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Sample records for machining skills cluster

  1. Illinois Occupational Skill Standards: Machining Skills Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    This document of skill standards for the machining skills cluster serves as a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. These 67 occupational skill standards describe what people should know and be able to do in an…

  2. Numerically Controlled Machine Tools and Worker Skills.

    Science.gov (United States)

    Keefe, Jeffrey H.

    1991-01-01

    Analysis of data from "Industry Wage Surveys of Machinery Manufacturers" on the skill levels of 57 machining jobs found that introduction of numerically controlled machine tools has resulted in a very small reduction in skill levels or no significant change, supporting neither the deskilling argument nor argument that skill levels…

  3. Numerically Controlled Machine Tools and Worker Skills.

    Science.gov (United States)

    Keefe, Jeffrey H.

    1991-01-01

    Analysis of data from "Industry Wage Surveys of Machinery Manufacturers" on the skill levels of 57 machining jobs found that introduction of numerically controlled machine tools has resulted in a very small reduction in skill levels or no significant change, supporting neither the deskilling argument nor argument that skill levels…

  4. Clustering Categories in Support Vector Machines

    DEFF Research Database (Denmark)

    Carrizosa, Emilio; Nogales-Gómez, Amaya; Morales, Dolores Romero

    2017-01-01

    The support vector machine (SVM) is a state-of-the-art method in supervised classification. In this paper the Cluster Support Vector Machine (CLSVM) methodology is proposed with the aim to increase the sparsity of the SVM classifier in the presence of categorical features, leading to a gain in in...

  5. Applying Machine Learning to Star Cluster Classification

    Science.gov (United States)

    Fedorenko, Kristina; Grasha, Kathryn; Calzetti, Daniela; Mahadevan, Sridhar

    2016-01-01

    Catalogs describing populations of star clusters are essential in investigating a range of important issues, from star formation to galaxy evolution. Star cluster catalogs are typically created in a two-step process: in the first step, a catalog of sources is automatically produced; in the second step, each of the extracted sources is visually inspected by 3-to-5 human classifiers and assigned a category. Classification by humans is labor-intensive and time consuming, thus it creates a bottleneck, and substantially slows down progress in star cluster research.We seek to automate the process of labeling star clusters (the second step) through applying supervised machine learning techniques. This will provide a fast, objective, and reproducible classification. Our data is HST (WFC3 and ACS) images of galaxies in the distance range of 3.5-12 Mpc, with a few thousand star clusters already classified by humans as a part of the LEGUS (Legacy ExtraGalactic UV Survey) project. The classification is based on 4 labels (Class 1 - symmetric, compact cluster; Class 2 - concentrated object with some degree of asymmetry; Class 3 - multiple peak system, diffuse; and Class 4 - spurious detection). We start by looking at basic machine learning methods such as decision trees. We then proceed to evaluate performance of more advanced techniques, focusing on convolutional neural networks and other Deep Learning methods. We analyze the results, and suggest several directions for further improvement.

  6. Illinois Occupational Skill Standards: Welding Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These Illinois skill standards for the welding cluster are intended to serve as a guide to workforce preparation program providers as they define content for their programs and to employers as they establish the skills and standards necessary for job acquisition. They could also serve as a mechanism for communication among education, business,…

  7. Illinois Occupational Skill Standards. Beef Production Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    This document, which is intended as a guide for workforce preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the beef production cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards and…

  8. Illinois Occupational Skill Standards: Accounting Services Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These Illinois skill standards for the accounting services cluster are intended to serve as a guide to workforce preparation program providers as they define content for their programs and to employers as they establish the skills and standards necessary for job acquisition. They could also serve as a mechanism for communication among education,…

  9. Fast Affinity Propagation Clustering based on Machine Learning

    OpenAIRE

    Shailendra Kumar Shrivastava; J. L. Rana; DR.R.C.JAIN

    2013-01-01

    Affinity propagation (AP) was recently introduced as an un-supervised learning algorithm for exemplar based clustering. In this paper a novel Fast Affinity Propagation clustering Approach based on Machine Learning (FAPML) has been proposed. FAPML tries to put data points into clusters based on the history of the data points belonging to clusters in early stages. In FAPML we introduce affinity learning constant and dispersion constant which supervise the clustering process. FAPML also enforces...

  10. Automated Parallel Computing Tools for Multicore Machines and Clusters Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to improve productivity of high performance computing for applications on multicore computers and clusters. These machines built from one or more chips...

  11. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

    CERN Document Server

    Ntampaka, M; Sutherland, D J; Fromenteau, S; Poczos, B; Schneider, J

    2015-01-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark's publicly-available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power law scaling relation to infer cluster mass from galaxy line of sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with width = 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (width = 2.13). We employ the Support Distribution Machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to...

  12. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

    Science.gov (United States)

    Ntampaka, M.; Trac, H.; Sutherland, D. J.; Fromenteau, S.; Póczos, B.; Schneider, J.

    2016-11-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width of {{Δ }}ε ≈ 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further ({{Δ }}ε ≈ 2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement ({{Δ }}ε ≈ 0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncontaminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

  13. Critical machine cluster identification using the equal area criterion

    DEFF Research Database (Denmark)

    Weckesser, Johannes Tilman Gabriel; Jóhannsson, Hjörtur; Østergaard, Jacob

    2015-01-01

    The paper introduces a new method to early identify the critical machine cluster (CMC) after a transient disturbance. For transient stability assessment with methods based on the equal area criterion it is necessary to split the generators into a group of critical and non-critical machines...... coupling coefficient is derived and a cluster identification algorithm is developed. The algorithm determines the CMC based on the impact of the fault on the derived coupling coefficient of individual generator pairs. The results from two cases are presented and discussed, where the CMC is successfully...

  14. Virtual Machine Scheduling in Dedicated Computing Clusters

    CERN Document Server

    Boettger, Stefan; Zicari, V Roberto

    2014-01-08

    Time-critical applications process a continuous stream of input data and have to meet specific timing constraints. A common approach to ensure that such an application satisfies its constraints is over-provisioning: The application is deployed in a dedicated cluster environment with enough processing power to achieve the target performance for every specified data input rate. This approach comes with a drawback: At times of decreased data input rates, the cluster resources are not fully utilized. A typical use case is the HLT-Chain application that processes physics data at runtime of the ALICE experiment at CERN. From a perspective of cost and efficiency it is desirable to exploit temporarily unused cluster resources. Existing approaches aim for that goal by running additional applications. These approaches, however, a) lack in flexibility to dynamically grant the time-critical application the resources it needs, b) are insufficient for isolating the time-critical application from harmful side-effects i...

  15. Fast Affinity Propagation Clustering based on Machine Learning

    Directory of Open Access Journals (Sweden)

    Shailendra Kumar Shrivastava

    2013-01-01

    Full Text Available Affinity propagation (AP was recently introduced as an un-supervised learning algorithm for exemplar based clustering. In this paper a novel Fast Affinity Propagation clustering Approach based on Machine Learning (FAPML has been proposed. FAPML tries to put data points into clusters based on the history of the data points belonging to clusters in early stages. In FAPML we introduce affinity learning constant and dispersion constant which supervise the clustering process. FAPML also enforces the exemplar consistency and one of 'N constraints. Experiments conducted on many data sets such as Olivetti faces, Mushroom, Documents summarization, Thyroid, Yeast, Wine quality Red, Balance etc. show that FAPML is up to 54 % faster than the original AP with better Net Similarity.

  16. PC Cluster Machine Equipped with High-Speed Communication Software

    CERN Document Server

    Tanaka, M

    2004-01-01

    A high performance Beowulf (PC cluster) machine installed with Linux operating system and MPI (Message Passing Interface) for interprocessor communications has been constructed using Gigabit Ethernet and the communication software GAMMA (Genoa Active Message Machine), instead of the standard TCP/IP protocol. Fast C/Fortran compilers have been exploited with the GAMMA communication libraries. This method has eliminated large communication overhead of TCP/IP and resulted in significant increase in the computational performance of real application programs including the first-principle molecular dynamics simulation code. (Keywords: non TCP/IP, active messages, small latency, fast C/Fortran compilers, materials science, first-principle molecular dynamics)

  17. Illinois Occupational Skill Standards: Metal Stamping Skills Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards, developed through a consortium of educational and industry partners in Illinois, serve as guides to workforce preparation program providers to define content for their programs and to employers to establish the skills and standards necessary for job acquisition and performance. The skill standards include the following…

  18. Illinois Occupational Skill Standards: Medical Office Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards, developed through a consortium of educational and industry partners in Illinois, serve as guides to workforce preparation program providers to define content for their programs and to employers to establish the skills and standards necessary for job acquisition and performance. The skill standards include the following…

  19. Illinois Occupational Skill Standards: Nursing Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards, developed through a consortium of educational and industry partners in Illinois, serve as guides to workforce preparation program providers to define content for their programs and to employers to establish the skills and standards necessary for job acquisition and performance. The skill standards include the following…

  20. Illinois Occupational Skill Standards: Press Operations Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards, developed through a consortium of educational and industry partners in Illinois, serve as guides to workforce preparation program providers to define content for their programs and to employers to establish the skills and standards necessary for job acquisition and performance. The skill standards include the following…

  1. Fuzzy support vector machines based on linear clustering

    Science.gov (United States)

    Xiong, Shengwu; Liu, Hongbing; Niu, Xiaoxiao

    2005-10-01

    A new Fuzzy Support Vector Machines (FSVMs) based on linear clustering is proposed in this paper. Its concept comes from the idea of linear clustering, selecting the data points near to the preformed hyperplane, which is formed on the training set including one positive and one negative training samples respectively. The more important samples near to the preformed hyperplane are selected by linear clustering technique, and the new FSVMs are formed on the more important data set. It integrates the merit of two kinds of FSVMs. The membership functions are defined using the relative distance between the data points and the preformed hyperplane during the training process. The fuzzy membership decision functions of multi-class FSVMs adopt the minimal value of all the decision functions of two-class FSVMs. To demonstrate the superiority of our methods, the benchmark data sets of machines learning databases are selected to verify the proposed FSVMs. The experimental results indicate that the proposed FSVMs can reduce the training data and running time, and its recognition rate is greater than or equal to that of FSVMs through selecting a suitable linear clustering parameter.

  2. Illinois Occupational Skill Standards: Row Crop Production Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    This document, which is intended as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in occupations in the row crop production cluster. The document begins with a brief overview of the Illinois perspective on occupational skill standards and…

  3. Illinois Occupational Skill Standards: Industrial Maintenance General Maintenance Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards for the industrial maintenance general maintenance cluster are intended to be a guide to workforce preparation program providers in defining content for their programs and to employers to establish the skills and standards necessary for job acquisition. An introduction provides the Illinois perspective; Illinois Occupational…

  4. Illinois Occupational Skill Standards: Agricultural Laboratory and Field Technician Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These Illinois skill standards for the agricultural laboratory and field technician cluster are intended to serve as a guide to workforce preparation program providers as they define content for their programs and to employers as they establish the skills and standards necessary for job acquisition. They could also serve as a mechanism for…

  5. Illinois Occupational Skill Standards: Occupational Therapy Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    This document, which is intended to serve as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in jobs in occupational therapy. Agency partners involved in this project include: the Illinois State board of Education, Illinois Community College…

  6. Automatic application of teat disinfectant through the milking machine cluster.

    Science.gov (United States)

    Grindal, R J; Priest, D J

    1989-08-01

    An automatic device, which infuses disinfectant into the mouthpiece of the liner of the milking machine cluster as teatcups are removed, is described. Application at this time avoids any delay in disinfection, reduces the workload in the parlour and increases reliability of application. The teats of 20 cows were contaminated before each milking by immersion in a suspension of Staphylococcus aureus and Streptococcus agalactiae and then disinfected manually or automatically with iodophor after milking. Str. agalactiae was recovered from less than 5% of swabs and there was no difference between the results from the two methods. Neither method of disinfection was as effective against Staph. aureus and the recovery rate was significantly greater for the automatic method for both swabs from teat barrel (P less than 0.05) and teat apex (P less than 0.001). Rates of intramammary infection for quarters automatically or manually disinfected were similar and low (3/40 v. 6/40 respectively). The automatic method facilitates cluster removal by relieving vacuum and decreasing frictional contact at the mouthpiece lip, and utilizes approximately half the quantity of disinfectant used by manual dipping (0.9 v. 1.9 ml/teat). However, iodine contamination in the milk from the iodophor teat disinfectant was significantly increased from 14.4 to 102.2 micrograms 12/100 ml milk when no backflushing was practised.

  7. Optimal Machine Tools Selection Using Interval-Valued Data FCM Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Yupeng Xin

    2014-01-01

    Full Text Available Machine tool selection directly affects production rates, accuracy, and flexibility. In order to quickly and accurately select the appropriate machine tools in machining process planning, this paper proposes an optimal machine tools selection method based on interval-valued data fuzzy C-means (FCM clustering algorithm. We define the machining capability meta (MAE as the smallest unit to describe machining capacity of machine tools and establish MAE library based on the MAE information model. According to the manufacturing process requirements, the MAEs can be queried from MAE library. Subsequently, interval-valued data FCM algorithm is used to select the appropriate machine tools for manufacturing process. Through computing matching degree between manufacturing process machining constraints and MAEs, we get the most appropriate MAEs and the corresponding machine tools. Finally, a case study of an exhaust duct part of the aeroengine is presented to demonstrate the applicability of the proposed method.

  8. A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

    Science.gov (United States)

    Pfeiffenberger, Erik; Chaleil, Raphael A G; Moal, Iain H; Bates, Paul A

    2017-03-01

    Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near-native from incorrect clusters. The results show that our approach is able to identify clusters containing near-native protein-protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528-543. © 2016 Wiley Periodicals, Inc.

  9. Detecting intermediate mass black holes in globular clusters with machine learning

    CERN Document Server

    Pasquato, Mario

    2016-01-01

    Mergers of stellar-mass black holes were recently observed in the gravitational wave window opened by LIGO. This puts the spotlight on dense stellar systems and their ability to create intermediate-mass black holes (IMBHs) through repeated merging. Unfortunately, attempts at direct and indirect IMBH detection in star clusters in the nearby universe have proven inconclusive as of now. Indirect detection methods attempt to constrain IMBHs through their effect on star cluster photometric and kinematic observables. They are usually based on looking for a specific, physically motivated signature. While this approach is justified, it may be suboptimal in its usage of the available data. Here I present a new indirect detection method, based on machine learning, that is unaffected by these restrictions. I reduce the scientific question whether a star cluster hosts an IMBH to a classification problem in the machine learning framework. I present preliminary results to illustrate how machine learning models are trained ...

  10. Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

    CERN Document Server

    Chattopadhyay, Manojit; Dan, Pranab K; 10.1007/s00170-010-2802-4

    2011-01-01

    Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in t...

  11. Clustering and Candidate Motif Detection in Exosomal miRNAs by Application of Machine Learning Algorithms.

    Science.gov (United States)

    Gaur, Pallavi; Chaturvedi, Anoop

    2017-07-22

    The clustering pattern and motifs give immense information about any biological data. An application of machine learning algorithms for clustering and candidate motif detection in miRNAs derived from exosomes is depicted in this paper. Recent progress in the field of exosome research and more particularly regarding exosomal miRNAs has led much bioinformatic-based research to come into existence. The information on clustering pattern and candidate motifs in miRNAs of exosomal origin would help in analyzing existing, as well as newly discovered miRNAs within exosomes. Along with obtaining clustering pattern and candidate motifs in exosomal miRNAs, this work also elaborates the usefulness of the machine learning algorithms that can be efficiently used and executed on various programming languages/platforms. Data were clustered and sequence candidate motifs were detected successfully. The results were compared and validated with some available web tools such as 'BLASTN' and 'MEME suite'. The machine learning algorithms for aforementioned objectives were applied successfully. This work elaborated utility of machine learning algorithms and language platforms to achieve the tasks of clustering and candidate motif detection in exosomal miRNAs. With the information on mentioned objectives, deeper insight would be gained for analyses of newly discovered miRNAs in exosomes which are considered to be circulating biomarkers. In addition, the execution of machine learning algorithms on various language platforms gives more flexibility to users to try multiple iterations according to their requirements. This approach can be applied to other biological data-mining tasks as well.

  12. Adaptive Cluster Expansion for Inferring Boltzmann Machines with Noisy Data

    CERN Document Server

    Cocco, Simona

    2011-01-01

    We introduce a procedure to infer the interactions among a set of binary variables, based on their sampled frequencies and pairwise correlations. The algorithm builds the clusters of variables contributing most to the entropy of the inferred Ising model, and rejects the small contributions due to the sampling noise. Our procedure successfully recovers benchmark Ising models even at criticality and in the low temperature phase, and is applied to neurobiological data.

  13. Engineering, Trade, and Technical Cluster. Task Analyses. Drafting and Design Technology, Precision Machining Technology, Electronics Technology.

    Science.gov (United States)

    Henrico County Public Schools, Glen Allen, VA. Virginia Vocational Curriculum and Resource Center.

    Developed in Virginia, this publication contains task analysis guides to support selected tech prep programs that prepare students for careers in the engineering, trade, and technical cluster. Three occupations are profiled: drafting and design technology, precision machining technology, and electronics technology. Each guide contains the…

  14. Enhance the Performance of Virtual Machines by Using Cluster Computing Architecture

    Directory of Open Access Journals (Sweden)

    Chia-Ying Tseng

    2013-05-01

    Full Text Available Virtualization is a very important technology in the IaaS of the cloud computing. User uses computing resource as a virtual machine (VM provided from the system provider. The VM's performance is depended on physical machine. A VM should be deployed all required resources when it is created. If there is no more resource could be deployed, the VM should be move to another physical machine for getting higher performance by using VM's live migration. The overhead of a VM's live migration is 30 to 90 seconds. If there are many virtual machines which need live migration, the cost of overhead will be very much. This paper presents how to use cluster computing architecture to improve the VM's performance. It will enhance 15% of per-formance compared with VM's live migration.  

  15. Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

    Science.gov (United States)

    Pasquato, Mario; Chung, Chul

    2016-05-01

    Context. Machine-learning (ML) solves problems by learning patterns from data with limited or no human guidance. In astronomy, ML is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims: We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify globular clusters (GCs) that may have a history of merging from observational data. Methods: We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After carrying out dimensionality reduction on the feature space, the resulting datapoints are fed in to various classification algorithms. Using repeated random subsampling validation, we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations. Results: The three algorithms we considered (C5.0 trees, k-nearest neighbour, and support-vector machines) all achieve a test misclassification rate of about 10% without parameter tuning, with support-vector machines slightly outperforming the others. The first principal component of feature space correlates with cluster concentration. If we exclude it from the regression, the performance of the algorithms is only slightly reduced.

  16. Illinois Occupational Skill Standards: Retail Garden Center Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards, developed through a consortium of educational and industry partners in Illinois, serve as guides to workforce preparation program providers to define content for their programs and to employers to establish the skills and standards necessary for job acquisition and performance. The skill standards include the following…

  17. Illinois Occupational Skill Standards: Physical Therapist Assistant Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    These skill standards, developed through a consortium of educational and industry partners in Illinois, serve as guides to workforce preparation program providers to define content for their programs and to employers to establish the skills and standards necessary for job acquisition and performance. The skill standards include the following…

  18. Data Transmission through Nano Machines using the Clustering Tree for Mobile Adhoc Network

    Directory of Open Access Journals (Sweden)

    T.Ganesan

    2014-05-01

    Full Text Available Mobile Ad hoc Networks (MANET are normally characterized by high mobility and frequent link failures. With our previous work Optimization of Nano Adhoc on Demand distance Vector routing protocol in manet (O-NAODV we incorporated clustering technique and designed a new routing protocol called Enhanced NAODV (ENAODV. In manet nanotechnology is constituted by two kinds of nano machines used for sending and receiving of data with base stations. The Base stations(BS also called info stations to collect the information coming from nano machines are assumed to make decision for an appropriate action in routing through routing tables. In O-NAODV all source nodes needs to send the information to base station which takes more time and data loss on that network. In our new E-NAODV routing protocol the clustering tree is used in which a cluster head collects data from mobile nodes belonging to the cluster and sends the data to the sink node after data aggregation process. To reduce overall communication costs, energy consumption and reduction in delay the cluster head performs data aggregation and then send the data to sink node. Compared with optimized model the enhanced model behaves well in various aspects in the same simulation scenario.

  19. Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

    CERN Document Server

    Pasquato, Mario

    2016-01-01

    Context. Machine-Learning (ML) solves problems by learning patterns from data, with limited or no human guidance. In Astronomy, it is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims. We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify Globular Clusters (GCs) that may have a history of merging from observational data. Methods. We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After dimensionality reduction on the feature space, the resulting datapoints are fed to various classification algorithms. Using repeated random subsampling validation we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations. Results. The three algorithms we considered (C5.0 tree...

  20. Conditional Subspace Clustering of Skill Mastery: Identifying Skills that Separate Students

    Science.gov (United States)

    Nugent, Rebecca; Ayers, Elizabeth; Dean, Nema

    2009-01-01

    In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of mastering. As the number of examinees, items, and skills increases, the estimation of even simple cognitive diagnosis models becomes difficult. We adopt a faster, simpler approach:…

  1. Investigation and research on classification of productive skills (2): Cluster structure of productive skills in the car manufacturing industry.

    Science.gov (United States)

    Mori, K; Kikuchi, Y

    1993-12-01

    A survey was conducted at a production facility to study the categories of productive skills. In August 1991, a questionnaire survey was given to skilled workers of a car manufacturing company. The number of valid responses was 1,215. The survey items included 133 items in the following three areas: nature of productive skills, human functions and vocational ability necessary for the work, and working conditions. The survey results were analyzed by cluster analysis to verify the hypothesis that skills can be classified based on two axes--sensory motor and intellectual management. Moreover, the analysis results clarify that the structure of "nature of productive skills" in car manufacturing can be divided into maintenance, processing, information analysis and transmission, and parts assembly. The results also show that the internal structure of intellectual management skills, which had been unknown up to this point, consists of five skill clusters: field of technical knowledge, operation of controlling equipment, preparation abilities, analysis and judgment abilities, and measurement.

  2. Detecting intermediate mass black holes in globular clusters with machine learning.

    Science.gov (United States)

    Pasquato, M.

    Mergers of stellar-mass black holes were recently observed in the gravitational wave window opened by LIGO. This puts the spotlight on dense stellar systems and their ability to create intermediate-mass black holes (IMBHs) through repeated merging. Unfortunately, attempts at direct and indirect IMBH detection in star clusters in the nearby universe have proven inconclusive as of now. Indirect detection methods attempt to constrain IMBHs through their effect on star cluster photometric and kinematic observables. They are usually based on looking for a specific, physically motivated signature. While this approach is justified, it may be suboptimal in its usage of the available data. Here I present a new indirect detection method, based on machine learning, that is unaffected by these restrictions. I reduce the scientific question whether a star cluster hosts an IMBH to a classification problem in the machine learning framework. I present preliminary results to illustrate how machine learning models are trained on simulated dataset and measure their performance on previously unseen, simulated data.

  3. A new model for virtual machine migration in virtualized cluster server based on Fuzzy Decision Making

    CERN Document Server

    Tarighi, M; Sharifian, S

    2010-01-01

    In this paper, we show that performance of the virtualized cluster servers could be improved through intelligent decision over migration time of Virtual Machines across heterogeneous physical nodes of a cluster server. The cluster serves a variety range of services from Web Service to File Service. Some of them are CPU-Intensive while others are RAM-Intensive and so on. Virtualization has many advantages such as less hardware cost, cooling cost, more manageability. One of the key benefits is better load balancing by using of VM migration between hosts. To migrate, we must know which virtual machine needs to be migrated and when this relocation has to be done and, moreover, which host must be destined. To relocate VMs from overloaded servers to underloaded ones, we need to sort nodes from the highest volume to the lowest. There are some models to finding the most overloaded node, but they have some shortcomings. The focus of this paper is to present a new method to migrate VMs between cluster nodes using TOPSI...

  4. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 13: Laser Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    Science.gov (United States)

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  5. A cluster analysis to investigating nurses' knowledge, attitudes, and skills regarding the clinical management system.

    Science.gov (United States)

    Chan, M F

    2007-01-01

    Nurses' knowledge, attitudes, and skills regarding the Clinical Management System are explored by identifying profiles of nurses working in Hong Kong. A total of 282 nurses from four hospitals completed a self-reported questionnaire during the period from December 2004 to May 2005. Two-step cluster analysis yielded two clusters. The first cluster (n = 159, 56.4%) was labeled "negative attitudes, less skillful, and average knowledge" group. The second cluster (n = 123, 43.6%) was labeled "positive attitudes, good knowledge, but less skillful." There was a positive correlation in cluster 1 for nurses' knowledge and attitudes (rs = 0.28) and in cluster 2 for nurses' skills and attitudes (rs = 0.25) toward computerization. The study showed that senior and more highly educated nurses generally held more positive attitudes to computerization, whereas the attitudes among younger and less well educated nurses generally were more negative. Such findings should be used to formulate strategies to encourage nurses to resolve actual problems following computer training and to increase the depth and breadth of nurses' computer knowledge and skills and improve their attitudes toward computerization.

  6. Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

    Energy Technology Data Exchange (ETDEWEB)

    Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada)

    2015-01-01

    Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.

  7. Documentation for the machine-readable version of a table of Redshifts for Abell clusters (Sarazin, Rood and Struble 1982)

    Science.gov (United States)

    Warren, W. H., Jr.

    1983-01-01

    The machine readable catalog is described. The machine version contains the same data as the published table, which includes a second file with the notes. The computerized data files are prepared at the Astronomical Data Center. Detected discrepancies and cluster identifications based on photometric estimators are included.

  8. HT-Paxos: High Throughput State-Machine Replication Protocol for Large Clustered Data Centers

    Directory of Open Access Journals (Sweden)

    Vinit Kumar

    2015-01-01

    Full Text Available Paxos is a prominent theory of state-machine replication. Recent data intensive systems that implement state-machine replication generally require high throughput. Earlier versions of Paxos as few of them are classical Paxos, fast Paxos, and generalized Paxos have a major focus on fault tolerance and latency but lacking in terms of throughput and scalability. A major reason for this is the heavyweight leader. Through offloading the leader, we can further increase throughput of the system. Ring Paxos, Multiring Paxos, and S-Paxos are few prominent attempts in this direction for clustered data centers. In this paper, we are proposing HT-Paxos, a variant of Paxos that is the best suitable for any large clustered data center. HT-Paxos further offloads the leader very significantly and hence increases the throughput and scalability of the system, while at the same time, among high throughput state-machine replication protocols, it provides reasonably low latency and response time.

  9. A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters

    CERN Document Server

    Ntampaka, Michelle; Sutherland, Dougal J; Battaglia, Nicholas; Poczos, Barnabas; Schneider, Jeff

    2014-01-01

    We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed using halos with mass >= 10^14 Msolar/h from Multidark's publicly-available N-body MDPL halo catalog. In the conventional method, we use a standard M(sigma_v) power law scaling relation to infer cluster mass, M, from line-of-sight (LOS) galaxy velocity dispersion, sigma_v. The resulting fractional mass error distribution is broad, with width = 0.86 (68% scatter), and has extended high-error tails. The standard scaling relation can be simply enhanced by including higher-order moments of the LOS velocity distribution. Applying the kurtosis as a linear correction term to log(sigma_v) reduces the width of the error distribution to 0.74 (15% improvement). Machine learning can be used to take full advantage of all the information in the velocity distribution. We employ the Support ...

  10. Illinois Occupational Skill Standards: HVAC/R Technician Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    This document, which is intended to serve as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in jobs in the heating, ventilation, air conditioning, and refrigeration (HVAC/R) industry. Agency partners involved in this project include: the…

  11. Illinois Occupational Skill Standards: Agricultural Sales and Marketing Cluster.

    Science.gov (United States)

    Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

    This document, which is intended to serve as a guide for work force preparation program providers, details the Illinois occupational skill standards for programs preparing students for employment in jobs in agricultural sales and marketing. Agency partners involved in this project include: the Illinois State Board of Education, Illinois Community…

  12. A machine learning approach to graph-theoretical cluster expansions of the energy of adsorbate layers

    Science.gov (United States)

    Vignola, Emanuele; Steinmann, Stephan N.; Vandegehuchte, Bart D.; Curulla, Daniel; Stamatakis, Michail; Sautet, Philippe

    2017-08-01

    The accurate description of the energy of adsorbate layers is crucial for the understanding of chemistry at interfaces. For heterogeneous catalysis, not only the interaction of the adsorbate with the surface but also the adsorbate-adsorbate lateral interactions significantly affect the activation energies of reactions. Modeling the interactions of the adsorbates with the catalyst surface and with each other can be efficiently achieved in the cluster expansion Hamiltonian formalism, which has recently been implemented in a graph-theoretical kinetic Monte Carlo (kMC) scheme to describe multi-dentate species. Automating the development of the cluster expansion Hamiltonians for catalytic systems is challenging and requires the mapping of adsorbate configurations for extended adsorbates onto a graphical lattice. The current work adopts machine learning methods to reach this goal. Clusters are automatically detected based on formalized, but intuitive chemical concepts. The corresponding energy coefficients for the cluster expansion are calculated by an inversion scheme. The potential of this method is demonstrated for the example of ethylene adsorption on Pd(111), for which we propose several expansions, depending on the graphical lattice. It turns out that for this system, the best description is obtained as a combination of single molecule patterns and a few coupling terms accounting for lateral interactions.

  13. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 1: Executive Summary, of a 15-Volume Set of Skills Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    Science.gov (United States)

    Texas State Technical Coll., Waco.

    The Machine Tool Advanced Skills Technology (MAST) consortium was formed to address the shortage of skilled workers for the machine tools and metals-related industries. Featuring six of the nation's leading advanced technology centers, the MAST consortium developed, tested, and disseminated industry-specific skill standards and model curricula for…

  14. Clustering technique-based least square support vector machine for EEG signal classification.

    Science.gov (United States)

    Siuly; Li, Yan; Wen, Peng Paul

    2011-12-01

    This paper presents a new approach called clustering technique-based least square support vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is performed in two stages. In the first stage, clustering technique (CT) has been used to extract representative features of EEG data. In the second stage, least square support vector machine (LS-SVM) is applied to the extracted features to classify two-class EEG signals. To demonstrate the effectiveness of the proposed method, several experiments have been conducted on three publicly available benchmark databases, one for epileptic EEG data, one for mental imagery tasks EEG data and another one for motor imagery EEG data. Our proposed approach achieves an average sensitivity, specificity and classification accuracy of 94.92%, 93.44% and 94.18%, respectively, for the epileptic EEG data; 83.98%, 84.37% and 84.17% respectively, for the motor imagery EEG data; and 64.61%, 58.77% and 61.69%, respectively, for the mental imagery tasks EEG data. The performance of the CT-LS-SVM algorithm is compared in terms of classification accuracy and execution (running) time with our previous study where simple random sampling with a least square support vector machine (SRS-LS-SVM) was employed for EEG signal classification. We also compare the proposed method with other existing methods in the literature for the three databases. The experimental results show that the proposed algorithm can produce a better classification rate than the previous reported methods and takes much less execution time compared to the SRS-LS-SVM technique. The research findings in this paper indicate that the proposed approach is very efficient for classification of two-class EEG signals.

  15. Teaching a functional leisure skill cluster to rehabilitation clients: the art of macrame.

    Science.gov (United States)

    Halasz-Dees, M; Cuvo, A J

    1986-01-01

    Disabled people often do not use leisure time productively. Past research has focused on teaching specific recreational activities isolated from related skills that would provide subjects a functional independent living repertoire. In the present study disabled subjects were taught the art of macrame. Additionally, they role-played related shopping skills such as buying materials, engaging in appropriate social-interpersonal skills, making monetary transactions, and securing their own transportation to and from the store. Subjects were taught six basic macrame knots using an instructional manual, series of error-correction procedures, and social reinforcement. After mastering those basic knots they independently used the instructional materials to make three complete macrame projects without direct instruction on the projects themselves. Subjects also demonstrated skill maintenance and generalization by making a novel project after independently engaging in all relevant shopping behavior. Two varieties of the multiple baseline design were employed. The importance of teaching a leisure skill cluster and adapting instructional materials were emphasized.

  16. Investigating nurses' knowledge, attitudes, and skills patterns towards clinical management system: results of a cluster analysis.

    Science.gov (United States)

    Chan, M F

    2006-09-01

    To determine whether definable subtypes exist within a cohort of Hong Kong nurses as related to the clinical management system use in their clinical practices based on their knowledge, attitudes, skills, and background factors. Data were collected using a structured questionnaire. The sample of 242 registered nurses was recruited from three hospitals in Hong Kong. The study employs personal and demographic variables, knowledge, attitudes, and skills scale. A cluster analysis yielded two clusters. Each cluster represents a different profile of Hong Kong nurses on the clinical management system use in their clinical practices. The first group (Cluster 1) was labeled 'lower attitudes, less skilful and average knowledge' group, and represented 55.4% of the total respondents. The second group (Cluster 2) was labeled as 'positive attitudes, good knowledge but less skilful'. They comprised almost 44.6% of this nursing sample. Cluster 2 had more older nurses, the majority were educated to the baccalaureate or above level, with more than 10 years working experience, and they held a more senior ranking then Cluster 1. A clear profile of Hong Kong nurses may benefit healthcare professionals in making appropriate education or assistance to prompt the use of the clinical management system by nurses an officially recognized profession. The findings were useful in determining nurse-users' specific needs and their preferences for modification of the clinical management system. Such findings should be used to formulate strategies to encourage nurses to resolve actual problems following computer training and to increase the depth and breadth of nurses' knowledge, attitudes, and skills toward such system.

  17. A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine

    2015-12-01

    Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environment and the acquired condition monitoring data are usually noisy and subject to a high level of uncertainty/unpredictability, which complicates prognostics. The complexity further increases, when there is absence of prior knowledge about ground truth (or failure definition). For such issues, data-driven prognostics can be a valuable solution without deep understanding of system physics. This paper contributes a new data-driven prognostics approach namely, an "enhanced multivariate degradation modeling," which enables modeling degrading states of machinery without assuming a homogeneous pattern. In brief, a predictability scheme is introduced to reduce the dimensionality of the data. Following that, the proposed prognostics model is achieved by integrating two new algorithms namely, the summation wavelet-extreme learning machine and subtractive-maximum entropy fuzzy clustering to show evolution of machine degradation by simultaneous predictions and discrete state estimation. The prognostics model is equipped with a dynamic failure threshold assignment procedure to estimate RUL in a realistic manner. To validate the proposition, a case study is performed on turbofan engines data from PHM challenge 2008 (NASA), and results are compared with recent publications.

  18. Development of Estimating Equation of Machine Operational Skill by Utilizing Eye Movement Measurement and Analysis of Stress and Fatigue

    Directory of Open Access Journals (Sweden)

    Satoshi Suzuki

    2013-01-01

    Full Text Available For an establishment of a skill evaluation method for human support systems, development of an estimating equation of the machine operational skill is presented. Factors of the eye movement such as frequency, velocity, and moving distance of saccade were computed using the developed eye gaze measurement system, and the eye movement features were determined from these factors. The estimating equation was derived through an outlier test (to eliminate nonstandard data and a principal component analysis (to find dominant components. Using a cooperative carrying task (cc-task simulator, the eye movement and operational data of the machine operators were recorded, and effectiveness of the derived estimating equation was investigated. As a result, it was confirmed that the estimating equation was effective strongly against actual simple skill levels (r=0.56–0.84. In addition, effects of internal condition such as fatigue and stress on the estimating equation were analyzed. Using heart rate (HR and coefficient of variation of R-R interval (Cvrri. Correlation analysis between these biosignal indexes and the estimating equation of operational skill found that the equation reflected effects of stress and fatigue, although the equation could estimate the skill level adequately.

  19. Driver style and driver skillsclustering drivers differing in their potential danger in traffic

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Møller, Mette; Prato, Carlo Giacomo

    and the DSI. Moreover, the joint use of the two instruments was applied to identify sub-groups of drivers that differ in their potential danger in traffic, as well as to test for heterogeneity across the population, namely whether the sub-groups of drivers differed in characteristics such as age, gender......, annual mileage and accident involvement. 3908 drivers aged 18–84 participated in the survey. The results suggested that the drivers have good insight into their own driving ability, as the driving skill level mirrored the frequency of aberrant driving behaviors. K-means cluster analysis revealed four...... distinct clusters that differed in the frequency of aberrant driving behavior and driving skills, as well as individual characteristics and driving related factors such as annual mileage, accident frequency and number of tickets and fines. Thus, two sub-groups were identified as more unsafe than the two...

  20. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 7: Industrial Maintenance Technology, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    Science.gov (United States)

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  1. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 11: Computer-Aided Manufacturing & Advanced CNC, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    Science.gov (United States)

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  2. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 14: Automated Equipment Technician (CIM), of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    Science.gov (United States)

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  3. Driver style and driver skillsclustering drivers differing in their potential danger in traffic

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Møller, Mette; Prato, Carlo Giacomo

    The Driver Behavior Questionnaire (DBQ) and the Driver Skill Inventory (DSI) are two of the most frequently used measures of driving style and driving skill. The motivation behind the present study was to test drivers’ insight into their own driving ability based on a combined use of the DBQ......, annual mileage and accident involvement. 3908 drivers aged 18–84 participated in the survey. The results suggested that the drivers have good insight into their own driving ability, as the driving skill level mirrored the frequency of aberrant driving behaviors. K-means cluster analysis revealed four...... and the DSI. Moreover, the joint use of the two instruments was applied to identify sub-groups of drivers that differ in their potential danger in traffic, as well as to test for heterogeneity across the population, namely whether the sub-groups of drivers differed in characteristics such as age, gender...

  4. SETTING OF TASK OF OPTIMIZATION OF THE ACTIVITY OF A MACHINE-BUILDING CLUSTER COMPANY

    Directory of Open Access Journals (Sweden)

    A. V. Romanenko

    2014-01-01

    Full Text Available The work is dedicated to the development of methodological approaches to the management of machine-building enterprise on the basis of cost reduction, optimization of the portfolio of orders and capacity utilization in the process of operational management. Evaluation of economic efficiency of such economic entities of the real sector of the economy is determined, including the timing of orders, which depend on the issues of building a production facility, maintenance of fixed assets and maintain them at a given level. Formulated key components of economic-mathematical model of industrial activity and is defined as the optimization criterion. As proposed formula accumulating profits due to production capacity and technology to produce products current direct variable costs, the amount of property tax and expenses appearing as a result of manifestations of variance when performing replacement of production tasks for a single period of time. The main component of the optimization of the production activity of the enterprise on the basis of this criterion is the vector of direct variable costs. It depends on the number of types of products in the current portfolio of orders, production schedules production, the normative time for the release of a particular product available Fund time efficient production positions, the current valuation for certain groups of technological operations and the current priority of operations for the degree of readiness performed internal orders. Modeling of industrial activity based on the proposed provisions would allow the enterprises of machine-building cluster, active innovation, improve the efficient use of available production resources by optimizing current operations at the high uncertainty of the magnitude of the demand planning and carrying out maintenance and routine repairs.

  5. Enhancing Fine Motor Skills of Wards with Special Needs Using Cluster Model of Cognition

    CERN Document Server

    Nair, T R Gopalakrishnan; Bukkambudhi, Ananda

    2010-01-01

    Technology offers great potential to overcome physical barriers of human race. This paper presents the methods of enhanced learning applicable to children having special needs using better human-computer interaction. The Audio-Visual (AV) effects that the graphic tools or animations help in achieving better learning, understanding, remembering and performance from such students. The 3L-R Cluster Program Model enable them to look into pictures and animated objects while listening to the related audio. It also motivates them to do the FMS development activities like drawing, coloring, tracing etc., certain types of games in the clustered model will help the children to improve concentration, thinking, reasoning, cognitive skills and the eye-to hand co-ordination. Here we introduced a novel cluster model along with the methodology described which provides an ample exposure to the effectiveness of the training. Classify the students with similar problems or disability and the associated curriculum of modified tea...

  6. Skill for machining worm screw with NC lathe%数控车床上蜗杆的加工技巧

    Institute of Scientific and Technical Information of China (English)

    赵健

    2001-01-01

    介绍了一种在数控车床上加工大螺距蜗杆的切削技巧以及相应的数控程序。%The machining skill and relevant NC program of machining worm screw with large pitch using a NC lathe are introduced.

  7. The Fuzzy Cluster Analysis in Identification of Key Temperatures in Machine Tool

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measu...

  8. Taxonomy of Manufacturing Flexibility at Manufacturing Companies Using Imperialist Competitive Algorithms, Support Vector Machines and Hierarchical Cluster Analysis

    Directory of Open Access Journals (Sweden)

    M. Khoobiyan

    2017-04-01

    Full Text Available Manufacturing flexibility is a multidimensional concept and manufacturing companies act differently in using these dimensions. The purpose of this study is to investigate taxonomy and identify dominant groups of manufacturing flexibility. Dimensions of manufacturing flexibility are extracted by content analysis of literature and expert judgements. Manufacturing flexibility was measured by using a questionnaire developed to survey managers of manufacturing companies. The sample size was set at 379. To identify dominant groups of flexibility based on dimensions of flexibility determined, Hierarchical Cluster Analysis (HCA, Imperialist Competitive Algorithms (ICAs and Support Vector Machines (SVMs were used by cluster validity indices. The best algorithm for clustering was SVMs with three clusters, designated as leading delivery-based flexibility, frugal flexibility and sufficient plan-based flexibility.

  9. The Relative Costs of American Men, Skills, and Machines: A Long View.

    Science.gov (United States)

    Williamson, Jeffrey G.

    The document is based on a premise that mid-twentieth century experience with income distribution cannot be adequately understood without a better knowledge of the long-term macroeconomic forces that have endogenously determined the wage structure. The secular performance of the price of skills and the occupational wage structure are important to…

  10. Efficacy of communication skills training on colorectal cancer screening by GPs: a cluster randomised controlled trial.

    Science.gov (United States)

    Aubin-Auger, I; Laouénan, C; Le Bel, J; Mercier, A; Baruch, D; Lebeau, J P; Youssefian, A; Le Trung, T; Peremans, L; Van Royen, P

    2016-01-01

    Colorectal cancer (CRC) mass screening has been implemented in France since 2008. Participation rates remain too low. The objective of this study was to test if the implementation of a training course focused on communication skills among general practitioners (GP) would increase the delivery of gaiac faecal occult blood test and CRC screening participation among the target population of each participating GP. A cluster randomised controlled trial was conducted with GP's practice as a cluster unit. GPs from practices in the control group were asked to continue their usual care. GPs of the intervention group received a 4-h educational training, built with previous qualitative data on CRC screening focusing on doctor-patient communication with a follow-up of 7 months for both groups. The primary outcome measure was the patients' participation rate in the target population for each GP. Seventeen GPs (16 practices) in intervention group and 28 GPs (19 practices) in control group participated. The patients' participation rate in the intervention group were 36.7% vs. 24.5% in the control group (P = 0.03). Doctor-patient communication should be developed and appear to be one of the possible targets of improvement patients adherence and participation rate in the target population for CRC mass screening.

  11. Single-Trial Classification of Bistable Perception by Integrating Empirical Mode Decomposition, Clustering, and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Hualou Liang

    2008-04-01

    Full Text Available We propose an empirical mode decomposition (EMD- based method to extract features from the multichannel recordings of local field potential (LFP, collected from the middle temporal (MT visual cortex in a macaque monkey, for decoding its bistable structure-from-motion (SFM perception. The feature extraction approach consists of three stages. First, we employ EMD to decompose nonstationary single-trial time series into narrowband components called intrinsic mode functions (IMFs with time scales dependent on the data. Second, we adopt unsupervised K-means clustering to group the IMFs and residues into several clusters across all trials and channels. Third, we use the supervised common spatial patterns (CSP approach to design spatial filters for the clustered spatiotemporal signals. We exploit the support vector machine (SVM classifier on the extracted features to decode the reported perception on a single-trial basis. We demonstrate that the CSP feature of the cluster in the gamma frequency band outperforms the features in other frequency bands and leads to the best decoding performance. We also show that the EMD-based feature extraction can be useful for evoked potential estimation. Our proposed feature extraction approach may have potential for many applications involving nonstationary multivariable time series such as brain-computer interfaces (BCI.

  12. Machine learning. Clustering by fast search and find of density peaks.

    Science.gov (United States)

    Rodriguez, Alex; Laio, Alessandro

    2014-06-27

    Cluster analysis is aimed at classifying elements into categories on the basis of their similarity. Its applications range from astronomy to bioinformatics, bibliometrics, and pattern recognition. We propose an approach based on the idea that cluster centers are characterized by a higher density than their neighbors and by a relatively large distance from points with higher densities. This idea forms the basis of a clustering procedure in which the number of clusters arises intuitively, outliers are automatically spotted and excluded from the analysis, and clusters are recognized regardless of their shape and of the dimensionality of the space in which they are embedded. We demonstrate the power of the algorithm on several test cases. Copyright © 2014, American Association for the Advancement of Science.

  13. Driver style and driver skillClustering sub-groups of drivers differing in their potential danger in traffic

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Møller, Mette; Prato, Carlo Giacomo

    based on a combined use of the DBQ and the DSI. Moreover, the joint use of the two instruments was applied to identify sub-groups of drivers that differ in their potential danger in traffic (as measured by frequency of aberrant driving behaviors and level of driving skills), as well as to test whether...... the sub-groups of drivers differed in characteristics such as age, gender, annual mileage and accident involvement. 3908 drivers aged 18–84 participated in the survey. The results suggested that the drivers are consistent in their reporting of driving ability, as the self-reported driving skill level...... mirrored the self-reported frequency of aberrant driving behaviors. K-means cluster analysis revealed four distinct clusters that differed in the frequency of aberrant driving behavior and driving skills, as well as individual characteristics and driving related factors such as annual mileage, accident...

  14. Using Trajectory Clusters to Define the Most Relevant Features for Transient Stability Prediction Based on Machine Learning Method

    Directory of Open Access Journals (Sweden)

    Luyu Ji

    2016-11-01

    Full Text Available To achieve rapid real-time transient stability prediction, a power system transient stability prediction method based on the extraction of the post-fault trajectory cluster features of generators is proposed. This approach is conducted using data-mining techniques and support vector machine (SVM models. First, the post-fault rotor angles and generator terminal voltage magnitudes are considered as the input vectors. Second, we construct a high-confidence dataset by extracting the 27 trajectory cluster features obtained from the chosen databases. Then, by applying a filter–wrapper algorithm for feature selection, we obtain the final feature set composed of the eight most relevant features for transient stability prediction, called the global trajectory clusters feature subset (GTCFS, which are validated by receiver operating characteristic (ROC analysis. Comprehensive simulations are conducted on a New England 39-bus system under various operating conditions, load levels and topologies, and the transient stability predicting capability of the SVM model based on the GTCFS is extensively tested. The experimental results show that the selected GTCFS features improve the prediction accuracy with high computational efficiency. The proposed method has distinct advantages for transient stability prediction when faced with incomplete Wide Area Measurement System (WAMS information, unknown operating conditions and unknown topologies and significantly improves the robustness of the transient stability prediction system.

  15. EFFECT OF DATA TRUNCATION IN AN IMPLEMENTATION OF PIXEL CLUSTERING ON A CUSTOM COMPUTING MACHINE

    Energy Technology Data Exchange (ETDEWEB)

    M. LEESER; J. THEILER; ET AL

    2000-08-01

    We investigate the effect of truncating the precision of hyperspectral image data for the purpose of more efficiently segmenting the image using a variant of k-means clustering. We describe the implementation of the algorithm on field-programmable gate array (FPGA) hardware. Truncating the data to only a few bits per pixel in each spectral channel permits a more compact hardware design, enabling greater parallelism, and ultimately a more rapid execution. It also enables the storage of larger images in the onboard memory. In exchange for faster clustering, however, one trades off the quality of the produced segmentation. We find, however, that the clustering algorithm can tolerate considerable data truncation with little degradation in cluster quality. This robustness to truncated data can be extended by computing the cluster centers to a few more bits of precision than the data. Since there are so many more pixels than centers, the more aggressive data truncation leads to significant gains in the number of pixels that can be stored in memory and processed in hardware concurrently.

  16. A compilation of redshifts and velocity dispersions for Abell clusters (Struble and Rood 1987): Documentation for the machine-readable version

    Science.gov (United States)

    Warren, Wayne H., Jr.

    1989-01-01

    The machine readable version of the compilation, as it is currently being distributed from the Astronomical Data Center, is described. The catalog contains redshifts and velocity dispersions for all Abell clusters for which these data had been published up to 1986 July. Also included are 1950 equatorial coordinates for the centers of the listed clusters, numbers of observations used to determine the redshifts, and bibliographical references citing the data sources.

  17. Reducing child conduct problems and promoting social skills in a middle-income country: cluster randomised controlled trial†

    OpenAIRE

    Baker-Henningham, Helen; Scott, Stephen; Jones, Kelvyn; Walker, Susan

    2012-01-01

    Background There is an urgent need for effective, affordable interventions to prevent child mental health problems in low- and middle-income countries. Aims To determine the effects of a universal pre-school-based intervention on child conduct problems and social skills at school and at home. Method In a cluster randomised design, 24 community pre-schools in inner-city areas of Kingston, Jamaica, were randomly assigned to receive the Incredible Years Teacher Training intervention (n = 12) or ...

  18. Real Time Classification and Clustering Of IDS Alerts Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    T. Subbulakshmi

    2010-01-01

    Full Text Available Intrusion Detection Systems (IDS monitor a secured network for the evidence of maliciousactivities originating either inside or outside. Upon identifying a suspicious traffic, IDSgenerates and logs an alert. Unfortunately, most of the alerts generated are either false positive,i.e. benign traffic that has been classified as intrusions, or irrelevant, i.e. attacks that are notsuccessful. The abundance of false positive alerts makes it difficult for the security analyst tofind successful attacks and take remedial action. This paper describes a two phase automaticalert classification system to assist the human analyst in identifying the false positives. In thefirst phase, the alerts collected from one or more sensors are normalized and similar alerts aregrouped to form a meta-alert. These meta-alerts are passively verified with an asset database tofind out irrelevant alerts. In addition, an optional alert generalization is also performed for rootcause analysis and thereby reduces false positives with human interaction. In the second phase,the reduced alerts are labeled and passed to an alert classifier which uses machine learningtechniques for building the classification rules. This helps the analyst in automatic classificationof the alerts. The system is tested in real environments and found to be effective in reducing thenumber of alerts as well as false positives dramatically, and thereby reducing the workload ofhuman analyst.

  19. REAL TIME CLASSIFICATION AND CLUSTERING OF IDS ALERTS USING MACHINE LEARNING ALGORITHMS

    Directory of Open Access Journals (Sweden)

    T. Subbulakshmi

    2010-01-01

    Full Text Available Intrusion Detection Systems (IDS monitor a secured network for the evidence of malicious activities originating either inside or outside. Upon identifying a suspicious traffic, IDS generates and logs an alert. Unfortunately, most of the alerts generated are either false positive, i.e. benign traffic that has been classified as intrusions, or irrelevant, i.e. attacks that are not successful. The abundance of false positive alerts makes it difficult for the security analyst to find successful attacks and take remedial action. This paper describes a two phase automatic alert classification system to assist the human analyst in identifying the false positives. In the first phase, the alerts collected from one or more sensors are normalized and similar alerts are grouped to form a meta-alert. These meta-alerts are passively verified with an asset database to find out irrelevant alerts. In addition, an optional alert generalization is also performed for root cause analysis and thereby reduces false positives with human interaction. In the second phase, the reduced alerts are labeled and passed to an alert classifier which uses machine learning techniques for building the classification rules. This helps the analyst in automatic classification of the alerts. The system is tested in real environments and found to be effective in reducing the number of alerts as well as false positives dramatically, and thereby reducing the workload of human analyst.

  20. Clustering of the Self-Organizing Map based Approach in Induction Machine Rotor Faults Diagnostics

    Directory of Open Access Journals (Sweden)

    Ahmed TOUMI

    2009-12-01

    Full Text Available Self-Organizing Maps (SOM is an excellent method of analyzingmultidimensional data. The SOM based classification is attractive, due to itsunsupervised learning and topology preserving properties. In this paper, theperformance of the self-organizing methods is investigated in induction motorrotor fault detection and severity evaluation. The SOM is based on motor currentsignature analysis (MCSA. The agglomerative hierarchical algorithms using theWard’s method is applied to automatically dividing the map into interestinginterpretable groups of map units that correspond to clusters in the input data. Theresults obtained with this approach make it possible to detect a rotor bar fault justdirectly from the visualization results. The system is also able to estimate theextent of rotor faults.

  1. Availability Of JobTracker Machine In Hadoop/MapReduce Zookeeper Coordinated Clusters

    Directory of Open Access Journals (Sweden)

    Ekpe Okorafor

    2012-06-01

    Full Text Available It is difficult to use the traditional Message Passing Interface (MPI approach to implement synchronization, coordination, and prevent deadlocks in distributed systems. This difficulty is lessened by the use of Apache's Hadoop/MapReduce and Zookeeper to provide Fault Tolerance in a Homogeneously Distributed Hardware/Software environment. A mathematical model for the availability of the JobTracker in Hadoop/MapReduce using Zookeeper's Leader Election Service is presented in this paper. Although the availability is less than what is expected in f+1 Fault Tolerance systems for crash failures, this approach makes coordination and synchronization easy, reduces the effect of Byzantine faults and provides Fault Tolerance for distributed systems. The results obtained show that the availability changes with change in the number of Zookeeper servers. This model can help determine how many servers are optimal for high availability, from which vendor they must be purchased, and when to use a Zookeeper coordinated Hadoop cluster to perform safety critical tasks.

  2. The combination of a histogram-based clustering algorithm and support vector machine for the diagnosis of osteoporosis

    Energy Technology Data Exchange (ETDEWEB)

    Heo, Min Suk; Kavitha, Muthu Subash [Dept. of Oral and Maxillofacial Radiology and Dental Research Institute, School of Dentistry, Seoul National University, Seoul (Korea, Republic of); Asano, Akira [Graduate School of Engineering, Hiroshima University, Hiroshima (Japan); Taguchi, Akira [Dept. of Oral and Maxillofacial Radiology, Matsumoto Dental University, Nagano (Japan)

    2013-09-15

    To prevent low bone mineral density (BMD), that is, osteoporosis, in postmenopausal women, it is essential to diagnose osteoporosis more precisely. This study presented an automatic approach utilizing a histogram-based automatic clustering (HAC) algorithm with a support vector machine (SVM) to analyse dental panoramic radiographs (DPRs) and thus improve diagnostic accuracy by identifying postmenopausal women with low BMD or osteoporosis. We integrated our newly-proposed histogram-based automatic clustering (HAC) algorithm with our previously-designed computer-aided diagnosis system. The extracted moment-based features (mean, variance, skewness, and kurtosis) of the mandibular cortical width for the radial basis function (RBF) SVM classifier were employed. We also compared the diagnostic efficacy of the SVM model with the back propagation (BP) neural network model. In this study, DPRs and BMD measurements of 100 postmenopausal women patients (aged >50 years), with no previous record of osteoporosis, were randomly selected for inclusion. The accuracy, sensitivity, and specificity of the BMD measurements using our HAC-SVM model to identify women with low BMD were 93.0% (88.0%-98.0%), 95.8% (91.9%-99.7%) and 86.6% (79.9%-93.3%), respectively, at the lumbar spine; and 89.0% (82.9%-95.1%), 96.0% (92.2%-99.8%) and 84.0% (76.8%-91.2%), respectively, at the femoral neck. Our experimental results predict that the proposed HAC-SVM model combination applied on DPRs could be useful to assist dentists in early diagnosis and help to reduce the morbidity and mortality associated with low BMD and osteoporosis.

  3. A Cluster of Technical Teaching Skills--Acquisition through Microsimulation and Evaluation through Microteaching.

    Science.gov (United States)

    Casteel, J. Doyle; Gregory, John W.

    This study was designed to investigate the degree to which skills may be learned and practiced through microsimulation and then used under microteaching conditions. This investigation was conducted to determine the following: (a) if preservice teachers who have acquired and practiced complex teaching skills through microsimulation employ these…

  4. Functional Analytic Psychotherapy (FAP) for Cluster B Personality Disorders: Creating Meaning, Mattering, and Skills

    Science.gov (United States)

    Pankey, Julieann

    2012-01-01

    There are ten identified personality disorders, broken into three clusters: A, B, and C. Individuals with a cluster B diagnosis may demonstrate marked displays of emotional instability, erratic and disruptive patterns around interpersonal relationships, a myopic and restricted range of affect, a pronounced lack of empathy and insight, barriers…

  5. Combining cluster analysis, feature selection and multiple support vector machine models for the identification of human ether-a-go-go related gene channel blocking compounds.

    Science.gov (United States)

    Nisius, Britta; Göller, Andreas H; Bajorath, Jürgen

    2009-01-01

    Blockade of the human ether-a-go-go related gene potassium channel is regarded as a major cause of drug toxicity and associated with severe cardiac side-effects. A variety of in silico models have been reported to aid in the identification of compounds blocking the human ether-a-go-go related gene channel. Herein, we present a classification approach for the detection of diverse human ether-a-go-go related gene blockers that combines cluster analysis of training data, feature selection and support vector machine learning. Compound learning sets are first divided into clusters of similar molecules. For each cluster, independent support vector machine models are generated utilizing preselected MACCS structural keys as descriptors. These models are combined to predict human ether-a-go-go related gene inhibition of our large compound data set with consistent experimental measurements (i.e. only patch clamp measurements on mammalian cell lines). Our combined support vector machine model achieves a prediction accuracy of 85% on this data set and performs better than alternative methods used for comparison. We also find that structural keys selected on the basis of statistical criteria are associated with molecular substructures implicated in human ether-a-go-go related gene channel binding.

  6. Machining Feature Recognition Based on Surface Clustering%基于表面聚类优化的加工特征识别方法

    Institute of Scientific and Technical Information of China (English)

    汤岑书; 褚学宁; 孙习武; 苏於梁

    2009-01-01

    To realize the effective integration of CAD and CAPP system, an approach of machining feature recognition was proposed based on the generation and clustering of surface machining methods. Three kinds of information models, such as manufacturing resource, machined surface and machining method were built. A concept of cutting mode was proposed and used for generating the machining methods of part surfaces. Aiming at minimizing the number of tool type and the number of setups used, an optimal model for surface clustering was established to select the best machining method for every surface. Surfaces which can be simultaneously machined by a common type of tool in the same setup were then recognized as a machining feature. Finally, an example part was used to test the validity and effectiveness of the approach proposed, and the final results illustrate that the approach can effectively solve some problems such as the recognition of intersecting features which are difficult to traditional feature recognition approaches.%为了实现计算机辅助设计与计算机辅助工艺设计系统的有效集成,提出了以表面加工方法生成和聚类优化为基础的加工特征识别新方法.基于加工资源、加工表面和加工方法3类信息模型,引出了切削模式概念和表面加工方法生成的原理.以刀具种类数和零件装夹次数最少为目标,建立了表面聚类优化模型,为加工表面选择最优加工方法,并把可用同类刀具、在同一装夹下连续加工的一组表面聚为一个加工特征.通过实例测试,验证了该方法的正确性和有效性.

  7. Promoting the purchase of low-calorie foods from school vending machines: A cluster-randomized controlled study

    NARCIS (Netherlands)

    Kocken, P.L.; Eeuwijk, J.; Kesten, N.M.C. van; Dusseldorp, E.; Buijs, G.; Bassa-Dafesh, Z.; Snel, J.

    2012-01-01

    BACKGROUND: Vending machines account for food sales and revenue in schools. We examined 3 strategies for promoting the sale of lower-calorie food products from vending machines in high schools in the Netherlands. METHODS: A school-based randomized controlled trial was conducted in 13 experimental

  8. Promoting the Purchase of Low-Calorie Foods from School Vending Machines: A Cluster-Randomized Controlled Study

    Science.gov (United States)

    Kocken, Paul L.; Eeuwijk, Jennifer; van Kesteren, Nicole M.C.; Dusseldorp, Elise; Buijs, Goof; Bassa-Dafesh, Zeina; Snel, Jeltje

    2012-01-01

    Background: Vending machines account for food sales and revenue in schools. We examined 3 strategies for promoting the sale of lower-calorie food products from vending machines in high schools in the Netherlands. Methods: A school-based randomized controlled trial was conducted in 13 experimental schools and 15 control schools. Three strategies…

  9. Fog Prediction for Road Traffic Safety in a Coastal Desert Region: Improvement of Nowcasting Skills by the Machine-Learning Approach

    Science.gov (United States)

    Bartoková, Ivana; Bott, Andreas; Bartok, Juraj; Gera, Martin

    2015-12-01

    A new model for nowcasting fog events in the coastal desert area of Dubai is presented, based on a machine-learning algorithm—decision-tree induction. In the investigated region high frequency observations from automatic weather stations were utilized as a database for the analysis of useful patterns. The induced decision trees yield for the first six forecasting hours increased prediction skill when compared to the coupled Weather Research and Forecasting (WRF) model and the PAFOG fog model (Bartok et al., Boundary-Layer Meteorol 145:485-506, 2012). The decision tree results were further improved by integrating the output of the coupled numerical fog forecasting models in the training database of the decision tree. With this treatment, the statistical quality measures, i.e. the probability of detection, the false alarm ratio, and the Gilbert's skill score, achieved values of 0.88, 0.19, and 0.69, respectively. From these results we conclude that the best fog forecast in the Dubai region is obtained by applying for the first six forecast hours the newly-developed machine-learning algorithm, while for forecast times exceeding 6 h the coupled numerical models are the best choice.

  10. A Fault Diagnosis Approach for Gas Turbine Exhaust Gas Temperature Based on Fuzzy C-Means Clustering and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhi-tao Wang

    2015-01-01

    Full Text Available As an important gas path performance parameter of gas turbine, exhaust gas temperature (EGT can represent the thermal health condition of gas turbine. In order to monitor and diagnose the EGT effectively, a fusion approach based on fuzzy C-means (FCM clustering algorithm and support vector machine (SVM classification model is proposed in this paper. Considering the distribution characteristics of gas turbine EGT, FCM clustering algorithm is used to realize clustering analysis and obtain the state pattern, on the basis of which the preclassification of EGT is completed. Then, SVM multiclassification model is designed to carry out the state pattern recognition and fault diagnosis. As an example, the historical monitoring data of EGT from an industrial gas turbine is analyzed and used to verify the performance of the fusion fault diagnosis approach presented in this paper. The results show that this approach can make full use of the unsupervised feature extraction ability of FCM clustering algorithm and the sample classification generalization properties of SVM multiclassification model, which offers an effective way to realize the online condition recognition and fault diagnosis of gas turbine EGT.

  11. Hadoop cluster deployment

    CERN Document Server

    Zburivsky, Danil

    2013-01-01

    This book is a step-by-step tutorial filled with practical examples which will show you how to build and manage a Hadoop cluster along with its intricacies.This book is ideal for database administrators, data engineers, and system administrators, and it will act as an invaluable reference if you are planning to use the Hadoop platform in your organization. It is expected that you have basic Linux skills since all the examples in this book use this operating system. It is also useful if you have access to test hardware or virtual machines to be able to follow the examples in the book.

  12. Basic life support skill improvement with newly designed renewal programme: cluster randomised study of small-group-discussion method versus practice-while-watching method.

    Science.gov (United States)

    Na, Ji Ung; Lee, Tae Rim; Kang, Mun Ju; Shin, Tae Gun; Sim, Min Seob; Jo, Ik Joon; Song, Keun Jeong; Jeong, Yeon Kwon

    2014-12-01

    For the basic life support (BLS) renewal course, we have devised a new educational programme entitled a small-group-discussion (SGD) programme using personalised video-based debriefing. We compared the efficacy in BLS skill improvement of the SGD programme with the currently used practice-while-watching (PWW) programme, which uses a standardised education video. This was a prospective, cluster randomised study, conducted in a single centre, over 6 months from May 2009 to October 2009. Training was performed in two groups of participants, each group with a different renewal education programme. The efficacy of the programmes was compared using the modified Cardiff test and skill-reporting manikins. Results from 2169 participants were analysed: 1061 in the SGD programme group and 1108 in the PWW programme group. There were no differences between groups on the pretest, either in compression or non-compression skills. However, on the post-test, the SGD programme gave better results for both compression skills and non-compression skills. The new SGD renewal programme is more effective than the PWW programme for improving skills in BLS renewal training. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  13. Teaching a machine to see: unsupervised image segmentation and categorisation using growing neural gas and hierarchical clustering

    CERN Document Server

    Hocking, Alex; Davey, Neil; Sun, Yi

    2015-01-01

    We present a novel unsupervised learning approach to automatically segment and label images in astronomical surveys. Automation of this procedure will be essential as next-generation surveys enter the petabyte scale: data volumes will exceed the capability of even large crowd-sourced analyses. We demonstrate how a growing neural gas (GNG) can be used to encode the feature space of imaging data. When coupled with a technique called hierarchical clustering, imaging data can be automatically segmented and labelled by organising nodes in the GNG. The key distinction of unsupervised learning is that these labels need not be known prior to training, rather they are determined by the algorithm itself. Importantly, after training a network can be be presented with images it has never 'seen' before and provide consistent categorisation of features. As a proof-of-concept we demonstrate application on data from the Hubble Space Telescope Frontier Fields: images of clusters of galaxies containing a mixture of galaxy type...

  14. Street ball, swim team and the sour cream machine: a cluster analysis of out of school time participation portfolios.

    Science.gov (United States)

    Nelson, Ingrid Ann; Gastic, Billie

    2009-10-01

    Adolescents spend only a fraction of their waking hours in school and what they do with the rest of their time varies dramatically. Despite this, research on out-of-school time has largely focused on structured programming. The authors analyzed data from the Educational Longitudinal Study of 2002 (ELS:2002) to examine the out-of-school time activity portfolios of 6,338 high school sophomores, accounting for time spent in school clubs and sports as well as 17 other activities. The analytical sample was balanced with respect to sex and racially and ethnically diverse: 49% female, 67% White, 10% Latino, 10% African American, and 6% Asian and Pacific Islander. Approximately 76% of the sample attended public schools, 30% were in the highest socioeconomic quartile, and 20% were in the lowest socioeconomic quartile. The authors identified five distinct out-of-school time activity portfolios based on a cluster analysis. The demographic profiles of students by portfolio type differed significantly with respect to sex, race/ethnicity, socioeconomic status, school type and location. Students by portfolio type also differed significantly in terms of measures of academic success, school behavior, victimization and perceptions of school climate, controlling for covariates. These findings underscore the importance of more complex considerations of adolescents' out-of-school time.

  15. An Efficient Diagnosis System for Parkinson’s Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

    Directory of Open Access Journals (Sweden)

    Chao Ma

    2014-01-01

    Full Text Available A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM, has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC curve (AUC, f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance.

  16. SU-D-204-01: A Methodology Based On Machine Learning and Quantum Clustering to Predict Lung SBRT Dosimetric Endpoints From Patient Specific Anatomic Features

    Energy Technology Data Exchange (ETDEWEB)

    Lafata, K; Ren, L; Wu, Q; Kelsey, C; Hong, J; Cai, J; Yin, F [Duke University Medical Center, Durham, NC (United States)

    2016-06-15

    Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space to identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong

  17. 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

  18. Minimal improvement of nurses' motivational interviewing skills in routine diabetes care one year after training: a cluster randomized trial

    NARCIS (Netherlands)

    Jansink, R.M.E.; Braspenning, J.C.C.; Laurant, M.G.H.; Keizer, E.; Elwyn, G.; Weijden, T. van der; Grol, R.P.T.M.

    2013-01-01

    BACKGROUND: The effectiveness of nurse-led motivational interviewing (MI) in routine diabetes care in general practice is inconclusive. Knowledge about the extent to which nurses apply MI skills and the factors that affect the usage can help to understand the black box of this intervention. The curr

  19. Mixed-Initiative Clustering

    Science.gov (United States)

    Huang, Yifen

    2010-01-01

    Mixed-initiative clustering is a task where a user and a machine work collaboratively to analyze a large set of documents. We hypothesize that a user and a machine can both learn better clustering models through enriched communication and interactive learning from each other. The first contribution or this thesis is providing a framework of…

  20. 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...

  1. Effect of a governmentally-led physical activity program on motor skills in young children attending child care centers: a cluster randomized controlled trial.

    Science.gov (United States)

    Bonvin, Antoine; Barral, Jérôme; Kakebeeke, Tanja H; Kriemler, Susi; Longchamp, Anouk; Schindler, Christian; Marques-Vidal, Pedro; Puder, Jardena J

    2013-07-08

    To assess the effect of a governmentally-led center based child care physical activity program (Youp'là Bouge) on child motor skills. We conducted a single blinded cluster randomized controlled trial in 58 Swiss child care centers. Centers were randomly selected and 1:1 assigned to a control or intervention group. The intervention lasted from September 2009 to June 2010 and included training of the educators, adaptation of the child care built environment, parental involvement and daily physical activity. Motor skill was the primary outcome and body mass index (BMI), physical activity and quality of life secondary outcomes. The intervention implementation was also assessed. At baseline, 648 children present on the motor test day were included (age 3.3 ± 0.6, BMI 16.3 ± 1.3 kg/m2, 13.2% overweight, 49% girls) and 313 received the intervention. Relative to children in the control group (n = 201), children in the intervention group (n = 187) showed no significant increase in motor skills (delta of mean change (95% confidence interval: -0.2 (-0.8 to 0.3), p = 0.43) or in any of the secondary outcomes. Not all child care centers implemented all the intervention components. Within the intervention group, several predictors were positively associated with trial outcomes: (1) free-access to a movement space and parental information session for motor skills (2) highly motivated and trained educators for BMI (3) free-access to a movement space and purchase of mobile equipment for physical activity (all p physical activity program in child care centers confirms the complexity of implementing an intervention outside a study setting and identified potentially relevant predictors that could improve future programs. Clinical trials.gov NCT00967460.

  2. Effectiveness of music education for the improvement of reading skills and academic achievement in young poor readers: a pragmatic cluster-randomized, controlled clinical trial.

    Science.gov (United States)

    Cogo-Moreira, Hugo; Brandão de Ávila, Clara Regina; Ploubidis, George B; Mari, Jair de Jesus

    2013-01-01

    Difficulties in word-level reading skills are prevalent in Brazilian schools and may deter children from gaining the knowledge obtained through reading and academic achievement. Music education has emerged as a potential method to improve reading skills because due to a common neurobiological substratum. To evaluate the effectiveness of music education for the improvement of reading skills and academic achievement among children (eight to 10 years of age) with reading difficulties. 235 children with reading difficulties in 10 schools participated in a five-month, randomized clinical trial in cluster (RCT) in an impoverished zone within the city of São Paulo to test the effects of music education intervention while assessing reading skills and academic achievement during the school year. Five schools were chosen randomly to incorporate music classes (n = 114), and five served as controls (n = 121). Two different methods of analysis were used to evaluate the effectiveness of the intervention: The standard method was intention-to-treat (ITT), and the other was the Complier Average Causal Effect (CACE) estimation method, which took compliance status into account. The ITT analyses were not very promising; only one marginal effect existed for the rate of correct real words read per minute. Indeed, considering ITT, improvements were observed in the secondary outcomes (slope of Portuguese = 0.21 [pread per minute [β = 13.98, p<0.001] and phonological awareness [β = 19.72, p<0.001] as well as secondary outcomes (academic achievement in Portuguese [β = 0.77, p<0.0001] and math [β = 0.49, p<0.001] throughout the school year). The results may be seen as promising, but they are not, in themselves, enough to make music lessons as public policy.

  3. Cluster-cluster clustering

    Science.gov (United States)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

    1985-01-01

    The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

  4. Cluster-cluster clustering

    Energy Technology Data Exchange (ETDEWEB)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.

    1985-08-01

    The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references.

  5. 基于加权聚类质心的 SVM 不平衡分类方法%Support vector machine imbalanced data classification based on weighted clustering centroid

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

    Classification of imbalanced data has become a research hot topic in machine learning .Traditional classi-fication algorithms assume that different classes have balanced distribution or equal misclassification cost , thus, making it hard to get ideal result of classifications .A support vector machine (SVM) classification method based on weighted clustering centroid was proposed in this paper .First, unsupervised clustering was applied to the positive and negative samples respectively to extract the clustering centroid of each clustering , which was represented the most in compactness of the clustering sample .Next, all clustering centroids formed a new set of balance training .In order to minimize the information loss during clustering , each clustering centroid was associated with a weight factor that was defined proportional to the number of samples of the class .Finally, all clustering centroids and weight fac-tors participated in the training of the improved SVM model .Experimental results show that the proposed method can make the sample selected from model train sets more typical and improve the classification performance better than other sampling techniques for dealing with imbalanced data .%  不平衡数据分类是机器学习研究的热点问题,传统分类算法假定不同类别具有平衡分布或误分代价相同,难以得到理想的分类结果。提出一种基于加权聚类质心的SVM分类方法,在正负类样本上分别进行聚类,对每个聚类,用聚类质心和权重因子代表聚类内样本分布和数量,相等类别数量的质心和权重因子参与SVM模型训练。实验结果表明,该方法使模型的训练样本具有较高的代表性,分类性能与其他采样方法相比得到了提升。

  6. Self-efficacy theory-based intervention in adolescents: a cluster randomized trial-focus on oral self-care practice and oral self-care skills.

    Science.gov (United States)

    Džiaugytė, Lina; Aleksejūnienė, Jolanta; Brukienė, Vilma; Pečiulienė, Vytaute

    2017-01-01

    The cluster randomized trial tested the efficacy of professional dental education for improving oral self-care skills (OSC-S) and oral self-care practice (OSC-P) in adolescents. All 15- to 16-year-old adolescents from four public schools were invited and 206 agreed to participate. Schools were randomly allocated to the intervention group and to the control group. Five sessions were given for the intervention group and one for the control group. The OSC-S and OSC-P outcomes were measured as % Oral Cleanliness Scores at the baseline, 6-month, and 12-month observations. OSC-S and OSC-P correlated significantly (Pearson's) at the baseline (r = 0.777, P oral healthcare interventions, a significant time × group effect was observed (repeated-measures anova, P Oral self-care skills and oral self-care practice scores were significantly correlated, (ii) self-efficacy theory-guided intervention was superior to the conventional dental instruction to improve oral self-care in adolescents, and (iii) varying levels of oral self-care improvement were observed among the intervention group adolescents. © 2016 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Outlier Mining Based Abnormal Machine Detection in Intelligent Maintenance

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; CAO Qi-xin; LEE Jay

    2009-01-01

    Assessing machine's performance through comparing the same or similar machines is important to implement intelligent maintenance for swarm machine. In this paper, an outlier mining based abnormal machine detection algorithm is proposed for this purpose. Firstly, the outlier mining based on clustering is introduced and the definition of cluster-based global outlier factor (CBGOF) is presented. Then the modified swarm intelligence clustering(MSIC) algorithm is suggested and the outlier mining algorithm based on MSIC is proposed. The algorithm can not only cluster machines according to their performance but also detect possible abnormal machines. Finally, a comparison of mobile soccer robots' performance proves the algorithm is feasible and effective.

  8. Effectiveness of music education for the improvement of reading skills and academic achievement in young poor readers: a pragmatic cluster-randomized, controlled clinical trial.

    Directory of Open Access Journals (Sweden)

    Hugo Cogo-Moreira

    Full Text Available INTRODUCTION: Difficulties in word-level reading skills are prevalent in Brazilian schools and may deter children from gaining the knowledge obtained through reading and academic achievement. Music education has emerged as a potential method to improve reading skills because due to a common neurobiological substratum. OBJECTIVE: To evaluate the effectiveness of music education for the improvement of reading skills and academic achievement among children (eight to 10 years of age with reading difficulties. METHOD: 235 children with reading difficulties in 10 schools participated in a five-month, randomized clinical trial in cluster (RCT in an impoverished zone within the city of São Paulo to test the effects of music education intervention while assessing reading skills and academic achievement during the school year. Five schools were chosen randomly to incorporate music classes (n = 114, and five served as controls (n = 121. Two different methods of analysis were used to evaluate the effectiveness of the intervention: The standard method was intention-to-treat (ITT, and the other was the Complier Average Causal Effect (CACE estimation method, which took compliance status into account. RESULTS: The ITT analyses were not very promising; only one marginal effect existed for the rate of correct real words read per minute. Indeed, considering ITT, improvements were observed in the secondary outcomes (slope of Portuguese = 0.21 [p<0.001] and slope of math = 0.25 [p<0.001]. As for CACE estimation (i.e., complier children versus non-complier children, more promising effects were observed in terms of the rate of correct words read per minute [β = 13.98, p<0.001] and phonological awareness [β = 19.72, p<0.001] as well as secondary outcomes (academic achievement in Portuguese [β = 0.77, p<0.0001] and math [β = 0.49, p<0.001] throughout the school year. CONCLUSION: The results may be seen as promising, but they are not

  9. Electromechanical Technician Skills Questionnaire.

    Science.gov (United States)

    Anoka-Hennepin Technical Coll., Minneapolis, MN.

    This document contains test items to measure the job skills of electromechanical technicians. Questions are organized in four sections that cover the following topics: (1) shop math; (2) electricity and electronics; (3) mechanics and machining; and (4) plumbing, heating, ventilation and air conditioning, and welding skills. Questions call for…

  10. Enterprise brand construction based on the enterprise in bowang machine tool industry cluster%基于企业视角的博望机床产业品牌建设

    Institute of Scientific and Technical Information of China (English)

    何莉; 吴永纯; 李德俊

    2011-01-01

    Bowang town is an under developed typical region.The present situation of Bowang machine tool industry cluster is investigated.Based on the brand,the problems in the development are analyzed,like brand awareness,weak brand foundation,few number of brands,low brand quality,the cluster consciousness indifference.The countermeasures for the Bowang machine tool industry cluster are explored:strengthening brand awareness,reinforceing brand and striving for brand management,enhancing brand innovation,expanding and growing stronger brand relying on industry clusters.%博望镇是欠发达地区产业集群的典型区域,深入到博望镇及博望机床企业了解其产业和品牌建设现状.基于企业的视角,剖析博望机床产业品牌存在的问题:品牌意识不强、品牌基础薄弱、品牌数量偏少、品牌品质偏低、集群意识淡漠.探讨适合于博望机床产业品牌发展的对策:加强品牌意识、夯实品牌基础、提升品牌管理力度、加强品牌创新、依托产业集群做大做强企业品牌.

  11. 运架一体式架梁机隧道架梁技术%Tunnel Girder Skill of Transported Frame Integrated Girder Machine

    Institute of Scientific and Technical Information of China (English)

    乐锋

    2013-01-01

      本文介绍了运架一体式架梁机的组成结构,施工前的各项准备工作。本文详细阐述了运架一体式架梁机进出隧道架设第一孔或最后一孔双线整孔预制箱梁的施工技术。%This article describes the structure composition of the transported frame integrated girder machine and the preparatory work before construction. This paper describes the double track prefabricated box girder construction technology of entering and going out the first or last hole of tunnel for the transported frame integrated girder machine.

  12. On a correlational clustering of integers

    OpenAIRE

    Aszalós László; Hajdu Lajos (1968-) (matematikus); Pethő Attila (1950-) (matematikus, informatikus)

    2016-01-01

    Correlation clustering is a concept of machine learning. The ultimate goal of such a clustering is to find a partition with minimal conflicts. In this paper we investigate a correlation clustering of integers, based upon the greatest common divisor.

  13. 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.

  14. 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.

  15. 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.

  16. STEP-NC oriented parts setup planning based on machining feature clustering%面向STEP-NC基于加工特征规则聚类的零件装夹规划

    Institute of Scientific and Technical Information of China (English)

    欧阳华兵; 沈斌

    2012-01-01

    Aiming at the setup planning problem in parts process planning,a heuristic clustering setup planning solving method oriented to STEP-NC machining feature was proposed.Based on the analysis of STEP-NC data model and machining unit,a mathematical model for setup planning was established.The machining unit was clustered by using manufacturing priority rules of machining features,and the setup scheme set was formed.Through expert estimation and evaluating scheme,these setup scheme sets were ordered.Thus the setup planning scheme that accord with parts setup demand was generated.The concrete shape and stability of parts were considered and each unit’s locating surface as well as clamping surface were determined.Based on Solidworks 3D computer aided design platform,the generation of parts setup planning was realized.The proposed algorithm was verified by examples.%针对零件工艺规划过程中的装夹规划问题,提出一种面向STEP-NC加工特征的启发式聚类装夹规划求解方法。在分析STEP-NC数据模型和加工单元的基础上,建立了零件装夹规划的数学模型,基于加工特征制造优先级规则对加工单元进行聚类分组,形成零件的装夹方案集;随后通过专家打分和评定策略对这些装夹方案集进行排序,生成符合零件装夹要求的装夹规划方案。装夹规划考虑了零件的具体形状及其稳定性等多种约束条件,确定零件每一个加工单元的定位面和装夹面,较好地体现了零件实际加工过程中的装夹情况。基于Solid-works三维计算机辅助设计平台实现了零件装夹规划的生成,通过实例对所提算法进行了验证。

  17. Improved self-management skills in Chinese diabetes patients through a comprehensive health literacy strategy: study protocol of a cluster randomized controlled trial.

    Science.gov (United States)

    Xu, Wang Hong; Rothman, Russell L; Li, Rui; Chen, Yingyao; Xia, Qinghua; Fang, Hong; Gao, Junling; Yan, Yujie; Zhou, Peng; Jiang, Yu; Liu, Yinan; Zhou, Fangjia; Wang, Wei; Chen, Minling; Liu, Xiao Yu; Liu, Xiao Na

    2014-12-20

    Diabetes self-management often involves the interpretation and application of oral, written, or quantitative information. Numerous diabetes patients in China have limited health literacy, which likely leads to poorer clinical outcomes. This study is designed to examine the efficacy and cost-effectiveness of addressing health literacy to improve self-management skills and glycemic control in Chinese diabetes patients. This is a cluster randomized controlled trial (RCT) conducted in 20 community healthcare sites in Shanghai, China. Overall, 800 diabetes patients will be randomized into intervention and control arms and will have a baseline hemoglobin A1c (HbA1c) assay and undergo a baseline survey which includes measures of health literacy and diabetes numeracy using revised Chinese versions of the Health Literacy Management Scale and Diabetes Numeracy Test Scale. During the 1-year period of intervention, while the control group will receive usual care, the intervention group will be supplemented with a comprehensive health literacy strategy which includes i) training healthcare providers in effective health communication skills that address issues related to low literacy, and ii) use of an interactive Diabetes Education Toolkit to improve patient understanding and behaviors. Assessments will be conducted at both patient and healthcare provider levels, and will take place upon admission and after 3, 6, 12, and 24 months of intervention. The primary outcome will be the improvement in HbA1c between Intervention group and Control group patients. Secondary outcomes at the patient level will include improvement in i) clinical outcomes (blood pressure, fasting lipids, body mass index, weight, smoking status), ii) patient reported self-management behaviors, and iii) patient-reported self-efficacy. Outcomes at the provider level will include: i) provider satisfaction and ii) intensity and type of care provided. The effects of the intervention will be examined in

  18. 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...

  19. 基于支持向量机与无监督聚类相结合的中文网页分类器%A Chinese Web Page Classifier Based on Support Vector Machine and Unsupervised Clustering

    Institute of Scientific and Technical Information of China (English)

    李晓黎; 刘继敏; 史忠植

    2001-01-01

    This paper presents a new algorithm that combines Support VectorMachine (SVM) and unsupervised clustering. After analyzing the characteristics of web pages, it proposes a new vector representation of web pages and applies it to web page classification. Given a training set, the algorithm clusters positive and negative examples respectively by the unsupervised clustering algorithm (UC), which will produce a number of positive and negative centers. Then, it selects only some of the examples to input to SVM according to ISUC algorithm. At the end, it constructs a classifier through SVM learning. Any text can be classified by comparing the distance of clustering centers or by SVM. If the text nears one cluster center of a category and far away from all the cluster centers of other categories, UC can classify it rightly with high possibility, otherwise SVM is employed to decide the category it belongs. The algorithm utilizes the virtues of SVM and unsupervised clustering. The experiment shows that it not only improves training efficiency, but also has good precision.%提出了一种将支持向量机与无监督聚类相结合的新分类算法,给出了一种新的网页表示方法并应用于网页分类问题.该算法首先利用无监督聚类分别对训练集中正例和反例聚类,然后挑选一些例子训练SVM并获得SVM分类器.任何网页可以通过比较其与聚类中心的距离决定采用无监督聚类方法或SVM分类器进行分类.该算法充分利用了SVM准确率高与无监督聚类速度快的优点.实验表明它不仅具有较高的训练效率,而且有很高的精确度.

  20. 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 ...

  1. 模糊聚类支持向量机的区域空气PM2.5浓度预报%Fuzzy Clustering Support Vector Machine for Predicting Regional PM2.5 Concentration

    Institute of Scientific and Technical Information of China (English)

    李海琴; 杨忠; 俞杰; 史旭华

    2016-01-01

    在分析模糊C均值聚类算法与支持向量机回归的特点后,将二者结合,提出了模糊聚类支持向量机回归(FCM-SVR)算法,对空气中颗粒物浓度PM2.5进行预测.该方法首先利用模糊C均值聚类算法把一个复杂的数据集分成多个群体,再在每个群体上建立支持向量机回归(SVR)模型,然后进行集成,对区域空气的 PM2.5浓度进行预测.预测结果分别与自组织竞争神经网络支持向量机回归(SOM-SVR)模型和单一的支持向量机回归(SVR)的结果进行比较.结果表明, FCM-SVR模型的预报准确率高于SOM-SVR模型和SVR模型.%A fuzzy clustering support vector machine regression algorithm is proposed by analyzing and combining the characteristics of the fuzzy C-mean clustering algorithm and the support vector machine regression. The SVM is designed to forecast the particles density PM2.5 in the air. Firstly, a complex data set is separated and inserted into multiple groups using fuzzy C-mean clustering algorithm. Then the SVM regression model in each group is established. The integrated fuzzy clustering SVM regression is applied to forecast the PM2.5 in the local air. By comparing the predicted result with that of the self-organizing competitive neural network SVM regression model, as well as that of the single SVM regression model respectively, it is found that the predicted accuracy rate of the FCM-SVR is higher than that of the SOM-SVR model and SVR model.

  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. Personal credit scoring based on hybrid support vector machines with cluster analysis%基于聚类和支持向量机的个人信誉评估方法

    Institute of Scientific and Technical Information of China (English)

    刘夫成; 高尚

    2013-01-01

    There are some problems exist in traditional individual credit assessment system. To solve those problems, a credit assessment model basesed on k-means method and support vector method is proposed. First the training samples are clustered using the K-means method. Then, the new samples defined according the feature of samples in cluster train the support vector machines, and to classify the test set by SVM. The result shows the approach improves training precision and test precision of the whole model compared with the traditional support vector classification method and improved the training speed.%针对传统的个人信誉评估方法存在的缺陷,提出了一种基于K均值聚类和支持向量机结合的个人信誉评估方法.该方法先将测试数据集进行聚类,根据数据离聚类的数据分布来选取合适数据训练支持向量机,然后利用支持向量机进行分类.结果表明,同单一利用支持向量机分类进行比较,该方法减少了训练时间,同时具有较高的测试精度,比传统的个人信誉评估模型有更好的效果.

  5. Effectiveness of Music Education for the Improvement of Reading Skills and Academic Achievement in Young Poor Readers: A Pragmatic Cluster-Randomized, Controlled Clinical Trial

    OpenAIRE

    Cogo-Moreira, H; de Avila, CRB; Ploubidis, GB; Mari, JD

    2013-01-01

    INTRODUCTION: Difficulties in word-level reading skills are prevalent in Brazilian schools and may deter children from gaining the knowledge obtained through reading and academic achievement. Music education has emerged as a potential method to improve reading skills because due to a common neurobiological substratum. OBJECTIVE: To evaluate the effectiveness of music education for the improvement of reading skills and academic achievement among children (eight to 10 years of age) with reading...

  6. Efficacy of an internet-based learning module and small-group debriefing on trainees' attitudes and communication skills toward patients with substance use disorders: results of a cluster randomized controlled trial.

    Science.gov (United States)

    Lanken, Paul N; Novack, Dennis H; Daetwyler, Christof; Gallop, Robert; Landis, J Richard; Lapin, Jennifer; Subramaniam, Geetha A; Schindler, Barbara A

    2015-03-01

    To examine whether an Internet-based learning module and small-group debriefing can improve medical trainees' attitudes and communication skills toward patients with substance use disorders (SUDs). In 2011-2012, 129 internal and family medicine residents and 370 medical students at two medical schools participated in a cluster randomized controlled trial, which assessed the effect of adding a two-part intervention to the SUDs curricula. The intervention included a self-directed, media-rich Internet-based learning module and a small-group, faculty-led debriefing. Primary study outcomes were changes in self-assessed attitudes in the intervention group (I-group) compared with those in the control group (C-group) (i.e., a difference of differences). For residents, the authors used real-time, Web-based interviews of standardized patients to assess changes in communication skills. Statistical analyses, conducted separately for residents and students, included hierarchical linear modeling, adjusted for site, participant type, cluster, and individual scores at baseline. The authors found no significant differences between the I- and C-groups in attitudes for residents or students at baseline. Compared with those in the C-group, residents, but not students, in the I-group had more positive attitudes toward treatment efficacy and self-efficacy at follow-up (Pgroup, residents in the I-group received higher scores on screening and counseling skills during the standardized patient interview at follow-up (P=.0009). This intervention produced improved attitudes and communication skills toward patients with SUDs among residents. Enhanced attitudes and skills may result in improved care for these patients.

  7. Basic machines and how they work

    CERN Document Server

    Education, Naval

    1997-01-01

    Only elementary math skills are needed to follow this manual, which covers many machines and their components, including hydrostatics and hydraulics, internal combustion engines, trains, and more. 204 black-and-white illustrations.

  8. 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 ...

  9. 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…

  10. 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.

  11. A Commodity Computing Cluster

    Science.gov (United States)

    Teuben, P. J.; Wolfire, M. G.; Pound, M. W.; Mundy, L. G.

    We have assembled a cluster of Intel-Pentium based PCs running Linux to compute a large set of Photodissociation Region (PDR) and Dust Continuum models. For various reasons the cluster is heterogeneous, currently ranging from a single Pentium-II 333 MHz to dual Pentium-III 450 MHz CPU machines. Although this will be sufficient for our ``embarrassingly parallelizable problem'' it may present some challenges for as yet unplanned future use. In addition the cluster was used to construct a MIRIAD benchmark, and compared to equivalent Ultra-Sparc based workstations. Currently the cluster consists of 8 machines, 14 CPUs, 50GB of disk-space, and a total peak speed of 5.83 GHz, or about 1.5 Gflops. The total cost of this cluster has been about $12,000, including all cabling, networking equipment, rack, and a CD-R backup system. The URL for this project is http://dustem.astro.umd.edu.

  12. Multi-label classification based on semi-fuzzy kernel clustering and fuzzy support vector machine%基于模糊支持向量的多标签分类方法

    Institute of Scientific and Technical Information of China (English)

    郑文博; 杨燕; 王洪军

    2011-01-01

    单实例多标签分类是指一个样本拥有多个标签的分类问题,对此提出了一种基于半模糊核聚类和模糊支持向量机的多标签分类算法.该算法采用一对一分解策略将多类多标签数据集分解为多个两类双标签数据子集,在每个子集上训练两类双标签模糊支持向量机.为提高分类器的性能引入了半模糊核聚类技术.实验结果表明,与现有的一些算法相比新算法具有其优越性.%Single instance multi-label classification problem lies in that its sample may own multiple classes. Aiming at this subject a multi-label classification algorithm based on fuzzy support vector machine (FSVM) and semi-fuzzy kernel clustering is proposed. One versus one decomposition policy is used to decompose the multi-label problem into several binary class double label classification sub-problems. For each sub-problem, a sub-classifier using binary class double label FSVM model is built. To improve the classification performance, a kind of semi-fuzzy kernel clustering technology is employed. Experimental results show that the proposed method is superior to several existent multi-label classification algorithms.

  13. Unconventional methods for clustering

    Science.gov (United States)

    Kotyrba, Martin

    2016-06-01

    Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is the main task of exploratory data mining and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics. The topic of this paper is one of the modern methods of clustering namely SOM (Self Organising Map). The paper describes the theory needed to understand the principle of clustering and descriptions of algorithm used with clustering in our experiments.

  14. 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.

  15. 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...

  16. 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...

  17. Data clustering algorithms and applications

    CERN Document Server

    Aggarwal, Charu C

    2013-01-01

    Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as fea

  18. Parallel Wolff Cluster Algorithms

    Science.gov (United States)

    Bae, S.; Ko, S. H.; Coddington, P. D.

    The Wolff single-cluster algorithm is the most efficient method known for Monte Carlo simulation of many spin models. Due to the irregular size, shape and position of the Wolff clusters, this method does not easily lend itself to efficient parallel implementation, so that simulations using this method have thus far been confined to workstations and vector machines. Here we present two parallel implementations of this algorithm, and show that one gives fairly good performance on a MIMD parallel computer.

  19. Technological Level of Machines in Production Process of Screws

    Directory of Open Access Journals (Sweden)

    Ingaldi Manuela

    2014-12-01

    Full Text Available The article focuses on analysing one of the elements of technological level in a company using the ABC method. The technological modernity of a machine used during the production process of screws was evaluated. In average, this machine was assigned the score 3.4, meaning that most parts of the machine were manufactured using more complex technologies requiring technical skills and knowledge, and many of them also with modern technologies. This means that the machine examined was quite modern

  20. The Effect of an Integrated Course Cluster Learning Community on the Oral and Written Communication Skills and Technical Content Knowledge of Upper-Level College of Agriculture Students

    Science.gov (United States)

    Barnett, Cynthia; Miller, Greg; Polito, Thomas A.; Gibson, Lance

    2009-01-01

    The purpose of this quasi-experimental study was to determine if upper-level college students who participated in AgPAQ, an integrated course cluster learning community, would demonstrate enhanced learning in the areas of oral communication, written communication, and agronomic/economic technical content knowledge. The population (N = 182)…

  1. 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.

  2. Testing the impact of a social skill training versus waiting list control group for the reduction of disruptive behaviors and stress among preschool children in child care: the study protocol for a cluster randomized trial.

    Science.gov (United States)

    Côté, Sylvana M; Larose, Marie-Pier; Geoffroy, Marie Claude; Laurin, Julie; Vitaro, Frank; Tremblay, Richard E; Ouellet-Morin, Isabelle

    2017-08-07

    Most preschoolers growing up in western industrialized countries receive child care services (CCS) during the day, while their parents are at work. Meta-analytic data suggest that CCS represent a stressful experience for preschoolers. This may be because preschoolers have not yet developed the social skills necessary to cope with the new and rapidly fluctuating social contexts of CCS. We tested the effectiveness of a child care-based social skill training program aiming to improve children's social behaviors and reduce the stress they experience. We used a cluster randomized control trial (cRCT) to compare children's social behaviors and stress levels in pre- and post-intervention according to whether they received a social skill training intervention or not. Nineteen (n = 19) public CCS (n = 362, 3-years-old preschoolers) of underprivileged neighborhoods (Montreal, Canada) were randomized to one of two conditions: 1) social skills training (n = 10 CCS); or 2) waiting list control group (n = 9 CCS). Educators in the intervention group conducted bi-weekly social skills training sessions over a period of 8 months. The intervention covered four topics: making social contacts, problem solving, emotional self-regulation, as well as emotional expression and recognition. Main outcome measures included preschoolers' disruptive (e.g. aggression, opposition, conflicts) and prosocial behaviors (e.g. sharing toys, helping another child), and stress levels assessed by salivary cortisol sampling at pre and post intervention assessments. Educators' practices will be tested as potential mediators of the expected changes in behaviors and neuroendocrine stress. To our knowledge, this is the first cRCT to test the effectiveness of a child care based social skill training program on the reduction of disruptive behaviors and levels of stress. Significant challenges include the degree of adherence to the intervention protocol as well educators and preschoolers' turnover

  3. Shaper and Milling Machine Operation, Machine Shop Work 2: 9555.04.

    Science.gov (United States)

    Dade County Public Schools, Miami, FL.

    The course outline has been prepared to assist the student in learning the basic skills and safety for shaper and milling operations. The course presents the various types of machines, work holding devices, cutting tools and feeds and speeds, and instruction designed to enable the student to obtain the manipulative skills and related knowledge…

  4. 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.

  5. Accelerating Relevance-Vector-Machine-Based Classification of Hyperspectral Image with Parallel Computing

    Directory of Open Access Journals (Sweden)

    Chao Dong

    2012-01-01

    Full Text Available Benefiting from the kernel skill and the sparse property, the relevance vector machine (RVM could acquire a sparse solution, with an equivalent generalization ability compared with the support vector machine. The sparse property requires much less time in the prediction, making RVM potential in classifying the large-scale hyperspectral image. However, RVM is not widespread influenced by its slow training procedure. To solve the problem, the classification of the hyperspectral image using RVM is accelerated by the parallel computing technique in this paper. The parallelization is revealed from the aspects of the multiclass strategy, the ensemble of multiple weak classifiers, and the matrix operations. The parallel RVMs are implemented using the C language plus the parallel functions of the linear algebra packages and the message passing interface library. The proposed methods are evaluated by the AVIRIS Indian Pines data set on the Beowulf cluster and the multicore platforms. It shows that the parallel RVMs accelerate the training procedure obviously.

  6. PVM Support for Clusters

    Science.gov (United States)

    Springer, P.

    2000-01-01

    The latest version of PVM (3.4.3) now contains support for a PC cluster running Linux, also known as a Beowulf system. A PVM user of a computer outside the Beowulf system can add the Beowulf as a single machine.

  7. Skills, Stakes, and Clout

    DEFF Research Database (Denmark)

    Vanhuysse, Pieter

    2015-01-01

    but no longer Central Europe. Reviewing decade-long evidence on subsidized, high-quality early childhood education pilot programs, I argue that such programs are a tested tool for marrying economic efficiency with social justice (equality of opportunity). I conclude by reflecting on which human skills...... are likely to be valued in the Second Machine Age. And I recommend policies, including new schemes to compensate for the way in which Europe's existing core-periphery divide is being (self-)perpetuated through periphery-to-core brain drain of highly skilled young Europeans....

  8. Extending Beowulf Clusters

    Science.gov (United States)

    Steinwand, Daniel R.; Maddox, Brian; Beckmann, Tim; Hamer, George

    2003-01-01

    Beowulf clusters can provide a cost-effective way to compute numerical models and process large amounts of remote sensing image data. Usually a Beowulf cluster is designed to accomplish a specific set of processing goals, and processing is very efficient when the problem remains inside the constraints of the original design. There are cases, however, when one might wish to compute a problem that is beyond the capacity of the local Beowulf system. In these cases, spreading the problem to multiple clusters or to other machines on the network may provide a cost-effective solution.

  9. 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

  10. The sydney playground project: popping the bubblewrap - unleashing the power of play: a cluster randomized controlled trial of a primary school playground-based intervention aiming to increase children's physical activity and social skills

    Directory of Open Access Journals (Sweden)

    Luckett Tim

    2011-09-01

    Full Text Available Abstract Background In the Westernised world, numerous children are overweight and have problems with bullying and mental health. One of the underlying causes for all three is postulated to be a decrease in outdoor free play. The aim of the Sydney Playground Project is to demonstrate the effectiveness of two simple interventions aimed to increase children's physical activity and social skills. Methods/Design This study protocol describes the design of a 3-year cluster randomised controlled trial (CRCT, in which schools are the clusters. The study consists of a 13-week intervention and 1 week each of pre-and post-testing. We are recruiting 12 schools (6 control; 6 intervention, with 18 randomly chosen participants aged 5 to 7 years in each school. The two intervention strategies are: (1 Child-based intervention: Unstructured materials with no obvious play value introduced to the playground; and (2 Adult-based intervention: Risk reframing sessions held with parents and teachers with the aim of exploring the benefits of allowing children to engage in activities with uncertain outcomes. The primary outcome of the study, physical activity as measured by accelerometer counts, is assessed at baseline and post-intervention. Additional assessments include social skills and interactions, self-concept, after school time use and anthropometric data. Qualitative data (i.e., transcriptions of audio recordings from the risk reframing sessions and of interviews with selected teacher and parent volunteers are analysed to understand their perceptions of risk in play. The control schools have recess as usual. In addition to outcome evaluation, regular process evaluation sessions are held to monitor fidelity to the treatment. Discussion These simple interventions, which could be adopted in every primary school, have the potential of initiating a self-sustaining cycle of prevention for childhood obesity, bullying and mental ill health. Trial registration Australian

  11. 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.

  12. Protocol for a cluster randomised trial of a communication skills intervention for physicians to facilitate survivorship transition in patients with lymphoma

    Science.gov (United States)

    Parker, Patricia A; Banerjee, Smita C; Matasar, Matthew J; Bylund, Carma L; Franco, Kara; Li, Yuelin; Levin, Tomer T; Jacobsen, Paul B; Astrow, Alan B; Leventhal, Howard; Horwitz, Steven; Kissane, David W

    2016-01-01

    Introduction Survivors of cancer often describe a sense of abandonment post-treatment, with heightened worry, uncertainty, fear of recurrence and limited understanding of what lies ahead. This study examines the efficacy of a communication skills training (CST) intervention to help physicians address survivorship issues and introduce a new consultation focused on the use of a survivorship care plan for patients with Hodgkin's lymphoma and diffuse large B-cell lymphoma. Methods and analysis Specifically, this randomised, 4-site trial will test the efficacy of a survivorship planning consultation (physicians receive CST and apply these skills in a new survivorship-focused office visit using a survivorship plan) with patients who have achieved complete remission after completion of first-line therapy versus a control arm in which physicians are trained to subsequently provide a time-controlled, manualised wellness rehabilitation consultation focused only on discussion of healthy nutrition and exercise as rehabilitation postchemotherapy. The primary outcome for physicians will be uptake and usage of communication skills and maintenance of these skills over time. The primary outcome for patients is changes in knowledge about lymphoma and adherence to physicians’ recommendations (eg, pneumococcus and influenza vaccinations); secondary outcomes will include perceptions of the doctor–patient relationship, decreased levels of cancer worry and depression, quality of life changes, satisfaction with care and usage of healthcare. This study will also examine the moderators and mediators of change within our theoretical model derived from Leventhal's Common-Sense Model of health beliefs. Ethics and dissemination This study was approved by the Institutional Review Boards at Memorial Sloan Kettering Cancer Centers and all other participating sites. This work is funded by the National Cancer Institute (R01 CA 151899 awarded to DWK and SH as coprincipal investigators). The

  13. 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.

  14. An Overview on Clustering Methods

    CERN Document Server

    Madhulatha, T Soni

    2012-01-01

    Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the process of grouping similar objects into different groups, or more precisely, the partitioning of a data set into subsets, so that the data in each subset according to some defined distance measure. This paper covers about clustering algorithms, benefits and its applications. Paper concludes by discussing some limitations.

  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. 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...

  17. 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 ...

  18. Analysis of Current Situations and Countermeasures of Intermediate and Advanced "Machining Center Operator" Skill Appraisal in Guangzhou%广州地区中高级“加工中心操作工”技能鉴定的问题与对策

    Institute of Scientific and Technical Information of China (English)

    廖志财

    2012-01-01

    分析了广州地区中、高级“加工中心操作工”技能鉴定的现状及存在的问题,并提出了相应的对策,以期引起有关部门的重视,使该工种的技能鉴定工作逐步规范和完善。%This paper analyzes the present situations and the existing problems of intermediate and advanced "machining center operator" skill appraisal in Guangzhou, and proposes corresponding countermeasures, in the hope of drawing the attention of relevant departments to gradually standardize and perfect the skill appraisal.

  19. Implementation of Clustering Algorithms for real datasets in Medical Diagnostics using MATLAB

    Directory of Open Access Journals (Sweden)

    B. Venkataramana

    2017-03-01

    Full Text Available As in the medical field, for one disease there require samples given by diagnosis. The samples will be analyzed by a doctor or a pharmacist. As the no. of patients increases their samples also increases, there require more time to analyze samples for deciding the stage of the disease. To analyze the sample every time requires a skilled person. The samples can be classified by applying them to clustering algorithms. Data clustering has been considered as the most important raw data analysis method used in data mining technology. Most of the clustering techniques proved their efficiency in many applications such as decision making systems, medical sciences, earth sciences etc. Partition based clustering is one of the main approach in clustering. There are various algorithms of data clustering, every algorithm has its own advantages and disadvantages. This work reports the results of classification performance of three such widely used algorithms namely K-means (KM, Fuzzy c-means and Fuzzy Possibilistic c-Means (FPCM clustering algorithms. To analyze these algorithms three known data sets from UCI machine learning repository are taken such as thyroid data, liver and wine. The efficiency of clustering output is compared with the classification performance, percentage of correctness. The experimental results show that K-means and FCM give same performance for liver data. And FCM and FPCM are giving same performance for thyroid and wine data. FPCM has more efficient classification performance in all the given data sets.

  20. 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...

  1. Machine Learning for Biological Trajectory Classification Applications

    Science.gov (United States)

    Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros

    2002-01-01

    Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

  2. Machine Learning wins the Higgs Challenge

    CERN Multimedia

    Abha Eli Phoboo

    2014-01-01

    The winner of the four-month-long Higgs Machine Learning Challenge, launched on 12 May, is Gábor Melis from Hungary, followed closely by Tim Salimans from the Netherlands and Pierre Courtiol from France. The challenge explored the potential of advanced machine learning methods to improve the significance of the Higgs discovery.   Winners of the Higgs Machine Learning Challenge: Gábor Melis and Tim Salimans (top row), Tianqi Chen and Tong He (bottom row). Participants in the Higgs Machine Learning Challenge were tasked with developing an algorithm to improve the detection of Higgs boson signal events decaying into two tau particles in a sample of simulated ATLAS data* that contains few signal and a majority of non-Higgs boson “background” events. No knowledge of particle physics was required for the challenge but skills in machine learning - the training of computers to recognise patterns in data – were essential. The Challenge, hosted by Ka...

  3. Sewing Skills for Home and Community Services. Student Material.

    Science.gov (United States)

    Sharpton, James L.

    These student learning materials deal with basic sewing skills. The following topics are covered in the individual units: the principal parts of a sewing machine and their purposes; procedures for caring for a sewing machine (putting it away, lubricating it, and changing the needle); operation of an unthreaded sewing machine (maintaining correct…

  4. 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...

  5. Clustering Techniques in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Muhammad Ali Masood

    2015-01-01

    Full Text Available Dealing with data means to group information into a set of categories either in order to learn new artifacts or understand new domains. For this purpose researchers have always looked for the hidden patterns in data that can be defined and compared with other known notions based on the similarity or dissimilarity of their attributes according to well-defined rules. Data mining, having the tools of data classification and data clustering, is one of the most powerful techniques to deal with data in such a manner that it can help researchers identify the required information. As a step forward to address this challenge, experts have utilized clustering techniques as a mean of exploring hidden structure and patterns in underlying data. Improved stability, robustness and accuracy of unsupervised data classification in many fields including pattern recognition, machine learning, information retrieval, image analysis and bioinformatics, clustering has proven itself as a reliable tool. To identify the clusters in datasets algorithm are utilized to partition data set into several groups based on the similarity within a group. There is no specific clustering algorithm, but various algorithms are utilized based on domain of data that constitutes a cluster and the level of efficiency required. Clustering techniques are categorized based upon different approaches. This paper is a survey of few clustering techniques out of many in data mining. For the purpose five of the most common clustering techniques out of many have been discussed. The clustering techniques which have been surveyed are: K-medoids, K-means, Fuzzy C-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN and Self-Organizing Map (SOM clustering.

  6. Discharge estimation based on machine learning

    Institute of Scientific and Technical Information of China (English)

    Zhu JIANG; Hui-yan WANG; Wen-wu SONG

    2013-01-01

    To overcome the limitations of the traditional stage-discharge models in describing the dynamic characteristics of a river, a machine learning method of non-parametric regression, the locally weighted regression method was used to estimate discharge. With the purpose of improving the precision and efficiency of river discharge estimation, a novel machine learning method is proposed:the clustering-tree weighted regression method. First, the training instances are clustered. Second, the k-nearest neighbor method is used to cluster new stage samples into the best-fit cluster. Finally, the daily discharge is estimated. In the estimation process, the interference of irrelevant information can be avoided, so that the precision and efficiency of daily discharge estimation are improved. Observed data from the Luding Hydrological Station were used for testing. The simulation results demonstrate that the precision of this method is high. This provides a new effective method for discharge estimation.

  7. Access, Equity, and Opportunity. Women in Machining: A Model Program.

    Science.gov (United States)

    Warner, Heather

    The Women in Machining (WIM) program is a Machine Action Project (MAP) initiative that was developed in response to a local skilled metalworking labor shortage, despite a virtual absence of women and people of color from area shops. The project identified post-war stereotypes and other barriers that must be addressed if women are to have an equal…

  8. Learning scikit-learn machine learning in Python

    CERN Document Server

    Garreta, Raúl

    2013-01-01

    The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous experience with machine-learning algorithms is required.

  9. Precision Machining Technology. Technical Committee Report.

    Science.gov (United States)

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

    This Technical Committee Report prepared by industry representatives in Idaho lists the skills currently necessary for an employee in that state to obtain a job in precision machining technology, retain a job once hired, and advance in that occupational field. (Task lists are grouped according to duty areas generally used in industry settings, and…

  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. Remediation, General Education, and Technical Mathematics. Educational Resources for the Machine Tool Industry.

    Science.gov (United States)

    Texas State Technical Coll. System, Waco.

    This document contains descriptions of adult education courses in remediation, general education, and technical mathematics. They are part of a program developed by the Machine Tool Advanced Skills Technology Educational Resources (MASTER) program to help workers become competent in the skills needed to be productive workers in the machine tools…

  14. Interpersonal Skills

    Directory of Open Access Journals (Sweden)

    Barakat NG

    2007-01-01

    Full Text Available INTRODUCTIONInterpersonal skills are becoming more and more a necessity in the medical profession. The expectation from health care professionals is beyond just knowledge of the medical facts. To practice medicine effectively, doctors need to develop interpersonal skills in communication, leadership, management, teaching and time management. All of these are vital tools and are becoming increasingly essential subjects in teaching both undergraduate students and postgraduate doctors. However, a degree of self-motivation and personal initiative is needed to develop these skills. In this article, I will give an overview on interpersonal skills and will be follow this by a series of articles, in future issues, dealing with these skills.

  15. Comparative Study of K-means and Robust Clustering

    Directory of Open Access Journals (Sweden)

    Shashi Sharma

    2013-09-01

    Full Text Available Data mining is the mechanism of implementing patterns in large amount of data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. Clustering is the very big area in which grouping of same type of objects in data mining. Clustering has divided into different categories – partitioned clustering and hierarchical clustering. In this paper we study two types of clustering first is Kmeans which is part of partitioned clustering. Kmeans clustering generates a specific number of disjoint, flat (non-hierarchical clusters. Second clustering is robust clustering which is part of hierarchical clustering. This clustering uses Jaccard coefficient instead of using the distance measures to find the similarity between the data or documents to classify the clusters. We show comparison between Kmeans clustering and robust clustering which is better for categorical data.

  16. Cluster headache

    Science.gov (United States)

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... A cluster headache begins as a severe, sudden headache. The headache commonly strikes 2 to 3 hours after you fall ...

  17. Cluster Forests

    CERN Document Server

    Yan, Donghui; Jordan, Michael I

    2011-01-01

    Inspired by Random Forests (RF) in the context of classification, we propose a new clustering ensemble method---Cluster Forests (CF). Geometrically, CF randomly probes a high-dimensional data cloud to obtain "good local clusterings" and then aggregates via spectral clustering to obtain cluster assignments for the whole dataset. The search for good local clusterings is guided by a cluster quality measure $\\kappa$. CF progressively improves each local clustering in a fashion that resembles the tree growth in RF. Empirical studies on several real-world datasets under two different performance metrics show that CF compares favorably to its competitors. Theoretical analysis shows that the $\\kappa$ criterion is shown to grow each local clustering in a desirable way---it is "noise-resistant." A closed-form expression is obtained for the mis-clustering rate of spectral clustering under a perturbation model, which yields new insights into some aspects of spectral clustering.

  18. Skills, Stakes, and Clout

    DEFF Research Database (Denmark)

    Vanhuysse, Pieter

    2015-01-01

    I ask why and how early human capital investment may boost the future foundations of European welfare states. Regarding the material circumstances of young adults and very young children, and educational outcomes such as PISA results in mathematics, reading, writing and problem solving, the years...... but no longer Central Europe. Reviewing decade-long evidence on subsidized, high-quality early childhood education pilot programs, I argue that such programs are a tested tool for marrying economic efficiency with social justice (equality of opportunity). I conclude by reflecting on which human skills...... are likely to be valued in the Second Machine Age. And I recommend policies, including new schemes to compensate for the way in which Europe's existing core-periphery divide is being (self-)perpetuated through periphery-to-core brain drain of highly skilled young Europeans....

  19. Star Clusters

    OpenAIRE

    Gieles, M.

    1993-01-01

    Star clusters are observed in almost every galaxy. In this thesis we address several fundamental problems concerning the formation, evolution and disruption of star clusters. From observations of (young) star clusters in the interacting galaxy M51, we found that clusters are formed in complexes of stars and star clusters. These complexes share similar properties with giant molecular clouds, from which they are formed. Many (70%) of the young clusters will not survive the fist 10 Myr, due to t...

  20. 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....

  1. 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

  2. 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

  3. Two-year outcome of alcohol interventions in Swedish university halls of residence: a cluster randomized trial of a brief skills training program, twelve-step-influenced intervention, and controls.

    Science.gov (United States)

    Ståhlbrandt, Henriettae; Johnsson, Kent O; Berglund, Mats

    2007-03-01

    High-risk alcohol consumption among university students is well documented. Several types of intervention have proved to be effective in reducing alcohol consumption. This study examines the 2-year outcome of 2 different alcohol intervention programs at university halls of residence. Ninety-eight university halls of residence (with 556 students) were cluster randomized to 2 different intervention groups: a brief skills training program (BSTP) with interactive lectures and discussions, a twelve-step-influenced (TSI) program with didactic lectures by therapists trained in the 12-step approach, and a control group. All students completing the baseline assessment received personalized feedback by mail. Students responded to mailed follow-up questionnaires after 1, 2, and 3 years, including alcohol use disorders identification test (AUDIT; years 2 and 3), short index of problems (SIP), and estimated blood alcohol concentration (eBAC). All groups significantly reduced their AUDIT scores from baseline to the second year follow-up, with no significant differences between the groups. Seventy-seven percent of the students belonged to a population with high-risk consumption, using the AUDIT cut-off scores of 8 and 4 for men and women, respectively. Students with high-risk alcohol consumption showed significant differences in AUDIT score reduction in favor of the BSTP compared with controls, and had a tendency to show better results than the TSI intervention (p=0.06). Similar trends could be seen using SIP and eBAC. The TSI did not differ significantly from the control group within the group of students with high-risk alcohol consumption. This study suggests that a BSTP is effective as an intervention in students with high-risk alcohol consumption.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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)

  9. 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...

  10. 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

  11. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  12. 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...

  13. 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

  14. 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.

  15. 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.

  16. Pruning nearest neighbor cluster trees

    CERN Document Server

    Kpotufe, Samory

    2011-01-01

    Nearest neighbor (k-NN) graphs are widely used in machine learning and data mining applications, and our aim is to better understand what they reveal about the cluster structure of the unknown underlying distribution of points. Moreover, is it possible to identify spurious structures that might arise due to sampling variability? Our first contribution is a statistical analysis that reveals how certain subgraphs of a k-NN graph form a consistent estimator of the cluster tree of the underlying distribution of points. Our second and perhaps most important contribution is the following finite sample guarantee. We carefully work out the tradeoff between aggressive and conservative pruning and are able to guarantee the removal of all spurious cluster structures at all levels of the tree while at the same time guaranteeing the recovery of salient clusters. This is the first such finite sample result in the context of clustering.

  17. Entanglement-based machine learning on a quantum computer.

    Science.gov (United States)

    Cai, X-D; Wu, D; Su, Z-E; Chen, M-C; Wang, X-L; Li, Li; Liu, N-L; Lu, C-Y; Pan, J-W

    2015-03-20

    Machine learning, a branch of artificial intelligence, learns from previous experience to optimize performance, which is ubiquitous in various fields such as computer sciences, financial analysis, robotics, and bioinformatics. A challenge is that machine learning with the rapidly growing "big data" could become intractable for classical computers. Recently, quantum machine learning algorithms [Lloyd, Mohseni, and Rebentrost, arXiv.1307.0411] were proposed which could offer an exponential speedup over classical algorithms. Here, we report the first experimental entanglement-based classification of two-, four-, and eight-dimensional vectors to different clusters using a small-scale photonic quantum computer, which are then used to implement supervised and unsupervised machine learning. The results demonstrate the working principle of using quantum computers to manipulate and classify high-dimensional vectors, the core mathematical routine in machine learning. The method can, in principle, be scaled to larger numbers of qubits, and may provide a new route to accelerate machine learning.

  18. Evidence for Multiple Rhythmic Skills.

    Directory of Open Access Journals (Sweden)

    Adam Tierney

    Full Text Available Rhythms, or patterns in time, play a vital role in both speech and music. Proficiency in a number of rhythm skills has been linked to language ability, suggesting that certain rhythmic processes in music and language rely on overlapping resources. However, a lack of understanding about how rhythm skills relate to each other has impeded progress in understanding how language relies on rhythm processing. In particular, it is unknown whether all rhythm skills are linked together, forming a single broad rhythmic competence, or whether there are multiple dissociable rhythm skills. We hypothesized that beat tapping and rhythm memory/sequencing form two separate clusters of rhythm skills. This hypothesis was tested with a battery of two beat tapping and two rhythm memory tests. Here we show that tapping to a metronome and the ability to adjust to a changing tempo while tapping to a metronome are related skills. The ability to remember rhythms and to drum along to repeating rhythmic sequences are also related. However, we found no relationship between beat tapping skills and rhythm memory skills. Thus, beat tapping and rhythm memory are dissociable rhythmic aptitudes. This discovery may inform future research disambiguating how distinct rhythm competencies track with specific language functions.

  19. Evidence for Multiple Rhythmic Skills.

    Science.gov (United States)

    Tierney, Adam; Kraus, Nina

    2015-01-01

    Rhythms, or patterns in time, play a vital role in both speech and music. Proficiency in a number of rhythm skills has been linked to language ability, suggesting that certain rhythmic processes in music and language rely on overlapping resources. However, a lack of understanding about how rhythm skills relate to each other has impeded progress in understanding how language relies on rhythm processing. In particular, it is unknown whether all rhythm skills are linked together, forming a single broad rhythmic competence, or whether there are multiple dissociable rhythm skills. We hypothesized that beat tapping and rhythm memory/sequencing form two separate clusters of rhythm skills. This hypothesis was tested with a battery of two beat tapping and two rhythm memory tests. Here we show that tapping to a metronome and the ability to adjust to a changing tempo while tapping to a metronome are related skills. The ability to remember rhythms and to drum along to repeating rhythmic sequences are also related. However, we found no relationship between beat tapping skills and rhythm memory skills. Thus, beat tapping and rhythm memory are dissociable rhythmic aptitudes. This discovery may inform future research disambiguating how distinct rhythm competencies track with specific language functions.

  20. 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

  1. Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

    Science.gov (United States)

    Hendrix, Val; Benjamin, Doug; Yao, Yushu

    2012-12-01

    Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

  2. Meaningful Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Calapristi, Augustin J.; Crow, Vernon L.; Hetzler, Elizabeth G.; Turner, Alan E.

    2004-05-26

    We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense disambiguation.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Cluster Lenses

    CERN Document Server

    Kneib, Jean-Paul; 10.1007/s00159-011-0047-3

    2012-01-01

    Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining...

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. Cost Effective Machining Of Ceramics (CEMOC)

    Energy Technology Data Exchange (ETDEWEB)

    Barkman, W.E.

    1997-04-18

    The purpose of the CEMOC program was to support U.S. industry needs in fabricating precision components, from difficult to machine materials, while maintaining and enhancing the precision manufacturing skills of the Oak Ridge Complex. Oak Ridge and partner company personnel worked in a team relationship wherein each contributed equally to the success of the program. In general, Oak Ridge contributed a wider range of expertise to a given task while the companies provided operations-specific equipment and shop-floor services. Process control technologies, machining procedures and parameters, and coolant-related environmental tasks were the primary focus areas. The companies were very pleased with the results of the CRADAs and are planning on continuing the relationships. Finish machining operations contribute the majority of the costs associated with fabricating high quality ceramic products. These components are typically used in harsh environments such as diesel engines, defense machinery, and automotive components. The required finishing operations involve a variety of technologies including process controls, machine coolants, product certification, etc. and are not limited only to component grinding methods. The broad range of manufacturing problem solving expertise available in Oak Ridge provided resources that were far beyond what are typically available to the CRADA partners. These partners contributed equipment, such as state-of-the-art machine tools, and operation-specific experience base. In addition, addressing these challenging tasks enabled Oak Ridge personnel to maintain familiarity with rapidly advancing technologies, such as those associated with computer control systems.

  17. Fuzzy clustering of mechanisms

    Indian Academy of Sciences (India)

    Amitabha Ghosh; Dilip Kumar Pratihar; M V V Amarnath; Guenter Dittrich; Jorg Mueller

    2012-10-01

    During the course of development of Mechanical Engineering, a large number of mechanisms (that is, linkages to perform various types of tasks) have been conceived and developed. Quite a few atlases and catalogues were prepared by the designers of machines and mechanical systems. However, often it is felt that a clustering technique for handling the list of large number of mechanisms can be very useful,if it is developed based on a scientific principle. In this paper, it has been shown that the concept of fuzzy sets can be conveniently used for this purpose, if an adequate number of properly chosen attributes (also called characteristics) are identified. Using two clustering techniques, the mechanisms have been classified in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors’ knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the first attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.

  18. 20 CFR 404.1568 - Skill requirements.

    Science.gov (United States)

    2010-04-01

    ... work requires qualifications in which a person uses judgment to determine the machine and manual... Employees' Benefits SOCIAL SECURITY ADMINISTRATION FEDERAL OLD-AGE, SURVIVORS AND DISABILITY INSURANCE (1950... evaluate your skills and to help determine the existence in the national economy of work you are able to...

  19. Transportation Cluster Volume 3 [Small Power Sources].

    Science.gov (United States)

    Pennsylvania State Dept. of Justice, Harrisburg. Bureau of Correction.

    The document is one of seven volumes of instructional materials developed around a cluster of Transportation Industries. Primarily technical in focus, they are designed to be used in a cluster-concept program and to integrate with a regular General Education Development (G.E.D.) program so that students may attain an employable skill level and a…

  20. LHCb: Machine assisted histogram classification

    CERN Multimedia

    Somogyi, P; Gaspar, C

    2009-01-01

    LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty components can be either done visually using instruments such as the LHCb Histogram Presenter, or by automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, a graph-theoretic based clustering tool, combined with machine learning algorithms is proposed and demonstrated by processing histograms representing 2D event hitmaps. The concept is proven by detecting ion feedback events in the LHCb RICH subdetector.

  1. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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...

  9. 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,…

  10. 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…

  11. 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.

  12. 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...

  13. 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 –...

  14. 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.

  15. 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.

  16. Leadership Skills

    Science.gov (United States)

    Parish, Thomas S.

    2006-01-01

    While this may not be a "complete list" of what leadership skills one needs to effectively lead in any/every situation, it should provide a great overview of many of the things s/he needs to do, at least initially.

  17. Coping Skills.

    Science.gov (United States)

    Library of Congress, Washington, DC. National Library Service for the Blind and Physically Handicapped.

    This annotated bibliography lists approximately 150 braille books and 300 audiocassettes of books which address coping skills for people in a variety of situations. All items listed are available in the network library collections provided by the National Library Service for the Blind and Physically Handicapped of the Library of Congress.…

  18. Cluster Chemistry

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    @@ Cansisting of eight scientists from the State Key Laboratory of Physical Chemistry of Solid Surfaces and Xiamen University, this creative research group is devoted to the research of cluster chemistry and creation of nanomaterials.After three-year hard work, the group scored a series of encouraging progresses in synthesis of clusters with special structures, including novel fullerenes, fullerene-like metal cluster compounds as well as other related nanomaterials, and their properties study.

  19. Force Based Skill Learning for Robot Tasks in Contact Conditions

    Institute of Scientific and Technical Information of China (English)

    王琴; 梅志千; 张广立; 杨汝清

    2004-01-01

    To acquire human operation skill based on force sense, element contact form (ECF) is proposed to describe contact condition firstly. The skill is modeled as a sequence of discrete ECFs. Since different ECF has different force distribution, a support vector machine classifier is built to identify the contact conditions according to the force signal. Finally, the robot can obtain the skill from the human demonstration.

  20. Clustered regression with unknown clusters

    CERN Document Server

    Barman, Kishor

    2011-01-01

    We consider a collection of prediction experiments, which are clustered in the sense that groups of experiments ex- hibit similar relationship between the predictor and response variables. The experiment clusters as well as the regres- sion relationships are unknown. The regression relation- ships define the experiment clusters, and in general, the predictor and response variables may not exhibit any clus- tering. We call this prediction problem clustered regres- sion with unknown clusters (CRUC) and in this paper we focus on linear regression. We study and compare several methods for CRUC, demonstrate their applicability to the Yahoo Learning-to-rank Challenge (YLRC) dataset, and in- vestigate an associated mathematical model. CRUC is at the crossroads of many prior works and we study several prediction algorithms with diverse origins: an adaptation of the expectation-maximization algorithm, an approach in- spired by K-means clustering, the singular value threshold- ing approach to matrix rank minimization u...

  1. Rise of the machines: the effects of labor-saving innovations on jobs and wages

    OpenAIRE

    2015-01-01

    Job polarization the rise in employment shares of high and low skill jobs at the expense of middle skill jobs occurred in the US not just recently, but also in the late nineteenth and early twentieth centuries. We argue that in each case polarization resulted from increased automation, and provide a theoretical explanation. In our model, firms deciding whether to employ machines or workers in a given task weigh the cost of using machines, which is increasing in the complexity (in an engineeri...

  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. Subspace clustering through attribute clustering

    Institute of Scientific and Technical Information of China (English)

    Kun NIU; Shubo ZHANG; Junliang CHEN

    2008-01-01

    Many recently proposed subspace clustering methods suffer from two severe problems. First, the algorithms typically scale exponentially with the data dimensionality or the subspace dimensionality of clusters. Second, the clustering results are often sensitive to input parameters. In this paper, a fast algorithm of subspace clustering using attribute clustering is proposed to over-come these limitations. This algorithm first filters out redundant attributes by computing the Gini coefficient. To evaluate the correlation of every two non-redundant attributes, the relation matrix of non-redundant attributes is constructed based on the relation function of two dimensional united Gini coefficients. After applying an overlapping clustering algorithm on the relation matrix, the candidate of all interesting subspaces is achieved. Finally, all subspace clusters can be derived by clustering on interesting subspaces. Experiments on both synthesis and real datasets show that the new algorithm not only achieves a significant gain of runtime and quality to find subspace clusters, but also is insensitive to input parameters.

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. Negotiating skills.

    Science.gov (United States)

    Hughes, G

    1996-01-01

    The Collins English Dictionary defines negotiation as "a discussion set up or intended to produce a "settlement or agreement." It is a skill everyone uses on a regular basis in daily life; often without realising. A plan to meet friends fo an evening meal for example involves agreeing a time and venue--this is negotiation. As it is the the process of coming to terms with the "other side" and trying to get the best deal possible it is necessary to accept the fact that a conflict of interest does exist. There is an atmosphere of uncertainty until the deal is completed and one side may gain and one may lose relative to their opening position. For this skill to be successfully applied when working with clinical management colleagues, a formal set of guidelines is necessary. In this article I highlight some of the problems which can arise and offer a systematic approach to this difficult but rewarding management activity. PMID:9091105

  15. Effectiveness of Podcasts as Laboratory Instructional Support: Learner Perceptions of Machine Shop and Welding Students

    Science.gov (United States)

    Lauritzen, Louis Dee

    2014-01-01

    Machine shop students face the daunting task of learning the operation of complex three-dimensional machine tools, and welding students must develop specific motor skills in addition to understanding the complexity of material types and characteristics. The use of consumer technology by the Millennial generation of vocational students, the…

  16. Effectiveness of Podcasts as Laboratory Instructional Support: Learner Perceptions of Machine Shop and Welding Students

    Science.gov (United States)

    Lauritzen, Louis Dee

    2014-01-01

    Machine shop students face the daunting task of learning the operation of complex three-dimensional machine tools, and welding students must develop specific motor skills in addition to understanding the complexity of material types and characteristics. The use of consumer technology by the Millennial generation of vocational students, the…

  17. The SMART CLUSTER METHOD - adaptive earthquake cluster analysis and declustering

    Science.gov (United States)

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

    2016-04-01

    Earthquake declustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity with usual applications comprising of probabilistic seismic hazard assessments (PSHAs) and earthquake prediction methods. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation. Various methods have been developed to address this issue from other researchers. These have differing ranges of complexity ranging from rather simple statistical window methods to complex epidemic models. This study introduces the smart cluster method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal identification. Hereby, an adaptive search algorithm for data point clusters is adopted. It uses the earthquake density in the spatio-temporal neighbourhood of each event to adjust the search properties. The identified clusters are subsequently analysed to determine directional anisotropy, focussing on a strong correlation along the rupture plane and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010/2011 Darfield-Christchurch events, an adaptive classification procedure is applied to disassemble subsequent ruptures which may have been grouped into an individual cluster using near-field searches, support vector machines and temporal splitting. The steering parameters of the search behaviour are linked to local earthquake properties like magnitude of completeness, earthquake density and Gutenberg-Richter parameters. The method is capable of identifying and classifying earthquake clusters in space and time. It is tested and validated using earthquake data from California and New Zealand. As a result of the cluster identification process, each event in

  18. Leadership skills?

    Science.gov (United States)

    2016-09-01

    Senior executive leaders might be interested in applying for the NHS Leadership Academy's director programme, which is designed to 'stretch and challenge' those with an 'existing level of complex leadership skills'. The programme also offers an opportunity for participants to work with other leaders and other parts of the system to enhance inclusiveness. There are three cohorts a year, and the programme runs for a 12 months. Closing dates for applicants are 4 September 2016, 22 January 2017 and 21 May 2017.

  19. Three-dimensional facial feature points matching based on K-means clustering of relative angle context distribution and support vector machine%基于相对角分布聚类和支持向量机的3维人脸特征点匹配技术的研究

    Institute of Scientific and Technical Information of China (English)

    麻宏静; 张德同; 冯筠; 耿国华

    2011-01-01

    Feature points searching or point correspondence matching is a challenge in computer vision and pattern recognition, which is very important perquisite for many 2D/3D applications such as image registration, object recognition and statistical model construction. In this paper, we propose an algorithm for facial feature points matching among 3D point cloud models. Specifically, the surface points are clustered based on relative angle context (RAC) features, and then the geometric features of the clustered points are extracted. Afterwards, supported Vector Machine based classification is employed for final accurate correspondence location. The experimental results demonstrate that our algorithm achieves better performance than RAC algorithm proposed. Within the confines of a given distance threshold, the accuracy rates of 50% feature points have even reached to 100%.%人脸特征点自动定位及对应点匹配是计算机视觉和模式识别领域一个非常热门的研究方向,应用领域包括图像配准、对象识别与跟踪、3维重建、立体匹配等.通过相对角直方图分布和K均值聚类确定脸部特征点的聚类点集,再利用几何信息提取聚类点集的特征,进而采用支持向量机分类最终从点集中分离出39个脸部特征点.实验结果表明,此混合提取方法比单纯使用RAC得到了更好的匹配准确率,在给定的距离阈值范围内,50%的特征点定位准确率达到了100%.

  20. A Survey of Grid Based Clustering Algorithms

    Directory of Open Access Journals (Sweden)

    MR ILANGO

    2010-08-01

    Full Text Available Cluster Analysis, an automatic process to find similar objects from a database, is a fundamental operation in data mining. A cluster is a collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other clusters. Clustering techniques have been discussed extensively in SimilaritySearch, Segmentation, Statistics, Machine Learning, Trend Analysis, Pattern Recognition and Classification [1]. Clustering methods can be classified into i Partitioning methods ii Hierarchical methods iii Density-based methods iv Grid-based methods v Model-based methods. Grid based methods quantize the object space into a finite number of cells (hyper-rectangles and then perform the required operations on the quantized space. The main advantage of Grid based method is its fast processing time which depends on number of cells in each dimension in quantized space. In this research paper, we present some of the grid based methods such as CLIQUE (CLustering In QUEst [2], STING (STatistical INformation Grid [3], MAFIA (Merging of Adaptive Intervals Approach to Spatial Data Mining [4], Wave Cluster [5]and O-CLUSTER (Orthogonal partitioning CLUSTERing [6], as a survey andalso compare their effectiveness in clustering data objects. We also present some of the latest developments in Grid Based methods such as Axis Shifted Grid Clustering Algorithm [7] and Adaptive Mesh Refinement [Wei-Keng Liao etc] [8] to improve the processing time of objects.

  1. Educational Resources for the Machine Tool Industry. Executive Summary.

    Science.gov (United States)

    Texas State Technical Coll. System, Waco.

    This document describes the MASTER (Machine Tool Advanced Skills Educational Resources) program, a geographic partnership of seven of the nation's best 2-year technical and community colleges located in seven states. The project developed and disseminated a national training model for manufacturing processes and new technologies within the…

  2. Application of case-based reasoning for machining parameters selection

    Science.gov (United States)

    Grabowik, C.; Kalinowski, K.; Krenczyk, D.; Paprocka, I.; Kempa, W.

    2016-08-01

    Process planning, as one of the most important stage of the technological production preparation, consists in selection of manufacturing operations taking into account the minimal manufacturing cost. The minimal manufacturing cost could be achieved by selection of the best sequence of manufacturing operations, machine tools, manufacturing tools, and accompanying machining parameters selection. On the other hand, it is almost impossible, especially in industrial conditions, to design an optimal process plan, first of all due to restrictions imposed by the installed in the factory machine park. Taking into consideration above, machining parameter selection seems to be one of the potential areas of optimization. In manual process planning process engineers select machining parameters using selection rules and data stored in manuals and tool catalogues. It makes this process time and labour consuming and non-error free. On the other hand, in workshop practice, machine operators select parameters having their skills and habits in mind. It could be a reason for suboptimal process planning. Considering this, new methods of machining parameters selection free of human factor influence are still sought. In our approach, we propose to apply case-based reasoning for machining parameter selection. In the paper, a detailed description of our approach is presented.

  3. 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.

  4. 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 ...

  5. 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...

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. Cluster editing

    DEFF Research Database (Denmark)

    Böcker, S.; Baumbach, Jan

    2013-01-01

    . The problem has been the inspiration for numerous algorithms in bioinformatics, aiming at clustering entities such as genes, proteins, phenotypes, or patients. In this paper, we review exact and heuristic methods that have been proposed for the Cluster Editing problem, and also applications......The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side...

  14. Weighted Clustering

    CERN Document Server

    Ackerman, Margareta; Branzei, Simina; Loker, David

    2011-01-01

    In this paper we investigate clustering in the weighted setting, in which every data point is assigned a real valued weight. We conduct a theoretical analysis on the influence of weighted data on standard clustering algorithms in each of the partitional and hierarchical settings, characterising the precise conditions under which such algorithms react to weights, and classifying clustering methods into three broad categories: weight-responsive, weight-considering, and weight-robust. Our analysis raises several interesting questions and can be directly mapped to the classical unweighted setting.

  15. Cluster analysis

    CERN Document Server

    Everitt, Brian S; Leese, Morven; Stahl, Daniel

    2011-01-01

    Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.Real life examples are used throughout to demons

  16. 基于自适应核学习相关向量机的乳腺X线图像微钙化点簇处理方法研究%Microcalcification clusters processing in mammograms based on relevance vector machine with adaptive kernel learning∗

    Institute of Scientific and Technical Information of China (English)

    姚畅†; 陈后金; YangYong-Yi; 李艳凤; 韩振中; 张胜君

    2013-01-01

    Using the method of adaptive kernel learning based relevance vector machine (ARVM) and combining the morphological filtering and the clustering criterion recommended by Kallergi, a new algorithm for microcalcification (MC) clusters processing in mammo-grams is investigated. Firstly, the detection of MC is formulated as a supervised-learning problem. Then the ARVM is used as a classifier to determine whether an MC object is present at each location in the mammogram and a morphological processing is used to remove the isolated spurious pixels. Finally, the identified MC clusters are obtained by Kallergi criterion. To improve the compu-tational speed, a fast processing method based on ARVM is developed, in which the whole image is decomposed first into sub-image blocks for parallel operation. Experimental results indicate that the ARVM method outperforms the RVM method and, in particular, the fast processing method could greatly reduce the testing time.%  采用自适应核学习相关向量机方法,结合形态学滤波和Kallergi分簇标准,研究了乳腺X线图像中微钙化点簇的处理。首先将微钙化点检测看作一个监督学习问题,然后应用自适应核学习相关向量机作为分类器判断图像中每一个位置是否为微钙化点并采用形态学处理滤除干扰噪声,最后对获得的微钙化点采用Kallergi标准进行分簇。为提高运算速度,在微钙化点检测时将整个图像分解为多个子图像并行运算,实现了一种基于自适应核学习相关向量机的微钙化点簇快速处理方法。实验结果和分析表明,自适应核学习相关向量机方法算法性能优于相关向量机方法,特别是实现的快速方法能进一步降低微钙化点簇的处理时间。

  17. 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.

  18. 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...

  19. Fast Training of Support Vector Machines Using Error-Center-Based Optimization

    Institute of Scientific and Technical Information of China (English)

    L. Meng; Q. H. Wu

    2005-01-01

    This paper presents a new algorithm for Support Vector Machine (SVM) training, which trains a machine based on the cluster centers of errors caused by the current machine. Experiments withvarious training sets show that the computation time of this new algorithm scales almost linear with training set size and thus may be applied to much larger training sets, in comparison to standard quadratic programming (QP) techniques.

  20. Modern machine learning techniques and their applications in cartoon animation research

    CERN Document Server

    Yu, Jun

    2013-01-01

    The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations

  1. TensorFlow: A system for large-scale machine learning

    OpenAIRE

    2016-01-01

    TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general-purpose GPUs, and custom designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexib...

  2. An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

    Science.gov (United States)

    Hennig, Holger; Rees, Paul; Blasi, Thomas; Kamentsky, Lee; Hung, Jane; Dao, David; Carpenter, Anne E; Filby, Andrew

    2017-01-01

    Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples. However, data analysis is often performed in a highly manual and subjective manner using very limited image analysis techniques in combination with conventional flow cytometry gating strategies. This approach is not scalable to the hundreds of available image-based features per cell and thus makes use of only a fraction of the spatial and morphometric information. As a result, the quality, reproducibility and rigour of results are limited by the skill, experience and ingenuity of the data analyst. Here, we describe a pipeline using open-source software that leverages the rich information in digital imagery using machine learning algorithms. Compensated and corrected raw image files (.rif) data files from an imaging flow cytometer (the proprietary .cif file format) are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analysed using cutting-edge machine learning and clustering approaches using "user-friendly" platforms such as CellProfiler Analyst. Researchers can train an automated cell classifier to recognize different cell types, cell cycle phases, drug treatment/control conditions, etc., using supervised machine learning. This workflow should enable the scientific community to leverage the full analytical power of IFC-derived data sets. It will help to reveal otherwise unappreciated populations of cells based on features that may be hidden to the human eye that include subtle measured differences in label free detection channels such as bright-field and dark-field imagery.

  3. Fuzzy Clustering

    DEFF Research Database (Denmark)

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  4. 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.

  5. 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...

  6. Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

    Science.gov (United States)

    Saeed, Faisal; Salim, Naomie; Abdo, Ammar

    2013-07-01

    Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures.

  7. Using Sub Skills to Model and Estimate Final Skill Level

    Directory of Open Access Journals (Sweden)

    Hadi Moradi

    2013-04-01

    Full Text Available Skill level estimation is very important since it allows an instructor, a human or an artificial instructor through an intelligent tutoring system, to predict the level of a student and adjust the learning materials accordingly. In this paper, a new approach based on 1-NN (First Nearest Neighbor is introduced to determine the skill level of a student based on the pattern of skill levels learned over time in the same course. The data over several years are used to determine four clusters of expert, good, average and bad skill level. The advantage of the proposed approach is in its capability to adjust the levels over time based on the new data received each year. Furthermore, it can estimate the skill level after a few homework or project assignments. Consequently it can help an instructor to better conduct its class. The proposed approach has been implemented and tested on an introductory computer programming course and the results prove the validity of the approach.

  8. Scalable Machine Learning Framework for Behavior-Based Access Control

    Science.gov (United States)

    2013-08-01

    Mahout [10] is an open-source project for scalable machine learning. It provide ready implementations for K-Means clustering following a MapReduce ...paradigm, but does not provide MapReduce implementations for SVMs, which are the most expensive models to train in BBAC. Massive Online Analysis

  9. 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.

  10. Numerical Control Machining and the Issue of Deskilling. An Empirical View.

    Science.gov (United States)

    Zicklin, Gilbert

    1987-01-01

    Research on the effects of numerical control (NC) machining on the skills of machinists presents mixed results. Interviews with a small group of machinists experienced in both conventional and NC matching suggest seven major factors that affect whether NC automation changes the overall skill level. The deskilling hypothesis is not supported by…

  11. 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.

  12. Experiments with the Dragon Machine

    Energy Technology Data Exchange (ETDEWEB)

    R.E. Malenfant

    2005-08-12

    The basic characteristics of a self-sustaining chain reaction were demonstrated with the Chicago Pile in 1943, but it was not until early 1945 that sufficient enriched material became available to experimentally verify fast-neutron cross-sections and the kinetic characteristics of a nuclear chain reaction sustained with prompt neutrons alone. However, the demands of wartime and the rapid decline in effort following the cessation of hostilities often resulted in the failure to fully document the experiments or in the loss of documentation as personnel returned to civilian pursuits. When documented, the results were often highly classified. Even when eventually declassified, the data were often not approved for public release until years later.2 Even after declassification and approval for public release, the records are sometimes difficult to find. Through a fortuitous discovery, a set of handwritten notes by ''ORF July 1945'' entitled ''Dragon - Research with a Pulsed Fission Reactor'' was found by William L. Myers in an old storage safe at Pajarito Site of the Los Alamos National Laboratory3. Of course, ORF was identified as Otto R. Frisch. The document was attached to a page in a nondescript spiral bound notebook labeled ''494 Book'' that bore the signatures of Louis Slotin and P. Morrison. The notes also reference an ''Idea LS'' that can only be Louis Slotin. The discovery of the notes led to a search of Laboratory Archives, the negative files of the photo lab, and the Report Library for additional details of the experiments with the Dragon machine that were conducted between January and July 1945. The assembly machine and the experiments were carefully conceived and skillfully executed. The analyses--without the crutch of computers--display real insight into the characteristics of the nuclear chain reaction. The information presented here provides what is believed to be a complete

  13. 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.

  14. Turning toys into microgravity machines

    Science.gov (United States)

    Sumners, C.; Reiff, P.

    The Toys in Space program communicates the experience of being in space and ultimately living in space. In space, what would happen to a yo-yo's speed, a top's wobble, or your skill in playing soccer, throwing a boomerang or jumping rope? Discover how these toys and others have performed in microgravity and how these demonstrations can link children to the space program. On April 12, 1985 astronauts carried the first experiment package of miniature mechanical systems called toys into space. Since that time 54 toys have been demonstrated in microgravity. This summer, NASA and the Houston Museum of Natural Science have sponsored the first International Toys in Space project with sixteen toys chosen for their popularity and relevance around the world. This set of toys takes advantage of the larger Space Station by providing toys that take up more room - from two-person games of soccer, lacrosse, marbles, and hockey to a jump rope and several kinds of yoyos. Three earlier Toys in Space missions have shown that toys are ideal machines to demonstrate how gravity affects moving objects on the Earth's surface and how the motions of these objects change in microgravity. In this presentation, participants actually experiment with miniature versions of toys, predict their behavior on orbit, and watch the surprising results. Participants receive toy patterns to share with young people at home, around the world. The Toys in Space program scales for all ages. Young learners can use their observation and comparison skills while older students apply physics concepts to toy behaviors. Concepts demonstrated include all of Newton's Laws of Motion, gyroscopic stability, centripetal force, density, as well as conservation of linear and angular momentum.

  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. EVALUATION OF THE MACHINE MODERNITY IN THE MOTOR INDUSTRY

    Directory of Open Access Journals (Sweden)

    Manuela Krystyna Ingaldi

    2014-12-01

    Full Text Available Most manufacturing companies realize its technologies, implemented through concrete machinery parts. They differ in terms of importance, the relevance of their selection and the level of their modernity. The purpose of this article is to analyse the chosen production machine in terms of its modernity. The ABC technology method was chosen do this research. All parts of the machine were divided into three groups: parts of main subassembly A, parts of supportive subassembly B, parts of collateral subassembly C. Then each of these parts was evaluated in the Parker's five-point scale. From the conducted analysis it results that most parts of the research machine were manufactured with more complex technologies, requiring technical skills and knowledge or with unchanging technologies used for years. It means that the research machine is not a modern machine. Perhaps company managers should take a decision on the change of the machine for the newer one. This would allow for improvement of the technical parameters of the products, increase in production efficiency and reduction of the amount of nonconforming products. Therefore, it can be concluded that a properly selected and correctly applied parts of the subassemblies contribute to the improvement in quality of products and the efficiency of the machine.

  20. Scaling Datalog for Machine Learning on Big Data

    CERN Document Server

    Bu, Yingyi; Carey, Michael J; Rosen, Joshua; Polyzotis, Neoklis; Condie, Tyson; Weimer, Markus; Ramakrishnan, Raghu

    2012-01-01

    In this paper, we present the case for a declarative foundation for data-intensive machine learning systems. Instead of creating a new system for each specific flavor of machine learning task, or hardcoding new optimizations, we argue for the use of recursive queries to program a variety of machine learning systems. By taking this approach, database query optimization techniques can be utilized to identify effective execution plans, and the resulting runtime plans can be executed on a single unified data-parallel query processing engine. As a proof of concept, we consider two programming models--Pregel and Iterative Map-Reduce-Update---from the machine learning domain, and show how they can be captured in Datalog, tuned for a specific task, and then compiled into an optimized physical plan. Experiments performed on a large computing cluster with real data demonstrate that this declarative approach can provide very good performance while offering both increased generality and programming ease.

  1. 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...

  2. 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...

  3. 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

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. 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.

  10. 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.

  11. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    .g. sustainability or quality of life. The purpose of this paper is to explore how and to what extent public sector interventions that aim at forcing cluster development in industries can support sustainable development as defined in the Brundtland tradition and more recently elaborated in such concepts as eco......, Portugal and New Zealand have adopted the concept. Public sector interventions that aim to support cluster development in industries most often focus upon economic policy goals such as enhanced employment and improved productivity, but rarely emphasise broader societal policy goals relating to e...... to the automotive sector in Wales. Specifically, the paper evaluates the "Accelerates" programme initiated by the Welsh Development Agency and elaborates on how and to what extent the Accelerate programme supports the development of a sustainable automotive industry cluster. The Accelerate programme was set up...

  12. Scalable Machine Learning for Massive Astronomical Datasets

    Science.gov (United States)

    Ball, Nicholas M.; Gray, A.

    2014-04-01

    We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex

  13. 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

  14. Clustervision: Visual Supervision of Unsupervised Clustering.

    Science.gov (United States)

    Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; deFilippi, Christopher; Stewart, Walter F; Perer, Adam

    2017-08-29

    Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

  15. Characterization of oats (Avena sativa L.) cultivars using machine vision.

    Science.gov (United States)

    Sumathi, S; Balamurugan, P

    2013-10-15

    Machine vision or image analysis is an important tool in the study of morphology of any materials. This technique has been used successfully to differentiate the eleven oats cultivars based on morphological characters. The geometry of seeds was measured through image analyzer and the variation was observed and recorded. From the recorded data, the cluster analysis was carried out and it revealed that the cultivars could be grouped into two main clusters based on similarity in the measured parameters. Cultivar Sabzar, UPO 212, OL 9 and OL 88 formed one main cluster. The another main cluster includes cv. Kent, OS 6, UPO 94, HFO 114, OS 7, HJ 8 and JHO 822 with many sub clusters. Among the cultivars HJ 8 and JHO 822 has more similarity in all measured parameters than other cultivars. Thus morphological characterization through seed image analysis was found useful to discriminate the cultivars.

  16. Cluster Formation Using Kohonens Self-Organising Map

    Directory of Open Access Journals (Sweden)

    Vivekanand S Gogi

    2012-06-01

    Full Text Available An Artificial Neural Network (ANN is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons working in unison to solve specific problems. The objective of this research paper is to study the clustering of requests from the Flexible Manufacturing System machines to the Automated Storage/Retrieval system and to optimize the clustering of the requests. Artificial Neural Networks has been used for clustering the requests from the machines. Unsupervised Learning (training algorithm in Artificial Neural Networks is used and implemented using C++ programming language. The requests from the machines are successfully analyzed and optimization of clusters is done using Kohonens SelfOrganizing Map technique.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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...

  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...

  5. 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.

  6. 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,…

  7. 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;…

  8. 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

  9. 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.

  10. Cluster forcing

    DEFF Research Database (Denmark)

    Christensen, Thomas Budde

    The cluster theory attributed to Michael Porter has significantly influenced industrial policies in countries across Europe and North America since the beginning of the 1990s. Institutions such as the EU, OECD and the World Bank and governments in countries such as the UK, France, The Netherlands...

  11. THE INFLUENCE OF THEME AS SLOT MACHINE ATTRIBUTE ON CASINO GAMERS DECISION-MAKING

    Directory of Open Access Journals (Sweden)

    Elizma Wannenburg

    2013-01-01

    Full Text Available When entering the casino gaming area, gamers are faced with hundreds of slot machines that vary in terms of themes, colours and sounds. Some gaming situations are characterized by low gamer involvement, but with considerable brand differences. Gamers visiting a casino have the option to play on various types of slot machines. Slot machine games range from single-bar to triple-bar combinations that range in themes and symbols. Some gamers prefer to play on the same slot machine game each time they visit the casino; while other gamers often do slot machine switching. The hypothesis set for this study was to determine if any differences exist between male and female slot machine gamers regarding the way they perceive theme as a slot machine attribute. The sample population identified consists of slot machine gamers busy playing at a specific slot machine in the gaming area of the casino. Cluster sampling was used in the selection of the six South African casinos. A total of six hundred and thirty structured questionnaires were obtained through personal interviews in the gaming areas of the casinos. The raw data collected were statistically analysed on the SPSS program. The main findings of the research indicated that no significant differences exist between male and female slot machine gamers regarding the way they perceive theme as a slot machine attribute. The findings of this study could assist the casino management and slot machine manufacturers in understanding how themes as slot machine attributes influence gamers. By understanding the importance of themes for slot machine gamers can assist casino management and slot machine manufacturers in the development of new slot machines.

  12. 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.

  13. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... and Skills Resources Educational Resources Educational Resources E-Learning Evidence-Based Decisions in Surgery Medical Student Resources ... Skills Kit supports patients with educational and simulation materials to learn and practice the skills needed for ...

  14. 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"--

  15. 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...

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. Quotients of cluster categories

    OpenAIRE

    Jorgensen, Peter

    2007-01-01

    Higher cluster categories were recently introduced as a generalization of cluster categories. This paper shows that in Dynkin types A and D, half of all higher cluster categories are actually just quotients of cluster categories. The other half can be obtained as quotients of 2-cluster categories, the "lowest" type of higher cluster categories. Hence, in Dynkin types A and D, all higher cluster phenomena are implicit in cluster categories and 2-cluster categories. In contrast, the same is not...

  3. 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

  4. 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

  5. Mechanical considerations and design skills.

    Energy Technology Data Exchange (ETDEWEB)

    Alvis, Robert L.

    2008-03-01

    The purpose of the report is to provide experienced-based insights into design processes that will benefit designers beginning their employment at Sandia National Laboratories or those assuming new design responsibilities. The main purpose of this document is to provide engineers with the practical aspects of system design. The material discussed here may not be new to some readers, but some of it was to me. Transforming an idea to a design to solve a problem is a skill, and skills are similar to history lessons. We gain these skills from experience, and many of us have not been fortunate enough to grow in an environment that provided the skills that we now need. I was fortunate to grow up on a farm where we had to learn how to maintain and operate several different kinds of engines and machines. If you are like me, my formal experience is partially based upon the two universities from which I graduated, where few practical applications of the technologies were taught. What was taught was mainly theoretical, and few instructors had practical experience to offer the students. I understand this, as students have their hands full just to learn the theoretical. The practical part was mainly left up to 'on the job experience'. However, I believe it is better to learn the practical applications early and apply them quickly 'on the job'. System design engineers need to know several technical things, both in and out of their field of expertise. An engineer is not expected to know everything, but he should know when to ask an expert for assistance. This 'expert' can be in any field, whether it is in analyses, drafting, machining, material properties, testing, etc. The best expert is a person who has practical experience in the area of needed information, and consulting with that individual can be the best and quickest way for one to learn. If the information provided here can improve your design skills and save one design from having a problem

  6. Regional Innovation Clusters

    Data.gov (United States)

    Small Business Administration — The Regional Innovation Clusters serve a diverse group of sectors and geographies. Three of the initial pilot clusters, termed Advanced Defense Technology clusters,...

  7. 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.

  8. 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

  9. 3D Visualization of Machine Learning Algorithms with Astronomical Data

    Science.gov (United States)

    Kent, Brian R.

    2016-01-01

    We present innovative machine learning (ML) methods using unsupervised clustering with minimum spanning trees (MSTs) to study 3D astronomical catalogs. Utilizing Python code to build trees based on galaxy catalogs, we can render the results with the visualization suite Blender to produce interactive 360 degree panoramic videos. The catalogs and their ML results can be explored in a 3D space using mobile devices, tablets or desktop browsers. We compare the statistics of the MST results to a number of machine learning methods relating to optimization and efficiency.

  10. Energy landscapes for a machine learning application to series data.

    Science.gov (United States)

    Ballard, Andrew J; Stevenson, Jacob D; Das, Ritankar; Wales, David J

    2016-03-28

    Methods developed to explore and characterise potential energy landscapes are applied to the corresponding landscapes obtained from optimisation of a cost function in machine learning. We consider neural network predictions for the outcome of local geometry optimisation in a triatomic cluster, where four distinct local minima exist. The accuracy of the predictions is compared for fits using data from single and multiple points in the series of atomic configurations resulting from local geometry optimisation and for alternative neural networks. The machine learning solution landscapes are visualised using disconnectivity graphs, and signatures in the effective heat capacity are analysed in terms of distributions of local minima and their properties.

  11. 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

  12. Cluster Radioactivity

    Science.gov (United States)

    Poenaru, Dorin N.; Greiner, Walter

    One of the rare examples of phenomena predicted before experimental discovery, offers the opportunity to introduce fission theory based on the asymmetric two center shell model. The valleys within the potential energy surfaces are due to the shell effects and are clearly showing why cluster radioactivity was mostly detected in parent nuclei leading to a doubly magic lead daughter. Saddle point shapes can be determined by solving an integro-differential equation. Nuclear dynamics allows us to calculate the half-lives. The following cluster decay modes (or heavy particle radioactivities) have been experimentally confirmed: 14C, 20O, 23F, 22,24-26Ne, 28,30Mg, 32,34Si with half-lives in good agreement with predicted values within our analytical superasymmetric fission model. The preformation probability is calculated as the internal barrier penetrability. An universal curve is described and used as an alternative for the estimation of the half-lives. The macroscopic-microscopic method was extended to investigate two-alpha accompanied fission and true ternary fission. The methods developed in nuclear physics are also adapted to study the stability of deposited atomic clusters on the planar surfaces.

  13. 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.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

  19. 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...

  20. 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...

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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 ...

  10. Voting-based consensus clustering for combining multiple clusterings of chemical structures

    Directory of Open Access Journals (Sweden)

    Saeed Faisal

    2012-12-01

    Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

  11. Mutation Clusters from Cancer Exome.

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2017-08-15

    We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development.

  12. 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...

  13. 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...

  14. Practical skills of the future innovator

    Science.gov (United States)

    Kaurov, Vitaliy

    2015-03-01

    Physics graduates face and often are disoriented by the complex and turbulent world of startups, incubators, emergent technologies, big data, social network engineering, and so on. In order to build the curricula that foster the skills necessary to navigate this world, we will look at the experiences at the Wolfram Science Summer School that gathers annually international students for already more than a decade. We will look at the examples of projects and see the development of such skills as innovative thinking, data mining, machine learning, cloud technologies, device connectivity and the Internet of things, network analytics, geo-information systems, formalized computable knowledge, and the adjacent applied research skills from graph theory to image processing and beyond. This should give solid ideas to educators who will build standard curricula adapted for innovation and entrepreneurship education.

  15. An interesting review on soft skills and dental practice.

    Science.gov (United States)

    Dalaya, Maya; Ishaquddin, Syed; Ghadage, Mahesh; Hatte, Geeta

    2015-03-01

    In today's world of education, we concentrate on teaching activities and academic knowledge. We are taught to improve our clinical skills. Soft skills refer to the cluster of personality traits, social graces, and personal habits, facility with language, friendliness and personal habits that mark people to varying degrees. Soft Skills are interpersonal, psychological, self-promoted and non-technical qualities for every practitioner and academician, whereas hard skills are new tools or equipment and professional knowledge. Hence, more and more clinicians now days consider soft skills as important job criteria. An increase in service industry and competitive practices emphasizes the need for soft skills. Soft Skills are very important and useful in personal and professional life.

  16. Competency Index. [Business/Computer Technologies Cluster.

    Science.gov (United States)

    Ohio State Univ., Columbus. Center on Education and Training for Employment.

    This index allows the user to scan the competencies under each title for the 28 subjects appropriate for use in a competency list for the 12 occupations within the business/computer technologies cluster. Titles of the 28 units are as follows: employability skills; professionalism; teamwork; professional and ethical standards; economic and business…

  17. CELL FORMATION IN GROUP TECHNOLOGY: A SIMILARITY ORDER CLUSTERING APPROACH

    Directory of Open Access Journals (Sweden)

    Godfrey C. Onwubolu

    2012-01-01

    Full Text Available Grouping parts into families which can be produced by a cluster of machine cells is the cornerstone of cellular manufacturing, which in turn is the building block for flexible manufacturing systems. Cellular manufacturing is a group technology (GT concept that has recently attracted the attention of manufacturing firms operating under jobshop environment to consider redesigning their manufacturing systems so as to take advantage of increased throughput, reduction in work-in-progress, set-up time, and lead times; leading to product quality and customer satisfaction. The paper presents a generalised approach for machine cell formation from a jobshop using similarity order clustering technique for preliminary cell grouping and considering machine utilisation for the design of nonintergrouping material handling using the single-pass heuristic. The work addresses the shortcomings of cellular manufacturing systems design and implementations which ignore machine utilisations, group sizes and intergroup moves.

  18. Associations between Early Childhood Temperament Clusters and Later Psychosocial Adjustment

    Science.gov (United States)

    Sanson, Ann; Letcher, Primrose; Smart, Diana; Prior, Margot; Toumbourou, John W.; Oberklaid, Frank

    2009-01-01

    The study adopted a person-centered approach to examine whether clusters of children could be identified on the basis of temperament profiles assessed on four occasions from infancy to early childhood, and if so whether differing temperament clusters were associated with subsequent differences in behavior problems, social skills, and school…

  19. Module Cluster: IFE - 002.00 (GSC) Educational Policy.

    Science.gov (United States)

    Zahn, R. D.

    This document is one of several module clusters developed for the Camden Teacher Corps project. This module cluster is designed to enable students to have experience with and develop skills in writing educational policy, anticipating problems related to the implementation of the policy, and planning possible actions or strategies the teacher might…

  20. Performance Analysis of Hierarchical Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    K.Ranjini

    2011-07-01

    Full Text Available Clustering is the classification of objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters, so that the data in each subset (ideally share some common trait - often proximity according to some defined distance measure. Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. This paper explains the implementation of agglomerative and divisive clustering algorithms applied on various types of data. The details of the victims of Tsunami in Thailand during the year 2004, was taken as the test data. Visual programming is used for implementation and running time of the algorithms using different linkages (agglomerative to different types of data are taken for analysis.

  1. Optimization of line configuration and balancing for flexible machining lines

    Science.gov (United States)

    Liu, Xuemei; Li, Aiping; Chen, Zurui

    2016-05-01

    Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.

  2. 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.

  3. An Automatic Clustering Technique for Optimal Clusters

    CERN Document Server

    Pavan, K Karteeka; Rao, A V Dattatreya; 10.5121/ijcsea.2011.1412

    2011-01-01

    This paper proposes a simple, automatic and efficient clustering algorithm, namely, Automatic Merging for Optimal Clusters (AMOC) which aims to generate nearly optimal clusters for the given datasets automatically. The AMOC is an extension to standard k-means with a two phase iterative procedure combining certain validation techniques in order to find optimal clusters with automation of merging of clusters. Experiments on both synthetic and real data have proved that the proposed algorithm finds nearly optimal clustering structures in terms of number of clusters, compactness and separation.

  4. 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.

  5. Waveform interative techniques for device transient simulation on parallel machines

    Energy Technology Data Exchange (ETDEWEB)

    Lumsdaine, A. [Univ. of Notre Dame, IN (United States); Reichelt, M.W. [Massachusetts Institute of Technology, Cambridge, MA (United States)

    1993-12-31

    In this paper we describe our experiences with parallel implementations of several different waveform algorithms for performing transient simulation of semiconductor devices. Because of their inherent computation and communication structure, waveform methods are well suited to MIMD-type parallel machines having a high communication latency - such as a cluster of workstations. Experimental results using pWORDS, a parallel waveform-based device transient simulation program, in conjunction with PVM running on a cluster of eight workstations demonstrate that parallel waveform techniques are an efficient and faster alternative to standard simulation algorithms.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions

    CERN Document Server

    Poczos, Barnabas; Schneider, Jeff

    2012-01-01

    Low-dimensional embedding, manifold learning, clustering, classification, and anomaly detection are among the most important problems in machine learning. The existing methods usually consider the case when each instance has a fixed, finite-dimensional feature representation. Here we consider a different setting. We assume that each instance corresponds to a continuous probability distribution. These distributions are unknown, but we are given some i.i.d. samples from each distribution. Our goal is to estimate the distances between these distributions and use these distances to perform low-dimensional embedding, clustering/classification, or anomaly detection for the distributions. We present estimation algorithms, describe how to apply them for machine learning tasks on distributions, and show empirical results on synthetic data, real word images, and astronomical data sets.

  13. Dimensionality Reduction for Optimal Clustering In Data Mining

    Directory of Open Access Journals (Sweden)

    Ch. Raja Ramesh

    2011-10-01

    Full Text Available Spectral clustering and Leader’s algorithm have both been used to identify clusters that are nonlinearly separable in input space. Despite significant research, these methods have remained only loosely related. Sigmoid kernel and polynomial kernel were quite popular for support vector machines due to its origin from clustering. In this paper we are submitting the comparison of above kernel methods after reducing the dimensions using feature functions. For this we have given hand writing data -sets to create and compare the clusters.

  14. Assessing Progress in Mastery of Counseling Communication Skills

    NARCIS (Netherlands)

    A.J. Kuntze (Jeroen)

    2009-01-01

    textabstractDuring the last century the attention paid in higher education to the development of professional skills has progressively increased. In the first half of the last century the term ‘skill’ mainly referred to motor or technical actions, for instance driving a car or operating a machine (M

  15. Assessing Progress in Mastery of Counseling Communication Skills

    NARCIS (Netherlands)

    A.J. Kuntze (Jeroen)

    2009-01-01

    textabstractDuring the last century the attention paid in higher education to the development of professional skills has progressively increased. In the first half of the last century the term ‘skill’ mainly referred to motor or technical actions, for instance driving a car or operating a machine (M

  16. Assessing Progress in Mastery of Counseling Communication Skills

    NARCIS (Netherlands)

    A.J. Kuntze (Jeroen)

    2009-01-01

    textabstractDuring the last century the attention paid in higher education to the development of professional skills has progressively increased. In the first half of the last century the term ‘skill’ mainly referred to motor or technical actions, for instance driving a car or operating a machine

  17. Detecting Clusters in Atom Probe Data with Gaussian Mixture Models.

    Science.gov (United States)

    Zelenty, Jennifer; Dahl, Andrew; Hyde, Jonathan; Smith, George D W; Moody, Michael P

    2017-04-01

    Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.

  18. 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...

  19. 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.

  20. Kernel-based Maximum Entropy Clustering

    Institute of Scientific and Technical Information of China (English)

    JIANG Wei; QU Jiao; LI Benxi

    2007-01-01

    With the development of Support Vector Machine (SVM),the "kernel method" has been studied in a general way.In this paper,we present a novel Kernel-based Maximum Entropy Clustering algorithm (KMEC).By using mercer kernel functions,the proposed algorithm is firstly map the data from their original space to high dimensional space where the data are expected to be more separable,then perform MEC clustering in the feature space.The experimental results show that the proposed method has better performance in the non-hyperspherical and complex data structure.

  1. Towards the compression of parton densities through machine learning algorithms

    CERN Document Server

    Carrazza, Stefano

    2016-01-01

    One of the most fascinating challenges in the context of parton density function (PDF) is the determination of the best combined PDF uncertainty from individual PDF sets. Since 2014 multiple methodologies have been developed to achieve this goal. In this proceedings we first summarize the strategy adopted by the PDF4LHC15 recommendation and then, we discuss about a new approach to Monte Carlo PDF compression based on clustering through machine learning algorithms.

  2. Machine Learning Tools for Geomorphic Mapping of Planetary Surfaces

    OpenAIRE

    Stepinski, Tomasz F.; Vilalta, Ricardo

    2010-01-01

    Geomorphic auto-mapping of planetary surfaces is a challenging problem. Here we have described how machine learning techniques, such as clustering or classification, can be utilized to automate the process of geomorphic mapping for exploratory and exploitation purposes. Relatively coarse resolution of planetary topographic data limits the number of features that can be used in the learning process and makes planetary auto-mapping more challenging than terrestrial auto-mapping. With this cavea...

  3. 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.

  4. 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.

  5. 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....

  6. Desired skills and attributes for dietitian preceptors.

    Science.gov (United States)

    Walker, Sharon; Grosjean, Garnet

    2010-01-01

    We examined the research literature to determine the skills and attributes that dietetic interns desire in clinical preceptors. A search of three databases produced little information specific to dietetics. Literature on preceptors in other health disciplines identified preceptor attributes that students in clinical placements value. We were able to cluster the data from these studies into four themes: knowledge and experience, personal characteristics, teaching skills and attitudes, and interpersonal relationships. This review suggests a need for further development of dietitian preceptor training, as well as for further research specific to dietetic interns' needs.

  7. 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.

  8. 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.

  9. Transliteration normalization for Information Extraction and Machine Translation

    Directory of Open Access Journals (Sweden)

    Yuval Marton

    2014-12-01

    Full Text Available Foreign name transliterations typically include multiple spelling variants. These variants cause data sparseness and inconsistency problems, increase the Out-of-Vocabulary (OOV rate, and present challenges for Machine Translation, Information Extraction and other natural language processing (NLP tasks. This work aims to identify and cluster name spelling variants using a Statistical Machine Translation method: word alignment. The variants are identified by being aligned to the same “pivot” name in another language (the source-language in Machine Translation settings. Based on word-to-word translation and transliteration probabilities, as well as the string edit distance metric, names with similar spellings in the target language are clustered and then normalized to a canonical form. With this approach, tens of thousands of high-precision name transliteration spelling variants are extracted from sentence-aligned bilingual corpora in Arabic and English (in both languages. When these normalized name spelling variants are applied to Information Extraction tasks, improvements over strong baseline systems are observed. When applied to Machine Translation tasks, a large improvement potential is shown.

  10. 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

  11. 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.

  12. 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.

  13. First Cluster Algorithm Special Purpose Processor

    Science.gov (United States)

    Talapov, A. L.; Andreichenko, V. B.; Dotsenko S., Vi.; Shchur, L. N.

    We describe the architecture of the special purpose processor built to realize in hardware cluster Wolff algorithm, which is not hampered by a critical slowing down. The processor simulates two-dimensional Ising-like spin systems. With minor changes the same very effective architecture, which can be defined as a Memory Machine, can be used to study phase transitions in a wide range of models in two or three dimensions.

  14. Heavy hitters via cluster-preserving clustering

    DEFF Research Database (Denmark)

    Larsen, Kasper Green; Nelson, Jelani; Nguyen, Huy L.

    2016-01-01

    , providing correctness whp. In fact, a simpler version of our algorithm for p = 1 in the strict turnstile model answers queries even faster than the "dyadic trick" by roughly a log n factor, dominating it in all regards. Our main innovation is an efficient reduction from the heavy hitters to a clustering...... problem in which each heavy hitter is encoded as some form of noisy spectral cluster in a much bigger graph, and the goal is to identify every cluster. Since every heavy hitter must be found, correctness requires that every cluster be found. We thus need a "cluster-preserving clustering" algorithm......, that partitions the graph into clusters with the promise of not destroying any original cluster. To do this we first apply standard spectral graph partitioning, and then we use some novel combinatorial techniques to modify the cuts obtained so as to make sure that the original clusters are sufficiently preserved...

  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. Brief introduction of lathe machining

    Institute of Scientific and Technical Information of China (English)

    蔡亮

    2015-01-01

    In the vocational education, the general lathe and CNC lathe skill teaching is the mechanical profession student's required spe⁃cialized basic skill course, this paper combined with the teaching practice, the above two kinds of lathes are simply introduced.

  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. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Legislation Tracked by the College Quality Quality Quality Electronic Health Records (EHR) Incentive Program Physician Quality Reporting ... Skills Kit supports patients with educational and simulation materials to learn and practice the skills needed for ...

  1. Ostomy Home Skills Program

    Science.gov (United States)

    ... Surgery Resident Skills Curriculum ACS/APDS/ASE Resident Prep Curriculum ACS/ASE Medical Student Core Curriculum ACS/ ... Registry Trauma Education Trauma Education Trauma Education Achieving Zero Preventable Deaths Trauma Systems Conference Advanced Surgical Skills ...

  2. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Surgery Resident Skills Curriculum ACS/APDS/ASE Resident Prep Curriculum ACS/ASE Medical Student Core Curriculum ACS/ ... Registry Trauma Education Trauma Education Trauma Education Achieving Zero Preventable Deaths Trauma Systems Conference Advanced Surgical Skills ...

  3. Teaching Reading Skills

    Institute of Scientific and Technical Information of China (English)

    刘恒

    2014-01-01

    Reading skills are very important part in language teaching and learning. This paper is written after attending lectures given by an Australian teacher named Rod Ellis focusing on how to teach reading skills using authentic materials.

  4. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... skills such as emptying and changing a pouch, problem solving, and home management. A DVD with demonstration of each skill Stoma Practice Model Stoma supplies (measurement guide, marking ...

  5. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... You Want to Be a Surgeon Resident Resources Teaching Resources Online Guide to Choosing a Surgical Residency ... Skills Kit supports patients with educational and simulation materials to learn and practice the skills needed for ...

  6. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... You Want to Be a Surgeon Resident Resources Teaching Resources Online Guide to Choosing a Surgical Residency ... Ostomy Home Skills Program Ostomy Home Skills Program Adult Ostomy Pediatric Ostomy Programa de Destrezas para manejo ...

  7. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Stay Up to Date with ACS Association Management Jobs Events Find a Surgeon Patients and Family Contact My Profile Shop/Donate ( 0 ) Items American College of Surgeons Education Patients and Family Skills Programs Ostomy Home Skills ...

  8. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Trauma and EMS Cancer and Research Health Information Technology Scope of Practice Pediatric Issues Other Federal Legislative ... Skills Kit supports patients with educational and simulation materials to learn and practice the skills needed for ...

  9. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... kit contains: A booklet with information on the operation, home skills such as emptying and changing a pouch, problem solving, and home management. A DVD with demonstration of each skill Stoma ...

  10. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... AEI Consortium Quarterly ACS Chapter News The CoC Source Committee on Trauma News The Cutting Edge NAPBC ... login or create account first) Skills Kits Broadcast Rights for Hospitals Ostomy Home Skills Hospital Quality Improvement ...

  11. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... About SSC SSC Membership Directory 2016 Annual Meeting Women's Committee Mentorship Program Outside Activities ACS Archives Contact ... login or create account first) Skills Kits Broadcast Rights for Hospitals Ostomy Home Skills Hospital Quality Improvement ...

  12. Collaborative Clustering for Sensor Networks

    Science.gov (United States)

    Wagstaff. Loro :/; Green Jillian; Lane, Terran

    2011-01-01

    Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative

  13. 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.

  14. 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.

  15. 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...

  16. 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....

  17. 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 ...

  18. Cluster headache

    Directory of Open Access Journals (Sweden)

    Ducros Anne

    2008-07-01

    Full Text Available Abstract Cluster headache (CH is a primary headache disease characterized by recurrent short-lasting attacks (15 to 180 minutes of excruciating unilateral periorbital pain accompanied by ipsilateral autonomic signs (lacrimation, nasal congestion, ptosis, miosis, lid edema, redness of the eye. It affects young adults, predominantly males. Prevalence is estimated at 0.5–1.0/1,000. CH has a circannual and circadian periodicity, attacks being clustered (hence the name in bouts that can occur during specific months of the year. Alcohol is the only dietary trigger of CH, strong odors (mainly solvents and cigarette smoke and napping may also trigger CH attacks. During bouts, attacks may happen at precise hours, especially during the night. During the attacks, patients tend to be restless. CH may be episodic or chronic, depending on the presence of remission periods. CH is associated with trigeminovascular activation and neuroendocrine and vegetative disturbances, however, the precise cautive mechanisms remain unknown. Involvement of the hypothalamus (a structure regulating endocrine function and sleep-wake rhythms has been confirmed, explaining, at least in part, the cyclic aspects of CH. The disease is familial in about 10% of cases. Genetic factors play a role in CH susceptibility, and a causative role has been suggested for the hypocretin receptor gene. Diagnosis is clinical. Differential diagnoses include other primary headache diseases such as migraine, paroxysmal hemicrania and SUNCT syndrome. At present, there is no curative treatment. There are efficient treatments to shorten the painful attacks (acute treatments and to reduce the number of daily attacks (prophylactic treatments. Acute treatment is based on subcutaneous administration of sumatriptan and high-flow oxygen. Verapamil, lithium, methysergide, prednisone, greater occipital nerve blocks and topiramate may be used for prophylaxis. In refractory cases, deep-brain stimulation of the

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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…

  6. 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.

  7. 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.

  8. 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…

  9. 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.…

  10. 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).

  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. 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.

  13. Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering

    DEFF Research Database (Denmark)

    Cluster detection is a very traditional data analysis task with several decades of research. However, it also includes a large variety of different subtopics investigated by different communities such as data mining, machine learning, statistics, and database systems. "Multiple Clusterings, Multi...

  14. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Ostomy Home Skills Program Ostomy Home Skills Program Adult Ostomy Pediatric Ostomy Programa de Destrezas para manejo Doméstico de Ostomía Ostomy Home Skills Program Adult Ostomy Pediatric Ostomy Programa de Destrezas para manejo ...

  15. School Leadership Skill Development

    Science.gov (United States)

    Weigel, Richard A.

    2013-01-01

    The purpose of this study was to investigate the relationship between what is currently understood about skills for school leadership and the need for a greater understanding of those skills. The importance of developing leadership skills to improve school performance and effectiveness is great. In the field of school leadership, most leaders…

  16. Assessing Skill Development

    Science.gov (United States)

    Mueller, Jon

    2008-01-01

    Most educators are familiar with instances of authentic assessment of "content" within the disciplines or of authentic assessment of "discipline-specific skills." In such authentic assessments, students apply the knowledge and skills of the discipline to situations or tasks that replicate real world challenges. The measurement of skills is…

  17. School Leadership Skill Development

    Science.gov (United States)

    Weigel, Richard A.

    2013-01-01

    The purpose of this study was to investigate the relationship between what is currently understood about skills for school leadership and the need for a greater understanding of those skills. The importance of developing leadership skills to improve school performance and effectiveness is great. In the field of school leadership, most leaders…

  18. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... SSC About SSC SSC Membership Directory Annual Meeting ... Ostomy Pediatric Ostomy Ostomía Adulto Order Today Ostomy Home Skills Kit (login or create account first) Skills Kits Broadcast Rights for Hospitals Ostomy Home Skills Hospital Quality Improvement ...

  19. Ageing and skills

    DEFF Research Database (Denmark)

    Desjardins, Richard; Warnke, Arne Jonas

    of countries. Specifically, repeated measures will enable an analysis of whether there is skill gain and skill loss over the lifespan of cohorts and overtime between cohorts. This is especially important because age-skill profiles observed on the basis of a single cross-section are difficult to interpret...... the lifespan and over time....

  20. GEOLOGICAL MAPPING USING MACHINE LEARNING ALGORITHMS

    Directory of Open Access Journals (Sweden)

    A. S. Harvey

    2016-06-01

    Full Text Available Remotely sensed spectral imagery, geophysical (magnetic and gravity, and geodetic (elevation data are useful in a variety of Earth science applications such as environmental monitoring and mineral exploration. Using these data with Machine Learning Algorithms (MLA, which are widely used in image analysis and statistical pattern recognition applications, may enhance preliminary geological mapping and interpretation. This approach contributes towards a rapid and objective means of geological mapping in contrast to conventional field expedition techniques. In this study, four supervised MLAs (naïve Bayes, k-nearest neighbour, random forest, and support vector machines are compared in order to assess their performance for correctly identifying geological rocktypes in an area with complete ground validation information. Geological maps of the Sudbury region are used for calibration and validation. Percent of correct classifications was used as indicators of performance. Results show that random forest is the best approach. As expected, MLA performance improves with more calibration clusters, i.e. a more uniform distribution of calibration data over the study region. Performance is generally low, though geological trends that correspond to a ground validation map are visualized. Low performance may be the result of poor spectral images of bare rock which can be covered by vegetation or water. The distribution of calibration clusters and MLA input parameters affect the performance of the MLAs. Generally, performance improves with more uniform sampling, though this increases required computational effort and time. With the achievable performance levels in this study, the technique is useful in identifying regions of interest and identifying general rocktype trends. In particular, phase I geological site investigations will benefit from this approach and lead to the selection of sites for advanced surveys.

  1. Geological Mapping Using Machine Learning Algorithms

    Science.gov (United States)

    Harvey, A. S.; Fotopoulos, G.

    2016-06-01

    Remotely sensed spectral imagery, geophysical (magnetic and gravity), and geodetic (elevation) data are useful in a variety of Earth science applications such as environmental monitoring and mineral exploration. Using these data with Machine Learning Algorithms (MLA), which are widely used in image analysis and statistical pattern recognition applications, may enhance preliminary geological mapping and interpretation. This approach contributes towards a rapid and objective means of geological mapping in contrast to conventional field expedition techniques. In this study, four supervised MLAs (naïve Bayes, k-nearest neighbour, random forest, and support vector machines) are compared in order to assess their performance for correctly identifying geological rocktypes in an area with complete ground validation information. Geological maps of the Sudbury region are used for calibration and validation. Percent of correct classifications was used as indicators of performance. Results show that random forest is the best approach. As expected, MLA performance improves with more calibration clusters, i.e. a more uniform distribution of calibration data over the study region. Performance is generally low, though geological trends that correspond to a ground validation map are visualized. Low performance may be the result of poor spectral images of bare rock which can be covered by vegetation or water. The distribution of calibration clusters and MLA input parameters affect the performance of the MLAs. Generally, performance improves with more uniform sampling, though this increases required computational effort and time. With the achievable performance levels in this study, the technique is useful in identifying regions of interest and identifying general rocktype trends. In particular, phase I geological site investigations will benefit from this approach and lead to the selection of sites for advanced surveys.

  2. Exploiting Document Level Semantics in Document Clustering

    Directory of Open Access Journals (Sweden)

    Muhammad Rafi

    2016-06-01

    Full Text Available Document clustering is an unsupervised machine learning method that separates a large subject heterogeneous collection (Corpus into smaller, more manageable, subject homogeneous collections (clusters. Traditional method of document clustering works around extracting textual features like: terms, sequences, and phrases from documents. These features are independent of each other and do not cater meaning behind these word in the clustering process. In order to perform semantic viable clustering, we believe that the problem of document clustering has two main components: (1 to represent the document in such a form that it inherently captures semantics of the text. This may also help to reduce dimensionality of the document and (2 to define a similarity measure based on the lexical, syntactic and semantic features such that it assigns higher numerical values to document pairs which have higher syntactic and semantic relationship. In this paper, we propose a representation of document by extracting three different types of features from a given document. These are lexical , syntactic and semantic features. A meta-descriptor for each document is proposed using these three features: first lexical, then syntactic and in the last semantic. A document to document similarity matrix is produced where each entry of this matrix contains a three value vector for each lexical , syntactic and semantic . The main contributions from this research are (i A document level descriptor using three different features for text like: lexical, syntactic and semantics. (ii we propose a similarity function using these three, and (iii we define a new candidate clustering algorithm using three component of similarity measure to guide the clustering process in a direction that produce more semantic rich clusters. We performed an extensive series of experiments on standard text mining data sets with external clustering evaluations like: FMeasure and Purity, and have obtained

  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. TWIN SUPPORT TENSOR MACHINES FOR MCS DETECTION

    Institute of Scientific and Technical Information of China (English)

    Zhang Xinsheng; Gao Xinbo; Wang Ying

    2009-01-01

    Tensor representation is useful to reduce the overfitting problem in vector-based learning algorithm in pattern recognition.This is mainly because the structure information of objects in pattern analysis is a reasonable constraint to reduce the number of unknown parameters used to model a classifier.In this paper,we generalize the vector-based learning algorithm TWin Support Vector Machine (TWSVM)to the tensor-based method TWin Support Tensor Machines(TWSTM),which accepts general tensors as input.To examine the effectiveness of TWSTM,we implement the TWSTM method for Microcalcification Clusters (MCs) detection.In the tensor subspace domain,the MCs detection procedure is formulated as a supervised learning and classification problem.and TWSTM is used as a classifier to make decision for the presence of MCs or not.A large number of experiments were carried out to evaluate and compare the performance of the proposed MCs detection algorithm.By comparison with TWSVM,the tensor version reduces the overfitting problem.

  9. Simulating and Visualizing Real-Time Crowds on GPU Clusters

    OpenAIRE

    Benjamín Hernández; Hugo Pérez; Isaac Rudomin; Sergio Ruiz; Oriam de Gyves; Leonel Toledo

    2014-01-01

    We present a set of algorithms for simulating and visualizing real-time crowds in GPU (Graphics Processing Units) clusters. First we present crowd simulation and rendering techniques that take advantage of single GPU machines. Then, using as an example a wandering crowd behavior simulation algorithm, we explain how this kind of algorithms can be extended for their use in GPU cluster environments. We also present a visualization architecture that renders the simulation results using detailed 3...

  10. Discussion of CoSA: Clustering of Sparse Approximations

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, Derek Elswick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-07

    The purpose of this talk is to discuss the possible applications of CoSA (Clustering of Sparse Approximations) to the exploitation of HSI (HyperSpectral Imagery) data. CoSA is presented by Moody et al. in the Journal of Applied Remote Sensing (“Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries”, Vol. 8, 2014) and is based on machine learning techniques.

  11. Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm

    OpenAIRE

    Dong Qin

    2014-01-01

    Contraposing to the features of image data with high sparsity of and the problems on determination of clustering numbers, we try to put forward an color image segmentation algorithm, combined with semi-supervised machine learning technology and spectral graph theory. By the research of related theories and methods of spectral clustering algorithms, we introduce information entropy conception to design a method which can automatically optimize the scale parameter value. So it avoids the unstab...

  12. 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.

  13. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

    This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

  14. Clustering and Community Detection with Imbalanced Clusters

    OpenAIRE

    Aksoylar, Cem; Qian, Jing; Saligrama, Venkatesh

    2016-01-01

    Spectral clustering methods which are frequently used in clustering and community detection applications are sensitive to the specific graph constructions particularly when imbalanced clusters are present. We show that ratio cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced cluster sizes since they tend to emphasize cut sizes over cut values. We propose a graph partitioning problem that seeks minimum cut partitions under minimum size constraints on partitions to de...

  15. Cluster headaches.

    Science.gov (United States)

    Ryan, R E; Ryan, R E

    1989-12-01

    The patient with cluster headaches will be afflicted with the most severe type of pain that one will encounter. If the physician can do something to help this patient either by symptomatic or, more importantly, prophylactic treatment, he or she will have a most thankful patient. This type of headache is seen most frequently in men, and occurs in a cyclic manner. During an acute cycle, the patient will experience a daily type of pain that may occur many times per day. The pain is usually unilateral and may be accompanied by unilateral lacrimation, conjunctivitis, and clear rhinorrhea. Prednisone is the first treatment we employ. Patients are seen for follow-up approximately twice a week, and their medication is lowered in an appropriate manner, depending on their response to the treatment. Regulation of dosage has to be individualized, and when one reaches the lower dose such as 5 to 10 mg per day, the drug may have to be tapered more slowly, or even maintained at that level for a period of time to prevent further recurrence of symptoms. We frequently will use an intravenous histamine desensitization technique to prevent further attacks. We will give the patient an ergotamine preparation to use for symptomatic relief. As these patients often have headaches during the middle of the night, we will place the patient on a 2-mg ergotamine preparation to take prior to going to bed in the evening. This often works in a prophylactic nature, and prevents the nighttime occurrence of a headache. We believe that following these principles to make the accurate diagnosis and institute the proper therapy will help the practicing otolaryngologist recognize and treat patients suffering from this severe pain.

  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. PENGEMBANGAN EMPLOYABILITY SKILLS SISWA SMK DITINJAU DARI IMPLEMENTASI PENDEKATAN SAINTIFIK

    Directory of Open Access Journals (Sweden)

    Sunardi Sunardi

    2016-07-01

    Full Text Available The industry now needs a workforce that has the technical skills and employability skills. Completion of the CMS so that students have a technical skill and employability skills based on a scientific approach to implementation that is one indicator of the quality of learning. This research aims to know the contribution of the scientific approach towards implementation of employability skills the students of SMK Package Engineering Machining in South Sulawesi. Research using quantitative non experimental design approach is the type of survey that is ex-post facto. Pupulasi research is a grade XII Package Engineering Machining on SMK in South Sulawesi as much as 503 students with samples of 221. Data collection techniques used are the now. Research data were analyzed with descriptive analysis, comfirmatory factor analysis (CFA, regression analysis. The data analysis was done with the help of SPSS software version 4.5 for Windows and version of LISREL 9.10 Windows Application. Based on the results of the study it can be concluded that the implementation of the scientific approach contributes to employability skills students of SMK Package Engineering Machining in South Sulawesi. Therefore it can be said that the implementation of the scientific approach as a system of learning can develop employability skills graduates SMK. Industri saat ini membutuhkan tenaga kerja yang memiliki keterampilan teknis dan employability skill. Penyiapan siswa SMK agar memiliki keterampilan teknis dan employability skills berpangkal pada implementasi pendekatan saintifik yang merupakan salah satu indikator kualitas pembelajaran. Penelitian ini bertujuan untuk mengetahui kontribusi implementasi pendekatan saintifik terhadap employability skills siswa SMK Paket Keahlian Teknik Pemesinan di Sulawesi Selatan. Penelitian menggunakan pendekatan kuantitatif rancangan non eksperimen jenis survey yang bersifat ex-post facto. Pupulasi penelitian adalah siswa kelas XII Paket

  19. PENGEMBANGAN SOFT SKILL BERBASIS KARIR PADA SMK DI KOTA SEMARANG

    Directory of Open Access Journals (Sweden)

    Sri Utaminingsih

    2016-02-01

    Full Text Available The objectives of the study was to find and develop the soft skill learning model based careers on Vocational High School (SMK with Tourism Cluster through a set of tryout and validation. The soft skill development based careers was expected to improve Vocational High Schools’ graduates and fulfill the qualifications which were set by BI (Business and Industry. It was relevant to the President’s policy to improve Indonesian workers. The specific purposes of the study were: (1 to formulate the development of soft skill model design based careers on Vocational High School, (2 to find the soft skill development model based the effective careers on Vocational High Schools, (3 to compile the soft skill model guidance. This study used Research and Development approach, then continued to the field study process, developing the model design, tryout and finally, validation. At the introduction study, it was identified the values and soft skills supporting careers in business and industry. Then, those values became the foundation to (1 formulate the model design, and (2 compile the model develop the soft skills collaboratively involving the parties and stakeholders related to Vocational High Schools with Tourism Cluster, (3 create an effective model guidance. From the process of development above, it was obtained the model design and the soft skill development model guidance to improve the graduates’ careers.

  20. Elments constintute teachers’ teaching skills

    OpenAIRE

    Hoa, H.; Lам, P.

    2014-01-01

    Teachers’ pedagogical activities are constituted by many skills such as teaching skills, education skills, and skills of performing varied pedagogical ac- tivities. Each skill is formed from a variety of specifi c skills. Approaching teachers’ teaching skills based on pedagogical operation base can help us establish methods and develop skills for teachers. By doing so, we can assist teachers to enhance their teaching competence contributing to teaching quality improvement in schools

  1. 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.

  2. Cognitive Skill in Medicine: An Introduction

    NARCIS (Netherlands)

    Cnossen, Fokie; Lanzer, Peter

    2015-01-01

    Cognition encompasses all processes from perception to action including attention and memory, reasoning, and decision making. Therefore, all skills (perceptual skills, motor skills, diagnosing skill, medical skills) are cognitive skills. Cognitive skills are supported by two types of knowledge:

  3. 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.

  4. Knowledge discovery via machine learning for neurodegenerative disease researchers.

    Science.gov (United States)

    Ozyurt, I Burak; Brown, Gregory G

    2009-01-01

    Ever-increasing size of the biomedical literature makes more precise information retrieval and tapping into implicit knowledge in scientific literature a necessity. In this chapter, first, three new variants of the expectation-maximization (EM) method for semisupervised document classification (Machine Learning 39:103-134, 2000) are introduced to refine biomedical literature meta-searches. The retrieval performance of a multi-mixture per class EM variant with Agglomerative Information Bottleneck clustering (Slonim and Tishby (1999) Agglomerative information bottleneck. In Proceedings of NIPS-12) using Davies-Bouldin cluster validity index (IEEE Transactions on Pattern Analysis and Machine Intelligence 1:224-227, 1979), rivaled the state-of-the-art transductive support vector machines (TSVM) (Joachims (1999) Transductive inference for text classification using support vector machines. In Proceedings of the International Conference on Machine Learning (ICML)). Moreover, the multi-mixture per class EM variant refined search results more quickly with more than one order of magnitude improvement in execution time compared with TSVM. A second tool, CRFNER, uses conditional random fields (Lafferty et al. (2001) Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of ICML-2001) to recognize 15 types of named entities from schizophrenia abstracts outperforming ABNER (Settles (2004) Biomedical named entity recognition using conditional random fields and rich feature sets. In Proceedings of COLING 2004 International Joint Workshop on Natural Language Processing in Biomedicine and its Applications (NLPBA)) in biological named entity recognition and reaching F(1) performance of 82.5% on the second set of named entities.

  5. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  6. Factorial PD-Clustering

    CERN Document Server

    Tortora, Cristina; Summa, Mireille Gettler

    2011-01-01

    Factorial clustering methods have been developed in recent years thanks to the improving of computational power. These methods perform a linear transformation of data and a clustering on transformed data optimizing a common criterion. Factorial PD-clustering is based on Probabilistic Distance clustering (PD-clustering). PD-clustering is an iterative, distribution free, probabilistic, clustering method. Factorial PD-clustering make a linear transformation of original variables into a reduced number of orthogonal ones using a common criterion with PD-Clustering. It is demonstrated that Tucker 3 decomposition allows to obtain this transformation. Factorial PD-clustering makes alternatively a Tucker 3 decomposition and a PD-clustering on transformed data until convergence. This method could significantly improve the algorithm performance and allows to work with large dataset, to improve the stability and the robustness of the method.

  7. 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

  8. 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.

  9. 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.

  10. Possibilistic Exponential Fuzzy Clustering

    Institute of Scientific and Technical Information of China (English)

    Kiatichai Treerattanapitak; Chuleerat Jaruskulchai

    2013-01-01

    Generally,abnormal points (noise and outliers) cause cluster analysis to produce low accuracy especially in fuzzy clustering.These data not only stay in clusters but also deviate the centroids from their true positions.Traditional fuzzy clustering like Fuzzy C-Means (FCM) always assigns data to all clusters which is not reasonable in some circumstances.By reformulating objective function in exponential equation,the algorithm aggressively selects data into the clusters.However noisy data and outliers cannot be properly handled by clustering process therefore they are forced to be included in a cluster because of a general probabilistic constraint that the sum of the membership degrees across all clusters is one.In order to improve this weakness,possibilistic approach relaxes this condition to improve membership assignment.Nevertheless,possibilistic clustering algorithms generally suffer from coincident clusters because their membership equations ignore the distance to other clusters.Although there are some possibilistic clustering approaches that do not generate coincident clusters,most of them require the right combination of multiple parameters for the algorithms to work.In this paper,we theoretically study Possibilistic Exponential Fuzzy Clustering (PXFCM) that integrates possibilistic approach with exponential fuzzy clustering.PXFCM has only one parameter and not only partitions the data but also filters noisy data or detects them as outliers.The comprehensive experiments show that PXFCM produces high accuracy in both clustering results and outlier detection without generating coincident problems.

  11. Development and Evaluation of a Psychosocial Intervention for Children and Teenagers Experiencing Diabetes (DEPICTED: a protocol for a cluster randomised controlled trial of the effectiveness of a communication skills training programme for healthcare professionals working with young people with type 1 diabetes

    Directory of Open Access Journals (Sweden)

    Lowes Lesley

    2010-02-01

    Full Text Available Abstract Background Diabetes is the third most common chronic condition in childhood and poor glycaemic control leads to serious short-term and life-limiting long-term complications. In addition to optimal medical management, it is widely recognised that psychosocial and educational factors play a key role in improving outcomes for young people with diabetes. Recent systematic reviews of psycho-educational interventions recognise the need for new methods to be developed in consultation with key stakeholders including patients, their families and the multidisciplinary diabetes healthcare team. Methods/design Following a development phase involving key stakeholders, a psychosocial intervention for use by paediatric diabetes staff and not requiring input from trained psychologists has been developed, incorporating a communication skills training programme for health professionals and a shared agenda-setting tool. The effectiveness of the intervention will be evaluated in a cluster-randomised controlled trial (RCT. The primary outcome, to be measured in children aged 4-15 years diagnosed with type 1 diabetes for at least one year, is the effect on glycaemic control (HbA1c during the year after training of the healthcare team is completed. Secondary outcomes include quality of life for patients and carers and cost-effectiveness. Patient and carer preferences for service delivery will also be assessed. Twenty-six paediatric diabetes teams are participating in the trial, recruiting a total of 700 patients for evaluation of outcome measures. Half the participating teams will be randomised to receive the intervention at the beginning of the trial and remaining centres offered the training package at the end of the one year trial period. Discussion The primary aim of the trial is to determine whether a communication skills training intervention for specialist paediatric diabetes teams will improve clinical and psychological outcomes for young people with

  12. 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...

  13. Space, time and machines

    CERN Document Server

    Annila, Arto

    2009-01-01

    The 2nd law of thermodynamics sheds light on present-day puzzles in cosmology. The universal law, as an equation of motion, describes diverse systems consuming free energy via various mechanisms to attain stationary states in their respective surroundings. Increasing rate of expansion of the Universe, galactic rotation and lensing as well as clustering of red-shifted spectral lines are found as natural consequences of the maximal energy dispersal that satisfies the conservation of energy, in the forms of kinetic, potential and dissipation. The Universe in its entirety is pictured as a giant Riemannian resonator in evolution via step-by-step spontaneous breaking of one stationary-state symmetry to another to diminish the energy density difference relative to its zero-density surroundings. The continuum equation of evolution is proven equivalent to the Navier-Stokes equation. The ubiquitous flow equation has no solution because the forces and flows are inseparable when the dissipative process has three or more ...

  14. Physico-chemical surface characterization of a bacterial population isolated from a milking machine

    OpenAIRE

    Teixeira, P.; Lopes, Zulmira; Azeredo, Joana; Oliveira, Rosário; Vieira, M. J.

    2005-01-01

    The hydrophobicity of 26 species of bacteria representative of the main genera isolated from a rubber short milk tube, which is a constituent of a cluster from a milking machine, was determined. The materials forming the cluster namely rubber, stainless steel (SS) 316, stainless steel (SS) 304, glass and polymethylmethacrylate (PMMA) were also assayed in terms of hydrophobicity. In relation with the hydrophobicity of bacteria, all the strains of Lactobacillus lactis lactis as well as...

  15. Intergalactic stellar populations in intermediate redshift clusters

    CERN Document Server

    Melnick, J; Toledo, I; Selman, F J; Quintana, H

    2012-01-01

    A substantial fraction of the total stellar mass in rich clusters of galaxies resides in a diffuse intergalactic component usually referred to as the Intra-Cluster Light (ICL). Theoretical models indicate that these intergalactic stars originate mostly from the tidal interaction of the cluster galaxies during the assembly history of the cluster, and that a significant fraction of these stars could have formed in-situ from the late infall of cold metal-poor gas clouds onto the cluster. The models make predictions about the age distribution of the ICL stars, which may provide additional observational constraints. However, these models also over-predict the fraction of stellar mass in the ICL by a substantial margin. Here we present population synthesis models for the ICL of a dumb-bell dominated intermediate redshift (z=0.29) X-ray cluster for which we have deep MOS data obtained with the FORS2 instrument. In a previous paper we have proposed that the dumbell galaxy act as a grinding machine tearing to pieces t...

  16. Performance of a table vibration type coffee grading machine

    Directory of Open Access Journals (Sweden)

    Sukrisno Widyotomo

    2005-05-01

    Full Text Available One of important coffee beans quality is the size uniformity. To confirm with the standart requirement, coffee beans have to be graded before being traded. Until now, grading process is still carried out fully manual, so that the grading cost is very expensive about 40% of total processing cost. Meanwhile, shortage of skill workers is as a limiting factor of the process. Therefore, machine for grading coffee beans is good alternative for grading cost. Indonesian Coffee and Cocoa Research Institute has designed a table vibration type coffee grading machine for grouping of coffee beans in order to consistent quality and reduce grading cost. The machine has dimension of 272 cm length, 126 cm height, and 144 cm width. The machine has three primary components, i.e. grader table, combustion engine, and beam. The machine has three kinds of grader table that each grader table has different holes size, i.e. 7 mm x 7 mm for top grader table, 5 mm x 5 mm for axle grader table, and 4 mm x 4 mm for bottom grader table. Each grader table has dimension of 206 cm length, 105.5 cm height, and 14 cm width. The grading mechanism is by vibration grader table with the power source 5.5 HP combustion engine. The results shown that the outlet are in farms of three grades of coffee beans with connected to each compartement. Assessment of the grading machine reveals that the optimum capacity of 1,406 kg/hour reached when the speed 2,600 rpm and the angle 10O. Economic analysis showed that operational cost for grading one kilogram Robusta coffee beans with moisture content 13—14% wet basis is Rp 7.17.Key words : grading, coffee, quality, vibration table.

  17. Generalised Brown Clustering and Roll-up Feature Generation

    DEFF Research Database (Denmark)

    Derczynski, Leon; Chester, Sean

    2016-01-01

    Brown clustering is an established technique, used in hundreds of computational linguistics papers each year, to group word types that have similar distributional information. It is unsupervised and can be used to create powerful word representations for machine learning. Despite its improbable...

  18. Mathematics for the Workplace. Applications from Machine Tool Technology (Michelin Tire Corporation). A Teacher's Guide.

    Science.gov (United States)

    Wallace, Johnny M.; Stewart, Grover

    This module presents a real-world context in which mathematics skills (geometry and trigonometry) are used as part of a daily routine. The context is the machine tool technology field, and the module aims to help students develop the ability to analyze diagrams in order to make mathematical computations. The modules, which features applications…

  19. Semi-Supervised Clustering for High-Dimensional and Sparse Features

    Science.gov (United States)

    Yan, Su

    2010-01-01

    Clustering is one of the most common data mining tasks, used frequently for data organization and analysis in various application domains. Traditional machine learning approaches to clustering are fully automated and unsupervised where class labels are unknown a priori. In real application domains, however, some "weak" form of side…

  20. 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.