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Sample records for machines varies widely

  1. Linear Parameter Varying Control of Doubly Fed Induction Machines

    NARCIS (Netherlands)

    Tien, H. Nguyen; Scherer, Carsten W.; Scherpen, Jacquelien M.A.; Müller, Volkmar

    2016-01-01

    This paper is concerned with the design of a self-scheduled current controller for doubly fed induction machines. The design is based on the framework of linear parameter-varying systems where the mechanical angular speed is considered to be a measurable time-varying parameter. The objective is to o

  2. Prices of Generic Heart Failure Drugs Vary Widely

    Science.gov (United States)

    ... medlineplus.gov/news/fullstory_162035.html Prices of Generic Heart Failure Drugs Vary Widely Patients can spend from $12 to $ ... Nov. 15, 2016 (HealthDay News) -- Cash prices of generic medicines to treat heart failure vary so widely that ...

  3. Graduate Students' Pay and Benefits Vary Widely, Survey Shows

    Science.gov (United States)

    June, Audrey Williams

    2008-01-01

    Graduate students face an array of choices when evaluating compensation-and-benefits packages that make comparisons difficult. A "Chronicle" survey shows that the offers to teaching assistants and research assistants vary widely. Some institutions cover 100 percent of graduate students' tuition, while others waive only a portion. It is possible to…

  4. Additional Surgery after Breast-Conserving Surgery Varies Widely

    Science.gov (United States)

    A study published in the Feb. 1, 2012, issue of JAMA found that the number of women who have one or more additional surgeries to remove suspected residual tumor tissue (re-excisions) following breast-conserving surgery (BCS) for breast cancer varies widely across surgeons and hospitals.

  5. Finite element form of FDV for widely varying flowfields

    Science.gov (United States)

    Richardson, G. A.; Cassibry, J. T.; Chung, T. J.; Wu, S. T.

    2010-01-01

    We present the Flowfield Dependent Variation (FDV) method for physical applications that have widely varying spatial and temporal scales. Our motivation is to develop a versatile numerical method that is accurate and stable in simulations with complex geometries and with wide variations in space and time scales. The use of a finite element formulation adds capabilities such as flexible grid geometries and exact enforcement of Neumann boundary conditions. While finite element schemes are used extensively by researchers solving computational fluid dynamics in many engineering fields, their use in space physics, astrophysical fluids and laboratory magnetohydrodynamic simulations with shocks has been predominantly overlooked. The FDV method is unique in that numerical diffusion is derived from physical parameters rather than traditional artificial viscosity methods. Numerical instabilities account for most of the difficulties when capturing shocks in these regimes. The first part of this paper concentrates on the presentation of our numerical method formulation for Newtonian and relativistic hydrodynamics. In the second part we present several standard simulation examples that test the method's limitations and verify the FDV method. We show that our finite element formulation is stable and accurate for a range of both Mach numbers and Lorentz factors in one-dimensional test problems. We also present the converging/diverging nozzle which contains both incompressible and compressible flow in the flowfield over a range of subsonic and supersonic regions. We demonstrate the stability of our method and the accuracy by comparison with the results of other methods including the finite difference Total Variation Diminishing method. We explore the use of FDV for both non-relativistic and relativistic fluids (hydrodynamics) with strong shocks in order to establish the effectiveness in future applications of this method in astrophysical and laboratory plasma environments.

  6. Frontal Neurons Modulate Memory Retrieval across Widely Varying Temporal Scales

    Science.gov (United States)

    Zhang, Wen-Hua; Williams, Ziv M.

    2015-01-01

    Once a memory has formed, it is thought to undergo a gradual transition within the brain from short- to long-term storage. This putative process, however, also poses a unique problem to the memory system in that the same learned items must also be retrieved across broadly varying time scales. Here, we find that neurons in the ventrolateral…

  7. Predicting genome-wide redundancy using machine learning

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    Shasha Dennis E

    2010-11-01

    Full Text Available Abstract Background Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the test case used here. Results Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in Arabidopsis showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1, suggesting that redundancy is stable over long evolutionary periods. Conclusions Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for Arabidopsis provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.

  8. Malware Propagation on Social Time Varying Networks: A Comparative Study of Machine Learning Frameworks

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    A.A. Ojugo

    2014-08-01

    Full Text Available Significant research into the logarithmic analysis of complex networks yields solution to help minimize virus spread and propagation over networks. This task of virus propagation is been a recurring subject, and design of complex models will yield modeling solutions used in a number of events not limited to and include propagation, dataflow, network immunization, resource management, service distribution, adoption of viral marketing etc. Stochastic models are successfully used to predict the virus propagation processes and its effects on networks. The study employs SI-models for independent cascade and the dynamic models with Enron dataset (of e-mail addresses and presents comparative result using varied machine models. Study samples 25,000 emails of Enron dataset with Entropy and Information Gain computed to address issues of blocking targeting and extent of virus spread on graphs. Study addressed the problem of the expected spread immunization and the expected epidemic spread minimization; but not the epidemic threshold (for space constraint.

  9. Estimating wide-angle, spatially varying reflectance using time-resolved inversion of backscattered light.

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    Naik, Nikhil; Barsi, Christopher; Velten, Andreas; Raskar, Ramesh

    2014-05-01

    Imaging through complex media is a well-known challenge, as scattering distorts a signal and invalidates imaging equations. For coherent imaging, the input field can be reconstructed using phase conjugation or knowledge of the complex transmission matrix. However, for incoherent light, wave interference methods are limited to small viewing angles. On the other hand, time-resolved methods do not rely on signal or object phase correlations, making them suitable for reconstructing wide-angle, larger-scale objects. Previously, a time-resolved technique was demonstrated for uniformly reflecting objects. Here, we generalize the technique to reconstruct the spatially varying reflectance of shapes hidden by angle-dependent diffuse layers. The technique is a noninvasive method of imaging three-dimensional objects without relying on coherence. For a given diffuser, ultrafast measurements are used in a convex optimization program to reconstruct a wide-angle, three-dimensional reflectance function. The method has potential use for biological imaging and material characterization.

  10. Nutrient Intake Values for Folate during Pregnancy and Lactation Vary Widely around the World

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    Lisa A. Houghton

    2013-09-01

    Full Text Available Folate is a B-vitamin with particular importance during reproduction due to its role in the synthesis and maintenance of DNA. Folate is well known for its role in preventing neural tube defects (NTDs during the periconceptional period. There is also an increased need for folate throughout pregnancy to support optimal growth and development of the fetus and blood volume expansion and tissue growth of the mother. During lactation, women are at risk of folate deficiency due to increased demands to accommodate milk folate levels. Nutrient Intake Values (NIVs for folate have been calculated to take into account additional needs during pregnancy and lactation. However, these values vary widely between countries. For example, the folate requirement that is set to meet the needs of almost all healthy women during pregnancy varies from 300 µg/day in the United Kingdom to 750 µg/day in Mexico. Currently, there is no accepted standardized terminology or framework for establishing NIVs. This article reviews country-specific NIVs for folate during pregnancy and lactation and the basis for setting these reference values.

  11. Helical Milling of CFRP/Ti-6Al-4V Stacks with Varying Machining Parameters

    Institute of Scientific and Technical Information of China (English)

    He Gaiyun; Li Hao; Jiang Yuedong; Qin Xuda; Zhang Xinpei; Guan Yi

    2015-01-01

    The hole-making process in stack materials consisting of carbon fiber reinforced plastics(CFRP) and Ti-6Al-4V remains a critical challenge. In this paper, an experimental study on the helical milling of CFRP/Ti-6Al-4V stacks was conducted by using two different machining strategies. Helical milling strategyⅠmachines both materials with identical machining parameters, while machining strategyⅡuses two sets of machining parameters to machine each material. Helical milling performance was evaluated by the following indicators: tool life, cutting forces, hole quality(including diameter deviation, roundness, roughness, and hole edge quality). The results demonstrate that heli-cal milling strategyⅡoutperformed strategyⅠ, leading to longer tool life(up to 48 holes), smaller cutting forces and better hole quality with higher geometric accuracy and smoother surface finish(Ra≤0.58μm for Ti-6Al-4V and Ra≤0.81μm for CFRP), eliminating the need for reaming or de-burring.

  12. Biofilm-forming bacteria with varying tolerance to peracetic acid from a paper machine.

    Science.gov (United States)

    Rasimus, Stiina; Kolari, Marko; Rita, Hannu; Hoornstra, Douwe; Salkinoja-Salonen, Mirja

    2011-09-01

    Biofilms cause runnability problems in paper machines and are therefore controlled with biocides. Peracetic acid is usually effective in preventing bulky biofilms. This study investigated the microbiological status of a paper machine where low concentrations (≤ 15 ppm active ingredient) of peracetic acid had been used for several years. The paper machine contained a low amount of biofilms. Biofilm-forming bacteria from this environment were isolated and characterized by 16S rRNA gene sequencing, whole-cell fatty acid analysis, biochemical tests, and DNA fingerprinting. Seventy-five percent of the isolates were identified as members of the subclades Sphingomonas trueperi and S. aquatilis, and the others as species of the genera Burkholderia (B. cepacia complex), Methylobacterium, and Rhizobium. Although the isolation media were suitable for the common paper machine biofoulers Deinococcus, Meiothermus, and Pseudoxanthomonas, none of these were found, indicating that peracetic acid had prevented their growth. Spontaneous, irreversible loss of the ability to form biofilm was observed during subculturing of certain isolates of the subclade S. trueperi. The Sphingomonas isolates formed monoculture biofilms that tolerated peracetic acid at concentrations (10 ppm active ingredient) used for antifouling in paper machines. High pH and low conductivity of the process waters favored the peracetic acid tolerance of Sphingomonas sp. biofilms. This appears to be the first report on sphingomonads as biofilm formers in warm water using industries.

  13. Evaluation of the Machinability of Cast Ti-Si Alloys with Varying Si Content

    Science.gov (United States)

    Hsu, Hsueh-Chuan; Wu, Shih-Ching; Hsu, Shih-Kuang; Hsu, Chih-Cheng; Ho, Wen-Fu

    2016-05-01

    This study evaluated the machinability of a series of binary Ti-Si alloys with a goal of developing a titanium alloy with better machinability than commercially pure titanium (c.p. Ti). The alloys were slotted using a milling machine and end mills under four cutting conditions. Machinability was evaluated through cutting force. The experimental results indicate that alloying with Si significantly improved the machinability of c.p. Ti in terms of cutting force under the present cutting conditions. As the Si content increases, the cutting force decreases then greatly increases. The cutting forces of c.p. Ti and the Ti-Si alloys increased as the feed rate increased from 30 to 60 m/min under the cutting speed of 55 or 110 m/min. The cutting force of Ti-5Si at cutting speed 55 m/min was approximately 49% lower than that of c.p. Ti; at cutting speed 110 m/min, it was approximately 62% lower than that of c.p. Ti. The cutting force of Ti-10Si was significantly higher than those of the other Ti-Si alloys and c.p. Ti, a result that can be explained by a higher degree of hardness (626 HV) and larger amounts of Ti5Si3 (47.10 vol.%). For Ti-5Si, there was no obvious adhesion of chips observed on the cut surfaces. Furthermore, the specimens had the lowest surface roughness (Ra) values, approximately 0.3-0.4 μm, under the four cutting conditions. When cutting force, chip length, and surface roughness results are considered, the Ti-5Si alloy developed in this study is a viable candidate for machining.

  14. Chloroplast movement behavior varies widely among species and does not correlate with high light stress tolerance.

    Science.gov (United States)

    Königer, Martina; Bollinger, Nicole

    2012-08-01

    It is well known that chloroplasts move in response to changes in blue light intensity in order to optimize light interception, however, little is known about interspecific variation and the relative importance of this mechanism for the high light stress tolerance of plants. We characterized chloroplast movement behavior as changes in light transmission through a leaf in a variety of species ranging from ferns to monocots and eudicots and found a wide spectrum of responses. Most species exhibited a distinct accumulation response compared to the dark positioning, and all species showed a distinct avoidance response. The speed with which transmission values changed during the avoidance response was consistently faster than that during the accumulation response and speeds varied greatly between species. Plants thriving in higher growth light intensities showed greater degrees of accumulation responses and faster changes in transmission than those that prefer lower light intensities. In some species, the chloroplasts on both the adaxial and abaxial leaf surfaces changed their positioning in response to light, while in other species only the chloroplasts on one leaf side responded. No correlation was found between high light stress tolerance and the speed or degree of transmission changes, indicating that plants can compensate for slow and limited transmission changes using other photoprotective mechanisms.

  15. The HRA/Solarium Project: Processing of Widely Varying High- and Medium-Level Waste

    Energy Technology Data Exchange (ETDEWEB)

    Willems, M.; Luycx, P.; Gilis, R.; Belgoprocess; Renard, Cl.; Reyniers, H.; Cuchet, J. M.

    2003-02-26

    Starting in 2003, Belgoprocess will proceed with the treatment and conditioning of some 200 m{sup 3} of widely varying high- and medium-level waste from earlier research and development work, to meet standard acceptance criteria for later disposal. The gross volume of primary and secondary packages amounts to 2,600 m{sup 3}. The waste has been kept in decay storage for up to 30 years. The project was started in 1997. Operation of the various processing facilities will take 7-8 years. The overall volume of conditioned waste will be of the order of 800 m{sup 3}. All conditioned waste will be stored in appropriate storage facilities onsite. At present (November, 2002), a new processing facility has been constructed, the functional tests of the equipment have been performed and the startup phase has been started. Several cells of the Pamela vitrification facility onsite will be adapted for the treatment of high-level and highly a-contaminated waste; low-level a/a waste will be treated in the existing facility for super compaction and conditioning by embedding into cement (CILVA). The bulk of these waste, of which 95% are solids, the remainder consisting of mainly solidified liquids, have been produced between 1967 and 1988. They originate from various research programs and reactor operation at the Belgian nuclear energy research centre SCK CEN, isotope production, decontamination and dismantling operations.

  16. Winding Schemes for Wide Constant Power Range of Double Stator Transverse Flux Machine

    Energy Technology Data Exchange (ETDEWEB)

    Husain, Tausif; Hassan, Iftekhar; Sozer, Yilmaz; Husain, Iqbal; Muljadi, Eduard

    2015-05-01

    Different ring winding schemes for double sided transverse flux machines are investigated in this paper for wide speed operation. The windings under investigation are based on two inverters used in parallel. At higher power applications this arrangement improves the drive efficiency. The new winding structure through manipulation of the end connection splits individual sets into two and connects the partitioned turns from individual stator sets in series. This configuration offers the flexibility of torque profiling and a greater flux weakening region. At low speeds and low torque only one winding set is capable of providing the required torque thus providing greater fault tolerance. At higher speeds one set is dedicated to torque production and the other for flux control. The proposed method improves the machine efficiency and allows better flux weakening which is desirable for traction applications.

  17. Management of Inflammatory Bowel Disease during Pregnancy and Breastfeeding Varies Widely: A Need for Further Education

    Science.gov (United States)

    Goodman, Karen Jean; Hegadoren, Kathleen M.; Dieleman, Levinus Albert; Fedorak, Richard Neil

    2016-01-01

    Background. Inflammatory bowel disease (IBD) affects patients in their young reproductive years. Women with IBD require maintenance therapies during pregnancy and breastfeeding. However, physician management of IBD during pregnancy and breastfeeding has not been well characterized. Objective. To characterize physician perceptions and management of IBD during pregnancy and breastfeeding. Methods. A cross-sectional survey of Canadian physicians who are involved in the care of women with IBD was conducted. The survey included multiple-choice and Likert scale questions about perceptions and practice patterns regarding the management of IBD during pregnancy and breastfeeding. Results. 183 practicing physicians completed the questionnaire: 97/183 (53.0%) gastroenterologists; 75/183 (41.0%) general practitioners; and 11/183 (6.0%) other physicians. Almost half (87/183, 47.5%) of the physicians felt comfortable managing pregnant IBD patients. For specified IBD medications, proportions of physicians who indicated they would continue them during pregnancy were as follows: sulfasalazine, 47.4%; oral mesalamine, 67.0%; topical mesalamine, 70.3%; oral prednisone, 68.0%; topical prednisone, 78.0%; oral budesonide, 61.6%; topical budesonide, 75.0%; ciprofloxacin, 15.3%; metronidazole, 31.4%; azathioprine, 57.1%; methotrexate, 2.8%; infliximab, 55.6%; adalimumab, 78.1%. Similar proportions of physicians would continue these medications during breastfeeding. A higher proportion of gastroenterologists than nongastroenterologists indicated appropriate use of these IBD medications during pregnancy and breastfeeding. Conclusions. Physician management of IBD during pregnancy and breastfeeding varies widely. Relative to other physicians, responses of gastroenterologists more frequently reflected best practices pertaining to medications for control of IBD during pregnancy and breastfeeding. There is a need for further education regarding the management of IBD during pregnancy and

  18. Management of Inflammatory Bowel Disease during Pregnancy and Breastfeeding Varies Widely: A Need for Further Education

    Directory of Open Access Journals (Sweden)

    Vivian Wai-Mei Huang

    2016-01-01

    Full Text Available Background. Inflammatory bowel disease (IBD affects patients in their young reproductive years. Women with IBD require maintenance therapies during pregnancy and breastfeeding. However, physician management of IBD during pregnancy and breastfeeding has not been well characterized. Objective. To characterize physician perceptions and management of IBD during pregnancy and breastfeeding. Methods. A cross-sectional survey of Canadian physicians who are involved in the care of women with IBD was conducted. The survey included multiple-choice and Likert scale questions about perceptions and practice patterns regarding the management of IBD during pregnancy and breastfeeding. Results. 183 practicing physicians completed the questionnaire: 97/183 (53.0% gastroenterologists; 75/183 (41.0% general practitioners; and 11/183 (6.0% other physicians. Almost half (87/183, 47.5% of the physicians felt comfortable managing pregnant IBD patients. For specified IBD medications, proportions of physicians who indicated they would continue them during pregnancy were as follows: sulfasalazine, 47.4%; oral mesalamine, 67.0%; topical mesalamine, 70.3%; oral prednisone, 68.0%; topical prednisone, 78.0%; oral budesonide, 61.6%; topical budesonide, 75.0%; ciprofloxacin, 15.3%; metronidazole, 31.4%; azathioprine, 57.1%; methotrexate, 2.8%; infliximab, 55.6%; adalimumab, 78.1%. Similar proportions of physicians would continue these medications during breastfeeding. A higher proportion of gastroenterologists than nongastroenterologists indicated appropriate use of these IBD medications during pregnancy and breastfeeding. Conclusions. Physician management of IBD during pregnancy and breastfeeding varies widely. Relative to other physicians, responses of gastroenterologists more frequently reflected best practices pertaining to medications for control of IBD during pregnancy and breastfeeding. There is a need for further education regarding the management of IBD during

  19. Widely varying giant Goos-Hänchen shifts from Airy beams at nonlinear interfaces.

    Science.gov (United States)

    Chamorro-Posada, Pedro; Sánchez-Curto, Julio; Aceves, Alejandro B; McDonald, Graham S

    2014-03-15

    We present a numerical study of the giant Goos-Hänchen shifts (GHSs) obtained from an Airy beam impinging on a nonlinear interface. To avoid any angular restriction associated with the paraxial approximation, the analysis is based on the nonlinear Helmholtz equation. We report the existence of nonstandard nonlinear GHSs displaying an extreme sensitivity to the input intensity and the existence of multiple critical values. These intermittent and oscillatory regimes can be explained in terms of competition between critical coupling to a surface mode and soliton emission from the refracted beam component and how this interplay varies with localization of the initial Airy beam.

  20. Prediction and dissection of widely-varying association rate constants of actin-binding proteins.

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    Xiaodong Pang

    Full Text Available Actin is an abundant protein that constitutes a main component of the eukaryotic cytoskeleton. Its polymerization and depolymerization are regulated by a variety of actin-binding proteins. Their functions range from nucleation of actin polymerization to sequestering G-actin in 1∶1 complexes. The kinetics of forming these complexes, with rate constants varying at least three orders of magnitude, is critical to the distinct regulatory functions. Previously we have developed a transient-complex theory for computing protein association mechanisms and association rate constants. The transient complex refers to an intermediate in which the two associating proteins have near-native separation and relative orientation but have yet to form short-range specific interactions of the native complex. The association rate constant is predicted as k(a = k(a0 e(-ΔG(el*/k(BT, where k(a0 is the basal rate constant for reaching the transient complex by free diffusion, and the Boltzmann factor captures the bias of long-range electrostatic interactions. Here we applied the transient-complex theory to study the association kinetics of seven actin-binding proteins with G-actin. These proteins exhibit three classes of association mechanisms, due to their different molecular shapes and flexibility. The 1000-fold k(a variations among them can mostly be attributed to disparate electrostatic contributions. The basal rate constants also showed variations, resulting from the different shapes and sizes of the interfaces formed by the seven actin-binding proteins with G-actin. This study demonstrates the various ways that actin-binding proteins use physical properties to tune their association mechanisms and rate constants to suit distinct regulatory functions.

  1. The period length of fibroblast circadian gene expression varies widely among human individuals.

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    Steven A Brown

    2005-10-01

    Full Text Available Mammalian circadian behavior is governed by a central clock in the suprachiasmatic nucleus of the brain hypothalamus, and its intrinsic period length is believed to affect the phase of daily activities. Measurement of this period length, normally accomplished by prolonged subject observation, is difficult and costly in humans. Because a circadian clock similar to that of the suprachiasmatic nucleus is present in most cell types, we were able to engineer a lentiviral circadian reporter that permits characterization of circadian rhythms in single skin biopsies. Using it, we have determined the period lengths of 19 human individuals. The average value from all subjects, 24.5 h, closely matches average values for human circadian physiology obtained in studies in which circadian period was assessed in the absence of the confounding effects of light input and sleep-wake cycle feedback. Nevertheless, the distribution of period lengths measured from biopsies from different individuals was wider than those reported for circadian physiology. A similar trend was observed when comparing wheel-running behavior with fibroblast period length in mouse strains containing circadian gene disruptions. In mice, inter-individual differences in fibroblast period length correlated with the period of running-wheel activity; in humans, fibroblasts from different individuals showed widely variant circadian periods. Given its robustness, the presented procedure should permit quantitative trait mapping of human period length.

  2. Pathogen exposure varies widely among sympatric populations of wild and domestic felids across the United States

    Science.gov (United States)

    Carver, Scott; Bevins, Sarah N.; Lappin, Michael R.; Boydston, Erin E.; Lyren, Lisa M.; Alldredge, Mathew W.; Logan, Kenneth A.; Sweanor, Linda L.; Riley, Seth P.D.; Serieys, Laurel E.K.; Fisher, Robert N.; Vickers, T. Winston; Boyce, Walter M.; McBride, Roy; Cunnigham, Mark C.; Jennings, Megan; Lewis, Jesse S.; Lunn, Tamika; Crooks, Kevin R.; VandeWoude, Sue

    2016-01-01

    Understanding how landscape, host, and pathogen traits contribute to disease exposure requires systematic evaluations of pathogens within and among host species and geographic regions. The relative importance of these attributes is critical for management of wildlife and mitigating domestic animal and human disease, particularly given rapid ecological changes, such as urbanization. We screened >1,000 samples from sympatric populations of puma (Puma concolor), bobcat (Lynx rufus) and domestic cat (Felis catus) across urban gradients in six sites, representing three regions, in North America for exposure to a representative suite of bacterial, protozoal and viral pathogens (Bartonella sp., Toxoplasma gondii, feline herpesvirus-1, feline panleukopenea virus, feline calicivirus, feline immunodeficiency virus). We evaluated prevalence within each species, and examined host trait and land cover determinants of exposure-providing an unprecedented analysis of factors relating to potential for infections in domesticated and wild felids. Prevalence differed among host species (highest for puma and lowest for domestic cat) and was greater for indirectly transmitted pathogens. Sex was inconsistently predictive of exposure to directly transmitted pathogens only, and age infrequently predictive of both direct and indirectly transmitted pathogens. Determinants of pathogen exposure were widely divergent between the wild felid species. For puma, suburban landuse predicted increased exposure to Bartonella sp. in southern California, and FHV-1 exposure increased near urban edges in Florida. This may suggest inter-specific transmission with domestic cats via flea vectors (California) and direct contact (Florida) around urban boundaries. Bobcats captured near urban areas had increased exposure to T. gondii in Florida, suggesting an urban source of prey. Bobcats captured near urban areas in Colorado and Florida had higher FIV exposure, possibly suggesting increased intra

  3. A wide-range programmable frequency synthesizer based on a finite state machine filter

    Science.gov (United States)

    Alser, Mohammed H.; Assaad, Maher M.; Hussin, Fawnizu A.

    2013-11-01

    In this article, an FPGA-based design and implementation of a fully digital wide-range programmable frequency synthesizer based on a finite state machine filter is presented. The advantages of the proposed architecture are that, it simultaneously generates a high frequency signal from a low frequency reference signal (i.e. synthesising), and synchronising the two signals (signals have the same phase, or a constant difference) without jitter accumulation issue. The architecture is portable and can be easily implemented for various platforms, such as FPGAs and integrated circuits. The frequency synthesizer circuit can be used as a part of SERDES devices in intra/inter chip communication in system-on-chip (SoC). The proposed circuit is designed using Verilog language and synthesized for the Altera DE2-70 development board, with the Cyclone II (EP2C35F672C6) device on board. Simulation and experimental results are included; they prove the synthesizing and tracking features of the proposed architecture. The generated clock signal frequency of a range from 19.8 MHz to 440 MHz is synchronized to the input reference clock with a frequency step of 0.12 MHz.

  4. Computer vision and machine learning for robust phenotyping in genome-wide studies

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    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R. V. Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K.

    2017-01-01

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems. PMID:28272456

  5. Computer vision and machine learning for robust phenotyping in genome-wide studies.

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R V Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K

    2017-03-08

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems.

  6. Distributed Cloud Computing Environment Enhanced With Capabilities for Wide-Area Migration and Replication Of Virtual Machines

    Directory of Open Access Journals (Sweden)

    Young-Chul Shim

    2013-12-01

    Full Text Available When a network application is implemented as a virt ual machine on a cloud and is used by a large numbe r of users, the location of the virtual machine shoul d be selected carefully so that the response time experienced by users is minimized. As the user popu lation moves and/or increases, the virtual machine may need to be migrated to a new location or replicated on many locations over a wide-area network. Virtua l machine migration and replication have been studied extensively but in most cases are limited within a subnetwork to be able to maintain service continuit y. In this paper we introduce a distributed cloud computing environment which facilitates the migrati on and replication of a virtual machine over a wide area network. The mechanism is provided by an overl ay network of smart routers, each of which connects a cooperating data center to the Internet. The propos ed approach is analyzed and compared with related works.

  7. WIDE-AREA BASED ON COORDINATED TUNING OF FUZZY PSS AND FACTS CONTROLLER IN MULTI-MACHINE ENVIRONMENT

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    Homayoun Ebrahimian

    2016-03-01

    Full Text Available In this paper coordination of fuzzy power system stabilizer (FPSS and flexible ac transmission systems (FACTS have been considered in a multi-machine power system. The proposed model, has been applied for a wide-area power system. The proposed FPSS presented with local, nonlinear feedbacks, and the corresponding control synthesis conditions are given in terms of solutions to a set of linear matrix inequalities (LMIs. For this model, in fuzzy control synthesis, the new proposed control design method is based on fewer fuzzy rules and less computational burden. Also, the parameters of FACTS controller have been evaluated by improved honey bee mating optimization (IHBMO. The effectiveness of the proposed method has been applied over two case studies of single-machine infinite-bus (SMIB and two areas four machine (TAFM Kundur’s power system. The obtained results demonstrate the superiority of proposed strategy.

  8. PuMa-II: A wide band pulsar machine for the Westerbork Synthesis Radio Telescope

    NARCIS (Netherlands)

    Karuppusamy, R.; Stappers, B.; van Straten, W.

    2008-01-01

    The Pulsar Machine II (PuMa-II) is the new flexible pulsar processing back-end system at the Westerbork Synthesis Radio Telescope (WSRT), specifically designed to take advantage of the upgraded WSRT. The instrument is based on a computer cluster running the Linux operating system, with minimal custo

  9. Micro-Viscometer for Measuring Shear-Varying Blood Viscosity over a Wide-Ranging Shear Rate.

    Science.gov (United States)

    Kim, Byung Jun; Lee, Seung Yeob; Jee, Solkeun; Atajanov, Arslan; Yang, Sung

    2017-06-20

    In this study, a micro-viscometer is developed for measuring shear-varying blood viscosity over a wide-ranging shear rate. The micro-viscometer consists of 10 microfluidic channel arrays, each of which has a different micro-channel width. The proposed design enables the retrieval of 10 different shear rates from a single flow rate, thereby enabling the measurement of shear-varying blood viscosity with a fixed flow rate condition. For this purpose, an optimal design that guarantees accurate viscosity measurement is selected from a parametric study. The functionality of the micro-viscometer is verified by both numerical and experimental studies. The proposed micro-viscometer shows 6.8% (numerical) and 5.3% (experimental) in relative error when compared to the result from a standard rotational viscometer. Moreover, a reliability test is performed by repeated measurement (N = 7), and the result shows 2.69 ± 2.19% for the mean relative error. Accurate viscosity measurements are performed on blood samples with variations in the hematocrit (35%, 45%, and 55%), which significantly influences blood viscosity. Since the blood viscosity correlated with various physical parameters of the blood, the micro-viscometer is anticipated to be a significant advancement for realization of blood on a chip.

  10. PuMaII: A wide band pulsar machine for the WSRT

    CERN Document Server

    Karuppusamy, Ramesh; van Straten, Willem

    2008-01-01

    The Pulsar Machine II (PuMa II) is the new flexible pulsar processing backend system at the Westerbork Synthesis Radio Telescope (WSRT), specifically designed to take advantage of the upgraded WSRT. The instrument is based on a computer cluster running the Linux operating system, with minimal custom hardware. A maximum of 160 MHz analogue bandwidth sampled as 8X20 MHz subbands with 8-bit resolution can be recorded on disks attached to separate computer nodes. Processing of the data is done in the additional 32-nodes allowing near real time coherent dedispersion for most pulsars observed at the WSRT. This has doubled the bandwidth for pulsar observations in general, and has enabled the use of coherent dedispersion over a bandwidth eight times larger than was previously possible at the WSRT. PuMa II is one of the widest bandwidth coherent dedispersion machines currently in use and has a maximum time resolution of 50ns. The system is now routinely used for high precision pulsar timing studies, polarization studi...

  11. Three-Dimensional Finite Element Based Numerical Simulation of Machining of Thin-Wall Components with Varying Wall Constraints

    Science.gov (United States)

    Joshi, Shrikrishna Nandkishor; Bolar, Gururaj

    2017-06-01

    Control of part deflection and deformation during machining of low rigidity thin-wall components is an important aspect in the manufacture of desired quality products. This paper presents a comparative study on the effect of geometry constraints on the product quality during machining of thin-wall components made of an aerospace alloy aluminum 2024-T351. Three-dimensional nonlinear finite element (FE) based simulations of machining of thin-wall parts were carried out by considering three variations in the wall constraint viz. free wall, wall constrained at one end, and wall with constraints at both the ends. Lagrangian formulation based transient FE model has been developed to simulate the interaction between the workpiece and helical milling cutter. Johnson-Cook material and damage model were adopted to account for material behavior during machining process; damage initiation and chip separation. A modified Coulomb friction model was employed to define the contact between the cutting tool and the workpiece. The numerical model was validated with experimental results and found to be in good agreement. Based on the simulation results it was noted that deflection and deformation were maximum in the thin-wall constrained at one end in comparison with those obtained in other cases. It was noted that three dimensional finite element simulations help in a better way to predict the product quality during precision manufacturing of thin-wall components.

  12. Influence of Varying Training Set Composition and Size on Support Vector Machine-Based Prediction of Active Compounds.

    Science.gov (United States)

    Rodríguez-Pérez, Raquel; Vogt, Martin; Bajorath, Jürgen

    2017-04-24

    Support vector machine (SVM) modeling is one of the most popular machine learning approaches in chemoinformatics and drug design. The influence of training set composition and size on predictions currently is an underinvestigated issue in SVM modeling. In this study, we have derived SVM classification and ranking models for a variety of compound activity classes under systematic variation of the number of positive and negative training examples. With increasing numbers of negative training compounds, SVM classification calculations became increasingly accurate and stable. However, this was only the case if a required threshold of positive training examples was also reached. In addition, consideration of class weights and optimization of cost factors substantially aided in balancing the calculations for increasing numbers of negative training examples. Taken together, the results of our analysis have practical implications for SVM learning and the prediction of active compounds. For all compound classes under study, top recall performance and independence of compound recall of training set composition was achieved when 250-500 active and 500-1000 randomly selected inactive training instances were used. However, as long as ∼50 known active compounds were available for training, increasing numbers of 500-1000 randomly selected negative training examples significantly improved model performance and gave very similar results for different training sets.

  13. Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

    Science.gov (United States)

    Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

    2016-11-01

    The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

  14. Genome wide association analysis of the 16th QTL- MAS Workshop dataset using the Random Forest machine learning approach

    Science.gov (United States)

    2014-01-01

    Background Genome wide association studies are now widely used in the livestock sector to estimate the association among single nucleotide polymorphisms (SNPs) distributed across the whole genome and one or more trait. As computational power increases, the use of machine learning techniques to analyze large genome wide datasets becomes possible. Methods The objective of this study was to identify SNPs associated with the three traits simulated in the 16th MAS-QTL workshop dataset using the Random Forest (RF) approach. The approach was applied to single and multiple trait estimated breeding values, and on yield deviations and to compare them with the results of the GRAMMAR-CG method. Results The two QTL mapping methods used, GRAMMAR-CG and RF, were successful in identifying the main QTLs for trait 1 on chromosomes 1 and 4, for trait 2 on chromosomes 1, 4 and 5 and for trait 3 on chromosomes 1, 2 and 3. Conclusions The results of the RF approach were confirmed by the GRAMMAR-CG method and validated by the effective QTL position, even if their approach to unravel cryptic genetic structure is different. Furthermore, both methods showed complementary findings. However, when the variance explained by the QTL is low, they both failed to detect significant associations. PMID:25519518

  15. Guaranteed Student Loans: Profits of Secondary Market Lenders Vary Widely. United States General Accounting Office Briefing Report to Congressional Requesters.

    Science.gov (United States)

    General Accounting Office, Washington, DC. Div. of Human Resources.

    This report was prepared to determine lenders' rates of return or profitability on Stafford loans in their portfolios, reasons for varying levels of profitability among institutions that hold such loans, and the effect of 1986 subsidy reductions on these lenders' profitability. The study focused on the activities of lenders that purchase Stafford…

  16. Adaptive Time-Frequency Distribution Based on Time-Varying Autoregressive and Its Application to Machine Fault Diagnosis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The time-varying autoregressive (TVAR) modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-invariant problem by introducing a set of basic functions. Then, the parameters are estimated by using a recursive least square algorithm with a forgetting factor and an adaptive time-frequency distribution is achieved. The simulation results show that the proposed approach is superior to the short-time Fourier transform and Wigner distribution. And finally, the proposed method is applied to the fault diagnosis of a bearing, and the experiment result shows that the proposed method is effective in feature extraction.

  17. IgE and Drug Allergy: Antibody Recognition of ‘Small’ Molecules of Widely Varying Structures and Activities

    Directory of Open Access Journals (Sweden)

    Brian A. Baldo

    2014-01-01

    Full Text Available The variety of chemically diverse pharmacologically-active compounds administered to patients is large and seemingly forever growing, and, with every new drug released and administered, there is always the potential of an allergic reaction. The most commonly occurring allergic responses to drugs are the type I, or immediate hypersensitivity reactions mediated by IgE antibodies. These reactions may affect a single organ, such as the nasopharynx (allergic rhinitis, eyes (conjunctivitis, mucosa of mouth/throat/tongue (angioedema, bronchopulmonary tissue (asthma, gastrointestinal tract (gastroenteritis and skin (urticaria, eczema, or multiple organs (anaphylaxis, causing symptoms ranging from minor itching and inflammation to death. It seems that almost every drug is capable of causing an immediate reaction and it is unusual to find a drug that has not provoked an anaphylactic response in at least one patient. These facts alone indicate the extraordinary breadth of recognition of IgE antibodies for drugs ranging from relatively simple structures, for example, aspirin, to complex molecules, such as the macrolide antibiotics composed of a large macrocyclic ring with attached deoxy sugars. This wide recognition profile is borne out at the molecular level by results of quantitative immunochemical studies where hapten inhibition investigations have identified structural determinants complementary to IgE antibodies in the sera of allergic subjects. Allergenic determinants have been identified on a variety of drugs including neuromuscular blockers, penicillins, cephalosporins, opioids, thiopentone, sulfonamides, trimethoprim, quinolones, chlorhexidine and the non-steroidal anti-inflammatory drug aspirin. It is already clear that IgE can distinguish fine structural differences on a wide variety of molecules, determinants may be at least as small as an amino group or encompass the whole molecule, and individual drugs may demonstrate allergenic heterogeneity.

  18. Long-Term Fuid Flow Measurements From Widely Varied Oceanic Settings Elucidate Near-Surface Hydrologic Environments

    Science.gov (United States)

    Tryon, M. D.; Brown, K. M.

    2003-12-01

    The quantification of aqueous flux rates from various ocean floor environments has been a goal of numerous scientific programs for more than a decade with increasing focus on gas hydrate regions. Six years ago we developed the Chemical and Aqueous Transport (CAT) meter to collect long-term temporal records of low to moderate aqueous flow rates in sedimented ocean floor environments and, more specifically, to quantify to mass flux associated with the formation of gas hydrates. Since that time thirty of these instruments have been built and over a hundred deployments accomplished in a variety of hydrate and non-hydrate settings. We present here an overview of the results of these deployments and compare and contrast the flow records from these varied hydrological environments. Specific environments include: Gas Hydrates (Hydrate Ridge and the Eel River area on the Cascadia convergent margin, and Bush Hill in northern Gulf of Mexico), Hydrothermal (Japan's Sagami Bay and the incoming plate offshore Costa Rica's Nicoya Peninsula, TicoFlux area), and the tectonically active convergent margin off Nicoya and Osa. One of the most important outcomes of this research is the realization that fluid flow across the seabed/ocean interface is often dominated by shallow subsurface and oceanographic processes which vary significantly over time. These processes can be as simple as the diurnal pressure gradients caused by the rise and fall of tides to highly complex processes associated with the formation and transport of subsurface free gas. These processes have been both a boon and a bane to our research. Tidal oscillations have tended to mask the net flow in many very low flux settings. The high degree of spatial and temporal variation in some environments have revealed the extreme difficulty of quantifying the more widespread mass flux associated with the underlying tectonic processes. Yet, the nature of these variations have allowed us to better constrain the fundamental

  19. Time-Varying Total Stiffness Matrix of a Rigid Machine Spindle-Angular Contact Ball Bearings Assembly: Theory and Analytical/Experimental Verifications

    Directory of Open Access Journals (Sweden)

    Fawzi M.A. El-Saeidy

    2011-01-01

    Full Text Available A lagrangian formulation is presented for the total dynamic stiffness and damping matrices of a rigid rotor carrying noncentral rigid disk and supported on angular contact ball bearings (ACBBs. The bearing dynamic stiffness/damping marix is derived in terms of the bearing motions (displacements/rotations and then the principal of virtual work is used to transfer it from the bearing location to the rotor mass center to obtain the total dynamic stiffness/damping matrix. The bearing analyses take into account the bearing nonlinearities, cage rotation and bearing axial preload. The coefficients of these time-dependent matrices are presented analytically. The equations of motion of a rigid rotor-ACBBs assembly are derived using Lagrange's equation. The proposed analyses on deriving the bearing stiffness matrix are verified against existing bearing analyses of SKF researchers that, in turn, were verified using both SKF softwares/experiments and we obtained typical agreements. The presented total stiffness matrix is applied to a typical grinding machine spindle studied experimentally by other researchers and excellent agreements are obtained between our analytical eigenvalues and the experimental ones. The effect of using the total full stiffness matrix versus using the total diagonal stiffness matrix on the natural frequencies and dynamic response of the rigid rotor-bearings system is studied. It is found that using the diagonal matrix affects natural frequencies values (except the axial frequency and response amplitudes and pattern and causes important vibration tones to be missig from the response spectrum. Therefore it is recommended to use the full total stiffness matrix and not the diagonal matrix in the design/vibration analysis of these rotating machines. For a machine spindle-ACBBs assembly under mass unbalnce and a horizontal force at the spindle cutting nose when the bearing time-varying stiffness matrix (bearing cage rotation is considered

  20. Rooting depth and water source flexibility of Arundo donax across a wide and topographically varied floodplain inferred from stable isotopes

    Science.gov (United States)

    Moore, G. W.; West, J. B.; Li, F.; Kui, L.

    2011-12-01

    sources relative to groundwater. Rhizome water isotopic composition exhibited marked spatio-temporal variability that showed strong sensitivity to both soil moisture deficits and flooding. Our results demonstrate that Arundo readily switches water source from surface soil to groundwater to maintain relatively uniform transpiration across environmental gradients. Consistent with our observations of rooting depths to at least 5 m, dependence on groundwater increased with decreasing soil moisture in a similar manner across a wide range of groundwater depths (<1 m to 5 m), with no apparent influence of depth on deep water access. These trends illustrate how this now broadly-distributed species benefits from flexible use of hydrologic flowpaths unique to riparian environments. A more in-depth understanding of the ecohydrological interactions between the river, the hyporheic zone, riparian sediments and soils will improve our ability to predict ecosystem responses to changing climate and increasing human demands for water.

  1. Monitoring of the state of the paper machine circulation water with a wide-band impedance measurement; Paperikoneen kiertoveden tilan seuranta laajakaistaisella impedanssimittauksella - MPKT 02

    Energy Technology Data Exchange (ETDEWEB)

    Varpula, T. [VTT Automation, Espoo (Finland). Measurement Technology

    1998-12-31

    A new measurement method for monitoring the chemical state of the circulation water in the paper machine is proposed and studied. In the method, the electrical properties - conductivity and permittivity - of the water are measured in a wide frequency band: 20 Hz - 10 mhz. Large-molecule organic compounds in the water are expected cause characteristic changes in the dielectric properties of the water. Continuous monitoring of the permittivity in the wide frequency band thus reveals their presence. Various electronic measurement setups for the measurement are constructed and studied by using test samples. If the method turns out to be promising, a prototype device will be made. (orig.)

  2. Automated cell analysis tool for a genome-wide RNAi screen with support vector machine based supervised learning

    Science.gov (United States)

    Remmele, Steffen; Ritzerfeld, Julia; Nickel, Walter; Hesser, Jürgen

    2011-03-01

    RNAi-based high-throughput microscopy screens have become an important tool in biological sciences in order to decrypt mostly unknown biological functions of human genes. However, manual analysis is impossible for such screens since the amount of image data sets can often be in the hundred thousands. Reliable automated tools are thus required to analyse the fluorescence microscopy image data sets usually containing two or more reaction channels. The herein presented image analysis tool is designed to analyse an RNAi screen investigating the intracellular trafficking and targeting of acylated Src kinases. In this specific screen, a data set consists of three reaction channels and the investigated cells can appear in different phenotypes. The main issue of the image processing task is an automatic cell segmentation which has to be robust and accurate for all different phenotypes and a successive phenotype classification. The cell segmentation is done in two steps by segmenting the cell nuclei first and then using a classifier-enhanced region growing on basis of the cell nuclei to segment the cells. The classification of the cells is realized by a support vector machine which has to be trained manually using supervised learning. Furthermore, the tool is brightness invariant allowing different staining quality and it provides a quality control that copes with typical defects during preparation and acquisition. A first version of the tool has already been successfully applied for an RNAi-screen containing three hundred thousand image data sets and the SVM extended version is designed for additional screens.

  3. Modeling the Relationship between Vibration Features and Condition Parameters Using Relevance Vector Machines for Health Monitoring of Rolling Element Bearings under Varying Operation Conditions

    Directory of Open Access Journals (Sweden)

    Lei Hu

    2015-01-01

    Full Text Available Rotational speed and load usually change when rotating machinery works. Both this kind of changing operational conditions and machine fault could make the mechanical vibration characteristics change. Therefore, effective health monitoring method for rotating machinery must be able to adjust during the change of operational conditions. This paper presents an adaptive threshold model for the health monitoring of bearings under changing operational conditions. Relevance vector machines (RVMs are used for regression of the relationships between the adaptive parameters of the threshold model and the statistical characteristics of vibration features. The adaptive threshold model is constructed based on these relationships. The health status of bearings can be indicated via detecting whether vibration features exceed the adaptive threshold. This method is validated on bearings running at changing speeds. The monitoring results show that this method is effective as long as the rotational speed is higher than a relative small value.

  4. Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

    Directory of Open Access Journals (Sweden)

    M Muksitul Haque

    Full Text Available Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs. Different environmental toxicants have been shown to promote exposure (i.e., toxicant specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT and methoxychlor (MXC exposure lineage F3 generation. Analysis of this positive validation

  5. Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

    Science.gov (United States)

    Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

    2015-01-01

    Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set

  6. Model-Based Comparison of Deep Brain Stimulation Array Functionality with Varying Number of Radial Electrodes and Machine Learning Feature Sets.

    Science.gov (United States)

    Teplitzky, Benjamin A; Zitella, Laura M; Xiao, YiZi; Johnson, Matthew D

    2016-01-01

    Deep brain stimulation (DBS) leads with radially distributed electrodes have potential to improve clinical outcomes through more selective targeting of pathways and networks within the brain. However, increasing the number of electrodes on clinical DBS leads by replacing conventional cylindrical shell electrodes with radially distributed electrodes raises practical design and stimulation programming challenges. We used computational modeling to investigate: (1) how the number of radial electrodes impact the ability to steer, shift, and sculpt a region of neural activation (RoA), and (2) which RoA features are best used in combination with machine learning classifiers to predict programming settings to target a particular area near the lead. Stimulation configurations were modeled using 27 lead designs with one to nine radially distributed electrodes. The computational modeling framework consisted of a three-dimensional finite element tissue conductance model in combination with a multi-compartment biophysical axon model. For each lead design, two-dimensional threshold-dependent RoAs were calculated from the computational modeling results. The models showed more radial electrodes enabled finer resolution RoA steering; however, stimulation amplitude, and therefore spatial extent of the RoA, was limited by charge injection and charge storage capacity constraints due to the small electrode surface area for leads with more than four radially distributed electrodes. RoA shifting resolution was improved by the addition of radial electrodes when using uniform multi-cathode stimulation, but non-uniform multi-cathode stimulation produced equivalent or better resolution shifting without increasing the number of radial electrodes. Robust machine learning classification of 15 monopolar stimulation configurations was achieved using as few as three geometric features describing a RoA. The results of this study indicate that, for a clinical-scale DBS lead, more than four radial

  7. Adaptive Wide-Area Damping Control for HVDC Transmission System Considering Influence of Time-Varying Delay%考虑时变时滞影响的直流广域阻尼自适应控制

    Institute of Scientific and Technical Information of China (English)

    胡楠; 李兴源; 杨毅强; 覃波

    2014-01-01

    针对交直流系统区间低频振荡问题,尤其是广域测量系统引入的时滞影响问题,利用递归最小二乘法在线辨识区间振荡主导模态,在直流附加控制抑制低频振荡机理的基础上,通过在线计算利用交流联络线功率信号进行阻尼控制的滞后相位与时变时滞造成低频振荡模态信号的滞后相位,将时域信号转化为二维旋转坐标体系中的向量信号,经过参考坐标体系的角度旋转,分别进行阻尼与时滞滞后相角的自适应补偿,结合增益放大,通过时域反变换后可得到最终补偿后的直流附加控制量。8机36节点系统仿真表明,所提设计方法能够消除时变时滞的影响,有效阻尼系统低频振荡,并且具有鲁棒性,适合在线应用。%In allusion to inter-area low-frequency oscillation occurred in AC-DC power transmission system, especially to the time delay caused by wide-area measurement system, using recursive least squares (RLS), the online identification of dominant modal of inter-area oscillation is implemented, and on the basis of suppressing low-frequency oscillation by adding supplementary control of HVDC, through the online calculation of the lagging phase caused by utilizing power signal of AC tie line transmission line for damping control and the lagging phase of low-frequency oscillation signal due to the time-varying delay, the time-domain signals are transformed into vector signals in the two dimensional rotating coordinate system, then by means of angle rotated in reference coordinate system the adaptive compensation for lagging phase due to damping control and the adaptive compensation for lagging phase due to time-varying delay are carried out respectively. Combining with gain amplification, after the inverse transformation in time-domain the post-final compensation DC supplementary controlled quantity can be obtained. Simulation results of a 8-machine 36-bus system show that the

  8. 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.

  9. Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures.

    Science.gov (United States)

    Ge, Tian; Feng, Jianfeng; Hibar, Derrek P; Thompson, Paul M; Nichols, Thomas E

    2012-11-01

    Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics has attracted growing attention and interest, most brain-wide genome-wide association studies focus on voxel-wise single-locus approaches, without taking advantage of the spatial information in images or combining the effect of multiple genetic variants. In this paper we present a fast implementation of voxel- and cluster-wise inferences based on the random field theory to fully use the spatial information in images. The approach is combined with a multi-locus model based on least square kernel machines to associate the joint effect of several single nucleotide polymorphisms (SNP) with imaging traits. A fast permutation procedure is also proposed which significantly reduces the number of permutations needed relative to the standard empirical method and provides accurate small p-value estimates based on parametric tail approximation. We explored the relation between 448,294 single nucleotide polymorphisms and 18,043 genes in 31,662 voxels of the entire brain across 740 elderly subjects from the Alzheimer's disease neuroimaging initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. We find method to be more sensitive compared with voxel-wise single-locus approaches. A number of genes were identified as having significant associations with volumetric changes. The most associated gene was GRIN2B, which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit and affects both the parietal and temporal lobes in human brains. Its role in Alzheimer's disease has been widely acknowledged and studied, suggesting the validity of the approach. The

  10. 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.

  11. miRNA gene counts in chromosomes vary widely in a species and biogenesis of miRNA largely depends on transcription or posttranscriptional processing of coding genes

    Directory of Open Access Journals (Sweden)

    Atanu eGhorai

    2014-04-01

    Full Text Available MicroRNAs target specific mRNA(s to silence its expression and thereby regulate various cellular processes. We have investigated miRNA gene counts in chromosomes for 20 different species and observed wide variation. Certain chromosomes have extremely high number of miRNA gene compared with others in all the species. For example, high number of miRNA gene in X chromosome and the least or absence of miRNA gene in Y chromosome was observed in all species. To search the criteria governing such variation of miRNA gene counts in chromosomes, we have selected three parameters- length, number of non-coding and coding genes in a chromosome. We have calculated Pearson’s correlation coefficient of miRNA gene counts with length, number of non-coding and coding genes in a chromosome for all 20 species. Major number of species showed that number of miRNA gene was not correlated with chromosome length. 85% of species under study showed strong positive correlation coefficient (r≥0.5 between the numbers of miRNA gene vs non-coding gene in chromosomes as expected because miRNA is a sub-set of non-coding genes. 55% species under study showed strong positive correlation coefficient (r≥0.5 between numbers of miRNA gene vs coding gene. We hypothesize biogenesis of miRNA largely depends on coding genes, an evolutionary conserved process. Chromosomes having higher number of miRNA genes will be most likely playing regulatory roles in several cellular processes including different disorders. In humans, cancer and cardiovascular disease associated miRNAs are mostly intergenic and located in Chromosome 19, X, 14 and 1.

  12. The utility of protein structure as a predictor of site-wise dN/dS varies widely among HIV-1 proteins.

    Science.gov (United States)

    Meyer, Austin G; Wilke, Claus O

    2015-10-06

    Protein structure acts as a general constraint on the evolution of viral proteins. One widely recognized structural constraint explaining evolutionary variation among sites is the relative solvent accessibility (RSA) of residues in the folded protein. In influenza virus, the distance from functional sites has been found to explain an additional portion of the evolutionary variation in the external antigenic proteins. However, to what extent RSA and distance from a reference site in the protein can be used more generally to explain protein adaptation in other viruses and in the different proteins of any given virus remains an open question. To address this question, we have carried out an analysis of the distribution and structural predictors of site-wise dN/dS in HIV-1. Our results indicate that the distribution of dN/dS in HIV follows a smooth gamma distribution, with no special enrichment or depletion of sites with dN/dS at or above one. The variation in dN/dS can be partially explained by RSA and distance from a reference site in the protein, but these structural constraints do not act uniformly among the different HIV-1 proteins. Structural constraints are highly predictive in just one of the three enzymes and one of three structural proteins in HIV-1. For these two proteins, the protease enzyme and the gp120 structural protein, structure explains between 30 and 40% of the variation in dN/dS. Finally, for the gp120 protein of the receptor-binding complex, we also find that glycosylation sites explain just 2% of the variation in dN/dS and do not explain gp120 evolution independently of either RSA or distance from the apical surface. © 2015 The Author(s).

  13. Comparison between wire mesh and plate electrodes during Wide-pattern machining on invar fine sheet using through-mask electrochemical micromachining

    Energy Technology Data Exchange (ETDEWEB)

    Chun, Kwang-ho; Jin, Da-som; Kim, Seong-hyun; Lee, Eun-sang [Inha University, Incheon (Korea, Republic of)

    2017-04-15

    Many research on the fabrication of Organic light emitting diodes (OLED) shadow masks with high resolution have been carried out because of the development of the smart-display industry. It is the parts of display panel which has millions of micro holes on invar (Fe- Ni) fine sheet. Various techniques such as laser machining, chemical etching and Electrochemical micro-machining (EMM) are used to produce micro-hole arrays. In this study, Through-mask electrochemical machining (TMEMM) combine with portion of photolithography process was applied to fabricate micro-hole arrays on invar fine sheet. The sheet was coated with dry film photoresist. Two types of electrode, plate and mesh, was used to compare the influence of electrode type. The sheet was coated with dry film photoresist with micro- sized through holes. The results were compared in regard to uniformity and taper angle. Compared with the plate electrode, the mesh electrode has better uniformity and taper angle which is important criteria of OLED shadow mask. These results could be used to improve TMEMM for invar fine sheet when it is applied to fabricate micro-hole arrays and help to obtain optical uniformity and desired taper angles.

  14. 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...

  15. Appleton Papers Plant-Wide Energy Assessment Saves Energy and Reduces Waste (Paper machine at Appleton's West Carrollton paper mill)

    Energy Technology Data Exchange (ETDEWEB)

    None

    2002-03-01

    Plant-wide energy survey at the Appleton Papers, Inc. West Carrollton paper mill resulted in 21 recommendations for projects to reduce energy consumption and waste production and improve process efficiency.

  16. 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

  17. Varying Constants

    CERN Document Server

    Damour, Thibault Marie Alban Guillaume

    2003-01-01

    We review some string-inspired theoretical models which incorporate a correlated spacetime variation of coupling constants while remaining naturally compatible both with phenomenological constraints coming from geochemical data (Oklo; Rhenium decay) and with present equivalence principle tests. Barring unnatural fine-tunings of parameters, a variation of the fine-structure constant as large as that recently ``observed'' by Webb et al. in quasar absorption spectra appears to be incompatible with these phenomenological constraints. Independently of any model, it is emphasized that the best experimental probe of varying constants are high-precision tests of the universality of free fall, such as MICROSCOPE and STEP. Recent claims by Bekenstein that fine-structure-constant variability does not imply detectable violations of the equivalence principle are shown to be untenable.

  18. 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.

  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. SU-D-204-06: Integration of Machine Learning and Bioinformatics Methods to Analyze Genome-Wide Association Study Data for Rectal Bleeding and Erectile Dysfunction Following Radiotherapy in Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Oh, J; Deasy, J [Memorial Sloan Kettering Cancer Center, New York, NY (United States); Kerns, S [University of Rochester Medical Center, Rochester, NY (United States); Ostrer, H [Albert Einstein College of Medicine, Bronx, NY (United States); Rosenstein, B [Mount Sinai School of Medicine, New York, NY (United States)

    2016-06-15

    Purpose: We investigated whether integration of machine learning and bioinformatics techniques on genome-wide association study (GWAS) data can improve the performance of predictive models in predicting the risk of developing radiation-induced late rectal bleeding and erectile dysfunction in prostate cancer patients. Methods: We analyzed a GWAS dataset generated from 385 prostate cancer patients treated with radiotherapy. Using genotype information from these patients, we designed a machine learning-based predictive model of late radiation-induced toxicities: rectal bleeding and erectile dysfunction. The model building process was performed using 2/3 of samples (training) and the predictive model was tested with 1/3 of samples (validation). To identify important single nucleotide polymorphisms (SNPs), we computed the SNP importance score, resulting from our random forest regression model. We performed gene ontology (GO) enrichment analysis for nearby genes of the important SNPs. Results: After univariate analysis on the training dataset, we filtered out many SNPs with p>0.001, resulting in 749 and 367 SNPs that were used in the model building process for rectal bleeding and erectile dysfunction, respectively. On the validation dataset, our random forest regression model achieved the area under the curve (AUC)=0.70 and 0.62 for rectal bleeding and erectile dysfunction, respectively. We performed GO enrichment analysis for the top 25%, 50%, 75%, and 100% SNPs out of the select SNPs in the univariate analysis. When we used the top 50% SNPs, more plausible biological processes were obtained for both toxicities. An additional test with the top 50% SNPs improved predictive power with AUC=0.71 and 0.65 for rectal bleeding and erectile dysfunction. A better performance was achieved with AUC=0.67 when age and androgen deprivation therapy were added to the model for erectile dysfunction. Conclusion: Our approach that combines machine learning and bioinformatics techniques

  1. 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.

  2. Industrial Inspection with Open Eyes: Advance with Machine Vision Technology

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Zheng; Ukida, H.; Niel, Kurt; Ramuhalli, Pradeep

    2015-10-01

    Machine vision systems have evolved significantly with the technology advances to tackle the challenges from modern manufacturing industry. A wide range of industrial inspection applications for quality control are benefiting from visual information captured by different types of cameras variously configured in a machine vision system. This chapter screens the state of the art in machine vision technologies in the light of hardware, software tools, and major algorithm advances for industrial inspection. The inspection beyond visual spectrum offers a significant complementary to the visual inspection. The combination with multiple technologies makes it possible for the inspection to achieve a better performance and efficiency in varied applications. The diversity of the applications demonstrates the great potential of machine vision systems for industry.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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...

  9. 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

  10. 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.

  11. 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 ...

  12. 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.

  13. 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.

  14. MACHINE MOTION EQUATIONS

    Directory of Open Access Journals (Sweden)

    Florian Ion Tiberiu Petrescu

    2015-09-01

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

  15. 广义Hamilton多机电力系统的广域时滞阻尼控制%Wide-area Time-delay Damping Control of Generalized Hamilton Multi-machine Power System

    Institute of Scientific and Technical Information of China (English)

    古丽扎提·海拉提; 王杰

    2014-01-01

    随着跨区送电量的需求增加,大量功率需要进行远距离传输,因而抑制区域间的功率振荡仅靠局部反馈信号设计的控制器已难以保证整个系统的稳定运行。因此,含有时滞影响的广域控制器的分析和设计是近年来互联电网研究的热点之一。基于Hamilton系统理论,建立对应的广域测量电力系统的非线性时滞广义Hamilton模型,并以此模型为基础,给出相应的 Lyapunov-Krasovskii 泛函并推导出以矩阵不等式为形式的时滞依赖稳定性判据,注意到控制输入含有时滞信号的影响,设计出相应的广域阻尼控制器(wide-area damping controller,WADC),实现了含有时滞的广域反馈控制,并计算出能使闭环电力系统稳定的时滞裕度,权衡WADC的阻尼性能与时滞裕度之间的关系,从而给出对应的WADC控制参数。最后以16机68节点系统为例,用时域仿真的结果来说明所提时滞控制方法的有效性。%Large amount of power is required for long-distance transmission with the increase of cross-transmission of electricity demand, thus it is difficult to inhibit the power oscillation between the regions to guarantee the stable operation of the whole power system which only relies on local feedback signal designed controller. Therefore, it is one of the hot spots for the analysis and design with time delay influence of wide-area controller in recent study of interconnected grid. Based on Hamilton system theory, a nonlinear time-delay generalized Hamiltonian model of corresponding wide area measurement power system model was constructed. Based on the proposed model, the corresponding Lyapunov-Krasovskii functional was given to derive a delay-dependent steady stability criterion in term of matrix inequalities. It was noticed that control input contains the influence of time-delay signal;the corresponding wide-area damping controller (WADC) was designed. The WAN feedback control

  16. 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...

  17. 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.

  18. Optimization of Process Parameters in Wire Electrical Discharge Machining of MMC: A Review

    Directory of Open Access Journals (Sweden)

    J.M.Pujara

    2015-07-01

    Full Text Available Wire electrical discharge machining (WEDM is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes, which have sharp edges that are very difficult to be machined by the main stream machining processes. This practical technology of the WEDM process is based on the conventional EDM sparking phenomenon utilizing the widely accepted non-contact technique of material removal. Since the introduction of the process, WEDM has evolved from a simple means of making tools and dies to the best alternative of producing micro-scale parts with the highest degree of dimensional accuracy and surface finish quality. Metal matrix composites are advanced materials having high specific strength, good wear resistance, and high thermal expansion coefficient. To achieve this task, machining parameters such as pulse on time, pulse off time, peak current, servo voltage, wire feed, wire tension etc. of this process should be selected such that optimal value of their performance measures like Material Removal Rate (MRR, Surface Roughness (SR, Gap current, Dimensional deviation, etc. can be obtained or improved. In past decades, intensive research work had been carried out by different researchers for improvement and optimization of WEDM performance measures using various optimization techniques like Taguchi, Response Surface Methodology (RSM, Artificial Neural Network (ANN, Genetic Algorithm (GA, etc. This paper also highlights the feasibility of the different control strategies of obtaining the optimal machining conditions. This literature review helps to identify the suitable process parameters and their ranges in machining of metal matrix composites.

  19. Optimization of process parameters on EN24 Tool steel using Taguchi technique in Electro-Discharge Machining (EDM)

    Science.gov (United States)

    Jeykrishnan, J.; Vijaya Ramnath, B.; Akilesh, S.; Pradeep Kumar, R. P.

    2016-09-01

    In the field of manufacturing sectors, electric discharge machining (EDM) is widely used because of its unique machining characteristics and high meticulousness which can't be done by other traditional machines. The purpose of this paper is to analyse the optimum machining parameter, to curtail the machining time with respect to high material removal rate (MRR) and low tool wear rate (TWR) by varying the parameters like current, pulse on time (Ton) and pulse off time (Toff). By conducting several dry runs using Taguchi technique of L9 orthogonal array (OA), optimized parameters were found using analysis of variance (ANOVA) and the error percentage can be validated and parameter contribution for MRR and TWR were found.

  20. Program Design Report of the CNC Machine Tool(II)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H

    2007-06-15

    The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology.

  1. 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...

  2. 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...

  3. 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

  4. 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.

  5. 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.

  6. Ensuring proper and safe use of the cryotherapy machine

    Directory of Open Access Journals (Sweden)

    Ismael Cordero

    2015-04-01

    Full Text Available Cryotherapy machines, also known as cryosurgery machines, continue to be widely used for surgical procedures of the eye such as retinal detachment repair, cataract extraction, glaucoma and so on.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. A study of electrodischarge machining–pulse electrochemical machining combined machining for holes with high surface quality on superalloy

    Directory of Open Access Journals (Sweden)

    Ning Ma

    2015-11-01

    Full Text Available Noncircular holes on the surface of turbine rotor blades are usually machined by electrodischarge machining. A recast layer containing numerous micropores and microcracks is easily generated during the electrodischarge machining process due to the rapid heating and cooling effects, which restrict the wide applications of noncircular holes in aerospace and aircraft industries. Owing to the outstanding advantages of pulse electrochemical machining, electrodischarge machining–pulse electrochemical machining combined technique is provided to improve the overall quality of electrodischarge machining-drilled holes. The influence of pulse electrochemical machining processing parameters on the surface roughness and the influence of the electrodischarge machining–pulse electrochemical machining method on the surface quality and accuracy of holes have been studied experimentally. The results indicate that the pulse electrochemical machining processing time for complete removal of the recast layer decreases with the increase in the pulse electrochemical machining current. The low pulse electrochemical machining current results in uneven dissolution of the recast layer, while the higher pulse electrochemical machining current induces relatively homogeneous dissolution. The surface roughness is reduced from 4.277 to 0.299 µm, and the hole taper induced by top-down electrodischarge machining process was reduced from 1.04° to 0.17° after pulse electrochemical machining. On account of the advantages of electrodischarge machining and the pulse electrochemical machining, the electrodischarge machining–pulse electrochemical machining combined technique could be applied for machining noncircular holes with high shape accuracy and surface quality.

  12. 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 ...

  13. 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...

  14. COMPUTER SIMULATION OF A STIRLING REFRIGERATING MACHINE

    Directory of Open Access Journals (Sweden)

    V.V. Trandafilov

    2015-10-01

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

  15. Refining Nodes and Edges of State Machines

    DEFF Research Database (Denmark)

    Hallerstede, Stefan; Snook, Colin

    2011-01-01

    State machines are hierarchical automata that are widely used to structure complex behavioural specifications. We develop two notions of refinement of state machines, node refinement and edge refinement. We compare the two notions by means of examples and argue that, by adopting simple convention...... refinement theory and UML-B state machine refinement influences the style of node refinement. Hence we propose a method with direct proof of state machine refinement avoiding the detour via Event-B that is needed by UML-B....

  16. 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...

  17. 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.

  18. Design and manufacturing of abrasive jet machine for drilling operation

    Directory of Open Access Journals (Sweden)

    Mittal Divyansh

    2016-01-01

    Full Text Available Wide application of Abrasive Jet Machine (AJM is found in machining hard and brittle materials. Machining of brittle materials by AJM is due to brittle fracture and removal of micro chips from the work piece. Embedment of the abrasive particles in the brittle materials results in decrease of machining efficiency. In this paper design and manufacturing of AJM has been presented. Various parts of AJM have been designed using ANSYS 16.2 software. The parts are then manufactured indigenously as per designed parameters. The machine fabricated in this work will be used further for process optimization of AJM parameters for machining of glass and ceramics.

  19. 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...

  20. 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.

  1. 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

  2. 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...

  3. A study of electrodischarge machining–pulse electrochemical machining combined machining for holes with high surface quality on superalloy

    OpenAIRE

    Ning Ma; Xiaolong Yang; Mingqian Gao; Jinlong Song; Ganlin Liu; Wenji Xu

    2015-01-01

    Noncircular holes on the surface of turbine rotor blades are usually machined by electrodischarge machining. A recast layer containing numerous micropores and microcracks is easily generated during the electrodischarge machining process due to the rapid heating and cooling effects, which restrict the wide applications of noncircular holes in aerospace and aircraft industries. Owing to the outstanding advantages of pulse electrochemical machining, electrodischarge machining–pulse electrochemic...

  4. Nonlinear systems time-varying parameter estimation: Application to induction motors

    Energy Technology Data Exchange (ETDEWEB)

    Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)

    2008-11-15

    In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)

  5. Ultra wide band antennas

    CERN Document Server

    Begaud, Xavier

    2013-01-01

    Ultra Wide Band Technology (UWB) has reached a level of maturity that allows us to offer wireless links with either high or low data rates. These wireless links are frequently associated with a location capability for which ultimate accuracy varies with the inverse of the frequency bandwidth. Using time or frequency domain waveforms, they are currently the subject of international standards facilitating their commercial implementation. Drawing up a complete state of the art, Ultra Wide Band Antennas is aimed at students, engineers and researchers and presents a summary of internationally recog

  6. 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 ...

  7. Fluorosis varied treatment options

    OpenAIRE

    Sherwood I

    2010-01-01

    Fluorosis has been reported way back in 1901. The treatment options for fluorosis are varied depending upon individual cases. This article comes from Madurai in India where its surrounding towns are fluorosis-prone zones. The purpose of this article is to report various treatment options available for dental fluorosis; this is the first time that complete full mouth rehabilitation for dental fluorosis is being reported. This article also dwells on the need for the dentists to be aware of thei...

  8. 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

  9. Machine vision theory, algorithms, practicalities

    CERN Document Server

    Davies, E R

    2005-01-01

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

  10. 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

  11. Fluorosis varied treatment options

    Directory of Open Access Journals (Sweden)

    Sherwood I

    2010-01-01

    Full Text Available Fluorosis has been reported way back in 1901. The treatment options for fluorosis are varied depending upon individual cases. This article comes from Madurai in India where its surrounding towns are fluorosis-prone zones. The purpose of this article is to report various treatment options available for dental fluorosis; this is the first time that complete full mouth rehabilitation for dental fluorosis is being reported. This article also dwells on the need for the dentists to be aware of their local indigenous pathologies to treat it in a better manner.

  12. Evaluating Arabic to English Machine Translation

    Directory of Open Access Journals (Sweden)

    Laith S. Hadla

    2014-11-01

    Full Text Available Online text machine translation systems are widely used throughout the world freely. Most of these systems use statistical machine translation (SMT that is based on a corpus full with translation examples to learn from them how to translate correctly. Online text machine translation systems differ widely in their effectiveness, and therefore we have to fairly evaluate their effectiveness. Generally the manual (human evaluation of machine translation (MT systems is better than the automatic evaluation, but it is not feasible to be used. The distance or similarity of MT candidate output to a set of reference translations are used by many MT evaluation approaches. This study presents a comparison of effectiveness of two free online machine translation systems (Google Translate and Babylon machine translation system to translate Arabic to English. There are many automatic methods used to evaluate different machine translators, one of these methods; Bilingual Evaluation Understudy (BLEU method. BLEU is used to evaluate translation quality of two free online machine translation systems under consideration. A corpus consists of more than 1000 Arabic sentences with two reference English translations for each Arabic sentence is used in this study. This corpus of Arabic sentences and their English translations consists of 4169 Arabic words, where the number of unique Arabic words is 2539. This corpus is released online to be used by researchers. These Arabic sentences are distributed among four basic sentence functions (declarative, interrogative, exclamatory, and imperative. The experimental results show that Google machine translation system is better than Babylon machine translation system in terms of precision of translation from Arabic to English.

  13. Scikit-learn: Machine Learning in Python

    OpenAIRE

    Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu; Perrot, Matthieu

    2011-01-01

    International audience; Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic ...

  14. 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...

  15. 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.

  16. 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.

  17. 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)

  18. 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...

  19. 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

  20. Time Varying Feature Data

    Science.gov (United States)

    Echterhoff, J.; Simonis, I.; Atkinson, R.

    2012-04-01

    The infrastructure to gather, store and access information about our environment is improving and growing rapidly. The increasing amount of information allows us to get a better understanding of the current state of our environment, historical processes and to simulate and predict the future state of the environment. Finer grained spatial and temporal data and more reliable communications make it easier to model dynamic states and ephemeral features. The exchange of information within and across geospatial domains is facilitated through the use of harmonized information models. The Observations & Measurements (O&M) developed through OGC and standardised by ISO is an example of such a cross-domain information model. It is used in many domains, including meteorology, hydrology as well as the emergency management. O&M enables harmonized representation of common metadata that belong to the act of determining the state of a feature property, whether by sensors, simulations or humans. In addition to the resulting feature property value, information such as the result quality but especially the time that the result applies to the feature property can be represented. Temporal metadata is critical to modelling past and future states of a feature. The features, and the semantics of each property, are defined in domain specific Application Schema using the General Feature Model (GFM) from ISO 19109 and usually encoded following ISO 19136. However, at the moment these standards provide only limited support for the representation and handling of time varying feature data. Features like rivers, wildfires or gas plumes have a defined state - for example geographic extent - at any given point in time. To keep track of changes, a more complex model for example using time-series coverages is required. Furthermore, the representation and management of feature property value changes via the service interfaces defined by OGC and ISO - namely: WFS and WCS - would be rather complex

  1. 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...

  2. Comparative study on discharge conditions in micro-hole electrical discharge machining of tungsten carbide (WC-Co) material

    Institute of Scientific and Technical Information of China (English)

    Hyun-Seok TAK; Chang-Seung HA; Dong-Hyun KIM; Ho-Jun LEE; Hae-June LEE; Myung-Chang KANG

    2009-01-01

    WC-Co is used widely in die and mold industries due to its unique combination of hardness, strength and wear-resistance. For machining difficult-to-cut materials, such as tungsten carbide, micro-electrical discharge machining(EDM) is one of the most effective methods for making holes because the hardness is not a dominant parameter in EDM. This paper describes the characteristics of the discharge conditions for micro-hole EDM of tungsten carbide with a WC grain size of 0.5μm and Co content of 12%. The EDM process was conducted by varying the condenser and resistance values. A R-C discharge EDM device using arc erosion for micro-hole machining was suggested. Furthermore, the characteristics of the developed micro-EDM were analyzed in terms of the electro-optical observation using an oscilloscope and field emission scanning electron microscope.

  3. 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

  4. 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.

  5. 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.

  6. Characterization of machining quality attributes based on spindle probe, coordinate measuring machine, and surface roughness data

    Directory of Open Access Journals (Sweden)

    Tzu-Liang Bill Tseng

    2014-04-01

    Full Text Available This study investigates the effects of machining parameters as they relate to the quality characteristics of machined features. Two most important quality characteristics are set as the dimensional accuracy and the surface roughness. Before any newly acquired machine tool is put to use for production, it is important to test the machine in a systematic way to find out how different parameter settings affect machining quality. The empirical verification was made by conducting a Design of Experiment (DOE with 3 levels and 3 factors on a state-of-the-art Cincinnati Hawk Arrow 750 Vertical Machining Center (VMC. Data analysis revealed that the significant factor was the Hardness of the material and the significant interaction effect was the Hardness + Feed for dimensional accuracy, while the significant factor was Speed for surface roughness. Since the equally important thing is the capability of the instruments from which the quality characteristics are being measured, a comparison was made between the VMC touch probe readings and the measurements from a Mitutoyo coordinate measuring machine (CMM on bore diameters. A machine mounted touch probe has gained a wide acceptance in recent years, as it is more suitable for the modern manufacturing environment. The data vindicated that the VMC touch probe has the capability that is suitable for the production environment. The test results can be incorporated in the process plan to help maintain the machining quality in the subsequent runs.

  7. varying elastic parameters distributions

    KAUST Repository

    Moussawi, Ali

    2014-12-01

    The experimental identication of mechanical properties is crucial in mechanics for understanding material behavior and for the development of numerical models. Classical identi cation procedures employ standard shaped specimens, assume that the mechanical elds in the object are homogeneous, and recover global properties. Thus, multiple tests are required for full characterization of a heterogeneous object, leading to a time consuming and costly process. The development of non-contact, full- eld measurement techniques from which complex kinematic elds can be recorded has opened the door to a new way of thinking. From the identi cation point of view, suitable methods can be used to process these complex kinematic elds in order to recover multiple spatially varying parameters through one test or a few tests. The requirement is the development of identi cation techniques that can process these complex experimental data. This thesis introduces a novel identi cation technique called the constitutive compatibility method. The key idea is to de ne stresses as compatible with the observed kinematic eld through the chosen class of constitutive equation, making possible the uncoupling of the identi cation of stress from the identi cation of the material parameters. This uncoupling leads to parametrized solutions in cases where 5 the solution is non-unique (due to unknown traction boundary conditions) as demonstrated on 2D numerical examples. First the theory is outlined and the method is demonstrated in 2D applications. Second, the method is implemented within a domain decomposition framework in order to reduce the cost for processing very large problems. Finally, it is extended to 3D numerical examples. Promising results are shown for 2D and 3D problems.

  8. Dynamic Analysis of Integrally Geared Compressors with Varying Workloads

    Directory of Open Access Journals (Sweden)

    Ming Zhang

    2016-01-01

    Full Text Available Integrally geared compressors are characterized by compact and high efficiency machines, which are widely used in modern processing industries. As an important part of integrally geared compressors, a geared rotor-bearing system exhibits complicated dynamic behaviors. When running at rated speeds, a coupling system likely produces resonance with an adjusted workload, and a critical load phenomenon occurs. The dynamic coefficients of bearings, axial force and torque, and gear meshing stiffness vary with workload because of the interaction between rotors. In this study, a dynamic model of a geared rotor-bearing system influenced by the dynamic coefficients of bearings, axial force and torque, and gear meshing stiffness is developed. The dynamic responses of the coupling system are calculated and analyzed by using a typical five-shaft integrally geared compressor as an example. The effects of different parameters on the dynamic behaviors of the proposed system are also considered in the discussion. The geared rotor-bearing system is further investigated to examine the failure mechanism of the critical load.

  9. 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

  10. Improving Hospital-Wide Early Resource Allocation through Machine Learning.

    Science.gov (United States)

    Gartner, Daniel; Padman, Rema

    2015-01-01

    The objective of this paper is to evaluate the extent to which early determination of diagnosis-related groups (DRGs) can be used for better allocation of scarce hospital resources. When elective patients seek admission, the true DRG, currently determined only at discharge, is unknown. We approach the problem of early DRG determination in three stages: (1) test how much a Naïve Bayes classifier can improve classification accuracy as compared to a hospital's current approach; (2) develop a statistical program that makes admission and scheduling decisions based on the patients' clincial pathways and scarce hospital resources; and (3) feed the DRG as classified by the Naïve Bayes classifier and the hospitals' baseline approach into the model (which we evaluate in simulation). Our results reveal that the DRG grouper performs poorly in classifying the DRG correctly before admission while the Naïve Bayes approach substantially improves the classification task. The results from the connection of the classification method with the mathematical program also reveal that resource allocation decisions can be more effective and efficient with the hybrid approach.

  11. A Review of Virtual Machine Attack Based on Xen

    Directory of Open Access Journals (Sweden)

    Ren xun-yi

    2016-01-01

    Full Text Available Virtualization technology as the foundation of cloud computing gets more and more attention because the cloud computing has been widely used. Analyzing the threat with the security of virtual machine and summarizing attack about virtual machine based on XEN to predict visible security hidden recently. Base on this paper can provide a reference for the further research on the security of virtual machine.

  12. Deep Extreme Learning Machine and Its Application in EEG Classification

    OpenAIRE

    Shifei Ding; Nan Zhang; Xinzheng Xu; Lili Guo; Jian Zhang

    2015-01-01

    Recently, deep learning has aroused wide interest in machine learning fields. Deep learning is a multilayer perceptron artificial neural network algorithm. Deep learning has the advantage of approximating the complicated function and alleviating the optimization difficulty associated with deep models. Multilayer extreme learning machine (MLELM) is a learning algorithm of an artificial neural network which takes advantages of deep learning and extreme learning machine. Not only does MLELM appr...

  13. Deep Extreme Learning Machine and Its Application in EEG Classification

    OpenAIRE

    2015-01-01

    Recently, deep learning has aroused wide interest in machine learning fields. Deep learning is a multilayer perceptron artificial neural network algorithm. Deep learning has the advantage of approximating the complicated function and alleviating the optimization difficulty associated with deep models. Multilayer extreme learning machine (MLELM) is a learning algorithm of an artificial neural network which takes advantages of deep learning and extreme learning machine. Not only does MLELM appr...

  14. SOFT SENSING MODEL BASED ON SUPPORT VECTOR MACHINE AND ITS APPLICATION

    Institute of Scientific and Technical Information of China (English)

    Yan Weiwu; Shao Huihe; Wang Xiaofan

    2004-01-01

    Soft sensor is widely used in industrial process control.It plays an important role to improve the quality of product and assure safety in production.The core of soft sensor is to construct soft sensing model.A new soft sensing modeling method based on support vector machine (SVM) is proposed.SVM is a new machine learning method based on statistical learning theory and is powerful for the problem characterized by small sample, nonlinearity, high dimension and local minima.The proposed methods are applied to the estimation of frozen point of light diesel oil in distillation column.The estimated outputs of soft sensing model based on SVM match the real values of frozen point and follow varying trend of frozen point very well.Experiment results show that SVM provides a new effective method for soft sensing modeling and has promising application in industrial process applications.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. Machine learning methods for planning

    CERN Document Server

    Minton, Steven

    1993-01-01

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

  6. 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.

  7. A Protein Classification Benchmark collection for machine learning

    NARCIS (Netherlands)

    Sonego, P.; Pacurar, M.; Dhir, S.; Kertész-Farkas, A.; Kocsor, A.; Gáspári, Z.; Leunissen, J.A.M.; Pongor, S.

    2007-01-01

    Protein classification by machine learning algorithms is now widely used in structural and functional annotation of proteins. The Protein Classification Benchmark collection (http://hydra.icgeb.trieste.it/benchmark) was created in order to provide standard datasets on which the performance of machin

  8. Tribology in secondary wood machining

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-07-01

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

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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...

  16. 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,…

  17. 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…

  18. 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.

  19. 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...

  20. Media-Augmented Exercise Machines

    Science.gov (United States)

    Krueger, T.

    2002-01-01

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

  1. 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 –...

  2. 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.

  3. Self-Calibrating Surface Measuring Machine

    Science.gov (United States)

    Greenleaf, Allen H.

    1983-04-01

    A new kind of surface-measuring machine has been developed under government contract at Itek Optical Systems, a Division of Itek Corporation, to assist in the fabrication of large, highly aspheric optical elements. The machine uses four steerable distance-measuring interferometers at the corners of a tetrahedron to measure the positions of a retroreflective target placed at various locations against the surface being measured. Using four interferometers gives redundant information so that, from a set of measurement data, the dimensions of the machine as well as the coordinates of the measurement points can be determined. The machine is, therefore, self-calibrating and does not require a structure made to high accuracy. A wood-structured prototype of this machine was made whose key components are a simple form of air bearing steering mirror, a wide-angle cat's eye retroreflector used as the movable target, and tracking sensors and servos to provide automatic tracking of the cat's eye by the four laser beams. The data are taken and analyzed by computer. The output is given in terms of error relative to an equation of the desired surface. In tests of this machine, measurements of a 0.7 m diameter mirror blank have been made with an accuracy on the order of 0.2µm rms.

  4. Vending machine assessment methodology. A systematic review.

    Science.gov (United States)

    Matthews, Melissa A; Horacek, Tanya M

    2015-07-01

    The nutritional quality of food and beverage products sold in vending machines has been implicated as a contributing factor to the development of an obesogenic food environment. How comprehensive, reliable, and valid are the current assessment tools for vending machines to support or refute these claims? A systematic review was conducted to summarize, compare, and evaluate the current methodologies and available tools for vending machine assessment. A total of 24 relevant research studies published between 1981 and 2013 met inclusion criteria for this review. The methodological variables reviewed in this study include assessment tool type, study location, machine accessibility, product availability, healthfulness criteria, portion size, price, product promotion, and quality of scientific practice. There were wide variations in the depth of the assessment methodologies and product healthfulness criteria utilized among the reviewed studies. Of the reviewed studies, 39% evaluated machine accessibility, 91% evaluated product availability, 96% established healthfulness criteria, 70% evaluated portion size, 48% evaluated price, 52% evaluated product promotion, and 22% evaluated the quality of scientific practice. Of all reviewed articles, 87% reached conclusions that provided insight into the healthfulness of vended products and/or vending environment. Product healthfulness criteria and complexity for snack and beverage products was also found to be variable between the reviewed studies. These findings make it difficult to compare results between studies. A universal, valid, and reliable vending machine assessment tool that is comprehensive yet user-friendly is recommended.

  5. Digital repetitive control under varying frequency conditions

    CERN Document Server

    Ramos, Germán A; Olm, Josep M

    2013-01-01

    The tracking/rejection of periodic signals constitutes a wide field of research in the control theory and applications area. Repetitive Control has proven to be an efficient way to face this topic. However, in some applications the frequency of the reference/disturbance signal is time-varying or uncertain. This causes an important performance degradation in the standard Repetitive Control scheme. This book presents some solutions to apply Repetitive Control in varying frequency conditions without loosing steady-state performance. It also includes a complete theoretical development and experimental results in two representative systems. The presented solutions are organized in two complementary branches: varying sampling period Repetitive Control and High Order Repetitive Control. The first approach allows dealing with large range frequency variations while the second allows dealing with small range frequency variations. The book also presents applications of the described techniques to a Roto-magnet plant and...

  6. Machine perfusion in liver transplantation as a tool to prevent non-anastomotic biliary strictures: Rationale, current evidence and future directions.

    Science.gov (United States)

    Weeder, Pepijn D; van Rijn, Rianne; Porte, Robert J

    2015-07-01

    The high incidence of non-anastomotic biliary strictures (NAS) after transplantation of livers from extended criteria donors is currently a major barrier to widespread use of these organs. This review provides an update on the most recent advances in the understanding of the etiology of NAS. These new insights give reason to believe that machine perfusion can reduce the incidence of NAS after transplantation by providing more protective effects on the biliary tree during preservation of the donor liver. An overview is presented regarding the different endpoints that have been used for assessment of biliary injury and function before and after transplantation, emphasizing on methods used during machine perfusion. The wide spectrum of different approaches to machine perfusion is discussed, including the many different combinations of techniques, temperatures and perfusates at varying time points. In addition, the current understanding of the effect of machine perfusion in relation to biliary injury is reviewed. Finally, we explore directions for future research such as the application of (pharmacological) strategies during machine perfusion to further improve preservation. We stress the great potential of machine perfusion to possibly expand the donor pool by reducing the incidence of NAS in extended criteria organs. Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  7. 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

  8. 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.

  9. 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.

  10. Photometric Supernova Classification With Machine Learning

    CERN Document Server

    Lochner, Michelle; Peiris, Hiranya V; Lahav, Ofer; Winter, Max K

    2016-01-01

    Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Telescope (LSST), given that spectroscopic confirmation of type for all supernovae discovered with these surveys will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques fitting parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks and boosted decision trees. We test the pipeline on simulated multi-ba...

  11. Beam Dynamics Studies in Recirculating Machines

    CERN Document Server

    Pellegrini, Dario; Latina, A

    The LHeC and the CLIC Drive Beam share not only the high-current beams that make them prone to show instabilities, but also unconventional lattice topologies and operational schemes in which the time sequence of the bunches varies along the machine. In order to asses the feasibility of these projects, realistic simulations taking into account the most worrisome effects and their interplays, are crucial. These include linear and non-linear optics with time dependent elements, incoherent and coherent synchrotron radiation, short and long-range wakefields, beam-beam effect and ion cloud. In order to investigate multi-bunch effects in recirculating machines, a new version of the tracking code PLACET has been developed from scratch. PLACET2, already integrates most of the effects mentioned before and can easily receive additional physics. Its innovative design allows to describe complex lattices and track one or more bunches accordingly to the machine operation, reproducing the bunch train splitting and recombinat...

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Color in machine vision and its application

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Color is the phenomenon of human visual perception and the module of machine vision. Color information is widely used in the areas of virtual reality and humancomputer interaction. Color is the product of a visual environment, illumination and the human brain. Research on color information representation and its processing is typically interdisciplinary. Based on our research work on human color perception and machine color vision and its application, we summarized the hotspots of color studies in recent developments and new approaches to color vision,including basic theories and the application of color information in virtual reality, content-based image retrieval, and face recognition.

  1. A Machine Learning Approach to Automated Negotiation

    Institute of Scientific and Technical Information of China (English)

    Zhang Huaxiang(张化祥); Zhang Liang; Huang Shangteng; Ma Fanyuan

    2004-01-01

    Automated negotiation between two competitive agents is analyzed, and a multi-issue negotiation model based on machine learning, time belief, offer belief and state-action pair expected Q value is developed. Unlike the widely used approaches such as game theory approach, heuristic approach and argumentation approach, This paper uses a machine learning method to compute agents' average Q values in each negotiation stage. The delayed reward is used to generate agents' offer and counteroffer of every issue. The effect of time and discount rate on negotiation outcome is analyzed. Theory analysis and experimental data show this negotiation model is practical.

  2. Bouncing universes with varying constants

    Energy Technology Data Exchange (ETDEWEB)

    Barrow, John D [DAMTP, Centre for Mathematical Sciences, Cambridge University, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Kimberly, Dagny [Theoretical Physics, Blackett Laboratory, Imperial College, Prince Consort Road, London SW7 2BZ (United Kingdom); Magueijo, Joao [Theoretical Physics, Blackett Laboratory, Imperial College, Prince Consort Road, London SW7 2BZ (United Kingdom)

    2004-09-21

    We investigate the behaviour of exact closed bouncing Friedmann universes in theories with varying constants. We show that the simplest BSBM varying alpha theory leads to a bouncing universe. The value of alpha increases monotonically, remaining approximately constant during most of each cycle, but increasing significantly around each bounce. When dissipation is introduced we show that in each new cycle the universe expands for longer and to a larger size. We find a similar effect for closed bouncing universes in Brans-Dicke theory, where G also varies monotonically in time from cycle to cycle. Similar behaviour occurs also in varying speed of light theories.

  3. Bouncing Universes with Varying Constants

    CERN Document Server

    Barrow, J D; Magueijo, J; Barrow, John D.; Kimberly, Dagny; Magueijo, Joao

    2004-01-01

    We investigate the behaviour of exact closed bouncing Friedmann universes in theories with varying constants. We show that the simplest BSBM varying-alpha theory leads to a bouncing universe. The value of alpha increases monotonically, remaining approximately constant during most of each cycle, but increasing significantly around each bounce. When dissipation is introduced we show that in each new cycle the universe expands for longer and to a larger size. We find a similar effect for closed bouncing universes in Brans-Dicke theory, where $G$ also varies monotonically in time from cycle to cycle. Similar behaviour occurs also in varying speed of light theories.

  4. Investigation of Machine-ability of Inconel 800 in EDM with Coated Electrode

    Science.gov (United States)

    Karunakaran, K.; Chandrasekaran, M.

    2017-03-01

    The Inconel 800 is a high temperature application alloy which is classified as a nickel based super alloy. It has wide scope in aerospace engineering, gas Turbine etc. The machine-ability studies were found limited on this material. Hence This research focuses on machine-ability studies on EDM of Inconel 800 with Silver Coated Electrolyte Copper Electrode. The purpose of coating on electrode is to reduce tool wear. The factors pulse on Time, Pulse off Time and Peck Current were considered to observe the responses of surface roughness, material removal rate, tool wear rate. Taguchi Full Factorial Design is employed for Design the experiment. Some specific findings were reported and the percentage of contribution of each parameter was furnished

  5. 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.

  6. 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 ...

  7. 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...

  8. 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.

  9. 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.

  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. Modeling non-Gaussian time-varying vector autoregressive process

    Data.gov (United States)

    National Aeronautics and Space Administration — We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical...

  13. 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.

  14. 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...

  15. 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.

  16. 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...

  17. 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.

  18. Varying c and Particle Horizons

    CERN Document Server

    Chimento, L P; Pavón, D; Chimento, Luis P; Jakubi, Alejandro S; Pavon, Diego

    2001-01-01

    We explore what restrictions may impose the second law of thermodynamics on varying speed of light theories. We find that the attractor scenario solving the flatness problem is consistent with the generalized second law at late time.

  19. 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.

  20. Assessment of Partially Conductive Cracks from Eddy Current Non-Destructive Testing Signals using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Ladislav Janousek

    2015-01-01

    Full Text Available This paper deals with a three-dimensional non-destructive evaluation of partially conductive cracks from eddy current testing signals. An SUS316L plate specimen containing a crack is non-destructively inspected by the eddy current method using numerical simulations. An extensive database of eddy current response signals is prepared while dimensional parameters of a crack together with its partial conductivity are varied in wide ranges. A Support Vector Machine classification algorithm is employed to solve the electromagnetic inverse problem. The acquired signals are employed for training the algorithm and for testing its performance. It is demonstrated that the Support Vector Machine algorithm is able to properly classify detected defects into proper classes with very high probability even the partial conductivity of a detected crack together with its width are unknown.

  1. Damping of Inter-Area Low Frequency Oscillation Using an Adaptive Wide-Area Damping Controller

    DEFF Research Database (Denmark)

    Yao, Wei; Jiang, L.; Fang, Jiakun

    2013-01-01

    This paper presents an adaptive wide-area damping controller (WADC) based on generalized predictive control (GPC) and model identification for damping the inter-area low frequency oscillations in large-scale inter-connected power system. A recursive least-squares algorithm (RLSA) with a varying...... forgetting factor is applied to identify online the reduced-order linearlized model which contains dominant inter-area low frequency oscillations. Based on this linearlized model, the generalized predictive control scheme considering control output constraints is employed to obtain the optimal control signal...... in each sampling interval. Case studies are undertaken on a two-area fourmachine power system and the New England 10-machine 39-bus power system, respectively. Simulation results show that the proposed adaptive WADC not only can damp the inter-area oscillations effectively under a wide range of operation...

  2. Circular causality and indeterminism in machines for design

    OpenAIRE

    Thomas Fischer

    2014-01-01

    Presenting a hard-to-predict typography-varying system predicated on Nazi-era cryptography, the Enigma cipher machine, this paper illustrates conditions under which unrepeatable phenomena can arise, even from straight-forward mechanisms. Such conditions arise where systems are observed from outside of boundaries that arise through their observation, and where such systems refer to themselves in a circular fashion. It argues that the Enigma cipher machine is isomorphous with Heinz von Foerster...

  3. 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.

  4. 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 ...

  5. 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...

  6. 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...

  7. Multi-modal target detection for autonomous wide area search and surveillance

    Science.gov (United States)

    Breckon, Toby P.; Gaszczak, Anna; Han, Jiwan; Eichner, Marcin L.; Barnes, Stuart E.

    2013-10-01

    Generalised wide are search and surveillance is a common-place tasking for multi-sensory equipped autonomous systems. Here we present on a key supporting topic to this task - the automatic interpretation, fusion and detected target reporting from multi-modal sensor information received from multiple autonomous platforms deployed for wide-area environment search. We detail the realization of a real-time methodology for the automated detection of people and vehicles using combined visible-band (EO), thermal-band (IR) and radar sensing from a deployed network of multiple autonomous platforms (ground and aerial). This facilities real-time target detection, reported with varying levels of confidence, using information from both multiple sensors and multiple sensor platforms to provide environment-wide situational awareness. A range of automatic classification approaches are proposed, driven by underlying machine learning techniques, that facilitate the automatic detection of either target type with cross-modal target confirmation. Extended results are presented that show both the detection of people and vehicles under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance evaluation is presented at an episodic level with individual classifiers optimized for maximal each object of interest (vehicle/person) detection over a given search path/pattern of the environment, across all sensors and modalities, rather than on a per sensor sample basis. Episodic target detection, evaluated over a number of wide-area environment search and reporting tasks, generally exceeds 90%+ for the targets considered here.

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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...

  14. 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.

  15. 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.

  16. Deep Extreme Learning Machine and Its Application in EEG Classification

    Directory of Open Access Journals (Sweden)

    Shifei Ding

    2015-01-01

    Full Text Available Recently, deep learning has aroused wide interest in machine learning fields. Deep learning is a multilayer perceptron artificial neural network algorithm. Deep learning has the advantage of approximating the complicated function and alleviating the optimization difficulty associated with deep models. Multilayer extreme learning machine (MLELM is a learning algorithm of an artificial neural network which takes advantages of deep learning and extreme learning machine. Not only does MLELM approximate the complicated function but it also does not need to iterate during the training process. We combining with MLELM and extreme learning machine with kernel (KELM put forward deep extreme learning machine (DELM and apply it to EEG classification in this paper. This paper focuses on the application of DELM in the classification of the visual feedback experiment, using MATLAB and the second brain-computer interface (BCI competition datasets. By simulating and analyzing the results of the experiments, effectiveness of the application of DELM in EEG classification is confirmed.

  17. 4th International Conference on Man–Machine Interactions

    CERN Document Server

    Brachman, Agnieszka; Kozielski, Stanisław; Czachórski, Tadeusz

    2016-01-01

    This book provides an overview of the current state of research on development and application of methods, algorithms, tools and systems associated with the studies on man-machine interaction. Modern machines and computer systems are designed not only to process information, but also to work in dynamic environment, supporting or even replacing human activities in areas such as business, industry, medicine or military. The interdisciplinary field of research on man-machine interactions focuses on broad range of aspects related to the ways in which human make or use computational artifacts, systems and infrastructure.   This monograph is the fourth edition in the series and presents new concepts concerning analysis, design and evaluation of man-machine systems. The selection of high-quality, original papers covers a wide scope of research topics focused on the main problems and challenges encountered within rapidly evolving new forms of human-machine relationships. The presented material is structured into fol...

  18. Variable-Speed, Robust Synchronous Reluctance Machine Drive Systems

    DEFF Research Database (Denmark)

    Wang, Dong

    The synchronous reluctance machine drive is getting more and more interests from the industrial side, since it can provide higher system energy efficiency than traditional inverter-fed induction machine drive systems with similar production cost. It is considered as a good candidate for super...... premium efficiency machine and commercial products are available in the market. The research work in this dissertation aims at developing a simple, compact and robust synchronous reluctance machine drive system that can provide satisfactory performance with optimized system energy efficiency at various...... working conditions. Field oriented control assisted with various position estimation algorithms is in-vestigated. Position sensing via machine flux linkage is implemented with the assistance of a widely used flux observer. Experiments show that it may not always work properly and system oscillation...

  19. 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

  20. Machine learning for adaptive many-core machines a practical approach

    CERN Document Server

    Lopes, Noel

    2015-01-01

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

  1. 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.

  2. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear...... models to kernel learning, and means for restoring the generalizability in both kernel Principal Component Analysis and the Support Vector Machine are proposed. Viability is proved on a wide range of benchmark machine learning data sets....... as innerproducts in the model formulation. This dissertation presents research on improving the performance of standard kernel methods like kernel Principal Component Analysis and the Support Vector Machine. Moreover, the goal of the thesis has been two-fold. The first part focuses on the use of kernel Principal...

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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...

  9. 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...

  10. 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.

  11. 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,…

  12. 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;…

  13. 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

  14. 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.

  15. Time-varying Crash Risk

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae

    We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on re...

  16. Mass Varying Neutrinos in Supernovae

    CERN Document Server

    Rossi-Torres, F; de Holanda, P C; Peres, O L G

    2010-01-01

    We study limits for the mass varying neutrino model, using constrains from supernova neutrinos placed by the r-process condition, $Y_e<0.5$. Also, we use this model in a supernova environment to study the regions of survival probability in the oscillation space parameter ($\\tan^2\\theta$ and $\\Delta m^2_0$), considering the channel $\

  17. Time-varying Crash Risk

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae

    We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly...... on return variance once we include market illiquidity as an economic variable in the model....

  18. Esmaklassiline Karlovy Vary / Jaanus Noormets

    Index Scriptorium Estoniae

    Noormets, Jaanus

    2007-01-01

    Ilmar Raagi mängufilm "Klass" võitis 42. Karlovy Vary rahvusvahelise filmifestivalil kaks auhinda - ametliku kõrvalvõistlusprogrammi "East of the West" eripreemia "Special mention" ja Euroopa väärtfilmikinode keti Europa Cinemas preemia. Ka Asko Kase lühifilmi "Zen läbi prügi linastumisest ning teistest auhinnasaajatest ning osalejatest

  19. Optimistlik Karlovy Vary / Jaan Ruus

    Index Scriptorium Estoniae

    Ruus, Jaan, 1938-2017

    2007-01-01

    42. Karlovy Vary rahvusvahelise filmifestivali auhinnatud filmidest (žürii esimees Peter Bart). Kristallgloobuse sai Islandi-Saksamaa "Katseklaasilinn" (režii Baltasar Kormakur), parimaks režissööriks tunnistati norralane Bard Breien ("Negatiivse mõtlemise kunst"). Austraallase Michael James Rowlandi "Hea õnne teekond" sai žürii eripreemia

  20. Eestlased Karlovy Varys / J. R.

    Index Scriptorium Estoniae

    J. R.

    2007-01-01

    Ilmar Raagi mängufilm "Klass" osaleb 42. Karlovy Vary rahvusvahelise filmifestivali võistlusprogrammis "East of the West" ja Asko Kase lühimängufilm "Zen läbi prügi" on valitud festivali kõrvalprogrammi "Forum of Independents"

  1. Esmaklassiline Karlovy Vary / Jaanus Noormets

    Index Scriptorium Estoniae

    Noormets, Jaanus

    2007-01-01

    Ilmar Raagi mängufilm "Klass" võitis 42. Karlovy Vary rahvusvahelise filmifestivalil kaks auhinda - ametliku kõrvalvõistlusprogrammi "East of the West" eripreemia "Special mention" ja Euroopa väärtfilmikinode keti Europa Cinemas preemia. Ka Asko Kase lühifilmi "Zen läbi prügi linastumisest ning teistest auhinnasaajatest ning osalejatest

  2. 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.

  3. LSTM Neural Reordering Feature for Statistical Machine Translation

    OpenAIRE

    Cui, Yiming; Wang, Shijin; Li, Jianfeng

    2015-01-01

    Artificial neural networks are powerful models, which have been widely applied into many aspects of machine translation, such as language modeling and translation modeling. Though notable improvements have been made in these areas, the reordering problem still remains a challenge in statistical machine translations. In this paper, we present a novel neural reordering model that directly models word pairs and alignment. By utilizing LSTM recurrent neural networks, much longer context could be ...

  4. Human and machine perception communication, interaction, and integration

    CERN Document Server

    Cantoni, Virginio; Setti, Alessandra

    2005-01-01

    The theme of this book on human and machine perception is communication, interaction, and integration. For each basic topic there are invited lectures, corresponding to approaches in nature and machines, and a panel discussion. The lectures present the state of the art, outlining open questions and stressing synergies among the disciplines related to perception. The panel discussions are forums for open debate. The wide spectrum of topics allows comparison and synergy and can stimulate new approaches.

  5. Machining of Additively Manufactured Parts: Implications for Surface Integrity

    OpenAIRE

    Oyelola, O.; Crawforth, P.; M'Saoubi, R.; Clare, A.T.

    2016-01-01

    Additive manufacturing methods continue to move towards production ready technologies with the widely extolled virtues of rapid transition from design to part and enhanced design freedoms. However, due to fundamental limitations of laser based processes for metal additive manufacturing, there is a significant ongoing need for these parts to be subject to additional machining operations. This paper reports on a study to investigate the machining behavior and surface integrity of Ti-6Al-4 V com...

  6. Machining of Additively Manufactured Parts: Implications for Surface Integrity

    OpenAIRE

    Oyelola, O.; Crawforth, P.; M'Saoubi, R.; Clare, A.T.

    2016-01-01

    Additive manufacturing methods continue to move towards production ready technologies with the widely extolled virtues of rapid transition from design to part and enhanced design freedoms. However, due to fundamental limitations of laser based processes for metal additive manufacturing, there is a significant ongoing need for these parts to be subject to additional machining operations. This paper reports on a study to investigate the machining behavior and surface integrity of Ti-6Al-4 V com...

  7. Surface Analysis of Metal Materials After Water Jet Abrasive Machining

    Directory of Open Access Journals (Sweden)

    Pavel Polák

    2015-01-01

    Full Text Available In this article, we deal with a progressive production technology using the water jet cutting technology with the addition of abrasives for material removal. This technology is widely used in cutting various shapes, but also for the technology of machining such as turning, milling, drilling and cutting of threads. The aim of this article was to analyse the surface of selected types of metallic materials after abrasive machining, i.e. by assessing the impact of selected machining parameters on the surface roughness of metallic materials.

  8. Weighted K-means support vector machine for cancer prediction

    OpenAIRE

    Kim, Sunghwan

    2016-01-01

    To date, the support vector machine (SVM) has been widely applied to diverse bio-medical fields to address disease subtype identification and pathogenicity of genetic variants. In this paper, I propose the weighted K-means support vector machine (wKM-SVM) and weighted support vector machine (wSVM), for which I allow the SVM to impose weights to the loss term. Besides, I demonstrate the numerical relations between the objective function of the SVM and weights. Motivated by general ensemble tec...

  9. 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"--

  10. 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...

  11. 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...

  12. 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.

  13. 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.

  14. 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...

  15. 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

  16. 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

  17. An Investigation of Laser Assisted Machining of Al_2O_3 Particle Reinforced Aluminum Matrix Composite

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The Al 2O 3 particles reinforced aluminum matrix composite (Al 2O 3p/Al) are more and more widely used for their excellent physical and chemical properties. However, their poor machinability leads to severe tool wear and bad machined surface. In this paper laser assisted machining is adopted in machining Al 2O 3p/Al composite and good result was obtained. The result of experiment shows in machining Al 2O 3p/Al composites the cutting force is reduced in 30%~50%, the tool wear is reduced in 20%~30% an...

  18. 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.

  19. Design of a Cocoa Pod Splitting Machine

    Directory of Open Access Journals (Sweden)

    Adetunde, I.A

    2010-10-01

    Full Text Available This study outlines the design of a very efficient, highly productive, cost- effective, ergonomic and environmentally friendly cocoa splitting machine that will be used by cocoa Farmers world - wide to increase and boost productivity and enhance the quality of coca products to the highest possible level devoid of any hazards, dangers or perils. This machine can be manufactured from locally available scraps and assembled and maintained at a relatively low cost. The knives which do the splitting are actuated by simple hydraulic mechanisms devoid any major stresses, forces or moments acting on them. These mechanisms are powered by simple low - powered lobe positive displacement or hydrostatic hydraulic pumps of power rating of 87.5 kW (65.625 Hp. The machine can be assembled and/or disassembled easily and quickly, and, therefore can be owned patronized by a group of cocoa farmers who can easily bear the low cost of maintenance of the already relative cheap machine.

  20. Support vector machine applied in QSAR modelling

    Institute of Scientific and Technical Information of China (English)

    MEI Hu; ZHOU Yuan; LIANG Guizhao; LI Zhiliang

    2005-01-01

    Support vector machine (SVM), partial least squares (PLS), and Back-Propagation artificial neural network (ANN) were employed to establish QSAR models of 2 dipeptide datasets. In order to validate predictive capabilities on external dataset of the resulting models, both internal and external validations were performed. The division of dataset into both training and test sets was carried out by D-optimal design. The results showed that support vector machine (SVM) behaved well in both calibration and prediction. For the dataset of 48 bitter tasting dipeptides (BTD), the results obtained by support vector regression (SVR) were superior to that by PLS in both calibration and prediction. When compared with BP artificial neural network, SVR showed less calibration power but more predictive capability. For the dataset of angiotensin-converting enzyme (ACE) inhibitors, the results obtained by support vector machine (SVM) regression were equivalent to those by PLS and BP artificial neural network. In both datasets, SVR using linear kernel function behaved well as that using radial basis kernel function. The results showed that there is wide prospect for the application of support vector machine (SVM) into QSAR modeling.

  1. Integration of part selection, machine loading and machining optimisation decisions for balanced workload in flexible manufacturing system

    Directory of Open Access Journals (Sweden)

    Mussa I. Mgwatu

    2011-10-01

    Full Text Available This paper demonstrates the importance of incorporating and solving the machining optimisation problem jointly with part selection and machine loading problems in order to avoid unbalanced workload in the FMS. Unbalanced workload renders to ineffective FMS such that some machines on the manufacturing shop floor become more occupied than others. Since CNC machine tools employed in the FMS are rather expensive, it is mostly important to balance the workload so that all machines can be effectively utilised. Therefore, in this study, two mathematical models are presented and solved in efforts to balance the workload and improve the performance of the FMS. A two-stage sequential approach is adopted whereby the first stage deals with the maximum throughput objective while the second stage deals with the minimum production cost objective. The results show that when part selection, machine loading and machining optimisation problems are jointly solved, more practical decisions can be made and a wide range of balanced workload in the FMS can be realised with minimum production cost objective. The results also show that the available machine time and tooling budget have enormous effects on throughput and production cost.

  2. A Boltzmann machine for the organization of intelligent machines

    Science.gov (United States)

    Moed, Michael C.; Saridis, George N.

    1989-01-01

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

  3. Engineering molecular machines

    Science.gov (United States)

    Erman, Burak

    2016-04-01

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

  4. Boosting Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Elkin Eduardo García Díaz

    2006-11-01

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

  5. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

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

  6. Introduction to Machine Protection

    CERN Document Server

    Schmidt, R

    2016-01-01

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

  7. Technological requirements of profile machining

    Institute of Scientific and Technical Information of China (English)

    PARK Sangchul; CHUNG Yunchan

    2006-01-01

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

  8. Machining fiber-reinforced composites

    Science.gov (United States)

    Komanduri, Ranga

    1993-04-01

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

  9. Future database machine architectures

    OpenAIRE

    Hsiao, David K.

    1984-01-01

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

  10. Machine Learning at Scale

    OpenAIRE

    Izrailev, Sergei; Stanley, Jeremy M.

    2014-01-01

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

  11. Cost of photochemical machining

    OpenAIRE

    Roy, Rajkumar; Allen, David; Zamora, Oscar

    2004-01-01

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

  12. Austempered Ductile Iron Machining

    Science.gov (United States)

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

    2015-12-01

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

  13. Quantum Virtual Machine (QVM)

    Energy Technology Data Exchange (ETDEWEB)

    2016-11-18

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

  14. Agent Based Computing Machine

    Science.gov (United States)

    2005-12-09

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

  15. Magnetic Electrochemical Finishing Machining

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

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

  16. FMS precision machining

    Energy Technology Data Exchange (ETDEWEB)

    Burnham, M.W.

    1980-01-01

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

  17. Machine on Trial

    Science.gov (United States)

    2012-06-01

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

  18. Fast, Continuous Audiogram Estimation Using Machine Learning.

    Science.gov (United States)

    Song, Xinyu D; Wallace, Brittany M; Gardner, Jacob R; Ledbetter, Noah M; Weinberger, Kilian Q; Barbour, Dennis L

    2015-01-01

    Pure-tone audiometry has been a staple of hearing assessments for decades. Many different procedures have been proposed for measuring thresholds with pure tones by systematically manipulating intensity one frequency at a time until a discrete threshold function is determined. The authors have developed a novel nonparametric approach for estimating a continuous threshold audiogram using Bayesian estimation and machine learning classification. The objective of this study was to assess the accuracy and reliability of this new method relative to a commonly used threshold measurement technique. The authors performed air conduction pure-tone audiometry on 21 participants between the ages of 18 and 90 years with varying degrees of hearing ability. Two repetitions of automated machine learning audiogram estimation and one repetition of conventional modified Hughson-Westlake ascending-descending audiogram estimation were acquired by an audiologist. The estimated hearing thresholds of these two techniques were compared at standard audiogram frequencies (i.e., 0.25, 0.5, 1, 2, 4, 8 kHz). The two threshold estimate methods delivered very similar estimates at standard audiogram frequencies. Specifically, the mean absolute difference between estimates was 4.16 ± 3.76 dB HL. The mean absolute difference between repeated measurements of the new machine learning procedure was 4.51 ± 4.45 dB HL. These values compare favorably with those of other threshold audiogram estimation procedures. Furthermore, the machine learning method generated threshold estimates from significantly fewer samples than the modified Hughson-Westlake procedure while returning a continuous threshold estimate as a function of frequency. The new machine learning audiogram estimation technique produces continuous threshold audiogram estimates accurately, reliably, and efficiently, making it a strong candidate for widespread application in clinical and research audiometry.

  19. 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.

  20. 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 ...

  1. 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...

  2. Harmonic functions with varying coefficients

    Directory of Open Access Journals (Sweden)

    Jacek Dziok

    2016-05-01

    Full Text Available Abstract Complex-valued harmonic functions that are univalent and sense preserving in the open unit disk can be written in the form f = h + g ‾ $f=h+\\overline{g}$ , where h and g are analytic. In this paper we investigate some classes of univalent harmonic functions with varying coefficients related to Janowski functions. By using the extreme points theory we obtain necessary and sufficient convolution conditions, coefficients estimates, distortion theorems, and integral mean inequalities for these classes of functions. The radii of starlikeness and convexity for these classes are also determined.

  3. Linearized Bekenstein Varying Alpha Models

    CERN Document Server

    Pina-Avelino, P; Oliveira, J C

    2004-01-01

    We study the simplest class of Bekenstein-type, varying $\\alpha$ models, in which the two available free functions (potential and gauge kinetic function) are Taylor-expanded up to linear order. Any realistic model of this type reduces to a model in this class for a certain time interval around the present day. Nevertheless, we show that no such model is consistent with all existing observational results. We discuss possible implications of these findings, and in particular clarify the ambiguous statement (often found in the literature) that ``the Webb results are inconsistent with Oklo''.

  4. Linearized Bekenstein varying α models

    Science.gov (United States)

    Avelino, P. P.; Martins, C. J.; Oliveira, J. C.

    2004-10-01

    We study the simplest class of Bekenstein-type, varying α models, in which the two available free functions (potential and gauge kinetic function) are Taylor-expanded up to linear order. Any realistic model of this type reduces to a model in this class for a certain time interval around the present day. Nevertheless, we show that no such model is consistent with all existing observational results. We discuss possible implications of these findings, and, in particular, clarify the ambiguous statement (often found in the literature) that “the Webb results are inconsistent with Oklo.”

  5. Time-varying cosmological term

    Science.gov (United States)

    Socorro, J.; D'oleire, M.; Pimentel, Luis O.

    2015-11-01

    We present the case of time-varying cosmological term using the Lagrangian formalism characterized by a scalar field ϕ with standard kinetic energy and arbitrary potential V(ϕ). This model is applied to Friedmann-Robertson-Walker (FRW)cosmology. Exact solutions of the field equations are obtained by a special ansats to solve the Einstein-Klein-Gordon equation and a particular potential for the scalar field and barotropic perfect fluid. We present the evolution on this cosmological term with different scenarios.

  6. Machinability of Al 6061 Deposited with Cold Spray Additive Manufacturing

    Science.gov (United States)

    Aldwell, Barry; Kelly, Elaine; Wall, Ronan; Amaldi, Andrea; O'Donnell, Garret E.; Lupoi, Rocco

    2017-06-01

    Additive manufacturing techniques such as cold spray are translating from research laboratories into more mainstream high-end production systems. Similar to many additive processes, finishing still depends on removal processes. This research presents the results from investigations into aspects of the machinability of aluminum 6061 tubes manufactured with cold spray. Through the analysis of cutting forces and observations on chip formation and surface morphology, the effect of cutting speed, feed rate, and heat treatment was quantified, for both cold-sprayed and bulk aluminum 6061. High-speed video of chip formation shows changes in chip form for varying material and heat treatment, which is supported by the force data and quantitative imaging of the machined surface. The results shown in this paper demonstrate that parameters involved in cold spray directly impact on machinability and therefore have implications for machining parameters and strategy.

  7. An Investigation of Different Material on Abrasive Water jet Machine

    Directory of Open Access Journals (Sweden)

    Vaibhav.j.limbachiya

    2011-07-01

    Full Text Available Abrasive water jet machine (AWJM is a nontraditional machining process. Abrasive water jet machining is a process of removal of material by impact erosion of high pressure (1500-4000 bar, high velocity of water and entrained high velocity of grit abrasives on a work piece. It’s a non-conventional machining process. At herefirst works on theoretical work after it make some experimental work and then analyses both results. Theoretical MRR found equal to the experimental MRR. In this paper investigation for three different materials like en8,acrylic and aluminum is carried out using Taguchi design of experiment method. Experiments are carried out using L25 Orthogonal array by varying Material traverse speed and abrasive mass flow rate for each material respectively. Anova carried out for identifies significant parameters.

  8. Investigations on structural thinning in deformation machining stretching mode

    Science.gov (United States)

    Singh, Arshpreet; Nirala, Harish Kumar; Agrawal, Anupam

    2016-10-01

    Deformation machining is a combination of thin structure machining and single point incremental forming/bending. This process enables the creation of monolithic, complex structures and geometries, which are difficult or sometimes impossible to manufacture employing conventional manufacturing techniques. Section thinning of the formed structure is a measure of process formability and influences the strength and stiffness of the formed component. In this study, experimental and finite element investigations on structural thinning in Deformation machining stretching mode have been performed. Structural thinning was found out to be highly non uniform along the forming depth at varying forming angles. A compensation strategy in thin structure machining has been proposed for uniform section thickness in incremental forming.

  9. 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.

  10. Varying Constants, Gravitation and Cosmology

    Directory of Open Access Journals (Sweden)

    Jean-Philippe Uzan

    2011-03-01

    Full Text Available Fundamental constants are a cornerstone of our physical laws. Any constant varying in space and/or time would reflect the existence of an almost massless field that couples to matter. This will induce a violation of the universality of free fall. Thus, it is of utmost importance for our understanding of gravity and of the domain of validity of general relativity to test for their constancy. We detail the relations between the constants, the tests of the local position invariance and of the universality of free fall. We then review the main experimental and observational constraints that have been obtained from atomic clocks, the Oklo phenomenon, solar system observations, meteorite dating, quasar absorption spectra, stellar physics, pulsar timing, the cosmic microwave background and big bang nucleosynthesis. At each step we describe the basics of each system, its dependence with respect to the constants, the known systematic effects and the most recent constraints that have been obtained. We then describe the main theoretical frameworks in which the low-energy constants may actually be varying and we focus on the unification mechanisms and the relations between the variation of different constants. To finish, we discuss the more speculative possibility of understanding their numerical values and the apparent fine-tuning that they confront us with.

  11. Varying Constants, Gravitation and Cosmology.

    Science.gov (United States)

    Uzan, Jean-Philippe

    2011-01-01

    Fundamental constants are a cornerstone of our physical laws. Any constant varying in space and/or time would reflect the existence of an almost massless field that couples to matter. This will induce a violation of the universality of free fall. Thus, it is of utmost importance for our understanding of gravity and of the domain of validity of general relativity to test for their constancy. We detail the relations between the constants, the tests of the local position invariance and of the universality of free fall. We then review the main experimental and observational constraints that have been obtained from atomic clocks, the Oklo phenomenon, solar system observations, meteorite dating, quasar absorption spectra, stellar physics, pulsar timing, the cosmic microwave background and big bang nucleosynthesis. At each step we describe the basics of each system, its dependence with respect to the constants, the known systematic effects and the most recent constraints that have been obtained. We then describe the main theoretical frameworks in which the low-energy constants may actually be varying and we focus on the unification mechanisms and the relations between the variation of different constants. To finish, we discuss the more speculative possibility of understanding their numerical values and the apparent fine-tuning that they confront us with.

  12. Varying Constants, Gravitation and Cosmology

    Science.gov (United States)

    Uzan, Jean-Philippe

    2011-12-01

    Fundamental constants are a cornerstone of our physical laws. Any constant varying in space and/or time would reflect the existence of an almost massless field that couples to matter. This will induce a violation of the universality of free fall. Thus, it is of utmost importance for our understanding of gravity and of the domain of validity of general relativity to test for their constancy. We detail the relations between the constants, the tests of the local position invariance and of the universality of free fall. We then review the main experimental and observational constraints that have been obtained from atomic clocks, the Oklo phenomenon, solar system observations, meteorite dating, quasar absorption spectra, stellar physics, pulsar timing, the cosmic microwave background and big bang nucleosynthesis. At each step we describe the basics of each system, its dependence with respect to the constants, the known systematic effects and the most recent constraints that have been obtained. We then describe the main theoretical frameworks in which the low-energy constants may actually be varying and we focus on the unification mechanisms and the relations between the variation of different constants. To finish, we discuss the more speculative possibility of understanding their numerical values and the apparent fine-tuning that they confront us with.

  13. Machine tool metrology an industrial handbook

    CERN Document Server

    Smith, Graham T

    2016-01-01

    Maximizing reader insights into the key scientific disciplines of Machine Tool Metrology, this text will prove useful for the industrial-practitioner and those interested in the operation of machine tools. Within this current level of industrial-content, this book incorporates significant usage of the existing published literature and valid information obtained from a wide-spectrum of manufacturers of plant, equipment and instrumentation before putting forward novel ideas and methodologies. Providing easy to understand bullet points and lucid descriptions of metrological and calibration subjects, this book aids reader understanding of the topics discussed whilst adding a voluminous-amount of footnotes utilised throughout all of the chapters, which adds some additional detail to the subject. Featuring an extensive amount of photographic-support, this book will serve as a key reference text for all those involved in the field. .

  14. Iron Losses in Electrical Machines Due to Non Sinusoidal Alternating Fluxes

    DEFF Research Database (Denmark)

    Ritchie, Ewen; Walker, J.A.; Dorrell, D. G.

    2007-01-01

    This paper shows how the flux waveform in the core of an electrical machine can be vary non- sinusoidally which complicates the calculation of the iron loss in a machine. A set of tests are conducted on a steel sample using an Epstein square where harmonics are injected into the flux waveform which...

  15. Technical and Symbolic Knowledge in CNC Machining: A Study of Technical Workers of Different Backgrounds.

    Science.gov (United States)

    Martin, Laura M. W.; Beach, King

    Performances of 45 individuals with varying degrees of formal and informal training in machining and programming were compared on tasks designed to tap intellectual changes that may occur with the introduction of computer numerical control (CNC). Participants--30 machinists, 8 machine operators, and 7 engineers--were asked background questions and…

  16. Rinsing Processes in Open-width Washing Machines

    NARCIS (Netherlands)

    Kroezen, A.B.J.; Linden, van der H.J.L.J.; Groot Wassink, J.

    1986-01-01

    A simulator is described for rinsing processes carried out on open-width washing machines. In combination with a theoretical model, a simple method is given for testing rinsing processes. The method has been used to investigate the extraction of caustic soda from a cotton fabric, varying the tempera

  17. Local Varying-Alpha Theories

    CERN Document Server

    Barrow, John D

    2014-01-01

    In a recent paper we demonstrated how the simplest model for varying alpha may be interpreted as the effect of a dielectric material, generalized to be consistent with Lorentz invariance. Unlike normal dielectrics, such a medium cannot change the speed of light, and its dynamics obey a Klein-Gordon equation. This work immediately suggests an extension of the standard theory, even if we require compliance with Lorentz invariance. Instead of a wave equation, the dynamics may satisfy a local algebraic relation involving the permittivity and the properties of the electromagnetic field, in analogy with more conventional dielectric (but still preserving Lorentz invariance). We develop the formalism for such theories and investigate some phenomenological implications. The problem of the divergence of the classical self-energy can be solved, or at least softened, in this framework. Some interesting new cosmological solutions for the very early universe are found, including the possibility of a bounce, inflation and e...

  18. Varying constants, Gravitation and Cosmology

    CERN Document Server

    Uzan, Jean-Philippe

    2010-01-01

    Fundamental constants are a cornerstone of our physical laws. Any constant varying in space and/or time would reflect the existence of an almost massless field that couples to matter. This will induce a violation of the universality of free fall. It is thus of utmost importance for our understanding of gravity and of the domain of validity of general relativity to test for their constancy. We thus detail the relations between the constants, the tests of the local position invariance and of the universality of free fall. We then review the main experimental and observational constraints that have been obtained from atomic clocks, the Oklo phenomenon, Solar system observations, meteorites dating, quasar absorption spectra, stellar physics, pulsar timing, the cosmic microwave background and big bang nucleosynthesis. At each step we describe the basics of each system, its dependence with respect to the constants, the known systematic effects and the most recent constraints that have been obtained. We then describ...

  19. Exploration of Periodically Varying Graphs

    CERN Document Server

    Flocchini, Paola; Santoro, Nicola

    2009-01-01

    We study the computability and complexity of the exploration problem in a class of highly dynamic graphs: periodically varying (PV) graphs, where the edges exist only at some (unknown) times defined by the periodic movements of carriers. These graphs naturally model highly dynamic infrastructure-less networks such as public transports with fixed timetables, low earth orbiting (LEO) satellite systems, security guards' tours, etc. We establish necessary conditions for the problem to be solved. We also derive lower bounds on the amount of time required in general, as well as for the PV graphs defined by restricted classes of carriers movements: simple routes, and circular routes. We then prove that the limitations on computability and complexity we have established are indeed tight. In fact we prove that all necessary conditions are also sufficient and all lower bounds on costs are tight. We do so constructively presenting two worst case optimal solution algorithms, one for anonymous systems, and one for those w...

  20. Time-Varying Fundamental Constants

    Science.gov (United States)

    Olive, Keith

    2003-04-01

    Recent data from quasar absorption systems can be interpreted as arising from a time variation in the fine-structure constant. However, there are numerous cosmological, astro-physical, and terrestrial bounds on any such variation. These includes bounds from Big Bang Nucleosynthesis (from the ^4He abundance), the Oklo reactor (from the resonant neutron capture cross-section of Sm), and from meteoretic lifetimes of heavy radioactive isotopes. The bounds on the variation of the fine-structure constant are significantly strengthened in models where all gauge and Yukawa couplings vary in a dependent manner, as would be expected in unified theories. Models which are consistent with all data are severly challenged when Equivalence Principle constraints are imposed.

  1. Weighted approximation with varying weight

    CERN Document Server

    Totik, Vilmos

    1994-01-01

    A new construction is given for approximating a logarithmic potential by a discrete one. This yields a new approach to approximation with weighted polynomials of the form w"n"(" "= uppercase)P"n"(" "= uppercase). The new technique settles several open problems, and it leads to a simple proof for the strong asymptotics on some L p(uppercase) extremal problems on the real line with exponential weights, which, for the case p=2, are equivalent to power- type asymptotics for the leading coefficients of the corresponding orthogonal polynomials. The method is also modified toyield (in a sense) uniformly good approximation on the whole support. This allows one to deduce strong asymptotics in some L p(uppercase) extremal problems with varying weights. Applications are given, relating to fast decreasing polynomials, asymptotic behavior of orthogonal polynomials and multipoint Pade approximation. The approach is potential-theoretic, but the text is self-contained.

  2. Wire electrochemical machining with axial electrolyte flushing for titanium alloy

    Institute of Scientific and Technical Information of China (English)

    Qu Ningsong; Fang Xiaolong; Li Wei; Zeng Yongbin; Zhu Di

    2013-01-01

    Titanium and its alloys have found very wide application in aerospace due to their excellent characteristics although their processing is still a challenge.Electrochemical machining is an important issue in the fabrication of titanium and titanium alloys.Wire electrochemical machining (WECM) is mainly used for workpiece cutting under the condition of different thickness plates.It has a great advantage over wire electro-discharge machining,which is the absence of heat-affected zone around the cutting area.Moreover,the wire electrode in WECM could be used repetitively because it is not worn out.Thus,much attention has been paid to WECM.The effective way of removing electrolysis products is of importance to WECM.In this paper,the axial electrolyte flushing is presented to WECM for removing electrolysis products and renewing electrolyte.The Taguchi experiment is conducted to optimize the machining parameters,such as wire feedrate,machining voltage,electrolyte concentration,etc.Experimental results show that WECM with axial electrolyte flushing is a promising issue in the fabrication of titanium alloy (TC1).The feasibility of multi-wire electrochemical machining is also demonstrated to improve the machining productivity of WECM.

  3. 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.

  4. Fault detection in reciprocating compressor valves under varying load conditions

    Science.gov (United States)

    Pichler, Kurt; Lughofer, Edwin; Pichler, Markus; Buchegger, Thomas; Klement, Erich Peter; Huschenbett, Matthias

    2016-03-01

    This paper presents a novel approach for detecting cracked or broken reciprocating compressor valves under varying load conditions. The main idea is that the time frequency representation of vibration measurement data will show typical patterns depending on the fault state. The problem is to detect these patterns reliably. For the detection task, we make a detour via the two dimensional autocorrelation. The autocorrelation emphasizes the patterns and reduces noise effects. This makes it easier to define appropriate features. After feature extraction, classification is done using logistic regression and support vector machines. The method's performance is validated by analyzing real world measurement data. The results will show a very high detection accuracy while keeping the false alarm rates at a very low level for different compressor loads, thus achieving a load-independent method. The proposed approach is, to our best knowledge, the first automated method for reciprocating compressor valve fault detection that can handle varying load conditions.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Research in non-equalization machining method for spatial cam

    Institute of Scientific and Technical Information of China (English)

    Jun-hua CHEN; Yi-jie WU

    2008-01-01

    Many kinds of devices with cam have been widely used in various mechanical equipments.However,non-equalization machining for spatial cam trough remains to be a difficult problem.This paper focuses on the analysis of ruaning conditions and machining processes of spatial cam with oscillating follower.We point out the common errors in the biased distance cutting.By analyzing the motion of oscillating follower of spatial cam,we present a new 3D curve expansion model of spatial cam trough-outline.Based on this model.we have proposed a machining method for trochoidal milling with non-equalization diameter cutter.This new method has led to a creative and effective Way for non.equalization diameter machining for spatial cam with oscillating follower.

  11. 2015 International Conference on Machine Learning and Signal Processing

    CERN Document Server

    Woo, Wai; Sulaiman, Hamzah; Othman, Mohd; Saat, Mohd

    2016-01-01

    This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learni...

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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....

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Pulsed laser-assisted machining of Inconel 718 superalloy

    Science.gov (United States)

    Azhdari Tadavani, Soheila; Shoja Razavi, Reza; Vafaei, Reza

    2017-01-01

    Nickel-based superalloys including Inconel 718(IN718) are widely used in aerospace industries due to their superior high temperature strength, toughness, and corrosion resistance. These alloys are difficult to machine mainly because of their low thermal conductivity and high work hardening rate, which cause steep temperature gradient and high cutting forces at the tool edge. The application of laser assisted machining is the subject of many new researches since shear forces; surface coarsening and tool wear are reduced. The aim of this investigation was to evaluate laser assisted machining behavior of a 718 Inconel superalloy from the view point of machining specific energy, surface roughness, tool wear and chip appearance. Experimental apparatuses used included optical and scanning electron microscopy, spark emission spectroscopy, and EDS analysis. The results indicated that increasing the temperature to about 540 °C just ahead of primary shear zone, can result in 35% reduction of machining specific energy, in comparison with conventional machining. Furthermore, surface coarsening and tool wear were reduced by 22% and 23% respectively. Flank wear was the main deteriorating factor on cutting tools during laser assisted machining. SEM micrographs indicated that increase in temperature has no noticeable effect on finished workpiece surface. Analysis of variance obtained from regression analysis indicated that frequency of laser beam has the most influential effect on temperature. The optimum conditions for laser assisted machining of 718 superalloy is suggested as follows: 80 Hz frequency, 400 W power, 24 m/min cutting speed, and 0.052 mm/rev feed rate along with 540 °C temperature, 2.51 J/mm2 machining specific energy and 130 N cutting force.

  3. Machine Learning: A Crucial Tool for Sensor Design

    Directory of Open Access Journals (Sweden)

    Weixiang Zhao

    2008-12-01

    Full Text Available Sensors have been widely used for disease diagnosis, environmental quality monitoring, food quality control, industrial process analysis and control, and other related fields. As a key tool for sensor data analysis, machine learning is becoming a core part of novel sensor design. Dividing a complete machine learning process into three steps: data pre-treatment, feature extraction and dimension reduction, and system modeling, this paper provides a review of the methods that are widely used for each step. For each method, the principles and the key issues that affect modeling results are discussed. After reviewing the potential problems in machine learning processes, this paper gives a summary of current algorithms in this field and provides some feasible directions for future studies.

  4. Distinguished figures in mechanism and machine science

    CERN Document Server

    2014-01-01

    This book is composed of chapters that focus specifically on technological developments by distinguished figures in the history of MMS (Mechanism and Machine Science).  Biographies of well-known scientists are also included to describe their efforts and experiences, and surveys of their work and achievements, and a modern interpretation of their legacy are presented. After the first two volumes, the papers in this third volume again cover a wide range within the field of the History of Mechanical Engineering with specific focus on MMS and will be of interest and motivation to the work (historical or not) of many.

  5. Handbook of asynchronous machines with variable speed

    CERN Document Server

    Razik, Hubert

    2013-01-01

    This handbook deals with the asynchronous machine in its close environment. It was born from a reflection on this electromagnetic converter whose integration in industrial environments takes a wide part. Previously this type of motor operated at fixed speed, from now on it has been integrated more and more in processes at variable speed. For this reason it seemed useful, or necessary, to write a handbook on the various aspects from the motor in itself, via the control and while finishing by the diagnosis aspect. Indeed, an asynchronous motor is used nowadays in industry where variation speed a

  6. 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…

  7. 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)…

  8. Gait phase varies over velocities.

    Science.gov (United States)

    Liu, Yancheng; Lu, Kun; Yan, Songhua; Sun, Ming; Lester, D Kevin; Zhang, Kuan

    2014-02-01

    We sought to characterize the percent (PT) of the phases of a gait cycle (GC) as velocity changes to establish norms for pathological gait characteristics with higher resolution technology. Ninety five healthy subjects (49 males and 46 females with age 34.9 ± 11.8 yrs, body weight 64.0 ± 11.7 kg and BMI 23.5 ± 3.6) were enrolled and walked comfortably on a 10-m walkway at self-selected slower, normal, and faster velocities. Walking was recorded with a high speed camera (250 frames per second) and the eight phases of a GC were determined by examination of individual frames for each subject. The correlation coefficients between the mean PT of the phases of the three velocities gaits and PT defined by previous publications were all greater than 0.99. The correlation coefficient between velocity and PT of gait phases is -0.83 for loading response (LR), -0.75 for mid stance (MSt), and -0.84 for pre-swing (PSw). While the PT of the phases of three velocities from this study are highly correlated with PT described by Dr. Jacquenlin Perry decades ago, actual PT of each phase varied amongst these individuals with the largest coefficient variation of 24.31% for IC with slower velocity. From slower to faster walk, the mean PT of MSt diminished from 35.30% to 25.33%. High resolution recording revealed ambiguity of some gait phase definitions, and these data may benefit GC characterization of normal and pathological gait in clinical practice. The study results indicate that one should consider individual variations and walking velocity when evaluating gaits of subjects using standard gait phase classification.

  9. 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.

  10. 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...

  11. Genome-wide analysis reveals DNA methylation markers that vary with both age and obesity.

    Science.gov (United States)

    Almén, Markus Sällman; Nilsson, Emil K; Jacobsson, Josefin A; Kalnina, Ineta; Klovins, Janis; Fredriksson, Robert; Schiöth, Helgi B

    2014-09-10

    The combination of the obesity epidemic and an aging population presents growing challenges for the healthcare system. Obesity and aging are major risk factors for a diverse number of diseases and it is of importance to understand their interaction and the underlying molecular mechanisms. Herein the authors examined the methylation levels of 27578 CpG sites in 46 samples from adult peripheral blood. The effect of obesity and aging was ascertained with general linear models. More than one hundred probes were correlated to aging, nine of which belonged to the KEGG group map04080. Additionally, 10 CpG sites had diverse methylation profiles in obese and lean individuals, one of which was the telomerase catalytic subunit (TERT). In eight of ten cases the methylation change was reverted between obese and lean individuals. One region proved to be differentially methylated with obesity (LINC00304) independent of age. This study provides evidence that obesity influences age driven epigenetic changes, which provides a molecular link between aging and obesity. This link and the identified markers may prove to be valuable biomarkers for the understanding of the molecular basis of aging, obesity and associated diseases. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

  12. Going Wide, Not Wild: Varying Conceptualizations of Internationalization at a University of Technology in South Africa

    Science.gov (United States)

    Meda, Lawrence; Monnapula-Mapesela, Mabokang

    2016-01-01

    Internationalization has become a buzzword in universities today. As a result of the breadth of the term the concept lends itself to many interpretations. There is a view that South African higher education does not have a customized national framework of internationalization, which raises questions about whether the intended outcomes are…

  13. Machine vision is not computer vision

    Science.gov (United States)

    Batchelor, Bruce G.; Charlier, Jean-Ray

    1998-10-01

    The identity of Machine Vision as an academic and practical subject of study is asserted. In particular, the distinction between Machine Vision on the one hand and Computer Vision, Digital Image Processing, Pattern Recognition and Artificial Intelligence on the other is emphasized. The article demonstrates through four cases studies that the active involvement of a person who is sensitive to the broad aspects of vision system design can avoid disaster and can often achieve a successful machine that would not otherwise have been possible. This article is a transcript of the key- note address presented at the conference. Since the proceedings are prepared and printed before the conference, it is not possible to include a record of the response to this paper made by the delegates during the round-table discussion. It is hoped to collate and disseminate these via the World Wide Web after the event. (A link will be provided at http://bruce.cs.cf.ac.uk/bruce/index.html.).

  14. Effect of tube-electrode inner diameter on electrochemical discharge machining of nickel-based superalloy

    Institute of Scientific and Technical Information of China (English)

    Zhang Yan; Xu Zhengyang; Xing Jun; Zhu Di

    2016-01-01

    Nickel-based superalloys are widely employed in modern aircraft engines because of their excellent material characteristics, particularly in the fabrication of film cooling holes. How-ever, the high machining requirement of a large number of film cooling holes can be extremely chal-lenging. The hybrid machining technique of tube electrode high-speed electrochemical discharge drilling (TEHECDD) has been considered as a promising method for the production of film cooling holes. Compared with any single machining process, this hybrid technique requires the removal of more complex machining by-products, including debris produced in the electrical discharge machin-ing process and hydroxide and bubbles generated in the electrochemical machining process. These by-products significantly affect the machining efficiency and surface quality of the machined prod-ucts. In this study, tube electrodes in different inner diameters are designed and fabricated, and the effects of inner diameter on the machining efficiency and surface quality of TEHECDD are inves-tigated. The results show that larger inner diameters could effectively improve the flushing condi-tion and facilitate the removal of machining by-products. Therefore, higher material removal efficiency, surface quality, and electrode wear rate could be achieved by increasing the inner diam-eter of the tube electrode.

  15. Bearing Condition Recognition and Degradation Assessment under Varying Running Conditions Using NPE and SOM

    Directory of Open Access Journals (Sweden)

    Shaohui Zhang

    2014-01-01

    Full Text Available Manifold learning methods have been widely used in machine condition monitoring and fault diagnosis. However, the results reported in these studies focus on the machine faults under stable loading and rotational speeds, which cannot interpret the practical machine running. Rotating machine is always running under variable speeds and loading, which makes the vibration signal more complicated. To address such concern, the NPE (neighborhood preserving embedding is applied for bearing fault classification. Compared with other algorithms (PCA, LPP, LDA, and ISOP, the NPE performs well in feature extraction. Since the traditional time domain signal denoising is time consuming and memory consuming, we denoise the signal features directly in feature space. Furthermore, NPE and SOM (self-organizing map are combined to assess the bearing degradation performance. Simulation and experiment results validate the effectiveness of the proposed method.

  16. Uncertainty-Aware Estimation of Population Abundance using Machine Learning

    NARCIS (Netherlands)

    Boom, B.J.; Beauxis-Aussalet, E.M.A.L.; Hardman, L.; Fisher, R.B.

    2015-01-01

    Machine Learning is widely used for mining collections, such as images, sounds, or texts, by classifying their elements into categories. Automatic classication based on supervised learning requires groundtruth datasets for modeling the elements to classify, and for testing the quality of the classic

  17. Fluid motion for microgravity simulations in a random positioning machine

    NARCIS (Netherlands)

    Leguy, C.A.D.; Delfos, R.; Pourquie, M.J.M.B.; Poelma, C.; Krooneman, J.; Westerweel, J.; van Loon, J.J.W.A.

    2011-01-01

    To understand the role of gravity in biological systems one may decrease inertial acceleration by going into free-fall conditions such as available on various platforms. These experiments are cumbersome and expensive. Thus, alternative techniques like Random Positioning Machines (RPM) are now widely

  18. 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.

  19. 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.

  20. 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...

  1. 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....

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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…

  9. 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.

  10. 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.

  11. 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…

  12. 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.…

  13. 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).

  14. 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

  15. 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.

  16. 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

  17. Reactive alumina–LaPO4 composite as machinable bioceramics

    Indian Academy of Sciences (India)

    Abhishek Badolia; Ritwik Sarkar; Sumit Kumar Pal

    2015-08-01

    Sintered Al2O3–LaPO4 composites were prepared using commercially available reactive alumina and phase pure lanthanum phosphate (LP), prepared by the reaction synthesis technique. LP content was varied between 10 and 50 wt% and sintering was carried out between 1400 and 1600°C. Sintered composites were characterized for phase analysis, densification, strength, machinability, microstructure and bioactivity (in SBF solution) and biocompatibility (MTT assay protocol) studies. Composite nature was confirmed by phase analysis and LP was found to reduce the densification and strength values but imparted machinability. Again positive bioactivity and biocompatibility character were observed for all the compositions.

  18. 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.

  19. 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...

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. Research progress on ultra-precision machining technologies for soft-brittle crystal materials

    Science.gov (United States)

    Gao, Hang; Wang, Xu; Guo, Dongming; Chen, Yuchuan

    2016-12-01

    Soft-brittle crystal materials are widely used in many fields, especially optics and microelectronics. However, these materials are difficult to machine through traditional machining methods because of their brittle, soft, and anisotropic nature. In this article, the characteristics and machining difficulties of soft-brittle and crystals are presented. Moreover, the latest research progress of novel machining technologies and their applications for softbrittle crystals are introduced by using some representative materials (e.g., potassium dihydrogen phosphate (KDP), cadmium zinc telluride (CZT)) as examples. This article reviews the research progress of soft-brittle crystals processing.

  5. A review of literature on the use of machine learning methods for opinion mining

    Directory of Open Access Journals (Sweden)

    Aytuğ ONAN

    2016-05-01

    Full Text Available Opinion mining is an emerging field which uses methods of natural language processing, text mining and computational linguistics to extract subjective information of opinion holders. Opinion mining can be viewed as a classification problem. Hence, machine learning based methods are widely employed for sentiment classification. Machine learning based methods in opinion mining can be mainly classified as supervised, semi-supervised and unsupervised methods. In this study, main existing literature on the use of machine learning methods for opinion mining has been presented. Besides, the weak and strong characteristics of machine learning methods have been discussed.

  6. 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.

  7. 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...

  8. Microsatellites in varied arenas of research

    Directory of Open Access Journals (Sweden)

    K S Remya

    2010-01-01

    Full Text Available Microsatellites known as simple-sequence repeats (SSRs or short-tandem repeats (STRs, represent specific sequences of DNA consisting of tandemly repeated units of one to six nucleotides. The repetitive nature of microsatellites makes them particularly prone to grow or shrink in length and these changes can have both good and bad consequences for the organisms that possess them. They are responsible for various neurological diseases and hence the same cause is now utilized for the early detection of various diseases, such as, Schizophrenia and Bipolar Disorder, Congenital generalized Hypertrichosis, Asthma, and Bronchial Hyperresponsiveness. These agents are widely used for forensic identification and relatedness testing, and are predominant genetic markers in this area of application. The application of microsatellites is an extending web and covers the varied scenarios of science, such as, conservation biology, plant genetics, and population studies. At present, researches are progressing round the globe to extend the use of these genetic repeaters to unmask the hidden genetic secrets behind the creation of the world.

  9. 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.

  10. NEW TYPE OF VIBRATION STRUCTURE OF VERTICAL DYNAMIC BALANCING MACHINE

    Institute of Scientific and Technical Information of China (English)

    Li Dinggen; Cao Jiguang; Chen Chuanyao; Wang Junwen

    2004-01-01

    A new type of vibration structure of vertical dynamic balancing machine is designed, which is based on the analysis for swing frame of a traditional vertical dynamic balancing machine. The static unbalance and couple unbalance can be separated effectively by using the new machine with the new swing frame. By building the dynamics model, the advantages of the new structure are discussed in detail. The modal and harmonic response are analyzed by using the ANSYS7.0. By comparing the finite element modal analysis with the experimental modal analysis, the natural frequencies and vibration modes are found out. There are many spring boards in the new swing frame. Their stiffness is different and assort with each other. Furthermore, there are three sensors on the measurement points. Therefore, the new dynamic balancing machine can measure the static unbalance and couple unbalance directly, and the influence between them is faint. The new structure has the function of belt-strain compensation to improve the measurement precision. The practical result indicates that the new vertical dynamic balancing machine is suitable for inertial measurement of flying objects, and can overcome the shortcomings of traditional double-plane vertical dynamic balancing machines. The vertical dynamic balancing machine with the new vibration structure can be widely used in the future applications. The modeling and analysis of the new vibration structure provide theoretic instruction and practical experience for designing new type of vertical dynamic balancing machines. Based on the design principles such as stiffness-matching, frequency-adjacence and strain-compensation and so on, various new type of vibration structures can be designed.

  11. Machine Learning for Mapping Groundwater Salinity with Oil Well Log Data

    Science.gov (United States)

    Chang, W. H.; Shimabukuro, D.; Gillespie, J. M.; Stephens, M.

    2016-12-01

    An oil field may have thousands of wells with detailed petrophysical logs, and far fewer direct measurements of groundwater salinity. Can the former be used to extrapolate the latter into a detailed map of groundwater salinity? California Senate Bill 4, with its requirement to identify Underground Sources of Drinking Water, makes this a question worth answering. A well-known obstacle is that the basic petrophysical equations describe ideal scenarios ("clean wet sand") and even these equations contain many parameters that may vary with location and depth. Accounting for other common scenarios such as high-conductivity shaly sands or low-permeability diatomite (both characteristic of California's Central Valley) causes parameters to proliferate to the point where the model is underdetermined by the data. When parameters outnumber data points, however, is when machine learning methods are most advantageous. We present a method for modeling a generic oil field, where groundwater salinity and lithology are depth series parameters, and the constants in petrophysical equations are scalar parameters. The data are well log measurements (resistivity, porosity, spontaneous potential, and gamma ray) and a small number of direct groundwater salinity measurements. Embedded in the model are petrophysical equations that account for shaly sand and diatomite formations. As a proof of concept, we feed in well logs and salinity measurements from the Lost Hills Oil Field in Kern County, California, and show that with proper regularization and validation the model makes reasonable predictions of groundwater salinity despite the large number of parameters. The model is implemented using Tensorflow, which is an open-source software released by Google in November, 2015 that has been rapidly and widely adopted by machine learning researchers. The code will be made available on Github, and we encourage scrutiny and modification by machine learning researchers and hydrogeologists alike.

  12. 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.

  13. Design and Construction of a Spring Stiffness Testing Machine

    Directory of Open Access Journals (Sweden)

    Olugboji Oluwafemi Ayodeji

    2015-04-01

    Full Text Available A spring stiffness testing machine was produced which differentiates a good spring from bad one using hydraulic principle and locally sourced materials were used to produce at relative low cost and high efficiency. It also categories each spring by stiffness into one of several distinct categories based on its performance under test. This is to ensure that in the final assembly process, springs with similar performance characteristics are mated to ensure a better ride, more précised handling and improved overall vehicle or equipment performance. The construction of the machine involves basically the fabrication process which includes such operation as cutting, benching, welding, grinding, drilling, machining, casting and screw fastening. Taken into consideration under test, were types of compression springs with varying spring loading and their different displacement recorded at different pressures to compare their stiffness.

  14. Workspace and Kinematic Analysis of the VERNE machine

    CERN Document Server

    Kanaan, Daniel; Chablat, Damien

    2007-01-01

    This paper describes the workspace and the inverse and direct kinematic analysis of the VERNE machine, a serial/parallel 5-axis machine tool designed by Fatronik for IRCCyN. This machine is composed of a three-degree-of-freedom (DOF) parallel module and a two-DOF serial tilting table. The parallel module consists of a moving platform that is connected to a fixed base by three non-identical legs. This feature involves (i) a simultaneous combination of rotation and translation for the moving platform, which is balanced by the tilting table and (ii) workspace whose shape and volume vary as a function of the tool length. This paper summarizes results obtained in the context of the European projects NEXT ("Next Generation of Productions Systems").

  15. Circular causality and indeterminism in machines for design

    Directory of Open Access Journals (Sweden)

    Thomas Fischer

    2014-12-01

    Full Text Available Presenting a hard-to-predict typography-varying system predicated on Nazi-era cryptography, the Enigma cipher machine, this paper illustrates conditions under which unrepeatable phenomena can arise, even from straight-forward mechanisms. Such conditions arise where systems are observed from outside of boundaries that arise through their observation, and where such systems refer to themselves in a circular fashion. It argues that the Enigma cipher machine is isomorphous with Heinz von Foersters portrayals of non-triviality in his non-trivial machine (NTM, but not with surprising human behaviour, and it demonstrates that the NTM does not account for spontaneity as it is observed in humans in general.

  16. 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.

  17. 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.

  18. Influence of electrical resistivity and machining parameters on electrical discharge machining performance of engineering ceramics.

    Science.gov (United States)

    Ji, Renjie; Liu, Yonghong; Diao, Ruiqiang; Xu, Chenchen; Li, Xiaopeng; Cai, Baoping; Zhang, Yanzhen

    2014-01-01

    Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM) is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical discharge

  19. Influence of electrical resistivity and machining parameters on electrical discharge machining performance of engineering ceramics.

    Directory of Open Access Journals (Sweden)

    Renjie Ji

    Full Text Available Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR, electrode wear ratio (EWR, and surface roughness (SR. The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical

  20. 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...

  1. [The Application of Machine Perfusion on Clinical Liver Transplantation].

    Science.gov (United States)

    Ren, Fenggang; Zhu, Haoyang; Yan, Xiaopeng; Liu, Chang; Zhang, Xiaogang; Lv, Yi

    2015-11-01

    Liver transplantation is the only way to treat end-stage liver disease. In order to overcome the shortage of donor, marginal donors have been used widely, which bring about a series of problems. Machine perfusion can stimulate the circulation in vivo and is beneficial for the protection of liver. It could also improve the graft function and reduce postoperative complications, which makes it a hot spot in recent years. The aim of this study is to summarize the current status and prospects of application of machine perfusion on clinical liver transplantation.

  2. Machine Learning for Vision-Based Motion Analysis

    CERN Document Server

    Wang, Liang; Cheng, Li; Pietikainen, Matti

    2011-01-01

    Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second In

  3. Linguistically motivated statistical machine translation models and algorithms

    CERN Document Server

    Xiong, Deyi

    2015-01-01

    This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

  4. Effect of tube-electrode inner diameter on electrochemical discharge machining of nickel-based superalloy

    Directory of Open Access Journals (Sweden)

    Zhang Yan

    2016-08-01

    Full Text Available Nickel-based superalloys are widely employed in modern aircraft engines because of their excellent material characteristics, particularly in the fabrication of film cooling holes. However, the high machining requirement of a large number of film cooling holes can be extremely challenging. The hybrid machining technique of tube electrode high-speed electrochemical discharge drilling (TEHECDD has been considered as a promising method for the production of film cooling holes. Compared with any single machining process, this hybrid technique requires the removal of more complex machining by-products, including debris produced in the electrical discharge machining process and hydroxide and bubbles generated in the electrochemical machining process. These by-products significantly affect the machining efficiency and surface quality of the machined products. In this study, tube electrodes in different inner diameters are designed and fabricated, and the effects of inner diameter on the machining efficiency and surface quality of TEHECDD are investigated. The results show that larger inner diameters could effectively improve the flushing condition and facilitate the removal of machining by-products. Therefore, higher material removal efficiency, surface quality, and electrode wear rate could be achieved by increasing the inner diameter of the tube electrode.

  5. Energy dissipation in biomolecular machines

    Energy Technology Data Exchange (ETDEWEB)

    Lervik, Anders

    2012-07-01

    The operation of a molecular pump, the calcium pump of sarcoplasmic reticulum is studied using mesoscopic non-equilibrium thermodynamics and molecular dynamics. The mesoscopic non-equilibrium thermodynamic description of the pump is compared to the description obtained in the framework of Hill for kinetic enzyme cycles. By comparing these two descriptions at isothermal conditions, they are found to be equivalent. This supports the validity of the mesoscopic approach. An extension of the mesoscopic non-equilibrium framework to also include a heat flux and the corresponding temperature difference is proposed. This can be used to model phenomena such as non-shivering thermogenesis, a process which lack a theoretical description in the kinetic cycle picture. Further, the heat transfer in the calcium pump is studied using molecular dynamics. This is done in order to obtain phenomenological parameters that can be used for the modeling of thermogenesis. A non-stationary non-equilibrium molecular dynamics approach is developed, which may be used to study heat transfer between a small object and the surrounding solvent. This methodology is applied to the calcium pump solvated in water. It is found that the thermal conductivity of the protein is low (0.2 W K-1 m-1) compared to water (0.6 WK-1 m-1). This means that the protein may sustain a large temperature gradient across its structure. The simulations also show that the protein-water surface is important for the heat transfer. The time scale for vibrational energy relaxation is found to be of order 10/100 ps which strengthens the local equilibrium assumption of mesoscopic non-equilibrium thermodynamics. Mesoscopic non-equilibrium thermodynamics is also applied to calculate the thermodynamic efficiency of the calcium pump embedded in lipid bilayers of varying length and from different tissues. This is done in order to show the applicability of mesoscopic non-equilibrium thermodynamics to interpret experimental data. The

  6. Machine Learning examples on Invenio

    CERN Document Server

    CERN. Geneva

    2017-01-01

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

  7. ENERGY STAR Certified Vending Machines

    Data.gov (United States)

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

  8. Particle accelerator; the Universe machine

    CERN Multimedia

    Yurkewicz, Katie

    2008-01-01

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

  9. Quantum-Enhanced Machine Learning.

    Science.gov (United States)

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

    2016-09-23

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

  10. Quantum-Enhanced Machine Learning

    Science.gov (United States)

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

    2016-09-01

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

  11. Diamond turning machine controller implementation

    Energy Technology Data Exchange (ETDEWEB)

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

    1988-12-01

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

  12. The efficiency of combined machinings

    OpenAIRE

    2012-01-01

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

  13. Machine learning for healthcare technologies

    CERN Document Server

    Clifton, David A

    2016-01-01

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

  14. The Gravitational Asynchronous Machine

    CERN Document Server

    Foschini, Luigi

    2012-01-01

    How relativistic jets are generated is one of the hottest topics of the modern astrophysics. Several theories have been proposed to explain the wide variety of observed phenomena, but none seems to catch the general consensus, although the mechanism proposed for black holes in 1977 by Blandford & Znajek (BZ) deserves some favor. In the following essay, I study some relatively unexplored features in the black hole/jet/disk feedback as derived from the application of the BZ theory.

  15. World wide biomass resources

    NARCIS (Netherlands)

    Faaij, A.P.C.

    2012-01-01

    In a wide variety of scenarios, policy strategies, and studies that address the future world energy demand and the reduction of greenhouse gas emissions, biomass is considered to play a major role as renewable energy carrier. Over the past decades, the modern use of biomass has increased rapidly in

  16. Health Care Wide Hazards

    Science.gov (United States)

    ... Other Hazards (Lack of) PPE Slips/Trips/Falls Stress Tuberculosis Universal Precautions Workplace Violence Use of Medical Lasers Health Effects Use ... Needlesticks Noise Mercury Inappropriate PPE Slips/Trips/Falls ... of Universal Precautions Workplace Violence For more information, see Other Healthcare Wide ...

  17. World wide biomass resources

    NARCIS (Netherlands)

    Faaij, A.P.C.

    2012-01-01

    In a wide variety of scenarios, policy strategies, and studies that address the future world energy demand and the reduction of greenhouse gas emissions, biomass is considered to play a major role as renewable energy carrier. Over the past decades, the modern use of biomass has increased rapidly in

  18. World wide biomass resources

    NARCIS (Netherlands)

    Faaij, A.P.C.

    2012-01-01

    In a wide variety of scenarios, policy strategies, and studies that address the future world energy demand and the reduction of greenhouse gas emissions, biomass is considered to play a major role as renewable energy carrier. Over the past decades, the modern use of biomass has increased

  19. A Diagnostic System for Speed-Varying Motor Rotary Faults

    Directory of Open Access Journals (Sweden)

    Chwan-Lu Tseng

    2014-01-01

    Full Text Available This study proposed an intelligent rotary fault diagnostic system for motors. A sensorless rotational speed detection method and an improved dynamic structural neural network are used. Moreover, to increase the convergence speed of training, a terminal attractor method and a hybrid discriminant analysis are also adopted. The proposed method can be employed to detect the rotary frequencies of motors with varying speeds and can enhance the discrimination of motor faults. To conduct the experiments, this study used wireless sensor nodes to transmit vibration data and employed MATLAB to write codes for functional modules, including the signal processing, sensorless rotational speed estimation, neural network, and stochastic process control chart. Additionally, Visual Basic software was used to create an integrated human-machine interface. The experimental results regarding the test of equipment faults indicated that the proposed novel diagnostic system can effectively estimate rotational speeds and provide superior ability of motor fault discrimination with fast training convergence.

  20. 4th Machining Innovations Conference

    CERN Document Server

    2014-01-01

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

  1. Function Concepts for Machine Parts

    DEFF Research Database (Denmark)

    Mortensen, Niels Henrik

    1999-01-01

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

  2. Constructing a modern city machine

    DEFF Research Database (Denmark)

    Lindegaard, Hanne; Jørgensen, Ulrik

    1998-01-01

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

  3. Biosleeve Human-Machine Interface

    Science.gov (United States)

    Assad, Christopher (Inventor)

    2016-01-01

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

  4. Classification of Regional Ionospheric Disturbances Based on Support Vector Machines

    Science.gov (United States)

    Begüm Terzi, Merve; Arikan, Feza; Arikan, Orhan; Karatay, Secil

    2016-07-01

    Ionosphere is an anisotropic, inhomogeneous, time varying and spatio-temporally dispersive medium whose parameters can be estimated almost always by using indirect measurements. Geomagnetic, gravitational, solar or seismic activities cause variations of ionosphere at various spatial and temporal scales. This complex spatio-temporal variability is challenging to be identified due to extensive scales in period, duration, amplitude and frequency of disturbances. Since geomagnetic and solar indices such as Disturbance storm time (Dst), F10.7 solar flux, Sun Spot Number (SSN), Auroral Electrojet (AE), Kp and W-index provide information about variability on a global scale, identification and classification of regional disturbances poses a challenge. The main aim of this study is to classify the regional effects of global geomagnetic storms and classify them according to their risk levels. For this purpose, Total Electron Content (TEC) estimated from GPS receivers, which is one of the major parameters of ionosphere, will be used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. In this work, for the automated classification of the regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. SVM is a supervised learning model used for classification with associated learning algorithm that analyze the data and recognize patterns. In addition to performing linear classification, SVM can efficiently perform nonlinear classification by embedding data into higher dimensional feature spaces. Performance of the developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from the GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing the developed classification

  5. Photometric Supernova Classification with Machine Learning

    Science.gov (United States)

    Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.

    2016-08-01

    Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

  6. Early succession of bacterial biofilms in paper machines.

    Science.gov (United States)

    Tiirola, Marja; Lahtinen, Tomi; Vuento, Matti; Oker-Blom, Christian

    2009-07-01

    Formation of biofilms causes severe problems in paper machines, and hence financial costs. It would be preferable to prevent attachment of the primary-colonizing bacteria than to control the growth of secondary communities, which are sheltered by exopolysaccharide slime layers. We have therefore investigated the early succession of paper-machine biofilms by incubating stainless-steel test coupons in the process water-flow lines in two paper machines operating in slightly alkaline conditions in temperatures (45 and 49 degrees C) supporting thermophilic microbes. Microbial succession was profiled using length heterogeneity analysis of PCR-amplified 16S rRNA genes (LH-PCR) and linking the sequence data of the created 16S rRNA gene libraries to the dominant LH-PCR peaks. Although the bacterial fingerprints obtained from the attached surface communities varied slightly in different samples, the biomarker signals of the dominating primary-colonizing bacterial groups remained high over time in each paper machine. Most of the 16S rRNA gene copies in the early biofilms were assigned to the genera Rhodobacter, Tepidimonas, and Cloacibacterium. The dominance of these sequence types decreased in the developing biofilms. Finally, as phylogenetically identical primary-colonizers were detected in the two different paper mills, the machines evidently had similar environmental conditions for bacterial growth and potentially a common source of contamination.

  7. Analysis of space harmonic selectivity of period-varying folded waveguide

    Institute of Scientific and Technical Information of China (English)

    Xu Ao; Wang Wen-Xiang; Wei Yan-Yu; Gong Yu-Bin

    2009-01-01

    A period-varying folded waveguide is formed by varying the period of a folded waveguide. It has the advantages of the space harmonic selectivity and the wide bandwidth. However, the regularities of the variety of these period-varying folded waveguides are unavailable from the published papers. In order to solve this problem, the principle of the space harmonic selectivity of a period-varying folded waveguide is analysed, and the conditions to select the space harmonic for this slow wave system are obtained. In addition, the space harmonic selectivities for a linear period-varying folded waveguide and a hyperbolic sine-varying period folded waveguide are also analysed as examples.

  8. The Complexity of Abstract Machines

    Directory of Open Access Journals (Sweden)

    Beniamino Accattoli

    2017-01-01

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

  9. Dynamic behavior analysis for a six axis industrial machining robot

    CERN Document Server

    Bisu, Claudiu-Florinel; Gérard, Alain; K'Nevez, Jean-Yves

    2012-01-01

    The six axis robots are widely used in automotive industry for their good repeatability (as defined in the ISO92983) (painting, welding, mastic deposition, handling etc.). In the aerospace industry, robot starts to be used for complex applications such as drilling, riveting, fiber placement, NDT, etc. Given the positioning performance of serial robots, precision applications require usually external measurement device with complexes calibration procedure in order to reach the precision needed. New applications in the machining field of composite material (aerospace, naval, or wind turbine for example) intend to use off line programming of serial robot without the use of calibration or external measurement device. For those applications, the position, orientation and path trajectory precision of the tool center point of the robot are needed to generate the machining operation. This article presents the different conditions that currently limit the development of robots in robotic machining applications. We ana...

  10. Review on the progress of ultra-precision machining technologies

    Science.gov (United States)

    Yuan, Julong; Lyu, Binghai; Hang, Wei; Deng, Qianfa

    2017-06-01

    Ultra-precision machining technologies are the essential methods, to obtain the highest form accuracy and surface quality. As more research findings are published, such technologies now involve complicated systems engineering and been widely used in the production of components in various aerospace, national defense, optics, mechanics, electronics, and other high-tech applications. The conception, applications and history of ultra-precision machining are introduced in this article, and the developments of ultra-precision machining technologies, especially ultra-precision grinding, ultra-precision cutting and polishing are also reviewed. The current state and problems of this field in China are analyzed. Finally, the development trends of this field and the coping strategies employed in China to keep up with the trends are discussed.

  11. Gambling with stimulus payments: feeding gaming machines with federal dollars.

    Science.gov (United States)

    Lye, Jenny; Hirschberg, Joe

    2014-09-01

    In late 2008 and early 2009 the Australian Federal Government introduced a series of economic stimulus packages designed to maintain consumer spending in the early days of the Great Recession. When these packages were initiated the media suggested that the wide-spread availability of electronic gaming machines (EGMs, e.g. slot machines, poker machines, video lottery terminals) in Australia would result in stimulating the EGMs. Using state level monthly data we estimate that the stimulus packages led to an increase of 26 % in EGM revenues. This also resulted in over $60 million in additional tax revenue for State Governments. We also estimate a short-run aggregate income demand elasticity for EGMs to be approximately 2.

  12. Machine translation with minimal reliance on parallel resources

    CERN Document Server

    Tambouratzis, George; Sofianopoulos, Sokratis

    2017-01-01

    This book provides a unified view on a new methodology for Machine Translation (MT). This methodology extracts information from widely available resources (extensive monolingual corpora) while only assuming the existence of a very limited parallel corpus, thus having a unique starting point to Statistical Machine Translation (SMT). In this book, a detailed presentation of the methodology principles and system architecture is followed by a series of experiments, where the proposed system is compared to other MT systems using a set of established metrics including BLEU, NIST, Meteor and TER. Additionally, a free-to-use code is available, that allows the creation of new MT systems. The volume is addressed to both language professionals and researchers. Prerequisites for the readers are very limited and include a basic understanding of the machine translation as well as of the basic tools of natural language processing.

  13. Machine function based control code algebras

    NARCIS (Netherlands)

    Bergstra, J.A.

    2008-01-01

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

  14. Machining dynamics fundamentals, applications and practices

    CERN Document Server

    Cheng, Kai

    2008-01-01

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

  15. Singer CNC sewing and embroidery machine

    Directory of Open Access Journals (Sweden)

    Lokodi Zsolt

    2011-12-01

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

  16. Functional Piezocrystal Characterisation under Varying Conditions

    Directory of Open Access Journals (Sweden)

    Xiaochun Liao

    2015-12-01

    Full Text Available Piezocrystals, especially the relaxor-based ferroelectric crystals, have been subject to intense investigation and development within the past three decades, motivated by the performance advantages offered by their ultrahigh piezoelectric coefficients and higher electromechanical coupling coefficients than piezoceramics. Structural anisotropy of piezocrystals also provides opportunities for devices to operate in novel vibration modes, such as the d36 face shear mode, with domain engineering and special crystal cuts. These piezocrystal characteristics contribute to their potential usage in a wide range of low- and high-power ultrasound applications. In such applications, conventional piezoelectric materials are presently subject to varying mechanical stress/pressure, temperature and electric field conditions. However, as observed previously, piezocrystal properties are significantly affected by a single such condition or a combination of conditions. Laboratory characterisation of the piezocrystal properties under these conditions is therefore essential to fully understand these materials and to allow electroacoustic transducer design in realistic scenarios. This will help to establish the extent to which these high performance piezocrystals can replace conventional piezoceramics in demanding applications. However, such characterisation requires specific experimental arrangements, examples of which are reported here, along with relevant results. The measurements include high frequency-resolution impedance spectroscopy with the piezocrystal material under mechanical stress 0–60 MPa, temperature 20–200 °C, high electric AC drive and DC bias. A laser Doppler vibrometer and infrared thermal camera are also integrated into the measurement system for vibration mode shape scanning and thermal conditioning with high AC drive. Three generations of piezocrystal have been tested: (I binary, PMN-PT; (II ternary, PIN-PMN-PT; and (III doped ternary, Mn

  17. Electromagnetic interference of implantable cardiac devices from a shoulder massage machine.

    Science.gov (United States)

    Yoshida, Saeko; Fujiwara, Kousaku; Kohira, Satoshi; Hirose, Minoru

    2014-09-01

    Shoulder massage machines have two pads that are driven by solenoid coils to perform a per cussive massage on the shoulders. There have been concerns that such machines might create electromagnetic interference (EMI) in implantable cardiac devices because of the time-varying magnetic fields produced by the alternating current in the solenoid coils. The objective of this study was to investigate the potential EMI from one such shoulder massage machine on implantable cardiac devices. We measured the distribution profile of the magnetic field intensity around the massage machine. Furthermore, we performed an inhibition test and an asynchronous test on an implantable cardiac pacemaker using the standardized Irnich human body model. We examined the events on an implantable cardioverter-defibrillator (ICD) using a pacemaker programmer while the massage machine was in operation. The magnetic field distribution profile exhibited a peak intensity of 212 (A/m) in one of the solenoid coils. The maximal interference distance between the massage machine and the implantable cardiac pacemaker was 28 cm. Ventricular fibrillation was induced when the massage machine was brought near the electrode of the ICD and touched the Irnich human body model. It is necessary to provide a "don't use" warning on the box or the exterior of the massage machines or in the user manuals and to caution patients with implanted pacemakers about the dangers and appropriate usage of massage machines.

  18. How state taxes and policies targeting soda consumption modify the association between school vending machines and student dietary behaviors: a cross-sectional analysis.

    Directory of Open Access Journals (Sweden)

    Daniel R Taber

    Full Text Available Sodas are widely sold in vending machines and other school venues in the United States, particularly in high school. Research suggests that policy changes have reduced soda access, but the impact of reduced access on consumption is unclear. This study was designed to identify student, environmental, or policy characteristics that modify the associations between school vending machines and student dietary behaviors.Data on school vending machine access and student diet were obtained as part of the National Youth Physical Activity and Nutrition Study (NYPANS and linked to state-level data on soda taxes, restaurant taxes, and state laws governing the sale of soda in schools. Regression models were used to: 1 estimate associations between vending machine access and soda consumption, fast food consumption, and lunch source, and 2 determine if associations were modified by state soda taxes, restaurant taxes, laws banning in-school soda sales, or student characteristics (race/ethnicity, sex, home food access, weight loss behaviors..Contrary to the hypothesis, students tended to consume 0.53 fewer servings of soda/week (95% CI: -1.17, 0.11 and consume fast food on 0.24 fewer days/week (95% CI: -0.44, -0.05 if they had in-school access to vending machines. They were also less likely to consume soda daily (23.9% vs. 27.9%, average difference  =  -4.02, 95% CI: -7.28, -0.76. However, these inverse associations were observed primarily among states with lower soda and restaurant tax rates (relative to general food tax rates and states that did not ban in-school soda sales. Associations did not vary by any student characteristics except for weight loss behaviors.Isolated changes to the school food environment may have unintended consequences unless policymakers incorporate other initiatives designed to discourage overall soda consumption.

  19. Studies of Machine Learning Photometric Classification of Supernovae

    Science.gov (United States)

    Macaluso, Joseph Nicholas; Cunningham, John; Kuhlmann, Stephen; Gupta, Ravi; Kovacs, Eve

    2017-01-01

    We studied the use of machine learning for the photometuric classification of Type Ia (SNIa) and core collapse (SNcc) supernovae. We used a combination of simulated data for the Dark Energy survey (DES) and real data from SDSS and chose our metrics to be the sample purity and the efficiency of identifying SNIa supernovae. Our focus was to quantify the effects of varying the training and parameters for random-forest decision-tree algorithms.

  20. Contribution to the design and the control of synchronous double excitation machines: hybrid vehicle application; Contribution a la conception et a la commande des machines synchrones a double excitation: application au vehicule hybride

    Energy Technology Data Exchange (ETDEWEB)

    Amara, Y.

    2001-12-01

    Double excitation machines are synchronous machines where two excitation circuits coexist: one with permanent magnets and the other with windings. This study shows that double excitation allows to combine the advantages of synchronous machines with winded inductor with those of permanent magnet machines. This concept allows a better dimensioning of the converter-machine set and a better energy management. In order to allow the operation of permanent magnet machines over a wide range of speeds, it is necessary to have a magnetic reaction of the induced circuit of the same order than the excitation flux. On the other hand, the power factor is weaker and the power supply converter is over-dimensioned. The double excitation allows the permanent magnet machines to work over a large speed range with a better power factor, even when the magnetic reaction of the induced circuit is relatively weak with respect to the excitation flux. (J.S.)

  1. Social contagions on time-varying community networks

    CERN Document Server

    Liu, Mian-Xin; Liu, Ying; Tang, Ming; Cai, Shi-Min; Zhang, Hai-Feng

    2016-01-01

    Time-varying community structures widely exist in various real-world networks. However, the spreading dynamics on this kind of network has not been fully studied. To this end, we systematically study the effects of time-varying community structures on social contagions. We first propose a non-Markovian social contagion model on time-varying community networks based on the activity driven network model, in which an individual adopts a behavior if and only if the accumulated behavioral information it has ever received reaches a threshold. Then, we develop a mean-field theory to describe the proposed model. From theoretical analyses and numerical simulations, we find that behavior adoption in the social contagions exhibits a hierarchical feature, i.e., the behavior first quickly spreads in one of the communities, and then outbreaks in the other. Moreover, under different behavioral information transmission rates, the final behavior adoption proportion in the whole network versus the community strength shows one ...

  2. Design of 2D Time-Varying Vector Fields

    KAUST Repository

    Chen, Guoning

    2012-10-01

    Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

  3. Machine Learning Interface for Medical Image Analysis.

    Science.gov (United States)

    Zhang, Yi C; Kagen, Alexander C

    2016-10-11

    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  4. Compiling scheme using abstract state machines

    OpenAIRE

    2003-01-01

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

  5. Optimization of Support Vector Machine (SVM) for Object Classification

    Science.gov (United States)

    Scholten, Matthew; Dhingra, Neil; Lu, Thomas T.; Chao, Tien-Hsin

    2012-01-01

    The Support Vector Machine (SVM) is a powerful algorithm, useful in classifying data into species. The SVMs implemented in this research were used as classifiers for the final stage in a Multistage Automatic Target Recognition (ATR) system. A single kernel SVM known as SVMlight, and a modified version known as a SVM with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SVM as a method for classification. From trial to trial, SVM produces consistent results.

  6. Chaotic behaviour of Zeeman machines at introductory course of mechanics

    Science.gov (United States)

    Nagy, Péter; Tasnádi, Péter

    2016-05-01

    Investigation of chaotic motions and cooperative systems offers a magnificent opportunity to involve modern physics into the basic course of mechanics taught to engineering students. In the present paper it will be demonstrated that Zeeman Machine can be a versatile and motivating tool for students to get introductory knowledge about chaotic motion via interactive simulations. It works in a relatively simple way and its properties can be understood very easily. Since the machine can be built easily and the simulation of its movement is also simple the experimental investigation and the theoretical description can be connected intuitively. Although Zeeman Machine is known mainly for its quasi-static and catastrophic behaviour, its dynamic properties are also of interest with its typical chaotic features. By means of a periodically driven Zeeman Machine a wide range of chaotic properties of the simple systems can be demonstrated such as bifurcation diagrams, chaotic attractors, transient chaos and so on. The main goal of this paper is the presentation of an interactive learning material for teaching the basic features of the chaotic systems through the investigation of the Zeeman Machine.

  7. Data Triage of Astronomical Transients: A Machine Learning Approach

    Science.gov (United States)

    Rebbapragada, U.

    This talk presents real-time machine learning systems for triage of big data streams generated by photometric and image-differencing pipelines. Our first system is a transient event detection system in development for the Palomar Transient Factory (PTF), a fully-automated synoptic sky survey that has demonstrated real-time discovery of optical transient events. The system is tasked with discriminating between real astronomical objects and bogus objects, which are usually artifacts of the image differencing pipeline. We performed a machine learning forensics investigation on PTF’s initial system that led to training data improvements that decreased both false positive and negative rates. The second machine learning system is a real-time classification engine of transients and variables in development for the Australian Square Kilometre Array Pathfinder (ASKAP), an upcoming wide-field radio survey with unprecedented ability to investigate the radio transient sky. The goal of our system is to classify light curves into known classes with as few observations as possible in order to trigger follow-up on costlier assets. We discuss the violation of standard machine learning assumptions incurred by this task, and propose the use of ensemble and hierarchical machine learning classifiers that make predictions most robustly.

  8. Technique of performing construction works by machines with hybrid: manual and remote control

    Directory of Open Access Journals (Sweden)

    Sevryugina Nadezhda

    2017-01-01

    Full Text Available The article discusses issues dealing with efficiency of construction work mechanization. It offers a mathematical model for assessment of mutual influence between the members of the ‘construction site-machine-operator’ system triad, that can give a quantitative assessment of how the efficiency of a technological task varies with more comprehensive use of operational capacities of the machine, while lower effect that limiting parameters of production environment and technical condition of the machine have on the operator. The article contains a constructive remote control solution for upgrade of the base machine. It describes the conditions for using the machines with hybrid: manual and remote control at construction sites. There is also an imitation model of operator’s scanning pattern and data experimental research that prove the efficiency of remotely controlled technological operations. The article proves that lower psychological load on the operator and better comfort contribute to positive economic effect and higher quality of the construction process.

  9. Density Based Support Vector Machines for Classification

    Directory of Open Access Journals (Sweden)

    Zahra Nazari

    2015-04-01

    Full Text Available Support Vector Machines (SVM is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification of training points. However, sometimes there are some less meaningful samples amongst training points, which are corrupted by noises or misplaced in wrong side, called outliers. These outliers are affecting on margin and classification performance, and machine should better to discard them. SVM as a popular and widely used classification algorithm is very sensitive to these outliers and lacks the ability to discard them. Many research results prove this sensitivity which is a weak point for SVM. Different approaches are proposed to reduce the effect of outliers but no method is suitable for all types of data sets. In this paper, the new method of Density Based SVM (DBSVM is introduced. Population Density is the basic concept which is used in this method for both linear and non-linear SVM to detect outliers. Experiments on artificial data sets, real high-dimensional benchmark data sets of Liver disorder and Heart disease, and data sets of new and fatigued banknotes’ acoustic signals can prove the efficiency of this method on noisy data classification and the better generalization that it can provide compared to the standard SVM.

  10. Finding New Perovskite Halides via Machine learning

    Directory of Open Access Journals (Sweden)

    Ghanshyam ePilania

    2016-04-01

    Full Text Available Advanced materials with improved properties have the potential to fuel future technological advancements. However, identification and discovery of these optimal materials for a specific application is a non-trivial task, because of the vastness of the chemical search space with enormous compositional and configurational degrees of freedom. Materials informatics provides an efficient approach towards rational design of new materials, via learning from known data to make decisions on new and previously unexplored compounds in an accelerated manner. Here, we demonstrate the power and utility of such statistical learning (or machine learning via building a support vector machine (SVM based classifier that uses elemental features (or descriptors to predict the formability of a given ABX3 halide composition (where A and B represent monovalent and divalent cations, respectively, and X is F, Cl, Br or I anion in the perovskite crystal structure. The classification model is built by learning from a dataset of 181 experimentally known ABX3 compounds. After exploring a wide range of features, we identify ionic radii, tolerance factor and octahedral factor to be the most important factors for the classification, suggesting that steric and geometric packing effects govern the stability of these halides. The trained and validated models then predict, with a high degree of confidence, several novel ABX3 compositions with perovskite crystal structure.

  11. A Fast Reduced Kernel Extreme Learning Machine.

    Science.gov (United States)

    Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

    2016-04-01

    In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred.

  12. Finding New Perovskite Halides via Machine learning

    Science.gov (United States)

    Pilania, Ghanshyam; Balachandran, Prasanna V.; Kim, Chiho; Lookman, Turab

    2016-04-01

    Advanced materials with improved properties have the potential to fuel future technological advancements. However, identification and discovery of these optimal materials for a specific application is a non-trivial task, because of the vastness of the chemical search space with enormous compositional and configurational degrees of freedom. Materials informatics provides an efficient approach towards rational design of new materials, via learning from known data to make decisions on new and previously unexplored compounds in an accelerated manner. Here, we demonstrate the power and utility of such statistical learning (or machine learning) via building a support vector machine (SVM) based classifier that uses elemental features (or descriptors) to predict the formability of a given ABX3 halide composition (where A and B represent monovalent and divalent cations, respectively, and X is F, Cl, Br or I anion) in the perovskite crystal structure. The classification model is built by learning from a dataset of 181 experimentally known ABX3 compounds. After exploring a wide range of features, we identify ionic radii, tolerance factor and octahedral factor to be the most important factors for the classification, suggesting that steric and geometric packing effects govern the stability of these halides. The trained and validated models then predict, with a high degree of confidence, several novel ABX3 compositions with perovskite crystal structure.

  13. Machine Learning and Data Mining Methods in Diabetes Research.

    Science.gov (United States)

    Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

    2017-01-01

    The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

  14. GPU Generation of Large Varied Animated Crowds

    OpenAIRE

    Isaac Rudomin; Benjamín Hernández; Oriam de Gyves; Leonel Toledo; Ivan Rivalcoba; Sergio Ruiz

    2013-01-01

    ..We discuss several steps in the process of simulating and visualizing large and varied crowds in real time for consumer-level computers and graphic cards (GPUs). Animating varied crowds using a diversity of models and animations (assets) is complex and costly. One has to use models that are expensive if bought, take a long time to model, and consume too much memory and computing resources. We discuss methods for simulating, generating, animating and rendering crowds of varied aspect and a d...

  15. A new varied-time photonic crystals

    OpenAIRE

    Wu, Xiang-Yao; Ma, Ji; Liu, Xiao-Jing; Liang, Yu; Li, Hong; Chen, Wan-Jin; Yuan, Hong-chun; Li, Heng-Mei

    2015-01-01

    In this paper, we have firstly proposed a new one-dimensional varied-time photonic crystals, i.e., the refractive indices of media $A$ and $B$ are the time functions. We consider the varied-time photonic crystals of refractive indices period variation and calculate the transmissivity and electronic field distribution with and without defect layer, which are different from the conventional photonic crystals, which transmissivity and electronic field distribution are static, but the varied-time...

  16. Inflationary Phase with Time Varying Fundamental Constants

    CERN Document Server

    Berman, M S; Berman, Marcelo S.; Trevisan, Luis A.

    2002-01-01

    Following Barrow, and Barrow and collaborators, we find a cosmological JBD model, with varying speed of light and varying fine structure constant, where the deceleration parameter is -1,causing acceleration of the Universe.Indeed, we have an exponential inflationary phase. Plancks time, energy, length,etc.,might have had different numerical values in the past, than those available in the litterature, due to the varying values for speed of light, and gravitational constant.

  17. A new varied-time photonic crystals

    OpenAIRE

    2015-01-01

    In this paper, we have firstly proposed a new one-dimensional varied-time photonic crystals, i.e., the refractive indices of media $A$ and $B$ are the time functions. We consider the varied-time photonic crystals of refractive indices period variation and calculate the transmissivity and electronic field distribution with and without defect layer, which are different from the conventional photonic crystals, which transmissivity and electronic field distribution are static, but the varied-time...

  18. Game-powered machine learning.

    Science.gov (United States)

    Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

    2012-04-24

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

  19. Mechanical design of walking machines.

    Science.gov (United States)

    Arikawa, Keisuke; Hirose, Shigeo

    2007-01-15

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

  20. Reusable State Machine Code Generator

    Science.gov (United States)

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

    2010-12-01

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

  1. Machine Learning in Parliament Elections

    Directory of Open Access Journals (Sweden)

    Ahmad Esfandiari

    2012-09-01

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

  2. Viscoelastic machine elements elastomers and lubricants in machine systems

    CERN Document Server

    MOORE, D F

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Soheil Rostami

    2016-01-01

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

  4. Jihadism, Narrow and Wide

    DEFF Research Database (Denmark)

    Sedgwick, Mark

    2015-01-01

    The term “jihadism” is popular, but difficult. It has narrow senses, which are generally valuable, and wide senses, which may be misleading. This article looks at the derivation and use of “jihadism” and of related terms, at definitions provided by a number of leading scholars, and at media usage....... It distinguishes two main groups of scholarly definitions, some careful and narrow, and some appearing to match loose media usage. However, it shows that even these scholarly definitions actually make important distinctions between jihadism and associated political and theological ideology. The article closes...

  5. THE INFLUENCE SEWING MACHINE ON FOOTWEAR MOCCASIN ECONOMIC INDICATORS AI ASSEMBLY OPERATIONS

    Directory of Open Access Journals (Sweden)

    MALCOCI Marina

    2014-05-01

    Full Text Available With the evolution of time changes, grows and improves, construction, form, rationality and argumentation usefulness of various types of footwear, namely machines. In the present paper analyzes a number of sewing machines, bound for achieving moccasin shoes. With sewing machines can perform a wide variety of stitches, they create an aesthetically pleasing, but all at once enable product diversification with minimum expenses. Sewing machines moccasins are distinguished by technological parameters, number of stitches, design and affordability. Sewing operation carried out in these machines is carried out within 72 seconds to manual operation - 22 minutes. A flow diagram mechanical requires a reduced number of workers (e.g., 3 workers, to a manual flow diagram - 38 workers. Labour productivity in the use of sewing machines increase by 10 times, and operation cost decreases from 3,7 to 5,7 lei. Regardless of the sewing moccasins construction company helps to increase productivity, quality completion of the operation, ie products, reducing the time required to manufacture the products, shortening manufacturing cycle. Among the cars analyzed, the most recommended sewing machine as OS 7700 P Global company because it represents the best technical features. Sewing machines for manufacturing footwear moccasin were implemented in Moldova in 2010, at the "Cristina Mold Rom Simpex" in Chisinau. Because, company management understood beneficial role of sewing moccasins on quality operation, but also on other economic indicators. Currently the majority of footwear enterprises in Moldova sewing moccasins are done manually. One problem is the high price of sewing machines moccasins.

  6. Design of wide field and high resolution video lens

    Science.gov (United States)

    Xiao, Ze-xin; Zhan, Binzhou; Han, Haimei

    2009-11-01

    Online detecting is increasingly used in industrial process for the requirement of product quality improving. It is a trend that the "machine detecting" with "machine version + computer intelligence" as new method replaces traditional manual "eye observation". The essential of "machine detecting" is that image of object being collected with high resolution video lens on sensor panel of photoelectric (CCD ,CMOS) and detecting result being automatically gained by computer after the image saved and processed. "Machine detecting" is developing rapidly with the universal reception by enterprises because of its fine accurateness, high efficiency and the real time. Video lens is one of the important components of machine version system. Requirements of wide field and high resolution enlarged the complexity of video lens design. In this paper a design case used in visible light with field diameter Φ32mm, β=-0.25× and NA'=0.15. We give design parameters of the video lens which obtained with theoretically calculating and Oslo software optimization: MTF>0.3 in full field and 215lp/mm, distortion <0.05%.This lens has an excellent optic performance to match with 1.3 million pixels 1/2"CCD, and a high performance price ratio for being consist of only 7 single lens in the way of 5 units.

  7. Experimental analysis of the performance of machine learning algorithms in the classification of navigation accident records

    Directory of Open Access Journals (Sweden)

    REIS, M V. S. de A.

    2017-06-01

    Full Text Available This paper aims to evaluate the use of machine learning techniques in a database of marine accidents. We analyzed and evaluated the main causes and types of marine accidents in the Northern Fluminense region. For this, machine learning techniques were used. The study showed that the modeling can be done in a satisfactory manner using different configurations of classification algorithms, varying the activation functions and training parameters. The SMO (Sequential Minimal Optimization algorithm showed the best performance result.

  8. Analysis of Unbalanced Magnetic Pull in Wound Rotor Induction Machines using Finite Element Analysis – Transient, Motoring and Generating Modes

    DEFF Research Database (Denmark)

    Dorrell, David G.; Hermann, Alexander Niels August; Jensen, Bogi Bech

    2013-01-01

    There has been much literature on unbalanced magnetic pull in various types of electrical machine. This can lead to bearing wear and additional vibrations in the machine. In this paper a wound rotor induction is studied. Finite element analysis studies are conducted when the rotor has 10 % rotor...... eccentricity. The operating conditions are varied so that transient, motoring and doubly-fed induction generator modes are studied. This allows greater understanding of the radial forces involved. Wound rotor induction machines exhibit higher unbalanced magnetic pull than cage induction machines so...

  9. Machine Selection in A Dairy Product Company with Entropy and SAW Method Integration

    Directory of Open Access Journals (Sweden)

    Aşkın Özdağoğlu

    2017-07-01

    Full Text Available Machine selection is an important and difficult process for the firms, and its results may generate more problems than anticipated. In order to find the best alternative, managers should define the requirements of the factory and determine the necessary criteria. On the other hand, the decision making criteria in order to choose the right equipment may vary according to the type of the manufacturing facility, market requirements, and consumer assigned criteria. This study aims to find the best machine alternative  among  the three machine offerings according to twelve evaluation criteria by integrating entropy method with SAW method.

  10. Build your own time machine

    CERN Document Server

    Clegg, Brian

    2012-01-01

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

  11. Emerging Paradigms in Machine Learning

    CERN Document Server

    Jain, Lakhmi; Howlett, Robert

    2013-01-01

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

  12. INVESTIGATION OF MAGNESIUM ALLOYS MACHINABILITY

    Directory of Open Access Journals (Sweden)

    Berat Barıs BULDUM

    2013-01-01

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

  13. Higgs Machine Learning Challenge 2014

    CERN Multimedia

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

    2014-01-01

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

  14. Single Bacteria as Turing Machines

    Science.gov (United States)

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

    2014-03-01

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

  15. Plug into 'the modernizing machine'!

    DEFF Research Database (Denmark)

    Krejsler, John B.

    2013-01-01

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

  16. Machine learning methods in chemoinformatics

    Science.gov (United States)

    Mitchell, John B O

    2014-01-01

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

  17. Vector grammars and PN machines

    Institute of Scientific and Technical Information of China (English)

    蒋昌俊

    1996-01-01

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

  18. Machine learning phases of matter

    Science.gov (United States)

    Carrasquilla, Juan; Melko, Roger G.

    2017-02-01

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

  19. Alpha Channeling in Mirror Machines

    Energy Technology Data Exchange (ETDEWEB)

    Fisch N.J.

    2005-10-19

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

  20. Traditional machining processes research advances

    CERN Document Server

    2015-01-01

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

  1. 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.

  2. Aerosols generated during beryllium machining.

    Science.gov (United States)

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

    2000-01-01

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

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

    CERN Document Server

    International Electrotechnical Commission. Geneva

    1985-01-01

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

  4. Time varying effects in survival analysis

    DEFF Research Database (Denmark)

    Scheike, Thomas H.

    2002-01-01

    additive risk model; counting process; proportional hazards model; semi-parametric models; survival data; time-varying effects; nonparametric testing......additive risk model; counting process; proportional hazards model; semi-parametric models; survival data; time-varying effects; nonparametric testing...

  5. Fractal analysis of time varying data

    Science.gov (United States)

    Vo-Dinh, Tuan; Sadana, Ajit

    2002-01-01

    Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.

  6. Controls and Machine Protection Systems

    CERN Document Server

    Carrone, E

    2016-01-01

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

  7. Magnet management in electric machines

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-03-21

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

  8. Cooling system for rotating machine

    Science.gov (United States)

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

    2011-08-09

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

  9. Magnet management in electric machines

    Science.gov (United States)

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

    2017-03-21

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

  10. Towards green lubrication in machining

    CERN Document Server

    Liew Yun Hsien, Willey

    2014-01-01

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

  11. Energy harvesting using AC machines with high effective pole count

    Science.gov (United States)

    Geiger, Richard Theodore

    In this thesis, ways to improve the power conversion of rotating generators at low rotor speeds in energy harvesting applications were investigated. One method is to increase the pole count, which increases the generator back-emf without also increasing the I2R losses, thereby increasing both torque density and conversion efficiency. One machine topology that has a high effective pole count is a hybrid "stepper" machine. However, the large self inductance of these machines decreases their power factor and hence the maximum power that can be delivered to a load. This effect can be cancelled by the addition of capacitors in series with the stepper windings. A circuit was designed and implemented to automatically vary the series capacitance over the entire speed range investigated. The addition of the series capacitors improved the power output of the stepper machine by up to 700%. At low rotor speeds, with the addition of series capacitance, the power output of the hybrid "stepper" was more than 200% that of a similarly sized PMDC brushed motor. Finally, in this thesis a hybrid lumped parameter / finite element model was used to investigate the impact of number, shape and size of the rotor and stator teeth on machine performance. A typical off-the-shelf hybrid stepper machine has significant cogging torque by design. This cogging torque is a major problem in most small energy harvesting applications. In this thesis it was shown that the cogging and ripple torque can be dramatically reduced. These findings confirm that high-pole-count topologies, and specifically the hybrid stepper configuration, are an attractive choice for energy harvesting applications.

  12. Mistaking minds and machines: How speech affects dehumanization and anthropomorphism.

    Science.gov (United States)

    Schroeder, Juliana; Epley, Nicholas

    2016-11-01

    Treating a human mind like a machine is an essential component of dehumanization, whereas attributing a humanlike mind to a machine is an essential component of anthropomorphism. Here we tested how a cue closely connected to a person's actual mental experience-a humanlike voice-affects the likelihood of mistaking a person for a machine, or a machine for a person. We predicted that paralinguistic cues in speech are particularly likely to convey the presence of a humanlike mind, such that removing voice from communication (leaving only text) would increase the likelihood of mistaking the text's creator for a machine. Conversely, adding voice to a computer-generated script (resulting in speech) would increase the likelihood of mistaking the text's creator for a human. Four experiments confirmed these hypotheses, demonstrating that people are more likely to infer a human (vs. computer) creator when they hear a voice expressing thoughts than when they read the same thoughts in text. Adding human visual cues to text (i.e., seeing a person perform a script in a subtitled video clip), did not increase the likelihood of inferring a human creator compared with only reading text, suggesting that defining features of personhood may be conveyed more clearly in speech (Experiments 1 and 2). Removing the naturalistic paralinguistic cues that convey humanlike capacity for thinking and feeling, such as varied pace and intonation, eliminates the humanizing effect of speech (Experiment 4). We discuss implications for dehumanizing others through text-based media, and for anthropomorphizing machines through speech-based media. (PsycINFO Database Record

  13. Channel Identification Machines

    Directory of Open Access Journals (Sweden)

    Aurel A. Lazar

    2012-01-01

    Full Text Available We present a formal methodology for identifying a channel in a system consisting of a communication channel in cascade with an asynchronous sampler. The channel is modeled as a multidimensional filter, while models of asynchronous samplers are taken from neuroscience and communications and include integrate-and-fire neurons, asynchronous sigma/delta modulators and general oscillators in cascade with zero-crossing detectors. We devise channel identification algorithms that recover a projection of the filter(s onto a space of input signals loss-free for both scalar and vector-valued test signals. The test signals are modeled as elements of a reproducing kernel Hilbert space (RKHS with a Dirichlet kernel. Under appropriate limiting conditions on the bandwidth and the order of the test signal space, the filter projection converges to the impulse response of the filter. We show that our results hold for a wide class of RKHSs, including the space of finite-energy bandlimited signals. We also extend our channel identification results to noisy circuits.

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

    CERN Document Server

    Misic, Vojislav B

    2014-01-01

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

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

    Science.gov (United States)

    Hildebrandt, Mireille

    2017-01-01

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

  16. Wide Band Artificial Pulsar

    Science.gov (United States)

    Parsons, Zackary

    2017-01-01

    The Wide Band Artificial Pulsar (WBAP) is an instrument verification device designed and built by the National Radio Astronomy Observatory (NRAO) in Green Bank, West Virgina. The site currently operates the Green Bank Ultimate Pulsar Processing Instrument (GUPPI) and the Versatile Green Bank Astronomical Spectrometer (VEGAS) digital backends for their radio telescopes. The commissioning and continued support for these sophisticated backends has demonstrated a need for a device capable of producing an accurate artificial pulsar signal. The WBAP is designed to provide a very close approximation to an actual pulsar signal. This presentation is intended to provide an overview of the current hardware and software implementations and to also share the current results from testing using the WBAP.

  17. Model checking abstract state machines with answer set programming

    OpenAIRE

    2006-01-01

    Answer Set Programming (ASP) is a logic programming paradigm that has been shown as a useful tool in various application areas due to its expressive modelling language. These application areas include Bourided Model Checking (BMC). BMC is a verification technique that is recognized for its strong ability of finding errors in computer systems. To apply BMC, a system needs to be modelled in a formal specification language, such as the widely used formalism of Abstract State Machines (ASMs). In ...

  18. Electrical machine characterisation and analysis for renewable energy applications

    OpenAIRE

    Cashman, David P.

    2010-01-01

    There has been an increased use of the Doubly-Fed Induction Machine (DFIM) in ac drive applications in recent times, particularly in the field of renewable energy systems and other high power variable-speed drives. The DFIM is widely regarded as the optimal generation system for both onshore and offshore wind turbines and has also been considered in wave power applications. Wind power generation is the most mature renewable technology. However, wave energy has attracted a large interest recen...

  19. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    OpenAIRE

    Supriya Kinger; Rajesh Kumar; Anju Sharma

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a crit...

  20. Single-Machine Scheduling with Accelerating Learning Effects

    Directory of Open Access Journals (Sweden)

    T. C. E. Cheng

    2013-01-01

    Full Text Available Scheduling with learning effects has been widely studied. However, there are situations where the learning effect might accelerate. In this paper, we propose a new model where the learning effect accelerates as time goes by. We derive the optimal solutions for the single-machine problems to minimize the makespan, total completion time, total weighted completion time, maximum lateness, maximum tardiness, and total tardiness.

  1. 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

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

  3. Strategic Optimization and Investigation Effect Of Process Parameters On Performance Of Wire Electric Discharge Machine (WEDM

    Directory of Open Access Journals (Sweden)

    ATUL KUMAR

    2012-06-01

    Full Text Available Wire electrical discharge machining (WEDM is widely used in machining of conductive materials when precision is of primary significance. Wire-cut electric discharge machining of Skd 61alloy has been considered in the present work. Experimentation has been completed by using Taguchi’s L18 (21x37 orthogonal array under different conditions of parameters. Optimal combinations of parameters were obtained by this technique. The study shows that with the minimum number of experiments the complete problem can be solvedwhen compared to full factorial design. Experimental results make obvious that the machining model is proper and the Taguchi’s method satisfies the practical conditions. The results obtained are analyzed for the selection of an optimal combination of WEDM parameters for proper machining of Skd 61 alloy to achieve better surface finish. Different analysis was made on the data obtained from the experiments.

  4. A Review on Current Research and Development in Abrasive Waterjet Machining

    Directory of Open Access Journals (Sweden)

    M. M. Korat

    2014-01-01

    Full Text Available Abrasive waterjet machining (AWJM is an emerging machining technology option for hard material parts that are extremely difficult-to-machine by conventional machining processes. A narrow stream of high velocity water mixed with abrasive particles gives relatively inexpensive and environment friendly production with reasonably high material removal rate. Because of that abrasive waterjet machining has become one of the leading manufacturing technologies in a relatively short period of time. This paper reviews the research work carried out from the inception to the development of AWJM within the past decade. It reports on the AWJM research relating to improving performance measures, monitoring and control of process, optimizing the process variables. A wide range of AWJM industrial applications for different category of material are reported with variations. The paper also discusses the future trend of research work in the same area.

  5. Investigation of Surfaces after Non Conventional Machining

    Science.gov (United States)

    Micietova, Anna; Neslusan, Miroslav; Cillikova, Maria

    2016-12-01

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

  6. WIRED — World-Wide Web Interactive Remote Event Display

    Science.gov (United States)

    Coperchio, M. C.; Dönszelmann, M.; de Groot, N.; Gunnarsson, P.; Litmaath, M.; McNally, D.; Smirnov, N.

    1998-05-01

    WIRED (World-Wide Web Interactive Remote Event Display) is a framework, written in the Java™ language, for building High Energy Physics event displays. An event display based on the WIRED framework enables users of a HEP collaboration to visualise and analyse events remotely using ordinary WWW browsers, on any type of machine. In addition, event displays using WIRED may provide the general public with access to the research of high energy physics. The recent introduction of the object-oriented Java™ language enables the transfer of machine independent code across the Internet, to be safely executed by a Java enhanced WWW browser. We have employed this technology to create a remote event display in WWW. The combined Java-WWW technology hence assures a world wide availability of such an event display, an always up-to-date program and a platform independent implementation, which is easy to use and to install.

  7. Electric Drive for an In-wheel Fractional-slot Axial Flux Machine

    Institute of Scientific and Technical Information of China (English)

    Luigi Alberti; Nicola Bian-chi

    2008-01-01

    This paper describes the electric drive for an in-wheel fractional-slot axial flux machine, designed for achievinga wide flux-weakening operating region.By using a slotted stator with fractional-slot windings and additional coresenclosing end windings,the axial flux machine reaches a wide constant power speed range. The machine is designed forincreasing flux-weakening capability while obtaining low harmonic back-electromotive force and low cogging torque.A 10maximize the output torque in the flux-weakening region, is designed and implemented.The goodness of both design andcontrol algorithm is proved by experimental tests.However,such a fractional-slot machine has not only advantages.Rotorlosses are very high ,and they have to be properly considered during the design process.

  8. The Wide Field Imaging Interferometry Testbed

    CERN Document Server

    Zhang, X; Leisawitz, D T; Leviton, D B; Martino, A J; Mather, J C; Zhang, Xiaolei; Feinberg, Lee; Leisawitz, Dave; Leviton, Douglas B.; Martino, Anthony J.; Mather, John C.

    2001-01-01

    We are developing a Wide-Field Imaging Interferometry Testbed (WIIT) in support of design studies for NASA's future space interferometry missions, in particular the SPIRIT and SPECS far-infrared/submillimeter interferometers. WIIT operates at optical wavelengths and uses Michelson beam combination to achieve both wide-field imaging and high-resolution spectroscopy. It will be used chiefly to test the feasibility of using a large-format detector array at the image plane of the sky to obtain wide-field interferometry images through mosaicing techniques. In this setup each detector pixel records interferograms corresponding to averaging a particular pointing range on the sky as the optical path length is scanned and as the baseline separation and orientation is varied. The final image is constructed through spatial and spectral Fourier transforms of the recorded interferograms for each pixel, followed by a mosaic/joint-deconvolution procedure of all the pixels. In this manner the image within the pointing range ...

  9. Coordination Control Of Complex Machines

    NARCIS (Netherlands)

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

    2015-01-01

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

  10. Attention: A Machine Learning Perspective

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    2012-01-01

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

  11. Machine Learning applications in CMS

    CERN Document Server

    CERN. Geneva

    2017-01-01

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

  12. Parsing statistical machine translation output

    NARCIS (Netherlands)

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

    2009-01-01

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

  13. Man-machine interactions 3

    CERN Document Server

    Czachórski, Tadeusz; Kozielski, Stanisław

    2014-01-01

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

  14. Teaching Machines to Think Fuzzy

    Science.gov (United States)

    Technology Teacher, 2004

    2004-01-01

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

  15. Macchines per scoprire - Discovery Machines

    CERN Multimedia

    Auditorium, Rome

    2016-01-01

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

  16. Precision Machining Technology. Curriculum Guide.

    Science.gov (United States)

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

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

  17. The Garden and the Machine

    DEFF Research Database (Denmark)

    Clemmensen, Thomas Juel

    2014-01-01

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

  18. Automatic Evaluation of Machine Translation

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  19. THE GARDEN AND THE MACHINE

    DEFF Research Database (Denmark)

    Clemmensen, Thomas Juel

    2012-01-01

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

  20. Dimensioning, Tolerancing, and Machine Finishes.

    Science.gov (United States)

    Adams, George C.

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