines with Matlab

    CERN Document Server

    Gonen, Turan

    2011-01-01

    Basic ConceptsDistribution SystemImpact of Dispersed Storage and GenerationBrief Overview of Basic Electrical MachinesReal and Reactive Powers in Single-Phase AC CircuitsThree-Phase CircuitsThree-Phase SystemsUnbalanced Three-Phase LoadsMeasurement of Average Power in Three-Phase CircuitsPower Factor CorrectionMagnetic CircuitsMagnetic Field of Current-Carrying ConductorsAmpère's Magnetic Circuital LawMagnetic CircuitsMagnetic Circuit with Air GapBrief Review of FerromagnetismMagnetic Core LossesHow to Determine Flux for a Given MMFPermanent MagnetsTransformersTransformer ConstructionBrief Rev

  3. Cognitive Robotics

    OpenAIRE

    Levesque, Hector J.; Lakemeyer, Gerhard

    2010-01-01

    This chapter is dedicated to the memory of Ray Reiter. It is also an overview of cognitive robotics, as we understand it to have been envisaged by him.1 Of course, nobody can control the use of a term or the direction of research. We apologize in advance to those who feel that other approaches to cognitive robotics and related problems are inadequately represented here.

  4. Cognitive Linguistics

    OpenAIRE

    Nyord, Rune

    2015-01-01

    Cognitive linguistics is an influential branch of linguistics, which has played an increasing role in different areas of Egyptology over the last couple of decades. Concepts from cognitive linguistics have been especially influential in the study of determinatives/classifiers in the hieroglyphic script, but they have also proven useful to elucidate a number of other questions, both narrowly linguistic and more broadly cultural historical.

  5. 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...

  6. Learning thermodynamics with Boltzmann machines

    Science.gov (United States)

    Torlai, Giacomo; Melko, Roger G.

    2016-10-01

    A Boltzmann machine is a stochastic neural network that has been extensively used in the layers of deep architectures for modern machine learning applications. In this paper, we develop a Boltzmann machine that is capable of modeling thermodynamic observables for physical systems in thermal equilibrium. Through unsupervised learning, we train the Boltzmann machine on data sets constructed with spin configurations importance sampled from the partition function of an Ising Hamiltonian at different temperatures using Monte Carlo (MC) methods. The trained Boltzmann machine is then used to generate spin states, for which we compare thermodynamic observables to those computed by direct MC sampling. We demonstrate that the Boltzmann machine can faithfully reproduce the observables of the physical system. Further, we observe that the number of neurons required to obtain accurate results increases as the system is brought close to criticality.

  7. 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.

  8. 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.

  9. 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....

  10. Stacked Extreme Learning Machines.

    Science.gov (United States)

    Zhou, Hongming; Huang, Guang-Bin; Lin, Zhiping; Wang, Han; Soh, Yeng Chai

    2015-09-01

    Extreme learning machine (ELM) has recently attracted many researchers' interest due to its very fast learning speed, good generalization ability, and ease of implementation. It provides a unified solution that can be used directly to solve regression, binary, and multiclass classification problems. In this paper, we propose a stacked ELMs (S-ELMs) that is specially designed for solving large and complex data problems. The S-ELMs divides a single large ELM network into multiple stacked small ELMs which are serially connected. The S-ELMs can approximate a very large ELM network with small memory requirement. To further improve the testing accuracy on big data problems, the ELM autoencoder can be implemented during each iteration of the S-ELMs algorithm. The simulation results show that the S-ELMs even with random hidden nodes can achieve similar testing accuracy to support vector machine (SVM) while having low memory requirements. With the help of ELM autoencoder, the S-ELMs can achieve much better testing accuracy than SVM and slightly better accuracy than deep belief network (DBN) with much faster training speed.

  11. 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

  12. Beam Transfer and Machine Protection

    CERN Document Server

    Kain, V

    2016-01-01

    Beam transfer, such as injection into or extraction from an accelerator, is one of the most critical moments in terms of machine protection in a high-intensity machine. Special equipment is used and machine protection aspects have to be taken into account in the design of the beam transfer concepts. A brief introduction of the principles of beam transfer and the equipment involved will be given in this lecture. The main concepts of machine protection for injection and extraction will be presented, with examples from the CERN SPS and LHC.

  13. Turing Automata and Graph Machines

    Directory of Open Access Journals (Sweden)

    Miklós Bartha

    2010-06-01

    Full Text Available Indexed monoidal algebras are introduced as an equivalent structure for self-dual compact closed categories, and a coherence theorem is proved for the category of such algebras. Turing automata and Turing graph machines are defined by generalizing the classical Turing machine concept, so that the collection of such machines becomes an indexed monoidal algebra. On the analogy of the von Neumann data-flow computer architecture, Turing graph machines are proposed as potentially reversible low-level universal computational devices, and a truly reversible molecular size hardware model is presented as an example.

  14. Offloading Cognition onto Cognitive Technology

    CERN Document Server

    Dror, Itiel

    2008-01-01

    "Cognizing" (i.e., thinking, understanding, knowing, and having the capacity to do what cognizers can do) is a mental state. Systems without mental states, such as cognitive technology, can sometimes also do some of what cognizers can do, but that does not make them cognizers. Cognitive technology allows cognizers to offload some of the functions they would otherwise have had to execute with their own brains and bodies alone; it also extends cognizers' performance powers beyond those of brains and bodies alone. Language itself is a form of cognitive technology that allows cognizers to offload some of their brain functions onto the brains of other cognizers. Language also extends cognizers' individual and joint performance powers, distributing the load through interactive and collaborative cognition. Reading, writing, print, telecommunications and computing further extend cognizers' capacities. And now the web, with its distributed network of cognizers, digital databases and sofware agents, has become the Cogn...

  15. Production Machine Shop Employment Competencies. Part Four: The Milling Machine.

    Science.gov (United States)

    Bishart, Gus; Werner, Claire

    Competencies for production machine shop are provided for the fourth of four topic areas: the milling machine. Each competency appears in a one-page format. It is presented as a goal statement followed by one or more "indicator" statements, which are performance objectives describing an ability that, upon attainment, will establish…

  16. Standardized Curriculum for Machine Tool Operation/Machine Shop.

    Science.gov (United States)

    Mississippi State Dept. of Education, Jackson. Office of Vocational, Technical and Adult Education.

    Standardized vocational education course titles and core contents for two courses in Mississippi are provided: machine tool operation/machine shop I and II. The first course contains the following units: (1) orientation; (2) shop safety; (3) shop math; (4) measuring tools and instruments; (5) hand and bench tools; (6) blueprint reading; (7)…

  17. Machine Reading as a Cognitive Science Research Instrument

    Science.gov (United States)

    2007-01-01

    plan to experiment with rumination processes (cf. Forbus et al 2007). To test the system’s ability to capture knowledge, we plan to feed it the...lump of clay is the same amount of stuff if it is rolled up versus spread out, and (c) that the volume of a liquid is preserved over pouring it from

  18. 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.

  19. 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...

  20. User image mismatch in anaesthesia alarms: a cognitive systems analysis.

    Science.gov (United States)

    Raymer, Karen E; Bergström, Johan

    2013-01-01

    In this study, principles of Cognitive Systems Engineering are used to better understand the human-machine interaction manifesting in the use of anaesthesia alarms. The hypothesis is that the design of the machine incorporates built-in assumptions of the user that are discrepant with the anaesthesiologist's self-assessment, creating 'user image mismatch'. Mismatch was interpreted by focusing on the 'user image' as described from the perspectives of both machine and user. The machine-embedded image was interpreted through document analysis. The user-described image was interpreted through user (anaesthesiologist) interviews. Finally, an analysis was conducted in which the machine-embedded and user-described images were contrasted to identify user image mismatch. It is concluded that analysing user image mismatch expands the focus of attention towards macro-elements in the interaction between man and machine. User image mismatch is interpreted to arise from complexity of algorithm design and incongruity between alarm design and tenets of anaesthesia practice. Cognitive system engineering principles are applied to enhance the understanding of the interaction between anaesthesiologist and alarm. The 'user image' is interpreted and contrasted from the perspectives of machine as well as the user. Apparent machine-user mismatch is explored pertaining to specific design features.

  1. Semantic Vector Machines

    CERN Document Server

    Vincent, Etter

    2011-01-01

    We first present our work in machine translation, during which we used aligned sentences to train a neural network to embed n-grams of different languages into an $d$-dimensional space, such that n-grams that are the translation of each other are close with respect to some metric. Good n-grams to n-grams translation results were achieved, but full sentences translation is still problematic. We realized that learning semantics of sentences and documents was the key for solving a lot of natural language processing problems, and thus moved to the second part of our work: sentence compression. We introduce a flexible neural network architecture for learning embeddings of words and sentences that extract their semantics, propose an efficient implementation in the Torch framework and present embedding results comparable to the ones obtained with classical neural language models, while being more powerful.

  2. Regularized maximum correntropy machine

    KAUST Repository

    Wang, Jim Jing-Yan

    2015-02-12

    In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

  3. Machine Learning Exciton Dynamics

    CERN Document Server

    Häse, Florian; Pyzer-Knapp, Edward; Aspuru-Guzik, Alán

    2015-01-01

    Obtaining the exciton dynamics of large photosynthetic complexes by using mixed quantum mechanics/molecular mechanics (QM/MM) is computationally demanding. We propose a machine learning technique, multi-layer perceptrons, as a tool to reduce the time required to compute excited state energies. With this approach we predict time-dependent density functional theory (TDDFT) excited state energies of bacteriochlorophylls in the Fenna-Matthews-Olson (FMO) complex. Additionally we compute spectral densities and exciton populations from the predictions. Different methods to determine multi-layer perceptron training sets are introduced, leading to several initial data selections. In addition, we compute spectral densities and exciton populations. Once multi-layer perceptrons are trained, predicting excited state energies was found to be significantly faster than the corresponding QM/MM calculations. We showed that multi-layer perceptrons can successfully reproduce the energies of QM/MM calculations to a high degree o...

  4. Training Restricted Boltzmann Machines

    DEFF Research Database (Denmark)

    Fischer, Asja

    Restricted Boltzmann machines (RBMs) are probabilistic graphical models that can also be interpreted as stochastic neural networks. Training RBMs is known to be challenging. Computing the likelihood of the model parameters or its gradient is in general computationally intensive. Thus, training...... relies on sampling based approximations of the log-likelihood gradient. I will present an empirical and theoretical analysis of the bias of these approximations and show that the approximation error can lead to a distortion of the learning process. The bias decreases with increasing mixing rate...... of the applied sampling procedure and I will introduce a transition operator that leads to faster mixing. Finally, a different parametrisation of RBMs will be discussed that leads to better learning results and more robustness against changes in the data representation....

  5. Mechanics of Wood Machining

    CERN Document Server

    Csanády, Etele

    2013-01-01

    Wood is one of the most valuable materials for mankind, and since our earliest days wood materials have been widely used. Today we have modern woodworking machine and tools; however, the raw wood materials available are continuously declining. Therefore we are forced to use this precious material more economically, reducing waste wherever possible. This new textbook on the “Mechanics of Wood Machining” combines the quantitative, mathematical analysis of the mechanisms of wood processing with practical recommendations and solutions. Bringing together materials from many sources, the book contains new theoretical and experimental approaches and offers a clear and systematic overview of the theory of wood cutting, thermal loading in wood-cutting tools, dynamic behaviour of tool and work piece, optimum choice of operational parameters and energy consumption, the wear process of the tools, and the general regularities of wood surface roughness. Diagrams are provided for the quick estimation of various process ...

  6. The Tractable Cognition thesis

    National Research Council Canada - National Science Library

    Rooij, I.J.E.I. van

    2008-01-01

    ...: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories of cognition...

  7. CREDITWORTHINESS OF MACHINE BUILDING ENTERPRISES

    OpenAIRE

    Freimanis, Tālis; Svarinskis, Leonārs

    2009-01-01

    The previous research showed that the Latvian machine building enterprises experienced regular liquidity problems at the end of each year. Therefore to ensure their development the constant access to bank credits is a necessity. For that reason the analysis and evaluation of machine building enterprises creditworthiness was performed.

  8. SOLVENCY OF MACHINE BUILDING ENTERPRISES

    OpenAIRE

    Freimanis, Tālis; Svarinskis, Leonārs

    2009-01-01

    Machine building as a competative exporting industry plays an important role in the Latvian national open market economy. The further development of machine building is possible under the conditions of the stable solvency. Therefore, it is crucial to perform the solvency analysis of the industry enterprises and give its evaluation.

  9. Storytelling machines for video search

    NARCIS (Netherlands)

    Habibian, A.

    2016-01-01

    We study a fundamental question for developing storytelling machines: what vocabulary is suited for machines to tell the story of a video? We start by manually specifying the vocabulary concepts and their annotations. In order to effectively handcraft the vocabulary, we empirically study what are

  10. Understanding and applying machine vision

    CERN Document Server

    Zeuch, Nello

    2000-01-01

    A discussion of applications of machine vision technology in the semiconductor, electronic, automotive, wood, food, pharmaceutical, printing, and container industries. It describes systems that enable projects to move forward swiftly and efficiently, and focuses on the nuances of the engineering and system integration of machine vision technology.

  11. Storytelling machines for video search

    NARCIS (Netherlands)

    Habibian, A.

    2016-01-01

    We study a fundamental question for developing storytelling machines: what vocabulary is suited for machines to tell the story of a video? We start by manually specifying the vocabulary concepts and their annotations. In order to effectively handcraft the vocabulary, we empirically study what are th

  12. Cleaning of Free Machining Brass

    Energy Technology Data Exchange (ETDEWEB)

    Shen, T

    2005-12-29

    We have investigated four brightening treatments proposed by two cleaning vendors for cleaning free machining brass. The experimental results showed that none of the proposed brightening treatments passed the swipe test. Thus, we maintain the recommendation of not using the brightening process in the cleaning of free machining brass for NIF application.

  13. Man and Machines: Three Criticisms.

    Science.gov (United States)

    Schneider, Edward F.

    As machines have become a more common part of daily life through the passage of time, the idea that the line separating man and machine is slowly fading has become more popular as well. This paper examines three critics of change through their most famous works. One of the most popular views of Mary Shelley's "Frankenstein" is that it is a…

  14. Anaesthesia machine: Checklist, hazards, scavenging

    Directory of Open Access Journals (Sweden)

    Umesh Goneppanavar

    2013-01-01

    Full Text Available From a simple pneumatic device of the early 20 th century, the anaesthesia machine has evolved to incorporate various mechanical, electrical and electronic components to be more appropriately called anaesthesia workstation. Modern machines have overcome many drawbacks associated with the older machines. However, addition of several mechanical, electronic and electric components has contributed to recurrence of some of the older problems such as leak or obstruction attributable to newer gadgets and development of newer problems. No single checklist can satisfactorily test the integrity and safety of all existing anaesthesia machines due to their complex nature as well as variations in design among manufacturers. Human factors have contributed to greater complications than machine faults. Therefore, better understanding of the basics of anaesthesia machine and checking each component of the machine for proper functioning prior to use is essential to minimise these hazards. Clear documentation of regular and appropriate servicing of the anaesthesia machine, its components and their satisfactory functioning following servicing and repair is also equally important. Trace anaesthetic gases polluting the theatre atmosphere can have several adverse effects on the health of theatre personnel. Therefore, safe disposal of these gases away from the workplace with efficiently functioning scavenging system is necessary. Other ways of minimising atmospheric pollution such as gas delivery equipment with negligible leaks, low flow anaesthesia, minimal leak around the airway equipment (facemask, tracheal tube, laryngeal mask airway, etc. more than 15 air changes/hour and total intravenous anaesthesia should also be considered.

  15. A multipurpose tissue bending machine.

    Science.gov (United States)

    Vesely, I; Boughner, D R

    1985-01-01

    A unique tissue bending machine was developed to test the bending properties of normal and bioprosthetic heart valve material. It can be operated in air or in a tissue bath and can measure bending torques with an accuracy in excess of 1.0 microN m. Three contrasting substances were tested to compare their stiffness and to demonstrate the machine.

  16. Self-Adjusting Teaching Machines.

    Science.gov (United States)

    Dovgyallo, A. M.

    A study was made on the synthesis of teaching machine elements to ensure the stabilization of the chi indicator of the teaching process of each student. At first, a procedure was developed for calculating the chi indicator for the case when the teaching machine predicts the magnitude of this indicator based on probabilities derived from an…

  17. The Machine Scoring of Writing

    Science.gov (United States)

    McCurry, Doug

    2010-01-01

    This article provides an introduction to the kind of computer software that is used to score student writing in some high stakes testing programs, and that is being promoted as a teaching and learning tool to schools. It sketches the state of play with machines for the scoring of writing, and describes how these machines work and what they do.…

  18. Real Analytic Machines and Degrees

    CERN Document Server

    Gärtner, Tobias; 10.4204/EPTCS.24.12

    2010-01-01

    We study and compare in two degree-theoretic ways (iterated Halting oracles analogous to Kleene's arithmetical hierarchy and the Borel hierarchy of descriptive set theory) the capabilities and limitations of three models of analytic computation: BSS machines (aka real-RAM) and strongly/weakly analytic machines as introduced by Hotz et. al. (1995).

  19. Storytelling machines for video search

    NARCIS (Netherlands)

    Habibian, A.

    2016-01-01

    We study a fundamental question for developing storytelling machines: what vocabulary is suited for machines to tell the story of a video? We start by manually specifying the vocabulary concepts and their annotations. In order to effectively handcraft the vocabulary, we empirically study what are th

  20. Anaesthesia machine: checklist, hazards, scavenging.

    Science.gov (United States)

    Goneppanavar, Umesh; Prabhu, Manjunath

    2013-09-01

    From a simple pneumatic device of the early 20(th) century, the anaesthesia machine has evolved to incorporate various mechanical, electrical and electronic components to be more appropriately called anaesthesia workstation. Modern machines have overcome many drawbacks associated with the older machines. However, addition of several mechanical, electronic and electric components has contributed to recurrence of some of the older problems such as leak or obstruction attributable to newer gadgets and development of newer problems. No single checklist can satisfactorily test the integrity and safety of all existing anaesthesia machines due to their complex nature as well as variations in design among manufacturers. Human factors have contributed to greater complications than machine faults. Therefore, better understanding of the basics of anaesthesia machine and checking each component of the machine for proper functioning prior to use is essential to minimise these hazards. Clear documentation of regular and appropriate servicing of the anaesthesia machine, its components and their satisfactory functioning following servicing and repair is also equally important. Trace anaesthetic gases polluting the theatre atmosphere can have several adverse effects on the health of theatre personnel. Therefore, safe disposal of these gases away from the workplace with efficiently functioning scavenging system is necessary. Other ways of minimising atmospheric pollution such as gas delivery equipment with negligible leaks, low flow anaesthesia, minimal leak around the airway equipment (facemask, tracheal tube, laryngeal mask airway, etc.) more than 15 air changes/hour and total intravenous anaesthesia should also be considered.

  1. Cognitive linguistics.

    Science.gov (United States)

    Evans, Vyvyan

    2012-03-01

    Cognitive linguistics is one of the fastest growing and influential perspectives on the nature of language, the mind, and their relationship with sociophysical (embodied) experience. It is a broad theoretical and methodological enterprise, rather than a single, closely articulated theory. Its primary commitments are outlined. These are the Cognitive Commitment-a commitment to providing a characterization of language that accords with what is known about the mind and brain from other disciplines-and the Generalization Commitment-which represents a dedication to characterizing general principles that apply to all aspects of human language. The article also outlines the assumptions and worldview which arises from these commitments, as represented in the work of leading cognitive linguists. WIREs Cogn Sci 2012, 3:129-141. doi: 10.1002/wcs.1163 For further resources related to this article, please visit the WIREs website.

  2. Cognitive fitness.

    Science.gov (United States)

    Gilkey, Roderick; Kilts, Clint

    2007-11-01

    Recent neuroscientific research shows that the health of your brain isn't, as experts once thought, just the product of childhood experiences and genetics; it reflects your adult choices and experiences as well. Professors Gilkey and Kilts of Emory University's medical and business schools explain how you can strengthen your brain's anatomy, neural networks, and cognitive abilities, and prevent functions such as memory from deteriorating as you age. The brain's alertness is the result of what the authors call cognitive fitness -a state of optimized ability to reason, remember, learn, plan, and adapt. Certain attitudes, lifestyle choices, and exercises enhance cognitive fitness. Mental workouts are the key. Brain-imaging studies indicate that acquiring expertise in areas as diverse as playing a cello, juggling, speaking a foreign language, and driving a taxicab expands your neural systems and makes them more communicative. In other words, you can alter the physical makeup of your brain by learning new skills. The more cognitively fit you are, the better equipped you are to make decisions, solve problems, and deal with stress and change. Cognitive fitness will help you be more open to new ideas and alternative perspectives. It will give you the capacity to change your behavior and realize your goals. You can delay senescence for years and even enjoy a second career. Drawing from the rapidly expanding body of neuroscience research as well as from well-established research in psychology and other mental health fields, the authors have identified four steps you can take to become cognitively fit: understand how experience makes the brain grow, work hard at play, search for patterns, and seek novelty and innovation. Together these steps capture some of the key opportunities for maintaining an engaged, creative brain.

  3. Machinability of Stellite 6 hardfacing

    Science.gov (United States)

    Benghersallah, M.; Boulanouar, L.; Le Coz, G.; Devillez, A.; Dudzinski, D.

    2010-06-01

    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.

  4. 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...

  5. 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.

  6. 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...

  7. 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.

  8. Cognitive maps

    DEFF Research Database (Denmark)

    Minder, Bettina; Laursen, Linda Nhu; Lassen, Astrid Heidemann

    2014-01-01

    . Conceptual clustering is used to analyse and order information according to concepts or variables from within the data. The cognitive maps identified are validated through the comments of some of the same experts. The study presents three cognitive maps and respective world-views explaining how the design...... and innovation field are related and under which dimensions they differ. The paper draws preliminary conclusions on the implications of the different world- views on the innovation process. With the growing importance of the design approach in innovation e.g. design thinking, a clear conception...

  9. Cognitive maps

    DEFF Research Database (Denmark)

    Minder, Bettina; Laursen, Linda Nhu; Lassen, Astrid Heidemann

    2014-01-01

    . Conceptual clustering is used to analyse and order information according to concepts or variables from within the data. The cognitive maps identified are validated through the comments of some of the same experts. The study presents three cognitive maps and respective world-views explaining how the design...... and innovation field are related and under which dimensions they differ. The paper draws preliminary conclusions on the implications of the different world- views on the innovation process. With the growing importance of the design approach in innovation e.g. design thinking, a clear conception...

  10. Using neurophysiological signals that reflect cognitive or affective state: six recommendations to avoid common pitfalls

    NARCIS (Netherlands)

    Brouwer, A.M.; Zander, T.O.; Erp, J.B.F. van; Korteling, J.E.; Bronkhorst, A.W.

    2015-01-01

    Estimating cognitive or affective state from neurophysiological signals and designing applications that make use of this information requires expertise in many disciplines such as neurophysiology, machine learning, experimental psychology, and human factors. This makes it difficult to perform resear

  11. Microelectrical Discharge Machining: A Suitable Process for Machining Ceramics

    Directory of Open Access Journals (Sweden)

    Andreas Schubert

    2015-01-01

    Full Text Available Today ceramics are used in many industrial applications, for example, in the biomedical field, for high-temperature components or for cutting tools. This is attributed to their excellent mechanical and physical properties, as low density, high strength, and hardness or chemical resistance. However, these specific mechanical properties lead to problems regarding the postprocessing of ceramics. In particular, cutting processes require expensive tools which cause high manufacturing costs to machine ceramics. Consequently, there is a demand for alternative machining processes. Microelectrical discharge machining (micro-EDM is a thermal abrasion process which is based on electrical discharges between a tool and a workpiece. The advantages of micro-EDM are more and more in focus for ceramic machining. These advantages include the process of being a noncontact technology, an independency of material brittleness and hardness, a low impact on the material, and the achievable microstructures. This paper presents the current state of investigations regarding micro-EDM of ceramics. Beside the process principle of EDM, the used procedures for machining ceramics and insulating ceramics are described. Furthermore several machining examples are presented to demonstrate the possibilities of the micro-EDM process with regard to the machining of ceramics.

  12. Deciphering CAPTCHAs: What a Turing Test Reveals about Human Cognition

    OpenAIRE

    Thomas Hannagan; Maria Ktori; Myriam Chanceaux; Jonathan Grainger

    2012-01-01

    International audience; 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 fastacting automatic orthographic processing in humans has superior robustness to shape variations. A masked primi...

  13. Trusted Autonomy and Cognitive Cyber Symbiosis: Open Challenges

    OpenAIRE

    Abbass, Hussein A.; Petraki, Eleni; Merrick, Kathryn; Harvey, John; Barlow, Michael

    2015-01-01

    This paper considers two emerging interdisciplinary, but related topics that are likely to create tipping points in advancing the engineering and science areas. Trusted Autonomy (TA) is a field of research that focuses on understanding and designing the interaction space between two entities each of which exhibits a level of autonomy. These entities can be humans, machines, or a mix of the two. Cognitive Cyber Symbiosis (CoCyS) is a cloud that uses humans and machines for decision-making. In ...

  14. Cognitive Science.

    Science.gov (United States)

    Cocking, Rodney R.; Mestre, Jose P.

    The focus of this paper is on cognitive science as a model for understanding the application of human skills toward effective problem-solving. Sections include: (1) "Introduction" (discussing information processing framework, expert-novice distinctions, schema theory, and learning process); (2) "Application: The Expert-Novice…

  15. Moral Cognition

    NARCIS (Netherlands)

    Schleim, Stephan; Clausen, Jens; Levy, Neil

    2015-01-01

    Research on moral cognition is a growing and heavily multidisciplinary field. This section contains chapters addressing foundational psychological, neuroscientific, and philosophical issues of research on moral decision-making. Further- more, beyond summarizing the state of the art of their respecti

  16. Decomposition of forging dies for machining planning

    CERN Document Server

    Tapie, Laurent; Anselmetti, Bernard

    2009-01-01

    This paper will provide a method to decompose forging dies for machining planning in the case of high speed machining finishing operations. This method lies on a machining feature approach model presented in the following paper. The two main decomposition phases, called Basic Machining Features Extraction and Process Planning Generation, are presented. These two decomposition phases integrates machining resources models and expert machining knowledge to provide an outstanding process planning.

  17. Decomposition of forging dies for machining planning

    OpenAIRE

    Tapie, Laurent; Mawussi, Kwamiwi; Anselmetti, Bernard

    2009-01-01

    International audience; This paper will provide a method to decompose forging dies for machining planning in the case of high speed machining finishing operations. This method lies on a machining feature approach model presented in the following paper. The two main decomposition phases, called Basic Machining Features Extraction and Process Planning Generation, are presented. These two decomposition phases integrates machining resources models and expert machining knowledge to provide an outs...

  18. HUMAN MACHINE COOPERATIVE TELEROBOTICS

    Energy Technology Data Exchange (ETDEWEB)

    William R. Hamel; Spivey Douglass; Sewoong Kim; Pamela Murray; Yang Shou; Sriram Sridharan; Ge Zhang; Scott Thayer; Rajiv V. Dubey

    2003-06-30

    described as Human Machine Cooperative Telerobotics (HMCTR). The HMCTR combines the telerobot with robotic control techniques to improve the system efficiency and reliability in teleoperation mode. In this topical report, the control strategy, configuration and experimental results of Human Machines Cooperative Telerobotics (HMCTR), which modifies and limits the commands of human operator to follow the predefined constraints in the teleoperation mode, is described. The current implementation is a laboratory-scale system that will be incorporated into an engineering-scale system at the Oak Ridge National Laboratory in the future.

  19. 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.

  20. Learning with Support Vector Machines

    CERN Document Server

    Campbell, Colin

    2010-01-01

    Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such a

  1. Gloved Human-Machine Interface

    Science.gov (United States)

    Adams, Richard (Inventor); Olowin, Aaron (Inventor); Hannaford, Blake (Inventor)

    2015-01-01

    Certain exemplary embodiments can provide a system, machine, device, manufacture, circuit, composition of matter, and/or user interface adapted for and/or resulting from, and/or a method and/or machine-readable medium comprising machine-implementable instructions for, activities that can comprise and/or relate to: tracking movement of a gloved hand of a human; interpreting a gloved finger movement of the human; and/or in response to interpreting the gloved finger movement, providing feedback to the human.

  2. Machine learning in virtual screening.

    Science.gov (United States)

    Melville, James L; Burke, Edmund K; Hirst, Jonathan D

    2009-05-01

    In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a particular protein target. Both ligand-based similarity searching and structure-based docking have benefited from machine learning algorithms, including naïve Bayesian classifiers, support vector machines, neural networks, and decision trees, as well as more traditional regression techniques. Effective application of these methodologies requires an appreciation of data preparation, validation, optimization, and search methodologies, and we also survey developments in these areas.

  3. Fundamentals of Machine Learning for Neural Machine Translation

    OpenAIRE

    Kelleher, John

    2016-01-01

    This paper presents a short introduction to neural networks and how they are used for machine translation and concludes with some discussion on the current research challenges being addressed by neural machine translation (NMT) research. The primary goal of this paper is to give a no-tears introduction to NMT to readers that do not have a computer science or mathematical background. The secondary goal is to provide the reader with a deep enough understanding of NMT that they can appreciate th...

  4. Potential of Cognitive Computing and Cognitive Systems

    Science.gov (United States)

    Noor, Ahmed K.

    2014-11-01

    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

  5. Entrepreneurial Cognition

    DEFF Research Database (Denmark)

    Zichella, Giulio

    in the experiment were selected based on their entrepreneurial intentions, with a high degree of comparability and a limited impact of prior entrepreneurial experience. The data include measures of behavior in situations of risk and uncertainty with real monetary incentives, risk perception, and a number...... of individual characteristics, including personality traits, cognitive biases, and demographics. In the first essay, I explore how individuals with and without entrepreneurial intentions differ in terms of risk behavior by testing their sensitivity to prior monetary outcomes and an increasing degree of risk...... faced with risk and uncertainty. The purpose of this dissertation is to contribute to this latter stream of research by examining how individuals differ in their cognition and behaviors in situations of risk and uncertainty in a controlled environment. More specifically, the dissertation explores how...

  6. Machine Learning examples on Invenio

    CERN Document Server

    CERN. Geneva

    2017-01-01

    This talk will present the different Machine Learning tools that the INSPIRE is developing and integrating in order to automatize as much as possible content selection and curation in a subject based repository.

  7. ENERGY STAR Certified Vending Machines

    Data.gov (United States)

    U.S. Environmental Protection Agency — Certified models meet all ENERGY STAR requirements as listed in the Version 3.0 ENERGY STAR Program Requirements for Refrigerated Beverage Vending Machines that are...

  8. Particle accelerator; the Universe machine

    CERN Multimedia

    Yurkewicz, Katie

    2008-01-01

    "In summer 2008, scientists will switch on one of the largest machines in the world to search for the smallest of particle. CERN's Large Hadron Collider particle accelerator has the potential to chagne our understanding of the Universe."

  9. Quantum-Enhanced Machine Learning.

    Science.gov (United States)

    Dunjko, Vedran; Taylor, Jacob M; Briegel, Hans J

    2016-09-23

    The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.

  10. Quantum-Enhanced Machine Learning

    Science.gov (United States)

    Dunjko, Vedran; Taylor, Jacob M.; Briegel, Hans J.

    2016-09-01

    The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.

  11. 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.

  12. The efficiency of combined machinings

    OpenAIRE

    2012-01-01

    This paper analyses the efficiency of the finish process applied in machining of hard surfaces, completed by grinding, hard turning and also by the combination of these two procedures, on the basis of time consumption.

  13. Machine learning for healthcare technologies

    CERN Document Server

    Clifton, David A

    2016-01-01

    This book brings together chapters on the state-of-the-art in machine learning (ML) as it applies to the development of patient-centred technologies, with a special emphasis on 'big data' and mobile data.

  14. Nonquantum Cognition

    CERN Document Server

    Ghose, Partha

    2012-01-01

    The Hilbert space structure of classical field theory is proposed as a general theoretical framework to model human cognitive processes which do not often follow classical (Bayesian) probability principles. This leads to an extension of the circumplex model of affect and a Poincar\\'{e} sphere representation. A specific toy field theoretic model of the brain as a coherent structure in the presence of noise is also proposed that agrees qualitatively with Pavlovian fear conditioning studies.

  15. 4th Machining Innovations Conference

    CERN Document Server

    2014-01-01

    This contributed volume contains the research results presented at the 4th Machining Innovations Conference, Hannover, September 2013. The topic of the conference are new production technologies in aerospace industry and the focus is on energy efficient machine tools as well as sustainable process planning. The target audience primarily comprises researchers and experts in the field but the book may also be beneficial for graduate students.

  16. Function Concepts for Machine Parts

    DEFF Research Database (Denmark)

    Mortensen, Niels Henrik

    1999-01-01

    The majority of resources, like time and costs, consumed in industrial product development can be related to detailed design, i.e. the materialisation of machine parts (German Maschinenteile). Existing design theories based on a systems approach, e.g. Haberfellner [5] all have function, i...... to be identification of a purposeful behaviour concept, i.e. function for a machine part. The contribution is based on the theory of technical systems, Hubka and the domain theory, Andreasen....

  17. Constructing a modern city machine

    DEFF Research Database (Denmark)

    Lindegaard, Hanne; Jørgensen, Ulrik

    1998-01-01

    Based on the Copenhagen sewers debates and constructions the role of changing perceptions of water, hygiene and environment is discussed in relation to the modernisation of cities by machinating flows and infrastructures.......Based on the Copenhagen sewers debates and constructions the role of changing perceptions of water, hygiene and environment is discussed in relation to the modernisation of cities by machinating flows and infrastructures....

  18. Biosleeve Human-Machine Interface

    Science.gov (United States)

    Assad, Christopher (Inventor)

    2016-01-01

    Systems and methods for sensing human muscle action and gestures in order to control machines or robotic devices are disclosed. One exemplary system employs a tight fitting sleeve worn on a user arm and including a plurality of electromyography (EMG) sensors and at least one inertial measurement unit (IMU). Power, signal processing, and communications electronics may be built into the sleeve and control data may be transmitted wirelessly to the controlled machine or robotic device.

  19. Can cognitive science create a cognitive economics?

    Science.gov (United States)

    Chater, Nick

    2015-02-01

    Cognitive science can intersect with economics in at least three productive ways: by providing richer models of individual behaviour for use in economic analysis; by drawing from economic theory in order to model distributed cognition; and jointly to create more powerful 'rational' models of cognitive processes and social interaction. There is the prospect of moving from behavioural economics to a genuinely cognitive economics.

  20. 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…

  1. Error-related EEG patterns during tactile human-machine interaction

    NARCIS (Netherlands)

    Lehne, M.; Ihme, K.; Brouwer, A.M.; Erp, J.B.F. van; Zander, T.O.

    2009-01-01

    Recently, the use of brain-computer interfaces (BCIs) has been extended from active control to passive detection of cognitive user states. These passive BCI systems can be especially useful for automatic error detection in human-machine systems by recording EEG potentials related to human error proc

  2. 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…

  3. 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.

  4. 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.

  5. Machine function based control code algebras

    NARCIS (Netherlands)

    Bergstra, J.A.

    2008-01-01

    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 machin

  6. 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.

  7. 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.

  8. A Human-Information Interaction Perspective on Augmented Cognition

    Energy Technology Data Exchange (ETDEWEB)

    Greitzer, Frank L.; Griffith, Douglas

    2006-10-15

    Nearly a half-century ago, J.C.R. Licklider expressed a vision for “man-machine symbiosis,” coupling human brains and computing machines in a partnership that “will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.” Until relatively recently, this vision was largely left idle by human factors engineering (HFE) research that grew over the decades from an initial focus on design of equipment to accommodate human limitations to cognitive systems engineering research to a more recent perspective focusing on design of human-information interaction. These perspective shifts and insights have brought a degree of success to the field in design efforts aimed at enhancing human-system performance. In recent years, the research area of augmented cognition has begun to shift the focus once more not only to enhancing the interaction environment, but also the cognitive abilities of the human operators and decision makers themselves. Ambitious goals of increasing total cognitive capacity through augmented cognition technologies are still on the horizon of this research program. This paper describes a framework within which augmented cognition research may identify requirements that compensate for human information processing shortcomings and augment human potential.

  9. Psychobiology of the near-miss in fruit machine gambling.

    Science.gov (United States)

    Griffiths, M

    1991-05-01

    Explanations involving the etiology of pathological gambling have tended to emphasize psychosocial factors. However, the possibility that psychobiological factors may be important in the development of pathological gambling behavior should not be ruled out. Psychobiological approaches are becoming ever more prominent with the three main lines of research being (a) a search for a physiological disposition and/or underlying biological substrate in pathological gamblers, (b) an examination of the role of arousal in gambling, and (c) speculation about endorphin-related explanations. The data from questionnaires and interviews with fruit machine gamblers suggest that both physiological and cognitive factors (e.g., the psychology of the near-miss) may be important in the explanation of excessive fruit machine gambling. Thus, if a gambler becomes physiologically aroused when he or she wins or nearly wins, it will stimulate further play, here termed the psychobiology of the near-miss.

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

    Science.gov (United States)

    Wingfield, Cai; Su, Li; Liu, Xunying; Zhang, Chao; Woodland, Phil; Thwaites, Andrew; Fonteneau, Elisabeth; Marslen-Wilson, William D

    2017-09-01

    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.

  11. Compiling scheme using abstract state machines

    OpenAIRE

    2003-01-01

    The project investigates the use of Abstract State Machine in the process of computer program compilation. Compilation is to produce machine-code from a source program written in a high-level language. A compiler is a program written for the purpose. Machine-code is the computer-readable representation of sequences of computer instructions. An Abstract State Machine (ASM) is a notional computing machine, developed by Yuri Gurevich, for accurately and easily representing the semantics of...

  12. Doubly Cognitive Architecture Based Cognitive Wireless Sensor Network

    CERN Document Server

    Kumar, Sumit; Garimella, Rama Murthy

    2011-01-01

    Nowadays scarcity of spectrum availability is increasing highly. Adding cognition to the existing Wireless Sensor Network (WSN) infrastructure will help in this situation. As sensor nodes in WSN are limited with some constrains like power, efforts are required to increase the lifetime and other performance measures of the network. In this paper we propose the idea of Doubly Cognitive WSN. The basic idea is to progressively allocate the sensing resources only to the most promising areas of the spectrum. This work is based on Artificial Neural Network as well as on Support Vector Machine (SVM) concept. As the load of sensing resource is reduced significantly, this approach will save the energy of the nodes, and also reduce the sensing time dramatically. The proposed work can be enhanced by doing the pattern analysis thing after a sufficiently long time again and again to review the strategy of sensing. Thus Doubly Cognitive WSN will enable current WSN to overcome the spectrum scarcity as well as save the energy...

  13. 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.

  14. Claustrophobia in MRI: the role of cognitions.

    Science.gov (United States)

    Thorpe, Susan; Salkovskis, Paul M; Dittner, Antonia

    2008-10-01

    This study aimed to investigate the role of cognitive and behavioural factors in the experience of claustrophobia in the context of magnetic resonance imaging (MRI) scanners. One hundred and thirty outpatients attending an MRI unit completed questionnaires before and after their scans. Specific measures of experience in the scanner included subjective anxiety, panic symptoms, strategies used to stay calm and negative cognitions (such as 'I will suffocate' and 'I am going to faint in here'). Other general measures used included anxiety, depression, health anxiety and fears of restriction and suffocation. The amount of anxiety experienced during the scan was related to the perceived amount of time spent having physical symptoms of panic. Cognitions reported concerned the following: suffocation, harm caused by the machine and lack of perceived control. The number of strategies patients used to cope in the machine was also a related factor. Neither position in the scanner, nor head coil use nor previous experience of being in the scanner was related to levels of anxiety. The cognitions identified here may be used to construct a measure to identify those unable to enter the scanner or those most likely to become claustrophobic whilst undergoing the procedure and to further inform future brief, effective interventions.

  15. 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.

  16. 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.

  17. Reusable State Machine Code Generator

    Science.gov (United States)

    Hoffstadt, A. A.; Reyes, C.; Sommer, H.; Andolfato, L.

    2010-12-01

    The State Machine model is frequently used to represent the behaviour of a system, allowing one to express and execute this behaviour in a deterministic way. A graphical representation such as a UML State Chart diagram tames the complexity of the system, thus facilitating changes to the model and communication between developers and domain experts. We present a reusable state machine code generator, developed by the Universidad Técnica Federico Santa María and the European Southern Observatory. The generator itself is based on the open source project architecture, and uses UML State Chart models as input. This allows for a modular design and a clean separation between generator and generated code. The generated state machine code has well-defined interfaces that are independent of the implementation artefacts such as the middle-ware. This allows using the generator in the substantially different observatory software of the Atacama Large Millimeter Array and the ESO Very Large Telescope. A project-specific mapping layer for event and transition notification connects the state machine code to its environment, which can be the Common Software of these projects, or any other project. This approach even allows to automatically create tests for a generated state machine, using techniques from software testing, such as path-coverage.

  18. Machine Learning in Parliament Elections

    Directory of Open Access Journals (Sweden)

    Ahmad Esfandiari

    2012-09-01

    Full Text Available Parliament is considered as one of the most important pillars of the country governance. The parliamentary elections and prediction it, had been considered by scholars of from various field like political science long ago. Some important features are used to model the results of consultative parliament elections. These features are as follows: reputation and popularity, political orientation, tradesmen's support, clergymen's support, support from political wings and the type of supportive wing. Two parameters of reputation and popularity and the support of clergymen and religious scholars that have more impact in reducing of prediction error in election results, have been used as input parameters in implementation. In this study, the Iranian parliamentary elections, modeled and predicted using learnable machines of neural network and neuro-fuzzy. Neuro-fuzzy machine combines the ability of knowledge representation of fuzzy sets and the learning power of neural networks simultaneously. In predicting the social and political behavior, the neural network is first trained by two learning algorithms using the training data set and then this machine predict the result on test data. Next, the learning of neuro-fuzzy inference machine is performed. Then, be compared the results of two machines.

  19. 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

  20. Brain Machine Interface: Analysis of segmented EEG Signal Classification Using Short-Time PCA and Recurrent Neural Networks

    OpenAIRE

    C. R. Hema; Paulraj, M.P.; Nagarajan, R.; Sazali Yaacob; Abdul Hamid Adom

    2008-01-01

    Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients loose all communication pathways except for their sensory and cognitive functions. One of the possible rehabilitation methods for these patients is to provide a brain machine interface (BMI) for communication; the BMI uses the electrical activity of the brain detected by scalp ...

  1. Applying cognitive system engineering to cope with complexity in enterprises

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2012-08-01

    Full Text Available have the cognitive ability to develop creative solutions as required within the complex environment. The Human Machine Interfaces (HMI) between the humans and the enterprise Command and Control system must be geared to support and enhance the human...

  2. 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.

  3. 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.

  4. Build your own time machine

    CERN Document Server

    Clegg, Brian

    2012-01-01

    There is no physical law to prevent time travel nothing in physics to say it is impossible. So who is to say it can't be done? In Build Your Own Time Machine, acclaimed science writer Brian Clegg takes inspiration from his childhood heroes, Doctor Who and H. G. Wells, to explain the nature of time. How do we understand it and why measure it the way we do? How did the theories of one man change the way time was perceived by the world? Why wouldn't H. G. Wells's time machine have worked? And what would we need to do to make a real one? Build Your Own Time Machine explores the amazing possib

  5. Emerging Paradigms in Machine Learning

    CERN Document Server

    Jain, Lakhmi; Howlett, Robert

    2013-01-01

    This  book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The  multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.  The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems.  Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary ...

  6. INVESTIGATION OF MAGNESIUM ALLOYS MACHINABILITY

    Directory of Open Access Journals (Sweden)

    Berat Barıs BULDUM

    2013-01-01

    Full Text Available Magnesium is the lightest structural metal. Magnesium alloys have a hexagonal lattice structure, which affects the fundamental properties of these alloys. Plastic deformation of the hexagonal lattice is more complicated than in cubic latticed metals like aluminum, copper and steel. Magnesium alloy developments have traditionally been driven by industry requirements for lightweight materials to operate under increasingly demanding conditions. Magnesium alloys have always been attractive to designers due to their low density, only two thirds that of aluminium and its alloys [1]. The element and its alloys take a big part of modern industry needs. Especially nowadays magnesium alloys are used in automotive and mechanical (trains and wagons manufacture, because of its lightness and other features. Magnesium and magnesium alloys are the easiest of all metals to machine, allowing machining operations at extremely high speed. All standard machining operations such as turning, drilling, milling, are commonly performed on magnesium parts.

  7. Higgs Machine Learning Challenge 2014

    CERN Multimedia

    Olivier, A-P; Bourdarios, C ; LAL / Orsay; Goldfarb, S ; University of Michigan

    2014-01-01

    High Energy Physics (HEP) has been using Machine Learning (ML) techniques such as boosted decision trees (paper) and neural nets since the 90s. These techniques are now routinely used for difficult tasks such as the Higgs boson search. Nevertheless, formal connections between the two research fields are rather scarce, with some exceptions such as the AppStat group at LAL, founded in 2006. In collaboration with INRIA, AppStat promotes interdisciplinary research on machine learning, computational statistics, and high-energy particle and astroparticle physics. We are now exploring new ways to improve the cross-fertilization of the two fields by setting up a data challenge, following the footsteps of, among others, the astrophysics community (dark matter and galaxy zoo challenges) and neurobiology (connectomics and decoding the human brain). The organization committee consists of ATLAS physicists and machine learning researchers. The Challenge will run from Monday 12th to September 2014.

  8. Single Bacteria as Turing Machines

    Science.gov (United States)

    Bos, Julia; Zang, Qiucen; Vyawahare, Saurabh; Austin, Robert

    2014-03-01

    In Allan Turing's famous 1950 paper on Computing Machinery and Intelligence, he started with the provocative statement: ``I propose to consider the question, `Can machines think?' This should begin with definitions of the meaning of the terms `machine' and `think'.'' In our own work on exploring the way that organisms respond to stress and evolve, it seems at times as if they come to remarkably fast solutions to problems, indicating some sort of very clever computational machinery. I'll discuss how it would appear that bacteria can indeed create a form of a Turing Machine, the first example of a computer, and how they might use this algorithm to do rapid evolution to solve a genomics problem.

  9. Plug into 'the modernizing machine'!

    DEFF Research Database (Denmark)

    Krejsler, John B.

    2013-01-01

    ‘The modernizing machine’ codes individual bodies, things and symbols with images from New Public Management, neoliberal and Knowledge Economy discourses. Drawing on Deleuze & Guattari’s concept of machines, this article explores how ‘the modernizing machine’ produces neo-liberal modernization...... of the public sector. Taking its point of departure in Danish university reform, the article explores how the university is transformed by this desiring-producing machine. ‘The modernizing machine’ wrestles with the so-called ‘democratic-Humboldtian machine’. The University Act of 2003 and the host of reforms...... bodies and minds simultaneously produce academic subjectivities by plugging into these transformative machinic forces and are produced as they are traversed by them. What is experienced as stressful closures vis-à-vis new opportunities depends to a great extent upon how these producing...

  10. Machine learning methods in chemoinformatics

    Science.gov (United States)

    Mitchell, John B O

    2014-01-01

    Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some algorithms that chemoinformatics researchers frequently use. It makes no claim to be exhaustive. We concentrate on methods for supervised learning, predicting the unknown property values of a test set of instances, usually molecules, based on the known values for a training set. Particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k-Nearest Neighbors and naïve Bayes classifiers. WIREs Comput Mol Sci 2014, 4:468–481. How to cite this article: WIREs Comput Mol Sci 2014, 4:468–481. doi:10.1002/wcms.1183 PMID:25285160

  11. Vector grammars and PN machines

    Institute of Scientific and Technical Information of China (English)

    蒋昌俊

    1996-01-01

    The concept of vector grammars under the string semantic is introduced.The dass of vector grammars is given,which is similar to the dass of Chomsky grammars.The regular vector grammar is divided further.The strong and weak relation between the vector grammar and scalar grammar is discussed,so the spectrum system graph of scalar and vector grammars is made.The equivalent relation between the regular vector grammar and Petri nets (also called PN machine) is pointed.The hybrid PN machine is introduced,and its language is proved equivalent to the language of the context-free vector grammar.So the perfect relation structure between vector grammars and PN machines is formed.

  12. Machine learning phases of matter

    Science.gov (United States)

    Carrasquilla, Juan; Melko, Roger G.

    2017-02-01

    Condensed-matter physics is the study of the collective behaviour of infinitely complex assemblies of electrons, nuclei, magnetic moments, atoms or qubits. This complexity is reflected in the size of the state space, which grows exponentially with the number of particles, reminiscent of the `curse of dimensionality' commonly encountered in machine learning. Despite this curse, the machine learning community has developed techniques with remarkable abilities to recognize, classify, and characterize complex sets of data. Here, we show that modern machine learning architectures, such as fully connected and convolutional neural networks, can identify phases and phase transitions in a variety of condensed-matter Hamiltonians. Readily programmable through modern software libraries, neural networks can be trained to detect multiple types of order parameter, as well as highly non-trivial states with no conventional order, directly from raw state configurations sampled with Monte Carlo.

  13. Alpha Channeling in Mirror Machines

    Energy Technology Data Exchange (ETDEWEB)

    Fisch N.J.

    2005-10-19

    Because of their engineering simplicity, high-β, and steady-state operation, mirror machines and related open-trap machines such as gas dynamic traps, are an attractive concept for achieving controlled nuclear fusion. In these open-trap machines, the confinement occurs by means of magnetic mirroring, without the magnetic field lines closing upon themselves within the region of particle confinement. Unfortunately, these concepts have not achieved to date very spectacular laboratory results, and their reactor prospects are dimmed by the prospect of a low Q-factor, the ratio of fusion power produced to auxiliary power. Nonetheless, because of its engineering promise, over the years numerous improvements have been proposed to enhance the reactor prospects of mirror fusion, such as tandem designs, end-plugging, and electric potential barriers.

  14. Traditional machining processes research advances

    CERN Document Server

    2015-01-01

    This book collects several examples of research in machining processes. Chapter 1 provides information on polycrystalline diamond tool material and its emerging applications. Chapter 2 is dedicated to the analysis of orthogonal cutting experiments using diamond-coated tools with force and temperature measurements. Chapter 3 describes the estimation of cutting forces and tool wear using modified mechanistic models in high performance turning. Chapter 4 contains information on cutting under gas shields for industrial applications. Chapter 5 is dedicated to the machinability of magnesium and its alloys. Chapter 6 provides information on grinding science. Finally, chapter 7 is dedicated to flexible integration of shape and functional modelling of machine tool spindles in a design framework.    

  15. Machine learning for evolution strategies

    CERN Document Server

    Kramer, Oliver

    2016-01-01

    This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.

  16. Aerosols generated during beryllium machining.

    Science.gov (United States)

    Martyny, J W; Hoover, M D; Mroz, M M; Ellis, K; Maier, L A; Sheff, K L; Newman, L S

    2000-01-01

    Some beryllium processes, especially machining, are associated with an increased risk of beryllium sensitization and disease. Little is known about exposure characteristics contributing to risk, such as particle size. This study examined the characteristics of beryllium machining exposures under actual working conditions. Stationary samples, using eight-stage Lovelace Multijet Cascade Impactors, were taken at the process point of operation and at the closest point that the worker would routinely approach. Paired samples were collected at the operator's breathing zone by using a Marple Personal Cascade Impactor and a 35-mm closed-faced cassette. More than 50% of the beryllium machining particles in the breathing zone were less than 10 microns in aerodynamic diameter. This small particle size may result in beryllium deposition into the deepest portion of the lung and may explain elevated rates of sensitization among beryllium machinists.

  17. Rotating electrical machines part 4: methods for determining synchronous machine quantities from tests

    CERN Document Server

    International Electrotechnical Commission. Geneva

    1985-01-01

    Applies to three-phase synchronous machines of 1 kVA rating and larger with rated frequency of not more than 400 Hz and not less than 15 Hz. An appendix gives unconfirmed test methods for determining synchronous machine quantities. Notes: 1 -Tests are not applicable to synchronous machines such as permanent magnet field machines, inductor type machines, etc. 2 -They also apply to brushless machines, but certain variations exist and special precautions should be taken.

  18. Cognitive processes in CBT

    NARCIS (Netherlands)

    Becker, E.S.; Vrijsen, J.N.

    2017-01-01

    Automatic cognitive processing helps us navigate the world. However, if the emotional and cognitive interplay becomes skewed, those cognitive processes can become maladaptive and result in psychopathology. Although biases are present in most mental disorders, different disorders are characterized by

  19. Music and Cognitive Extension

    National Research Council Canada - National Science Library

    Kersten, Luke

    2014-01-01

    Extended cognition holds that cognitive processes sometimes leak into the world (Dawson, 2013). A recent trend among proponents of extended cognition has been to put pressure on phenomena thought to be safe havens for internalists...

  20. Music and Cognitive Extension

    National Research Council Canada - National Science Library

    Luke Kersten

    2015-01-01

    Extended cognition holds that cognitive processes sometimes leak into the world (Dawson, 2013). A recent trend among proponents of extended cognition has been to put pressure on phenomena thought to be safe havens for internalists...

  1. Controls and Machine Protection Systems

    CERN Document Server

    Carrone, E

    2016-01-01

    Machine protection, as part of accelerator control systems, can be managed with a 'functional safety' approach, which takes into account product life cycle, processes, quality, industrial standards and cybersafety. This paper will discuss strategies to manage such complexity and the related risks, with particular attention to fail-safe design and safety integrity levels, software and hardware standards, testing, and verification philosophy. It will also discuss an implementation of a machine protection system at the SLAC National Accelerator Laboratory's Linac Coherent Light Source (LCLS).

  2. Magnet management in electric machines

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, Patel Bhageerath; El-Refaie, Ayman Mohamed Fawzi; Huh, Kum Kang

    2017-03-21

    A magnet management method of controlling a ferrite-type permanent magnet electrical machine includes receiving and/or estimating the temperature permanent magnets; determining if that temperature is below a predetermined temperature; and if so, then: selectively heating the magnets in order to prevent demagnetization and/or derating the machine. A similar method provides for controlling magnetization level by analyzing flux or magnetization level. Controllers that employ various methods are disclosed. The present invention has been described in terms of specific embodiment(s), and it is recognized that equivalents, alternatives, and modifications, aside from those expressly stated, are possible and within the scope of the appending claims.

  3. Cooling system for rotating machine

    Science.gov (United States)

    Gerstler, William Dwight; El-Refaie, Ayman Mohamed Fawzi; Lokhandwalla, Murtuza; Alexander, James Pellegrino; Quirion, Owen Scott; Palafox, Pepe; Shen, Xiaochun; Salasoo, Lembit

    2011-08-09

    An electrical machine comprising a rotor is presented. The electrical machine includes the rotor disposed on a rotatable shaft and defining a plurality of radial protrusions extending from the shaft up to a periphery of the rotor. The radial protrusions having cavities define a fluid path. A stationary shaft is disposed concentrically within the rotatable shaft wherein an annular space is formed between the stationary and rotatable shaft. A plurality of magnetic segments is disposed on the radial protrusions and the fluid path from within the stationary shaft into the annular space and extending through the cavities within the radial protrusions.

  4. Magnet management in electric machines

    Science.gov (United States)

    Reddy, Patel Bhageerath; El-Refaie, Ayman Mohamed Fawzi; Huh, Kum Kang

    2017-03-21

    A magnet management method of controlling a ferrite-type permanent magnet electrical machine includes receiving and/or estimating the temperature permanent magnets; determining if that temperature is below a predetermined temperature; and if so, then: selectively heating the magnets in order to prevent demagnetization and/or derating the machine. A similar method provides for controlling magnetization level by analyzing flux or magnetization level. Controllers that employ various methods are disclosed. The present invention has been described in terms of specific embodiment(s), and it is recognized that equivalents, alternatives, and modifications, aside from those expressly stated, are possible and within the scope of the appending claims.

  5. Towards green lubrication in machining

    CERN Document Server

    Liew Yun Hsien, Willey

    2014-01-01

    The book gives an overview of environmental friendly gaseous and vapour, refrigerated compressed gas, solid lubricant, mist lubrication, minimum quantity lubrication (MQL) and vegetable oils that can be used as lubricants and additives in industrial machining applications. This book introduces vegetable oils as viable and good alternative resources because of their environmental friendly, non-toxic and readily biodegradable nature.  The effectiveness of various types of vegetables oils as lubricants and additives in reducing wear and friction is discussed in this book. Engineers and scientist working in the field of lubrication and machining will find this book useful.

  6. 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.

  7. 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, ...

  8. Learning as a Machine: Crossovers between Humans and Machines

    Science.gov (United States)

    Hildebrandt, Mireille

    2017-01-01

    This article is a revised version of the keynote presented at LAK '16 in Edinburgh. The article investigates some of the assumptions of learning analytics, notably those related to behaviourism. Building on the work of Ivan Pavlov, Herbert Simon, and James Gibson as ways of "learning as a machine," the article then develops two levels of…

  9. The Perfect Science Machine

    Science.gov (United States)

    2008-05-01

    ESO celebrates 10 years since First Light of the VLT Today marks the 10th anniversary since First Light with ESO's Very Large Telescope (VLT), the most advanced optical telescope in the world. Since then, the VLT has evolved into a unique suite of four 8.2-m Unit Telescopes (UTs) equipped with no fewer than 13 state-of-the-art instruments, and four 1.8-m moveable Auxiliary Telescopes (ATs). The telescopes can work individually, and they can also be linked together in groups of two or three to form a giant 'interferometer' (VLTI), allowing astronomers to see details corresponding to those from a much larger telescope. Green Flash at Paranal ESO PR Photo 16a/08 The VLT 10th anniversary poster "The Very Large Telescope array is a flagship facility for astronomy, a perfect science machine of which Europe can be very proud," says Tim de Zeeuw, ESO's Director General. "We have built the most advanced ground-based optical observatory in the world, thanks to the combination of a long-term adequately-funded instrument and technology development plan with an approach where most of the instruments were built in collaboration with institutions in the member states, with in-kind contributions in labour compensated by guaranteed observing time." Sitting atop the 2600m high Paranal Mountain in the Chilean Atacama Desert, the VLT's design, suite of instruments, and operating principles set the standard for ground-based astronomy. It provides the European scientific community with a telescope array with collecting power significantly greater than any other facilities available at present, offering imaging and spectroscopy capabilities at visible and infrared wavelengths. Blue Flash at Paranal ESO PR Photo 16b/08 A Universe of Discoveries The first scientifically useful images, marking the official 'First Light' of the VLT, were obtained on the night of 25 to 26 May 1998, with a test camera attached to "Antu", Unit Telescope number 1. They were officially presented to the press on

  10. Online algorithms for scheduling with machine activation cost on two uniform machines

    Institute of Scientific and Technical Information of China (English)

    HAN Shu-guang; JIANG Yi-wei; HU Jue-liang

    2007-01-01

    In this paper we investigate a variant of the scheduling problem on two uniform machines with speeds 1 and s. For this problem, we are given two potential uniform machines to process a sequence of independent jobs. Machines need to be activated before starting to process, and each machine activated incurs a fixed machine activation cost. No machines are initially activated,and when a job is revealed, the algorithm has the option to activate new machines. The objective is to minimize the sum of the makespan and the machine activation cost. We design optimal online algorithms with competitive ratio of (2s+1)/(s+1) for every s≥1.

  11. Conceptions of cognition for cognitive engineering

    DEFF Research Database (Denmark)

    Blomberg, Olle

    2011-01-01

    that there is not anything special about the biological boundary of the skin and skull per se, rather than some positive claim about where the boundaries of extended or distributed cognitive systems really are. I also examine the role of the concept of cognition in the theoretical frameworks of Distributed Cognition, Joint...... as part of the development of a new understanding of what cognition is and where the boundaries of cognitive systems are. Cognition, it is claimed, is not just situated or embedded, but extended and distributed in the world. My main question in this article is what the practical significance...... is of this framing of an expanded unit of analysis in a cognitive vocabulary. I focus on possible consequences for how cognitive engineering practitioners think about function allocation in system design, and on what the relative benefits and costs are of having a common framework and vocabulary for talking about...

  12. Investigation of Surfaces after Non Conventional Machining

    Science.gov (United States)

    Micietova, Anna; Neslusan, Miroslav; Cillikova, Maria

    2016-12-01

    This paper deals with analysis of surface integrity of steel after electro discharge machining (EDM), water jet machining, (WJM) laser beam machining (LBM) and plasma beam machining (PBM). The paper discusses surface integrity expressed in surface roughness, sample precision expressed in perpendicularity deviation as well as stress state. This study also demonstrates influence of the various non-conventional methods on structure transformations and reports about sensitivity of the different non-conventional methods of machining with regard to variable thickness of machined samples.

  13. The Neurodynamics of Cognition: A Tutorial on Computational Cognitive Neuroscience.

    Science.gov (United States)

    Ashby, F Gregory; Helie, Sebastien

    2011-08-01

    Computational Cognitive Neuroscience (CCN) is a new field that lies at the intersection of computational neuroscience, machine learning, and neural network theory (i.e., connectionism). The ideal CCN model should not make any assumptions that are known to contradict the current neuroscience literature and at the same time provide good accounts of behavior and at least some neuroscience data (e.g., single-neuron activity, fMRI data). Furthermore, once set, the architecture of the CCN network and the models of each individual unit should remain fixed throughout all applications. Because of the greater weight they place on biological accuracy, CCN models differ substantially from traditional neural network models in how each individual unit is modeled, how learning is modeled, and how behavior is generated from the network. A variety of CCN solutions to these three problems are described. A real example of this approach is described, and some advantages and limitations of the CCN approach are discussed.

  14. 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.

  15. Coordination Control Of Complex Machines

    NARCIS (Netherlands)

    J.C.M. Baeten; B. van Beek; J. Markovski; L.J.A.M. Somers

    2015-01-01

    Control and coordination are important aspects of the development of complex machines due to an ever-increasing demand for better functionality, quality, and performance. In WP6 of the C4C project, we developed a synthesis-centric systems engineering framework suitable for supervisory coordination o

  16. Attention: A Machine Learning Perspective

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    2012-01-01

    We review a statistical machine learning model of top-down task driven attention based on the notion of ‘gist’. In this framework we consider the task to be represented as a classification problem with two sets of features — a gist of coarse grained global features and a larger set of low...

  17. Machine Learning applications in CMS

    CERN Document Server

    CERN. Geneva

    2017-01-01

    Machine Learning is used in many aspects of CMS data taking, monitoring, processing and analysis. We review a few of these use cases and the most recent developments, with an outlook to future applications in the LHC Run III and for the High-Luminosity phase.

  18. Parsing statistical machine translation output

    NARCIS (Netherlands)

    Carter, S.; Monz, C.; Vetulani, Z.

    2009-01-01

    Despite increasing research into the use of syntax during statistical machine translation, the incorporation of syntax into language models has seen limited success. We present a study of the discriminative abilities of generative syntax-based language models, over and above standard n-gram models,

  19. 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...

  20. Teaching Machines to Think Fuzzy

    Science.gov (United States)

    Technology Teacher, 2004

    2004-01-01

    Fuzzy logic programs for computers make them more human. Computers can then think through messy situations and make smart decisions. It makes computers able to control things the way people do. Fuzzy logic has been used to control subway trains, elevators, washing machines, microwave ovens, and cars. Pretty much all the human has to do is push one…

  1. Macchines per scoprire - Discovery Machines

    CERN Multimedia

    Auditorium, Rome

    2016-01-01

    During the FCC week 2016 a public event entitled “Discovery Machines: The Higgs Boson and the Search for New Physics took place on 14 April at the Auditorium in Rome. The event, brought together physicists and experts from economics to discuss intriguing questions on the origin and evolution of the Universe and the societal impact of large-scale research projects.

  2. Precision Machining Technology. Curriculum Guide.

    Science.gov (United States)

    Idaho State Dept. of Education, Boise. Div. of Vocational Education.

    This curriculum guide was developed from a Technical Committee Report prepared with the assistance of industry personnel and containing a Task List which is the basis of the guide. It presents competency-based program standards for courses in precision machining technology and is part of the Idaho Vocational Curriculum Guide Project, a cooperative…

  3. The Garden and the Machine

    DEFF Research Database (Denmark)

    Clemmensen, Thomas Juel

    2014-01-01

    The aim of this paper is to explore how the concepts of garden and machine might inform our understanding of the complex relationship between infrastructure and nature. The garden is introduced as a third nature and used to shed a critical light on the promotion of landscape ‘as’ infrastructure...

  4. Automatic Evaluation of Machine Translation

    DEFF Research Database (Denmark)

    Martinez, Mercedes Garcia; Koglin, Arlene; Mesa-Lao, Bartolomé

    2015-01-01

    The availability of systems capable of producing fairly accurate translations has increased the popularity of machine translation (MT). The translation industry is steadily incorporating MT in their workflows engaging the human translator to post-edit the raw MT output in order to comply with a set...

  5. THE GARDEN AND THE MACHINE

    DEFF Research Database (Denmark)

    Clemmensen, Thomas Juel

    2012-01-01

    The aim of this paper is to explore how the concepts of garden and machine might inform our understanding of the complex relationship between infrastructure and nature. The garden is introduced as a third nature and used to shed a critical light on the promotion of landscape as infrastructure...

  6. Dimensioning, Tolerancing, and Machine Finishes.

    Science.gov (United States)

    Adams, George C.

    Intended for use with the vocational education student interested in technical drawing, this guide provides answers to questions relating to dimensioning and tolerancing machine drawings. It also gives examples of standard dimensioning practices, tolerancing applications, and finish applications. The problems and examples presented are based on…

  7. High Temperature Superconductor Machine Prototype

    DEFF Research Database (Denmark)

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

    2011-01-01

    A versatile testing platform for a High Temperature Superconductor (HTS) machine has been constructed. The stationary HTS field winding can carry up to 10 coils and it is operated at a temperature of 77K. The rotating armature is at room temperature. Test results and performance for the HTS field...

  8. Machine Tool Operation, Course Description.

    Science.gov (United States)

    Denny, Walter E.; Anderson, Floyd L.

    Prepared by an instructor and curriculum specialists, this course of study was designed to meet the individual needs of the dropout and/or hard-core unemployed youth by providing them skill training, related information, and supportive services knowledge in machine tool operation. The achievement level of each student is determined at entry, and…

  9. The Improved Relevance Voxel Machine

    DEFF Research Database (Denmark)

    Ganz, Melanie; Sabuncu, Mert; Van Leemput, Koen

    The concept of sparse Bayesian learning has received much attention in the machine learning literature as a means of achieving parsimonious representations of features used in regression and classification. It is an important family of algorithms for sparse signal recovery and compressed sensing...

  10. Electrical discharge machining in dentistry.

    Science.gov (United States)

    Van Roekel, N B

    1992-01-01

    A brief history of electrical discharge machining (EDM) is given and the process is discussed. A description of the application of EDM for fabricating precision attachment removable partial dentures, fixed-removable implant prostheses, and titanium-ceramic crowns is presented. The advantages and disadvantages of the EDM process for the dental profession are evaluated. Although expensive, the procedure has merit.

  11. Machinic Deconstruction : literature/ politics/ technics

    NARCIS (Netherlands)

    Ieven, Bram Koen

    2007-01-01

    Taking its cue from Jacques Derrida’s concept of différance, Machinic Deconstruction: Literature / Politics / Technics addresses the question whether it is possible to conceive of a work of technics that is operative at the same quasi-ontological level as différance itself. To do so, this study deve

  12. Molecular machines open cell membranes

    Science.gov (United States)

    García-López, Víctor; Chen, Fang; Nilewski, Lizanne G.; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B.; Robinson, Jacob T.; Wang, Gufeng; Pal, Robert; Tour, James M.

    2017-08-01

    Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

  13. Design of Waste Shredder Machine

    Directory of Open Access Journals (Sweden)

    Asst. Prof. S.Nithyananth

    2014-03-01

    Full Text Available The conventional agro-waste disposal is a traditional and oldest method of waste disposal in which agriculture wastes are dumped as it is to degrade in a particular place for decomposing. As the wastes are dumped as such, it takes more time to degrade and it causes environmental pollution. The waste shredder machine aims to reduce the agro waste and convert it into useful nourishing fertilizer. It decreases the man work making the farm neat and clean. Also it reduces the heap amount of pollution, disease causing agro-wastes and produces a better fertilizer with vermin compost. The waste shredder machine is an attachment as like a ploughing attachment. In the shredder attachment input power and rigid support is provided by a KAMCO Tera-trac 4W tractor by means of PTO (power take off shaft and three point linkage. PTO shaft of the tractor acts as a basic power input and the three point linkage provide a rigid support to the machine. Various kinds of blades are used for chipping and powdering operations like sawing blades, rotatory blades, and triangular shape blades. The blades are mounted on the shaft. The power is transmitted to another shaft by means of pulley and belt. For designing waste shredder machine, Creo parametric 1.0 software is used.

  14. Machine Gun Liner Bond Strength

    Science.gov (United States)

    2007-08-01

    explosive bonding of pure tantalum, several tantalum alloys, and Stellite 25 (an alloy of cobalt, chrome , nickel, and tungsten) in a liner...Difficulties have been experienced in machining an explosively- clad tantalum alloy in an M242 Bushmaster barrel [6].) One disadvantage of Stellite 25 was

  15. How To Teach Common Characteristics of Machine Tools

    Science.gov (United States)

    Kazanas, H. C.

    1970-01-01

    Organizes machine tools and machine operations into commonalities in order to help the student visualize and distinguish the common characteristics which exist between machine tools and operations. (GR)

  16. New Typewriter Displaces "Big Name" Machines.

    Science.gov (United States)

    School Business Affairs, 1983

    1983-01-01

    The Schoolwriter is a typewriter available at nearly half the price of competing machines. Schools in Minnesota and Maryland have purchased it for classroom machines and have had substantial savings. (MD)

  17. Mastering machine learning with scikit-learn

    CERN Document Server

    Hackeling, Gavin

    2014-01-01

    If you are a software developer who wants to learn how machine learning models work and how to apply them effectively, this book is for you. Familiarity with machine learning fundamentals and Python will be helpful, but is not essential.

  18. 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....

  19. Machine-Aided Indexing for NASA STI.

    Science.gov (United States)

    Wilson, John

    1987-01-01

    Describes the use of machine aided indexing as part of NASA's information systems. The discussion covers reasons for incorporating machine aided indexing, the lexical dictionary used, subject switching, natural language processing, benefits to the system, and possible future developments. (CLB)

  20. Novel Switched Flux Permanent Magnet Machine Topologies

    Institute of Scientific and Technical Information of China (English)

    诸自强

    2012-01-01

    This paper overviews various switched flux permanent magnet machines and their design and performance features,with particular emphasis on machine topologies with reduced magnet usage or without using magnet,as well as with variable flux capability.

  1. Setup Aid for Electrical-Discharge Machining

    Science.gov (United States)

    Lines, G.; Duca, J.

    1985-01-01

    Interlock assures that workpiece is correctly assembled in machining fixture. A Plunger in a Hollow Shaft actuates a switch, allowing a power supply to produce current for electrical-discharge machining. Plunger operates only when necessary parts are position.

  2. 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.

  3. Cutting tool materials for high speed machining

    Institute of Scientific and Technical Information of China (English)

    LIU Zhanqiang; AI Xing

    2005-01-01

    High speed machining (HSM) is one of the emerging cutting processes, which is machining at a speed significantlyhigher than the speed commonly in use on the shop floor. In the last twenty years, high speed machining has received great attentions as a technological solution for high productivity in manufacturing. This article reviews the developments of tool materials in high speed machining operations, and the properties, applications and prospective developments of tool materials in HSM are also presented.

  4. Design of equipment for training machine tools

    Directory of Open Access Journals (Sweden)

    Císar Miroslav

    2017-01-01

    Full Text Available The article proposes multiple devices designed to be used with training machine tools EMCO Concept series. Design was focused to enchant educational potential of training machine tools located in the laboratory of CNC programing, department of automation and production systems, Faculty of mechanical engineering, University of Zilina. The described device allows monitoring of machine tool, to measure tool offset and dimension, to use alternative ways of clamping, and to create video of machining.

  5. Calibration of a Parallel Kinematic Machine Tool

    Institute of Scientific and Technical Information of China (English)

    HE Xiao-mei; DING Hong-sheng; FU Tie; XIE Dian-huang; XU Jin-zhong; LI Hua-feng; LIU Hui-lin

    2006-01-01

    A calibration method is presented to enhance the static accuracy of a parallel kinematic machine tool by using a coordinate measuring machine and a laser tracker. According to the established calibration model and the calibration experiment, the factual 42 kinematic parameters of BKX-I parallel kinematic machine tool are obtained. By circular tests the comparison is made between the calibrated and the uncalibrated parameters and shows that there is 80% improvement in accuracy of this machine tool.

  6. FORMING AND PRECISION MACHINING TO NANOMATERIALS LUMP

    Institute of Scientific and Technical Information of China (English)

    Zhan Jie; Zhang Jin; Chen Bingkui; Chen Xiaoan

    2004-01-01

    The technology of forming and machining lump nano-materials has been investigated. Grinding, abrasive machining test has been conducted to Fe, Co, Ni and Al lump nano-materials. Experiments have been done to measure grinding force, grinding thermal, machining roughness and micro-hardness. Image analysis is carried out by metallographic and scanning tunnel microscopic microscope. Researches provide the basis data for forming and machining lump nano-materials.

  7. 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.

  8. Music cognition and the cognitive sciences.

    Science.gov (United States)

    Pearce, Marcus; Rohrmeier, Martin

    2012-10-01

    Why should music be of interest to cognitive scientists, and what role does it play in human cognition? We review three factors that make music an important topic for cognitive scientific research. First, music is a universal human trait fulfilling crucial roles in everyday life. Second, music has an important part to play in ontogenetic development and human evolution. Third, appreciating and producing music simultaneously engage many complex perceptual, cognitive, and emotional processes, rendering music an ideal object for studying the mind. We propose an integrated status for music cognition in the Cognitive Sciences and conclude by reviewing challenges and big questions in the field and the way in which these reflect recent developments. Copyright © 2012 Cognitive Science Society, Inc.

  9. 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.

  10. COGNITIVE COMPETENCE COMPARED TO COGNITIVE INDEPENDENCE AND COGNITIVE ACTIVITY

    OpenAIRE

    2014-01-01

    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 researc...

  11. Laser-assisted machining of difficult-to-machine materials

    Energy Technology Data Exchange (ETDEWEB)

    Incropera, F.P.; Rozzi, J.C.; Pfefferkorn, F.E.; Lei, S.; Shin, Y.C.

    1999-07-01

    Laser-assisted machining (LAM) is a hybrid process for which a difficult-to-machine material, such as a ceramic or super alloy, is irradiated by a laser source prior to material removal by a cutting tool. The process has the potential to significantly increase material removal rates, as well as to improve the geometry and properties of the finished work piece. Features and limitations of theoretical and experimental procedures for determining the transient thermal response of a work piece during LAM are described, and representative results are presented for laser-assisted turning of sintered silicon nitride. Significant physical trends are revealed by the calculations, as are guidelines for the selection of appropriate operating conditions.

  12. 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.

  13. Gold Rush to China for Italian Machines

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Italy exported two billion worth of textile machines in 2006, 46% of which went to Asia.China paid 365 million Euro to become the largest importer of ltaly’s machines in Aisa.China, a country that sustains Italian interest in coming,is the country where the investment in textile machines is growing...

  14. Evaluation of an improved centrifugal casting machine.

    Science.gov (United States)

    Donovan, T E; White, L E

    1985-05-01

    A Type III gold alloy, a silver-palladium alloy, and a base metal alloy were cast in two different centrifugal casting machines. With the number of complete cast mesh squares as an indicator of castability, the Airspin casting machine produced superior castings with all three alloys. The base metal alloy produced the greatest number of complete squares with both casting machines.

  15. 7 CFR 58.429 - Washing machine.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 3 2010-01-01 2010-01-01 false Washing machine. 58.429 Section 58.429 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards....429 Washing machine. When used, the washing machine for cheese cloths and bandages shall be...

  16. Method and apparatus for monitoring machine performance

    Science.gov (United States)

    Smith, Stephen F.; Castleberry, Kimberly N.

    1996-01-01

    Machine operating conditions can be monitored by analyzing, in either the time or frequency domain, the spectral components of the motor current. Changes in the electric background noise, induced by mechanical variations in the machine, are correlated to changes in the operating parameters of the machine.

  17. Machine scheduling with resource dependent processing times

    NARCIS (Netherlands)

    Grigoriev, A.; Sviridenko, M.; Uetz, Marc Jochen

    We consider machine scheduling on unrelated parallel machines with the objective to minimize the schedule makespan. We assume that, in addition to its machine dependence, the processing time of any job is dependent on the usage of a discrete renewable resource, e.g. workers. A given amount of that

  18. Automated solar-cell-array assembly machine

    Science.gov (United States)

    Costogue, E. N.; Mueller, R. L.; Person, J. K.; Yasui, R. K.

    1978-01-01

    Continuous-feeding machine automatically bonds solar cells to printed-circuit substrate. In completed machine, cells move to test station where electrical characteristics could be checked. If performance of cell is below specifications, that cell is marked and removed. All machine functions are synchronized by electronics located within unit. It may help to lower costs in future solar-cell production.

  19. Time-machine in Perfect Fluid Cosmologies

    Institute of Scientific and Technical Information of China (English)

    DUAN Yan-zhi

    2009-01-01

    This letter investigates the time-machine problem in perfect fluid cosmologies. It solves the Einstein's field equations with the energy-momentum tensors for perfect fluid and constructs a class of time-machine solutions,by which the time-machine problem in the perfect fluid cosmologies is solved.

  20. MACHINING OPTIMISATION AND OPERATION ALLOCATION FOR NC LATHE MACHINES IN A JOB SHOP MANUFACTURING SYSTEM

    Directory of Open Access Journals (Sweden)

    MUSSA I. MGWATU

    2013-08-01

    Full Text Available Numerical control (NC machines in a job shop may not be cost and time effective if the assignment of cutting operations and optimisation of machining parameters are overlooked. In order to justify better utilisation and higher productivity of invested NC machine tools, it is necessary to determine the optimum machining parameters and realize effective assignment of cutting operations on machines. This paper presents two mathematical models for optimising machining parameters and effectively allocating turning operations on NC lathe machines in a job shop manufacturing system. The models are developed as non-linear programming problems and solved using a commercial LINGO software package. The results show that the decisions of machining optimisation and operation allocation on NC lathe machines can be simultaneously made while minimising both production cost and cycle time. In addition, the results indicate that production cost and cycle time can be minimised while significantly reducing or totally eliminating idle times among machines.

  1. Temperature based Restricted Boltzmann Machines.

    Science.gov (United States)

    Li, Guoqi; Deng, Lei; Xu, Yi; Wen, Changyun; Wang, Wei; Pei, Jing; Shi, Luping

    2016-01-13

    Restricted Boltzmann machines (RBMs), which apply graphical models to learning probability distribution over a set of inputs, have attracted much attention recently since being proposed as building blocks of multi-layer learning systems called deep belief networks (DBNs). Note that temperature is a key factor of the Boltzmann distribution that RBMs originate from. However, none of existing schemes have considered the impact of temperature in the graphical model of DBNs. In this work, we propose temperature based restricted Boltzmann machines (TRBMs) which reveals that temperature is an essential parameter controlling the selectivity of the firing neurons in the hidden layers. We theoretically prove that the effect of temperature can be adjusted by setting the parameter of the sharpness of the logistic function in the proposed TRBMs. The performance of RBMs can be improved by adjusting the temperature parameter of TRBMs. This work provides a comprehensive insights into the deep belief networks and deep learning architectures from a physical point of view.

  2. Reliability analysis in intelligent machines

    Science.gov (United States)

    Mcinroy, John E.; Saridis, George N.

    1990-01-01

    Given an explicit task to be executed, an intelligent machine must be able to find the probability of success, or reliability, of alternative control and sensing strategies. By using concepts for information theory and reliability theory, new techniques for finding the reliability corresponding to alternative subsets of control and sensing strategies are proposed such that a desired set of specifications can be satisfied. The analysis is straightforward, provided that a set of Gaussian random state variables is available. An example problem illustrates the technique, and general reliability results are presented for visual servoing with a computed torque-control algorithm. Moreover, the example illustrates the principle of increasing precision with decreasing intelligence at the execution level of an intelligent machine.

  3. Machine learning a probabilistic perspective

    CERN Document Server

    Murphy, Kevin P

    2012-01-01

    Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic method...

  4. Attractor Control Using Machine Learning

    CERN Document Server

    Duriez, Thomas; Noack, Bernd R; Cordier, Laurent; Segond, Marc; Abel, Markus

    2013-01-01

    We propose a general strategy for feedback control design of complex dynamical systems exploiting the nonlinear mechanisms in a systematic unsupervised manner. These dynamical systems can have a state space of arbitrary dimension with finite number of actuators (multiple inputs) and sensors (multiple outputs). The control law maps outputs into inputs and is optimized with respect to a cost function, containing physics via the dynamical or statistical properties of the attractor to be controlled. Thus, we are capable of exploiting nonlinear mechanisms, e.g. chaos or frequency cross-talk, serving the control objective. This optimization is based on genetic programming, a branch of machine learning. This machine learning control is successfully applied to the stabilization of nonlinearly coupled oscillators and maximization of Lyapunov exponent of a forced Lorenz system. We foresee potential applications to most nonlinear multiple inputs/multiple outputs control problems, particulary in experiments.

  5. Differentially Private Support Vector Machines

    CERN Document Server

    Sarwate, Anand; Monteleoni, Claire

    2009-01-01

    This paper addresses the problem of practical privacy-preserving machine learning: how to detect patterns in massive, real-world databases of sensitive personal information, while maintaining the privacy of individuals. Chaudhuri and Monteleoni (2008) recently provided privacy-preserving techniques for learning linear separators via regularized logistic regression. With the goal of handling large databases that may not be linearly separable, we provide privacy-preserving support vector machine algorithms. We address general challenges left open by past work, such as how to release a kernel classifier without releasing any of the training data, and how to tune algorithm parameters in a privacy-preserving manner. We provide general, efficient algorithms for linear and nonlinear kernel SVMs, which guarantee $\\epsilon$-differential privacy, a very strong privacy definition due to Dwork et al. (2006). We also provide learning generalization guarantees. Empirical evaluations reveal promising performance on real and...

  6. Finite State Machine based Vending Machine Controller with Auto-Billing Features

    OpenAIRE

    2012-01-01

    Nowadays, Vending Machines are well known among Japan, Malaysia and Singapore. The quantity of machines in these countries is on the top worldwide. This is due to the modern lifestyles which require fast food processing with high quality. This paper describes the designing of multi select machine using Finite State Machine Model with Auto-Billing Features. Finite State Machine (FSM) modelling is the most crucial part in developing proposed model as this reduces the hardware. In this paper th...

  7. Study On Machining Processing Technology Risk Control

    Institute of Scientific and Technical Information of China (English)

    Li Xiqing

    2015-01-01

    In the industrial production process,only to ful y guarantee the machining production safety, it can been ensured that the smooth completion of machining process.Under this back ground,in the machining production process,the machinery processing safety would been ful y concerned,several factors, which may lead to the problem of mechanical processing and production process,were analyzed,and the relevant control strategies were researched.In view of this situation,this paper wil specifical y combined with the machining process characteristics to study the machining process manufacturability risk control.

  8. 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.

  9. A New Incremental Support Vector Machine Algorithm

    Directory of Open Access Journals (Sweden)

    Wenjuan Zhao

    2012-10-01

    Full Text Available Support vector machine is a popular method in machine learning. Incremental support vector machine algorithm is ideal selection in the face of large learning data set. In this paper a new incremental support vector machine learning algorithm is proposed to improve efficiency of large scale data processing. The model of this incremental learning algorithm is similar to the standard support vector machine. The goal concept is updated by incremental learning. Each training procedure only includes new training data. The time complexity is independent of whole training set. Compared with the other incremental version, the training speed of this approach is improved and the change of hyperplane is reduced.

  10. Strategies for measuring machine consciousness

    OpenAIRE

    2009-01-01

    The accurate measurement of the level of consciousness of a creature remains a major scientific challenge, nevertheless a number of new accounts that attempt to address this problem have been proposed recently. In this paper we analyze the principles of these new measures of consciousness along with other classical approaches focusing on their applicability to Machine Consciousness (MC). Furthermore, we propose a set of requirements of what we think a suitable measure for MC should be, discus...

  11. Machine vision theory, algorithms, practicalities

    CERN Document Server

    Davies, E R

    2005-01-01

    In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directl

  12. The bacteriophage DNA packaging machine.

    Science.gov (United States)

    Feiss, Michael; Rao, Venigalla B

    2012-01-01

    Large dsDNA bacteriophages and herpesviruses encode a powerful ATP-driven DNA-translocating machine that encapsidates a viral genome into a preformed capsid shell or prohead. The key components of the packaging machine are the packaging enzyme (terminase, motor) and the portal protein that forms the unique DNA entrance vertex of prohead. The terminase complex, comprised of a recognition subunit (small terminase) and an endonuclease/translocase subunit (large terminase), cuts viral genome concatemers. The terminase-viral DNA complex docks on the portal vertex, assembling a motor complex containing five large terminase subunits. The pentameric motor processively translocates DNA until the head shell is full with one viral genome. The motor cuts the DNA again and dissociates from the full head, allowing head-finishing proteins to assemble on the portal, sealing the portal, and constructing a platform for tail attachment. A body of evidence from molecular genetics and biochemical, structural, and biophysical approaches suggests that ATP hydrolysis-driven conformational changes in the packaging motor (large terminase) power DNA motion. Various parts of the motor subunit, such as the ATPase, arginine finger, transmission domain, hinge, and DNA groove, work in concert to translocate about 2 bp of DNA per ATP hydrolyzed. Powerful single-molecule approaches are providing precise delineation of steps during each translocation event in a motor that has a speed as high as a millisecond/step. The phage packaging machine has emerged as an excellent model for understanding the molecular machines, given the mechanistic parallels between terminases, helicases, and numerous motor proteins.

  13. Waterless Clothes-Cleaning Machine

    Science.gov (United States)

    Johnson, Glenn; Ganske, Shane

    2013-01-01

    A waterless clothes-cleaning machine has been developed that removes loose particulates and deodorizes dirty laundry with regenerative chemical processes to make the clothes more comfortable to wear and have a fresher smell. This system was initially developed for use in zero-g, but could be altered for 1-g environments where water or other re sources are scarce. Some of these processes include, but are not limited to, airflow, filtration, ozone generation, heat, ultraviolet light, and photocatalytic titanium oxide.

  14. Media-Augmented Exercise Machines

    Science.gov (United States)

    Krueger, T.

    2002-01-01

    Cardio-vascular exercise has been used to mitigate the muscle and cardiac atrophy associated with adaptation to micro-gravity environments. Several hours per day may be required. In confined spaces and long duration missions this kind of exercise is inevitably repetitive and rapidly becomes uninteresting. At the same time, there are pressures to accomplish as much as possible given the cost- per-hour for humans occupying orbiting or interplanetary. Media augmentation provides a the means to overlap activities in time by supplementing the exercise with social, recreational, training or collaborative activities and thereby reducing time pressures. In addition, the machine functions as an interface to a wide range of digital environments allowing for spatial variety in an otherwise confined environment. We hypothesize that the adoption of media augmented exercise machines will have a positive effect on psycho-social well-being on long duration missions. By organizing and supplementing exercise machines, data acquisition hardware, computers and displays into an interacting system this proposal increases functionality with limited additional mass. This paper reviews preliminary work on a project to augment exercise equipment in a manner that addresses these issues and at the same time opens possibilities for additional benefits. A testbed augmented exercise machine uses a specialty built cycle trainer as both input to a virtual environment and as an output device from it using spatialized sound, and visual displays, vibration transducers and variable resistance. The resulting interactivity increases a sense of engagement in the exercise, provides a rich experience of the digital environments. Activities in the virtual environment and accompanying physiological and psychological indicators may be correlated to track and evaluate the health of the crew.

  15. Machine learning phases of matter

    OpenAIRE

    Carrasquilla, Juan; Melko, Roger G.

    2016-01-01

    Neural networks can be used to identify phases and phase transitions in condensed matter systems via supervised machine learning. Readily programmable through modern software libraries, we show that a standard feed-forward neural network can be trained to detect multiple types of order parameter directly from raw state configurations sampled with Monte Carlo. In addition, they can detect highly non-trivial states such as Coulomb phases, and if modified to a convolutional neural network, topol...

  16. Spiking neuron network Helmholtz machine.

    Science.gov (United States)

    Sountsov, Pavel; Miller, Paul

    2015-01-01

    An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm) can be implemented in the brain is currently incomplete. There have been many proposed solutions that address how neurons can perform optimal inference but the question of how synaptic plasticity can implement optimal learning is rarely addressed. This paper aims to unify the two fields of probabilistic inference and synaptic plasticity by using a neuronal network of realistic model spiking neurons to implement a well-studied computational model called the Helmholtz Machine. The Helmholtz Machine is amenable to neural implementation as the algorithm it uses to learn its parameters, called the wake-sleep algorithm, uses a local delta learning rule. Our spiking-neuron network implements both the delta rule and a small example of a Helmholtz machine. This neuronal network can learn an internal model of continuous-valued training data sets without supervision. The network can also perform inference on the learned internal models. We show how various biophysical features of the neural implementation constrain the parameters of the wake-sleep algorithm, such as the duration of the wake and sleep phases of learning and the minimal sample duration. We examine the deviations from optimal performance and tie them to the properties of the synaptic plasticity rule.

  17. Quantum machines at the nanoscale

    OpenAIRE

    2015-01-01

    Thermodynamic machines have been studied for two centuries. The rapid advancement in fabrication techniques of the last decades has lead to size reduction from the macroscale to nanoscale. At the nanoscale, quantum properties become important and have thus to be fully taken into account. Quantum heat engines have been the subject of extensive theoretical studies in the last fifty years. However, while classical micro heat engines have been fabricated, to date no quantum heat engine has bee...

  18. The Database State Machine Approach

    OpenAIRE

    1999-01-01

    Database replication protocols have historically been built on top of distributed database systems, and have consequently been designed and implemented using distributed transactional mechanisms, such as atomic commitment. We present the Database State Machine approach, a new way to deal with database replication in a cluster of servers. This approach relies on a powerful atomic broadcast primitive to propagate transactions between database servers, and alleviates the need for atomic comm...

  19. Synthetic organisms and living machines

    OpenAIRE

    Deplazes, Anna; Huppenbauer, Markus

    2009-01-01

    The difference between a non-living machine such as a vacuum cleaner and a living organism as a lion seems to be obvious. The two types of entities differ in their material consistence, their origin, their development and their purpose. This apparently clear-cut borderline has previously been challenged by fictitious ideas of “artificial organism” and “living machines” as well as by progress in technology and breeding. The emergence of novel technologies such as artificial life, nanobiotechno...

  20. Galaxy Classification using Machine Learning

    Science.gov (United States)

    Fowler, Lucas; Schawinski, Kevin; Brandt, Ben-Elias; widmer, Nicole

    2017-01-01

    We present our current research into the use of machine learning to classify galaxy imaging data with various convolutional neural network configurations in TensorFlow. We are investigating how five-band Sloan Digital Sky Survey imaging data can be used to train on physical properties such as redshift, star formation rate, mass and morphology. We also investigate the performance of artificially redshifted images in recovering physical properties as image quality degrades.

  1. Machinability studies on INCONEL 718

    Science.gov (United States)

    Xavior, M. Anthony; Patil, Mahesh; Maiti, Abheek; Raj, Mrinal; Lohia, Nitesh

    2016-09-01

    The main objective of proposed work is to determine the influence of controllable parameters on machining characteristics of Inconel-718 and to achieve the optimum parameters for sustainable and efficient turning. Understanding the consequences of advanced tool materials together with higher cutting speeds on the formation of residual stresses and therefore the underlying mechanisms of small structural alteration within the subterranean layer thereby becomes terribly crucial for predicting product quality and more optimizing the machining conditions. Controllable cutting parameters such as cutting velocity, feed rate and depth of cut were selected at different level for experimentations in accordance with the Taguchi L9 array method using Minimum Quantity Lubrication (MQL) cutting condition and three different tools namely PVD TiAlN carbide, Cubic boron nitride and ceramic. Extensive study is done on the resulting surface roughness, surface subsurface hardness, tool wear and chip morphology. The results obtained from each of the tool were thoroughly analyzed and finally the optimized parameters are obtained for efficient machining of Inconel 718.

  2. Tribology in secondary wood machining

    Energy Technology Data Exchange (ETDEWEB)

    Ko, P.L.; Hawthorne, H.M.; Andiappan, J.

    1998-07-01

    Secondary wood manufacturing covers a wide range of products from furniture, cabinets, doors and windows, to musical instruments. Many of these are now mass produced in sophisticated, high speed numerical controlled machines. The performance and the reliability of the tools are key to an efficient and economical manufacturing process as well as to the quality of the finished products. A program concerned with three aspects of tribology of wood machining, namely, tool wear, tool-wood friction characteristics and wood surface quality characterization, was set up in the Integrated Manufacturing Technologies Institute (IMTI) of the National Research Council of Canada. The studies include friction and wear mechanism identification and modeling, wear performance of surface-engineered tool materials, friction-induced vibration and cutting efficiency, and the influence of wear and friction on finished products. This research program underlines the importance of tribology in secondary wood manufacturing and at the same time adds new challenges to tribology research since wood is a complex, heterogeneous, material and its behavior during machining is highly sensitive to the surrounding environments and to the moisture content in the work piece.

  3. The rise of machine consciousness: studying consciousness with computational models.

    Science.gov (United States)

    Reggia, James A

    2013-08-01

    Efforts to create computational models of consciousness have accelerated over the last two decades, creating a field that has become known as artificial consciousness. There have been two main motivations for this controversial work: to develop a better scientific understanding of the nature of human/animal consciousness and to produce machines that genuinely exhibit conscious awareness. This review begins by briefly explaining some of the concepts and terminology used by investigators working on machine consciousness, and summarizes key neurobiological correlates of human consciousness that are particularly relevant to past computational studies. Models of consciousness developed over the last twenty years are then surveyed. These models are largely found to fall into five categories based on the fundamental issue that their developers have selected as being most central to consciousness: a global workspace, information integration, an internal self-model, higher-level representations, or attention mechanisms. For each of these five categories, an overview of past work is given, a representative example is presented in some detail to illustrate the approach, and comments are provided on the contributions and limitations of the methodology. Three conclusions are offered about the state of the field based on this review: (1) computational modeling has become an effective and accepted methodology for the scientific study of consciousness, (2) existing computational models have successfully captured a number of neurobiological, cognitive, and behavioral correlates of conscious information processing as machine simulations, and (3) no existing approach to artificial consciousness has presented a compelling demonstration of phenomenal machine consciousness, or even clear evidence that artificial phenomenal consciousness will eventually be possible. The paper concludes by discussing the importance of continuing work in this area, considering the ethical issues it raises

  4. Online Dynamic Parameter Estimation of Synchronous Machines

    Science.gov (United States)

    West, Michael R.

    Traditionally, synchronous machine parameters are determined through an offline characterization procedure. The IEEE 115 standard suggests a variety of mechanical and electrical tests to capture the fundamental characteristics and behaviors of a given machine. These characteristics and behaviors can be used to develop and understand machine models that accurately reflect the machine's performance. To perform such tests, the machine is required to be removed from service. Characterizing a machine offline can result in economic losses due to down time, labor expenses, etc. Such losses may be mitigated by implementing online characterization procedures. Historically, different approaches have been taken to develop methods of calculating a machine's electrical characteristics, without removing the machine from service. Using a machine's input and response data combined with a numerical algorithm, a machine's characteristics can be determined. This thesis explores such characterization methods and strives to compare the IEEE 115 standard for offline characterization with the least squares approximation iterative approach implemented on a 20 h.p. synchronous machine. This least squares estimation method of online parameter estimation shows encouraging results for steady-state parameters, in comparison with steady-state parameters obtained through the IEEE 115 standard.

  5. 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......-by-value facets of an ordinary evaluator for the λ-calculus.We then reveal the denotational content of Hannan and Miller's CLS machine and of Landin's SECD machine. We formally compare the corresponding evaluators and we illustrate some degrees of freedom in the design spaces of evaluators and of abstract...

  6. 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

  7. A cognitive model's view of animal cognition

    Directory of Open Access Journals (Sweden)

    Sidney D'MELLO, Stan FRANKLIN

    2011-08-01

    Full Text Available Although it is a relatively new field of study, the animal cognition literature is quite extensive and difficult to synthesize. This paper explores the contributions a comprehensive, computational, cognitive model can make toward organizing and assimilating this literature, as well as toward identifying important concepts and their interrelations. Using the LIDA model as an example, a framework is described within which to integrate the diverse research in animal cognition. Such a framework can provide both an ontology of concepts and their relations, and a working model of an animal’s cognitive processes that can compliment active empirical research. In addition to helping to account for a broad range of cognitive processes, such a model can help to comparatively assess the cognitive capabilities of different animal species. After deriving an ontology for animal cognition from the LIDA model, we apply it to develop the beginnings of a database that maps the cognitive facilities of a variety of animal species. We conclude by discussing future avenues of research, particularly the use of computational models of animal cognition as valuable tools for hypotheses generation and testing [Current Zoology 57 (4: 499–513, 2011].

  8. 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

  9. Chip breaking system for automated machine tool

    Science.gov (United States)

    Arehart, Theodore A.; Carey, Donald O.

    1987-01-01

    The invention is a rotary selectively directional valve assembly for use in an automated turret lathe for directing a stream of high pressure liquid machining coolant to the interface of a machine tool and workpiece for breaking up ribbon-shaped chips during the formation thereof so as to inhibit scratching or other marring of the machined surfaces by these ribbon-shaped chips. The valve assembly is provided by a manifold arrangement having a plurality of circumferentially spaced apart ports each coupled to a machine tool. The manifold is rotatable with the turret when the turret is positioned for alignment of a machine tool in a machining relationship with the workpiece. The manifold is connected to a non-rotational header having a single passageway therethrough which conveys the high pressure coolant to only the port in the manifold which is in registry with the tool disposed in a working relationship with the workpiece. To position the machine tools the turret is rotated and one of the tools is placed in a material-removing relationship of the workpiece. The passageway in the header and one of the ports in the manifold arrangement are then automatically aligned to supply the machining coolant to the machine tool workpiece interface for breaking up of the chips as well as cooling the tool and workpiece during the machining operation.

  10. Cognitive Principles in Robust Multimodal Interpretation

    CERN Document Server

    Chai, J Y; Qu, S; 10.1613/jair.1936

    2011-01-01

    Multimodal conversational interfaces provide a natural means for users to communicate with computer systems through multiple modalities such as speech and gesture. To build effective multimodal interfaces, automated interpretation of user multimodal inputs is important. Inspired by the previous investigation on cognitive status in multimodal human machine interaction, we have developed a greedy algorithm for interpreting user referring expressions (i.e., multimodal reference resolution). This algorithm incorporates the cognitive principles of Conversational Implicature and Givenness Hierarchy and applies constraints from various sources (e.g., temporal, semantic, and contextual) to resolve references. Our empirical results have shown the advantage of this algorithm in efficiently resolving a variety of user references. Because of its simplicity and generality, this approach has the potential to improve the robustness of multimodal input interpretation.

  11. Single machine stochastic JIT scheduling problem subject to machine breakdowns

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In this paper we research the single machine stochastic JIT scheduling problem subject to the machine breakdowns for preemptive-resume and preemptive-repeat.The objective function of the problem is the sum of squared deviations of the job-expected completion times from the due date.For preemptive-resume,we show that the optimal sequence of the SSDE problem is V-shaped with respect to expected processing times.And a dynamic programming algorithm with the pseudopolynomial time complexity is given.We discuss the difference between the SSDE problem and the ESSD problem and show that the optimal solution of the SSDE problem is a good approximate optimal solution of the ESSD problem,and the optimal solution of the SSDE problem is an optimal solution of the ESSD problem under some conditions.For preemptive-repeat,the stochastic JIT scheduling problem has not been solved since the variances of the completion times cannot be computed.We replace the ESSD problem by the SSDE problem.We show that the optimal sequence of the SSDE problem is V-shaped with respect to the expected occupying times.And a dynamic programming algorithm with the pseudopolynomial time complexity is given.A new thought is advanced for the research of the preemptive-repeat stochastic JIT scheduling problem.

  12. Efficient Checkpointing of Virtual Machines using Virtual Machine Introspection

    Energy Technology Data Exchange (ETDEWEB)

    Aderholdt, Ferrol [Tennessee Technological University; Han, Fang [Tennessee Technological University; Scott, Stephen L [ORNL; Naughton, III, Thomas J [ORNL

    2014-01-01

    Cloud Computing environments rely heavily on system-level virtualization. This is due to the inherent benefits of virtualization including fault tolerance through checkpoint/restart (C/R) mechanisms. Because clouds are the abstraction of large data centers and large data centers have a higher potential for failure, it is imperative that a C/R mechanism for such an environment provide minimal latency as well as a small checkpoint file size. Recently, there has been much research into C/R with respect to virtual machines (VM) providing excellent solutions to reduce either checkpoint latency or checkpoint file size. However, these approaches do not provide both. This paper presents a method of checkpointing VMs by utilizing virtual machine introspection (VMI). Through the usage of VMI, we are able to determine which pages of memory within the guest are used or free and are better able to reduce the amount of pages written to disk during a checkpoint. We have validated this work by using various benchmarks to measure the latency along with the checkpoint size. With respect to checkpoint file size, our approach results in file sizes within 24% or less of the actual used memory within the guest. Additionally, the checkpoint latency of our approach is up to 52% faster than KVM s default method.

  13. Single machine stochastic JIT scheduling problem subject to machine breakdowns

    Institute of Scientific and Technical Information of China (English)

    TANG HengYong; ZHAO ChuanLi; CHENG CongDian

    2008-01-01

    In this paper we research the single machine stochastic JIT scheduling problem subject to the machine breakdowns for preemptive-resume and preemptive-repeat. The objective function of the problem is the sum of squared deviations of the job-expected completion times from the due date. For preemptive-resume, we show that the optimal sequence of the SSDE problem is V-shaped with respect to expected processing times. And a dynamic programming algorithm with the pseudopolynomial time complexity is, given. We discuss the difference between the SSDE problem and the ESSD problem and show that the optimal solution of the SSDE problem is a good approximate optimal solution of the ESSD problem, and the optimal solution of the SSDE problem is an optimal solution of the ESSD problem under some conditions. For preemptive-repeat, the stochastic JIT scheduling problem has not been solved since the variances of the completion times cannot be computed. We replace the ESSD problem by the SSDE problem. We show that the optimal sequence of the SSDE problem is V-shaped with respect to the expected occupying times. And a dynamic programming algorithm with the pseudopolynomial time complexity is given. A new thought is advanced for the research of the preemptive-repeat stochastic JIT scheduling problem.

  14. Local Search Method for a Parallel Machine Scheduling Problemof Minimizing the Number of Machines Operated

    Science.gov (United States)

    Yamana, Takashi; Iima, Hitoshi; Sannomiya, Nobuo

    Although there have been many studies on parallel machine scheduling problems, the number of machines operated is fixed in these studies. It is desirable to generate a schedule with fewer machines operated from the viewpoint of the operation cost of machines. In this paper, we cope with a problem of minimizing the number of parallel machines subject to the constraint that the total tardiness is not greater than the value given in advance. For this problem, we introduce a local search method in which the number of machines operated is changed efficiently and appropriately in a short time as well as reducing the total tardiness.

  15. Machine Phase Fullerene Nanotechnology: 1996

    Science.gov (United States)

    Globus, Al; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    NASA has used exotic materials for spacecraft and experimental aircraft to good effect for many decades. In spite of many advances, transportation to space still costs about $10,000 per pound. Drexler has proposed a hypothetical nanotechnology based on diamond and investigated the properties of such molecular systems. These studies and others suggest enormous potential for aerospace systems. Unfortunately, methods to realize diamonoid nanotechnology are at best highly speculative. Recent computational efforts at NASA Ames Research Center and computation and experiment elsewhere suggest that a nanotechnology of machine phase functionalized fullerenes may be synthetically relatively accessible and of great aerospace interest. Machine phase materials are (hypothetical) materials consisting entirely or in large part of microscopic machines. In a sense, most living matter fits this definition. To begin investigation of fullerene nanotechnology, we used molecular dynamics to study the properties of carbon nanotube based gears and gear/shaft configurations. Experiments on C60 and quantum calculations suggest that benzyne may react with carbon nanotubes to form gear teeth. Han has computationally demonstrated that molecular gears fashioned from (14,0) single-walled carbon nanotubes and benzyne teeth should operate well at 50-100 gigahertz. Results suggest that rotation can be converted to rotating or linear motion, and linear motion may be converted into rotation. Preliminary results suggest that these mechanical systems can be cooled by a helium atmosphere. Furthermore, Deepak has successfully simulated using helical electric fields generated by a laser to power fullerene gears once a positive and negative charge have been added to form a dipole. Even with mechanical motion, cooling, and power; creating a viable nanotechnology requires support structures, computer control, a system architecture, a variety of components, and some approach to manufacture. Additional

  16. Archetypal Analysis for Machine Learning

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    2010-01-01

    Archetypal analysis (AA) proposed by Cutler and Breiman in [1] estimates the principal convex hull of a data set. As such AA favors features that constitute representative ’corners’ of the data, i.e. distinct aspects or archetypes. We will show that AA enjoys the interpretability of clustering - ...... for K-means [2]. We demonstrate that the AA model is relevant for feature extraction and dimensional reduction for a large variety of machine learning problems taken from computer vision, neuroimaging, text mining and collaborative filtering....

  17. Creating unorganised machines from memristors

    Science.gov (United States)

    Howard, Gerard; Bull, Larry; Costello, Ben De Lacy; Adamatzky, Andrew

    2012-09-01

    There is growing interest in memristive devices following their recent nanoscale fabrication. This paper describes initial consideration of the implementation of artificial intelligence within predominantly memristive hardware. In particular, versions of Alan Turing's discrete dynamical network formalism — the unorganised machine — are used as the knowledge representation scheme and a population-based search technique is used to design appropriate networks. Issues including memristor count and global network synchrony are compared for two memristive logic implementations (NAND and IMP) on a well-known simulated robotics benchmark task. It is shown that IMP networks are harder to design than NAND, but are simpler to implement and require fewer processor cycles.

  18. Tracking by Machine Learning Methods

    CERN Document Server

    Jofrehei, Arash

    2015-01-01

    Current track reconstructing methods start with two points and then for each layer loop through all possible hits to find proper hits to add to that track. Another idea would be to use this large number of already reconstructed events and/or simulated data and train a machine on this data to find tracks given hit pixels. Training time could be long but real time tracking is really fast Simulation might not be as realistic as real data but tacking has been done for that with 100 percent efficiency while by using real data we would probably be limited to current efficiency.

  19. Micro-machined calorimetric biosensors

    Science.gov (United States)

    Doktycz, Mitchel J.; Britton, Jr., Charles L.; Smith, Stephen F.; Oden, Patrick I.; Bryan, William L.; Moore, James A.; Thundat, Thomas G.; Warmack, Robert J.

    2002-01-01

    A method and apparatus are provided for detecting and monitoring micro-volumetric enthalpic changes caused by molecular reactions. Micro-machining techniques are used to create very small thermally isolated masses incorporating temperature-sensitive circuitry. The thermally isolated masses are provided with a molecular layer or coating, and the temperature-sensitive circuitry provides an indication when the molecules of the coating are involved in an enthalpic reaction. The thermally isolated masses may be provided singly or in arrays and, in the latter case, the molecular coatings may differ to provide qualitative and/or quantitative assays of a substance.

  20. Setup reduction approaches for machining

    Energy Technology Data Exchange (ETDEWEB)

    Gillespie, L.K.

    1997-04-01

    Rapid setup is a common improvement approach in press working operations such as blanking and shearing. It has paid major dividends in the sheet metal industry. It also has been a major improvement thrust for high-production machining operations. However, the literature does not well cover all the setup operations and constraints for job shop work. This review provides some insight into the issues involved. It highlights the floor problems and provides insights for further improvement. The report is designed to provide a quick understanding of the issues.

  1. Machine learning methods for planning

    CERN Document Server

    Minton, Steven

    1993-01-01

    Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credi

  2. Cognitive Levels Matching.

    Science.gov (United States)

    Brooks, Martin; And Others

    1983-01-01

    The Cognitive Levels Matching Project trains teachers to guide students' skill acquisition and problem-solving processes by assessing students' cognitive levels and adapting their teaching materials accordingly. (MLF)

  3. COMPUTER SIMULATION OF A STIRLING REFRIGERATING MACHINE

    Directory of Open Access Journals (Sweden)

    V.V. Trandafilov

    2015-10-01

    Full Text Available In present numerical research, the mathematical model for precise performance simulation and detailed behavior of Stirling refrigerating machine is considered. The mathematical model for alpha Stirling refrigerating machine with helium as the working fluid will be useful in optimization of these machines mechanical design. Complete non-linear mathematical model of the machine, including thermodynamics of helium, and heat transfer from the walls, as well as heat transfer and gas resistance in the regenerator is developed. Non-dimensional groups are derived, and the mathematical model is numerically solved. Important design parameters are varied and their effect on Stirling refrigerating machine performance determined. The simulation results of Stirling refrigerating machine which include heat transfer and coefficient of performance are presented.

  4. Does machine perfusion decrease ischemia reperfusion injury?

    Science.gov (United States)

    Bon, D; Delpech, P-O; Chatauret, N; Hauet, T; Badet, L; Barrou, B

    2014-06-01

    In 1990's, use of machine perfusion for organ preservation has been abandoned because of improvement of preservation solutions, efficient without perfusion, easy to use and cheaper. Since the last 15 years, a renewed interest for machine perfusion emerged based on studies performed on preclinical model and seems to make consensus in case of expanded criteria donors or deceased after cardiac death donations. We present relevant studies highlighted the efficiency of preservation with hypothermic machine perfusion compared to static cold storage. Machines for organ preservation being in constant evolution, we also summarized recent developments included direct oxygenation of the perfusat. Machine perfusion technology also enables organ reconditioning during the last hours of preservation through a short period of perfusion on hypothermia, subnormothermia or normothermia. We present significant or low advantages for machine perfusion against ischemia reperfusion injuries regarding at least one primary parameter: risk of DFG, organ function or graft survival. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  5. High frequency group pulse electrochemical machining

    Institute of Scientific and Technical Information of China (English)

    WU Gaoyang; ZHANG Zhijing; ZHANG Weimin; TANG Xinglun

    2007-01-01

    In the process of machining ultrathin metal structure parts,the signal composition of high frequency group pulse,the influence of frequency to reverse current,and the design of the cathode in high frequency group pulse electrochemical machining (HGPECM) are discussed.The experiments on process were carried out.Results indicate that HGPECM can greatly improve the characteristics of the inter-electrode gap flow field,reduce electrode passivation,and obtain high machining quality.The machining quality is obviously improved by increasing the main pulse frequency.The dimensional accuracy reaches 30-40 pro and the roughness attained is at 0.30-0.35 μm.High frequency group pulse electrochemical machining can be successfully used in machining micro-parts.

  6. Interactive Team Cognition

    Science.gov (United States)

    Cooke, Nancy J.; Gorman, Jamie C.; Myers, Christopher W.; Duran, Jasmine L.

    2013-01-01

    Cognition in work teams has been predominantly understood and explained in terms of shared cognition with a focus on the similarity of static knowledge structures across individual team members. Inspired by the current zeitgeist in cognitive science, as well as by empirical data and pragmatic concerns, we offer an alternative theory of team…

  7. Handbook of Spatial Cognition

    Science.gov (United States)

    Waller, David, Ed.; Nadel, Lynn, Ed.

    2012-01-01

    Spatial cognition is a branch of cognitive psychology that studies how people acquire and use knowledge about their environment to determine where they are, how to obtain resources, and how to find their way home. Researchers from a wide range of disciplines, including neuroscience, cognition, and sociology, have discovered a great deal about how…

  8. The Tractable Cognition thesis

    NARCIS (Netherlands)

    Rooij, I.J.E.I. van

    2008-01-01

    The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by

  9. The Tractable Cognition Thesis

    Science.gov (United States)

    van Rooij, Iris

    2008-01-01

    The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the "Tractable Cognition thesis": Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories…

  10. The Tractable Cognition thesis

    NARCIS (Netherlands)

    Rooij, I.J.E.I. van

    2008-01-01

    The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constra

  11. The Tractable Cognition Thesis

    Science.gov (United States)

    van Rooij, Iris

    2008-01-01

    The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the "Tractable Cognition thesis": Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories…

  12. Interactive Team Cognition

    Science.gov (United States)

    Cooke, Nancy J.; Gorman, Jamie C.; Myers, Christopher W.; Duran, Jasmine L.

    2013-01-01

    Cognition in work teams has been predominantly understood and explained in terms of shared cognition with a focus on the similarity of static knowledge structures across individual team members. Inspired by the current zeitgeist in cognitive science, as well as by empirical data and pragmatic concerns, we offer an alternative theory of team…

  13. Handbook of Spatial Cognition

    Science.gov (United States)

    Waller, David, Ed.; Nadel, Lynn, Ed.

    2012-01-01

    Spatial cognition is a branch of cognitive psychology that studies how people acquire and use knowledge about their environment to determine where they are, how to obtain resources, and how to find their way home. Researchers from a wide range of disciplines, including neuroscience, cognition, and sociology, have discovered a great deal about how…

  14. Rapid Response Small Machining NNR Project 703025

    Energy Technology Data Exchange (ETDEWEB)

    Kanies, Tim

    2008-12-05

    This project was an effort to develop a machining area for small sized parts that is capable of delivering product with a quick response time. This entailed focusing efforts on leaning out specific work cells that would result in overall improvement to the entire machining area. This effort involved securing the most efficient available technologies for these areas. In the end, this incorporated preparing the small machining area for transformation to a new facility.

  15. 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.

  16. Extreme Learning Machine for land cover classification

    OpenAIRE

    Pal, Mahesh

    2008-01-01

    This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of one parameter and produce a unique solution. ETM+ multispectral data set (England) was used to judge the suitability of extreme learning machine for remote sensing classifications...

  17. Machine learning in genetics and genomics

    Science.gov (United States)

    Libbrecht, Maxwell W.; Noble, William Stafford

    2016-01-01

    The field of machine learning promises to enable computers to assist humans in making sense of large, complex data sets. In this review, we outline some of the main applications of machine learning to genetic and genomic data. In the process, we identify some recurrent challenges associated with this type of analysis and provide general guidelines to assist in the practical application of machine learning to real genetic and genomic data. PMID:25948244

  18. Speed-Selector Guard For Machine Tool

    Science.gov (United States)

    Shakhshir, Roda J.; Valentine, Richard L.

    1992-01-01

    Simple guardplate prevents accidental reversal of direction of rotation or sudden change of speed of lathe, milling machine, or other machine tool. Custom-made for specific machine and control settings. Allows control lever to be placed at only one setting. Operator uses handle to slide guard to engage or disengage control lever. Protects personnel from injury and equipment from damage occurring if speed- or direction-control lever inadvertently placed in wrong position.

  19. New approach to training support vector machine

    Institute of Scientific and Technical Information of China (English)

    Tang Faming; Chen Mianyun; Wang Zhongdong

    2006-01-01

    Support vector machine has become an increasingly popular tool for machine learning tasks involving classification, regression or novelty detection. Training a support vector machine requires the solution of a very large quadratic programming problem. Traditional optimization methods cannot be directly applied due to memory restrictions. Up to now, several approaches exist for circumventing the above shortcomings and work well. Another learning algorithm, particle swarm optimization, for training SVM is introduted. The method is tested on UCI datasets.

  20. Rotating Drive for Electrical-Arc Machining

    Science.gov (United States)

    Fransen, C. D.

    1986-01-01

    Rotating drive improves quality of holes made by electrical-arc machining. Mechanism (Uni-tek, rotary head, or equivalent) attached to electrical-arc system. Drive rotates electrode as though it were mechanical drill, while an arc disintegrates metal in workpiece, thereby creating hole. Rotating electrode method often used in electric-discharge machining. NASA innovation is application of technique to electrical-arc machining.