WorldWideScience

Sample records for machine performance msu

  1. Virtual machine performance benchmarking.

    Science.gov (United States)

    Langer, Steve G; French, Todd

    2011-10-01

    The attractions of virtual computing are many: reduced costs, reduced resources and simplified maintenance. Any one of these would be compelling for a medical imaging professional attempting to support a complex practice on limited resources in an era of ever tightened reimbursement. In particular, the ability to run multiple operating systems optimized for different tasks (computational image processing on Linux versus office tasks on Microsoft operating systems) on a single physical machine is compelling. However, there are also potential drawbacks. High performance requirements need to be carefully considered if they are to be executed in an environment where the running software has to execute through multiple layers of device drivers before reaching the real disk or network interface. Our lab has attempted to gain insight into the impact of virtualization on performance by benchmarking the following metrics on both physical and virtual platforms: local memory and disk bandwidth, network bandwidth, and integer and floating point performance. The virtual performance metrics are compared to baseline performance on "bare metal." The results are complex, and indeed somewhat surprising.

  2. Advances in superconducting cyclotrons at MSU

    International Nuclear Information System (INIS)

    Blosser, H.; Antaya, T.; Au, R.

    1987-01-01

    Intensive work on superconducting cyclotrons began at MSU in late 1973 (a brief earlier study had occurred in the early 1960's) and continues vigorously at present. One large cyclotron, the ''K500'', has been operating for a number of years, a second, the ''K800'', is nearing completion, the first operating tests of its magnet having occurred at the time of the previous conference, and a third, the ''medical cyclotron'', is now also nearing completion with first operation of its magnet expected just after the present conference. These cyclotrons like other superconducting cyclotrons are all dramatically smaller than comparable room temperature machines; overall weight is typically about 1/20th of that of room temperature cyclotrons of the same energy. This large reduction in the quantities of materials is partially offset by added complexity, but finally, a net overall cost savings of 50 to 70 % typically results; as a consequence the superconducting cyclotron is widely viewed as the cyclotron of the future. The thirteen years of experience at MSU involving three of these cyclotrons, together with much important work at other laboratories, gives a rather clear view of the advantages and disadvantages of various design approaches including by now a rather significant period of long term evaluation. This paper reviews highlights of this program. (author)

  3. Global Warming Estimation from MSU

    Science.gov (United States)

    Prabhakara, C.; Iacovazzi, Robert, Jr.

    1999-01-01

    In this study, we have developed time series of global temperature from 1980-97 based on the Microwave Sounding Unit (MSU) Ch 2 (53.74 GHz) observations taken from polar-orbiting NOAA operational satellites. In order to create these time series, systematic errors (approx. 0.1 K) in the Ch 2 data arising from inter-satellite differences are removed objectively. On the other hand, smaller systematic errors (approx. 0.03 K) in the data due to orbital drift of each satellite cannot be removed objectively. Such errors are expected to remain in the time series and leave an uncertainty in the inferred global temperature trend. With the help of a statistical method, the error in the MSU inferred global temperature trend resulting from orbital drifts and residual inter-satellite differences of all satellites is estimated to be 0.06 K decade. Incorporating this error, our analysis shows that the global temperature increased at a rate of 0.13 +/- 0.06 K decade during 1980-97.

  4. 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.

  5. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  6. Tunnel Boring Machine Performance Study. Final Report

    Science.gov (United States)

    1984-06-01

    Full face tunnel boring machine "TBM" performance during the excavation of 6 tunnels in sedimentary rock is considered in terms of utilization, penetration rates and cutter wear. The construction records are analyzed and the results are used to inves...

  7. Performance and portability of the SciBy virtual machine

    DEFF Research Database (Denmark)

    Andersen, Rasmus; Vinter, Brian

    2010-01-01

    The Scientific Bytecode Virtual Machine is a virtual machine designed specifically for performance, security, and portability of scientific applications deployed in a Grid environment. The performance overhead normally incurred by virtual machines is mitigated using native optimized scientific li...

  8. Commissioning of Theratron phoenix telecobalt machine and its performance assessment

    International Nuclear Information System (INIS)

    Rajendran, M.; Reddy, K.D.; Reddy, R.M.; Reddy, J.M.; Reddy, B.V.N.; Kumar, K.; Gopi, S.; Rajan, Dharani; Janardhanan

    2002-01-01

    Teletherapy machines like cobalt-60 unit and linear accelerator are extensively used for radiotherapy. Theratron phoenix machines have been installed. A brief report on the performance of this machine is presented

  9. Ultrasound scans and dual energy CT identify tendons as preferred anatomical location of MSU crystal depositions in gouty joints.

    Science.gov (United States)

    Yuan, Yuan; Liu, Chang; Xiang, Xi; Yuan, Tong-Ling; Qiu, Li; Liu, Yi; Luo, Yu-Bin; Zhao, Y; Herrmann, Martin

    2018-05-01

    The present study was performed to localize the articular deposition of monosodium urate (MSU) crystal in joints. We compare the detection efficiencies of dual-energy CT (DECT) and ultrasound scans. Analyses by DECT and ultrasound were performed with 184 bilateral joints of the lower limbs of 54 consecutive gout patients. All joints were categorized into (1) knee, (2) ankle, (3) MTP1, and (4) MTP2, and sorted into those with and those without detectable MSU deposition. The comparison of the positive rate between DECT and ultrasound and the agreement was performed using the McNemar test and the Cohen's κ coefficient, respectively. Next, we listed the MSU crystal deposition as assessed by ultrasound between the DECT-positive and -negative joints according to their interior structure. We included tendons, synovia, cartilage, subcutaneous tissue, etc. RESULTS: Among all joints, the percentages with MSU crystal deposition detected by DECT (99/184, 53.8%) and ultrasound (106/184, 57.6%) were comparable (P = 0.530 > 0.05). For MTP1 (21/34, 61.8%; 12/34, 35.3%; P efficient, respectively. The data concordance in 46 of 50 joints (92.00%; κ = 0.769, P location of MSU crystal deposition. The tendons are the most frequent anatomical location of MSU crystal depositions. The concordance rate of knee joints and MTP2-5 joints shows good agreement between DECT and ultrasound depending on the location.

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

    Directory of Open Access Journals (Sweden)

    Zhang Chengmao

    2015-01-01

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

  11. Dynamic Performances of Asynchronous Machines | Ubeku ...

    African Journals Online (AJOL)

    The per-phase parameters of a 1.5 hp, 380 V, 50 Hz, 4 poles, 3 phase asynchronous machine used in the simulation were computed with reading obtained from a dc, no-load and blocked rotor tests carried out on the machine in the laboratory. The results obtained from the computer simulations confirmed the capabilities ...

  12. MSU (Microwave Sounding Unit) Daily Troposphere Temperatures and Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of two MSU tropospheric temperatures levels and precipitation which are described in detail below. The NOAA satellites contributing to this...

  13. Multiple GISS AGCM Hindcasts and MSU Versions of 1979-1998

    Science.gov (United States)

    Shah, Kathryn Pierce; Rind, David; Druyan, Leonard; Lonergan, Patrick; Chandler, Mark

    1998-01-01

    had a maximum mid-tropospheric correlation of 0.54 +/- 0.11 while the U.S. Cornbelt had only 0.25 +/- .10. Precipitation and surface temperature performance are also examined over these regions. Correlations of MSU and AGCM time series mostly improved with addition of explicit atmospheric forcings in zonal bands but not in agricultural regional bins each encompassing only six AGCM gridcells.

  14. The differential induction machine: Theory and performance

    Indian Academy of Sciences (India)

    feasibility of taking a turn. ... Thus the axial gap between the two rotors is also ... inductance than a normal machine due to the separating gap between the two rotors .... Crelerot O, Bernot F, Kauffmann J F 1993 Study of an electrical differential ...

  15. Performance Analysis of Abrasive Waterjet Machining Process at Low Pressure

    Science.gov (United States)

    Murugan, M.; Gebremariam, MA; Hamedon, Z.; Azhari, A.

    2018-03-01

    Normally, a commercial waterjet cutting machine can generate water pressure up to 600 MPa. This range of pressure is used to machine a wide variety of materials. Hence, the price of waterjet cutting machine is expensive. Therefore, there is a need to develop a low cost waterjet machine in order to make the technology more accessible for the masses. Due to its low cost, such machines may only be able to generate water pressure at a much reduced rate. The present study attempts to investigate the performance of abrasive water jet machining process at low cutting pressure using self-developed low cost waterjet machine. It aims to study the feasibility of machining various materials at low pressure which later can aid in further development of an effective low cost water jet machine. A total of three different materials were machined at a low pressure of 34 MPa. The materials are mild steel, aluminium alloy 6061 and plastics Delrin®. Furthermore, a traverse rate was varied between 1 to 3 mm/min. The study on cutting performance at low pressure for different materials was conducted in terms of depth penetration, kerf taper ratio and surface roughness. It was found that all samples were able to be machined at low cutting pressure with varied qualities. Also, the depth of penetration decreases with an increase in the traverse rate. Meanwhile, the surface roughness and kerf taper ratio increase with an increase in the traverse rate. It can be concluded that a low cost waterjet machine with a much reduced rate of water pressure can be successfully used for machining certain materials with acceptable qualities.

  16. Failure Modes Analysis for the MSU-RIA Driver Linac

    CERN Document Server

    Wu, Xiaoyu; Gorelov, Dmitry; Grimm, Terry L; Marti, Felix; York, Richard

    2005-01-01

    Previous end-to-end beam dynamics simulation studies* using experimentally-based input beams including alignment and rf errors and variation in charge-stripping foil thickness have indicated that the Rare Isotope Accelerator (RIA) driver linac proposed by MSU has adequate transverse and longitudinal acceptances to accelerate light and heavy ions to final energies of at least 400 MeV/u with beam powers of 100 to 400 kW. During linac operation, equipment loss due to, for example, cavity contamination, availability of cryogens, or failure of rf or power supply systems, will lead to at least a temporary loss of some of the cavities and focusing elements. To achieve high facility availability, each segment of the linac should be capable of adequate performance even with failed elements. Beam dynamics studies were performed to evaluate the linac performance under various scenarios of failed cavities and focusing elements with proper correction schemes, in order to prove the flexibility and robustness of the driver ...

  17. Online space physics data services at SINP MSU

    Science.gov (United States)

    Kalegaev, V.; Bobrovnikov, S.; Alexeev, I.

    A WWW-based online space physics data services are developed at Skobeltsyn Institute of Nuclear Physics of Moscow State University (SINP MSU). These services provide fast access to data, images and information on the Earth's environment collected at SINP MSU. Data available on the Internet using anonymous ftp (dbserv.sinp.msu.ru) and WWW (http://alpha.sinp.msu.ru/datasets.html is the data archive, and http://alpha.sinp.msu.ru/dataintr.html is data retrieval forms). All the data have been loaded into the Oracle database. They were carefully organized for the fastest access and search capabilities. WWW interface is based on the Apache Webserver software and PHP scripting language. PHP-based scripts have the direct access to the tables of data in the Oracle database. HTML-based self-explanatory forms provide a simple mechanism of data selection for an appropriate period of time. They enable unified access to all datasets independent on the structure of the data. Using available tools user can browse and download data.

  18. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  19. Performance analysis of a composite dual-winding reluctance machine

    International Nuclear Information System (INIS)

    Anih, Linus U.; Obe, Emeka S.

    2009-01-01

    The electromagnetic energy conversion process of a composite dual-winding asynchronous reluctance machine is presented. The mechanism of torque production is explained using the magnetic fields distributions. The dynamic model developed in dq-rotor reference frame from first principles depicts the machine operation and response to sudden load change. The device is self-starting in the absence of rotor conductors and its starting current is lower than that of a conventional induction machine. Although the machine possesses salient pole rotors, it is clearly shown that its performance is that of an induction motor operating at half the synchronous speed. Hence the device produces synchronous torque while operating asynchronously. Simple tests were conducted on a prototype demonstration machine and the results obtained are seen to be in tune with the theory and the steady-state calculations.

  20. Development and Performance Evaluation of Fluted Pumpkin Seed Dehulling Machine

    Directory of Open Access Journals (Sweden)

    M. M. Odewole

    2017-08-01

    Full Text Available A machine for dehulling fluted pumpkin seed (Telfairia occidentalis was developed. The main objective of developing the machine was to provide a better substitute to traditional methods of dehulling the seed which contains edible oil of high medicinal and nutritional values. Traditional methods are full of drudgery, slow, injury prone and would lead to low and poor outputs in terms of quantity and quality of dehulled products. The machine is made of five major parts: the feed hopper (for holding the seeds to be dehulled before getting into the dehulling chamber, dehulling chamber (the part of the machine that impacts forces on seeds thereby causing fractures and opening of seeds coats for the delivery of the oily kernels, discharge unit (exit for oily kernels and seed coats after dehulling, the frame (for structural support and stability of all parts of the machine and electric motor (power source of the machine.The development process involved design of major components (shaft diameter (20 mm, machine velocity (7.59 m/s, power requirement (3hp single phase electric motor and structural support of mild steel angle iron, selection of construction materials and fabrication. ANSYS R14.5 machine design computer software was used to design the shaft and structural support; while other components were designed with conventional design method of using design equations. The machine works on the principle of centrifugal and impact forces. Performance evaluation was carried out after fabrication and 87.26%, 2.83g/s, 8.9% and 3.84%were obtained for dehulling efficiency, throughput capacity, percentage partially dehulled and percentage undehulled respectively.

  1. MSU-Northern Bio-Energy Center of Excellence

    Energy Technology Data Exchange (ETDEWEB)

    Kegel, Greg [Montana State Univ., Bozeman, MT (United States); Alcorn-Windy Boy, Jessica [Montana State Univ., Bozeman, MT (United States); Abedin, Md. Joynal [Montana State Univ., Bozeman, MT (United States); Maglinao, Randy [Montana State Univ., Bozeman, MT (United States)

    2014-09-30

    MSU-Northern established the Bio-Energy Center (the Center) into a Regional Research Center of Excellence to address the obstacles concerning biofuels, feedstock, quality, conversion process, economic viability and public awareness. The Center built its laboratories and expertise in order to research and support product development and commercialization for the bio-energy industry in our region. The Center wanted to support the regional agricultural based economy by researching biofuels based on feedstock’s that can be grown in our region in an environmentally responsible manner. We were also interested in any technology that will improve the emissions and fuel economy performance of heavy duty diesel engines. The Center had a three step approach to accomplish these goals: 1. Enhance the Center’s research and testing capabilities 2. Develop advanced biofuels from locally grown agricultural crops. 3. Educate and outreach for public understanding and acceptance of new technology. The Center was very successful in completing the tasks as outlined in the project plan. Key successes include discovering and patenting a new chemical conversion process for converting camelina oil to jet fuel, as well as promise in developing a heterogeneous Grubs catalyst to support the new chemical conversion process. The Center also successfully fragmented and deoxygenated naturally occurring lignin with a Ni-NHC catalyst, showing promise for further exploration of using lignin for fuels and fuel additives. This would create another value-added product for lignin that can be sourced from beetle kill trees or waste products from cellulose ethanol fuel facilities.

  2. Boxing headguard performance in punch machine tests.

    Science.gov (United States)

    McIntosh, Andrew S; Patton, Declan A

    2015-09-01

    The paper presents a novel laboratory method for assessing boxing headguard impact performance. The method is applied to examine the effects of headguards on head impact dynamics and injury risk. A linear impactor was developed, and a range of impacts was delivered to an instrumented Hybrid III head and neck system both with and without an AIBA (Association Internationale de Boxe Amateur)-approved headguard. Impacts at selected speeds between 4.1 and 8.3 m/s were undertaken. The impactor mass was approximately 4 kg and an interface comprising a semirigid 'fist' with a glove was used. The peak contact forces were in the range 1.9-5.9 kN. Differences in head impact responses between the Top Ten AIBA-approved headguard and bare headform in the lateral and forehead tests were large and/or significant. In the 8.3 m/s fist-glove impacts, the mean peak resultant headform accelerations for bare headform tests was approximately 130 g compared with approximately 85 g in the forehead impacts. In the 6.85 m/s bare headform impacts, mean peak resultant angular head accelerations were in the range of 5200-5600 rad/s(2) and almost halved by the headguard. Linear and angular accelerations in 45° forehead and 60° jaw impacts were reduced by the headguard. The data support the opinion that current AIBA headguards can play an important role in reducing the risk of concussion and superficial injury in boxing competition and training. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  3. Fabrication and Performance Evaluation of a Thevetia Nut Cracking Machine

    Directory of Open Access Journals (Sweden)

    M. M. Odewole

    2015-06-01

    Full Text Available Thevetia seed contains about 64 percent of non-edible oil in its oily kernel and this oil can be used for various purposes such as biofuel and bio-oil; making of paints, insecticides, cosmetics, lubricants and cooling oil in electrical transformers. The cakes obtained after oil extraction are incorporated on the field as manure. In order to get quality oil kernels from the hard nuts, there is need to properly crack them; this process of cracking is still a great challenge. As result of the aforementioned problem, this work focused on the design, fabrication and performance evaluation of a thevetia nut cracking machine. The machine works based on the principle of attrition force. Some of the parts designed for were diameter of shaft (13 mm solid shaft and length of belt (A55, power required to operate the machine (2.5 hp, speed of operation (9.14 m/s and the appropriate dimension of angle iron bar of 45 mm × 45 mm × 3 mm was used for the structural support. The fabrication was done systematically followed by the performance evaluation of the machine. The result of the overall cracking efficiency and throughput capacity of the machine were evaluated to be 96.65 % and 510 g⁄min respectively.

  4. 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

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

    International Nuclear Information System (INIS)

    Dastgir, G.

    2012-01-01

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

  6. A Performance Survey on Stack-based and Register-based Virtual Machines

    OpenAIRE

    Fang, Ruijie; Liu, Siqi

    2016-01-01

    Virtual machines have been widely adapted for high-level programming language implementations and for providing a degree of platform neutrality. As the overall use and adaptation of virtual machines grow, the overall performance of virtual machines has become a widely-discussed topic. In this paper, we present a survey on the performance differences of the two most widely adapted types of virtual machines - the stack-based virtual machine and the register-based virtual machine - using various...

  7. Factors Affecting Slot Machine Performance in an Electronic Gaming Machine Facility

    OpenAIRE

    Etienne Provencal; David L. St-Pierre

    2017-01-01

    A facility exploiting only electronic gambling machines (EGMs) opened in 2007 in Quebec City, Canada under the name of Salons de Jeux du Québec (SdjQ). This facility is one of the first worldwide to rely on that business model. This paper models the performance of such EGMs. The interest from a managerial point of view is to identify the variables that can be controlled or influenced so that a comprehensive model can help improve the overall performance of the business. The EGM individual per...

  8. Performance evaluation of coherent Ising machines against classical neural networks

    Science.gov (United States)

    Haribara, Yoshitaka; Ishikawa, Hitoshi; Utsunomiya, Shoko; Aihara, Kazuyuki; Yamamoto, Yoshihisa

    2017-12-01

    The coherent Ising machine is expected to find a near-optimal solution in various combinatorial optimization problems, which has been experimentally confirmed with optical parametric oscillators and a field programmable gate array circuit. The similar mathematical models were proposed three decades ago by Hopfield et al in the context of classical neural networks. In this article, we compare the computational performance of both models.

  9. Data on genome sequencing, analysis and annotation of a pathogenic Bacillus cereus 062011msu

    Directory of Open Access Journals (Sweden)

    Rashmi Rathy

    2018-04-01

    Full Text Available Bacillus species 062011 msu is a harmful pathogenic strain responsible for causing abscessation in sheep and goat population studied by Mariappan et al. (2012 [1]. The organism specifically targets the female sheep and goat population and results in the reduction of milk and meat production. In the present study, we have performed the whole genome sequencing of the pathogenic isolate using the Ion Torrent sequencing platform and generated 458,944 raw reads with an average length of 198.2 bp. The genome sequence was assembled, annotated and analysed for the genetic islands, metabolic pathways, orthologous groups, virulence factors and antibiotic resistance genes associated with the pathogen. Simultaneously the 16S rRNA sequencing study and genome sequence comparison data confirmed that the strain belongs to the species Bacillus cereus and exhibits 99% sequence homo;logy with the genomes of B. cereus ATCC 10987 and B. cereus FRI-35. Hence, we have renamed the organism as Bacillus cereus 062011msu. The Whole Genome Shotgun (WGS project has been deposited at DDBJ/ENA/GenBank under the accession NTMF00000000 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA404036(SAMN07629099. Keywords: Bacillus cereus, Genome sequencing, Abscessation, Virulence factors

  10. Pavement Subgrade Performance Study in the Danish Road Testing Machine

    DEFF Research Database (Denmark)

    Ullidtz, Per; Ertman Larsen, Hans Jørgen

    1997-01-01

    Most existing pavement subgrade criteria are based on the AASHO Road Test, where only one material was tested and for only one climatic condition. To study the validity of these criteria and to refine the criteria a co-operative research program entitled the "International Pavement Subgrade...... Performance Study" was sponsored by the FHWA with American, Finnish and Danish partners. This paper describes the first test series which was carried out in the Danish Road Testing Machine (RTM).The first step in this program is a full scale test on an instrumented pavement in the Danish Road Testing Machine....... Pressure gauges and strain cells were installed in the upper part of the subgrade, for measuring stresses and strains in all three directions. During and after construction FWD testing was carried out to evaluate the elastic parameters of the materials. These parameters were then used with the theory...

  11. Investigations of Cutting Fluid Performance Using Different Machining Operations

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Belluco, Walter

    2002-01-01

    An analysis of cutting fluid performance in dif-ferent metal cutting operations is presented based on performance criteria, work material and fluid type. Cutting fluid performance was evaluated in turning, drilling, reaming and tapping operations, with respect to tool life, cutting forces and prod...... will get the same performance ranking for different metalworking fluids no matter what machining test is used, when the fluids are of the same type. Results show that this is mostly true for the water-based fluids on austenitic stainless steel while ranking did change depending on the test with straight......-gated. In the case of austenitic stainless steel as the workpiece material, results using the different operations under different cutting conditions show that the performance of vegetable oil based prod-ucts is superior or equal to that of mineral oil based products. The hypothesis was investigated that one...

  12. Video Quality Assessment and Machine Learning: Performance and Interpretability

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

    2015-01-01

    In this work we compare a simple and a complex Machine Learning (ML) method used for the purpose of Video Quality Assessment (VQA). The simple ML method chosen is the Elastic Net (EN), which is a regularized linear regression model and easier to interpret. The more complex method chosen is Support...... Vector Regression (SVR), which has gained popularity in VQA research. Additionally, we present an ML-based feature selection method. Also, it is investigated how well the methods perform when tested on videos from other datasets. Our results show that content-independent cross-validation performance...... on a single dataset can be misleading and that in the case of very limited training and test data, especially in regards to different content as is the case for many video datasets, a simple ML approach is the better choice....

  13. Performance of a Folded-Strip Toroidally Wound Induction Machine

    DEFF Research Database (Denmark)

    Jensen, Bogi Bech; Jack, Alan G.; Atkinson, Glynn J.

    2011-01-01

    This paper presents the measured experimental results from a four-pole toroidally wound induction machine, where the stator is constructed as a pre-wound foldable strip. It shows that if the machine is axially restricted in length, the toroidally wound induction machine can have substantially...... shorter stator end-windings than conventionally wound induction machines, and hence that a toroidally wound induction machine can have lower losses and a higher efficiency. The paper also presents the employed construction method, which emphasizes manufacturability, and highlights the advantages...

  14. Performance of Process Damping in Machining Titanium Alloys at Low Cutting Speed with Different Helix Tools

    International Nuclear Information System (INIS)

    Shaharun, M A; Yusoff, A R; Reza, M S; Jalal, K A

    2012-01-01

    Titanium is a strong, lustrous, corrosion-resistant and transition metal with a silver color to produce strong lightweight alloys for industrial process, automotive, medical instruments and other applications. However, it is very difficult to machine the titanium due to its poor machinability. When machining titanium alloys with the conventional tools, the wear rate of the tool is rapidly accelerate and it is generally difficult to achieve at high cutting speed. In order to get better understanding of machining titanium alloy, the interaction between machining structural system and the cutting process which result in machining instability will be studied. Process damping is a useful phenomenon that can be exploited to improve the limited productivity of low speed machining. In this study, experiments are performed to evaluate the performance of process damping of milling under different tool helix geometries. The results showed that the helix of 42° angle is significantly increase process damping performance in machining titanium alloy.

  15. Comparative Performance Analysis of Machine Learning Techniques for Software Bug Detection

    OpenAIRE

    Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed

    2015-01-01

    Machine learning techniques can be used to analyse data from different perspectives and enable developers to retrieve useful information. Machine learning techniques are proven to be useful in terms of software bug prediction. In this paper, a comparative performance analysis of different machine learning techniques is explored f or software bug prediction on public available data sets. Results showed most of the mac ...

  16. MSU Contributes to New Research on Star Formation

    Science.gov (United States)

    2010-01-01

    EAST LANSING, Mich. - "Crazy" and "cool" are two of the words Michigan State University astronomer Megan Donahue uses to describe the two distinct "tails" found on a long tail of gas that is believed to be forming stars where few stars have been formed before. Donahue was part of an international team of astronomers that viewed the gas tail with a very long, new observation made by the Chandra X-ray Observatory and detailed it in a paper published this month in the publication Astrophysical Journal. "The double tail is very cool - that is, interesting - and ridiculously hard to explain," said Donahue, a professor in MSU's Department of Physics and Astronomy. "It could be two different sources of gas or something to do with magnetic fields. We just don't know." What is also unusual is the gas tail, which is more than 200,000 light years in length, extends well outside any galaxy. It is within objects such as this that new stars are formed, but usually within the confines of a galaxy. "This system is really crazy because where we're seeing the star formation is well away from any galaxy," Donahue said. "Star formation happens primarily in the disks of galaxies. What we're seeing here is very unexpected." This gas tail was originally spotted by astronomers three years ago using a multitude of telescopes, including NASA's Chandra X-ray Observatory and the SOuthern Astrophysical Research telescope, a Chilean-based observatory in which MSU is one of the partners. The new observations show a second tail, and a fellow galaxy, ESO 137-002, that also has a tail of hot X-ray-emitting gas. How these newly formed stars came to be in this particular place remains a mystery as well. Astronomers theorize this gas tail might have "pulled" star-making material from nearby gases, creating what some have called "orphan stars." "This system continues to surprise us as we get better observations of it," Donahue said. The gas tail is located in the southern hemisphere near a

  17. Setting Organizational Key Performance Indicators in the Precision Machine Industry

    Directory of Open Access Journals (Sweden)

    Mei-Hsiu Hong

    2015-11-01

    Full Text Available The aim of this research is to define (or set organizational key performance indicators (KPIs in the precision machine industry using the concept of core competence and the supply chain operations reference (SCOR model. The research is conducted in three steps. In the first step, a benchmarking study is conducted to collect major items of core competence and to group them into main categories in order to form a foundation for the research. In the second step, a case company questionnaire and interviews are conducted to identify the key factors of core competence in the precision machine industry. The analysis is conducted based on four dimensions and hence several analysis rounds are completed. Questionnaire data is analyzed with grey relational analysis (GRA and resulted in 5–6 key factors in each dimension or sub-dimension. Based on the conducted interviews, 13 of these identified key factors are separated into one organization objective, five key factors of core competence and seven key factors of core ability. In the final step, organizational KPIs are defined (or set for the five identified key factors of core competence. The most competitive core abilities for each of the five key factors are established. After that, organizational KPIs are set based on the core abilities within 3 main categories of KPIs (departmental, office grade and hierarchal for each key factor. The developed KPI system based on organizational objectives, core competences, and core abilities allow enterprises to handle dynamic market demand and business environments, as well as changes in overall corporate objectives.

  18. High-performance reconfigurable hardware architecture for restricted Boltzmann machines.

    Science.gov (United States)

    Ly, Daniel Le; Chow, Paul

    2010-11-01

    Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications has been limited. A primary cause for this lack of adoption is that neural networks are usually implemented as software running on general-purpose processors. Hence, a hardware implementation that can exploit the inherent parallelism in neural networks is desired. This paper investigates how the restricted Boltzmann machine (RBM), which is a popular type of neural network, can be mapped to a high-performance hardware architecture on field-programmable gate array (FPGA) platforms. The proposed modular framework is designed to reduce the time complexity of the computations through heavily customized hardware engines. A method to partition large RBMs into smaller congruent components is also presented, allowing the distribution of one RBM across multiple FPGA resources. The framework is tested on a platform of four Xilinx Virtex II-Pro XC2VP70 FPGAs running at 100 MHz through a variety of different configurations. The maximum performance was obtained by instantiating an RBM of 256 × 256 nodes distributed across four FPGAs, which resulted in a computational speed of 3.13 billion connection-updates-per-second and a speedup of 145-fold over an optimized C program running on a 2.8-GHz Intel processor.

  19. Simple, parallel, high-performance virtual machines for extreme computations

    International Nuclear Information System (INIS)

    Chokoufe Nejad, Bijan; Ohl, Thorsten; Reuter, Jurgen

    2014-11-01

    We introduce a high-performance virtual machine (VM) written in a numerically fast language like Fortran or C to evaluate very large expressions. We discuss the general concept of how to perform computations in terms of a VM and present specifically a VM that is able to compute tree-level cross sections for any number of external legs, given the corresponding byte code from the optimal matrix element generator, O'Mega. Furthermore, this approach allows to formulate the parallel computation of a single phase space point in a simple and obvious way. We analyze hereby the scaling behaviour with multiple threads as well as the benefits and drawbacks that are introduced with this method. Our implementation of a VM can run faster than the corresponding native, compiled code for certain processes and compilers, especially for very high multiplicities, and has in general runtimes in the same order of magnitude. By avoiding the tedious compile and link steps, which may fail for source code files of gigabyte sizes, new processes or complex higher order corrections that are currently out of reach could be evaluated with a VM given enough computing power.

  20. NOAA Climate Data Record (CDR) of MSU Level 1c Brightness Temperature, Version 1.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains Level 1c inter-calibrated brightness temperatures from the Microwave Sounding Unit (MSU) sensors onboard nine polar orbiting satellites...

  1. Performance of a Horizontal Triple Cylinder Type Pulping Machine

    Directory of Open Access Journals (Sweden)

    Sukrisno Widyotomo

    2011-05-01

    Full Text Available Pulping is one important step in wet coffee processing method. Pulping process usually uses a machine which constructed by wood or metal materials. A horizontal single cylinder type of fresh coffee cherries pulping machine is the most popular machine in coffee processing. One of the weaknesses of a horizontal single cylinder type of fresh coffee cherries pulping machine is higher in broken beans. Broken bean is one of mayor aspects in defect system that contribute to low quality. Indonesian Coffee and Cocoa Research Institute has designed and tested a horizontal double cylinder type of fresh coffee cherries pulping machine which resulted in 12.6—21.4% of broken beans. To reduce percentage of broken beans, Indonesian Coffee and Cocoa Research Institute has developed and tested a horizontal triple cylinder type of fresh coffee cherries pulping machine. Material tested was fresh mature Robusta coffee cherries, 60—65% (wet basis moisture content; has classified on 3 levels i.e. unsorted, small and medium, and clean from metal and foreign materials. The result showed that the machine produced 6,340 kg/h in optimal capacity for operational conditions, 1400 rpm rotor rotation speed for unsorted coffee cherries with composition 55.5% whole parchment coffee, 3.66% broken beans, and 1% beans in wet skin.Key words : coffee, pulp, pulper, cylinder, quality.

  2. Loop shaping design for tracking performance in machine axes.

    Science.gov (United States)

    Schinstock, Dale E; Wei, Zhouhong; Yang, Tao

    2006-01-01

    A modern interpretation of classical loop shaping control design methods is presented in the context of tracking control for linear motor stages. Target applications include noncontacting machines such as laser cutters and markers, water jet cutters, and adhesive applicators. The methods are directly applicable to the common PID controller and are pertinent to many electromechanical servo actuators other than linear motors. In addition to explicit design techniques a PID tuning algorithm stressing the importance of tracking is described. While the theory behind these techniques is not new, the analysis of their application to modern systems is unique in the research literature. The techniques and results should be important to control practitioners optimizing PID controller designs for tracking and in comparing results from classical designs to modern techniques. The methods stress high-gain controller design and interpret what this means for PID. Nothing in the methods presented precludes the addition of feedforward control methods for added improvements in tracking. Laboratory results from a linear motor stage demonstrate that with large open-loop gain very good tracking performance can be achieved. The resultant tracking errors compare very favorably to results from similar motions on similar systems that utilize much more complicated controllers.

  3. Application of Machine Learning Algorithms for the Query Performance Prediction

    Directory of Open Access Journals (Sweden)

    MILICEVIC, M.

    2015-08-01

    Full Text Available This paper analyzes the relationship between the system load/throughput and the query response time in a real Online transaction processing (OLTP system environment. Although OLTP systems are characterized by short transactions, which normally entail high availability and consistent short response times, the need for operational reporting may jeopardize these objectives. We suggest a new approach to performance prediction for concurrent database workloads, based on the system state vector which consists of 36 attributes. There is no bias to the importance of certain attributes, but the machine learning methods are used to determine which attributes better describe the behavior of the particular database server and how to model that system. During the learning phase, the system's profile is created using multiple reference queries, which are selected to represent frequent business processes. The possibility of the accurate response time prediction may be a foundation for automated decision-making for database (DB query scheduling. Possible applications of the proposed method include adaptive resource allocation, quality of service (QoS management or real-time dynamic query scheduling (e.g. estimation of the optimal moment for a complex query execution.

  4. Method and apparatus for characterizing and enhancing the functional performance of machine tools

    Science.gov (United States)

    Barkman, William E; Babelay, Jr., Edwin F; Smith, Kevin Scott; Assaid, Thomas S; McFarland, Justin T; Tursky, David A; Woody, Bethany; Adams, David

    2013-04-30

    Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include workpiece surface finish, and the ability to generate chips of the desired length.

  5. Exploration of Machine Learning Approaches to Predict Pavement Performance

    Science.gov (United States)

    2018-03-23

    Machine learning (ML) techniques were used to model and predict pavement condition index (PCI) for various pavement types using a variety of input variables. The primary objective of this research was to develop and assess PCI predictive models for t...

  6. Performance Evaluation of a Prototyped Breadfruit Seed Dehulling Machine

    Directory of Open Access Journals (Sweden)

    Nnamdi Anosike

    2016-05-01

    Full Text Available The drudgery involved in dehulling breadfruit seed by traditional methods has been highlighted as one of the major problems hindering the realization of the full potential of breadfruit as a field to food material. This paper describes a development in an African breadfruit seed dehulling machine with increased throughput of about 70% above reported machines. The machine consists of a 20 mm diameter shaft, carrying a spiral wound around its circumference (feeder. The feeder provides the required rotational motion and turns a circular disk that rotates against a fixed disk. The two disks can be adjusted to maintain a pre-determined gap for dehulling. An inbuilt drying unit reduces the moisture content of the breadfruit for easy separation of the cotyledon from the endosperm immediately after the dehulling process. The sifting unit that separates the shell from the seed is achieved in this design with an electric fan. The machine is design to run at a speed of 250 rpm with an electric motor as the prime mover. The dehulling efficiency up to 86% and breakage of less than 1.3% was obtained at a clearance setting of 12.4 mm between disks. A sifting efficiency of 100% was achieved. Based on the design diameter and clearance between the dehulling disks, the machine throughput was 216 kg/h with an electric power requirement of 1.207 kW.

  7. Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics

    Directory of Open Access Journals (Sweden)

    Haejoon Jung

    2018-01-01

    Full Text Available As an intrinsic part of the Internet of Things (IoT ecosystem, machine-to-machine (M2M communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

  8. Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics.

    Science.gov (United States)

    Jung, Haejoon; Lee, In-Ho

    2018-01-12

    As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

  9. Performance Characterization and Auto-Ignition Performance of a Rapid Compression Machine

    OpenAIRE

    Hao Liu; Hongguang Zhang; Zhicheng Shi; Haitao Lu; Guangyao Zhao; Baofeng Yao

    2014-01-01

    A rapid compression machine (RCM) test bench is developed in this study. The performance characterization and auto-ignition performance tests are conducted at an initial temperature of 293 K, a compression ratio of 9.5 to 16.5, a compressed temperature of 650 K to 850 K, a driving gas pressure range of 0.25 MPa to 0.7 MPa, an initial pressure of 0.04 MPa to 0.09 MPa, and a nitrogen dilution ratio of 35% to 65%. A new type of hydraulic piston is used to address the problem in which the hydraul...

  10. Intraoperative performance and postoperative outcome comparison of longitudinal, torsional, and transversal phacoemulsification machines.

    Science.gov (United States)

    Christakis, Panos G; Braga-Mele, Rosa M

    2012-02-01

    To compare the intraoperative performance and postoperative outcomes of 3 phacoemulsification machines that use different modes. Kensington Eye Institute, Toronto, Ontario, Canada. Comparative case series. This chart and video review comprised consecutive eligible patients who had phacoemulsification by the same surgeon using a Whitestar Signature Ellips-FX (transversal), Infiniti-Ozil-IP (torsional), or Stellaris (longitudinal) machine. The review included 98 patients. Baseline characteristics in the groups were similar; the mean nuclear sclerosis grade was 2.0 ± 0.8. There were no significant intraoperative complications. The torsional machine averaged less phacoemulsification needle time (83 ± 33 seconds) than the transversal (99 ± 40 seconds; P=.21) or longitudinal (110 ± 45 seconds; P=.02) machines; the difference was accentuated in cases with high-grade nuclear sclerosis. The torsional machine had less chatter and better followability than the transversal or longitudinal machines (P<.001). The torsional and longitudinal machines had better anterior chamber stability than the transversal machine (P<.001). Postoperatively, the torsional machine yielded less central corneal edema than the transversal (P<.001) and longitudinal (P=.04) machines, corresponding to a smaller increase in mean corneal thickness (torsional 5%, transversal 10%, longitudinal 12%; P=.04). Also, the torsional machine had better 1-day postoperative visual acuities (P<.001). All 3 phacoemulsification machines were effective with no significant intraoperative complications. The torsional machine outperformed the transversal and longitudinal machines, with a lower mean needle time, less chatter, and improved followability. This corresponded to less corneal edema 1 day postoperatively and better visual acuity. Copyright © 2011 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  11. Comparative analysis of partial imaging performance parameters of home and imported X-ray machines

    International Nuclear Information System (INIS)

    Cao Yunxi; Wang Xianyun; Liu Huiqin; Guo Yongxin

    2002-01-01

    Objective: To compare and analyze the performance indexes and the imaging quality of the home and imported X-ray machines through testing their partial imaging performance parameters. Methods: By separate sampling from 10 home and 10 imported X-ray machines, the parameters including tube current, time of exposure, machine total exposure, and repeatability were tested, and the imaging performance was evaluated according to the national standard. Results: All the performance indexes met the standard of GB4505-84. The first sampling tests showed the maximum changing coefficient of imaging performance repeatability of the home X-ray machines was Δmax1 = 0.025, while that of the imported X-ray machine was Δmax1 = 0.016. In the second sampling tests, the maximum changing coefficients of the two were Δmax2 = 0.048 and Δmax2 = 0.022, respectively. Conclusion: The 2 years' follow-up tests indicate that there is no significant difference between the above-mentioned parameters of the elaborately adjusted home X-ray machines and imported ones, but the home X-ray machines are no better than the imported X-ray machines in stability and consistency

  12. Improvement of the dynamic performance of an AC linear permanent magnet machine

    NARCIS (Netherlands)

    Jansen, J.W.; Lomonova, E.; Vandenput, A.J.A.; Compter, J.C.; Verweij, A.H.

    2003-01-01

    This paper discusses the controller design and test approaches leading to the performance improvement of a brushless 3-phase AC synchronous permanent magnet linear machine. The feasible controller design concept for the linear machine is presented and further implemented in Simulink and dSPACE. Two

  13. Quality control and performance evaluation of microselectron HDR machine over 30 months

    International Nuclear Information System (INIS)

    Balasubramanian, N.; Annex, E.H.; Sunderam, N.; Patel, N.P.; Kaushal, V.

    2008-01-01

    To assess the performance evaluation of Microselectron HDR machine the standard quality control and quality assurance checks were carried out after each loading of new 192 Ir brachytherapy source In the machine. Total 9 loadings were done over a period of 30 months

  14. Using GPS to evaluate productivity and performance of forest machine systems

    Science.gov (United States)

    Steven E. Taylor; Timothy P. McDonald; Matthew W. Veal; Ton E. Grift

    2001-01-01

    This paper reviews recent research and operational applications of using GPS as a tool to help monitor the locations, travel patterns, performance, and productivity of forest machines. The accuracy of dynamic GPS data collected on forest machines under different levels of forest canopy is reviewed first. Then, the paper focuses on the use of GPS for monitoring forest...

  15. Superconductor Armature Winding for High Performance Electrical Machines

    Science.gov (United States)

    2016-12-05

    eddy -induced currents used for shielding. 3.1 SOLID SHIELD. The frequency of the induced current for our machines ... eddy   current  shields)   •  SuperSat     •  switch  reluctance  generators   •  AC  Homopolar   • Toroidal  (Gramme...higher than expected, due probably to highly conducting Nb sheath around the MgB2 filaments (the measured losses were coupling or eddy current

  16. Application of JLab 12GeV helium refrigeration system for the FRIB accelerator at MSU

    International Nuclear Information System (INIS)

    Ganni, V.; Knudsen, P.; Arenius, D.; Casagrande, F.

    2014-01-01

    The planned approach to have a turnkey helium refrigeration system for the MSU-FRIB accelerator system, encompassing the design, fabrication, installation and commissioning of the 4.5-K refrigerator cold box(es), cold compression system, warm compression system, gas management, oil removal and utility/ancillary systems, was found to be cost prohibitive. Following JLab’s suggestion, MSU-FRIB accelerator management made a formal request to evaluate the applicability of the recently designed 12GeV JLab cryogenic system for this application. The following paper will outline the findings and the planned approach for the FRIB helium refrigeration system

  17. Performance of quantum cloning and deleting machines over coherence

    Science.gov (United States)

    Karmakar, Sumana; Sen, Ajoy; Sarkar, Debasis

    2017-10-01

    Coherence, being at the heart of interference phenomena, is found to be an useful resource in quantum information theory. Here we want to understand quantum coherence under the combination of two fundamentally dual processes, viz., cloning and deleting. We found the role of quantum cloning and deletion machines with the consumption and generation of quantum coherence. We establish cloning as a cohering process and deletion as a decohering process. Fidelity of the process will be shown to have connection with coherence generation and consumption of the processes.

  18. Performance Analysis of Ivshmem for High-Performance Computing in Virtual Machines

    Science.gov (United States)

    Ivanovic, Pavle; Richter, Harald

    2018-01-01

    High-Performance computing (HPC) is rarely accomplished via virtual machines (VMs). In this paper, we present a remake of ivshmem which can change this. Ivshmem was a shared memory (SHM) between virtual machines on the same server, with SHM-access synchronization included, until about 5 years ago when newer versions of Linux and its virtualization library libvirt evolved. We restored that SHM-access synchronization feature because it is indispensable for HPC and made ivshmem runnable with contemporary versions of Linux, libvirt, KVM, QEMU and especially MPICH, which is an implementation of MPI - the standard HPC communication library. Additionally, MPICH was transparently modified by us to get ivshmem included, resulting in a three to ten times performance improvement compared to TCP/IP. Furthermore, we have transparently replaced MPI_PUT, a single-side MPICH communication mechanism, by an own MPI_PUT wrapper. As a result, our ivshmem even surpasses non-virtualized SHM data transfers for block lengths greater than 512 KBytes, showing the benefits of virtualization. All improvements were possible without using SR-IOV.

  19. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    Science.gov (United States)

    Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

    2018-02-01

    In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

  20. Surface Coating of Plastic Parts for Business Machines (Industrial Surface Coating): New Source Performance Standards (NSPS)

    Science.gov (United States)

    Learn more about the new source performance standards (NSPS) for surface coating of plastic parts for business machines by reading the rule summary and history and finding the code of federal regulations as well as related rules.

  1. Effectiveness of Hamstring Knee Rehabilitation Exercise Performed in Training Machine vs. Elastic Resistance Electromyography Evaluation Study

    DEFF Research Database (Denmark)

    Jakobsen, M. D.; Sundstrup, E.; Andersen, C. H.

    2014-01-01

    Objective The aim of this study was to evaluate muscle activity during hamstring rehabilitation exercises performed in training machine compared with elastic resistance. Design Six women and 13 men aged 28-67 yrs participated in a crossover study. Electromyographic (EMG) activity was recorded...... inclinometers. Results Training machines and elastic resistance showed similar high levels of muscle activity (biceps femoris and semitendinosus peak normalized EMG >80%). EMG during the concentric phase was higher than during the eccentric phase regardless of exercise and muscle. However, compared with machine.......001) during hamstring curl performed with elastic resistance (7.58 +/- 0.08) compared with hamstring curl performed in a machine (5.92 +/- 0.03). Conclusions Hamstring rehabilitation exercise performed with elastic resistance induces similar peak hamstring muscle activity but slightly lower EMG values at more...

  2. Modification and Performance Evaluation of a Low Cost Electro-Mechanically Operated Creep Testing Machine

    Directory of Open Access Journals (Sweden)

    John J. MOMOH

    2010-12-01

    Full Text Available Existing mechanically operated tensile and creep testing machine was modified to a low cost, electro-mechanically operated creep testing machine capable of determining the creep properties of aluminum, lead and thermoplastic materials as a function of applied stress, time and temperature. The modification of the testing machine was necessitated by having an electro-mechanically operated creep testing machine as a demonstration model ideal for use and laboratory demonstrations, which will provide an economical means of performing standard creep experiments. The experimental result is a more comprehensive understanding of the laboratory experience, as the technology behind the creep testing machine, the test methodology and the response of materials loaded during experiment are explored. The machine provides a low cost solution for Mechanics of Materials laboratories interested in creep testing experiment and demonstration but not capable of funding the acquisition of commercially available creep testing machines. Creep curves of strain versus time on a thermoplastic material were plotted at a stress level of 1.95MPa, 3.25MPa and 4.55MPa and temperature of 20oC, 40oC and 60oC respectively. The machine is satisfactory since it is always ready for operation at any given time.

  3. A highly efficient machine planting system for forestry research plantations—the Wright-MSU method

    Science.gov (United States)

    James R. McKenna; Oriana Rueda-Krauss; Brian. Beheler

    2011-01-01

    For forestry research purposes, grid planting with uniform tree spacing is superior to planting with nonuniform spacing because it controls density across the plantation and facilitates accurate repeat measurements. The ability to cross-check tree positions in a grid-type plantation avoids problems associated with dead or missing trees and increases the efficiency and...

  4. MSU-Northern Bio-Energy Center of Excellence

    Energy Technology Data Exchange (ETDEWEB)

    Kegel, Greg [Montana State Univ. Northern, Havre, MT (United States); Windy Boy, Jessica [Montana State Univ. Northern, Havre, MT (United States). Bio-Energy Center of Excellence; Maglinao, Randy Latayan [Montana State Univ. Northern, Havre, MT (United States). Bio-Energy Center of Excellence; Abedin, Md. Joynal [Montana State Univ. Northern, Havre, MT (United States). Bio-Energy Center of Excellence

    2017-03-02

    The goal of this project was to establish the Bio-Energy Center (the Center) of Montana State University Northern (MSUN) as a Regional Research Center of Excellence in research, product development, and commercialization of non-food biomass for the bio-energy industry. A three-step approach, namely, (1) enhance the Center’s research and testing capabilities, (2) develop advanced biofuels from locally grown agricultural crops, and (3) educate the community through outreach programs for public understanding and acceptance of new technologies was identified to achieve this goal. The research activities aimed to address the obstacles concerning the production of biofuels and other bio-based fuel additives considering feedstock quality, conversion process, economic viability, and public awareness. First and foremost in enhancing the capabilities of the Center is the improvement of its laboratories and other physical facilities for investigating new biomass conversion technologies and the development of its manpower complement with expertise in chemistry, engineering, biology, and energy. MSUN renovated its Auto Diagnostics building and updated its mechanical and electrical systems necessary to house the state-of-the-art 525kW (704 hp) A/C Dynamometer. The newly renovated building was designated as the Advanced Fuels Building. Two laboratories, namely Biomass Conversion lab and Wet Chemistry lab were also added to the Center’s facilities. The Biomass Conversion lab was for research on the production of advanced biofuels including bio-jet fuel and bio-based fuel additives while the Wet Chemistry lab was used to conduct catalyst research. Necessary equipment and machines, such as gas chromatograph-mass spectrometry, were purchased and installed to help in research and testing. With the enhanced capabilities of the Center, research and testing activities were very much facilitated and more precise. New biofuels derived from Camelina sativa (camelina), a locally

  5. 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.

  6. TRACEABILITY OF ON COORDINATE MEASURING MACHINES – CALIBRATION AND PERFORMANCE VERIFICATION

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Savio, Enrico; Bariani, Paolo

    This document is used in connection with three exercises each of 45 minutes duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measurement traceability: 1) Performance verification of a CMM using a ball bar; 2) Calibration...... of an optical coordinate measuring machine; 3) Uncertainty assessment using the ISO 15530-3 “Calibrated workpieces” procedure....

  7. What limits the performance of current invasive Brain Machine Interfaces?

    Directory of Open Access Journals (Sweden)

    Gytis eBaranauskas

    2014-04-01

    Full Text Available The concept of a brain-machine interface (BMI or a computer-brain interface is simple: BMI creates a communication pathway for a direct control by brain of an external device. In reality BMIs are very complex devices and only recently the increase in computing power of microprocessors enabled a boom in BMI research that continues almost unabated to this date, the high point being the insertion of electrode arrays into the brains of 5 human patients in a clinical trial run by Cyberkinetics with few other clinical tests still in progress. Meanwhile several EEG-based BMI devices (non-invasive BMIs were launched commercially. Modern electronics and dry electrode technology made possible to drive the cost of some of these devices below few hundred dollars. However, the initial excitement of the direct control by brain waves of a computer or other equipment is dampened by large efforts required for learning, high error rates and slow response speed. All these problems are directly related to low information transfer rates typical for such EEG-based BMIs. In invasive BMIs employing multiple electrodes inserted into the brain one may expect much higher information transfer rates than in EEG-based BMIs because, in theory, each electrode provides an independent information channel. However, although invasive BMIs require more expensive equipment and have ethical problems related to the need to insert electrodes in the live brain, such financial and ethical costs are often not offset by a dramatic improvement in the information transfer rate. Thus the main topic of this review is why in invasive BMIs an apparently much larger information content obtained with multiple extracellular electrodes does not translate into much higher rates of information transfer? This paper explores possible answers to this question by concluding that more research on what movement parameters are encoded by neurons in motor cortex is needed before we can enjoy the next

  8. APPLICATION OF THE PERFORMANCE SELECTION INDEX METHOD FOR SOLVING MACHINING MCDM PROBLEMS

    Directory of Open Access Journals (Sweden)

    Dušan Petković

    2017-04-01

    Full Text Available Complex nature of machining processes requires the use of different methods and techniques for process optimization. Over the past few years a number of different optimization methods have been proposed for solving continuous machining optimization problems. In manufacturing environment, engineers are also facing a number of discrete machining optimization problems. In order to help decision makers in solving this type of optimization problems a number of multi criteria decision making (MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. performance selection index (PSI method for solving machining MCDM problems. The main motivation for using the PSI method is that it is not necessary to determine criteria weights as in other MCDM methods. Applicability and effectiveness of the PSI method have been demonstrated while solving two case studies dealing with machinability of materials and selection of the most suitable cutting fluid for the given machining application. The obtained rankings have good correlation with those derived by the past researchers using other MCDM methods which validate the usefulness of this method for solving machining MCDM problems.

  9. Correlation of cutting fluid performance in different machining operations

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Belluco, Walter

    2001-01-01

    An analysis of cutting fluid performance in different metal cutting operations is presented, based on experimental investigations in which type of operation, performance criteria, work material, and fluid type are considered. Cutting fluid performance was evaluated in turning, drilling, reaming...... investigated. Results show that correlation of cutting fluid performance in different operations exists, within the same group of cutting fluids, in the case of stainless steel as workpiece material. Under the tested conditions, the average correlation coefficients between efficiency parameters with different...... operations on austenitic stainless steel lied in the range 0.87-0.97 for waterbased fluids and 0.79-0.89 for straight oils. A similar correlation could not be found for the other workpiece materials investigated in this work. A rationalisation of cutting fluid performance tests is suggested....

  10. Solution procedure and performance evaluation for a water–LiBr absorption refrigeration machine

    International Nuclear Information System (INIS)

    Wonchala, Jason; Hazledine, Maxwell; Goni Boulama, Kiari

    2014-01-01

    The water–lithium bromide absorption cooling machine was investigated theoretically in this paper. A detailed solution procedure was proposed and validated. A parametric study was conducted over the entire admissible ranges of the desorber, condenser, absorber and evaporator temperatures. The performance of the machine was evaluated based on the circulation ratio which is a measure of the system size and cost, the first law coefficient of performance and the second law exergy efficiency. The circulation ratio and the coefficient of performance were seen to improve as the temperature of the heat source increased, while the second law performance deteriorated. The same qualitative responses were obtained when the temperature of the refrigerated environment was increased. On the other hand, simultaneously raising the condenser and absorber temperatures was seen to result in a severe deterioration of both the circulation ratio and first law coefficient of performance, while the second law performance indicator improved significantly. The influence of the difference between the condenser and absorber exit temperatures, as well as that of the internal recovery heat exchanger on the different performance indicators was also calculated and discussed. - Highlights: • Analysis of a water–LiBr absorption machine, including detailed solution procedure. • Performance assessed using first and second law considerations, as well as flow ratio. • Effects of heat source and refrigerated environment temperatures on the performance. • Effects of the difference between condenser and absorber temperatures. • Effects of internal heat exchanger efficiency on overall cooling machine performance

  11. STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

    OpenAIRE

    S.A. Oloruntoba1 ,J.L.Akinode2

    2017-01-01

    This paper investigates the relationship between students' preadmission academic profile and final academic performance. Data Sample of students in one of the Federal Polytechnic in south West part of Nigeria was used. The preadmission academic profile used for this study is the 'O' level grades(terminal high school results).The academic performance is defined using student's Grade Point Average(GPA). This research focused on using data mining technique to develop a model for predicting stude...

  12. Performance of Color Camera Machine Vision in Automated Furniture Rough Mill Systems

    Science.gov (United States)

    D. Earl Kline; Agus Widoyoko; Janice K. Wiedenbeck; Philip A. Araman

    1998-01-01

    The objective of this study was to evaluate the performance of color camera machine vision for lumber processing in a furniture rough mill. The study used 134 red oak boards to compare the performance of automated gang-rip-first rough mill yield based on a prototype color camera lumber inspection system developed at Virginia Tech with both estimated optimum rough mill...

  13. Performance Characterization and Auto-Ignition Performance of a Rapid Compression Machine

    Directory of Open Access Journals (Sweden)

    Hao Liu

    2014-09-01

    Full Text Available A rapid compression machine (RCM test bench is developed in this study. The performance characterization and auto-ignition performance tests are conducted at an initial temperature of 293 K, a compression ratio of 9.5 to 16.5, a compressed temperature of 650 K to 850 K, a driving gas pressure range of 0.25 MPa to 0.7 MPa, an initial pressure of 0.04 MPa to 0.09 MPa, and a nitrogen dilution ratio of 35% to 65%. A new type of hydraulic piston is used to address the problem in which the hydraulic buffer adversely affects the rapid compression process. Auto-ignition performance tests of the RCM are then performed using a DME–O2–N2 mixture. The two-stage ignition delay and negative temperature coefficient (NTC behavior of the mixture are observed. The effects of driving gas pressure, compression ratio, initial pressure, and nitrogen dilution ratio on the two-stage ignition delay are investigated. Results show that both the first-stage and overall ignition delays tend to increase with increasing driving gas pressure. The driving gas pressure within a certain range does not significantly influence the compressed pressure. With increasing compression ratio, the first-stage ignition delay is shortened, whereas the second-stage ignition delay is extended. With increasing initial pressure, both the first-stage and second-stage ignition delays are shortened. The second-stage ignition delay is shortened to a greater extent than that of the first-stage. With increasing nitrogen dilution ratio, the first-stage ignition delay is shortened, whereas the second-stage is extended. Thus, overall ignition delay presents different trends under various compression ratios and compressed pressure conditions.

  14. Machining of high performance workpiece materials with CBN coated cutting tools

    International Nuclear Information System (INIS)

    Uhlmann, E.; Fuentes, J.A. Oyanedel; Keunecke, M.

    2009-01-01

    The machining of high performance workpiece materials requires significantly harder cutting materials. In hard machining, the early tool wear occurs due to high process forces and temperatures. The hardest known material is the diamond, but steel materials cannot be machined with diamond tools because of the reactivity of iron with carbon. Cubic boron nitride (cBN) is the second hardest of all known materials. The supply of such PcBN indexable inserts, which are only geometrically simple and available, requires several work procedures and is cost-intensive. The development of a cBN coating for cutting tools, combine the advantages of a thin film system and of cBN. Flexible cemented carbide tools, in respect to the geometry can be coated. The cBN films with a thickness of up to 2 μm on cemented carbide substrates show excellent mechanical and physical properties. This paper describes the results of the machining of various workpiece materials in turning and milling operations regarding the tool life, resultant cutting force components and workpiece surface roughness. In turning tests of Inconel 718 and milling tests of chrome steel the high potential of cBN coatings for dry machining was proven. The results of the experiments were compared with common used tool coatings for the hard machining. Additionally, the wear mechanisms adhesion, abrasion, surface fatigue and tribo-oxidation were researched in model wear experiments.

  15. Design and Performance Improvement of AC Machines Sharing a Common Stator

    Science.gov (United States)

    Guo, Lusu

    With the increasing demand on electric motors in various industrial applications, especially electric powered vehicles (electric cars, more electric aircrafts and future electric ships and submarines), both synchronous reluctance machines (SynRMs) and interior permanent magnet (IPM) machines are recognized as good candidates for high performance variable speed applications. Developing a single stator design which can be used for both SynRM and IPM motors is a good way to reduce manufacturing and maintenance cost. SynRM can be used as a low cost solution for many electric driving applications and IPM machines can be used in power density crucial circumstances or work as generators to meet the increasing demand for electrical power on board. In this research, SynRM and IPM machines are designed sharing a common stator structure. The prototype motors are designed with the aid of finite element analysis (FEA). Machine performances with different stator slot and rotor pole numbers are compared by FEA. An 18-slot, 4-pole structure is selected based on the comparison for this prototype design. Sometimes, torque pulsation is the major drawback of permanent magnet synchronous machines. There are several sources of torque pulsations, such as back-EMF distortion, inductance variation and cogging torque due to presence of permanent magnets. To reduce torque pulsations in permanent magnet machines, all the efforts can be classified into two categories: one is from the design stage, the structure of permanent magnet machines can be optimized with the aid of finite element analysis. The other category of reducing torque pulsation is after the permanent magnet machine has been manufactured or the machine structure cannot be changed because of other reasons. The currents fed into the permanent magnet machine can be controlled to follow a certain profile which will make the machine generate a smoother torque waveform. Torque pulsation reduction methods in both categories will be

  16. Predicting the Performance of Chain Saw Machines Based on Shore Scleroscope Hardness

    Science.gov (United States)

    Tumac, Deniz

    2014-03-01

    Shore hardness has been used to estimate several physical and mechanical properties of rocks over the last few decades. However, the number of researches correlating Shore hardness with rock cutting performance is quite limited. Also, rather limited researches have been carried out on predicting the performance of chain saw machines. This study differs from the previous investigations in the way that Shore hardness values (SH1, SH2, and deformation coefficient) are used to determine the field performance of chain saw machines. The measured Shore hardness values are correlated with the physical and mechanical properties of natural stone samples, cutting parameters (normal force, cutting force, and specific energy) obtained from linear cutting tests in unrelieved cutting mode, and areal net cutting rate of chain saw machines. Two empirical models developed previously are improved for the prediction of the areal net cutting rate of chain saw machines. The first model is based on a revised chain saw penetration index, which uses SH1, machine weight, and useful arm cutting depth as predictors. The second model is based on the power consumed for only cutting the stone, arm thickness, and specific energy as a function of the deformation coefficient. While cutting force has a strong relationship with Shore hardness values, the normal force has a weak or moderate correlation. Uniaxial compressive strength, Cerchar abrasivity index, and density can also be predicted by Shore hardness values.

  17. Permanent Magnet Flux-Switching Machine, Optimal Design and Performance Analysis

    Directory of Open Access Journals (Sweden)

    Liviu Emilian Somesan

    2013-01-01

    Full Text Available In this paper an analytical sizing-design procedure for a typical permanent magnet flux-switching machine (PMFSM with 12 stator and respectively 10 rotor poles is presented. An optimal design, based on Hooke-Jeeves method with the objective functions of maximum torque density, is performed. The results were validated via two dimensions finite element analysis (2D-FEA applied on the optimized structure. The influence of the permanent magnet (PM dimensions and type, respectively of the rotor poles' shape on the machine performance were also studied via 2D-FEA.

  18. NOAA Climate Data Record (CDR) of MSU and AMSU-A Mean Layer Temperatures, UAH Version 6.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset includes monthly gridded temperature anomalies on a global 2.5 x 2.5 degree grid derived from Microwave Sounding Unit (MSU) and Advanced Microwave...

  19. MSU 1.6 GeV/c beam analysis system

    International Nuclear Information System (INIS)

    Nolen, J.A. Jr.

    1981-01-01

    This report describes the design of the beam analysis system which is to prepare the beam for the large high-resolution spectrograph to be used with the superconducting heavy ion cyclotrons at MSU. The system has a momentum resolving power of over 20,000 with a 1 mm object slit and is of a very flexible, modular design which is readily adaptable to other applications

  20. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  1. Investigations on the performance of ultrasonic drilling process with special reference to precision machining of advanced ceramics

    International Nuclear Information System (INIS)

    Adithan, M.; Laroiya, S.C.

    1997-01-01

    Advanced ceramics are assuming an important role in modern industrial technology. The applications and advantages of using advanced ceramics are many. There are several reasons why we should go in for machining of advanced ceramics after their compacting and sintering. These are discussed in this paper. However, precision machining of advanced ceramics must be economical. Critical technological issues to be addressed in cost effective machining of ceramics include design of machine tools, tooling arrangements, improved yield and precision, relationship of part dimensions and finish specifications to functional performance, and on-line inspection. Considering the above ultrasonic drilling is an important process used for the precision machining of advanced ceramics. Extensive studies on tool wear occurring in the ultrasonic machining of advanced ceramics have been carried out. In addition, production accuracy of holes drilled, surface finish obtained and surface integrity aspects in the machining of advanced ceramics have also been investigated. Some specific findings with reference to surface integrity are: a) there were no cracks or micro-cracks developed during or after ultrasonic machining of advanced ceramics, b) while machining Hexoloy alpha silicon carbide a recast layer is formed as a result of ultrasonic machining. This is attributed to the viscous heating resulting from high energy impacts during ultrasonic machining. While machining all other types of ceramics no such formation of recast layer was observed, and , c) there is no change in the microstructure of the advanced ceramics as a result of ultrasonic machining

  2. Teaching Machines, Programming, Computers, and Instructional Technology: The Roots of Performance Technology.

    Science.gov (United States)

    Deutsch, William

    1992-01-01

    Reviews the history of the development of the field of performance technology. Highlights include early teaching machines, instructional technology, learning theory, programed instruction, the systems approach, needs assessment, branching versus linear program formats, programing languages, and computer-assisted instruction. (LRW)

  3. Effectiveness and resolution of tests for evaluating the performance of cutting fluids in machining aerospace alloys

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Axinte, Dragos A.

    2008-01-01

    The paper discusses effectiveness and resolution of five cutting tests (turning, milling, drilling, tapping, VIPER grinding) and their quality output measures used in a multi-task procedure for evaluating the performance of cutting fluids when machining aerospace materials. The evaluation takes...

  4. Construction and performance of the scanning and measuring machine HOLMES used for bubble chamber holograms

    International Nuclear Information System (INIS)

    Drevermann, H.; Geissler, K.K.; Johansson, K.E.

    1985-01-01

    The construction and performance of the scanning and measuring machine HOLMES are described. It has been used to analyse in-line holograms taken with the small bubble chamber HOBC. A total of 8000 holograms has up to now been analysed on HOLMES. (orig.)

  5. Field weakening performance of flux-switching machines for hybrid/electric vehicles

    NARCIS (Netherlands)

    Tang, Y.; Paulides, J.J.H.; Lomonova, E.A.

    2015-01-01

    Flux-switching machines (FSMs) are a viable candidate for electric propulsion of hybrid/electric vehicles. This paper investigates the field weakening performance of FSMs. The investigation starts with general torque and voltage expressions, which reveal the relationships between certain parameters

  6. TRACEABILITY OF PRECISION MEASUREMENTS ON COORDINATE MEASURING MACHINESPERFORMANCE VERIFICATION OF CMMs

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo; Sobiecki, René; Tosello, Guido

    This document is used in connection with one exercise of 30 minutes duration as a part of the course VISION ONLINE – One week course on Precision & Nanometrology. The exercise concerns performance verification of the volumetric measuring capability of a small volume coordinate measuring machine...

  7. Effect of changing polarity of graphite tool/ Hadfield steel workpiece couple on machining performances in die sinking EDM

    Directory of Open Access Journals (Sweden)

    Özerkan Haci Bekir

    2017-01-01

    Full Text Available In this study, machining performance ouput parameters such as machined surface roughness (SR, material removal rate (MRR, tool wear rate (TWR, were experimentally examined and analyzed with the diversifying and changing machining parameters in (EDM. The processing parameters (input par. of this research are stated as tool material, peak current (I, pulse duration (ton and pulse interval (toff. The experimental machinings were put into practice by using Hadfield steel workpiece (prismatic and cylindrical graphite electrodes with kerosene dielectric at different machining current, polarity and pulse time settings. The experiments have shown that the type of tool material, polarity (direct polarity forms higher MRR, SR and TWR, current (high current lowers TWR and enhances MRR, TWR and pulse on time (ton=48□s is critical threshold value for MRR and TWR were influential on machining performance in electrical discharge machining.

  8. Performance and beam characteristics of the PANTAK THERAPAX HF225 X-ray therapy machine

    Energy Technology Data Exchange (ETDEWEB)

    Yiannakkaras, C; Papadopoulos, N; Christodoulides, G [Department of Medical Physics, Nicosia General Hospital, 1450 Nicosia (Cyprus)

    1999-12-31

    The performance and beam characteristics of the new PANTAK THERAPAX HF225 X-ray therapy machine have been measured, evaluated and discussed. Eight beam qualities within the working range of generating potentials between 50 and 225 kVp are used in our department. These beam qualities have been investigated in order to provide a data base specific to our machine. Beam Quality, Central Axis Depth Dose, Output, Relative Field Uniformity and Timer Error were investigated. (authors) 11 refs., 4 figs., 9 tabs.

  9. Performance Evaluation of Eleven-Phase Induction Machine with Different PWM Techniques

    Directory of Open Access Journals (Sweden)

    M.I. Masoud

    2015-06-01

    Full Text Available Multiphase induction machines are used extensively in low and medium voltage (MV drives. In MV drives, power switches have a limitation associated with switching frequency. This paper is a comparative study of the eleven-phase induction machine’s performance when used as a prototype and fed sinusoidal pulse-width-modulation (SPWM with a low switching frequency, selective harmonic elimination (SHE, and single pulse modulation (SPM techniques. The comparison depends on voltage/frequency controls for the same phase of voltage applied on the machine terminals for all previous techniques. The comparative study covers torque ripple, stator and harmonic currents, and motor efficiency.

  10. Design Enhancement and Performance Examination of External Rotor Switched Flux Permanent Magnet Machine for Downhole Application

    Science.gov (United States)

    Kumar, R.; Sulaiman, E.; Soomro, H. A.; Jusoh, L. I.; Bahrim, F. S.; Omar, M. F.

    2017-08-01

    The recent change in innovation and employments of high-temperature magnets, permanent magnet flux switching machine (PMFSM) has turned out to be one of the suitable contenders for seaward boring, however, less intended for downhole because of high atmospheric temperature. Subsequently, this extensive review manages the design enhancement and performance examination of external rotor PMFSM for the downhole application. Preparatory, the essential design parameters required for machine configuration are computed numerically. At that point, the design enhancement strategy is actualized through deterministic technique. At last, preliminary and refined execution of the machine is contrasted and as a consequence, the yield torque is raised from 16.39Nm to 33.57Nm while depreciating the cogging torque and PM weight up to 1.77Nm and 0.79kg, individually. In this manner, it is inferred that purposed enhanced design of 12slot-22pole with external rotor is convenient for the downhole application.

  11. Manufacturing and performance tests of in-pile creep measuring machine of zirconium alloys

    International Nuclear Information System (INIS)

    Choi, Y.; Kim, B. G.; Kang, Y. H.

    2000-01-01

    A mock-up of the in-pile creep test machine of zirconium alloys for HANARO was designed and manufactured, which performance tests were carried. The dimension of the in-pile creep machine is 55 mm in diameter and 700 mm in length for HANARO, respectively. Load is transferred to specimen by through the working mechanisms in which the contraction of bellows by gas pressure moves a yoke and an upper grip connected to a specimen, simultaneously. It was observed that the extension of the specimen mounted in grips was transferred to a linear voltage differential transformer perfectly by a yoke and a push rod in a bearing. The displacement of specimen with applied pressure was determined with the LVDT and a pressure gauge, respectively. Resultant stress-strain behaviors of the specimen was determined by the displacement-applied gas pressure curve, which showed similar values obtained with a standard tensile test machine

  12. Design of Parameter Independent, High Performance Sensorless Controllers for Permanent Magnet Synchronous Machines

    DEFF Research Database (Denmark)

    Xie, Ge

    . The transient fluctuation of the estimated rotor position error is around 20 degrees with a step load torque change from 0% to 100% of the rated torque. The position error in steady state is within ±2 electrical degrees for the best case. The proposed method may also be used for e.g. online machine parameter......The Permanent Magnet Synchronous Machine (PMSM) has become an attractive candidate for various industrial applications due to its high efficiency and torque density. In the PMSM drive system, simple and robust control methods play an important role in achieving satisfactory drive performances....... For reducing the cost and increasing the reliability of the drive system, eliminating the mechanical sensor brings a lot advantages to the PMSM drive system. Therefore, sensorless control was developed and has been increasingly used in different PMSM drive systems in the last 20 years. However, machine...

  13. Influence of Workpiece Material on Tool Wear Performance and Tribofilm Formation in Machining Hardened Steel

    Directory of Open Access Journals (Sweden)

    Junfeng Yuan

    2016-04-01

    Full Text Available In addition to the bulk properties of a workpiece material, characteristics of the tribofilms formed as a result of workpiece material mass transfer to the friction surface play a significant role in friction control. This is especially true in cutting of hardened materials, where it is very difficult to use liquid based lubricants. To better understand wear performance and the formation of beneficial tribofilms, this study presents an assessment of uncoated mixed alumina ceramic tools (Al2O3+TiC in the turning of two grades of steel, AISI T1 and AISI D2. Both workpiece materials were hardened to 59 HRC then machined under identical cutting conditions. Comprehensive characterization of the resulting wear patterns and the tribofilms formed at the tool/workpiece interface were made using X-ray Photoelectron Spectroscopy and Scanning Electron Microscopy. Metallographic studies on the workpiece material were performed before the machining process and the surface integrity of the machined part was investigated after machining. Tool life was 23% higher when turning D2 than T1. This improvement in cutting tool life and wear behaviour was attributed to a difference in: (1 tribofilm generation on the friction surface and (2 the amount and distribution of carbide phases in the workpiece materials. The results show that wear performance depends both on properties of the workpiece material and characteristics of the tribofilms formed on the friction surface.

  14. Using social media and machine learning to predict financial performance of a company

    OpenAIRE

    Forouzani, Sepehr

    2016-01-01

    Social media have recently become one of the most popular communicating form of media for numerous number of people. the text and posts shared on social media is widely used by researcher to analyze, study and relate them to various fields. In this master thesis, sentiment analysis has been performed on posts containing information about two companies that are shared on Twitter, and machine learning algorithms has been used to predict the financial performance of these companies.

  15. PROCESSING OF SOFT MAGNETIC MATERIALS BY POWDER METALLURGY AND ANALYSIS OF THEIR PERFORMANCE IN ELECTRICAL MACHINES

    Directory of Open Access Journals (Sweden)

    W. H. D. Luna

    2017-12-01

    Full Text Available This article presents the use of finite elements to analyze the yield of electric machines based on the use of different soft magnetic materials for the rotor and the stator, in order to verify the performance in electric machine using powder metallurgy. Traditionally, the cores of electric machines are built from rolled steel plates, thus the cores developed in this work are obtained from an alternative process known as powder metallurgy, where powders of soft magnetic materials are compacted and sintered. The properties of interest were analyzed (magnetic, electric and mechanical properties and they were introduced into the software database. The topology of the rotor used was 400 W three-phase synchronous motor manufactured by WEG Motors. The results show the feasibility to replace the metal sheets of the electric machines by solid blocks obtained by powder metallurgy process with only 0.37% yield losses. In addition, the powder metallurgical process reduces the use of raw materials and energy consumption per kg of raw material processed.

  16. Implementation of Total Productive Maintenance (TPM to Improve Sheeter Machine Performance

    Directory of Open Access Journals (Sweden)

    Candra Nofri Eka

    2017-01-01

    Full Text Available This paper purpose is an evaluation of TPM implementation, as a case study at sheeter machine cut size line 5 finishing department, PT RAPP, Indonesia. Research methodology collected the Overall Equipment Effectiveness (OEE data of sheeter machine and computed its scores. Then, OEE analysis big losses, statistical analysis using SPSS 20 and focused maintenance evaluation of TPM were performed. The data collected to machine sheeter’s production for 10 months (January-October 2016. The data analyses was resulted the OEE average score of 82.75%. This score was still below the world class OEE (85% and the company target (90%. Based the big losses of OEE analysis was obtained the reduce speed losses, which most significant losses of OEE scores. The reduce speed losses value was 44.79% of total losses during the research period. The high score of these losses due to decreasing of machine production speed by operators, which intended to improve the quality of resulting products. The OEE scores statistical analysis was found breakdown losses and reduces speed losses, which significantly affected to OEE scores. Implementations of focused maintenance of TPM in the case study may need to improve because there were still occurred un-expecting losses during the research period.

  17. PGHPF – An Optimizing High Performance Fortran Compiler for Distributed Memory Machines

    Directory of Open Access Journals (Sweden)

    Zeki Bozkus

    1997-01-01

    Full Text Available High Performance Fortran (HPF is the first widely supported, efficient, and portable parallel programming language for shared and distributed memory systems. HPF is realized through a set of directive-based extensions to Fortran 90. It enables application developers and Fortran end-users to write compact, portable, and efficient software that will compile and execute on workstations, shared memory servers, clusters, traditional supercomputers, or massively parallel processors. This article describes a production-quality HPF compiler for a set of parallel machines. Compilation techniques such as data and computation distribution, communication generation, run-time support, and optimization issues are elaborated as the basis for an HPF compiler implementation on distributed memory machines. The performance of this compiler on benchmark programs demonstrates that high efficiency can be achieved executing HPF code on parallel architectures.

  18. ASSESSMENT OF PERFORMANCES OF VARIOUS MACHINE LEARNING ALGORITHMS DURING AUTOMATED EVALUATION OF DESCRIPTIVE ANSWERS

    Directory of Open Access Journals (Sweden)

    C. Sunil Kumar

    2014-07-01

    Full Text Available Automation of descriptive answers evaluation is the need of the hour because of the huge increase in the number of students enrolling each year in educational institutions and the limited staff available to spare their time for evaluations. In this paper, we use a machine learning workbench called LightSIDE to accomplish auto evaluation and scoring of descriptive answers. We attempted to identify the best supervised machine learning algorithm given a limited training set sample size scenario. We evaluated performances of Bayes, SVM, Logistic Regression, Random forests, Decision stump and Decision trees algorithms. We confirmed SVM as best performing algorithm based on quantitative measurements across accuracy, kappa, training speed and prediction accuracy with supplied test set.

  19. Global Warming Estimation from MSU: Correction for Drift and Calibration Errors

    Science.gov (United States)

    Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz), made in the nadir direction from sequential, sun-synchronous, polar-orbiting NOAA morning satellites (NOAA 6, 10 and 12 that have about 7am/7pm orbital geometry) and afternoon satellites (NOAA 7, 9, 11 and 14 that have about 2am/2pm orbital geometry) are analyzed in this study to derive global temperature trend from 1980 to 1998. In order to remove the discontinuities between the data of the successive satellites and to get a continuous time series, first we have used shortest possible time record of each satellite. In this way we get a preliminary estimate of the global temperature trend of 0.21 K/decade. However, this estimate is affected by systematic time-dependent errors. One such error is the instrument calibration error. This error can be inferred whenever there are overlapping measurements made by two satellites over an extended period of time. From the available successive satellite data we have taken the longest possible time record of each satellite to form the time series during the period 1980 to 1998 to this error. We find we can decrease the global temperature trend by about 0.07 K/decade. In addition there are systematic time dependent errors present in the data that are introduced by the drift in the satellite orbital geometry arises from the diurnal cycle in temperature which is the drift related change in the calibration of the MSU. In order to analyze the nature of these drift related errors the multi-satellite Ch 2 data set is partitioned into am and pm subsets to create two independent time series. The error can be assessed in the am and pm data of Ch 2 on land and can be eliminated. Observations made in the MSU Ch 1 (50.3 GHz) support this approach. The error is obvious only in the difference between the pm and am observations of Ch 2 over the ocean. We have followed two different paths to assess the impact of the errors on the global temperature trend. In one path the

  20. Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

    Science.gov (United States)

    Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

    2014-09-04

    In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

  1. Performance of palm oil as a biobased machining lubricant when drilling inconel 718

    Directory of Open Access Journals (Sweden)

    Abd Rahim Erween

    2017-01-01

    Full Text Available Metalworking fluid acts as cooling and lubrication agent at the cutting zone in the machining process. However, conventional Metalworking fluid such mineral oil gives negative impact on the human and environment. Therefore, the manufacture tends to substitute the mineral oil to bio-based oil such as vegetables and synthetic oil. In this paper, the drilling experiment was carried out to evaluate the efficiency of palm oil and compare it with minimal quantity lubrication technique using synthetic ester, flood coolant and air blow with respect to cutting temperature, cutting force, torque and tool life. The experimental results showed that the application of palm oil under minimal quantity lubrication condition as the cutting fluid was more efficient process as it improves the machining performances.

  2. Transducer-actuator systems and methods for performing on-machine measurements and automatic part alignment

    Science.gov (United States)

    Barkman, William E.; Dow, Thomas A.; Garrard, Kenneth P.; Marston, Zachary

    2016-07-12

    Systems and methods for performing on-machine measurements and automatic part alignment, including: a measurement component operable for determining the position of a part on a machine; and an actuation component operable for adjusting the position of the part by contacting the part with a predetermined force responsive to the determined position of the part. The measurement component consists of a transducer. The actuation component consists of a linear actuator. Optionally, the measurement component and the actuation component consist of a single linear actuator operable for contacting the part with a first lighter force for determining the position of the part and with a second harder force for adjusting the position of the part. The actuation component is utilized in a substantially horizontal configuration and the effects of gravitational drop of the part are accounted for in the force applied and the timing of the contact.

  3. Impact of Health Care Employees’ Job Satisfaction on Organizational Performance Support Vector Machine Approach

    Directory of Open Access Journals (Sweden)

    CEMIL KUZEY

    2018-01-01

    Full Text Available This study is undertaken to search for key factors that contribute to job satisfaction among health care workers, and also to determine the impact of these underlying dimensions of employee satisfaction on organizational performance. Exploratory Factor Analysis (EFA is applied to initially uncover the key factors, and then, in the next stage of analysis, a popular data mining technique, Support Vector Machine (SVM is employed on a sample of 249 to determine the impact of job satisfaction factors on organizational performance. According to the proposed model, the main factors are revealed to be management’s attitude, pay/reward, job security and colleagues.

  4. A Navier-Strokes Chimera Code on the Connection Machine CM-5: Design and Performance

    Science.gov (United States)

    Jespersen, Dennis C.; Levit, Creon; Kwak, Dochan (Technical Monitor)

    1994-01-01

    in-processor. Form explicit terms in y, then transpose so z-lines are in processor. Form explicit terms in z, then solve linear systems in the z-direction. Transpose to the y-direction, then solve linear systems in the y-direction. Finally transpose to the x direction and solve linear systems in the x-direction. This strategy avoids inter-processor communication when differencing and solving linear systems, but requires a large amount of communication when doing the transposes. The transpose method is more efficient than the non-transpose strategy when dealing with scalar pentadiagonal or block tridiagonal systems. For handling geometrically complex problems the chimera strategy was adopted. For multiple zone cases we compute on each zone sequentially (using the whole parallel machine), then send the chimera interpolation data to a distributed data structure (array) laid out over the whole machine. This information transfer implies an irregular communication pattern, and is the second possible barrier to an efficient algorithm. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran. We make use of the Connection Machine Scientific Software Library (CMSSL) for the linear solver and array transpose operations.

  5. Applying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction

    Directory of Open Access Journals (Sweden)

    Ruijian Zhang

    2017-12-01

    Full Text Available Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future day’s water quality in an easy and efficient way. The idea is to combine the traditional ways and the computer algorithms together. Using machine learning algorithms, the assessment of water quality will be far more efficient, and by generating the decision tree, the prediction will be quite accurate. The drawback of the machine learning modeling is that the execution takes quite long time, especially when we employ a better accuracy but more time-consuming algorithm in clustering. Therefore, we applied the high performance computing (HPC System to deal with this problem. Up to now, the pilot experiments have achieved very promising preliminary results. The visualized water quality assessment and prediction obtained from this project would be published in an interactive website so that the public and the environmental managers could use the information for their decision making.

  6. Comparing the performance of different meta-heuristics for unweighted parallel machine scheduling

    Directory of Open Access Journals (Sweden)

    Adamu, Mumuni Osumah

    2015-08-01

    Full Text Available This article considers the due window scheduling problem to minimise the number of early and tardy jobs on identical parallel machines. This problem is known to be NP complete and thus finding an optimal solution is unlikely. Three meta-heuristics and their hybrids are proposed and extensive computational experiments are conducted. The purpose of this paper is to compare the performance of these meta-heuristics and their hybrids and to determine the best among them. Detailed comparative tests have also been conducted to analyse the different heuristics with the simulated annealing hybrid giving the best result.

  7. Performance test of the prototype-unit for J-PARC machine protection system

    International Nuclear Information System (INIS)

    Sakaki, Hironao; Nakamura, Naoki; Takahashi, Hiroki; Yoshikawa, Hiroshi

    2004-03-01

    In High Intensity Proton Accelerator Project (J-PARC), the high-power proton beam is accelerated. If the beam in J-PARC is not stopped at a few micro seconds or less, the fatal thermal shock destruction is caused on the surface of accelerating structure, because of the high-power proton beam. To avoid the thermal shock damage, we designed the high-speed machine protection system. And, the prototype unit for the system was produced. This report shows the result of its performance test. (author)

  8. Performance Improvement of Servo Machine Low Speed Operation Using RBFN Disturbance Observer

    DEFF Research Database (Denmark)

    Lee, Kyo-Beum; Blaabjerg, Frede

    2004-01-01

    A new scheme to estimate the moment of inertia in the servo motor drive system in very low speed is proposed in this paper. The typical speed estimation scheme in most servo system for low speed operation is sensitive to the variation of machine parameters, especially the moment of inertia....... To estimate the motor inertia value, the observer using the Radial Basis Function Networks (RBFN) is applied. The effectiveness of the proposed inertia estimation method is verified by experiments. It is concluded that the speed control performance in the low speed region is improved with the proposed...

  9. Advances in three-dimensional field analysis and evaluation of performance parameters of electrical machines

    Science.gov (United States)

    Sivasubramaniam, Kiruba

    This thesis makes advances in three dimensional finite element analysis of electrical machines and the quantification of their parameters and performance. The principal objectives of the thesis are: (1)the development of a stable and accurate method of nonlinear three-dimensional field computation and application to electrical machinery and devices; and (2)improvement in the accuracy of determination of performance parameters, particularly forces and torque computed from finite elements. Contributions are made in two general areas: a more efficient formulation for three dimensional finite element analysis which saves time and improves accuracy, and new post-processing techniques to calculate flux density values from a given finite element solution. A novel three-dimensional magnetostatic solution based on a modified scalar potential method is implemented. This method has significant advantages over the traditional total scalar, reduced scalar or vector potential methods. The new method is applied to a 3D geometry of an iron core inductor and a permanent magnet motor. The results obtained are compared with those obtained from traditional methods, in terms of accuracy and speed of computation. A technique which has been observed to improve force computation in two dimensional analysis using a local solution of Laplace's equation in the airgap of machines is investigated and a similar method is implemented in the three dimensional analysis of electromagnetic devices. A new integral formulation to improve force calculation from a smoother flux-density profile is also explored and implemented. Comparisons are made and conclusions drawn as to how much improvement is obtained and at what cost. This thesis also demonstrates the use of finite element analysis to analyze torque ripples due to rotor eccentricity in permanent magnet BLDC motors. A new method for analyzing torque harmonics based on data obtained from a time stepping finite element analysis of the machine is

  10. Electrical performance of a string of magnets representing a half-cell of the LHC machine

    International Nuclear Information System (INIS)

    Rodriguez-Mateos, F.; Coull, L.; Dahlerup-Petersen, K.; Hagedorn, D.; Krainz, G.; Rijllart, A.; McInturff, A.

    1996-01-01

    Tests have been carried out on a string of prototype superconducting magnets, consisting of one double-quadrupole and two double-dipoles forming the major part of a half-cell of the LHC machine. The magnets are protected individually by cold diodes and quench heaters. The electrical aspects of these tests are described here. The performance during quench of the protection diodes and the associated interconnections was studied. Tests determined the magnet quench performance in training and at different ramp-rates, and investigated the inter-magnet propagation of quenches. Current lead and inter-magnet contact resistances were controlled and the performance of the power converter and the dump switches assessed

  11. Electrical performance of a string of magnets representing a half-cell of the LHC machine

    International Nuclear Information System (INIS)

    Rodriguez-Mateos, F.; Coull, L.; Dahlerup-Petersen, K.; Hagedorn, D.; Krainz, G.; Rijllart, A.; McInturff, A.

    1995-01-01

    Tests have been carried out on a string prototype superconducting magnets, consisting of one double-quadrupole and two double-dipoles forming the major part of a half-cell of the LHC machine. The magnets are protected individually by ''cold diodes'' and quench heaters. The electrical aspects of these tests are described here. The performance during quench of the protection diodes and the associated interconnections was studied. Tests determined the magnet quench performance in training and at different ramp-rates, and investigated the inter-magnet propagation of quenches. Current lead and inter-magnet contact resistances were controlled and the performance of the power converter and the dump switches assessed

  12. Predictive Power of Machine Learning for Optimizing Solar Water Heater Performance: The Potential Application of High-Throughput Screening

    Directory of Open Access Journals (Sweden)

    Hao Li

    2017-01-01

    Full Text Available Predicting the performance of solar water heater (SWH is challenging due to the complexity of the system. Fortunately, knowledge-based machine learning can provide a fast and precise prediction method for SWH performance. With the predictive power of machine learning models, we can further solve a more challenging question: how to cost-effectively design a high-performance SWH? Here, we summarize our recent studies and propose a general framework of SWH design using a machine learning-based high-throughput screening (HTS method. Design of water-in-glass evacuated tube solar water heater (WGET-SWH is selected as a case study to show the potential application of machine learning-based HTS to the design and optimization of solar energy systems.

  13. Performance of refrigerating machineries with new refrigerants; Performance des machines frigorifiques avec les nouveaux refrigerants

    Energy Technology Data Exchange (ETDEWEB)

    Bailly, A; Jurkowski, R [CIAT, 01 - Culoz (France)

    1998-12-31

    This paper reports on a comparative study of the thermal performances of different refrigerants like R-22, R-134a, R-404A and R-407C when used as possible substitutes for the HCFC22 refrigerant in a given refrigerating machinery equipped with compact high performance plate exchangers. Thermal performances are compared in identical operating conditions. The behaviour of the two-phase exchange coefficient is analyzed with respect to the different parameters. The composition of the mixture after one year of operation has been analyzed too and the influence of oil on the performances is studied. (J.S.)

  14. Performance of refrigerating machineries with new refrigerants; Performance des machines frigorifiques avec les nouveaux refrigerants

    Energy Technology Data Exchange (ETDEWEB)

    Bailly, A.; Jurkowski, R. [CIAT, 01 - Culoz (France)

    1997-12-31

    This paper reports on a comparative study of the thermal performances of different refrigerants like R-22, R-134a, R-404A and R-407C when used as possible substitutes for the HCFC22 refrigerant in a given refrigerating machinery equipped with compact high performance plate exchangers. Thermal performances are compared in identical operating conditions. The behaviour of the two-phase exchange coefficient is analyzed with respect to the different parameters. The composition of the mixture after one year of operation has been analyzed too and the influence of oil on the performances is studied. (J.S.)

  15. Smith machine counterbalance system affects measures of maximal bench press throw performance.

    Science.gov (United States)

    Vingren, Jakob L; Buddhadev, Harsh H; Hill, David W

    2011-07-01

    Equipment with counterbalance weight systems is commonly used for the assessment of performance in explosive resistance exercise movements, but it is not known if such systems affect performance measures. The purpose of this study was to determine the effect of using a counterbalance weight system on measures of smith machine bench press throw performance. Ten men and 14 women (mean ± SD: age, 25 ± 4 years; height, 173 ± 10 cm; weight, 77.7 ± 18.3 kg) completed maximal smith machine bench press throws under 4 different conditions (2 × 2; counterbalance × load): with or without a counterbalance weight system and using 'light' or 'moderate' net barbell loads. Performance variables (peak force, peak velocity, and peak power) were measured using a linear accelerometer attached to the barbell. The counterbalance weight system resulted in significant (p velocity (light: -0.49 ± 0.10 m·s; moderate: -0.33 ± 0.07 m·s), and peak power (light: -220 ± 43 W; moderate: -143 ± 28 W) compared with no counterbalance system for both load conditions. Load condition did not affect absolute or percentage reductions from the counterbalance weight system for any variable. In conclusion, the use of a counterbalance weight system reduces accelerometer-based performance measures for the bench press throw exercise at light and moderate loads. This reduction in measures is likely because of an increase in the external resistance during the movement, which results in a discrepancy between the manually input and the actual value for external load. A counterbalance weight system should not be used when measuring performance in explosive resistance exercises with an accelerometer.

  16. Nonplanar machines

    International Nuclear Information System (INIS)

    Ritson, D.

    1989-05-01

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

  17. LEBIT - a low-energy beam and ion trap facility at NSCL/MSU

    International Nuclear Information System (INIS)

    Schwarz, S.; Bollen, G.; Davies, D.; Lawton, D.; Lofy, P.; Morrissey, D. J.; Ottarson, J.; Ringle, R.; Schury, P.; Sun, T.; VanWasshenova, D.; Sun, T.; Weissman, L.; Wiggins, D.

    2003-01-01

    The Low Energy Beam and Ion Trap (LEBIT) Project aims to convert the high-energy exotic beams produced at NSCL/MSU into low-energy low-emittance beams. A combination of a high-pressure gas stopping cell and a radiofrequency quadrupole (RFQ) ion accumulator and buncher will be used to manipulate the beam accordingly. High-accuracy mass measurements on very short-lived isotopes with a 9.4 T Penning trap system will be the first experimental program to profit from the low-energy beams. The status of the project is presented with a focus on recent stopping tests of 100-140 MeV/A Ar18+ ions in a gas cell

  18. The low-energy-beam and ion-trap facility at NSCL/MSU

    CERN Document Server

    Schwarz, S; Lawton, D; Lofy, P; Morrissey, D J; Ottarson, J; Ringle, R; Schury, P; Sun, T; Varentsov, V; Weissman, L

    2003-01-01

    The goal of the low-energy-beam and ion-trap (LEBIT) project is to convert the high-energy exotic beams produced at NSCL/MSU into low-energy low-emittance beams. This beam manipulation will be done by a combination of a high-pressure gas stopping cell and a radio-frequency quadrupole ion accumulator and buncher. The first experimental program to profit from the low-energy beams produced will be high-accuracy mass measurements on very short-lived isotopes with a 9.4 T Penning trap system. The status of the project is presented with an emphasis on recent stopping tests range of 100 MeV/A sup 4 sup 0 Ar sup 1 sup 8 sup + ions in a gas cell.

  19. The low-energy-beam and ion-trap facility at NSCL/MSU

    Energy Technology Data Exchange (ETDEWEB)

    Schwarz, S. E-mail: schwarz@nscl.msu.edu; Bollen, G.; Lawton, D.; Lofy, P.; Morrissey, D.J.; Ottarson, J.; Ringle, R.; Schury, P.; Sun, T.; Varentsov, V.; Weissman, L

    2003-05-01

    The goal of the low-energy-beam and ion-trap (LEBIT) project is to convert the high-energy exotic beams produced at NSCL/MSU into low-energy low-emittance beams. This beam manipulation will be done by a combination of a high-pressure gas stopping cell and a radio-frequency quadrupole ion accumulator and buncher. The first experimental program to profit from the low-energy beams produced will be high-accuracy mass measurements on very short-lived isotopes with a 9.4 T Penning trap system. The status of the project is presented with an emphasis on recent stopping tests range of 100 MeV/A {sup 40}Ar{sup 18+} ions in a gas cell.

  20. The low-energy-beam and ion-trap facility at NSCL/MSU

    International Nuclear Information System (INIS)

    Schwarz, S.; Bollen, G.; Lawton, D.; Lofy, P.; Morrissey, D.J.; Ottarson, J.; Ringle, R.; Schury, P.; Sun, T.; Varentsov, V.; Weissman, L.

    2003-01-01

    The goal of the low-energy-beam and ion-trap (LEBIT) project is to convert the high-energy exotic beams produced at NSCL/MSU into low-energy low-emittance beams. This beam manipulation will be done by a combination of a high-pressure gas stopping cell and a radio-frequency quadrupole ion accumulator and buncher. The first experimental program to profit from the low-energy beams produced will be high-accuracy mass measurements on very short-lived isotopes with a 9.4 T Penning trap system. The status of the project is presented with an emphasis on recent stopping tests range of 100 MeV/A 40 Ar 18+ ions in a gas cell

  1. Assessing the Performance of a Machine Learning Algorithm in Identifying Bubbles in Dust Emission

    Science.gov (United States)

    Xu, Duo; Offner, Stella S. R.

    2017-12-01

    Stellar feedback created by radiation and winds from massive stars plays a significant role in both physical and chemical evolution of molecular clouds. This energy and momentum leaves an identifiable signature (“bubbles”) that affects the dynamics and structure of the cloud. Most bubble searches are performed “by eye,” which is usually time-consuming, subjective, and difficult to calibrate. Automatic classifications based on machine learning make it possible to perform systematic, quantifiable, and repeatable searches for bubbles. We employ a previously developed machine learning algorithm, Brut, and quantitatively evaluate its performance in identifying bubbles using synthetic dust observations. We adopt magnetohydrodynamics simulations, which model stellar winds launching within turbulent molecular clouds, as an input to generate synthetic images. We use a publicly available three-dimensional dust continuum Monte Carlo radiative transfer code, HYPERION, to generate synthetic images of bubbles in three Spitzer bands (4.5, 8, and 24 μm). We designate half of our synthetic bubbles as a training set, which we use to train Brut along with citizen-science data from the Milky Way Project (MWP). We then assess Brut’s accuracy using the remaining synthetic observations. We find that Brut’s performance after retraining increases significantly, and it is able to identify yellow bubbles, which are likely associated with B-type stars. Brut continues to perform well on previously identified high-score bubbles, and over 10% of the MWP bubbles are reclassified as high-confidence bubbles, which were previously marginal or ambiguous detections in the MWP data. We also investigate the influence of the size of the training set, dust model, evolutionary stage, and background noise on bubble identification.

  2. Performance of Rotary Cutter Type Breaking Machine for Breakingand Deshelling Cocoa Roasted Beans

    Directory of Open Access Journals (Sweden)

    Sukrisno Widyotomo

    2005-12-01

    Full Text Available Conversion of cocoa beans to chocolate product is, therefore, one of the promising alternatives to increase the value added of dried cocoa beans. On the other hand, the development of chocolate industry requires an appropriate technology that is not available yet for small or medium scale of business. Breaking and deshelling cocoa roasted beans is one important steps in cocoa processing to ascertain good chocolate quality. The aim of this research is to study performance of rotary cutter type breaking machine for breaking and deshelling cocoa roasted beans. Indonesian Coffee and Cocoa Research Institute has designed and tested a rotary cutter type breaking machine for breaking and deshelling cocoa roasted beans. Breaker unit has rotated by ½ HP power, single phase, 110/220 V and 1440 rpm. Transmission system that use for rotating breaker unit is pulley and single V belt. Centrifugal blower as separator unit between cotyledon and shell has specification 0.5 m 3 /min air flow, 780 Pa, 370 W, and 220 V. Field tests showed that the optimum capacity of the machine was 268 kg/h with 500 rpm speed of rotary cutter, 2,8 m/s separator air flow, and power require was 833 W. Percentage product in outlet 1 and 2 were 94.5% and 5.5%. Particle distribution from outlet 1 was 92% as cotyledon, 8% as shell in cotyledon and on outlet 2 was 97% as shell, 3% as cotyledon in shell. Key words:cocoa, breaking, rotary cutter, quality.

  3. Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Thrane, Jakob; Wass, Jesper; Piels, Molly

    2017-01-01

    Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

  4. Modification and Performance Evaluation of a Low Cost Electro-Mechanically Operated Creep Testing Machine

    OpenAIRE

    John J. MOMOH; Lanre Y. SHUAIB-BABATA; Gabriel O. ADELEGAN

    2010-01-01

    Existing mechanically operated tensile and creep testing machine was modified to a low cost, electro-mechanically operated creep testing machine capable of determining the creep properties of aluminum, lead and thermoplastic materials as a function of applied stress, time and temperature. The modification of the testing machine was necessitated by having an electro-mechanically operated creep testing machine as a demonstration model ideal for use and laboratory demonstrations, which will prov...

  5. Very Large-Scale Neighborhoods with Performance Guarantees for Minimizing Makespan on Parallel Machines

    NARCIS (Netherlands)

    Brueggemann, T.; Hurink, Johann L.; Vredeveld, T.; Woeginger, Gerhard

    2006-01-01

    We study the problem of minimizing the makespan on m parallel machines. We introduce a very large-scale neighborhood of exponential size (in the number of machines) that is based on a matching in a complete graph. The idea is to partition the jobs assigned to the same machine into two sets. This

  6. Machine site preparation improves seedling performance on a high-elevation site in southwest Oregon

    International Nuclear Information System (INIS)

    McNabb, D.H.; Baker-Katz, K.; Tesch, S.D.

    1993-01-01

    Douglas-fir (Pseudotsuga menziesii) seedlings planted on areas receiving one of four site-preparation treatments (scarify, scarify/till, soil removal, and soil removal/till) and on unprepared control areas were compared for 5 yr at a high-elevation, nutrient-poor site in the western Siskiyou Mountains of southwest Oregon. Fifth-year survival of seedlings was at least 85% among machine-prepared plots, compared to 42% on control plots. Cover of competing vegetation remained less than 25% during the period for all machine treatments. In contrast, vegetation cover on control plots was 30% at the time of planting and increased to nearly 75% after 5 yr. Competing vegetation clearly impeded seedling performance. The effects of unusually droughty conditions at the time of planting in 1982 were examined further by interplanting additional seedlings in the soil-removal treatment in 1985. The interplanting was followed by more normal spring precipitation, and seedlings grew better over 5 yr than those planted in 1982. The slow recovery of competing vegetation and generally poor seedling growth on all treatments during both planting years are attributed to low soil fertility

  7. Short-Term Solar Forecasting Performance of Popular Machine Learning Algorithms: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Elgindy, Tarek [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dobbs, Alex [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-10-03

    A framework for assessing the performance of short-term solar forecasting is presented in conjunction with a range of numerical results using global horizontal irradiation (GHI) from the open-source Surface Radiation Budget (SURFRAD) data network. A suite of popular machine learning algorithms is compared according to a set of statistically distinct metrics and benchmarked against the persistence-of-cloudiness forecast and a cloud motion forecast. Results show significant improvement compared to the benchmarks with trade-offs among the machine learning algorithms depending on the desired error metric. Training inputs include time series observations of GHI for a history of years, historical weather and atmospheric measurements, and corresponding date and time stamps such that training sensitivities might be inferred. Prediction outputs are GHI forecasts for 1, 2, 3, and 4 hours ahead of the issue time, and they are made for every month of the year for 7 locations. Photovoltaic power and energy outputs can then be made using the solar forecasts to better understand power system impacts.

  8. Strategic Performance Measurement Using Balanced Scorecard: A Case of Machine Tool Industry

    Directory of Open Access Journals (Sweden)

    Kshatriya Anil

    2017-02-01

    Full Text Available This paper focuses on implementation, monitoring, and application of balanced scorecard (BSC techniques in an organization involved in providing machine tool solutions to the industrial sector. The growth of the company considered in real time constituted improvements of both top and bottom lines. In the industry under consideration, it was observed that in our company, the top line was steadily growing but not the bottom line. This is when we started getting down to brass tacks and strategically focusing on growth in overall profits of the company. This included growing revenues by improving of EBITDA (earnings before interests, taxes, depreciation, and amortization and by increasing efficiency (i.e., cutting costs. These improvements were implemented by chalking out a comprehensive BSC designed to suit the machine tool industry. The four perspectives of the management, namely, internal business process, organizational learning, financial perspective, and customer perspective, have been considered lucidly and enunciate the parameters that affect the BSC very aptly. The BSC designed considered 9 objectives and 27 relative measures of these factors to quantify the various quantitative and qualitative dimensions that affect the company’s performance. A Balanced Lean Index (BL Score was used to measure the results for company X.

  9. Application of rare-earth magnets in high-performance electric machines

    International Nuclear Information System (INIS)

    Ramsden, V.S.

    1998-01-01

    Some state of the art developments of high-performance machines using rare-earth magnets are reviewed with particular examples drawn from a number of novel machine designs developed jointly by the Faculty of Engineering, University of Technology, Sydney (UTS) and CSIRO Telecommunications and Industrial Physics. These designs include an 1800 W, 1060 rev/min, 98% efficient solar car in-wheel motor using a Halbach magnet array, axial flux, and ironless winding; a 1200 W, 3000 rev/min, 91% efficient solar-powered, water-filled, submersible, bore-hole pump motor using a surface magnet rotor; a 500 W, 10000 rev/min, 87% efficient, oil-filled, oil-well tractor motor using a 2-pole cylindrical magnet rotor and slotless winding; a 75 kW, 48000 rev/min, 97% efficient, high-speed compressor drive with 2-pole cylindrical magnet rotor, slotted stator, and refrigerant cooling; and a 20 kW, 211 rev/min, 87% efficient, direct-drive generator for wind turbines with very low starting torque using an outer rotor with surface magnets and a slotted stator. (orig.)

  10. Performance Evaluation of a Bench-Top Precision Glass Molding Machine

    Directory of Open Access Journals (Sweden)

    Peter Wachtel

    2013-01-01

    Full Text Available A Dyna Technologies Inc. GP-5000HT precision glass molding machine has been found to be a capable tool for bridging the gap between research-level instruments and the higher volume production machines typically used in industry, providing a means to apply the results of rigorous instrumentation analysis performed in the lab to industrial PGM applications. The GP-5000HT's thermal and mechanical functionality is explained and characterized through the measurement baseline functionality and the associated error. These baseline measurements were used to determine the center thickness repeatability of pressed glass parts, which is the main metric used in industrial pressing settings. The baselines and the repeatability tests both confirmed the need for three warm-up pressing cycles before the press reaches a thermal steady state. The baselines used for pressing a 2 mm glass piece to a 1 mm target center thickness yielded an average center thickness of 1.001 mm and a standard deviation of thickness of 0.0055 mm for glass samples pressed over 3 consecutive days. The baseline tests were then used to deconvolve the sources of error of final pressed piece center thickness.

  11. Investigation of tool engagement and cutting performance in machining a pocket

    Science.gov (United States)

    Adesta, E. Y. T.; Hamidon, R.; Riza, M.; Alrashidi, R. F. F. A.; Alazemi, A. F. F. S.

    2018-01-01

    This study investigates the variation of tool engagement for different profile of cutting. In addition, behavior of cutting force and cutting temperature for different tool engagements for machining a pocket also been explored. Initially, simple tool engagement models were developed for peripheral and slot cutting for different types of corner. Based on these models, the tool engagements for contour and zig zag tool path strategies for a rectangular shape pocket with dimension 80 mm x 60 mm were analyzed. Experiments were conducted to investigate the effect of tool engagements on cutting force and cutting temperature for the machining of a pocket of AISI H13 material. The cutting parameters used were 150m/min cutting speed, 0.05mm/tooth feed, and 0.1mm depth of cut. Based on the results obtained, the changes of cutting force and cutting temperature performance there exist a relationship between cutting force, cutting temperature and tool engagement. A higher cutting force and cutting temperature is obtained when the cutting tool goes through up milling and when the cutting tool makes a full engagement with the workpiece.

  12. Performance of machine-learning scoring functions in structure-based virtual screening.

    Science.gov (United States)

    Wójcikowski, Maciej; Ballester, Pedro J; Siedlecki, Pawel

    2017-04-25

    Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and -0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary).

  13. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

    Science.gov (United States)

    Giraldo, Sergio I.; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules

  14. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

    Directory of Open Access Journals (Sweden)

    Sergio Ivan Giraldo

    2016-12-01

    Full Text Available Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1 quantitatively evaluate the accuracy of the induced models, (2 analyse the relative importance of the considered musical features, (3 discuss some of the learnt expressive performance rules in the context of previous work, and (4 assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules’ performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the

  15. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music.

    Science.gov (United States)

    Giraldo, Sergio I; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules.

  16. The performance of disk arrays in shared-memory database machines

    Science.gov (United States)

    Katz, Randy H.; Hong, Wei

    1993-01-01

    In this paper, we examine how disk arrays and shared memory multiprocessors lead to an effective method for constructing database machines for general-purpose complex query processing. We show that disk arrays can lead to cost-effective storage systems if they are configured from suitably small formfactor disk drives. We introduce the storage system metric data temperature as a way to evaluate how well a disk configuration can sustain its workload, and we show that disk arrays can sustain the same data temperature as a more expensive mirrored-disk configuration. We use the metric to evaluate the performance of disk arrays in XPRS, an operational shared-memory multiprocessor database system being developed at the University of California, Berkeley.

  17. Performance optimization in electro- discharge machining using a suitable multiresponse optimization technique

    Directory of Open Access Journals (Sweden)

    I. Nayak

    2017-06-01

    Full Text Available In the present research work, four different multi response optimization techniques, viz. multiple response signal-to-noise (MRSN ratio, weighted signal-to-noise (WSN ratio, Grey relational analysis (GRA and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian methods have been used to optimize the electro-discharge machining (EDM performance characteristics such as material removal rate (MRR, tool wear rate (TWR and surface roughness (SR simultaneously. Experiments have been planned on a D2 steel specimen based on L9 orthogonal array. Experimental results are analyzed using the standard procedure. The optimum level combinations of input process parameters such as voltage, current, pulse-on-time and pulse-off-time, and percentage contributions of each process parameter using ANOVA technique have been determined. Different correlations have been developed between the various input process parameters and output performance characteristics. Finally, the optimum performances of these four methods are compared and the results show that WSN ratio method is the best multiresponse optimization technique for this process. From the analysis, it is also found that the current has the maximum effect on the overall performance of EDM operation as compared to other process parameters.

  18. Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

    Science.gov (United States)

    Hung, Andrew J; Chen, Jian; Che, Zhengping; Nilanon, Tanachat; Jarc, Anthony; Titus, Micha; Oh, Paul J; Gill, Inderbir S; Liu, Yan

    2018-05-01

    Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting. The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p algorithm in predicting, were largely related to camera manipulation. To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

  19. NOAA Climate Data Record of Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU-A) Mean Layer Temperature, Version 3.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains three channel-based, monthly gridded atmospheric layer temperature Climate Data Records generated by merging nine MSU NOAA polar orbiting...

  20. Performance analysis of parallel identical machines with a generalized shortest queue arrival mechanism

    NARCIS (Netherlands)

    van Houtum, Geert-Jan; Adan, I.J.B.F.; Wessels, J.; Zijm, Willem H.M.

    In this paper we study a production system consisting of a group of parallel machines producing multiple job types. Each machine has its own queue and it can process a restricted set of job types only. On arrival a job joins the shortest queue among all queues capable of serving that job. Under the

  1. Machine performance and its effects on experiments in JT-60U

    International Nuclear Information System (INIS)

    Kondo, I.

    1995-01-01

    The operational results of JT-60U were reviewed in light of the strategy made at the design stage. The operational plan for better confinement shifted from that of low q to high poloidal beta plasma configuration with higher q value according to the revealed machine properties. Some technical and operational skills helped bring about the recent results out of the machine. (orig.)

  2. Transient changes in shallow groundwater chemistry during the MSU ZERT CO2 injection experiment

    Science.gov (United States)

    Apps, J.A.; Zheng, Lingyun; Spycher, N.; Birkholzer, J.T.; Kharaka, Y.; Thordsen, J.; Kakouros, E.; Trautz, R.

    2011-01-01

    Food-grade CO2 was injected into a shallow aquifer through a perforated pipe placed horizontally 1-2 m below the water table at the Montana State University Zero Emission Research and Technology (MSU-ZERT) field site at Bozeman, Montana. The possible impact of elevated CO2 levels on groundwater quality was investigated by analyzing 80 water samples taken before, during, and following CO2 injection. Field determinations and laboratory analyses showed rapid and systematic changes in pH, alkalinity, and conductance, as well as increases in the aqueous concentrations of trace element species. The geochemical data were first evaluated using principal component analysis (PCA) in order to identify correlations between aqueous species. The PCA findings were then used in formulating a geochemical model to simulate the processes likely to be responsible for the observed increases in the concentrations of dissolved constituents. Modeling was conducted taking into account aqueous and surface complexation, cation exchange, and mineral precipitation and dissolution. Reasonable matches between measured data and model results suggest that: (1) CO2 dissolution in the groundwater causes calcite to dissolve. (2) Observed increases in the concentration of dissolved trace metals result likely from Ca+2-driven ion exchange with clays (smectites) and sorption/desorption reactions likely involving Fe (hydr)oxides. (3) Bicarbonate from CO2 dissolution appears to compete for sorption with anionic species such as HAsO4-2, potentially increasing dissolved As levels in groundwater. ?? 2011 Published by Elsevier Ltd.

  3. Inventory management performance in machine tool SMEs: What factors do influence them?

    Directory of Open Access Journals (Sweden)

    Rajeev Narayana Pillai

    2010-12-01

    Full Text Available Small and Medium Enterprises (SMEs are one of the principal driving forces in the development of an economy because of its significant contribution in terms of number of enterprises, employment, output and exports in most developing as well as developed countries. But SMEs, particularly in developing countries like India, face constraints in key areas such as technology, finance, marketing and human resources. Moreover these SMEs have been exposed to intense competition since early 1990s because of globalization. However, globalization, the process of continuing integration of the countries in the world has opened up new opportunities for SMEs of developing countries to cater to wider international market which brings out the need for these SMEs to develop competitiveness for their survival as well as growth. It is observed from literature that pursuing appropriate IM practice is one of the ways of acquiring competitiveness among others, by effectively managing and minimizing inventory investment. Inventory management can therefore be one of the crucial determinants of competitiveness as well as operational performance of SMEs in inventory intensive manufacturing industries. The key issue is whether Indian SMEs pursue better IM practices with an intension to reduce their inventory cost and enhance their competitiveness. If so, what are the IM practices pursued by these enterprises? What are the factors which influence the inventory cost and IM performance of enterprises? These questions have been addressed in this study with reference to machine tool SMEs located in the city of Bangalore, India.

  4. Research on Dynamic Models and Performances of Shield Tunnel Boring Machine Cutterhead Driving System

    Directory of Open Access Journals (Sweden)

    Xianhong Li

    2013-01-01

    Full Text Available A general nonlinear time-varying (NLTV dynamic model and linear time-varying (LTV dynamic model are presented for shield tunnel boring machine (TBM cutterhead driving system, respectively. Different gear backlashes and mesh damped and transmission errors are considered in the NLTV dynamic model. The corresponding multiple-input and multiple-output (MIMO state space models are also presented. Through analyzing the linear dynamic model, the optimal reducer ratio (ORR and optimal transmission ratio (OTR are obtained for the shield TBM cutterhead driving system, respectively. The NLTV and LTV dynamic models are numerically simulated, and the effects of physical parameters under various conditions of NLTV dynamic model are analyzed. Physical parameters such as the load torque, gear backlash and transmission error, gear mesh stiffness and damped, pinions inertia and damped, large gear inertia and damped, and motor rotor inertia and damped are investigated in detail to analyze their effects on dynamic response and performances of the shield TBM cutterhead driving system. Some preliminary approaches are proposed to improve dynamic performances of the cutterhead driving system, and dynamic models will provide a foundation for shield TBM cutterhead driving system's cutterhead fault diagnosis, motion control, and torque synchronous control.

  5. High catalytic activity and stability of Ni/CexZr1-xO2/MSU-H for CH4/CO2 reforming reaction

    Science.gov (United States)

    Chang, Xiaoqian; Liu, Bingsi; Xia, Hong; Amin, Roohul

    2018-06-01

    How to reduce emission of CO2 as greenhouse gases, which resulted in global warming, is of very important significance. A series of Ni/CexZr1-xO2/MSU-H catalysts was prepared by means of hexagonally ordered mesoporous MSU-H with thermal and hydrothermal stabilities, which is cheap and can be synthesized in the large scale. The 10%Ni/Ce0.75Zr0.25O2/MSU-H catalyst presents high catalytic activity, stability and the ability of coke-resistance for CH4/CO2 reforming reaction due to high SBET (428 m2/g) and smaller Nio nanoparticle size (3.14 nm). The high dispersed Nio nanoparticles over MSU-H promoted the decomposition of CH4 and the carbon species accumulated on active Nio sites reacting with crystal lattice oxygen in Ce0.75Zr0.25O2 to form CO molecules. In the meantime, the remained oxygen vacancies on the interface between Nio and Ce0.75Zr0.25O2 could be supplemented via CO2. HRTEM images and XRD results of Ni/Ce0.75Zr0.25O2/MSU-H verified that high dispersion of Ni nanoparticles over Ni/Ce0.75Zr0.25O2/MSU-H correlated closely with the synergistic action between Ce0.75Zr0.25O2 and MSU-H as well as hexagonally ordered structure of MSU-H, which can provide effectively the oxygen storage capacity and inhibit the formation of coke.

  6. Development and operating performance of the refuelling machine of the Fugen

    International Nuclear Information System (INIS)

    Kaneko, Jun; Kasai, Yoshimitsu; Takeshita, Norito; Ohta, Takeo

    1985-01-01

    In the advanced thermal reactor ''Fugen'' power station, with the refuelling machine the fuel replacement during operation is made through the reactor bottom. Its design was started in 1967 and up to 1975 various tests were conducted. Fugen's refuelling machine has thus been used from the initial fuel loading in 1978 and handled so far about 1300 fuel assemblies in seven times of the refuelling. In the stage of Fugen operation there occurred failure of the grab drive due to crud, etc. At present, with such troubles all eliminated, the refuelling machine is in steady operation with proper maintenance. The results with Fugen's refuelling machine are reflected in the development of the refuelling machine for the demonstration ATR. (Mori, K.)

  7. Effect of cutting parameters on sustainable machining performance of coated carbide tool in dry turning process of stainless steel 316

    Science.gov (United States)

    Bagaber, Salem A.; Yusoff, Ahmed Razlan

    2017-04-01

    The manufacturing industry aims to produce many products of high quality with relatively less cost and time. Different cutting parameters affect the machining performance of surface roughness, cutting force, and material removal rate. Nevertheless, a few studies reported on the effects of sustainable factors such as power consumed, cycle time during machining, and tool life on the dry turning of AISI 316. The present study aims to evaluate the machining performance of coated carbide in the machining of hard steel AISI 316 under the dry turning process. The influence of cutting parameters of cutting speed, feed rate, and depth of cut with their five (5) levels is established by a central composite design. Highly significant parameters were determined by analysis of variance (ANOVA), and the main effects of power consumed and time during machining, surface roughness, and tool wear were observed. Results showed that the cutting speed was proportional to power consumption and tool wear. Meanwhile, insignificant to surface roughness, feed rate most significantly affected surface roughness and power consumption followed by depth of cut.

  8. Investigations of Effect of Rotary EDM Electrode on Machining Performance of Al6061 Alloy

    Science.gov (United States)

    Robinson Smart, D. S.; Jenish Smart, Joses; Periasamy, C.; Ratna Kumar, P. S. Samuel

    2018-04-01

    Electric Discharge Machining is an essential process which is being used for machining desired shape using electrical discharges which creates sparks. There will be electrodes subjected to electric voltage and which are separated by a dielectric liquid. Removing of material will be due to the continuous and rapid current discharges between two electrodes.. The spark is very carefully controlled and localized so that it only affects the surface of the material. Usually in order to prevent the defects which are arising due to the conventional machining, the Electric Discharge Machining (EDM) machining is preferred. Also intricate and complicated shapes can be machined effectively by use of Electric Discharge Machining (EDM). The EDM process usually does not affect the heat treat below the surface. This research work focus on the design and fabrication of rotary EDM tool for machining Al6061alloy and investigation of effect of rotary tool on surface finish, material removal rate and tool wear rate. Also the effect of machining parameters of EDM such as pulse on & off time, current on material Removal Rate (MRR), Surface Roughness (SR) and Electrode wear rate (EWR) have studied. Al6061 alloy can be used for marine and offshore applications by reinforcing some other elements. The investigations have revealed that MRR (material removal rate), surface roughness (Ra) have been improved with the reduction in the tool wear rate (TWR) when the tool is rotating instead of stationary. It was clear that as rotary speed of the tool is increasing the material removal rate is increasing with the reduction of surface finish and tool wear rate.

  9. Intensification of the Students' Self-Development Process When Performing Design and Settlement Works on the "Machine Parts" Course

    Science.gov (United States)

    Timerbaev, Rais Mingalievich; Muhutdinov, Rafis Habreevich; Danilov, Valeriy Fedorovich

    2015-01-01

    The article addresses issues related to the methodology of intensifying self-development process when performing design and settlement works on the "Machine Parts" course for the students studying in such areas of training as "Technology" and "Vocational Education" with the use of computer technologies. At the same…

  10. In vivo and in vitro performance of a China-made hemodialysis machine: a multi-center prospective controlled study.

    Science.gov (United States)

    Wang, Yong; Chen, Xiang-Mei; Cai, Guang-Yan; Li, Wen-Ge; Zhang, Ai-Hua; Hao, Li-Rong; Shi, Ming; Wang, Rong; Jiang, Hong-Li; Luo, Hui-Min; Zhang, Dong; Sun, Xue-Feng

    2017-08-02

    To evaluate the in vivo and in vitro performance of a China-made dialysis machine (SWS-4000). This was a multi-center prospective controlled study consisting of both long-term in vitro evaluations and cross-over in vivo tests in 132 patients. The China-made SWS-4000 dialysis machine was compared with a German-made dialysis machine (Fresenius 4008) with regard to Kt/V values, URR values, and dialysis-related adverse reactions in patients on maintenance hemodialysis, as well as the ultrafiltration rate, the concentration of electrolytes in the proportioned dialysate, the rate of heparin injection, the flow rate of the blood pump, and the rate of malfunction. The Kt/V and URR values at the 1st and 4th weeks of dialysis as well as the incidence of adverse effects did not differ between the two groups in cross-over in vivo tests (P > 0.05). There were no significant differences between the two groups in the error values of the ultrafiltration rate, the rate of heparin injection or the concentrations of electrolytes in the proportioned dialysate at different time points under different parameter settings. At weeks 2 and 24, with the flow rate of the blood pump set at 300 mL/min, the actual error of the SWS-4000 dialysis machine was significantly higher than that of the Fresenius 4008 dialysis machine (P  0.05). The malfunction rate was higher in the SWS-4000 group than in the Fresenius 4008 group (P Fresenius 4008 dialysis machine; however, the malfunction rate of the former is higher than that of the latter in in vitro tests. The stability and long-term accuracy of the SWS-4000 dialysis machine remain to be improved.

  11. Performance evaluation of fractional-slot tubular permanent magnet machines with low space harmonics

    Directory of Open Access Journals (Sweden)

    Wang Jiabin

    2015-12-01

    Full Text Available This paper evaluates the perforamnce of fractional-slot per pole winding configurations for tubular permanent magnet (PM machines that can effectively eliminate the most undesirable space harmonics in a simple and cost-effective manner. The benefits of the proposed machine topology winding configurations are illustrated through comparison with 9-slot, 10-pole tubular PM machine developed for a free piston energy converter under the same specification and volumetric constraints. It has been shown that the proposed machine topology results in more than 7 times reduction in the eddy current loss in the mover magnets and supporting tube, and hence avoids potential problem of excessive mover temperature and risk of demagnetization.

  12. Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Wass, J.; Thrane, Jakob; Piels, Molly

    2016-01-01

    Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information....

  13. Performance and optimization of support vector machines in high-energy physics classification problems

    International Nuclear Information System (INIS)

    Sahin, M.Ö.; Krücker, D.; Melzer-Pellmann, I.-A.

    2016-01-01

    In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications.

  14. Performance and optimization of support vector machines in high-energy physics classification problems

    Energy Technology Data Exchange (ETDEWEB)

    Sahin, M.Ö., E-mail: ozgur.sahin@desy.de; Krücker, D., E-mail: dirk.kruecker@desy.de; Melzer-Pellmann, I.-A., E-mail: isabell.melzer@desy.de

    2016-12-01

    In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications.

  15. Performances of the PCA method in electrical machines diagnosis using Matlab

    OpenAIRE

    Ramahaleomiarantsoa , J.F.; Sambatra , Eric Jean Roy; Heraud , Nicolas; Razafimahenina , Jean Marie

    2012-01-01

    Nowadays, faults diagnosis is almost an inevitable step to be maintained in the optimal safety operating of every physical system. Electrical machines, main elements of every electromechanical system, are among the research topics of many academic and industrial laboratories because of the importance of their roles in the industrial process. Lots of technologies of these machines are old and well controlled. However, they remain the seat of several electrical and mechanical faults [1-4]. Thus...

  16. HIGH PERFORMANCE TAPS FOR CUTTING THREADS IN DIFFICULT TO MACHINE MATERIALS

    Directory of Open Access Journals (Sweden)

    M. R. Akhmedova

    2016-01-01

    Full Text Available Objectives. This article explores in detail questions of instrument operation function of tapping internal threads in hard materials. The existing relationship between vibration system amplitude and tool durability is indicated; on this basis, it is determined that the best course for improving the durability performance is increasing vibratory resistance. Based on a critical analysis of existing designs with consideration of their flaws, the development of new technological designs of taps is tasked with ensuring stable operation when handling hard materials. Methods. It is noteworthy that one of the main vibration resistance improvement methods of the tool is to reduce the contact area of the tool with the work piece in the cutting zone. Methods are proposed for improving the vibration resistance of taps, considering the correlation adjustment of tap teeth in order to completely eliminate friction at the sides of the thread cutting surface and uneven implementation flute cutting steps. Results. The idea of increasing vibration resistance has seen the new development of vibration-proof tap designs, heralded as innovations due to the accuracy of thread cutting and durability achieved by reducing the thread contact area with the work piece in the cutting zone. Increased vibration resistance is achieved in the modified taps through high correction by means of thread side downgrading of the coarse tap cone by an additional angle of 30º. In another design, the stylus provided with uneven angular spacing. Test results of designed taps machined in corrosion-resistant 1Kh18N9T steel. A manifold increase in tool durability was achieved due to its high vibration resistance. Conclusions. The redesigned taps have a number of advantages, characterised by a high resistance when processing difficult materials and an insignificant increase in the complexity of their manufacture compared with standard taps. Therefore they can be recommended for large

  17. Fabrication and performance tests of a prototype in-situ coating machine for JT-60

    International Nuclear Information System (INIS)

    Obara, Kenjiro; Abe, Tetsuya; Murakami, Yoshio

    1987-09-01

    Prior to the design and construction of the JT-60's in-situ coating device, a prototype machine was fabricated and tested to confirm the applicability of proposed driving methods and mechanical elements to the device which would be operated in very severe conditions including high ambient temperature and high vacuum. The machine basically consists of an in-vessel manipulator, a fiberscope and an ohmically heated titanium evaporator. From the test results, we recommended to use the combination of Inconel 625 and a self-lubricating alloy for the solid-lubricated bearings and MoS 2 -coated Inconel 625 for the solid-lubricated gears. It was also found that TiC coating showed a effect for the prevention of welding between bolts and nuts. In order to optimize the operating parameters of the machine, many wall inspection tests and titanium evaporation tests were carried out in a large vacuum vessel by simulating the JT-60 conditions. (author)

  18. Performance of a Horizontal Double Cylinder Type of Fresh Coffee Cherries Pulping Machine

    Directory of Open Access Journals (Sweden)

    Sukrisno Widyotomo

    2009-05-01

    Full Text Available Pulping is one important step in wet coffee processing method. Usually, pulping process uses a machine which constructed using wood or metal materials. A horizontal single cylinder type coffee pulping machine is the most popular machine in coffee processor and market. One of the weakness of a horizontal single cylinder type coffee pulping machine is high of broken beans. Broken beans is one of major aspect in defect system that result in low quality. Indonesian Coffee and Cocoa Research Institute has designed and tested a horizontal double cylinder type coffee pulping machine. Material tested is Robusta cherry, mature, 60—65% (wet basis moisture content, which size compostition of coffee cherries was 50.8% more than 15 mm diameter, 32% more than 10 mm diameter, and 16.6% to get through 10 mm hole diameter; 690—695 kg/m3 bulk density, and clean from methal and foreign materials. The result showed that this machine has 420 kg/h optimal capacity in operational conditions, 1400 rpm rotor rotation speed for unsorted coffee cherries with composition 53.08% whole parchment coffee, 16.92% broken beans, and 30% beans in the wet skin. For small size coffee cherries, 603 kg/h optimal capacity in operational conditions, 1600 rpm rotor rotation speed with composition 51.30% whole parchment coffee, 12.59% broken beans, and 36.1% beans in the wet skin. Finally, for medium size coffee cherries, 564 kg/h optimal capacity in operational conditions, 1800 rpm rotor rotation speed with composition 48.64% whole parchment coffee, 18.5% broken beans, and 32.86% beans in the wet skin.Key words : coffee, pulp, pulper, cylinder, quality.

  19. Performance and optimization of support vector machines in high-energy physics classification problems

    Energy Technology Data Exchange (ETDEWEB)

    Sahin, M.Oe.; Kruecker, D.; Melzer-Pellmann, I.A.

    2016-01-15

    In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications. A new C++ LIBSVM interface called SVM-HINT is developed and available on Github.

  20. An experimental result of surface roughness machining performance in deep hole drilling

    Directory of Open Access Journals (Sweden)

    Mohamad Azizah

    2016-01-01

    Full Text Available This study presents an experimental result of a deep hole drilling process for Steel material at different machining parameters which are feed rate (f, spindle speed (s, the depth of the hole (d and MQL, number of drops (m on surface roughness, Ra. The experiment was designed using two level full factorial design of experiment (DoE with centre points to collect surface roughness, Ra values. The signal to noise (S/N ratio analysis was used to discover the optimum level for each machining parameters in the experiment.

  1. Performance of machine learning methods for ligand-based virtual screening.

    Science.gov (United States)

    Plewczynski, Dariusz; Spieser, Stéphane A H; Koch, Uwe

    2009-05-01

    Computational screening of compound databases has become increasingly popular in pharmaceutical research. This review focuses on the evaluation of ligand-based virtual screening using active compounds as templates in the context of drug discovery. Ligand-based screening techniques are based on comparative molecular similarity analysis of compounds with known and unknown activity. We provide an overview of publications that have evaluated different machine learning methods, such as support vector machines, decision trees, ensemble methods such as boosting, bagging and random forests, clustering methods, neuronal networks, naïve Bayesian, data fusion methods and others.

  2. Performance and optimization of support vector machines in high-energy physics classification problems

    International Nuclear Information System (INIS)

    Sahin, M.Oe.; Kruecker, D.; Melzer-Pellmann, I.A.

    2016-01-01

    In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications. A new C++ LIBSVM interface called SVM-HINT is developed and available on Github.

  3. Applying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction

    OpenAIRE

    Ruijian Zhang; Deren Li

    2017-01-01

    Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future day’s water quality in an easy and efficient way. The idea is to combine the traditional ways and the computer algorithms together. Using machine learning algorithms, the ass...

  4. Some measurements of Java-to-bytecode compiler performance in the Java Virtual Machine

    OpenAIRE

    Daly, Charles; Horgan, Jane; Power, James; Waldron, John

    2001-01-01

    In this paper we present a platform independent analysis of the dynamic profiles of Java programs when executing on the Java Virtual Machine. The Java programs selected are taken from the Java Grande Forum benchmark suite, and five different Java-to-bytecode compilers are analysed. The results presented describe the dynamic instruction usage frequencies.

  5. Selecting a Benchmark Suite to Profile High-Performance Computing (HPC) Machines

    Science.gov (United States)

    2014-11-01

    architectures. Machines now contain central processing units (CPUs), graphics processing units (GPUs), and many integrated core ( MIC ) architecture all...evaluate the feasibility and applicability of a new architecture just released to the market . Researchers are often unsure how available resources will...architectures. Having a suite of programs running on different architectures, such as GPUs, MICs , and CPUs, adds complexity and technical challenges

  6. Machine vision-based high-resolution weed mapping and patch-sprayer performance simulation

    NARCIS (Netherlands)

    Tang, L.; Tian, L.F.; Steward, B.L.

    1999-01-01

    An experimental machine vision-based patch-sprayer was developed. This sprayer was primarily designed to do real-time weed density estimation and variable herbicide application rate control. However, the sprayer also had the capability to do high-resolution weed mapping if proper mapping techniques

  7. Performance of Ti-multilayer coated tool during machining of MDN431 alloyed steel

    Science.gov (United States)

    Badiger, Pradeep V.; Desai, Vijay; Ramesh, M. R.

    2018-04-01

    Turbine forgings and other components are required to be high resistance to corrosion and oxidation because which they are highly alloyed with Ni and Cr. Midhani manufactures one of such material MDN431. It's a hard-to-machine steel with high hardness and strength. PVD coated insert provide an answer to problem with its state of art technique on the WC tool. Machinability studies is carried out on MDN431 steel using uncoated and Ti-multilayer coated WC tool insert using Taguchi optimisation technique. During the present investigation, speed (398-625rpm), feed (0.093-0.175mm/rev), and depth of cut (0.2-0.4mm) varied according to Taguchi L9 orthogonal array, subsequently cutting forces and surface roughness (Ra) were measured. Optimizations of the obtained results are done using Taguchi technique for cutting forces and surface roughness. Using Taguchi technique linear fit model regression analysis carried out for the combination of each input variable. Experimented results are compared and found the developed model is adequate which supported by proof trials. Speed, feed and depth of cut are linearly dependent on the cutting force and surface roughness for uncoated insert whereas Speed and depth of cut feed is inversely dependent in coated insert for both cutting force and surface roughness. Machined surface for coated and uncoated inserts during machining of MDN431 is studied using optical profilometer.

  8. Performance optimization of a CNC machine through exploration of the timed state space

    NARCIS (Netherlands)

    Mota, M.A. Mujica; Piera, Miquel Angel

    2010-01-01

    Flexible production units provide very efficient mechanisms to adapt the type and production rate according to fluctuations in demand. The optimal sequence of the different manufacturing tasks in each machine is a challenging problem that can deal with important productivity benefits.

  9. Performance analysis of a new radial-axial flux machine with SMC cores and ferrite magnets

    Science.gov (United States)

    Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

    2017-05-01

    Soft magnetic composite (SMC) is a popular material in designing of new 3D flux electrical machines nowadays for it has the merits of isotropic magnetic characteristic, low eddy current loss and high design flexibility over the electric steel. The axial flux machine (AFM) with the extended stator tooth tip both in the radial and circumferential direction is a good example, which has been investigated in the last years. Based on the 3D flux AFM and radial flux machine, this paper proposes a new radial-axial flux machine (RAFM) with SMC cores and ferrite magnets, which has very high torque density though the low cost low magnetic energy ferrite magnet is utilized. Moreover, the cost of RAFM is quite low since the manufacturing cost can be reduced by using the SMC cores and the material cost will be decreased due to the adoption of the ferrite magnets. The 3D finite element method (FEM) is used to calculate the magnetic flux density distribution and electromagnetic parameters. For the core loss calculation, the rotational core loss computation method is used based on the experiment results from previous 3D magnetic tester.

  10. TRACEABILITY OF PRECISION MEASUREMENTS ON COORDINATE MEASURING MACHINES – TRACEABILITY, CALIBRATION AND PERFORMANCE VERIFICATION

    DEFF Research Database (Denmark)

    Bariani, Paolo; De Chiffre, Leonardo; Tosello, Guido

    This document is used in connection with an exercise of 1 hour duration as a part of the course VISION ONLINE – One week course on Precision & Nanometrology. The exercise concerns establishment of traceability of measurements with optical coordinate machine by mean of using two different calibrated...

  11. Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy

    Science.gov (United States)

    2017-01-01

    Background Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Conclusions Machine learning algorithms can classify open-text feedback

  12. Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy.

    Science.gov (United States)

    Gibbons, Chris; Richards, Suzanne; Valderas, Jose Maria; Campbell, John

    2017-03-15

    Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor's activity for the purposes of quality assurance, safety, and continuing professional development. The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors' professional performance in the United Kingdom. We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians' colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to "popular" (recall=.97), "innovator" (recall=.98), and "respected" (recall=.87) codes and was lower for the "interpersonal" (recall=.80) and "professional" (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as "respected," "professional," and "interpersonal" related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high

  13. Optimization of machining parameters of turning operations based on multi performance criteria

    Directory of Open Access Journals (Sweden)

    N.K.Mandal

    2013-01-01

    Full Text Available The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA. Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.

  14. THE EFFECT OF IMPLEMENTATION MAINTENANCE CARDS IN PERFORMANCE OF MACHINES IN SELECTED PRODUCTION COMPANY

    Directory of Open Access Journals (Sweden)

    Michał ZASADZIEŃ

    2015-10-01

    Full Text Available Intelligent development should become an inherent part of the policy of each enterprise which wants to develop and maintain its position on the competitive market. The article presents investigations related to the implementation of one of Total Productive Maintenance system elements. Reasons for introducing a new procedure for circulating information about machine inspections and overhauls planned, the major element of which are work sheets for key machines taking part in the production process, have been presented. The effectiveness of the new procedure was subjected to analysis by comparing particular machines’ work times and downtimes before and after the implementation of new procedures. The conducted research revealed an increased effectiveness of machines’ work, which resulted from shortened down-times, especially the duration of a failure.

  15. Experimental studies on improving the performance of electrochemical machining of high carbon, high chromium die steel using jet patterns

    Directory of Open Access Journals (Sweden)

    V. Sathiyamoorthy

    2014-03-01

    Full Text Available Electrochemical machining (ECM is a non-traditional process used mainly to cut hard or difficult-to-cut metals, where the application of a more traditional process is not convenient. Stiff market competition and ever-growing demand for better, durable and reliable products has brought about a material revolution, which has greatly expanded the families of difficult-to-machine materials namely highcarbon,high-chromium die steel; stainless steel and superalloys. This investigation attempts to analyze the effect of electrolyte distribution on material removal rate (MRR and surface roughness (SR on electrochemical machining of high-carbon, high-chromium die steel using NaCl aqueous solution. Three electrolyte jet patterns namely straight jet in circular, inclined jet in circular and straight jet in spiral were used for this experimentation. The results reveal that electrolyte distribution significantly improves the performance of ECM and the straight jet in spiral pattern performs satisfactorily in obtaining better MRR and surface roughness.

  16. Performance of palm oil as a biobased machining lubricant when drilling inconel 718

    OpenAIRE

    Abd Rahim Erween; Sasahara Hiroyuki

    2017-01-01

    Metalworking fluid acts as cooling and lubrication agent at the cutting zone in the machining process. However, conventional Metalworking fluid such mineral oil gives negative impact on the human and environment. Therefore, the manufacture tends to substitute the mineral oil to bio-based oil such as vegetables and synthetic oil. In this paper, the drilling experiment was carried out to evaluate the efficiency of palm oil and compare it with minimal quantity lubrication technique using synthet...

  17. Can machine learning on learner analytics produce a predictive model on student performance?

    OpenAIRE

    Busch, John; Hanna, Philip; O'Neill, Ian; McGowan, Aidan; Collins, Matthew

    2017-01-01

    The aim of this research is to analysis past student learner analytics using machine learning algorithms that had undertaken a web development and programming module. By specifically using the access and error web server logs from each student web server it provides a deeper learner analytic data. The web server logs every web file access and error access from a browser so in turn each data file can directly relate to a student's engagement level and assessment strategy. Each log holds severa...

  18. Computational Principle and Performance Evaluation of Coherent Ising Machine Based on Degenerate Optical Parametric Oscillator Network

    Directory of Open Access Journals (Sweden)

    Yoshitaka Haribara

    2016-04-01

    Full Text Available We present the operational principle of a coherent Ising machine (CIM based on a degenerate optical parametric oscillator (DOPO network. A quantum theory of CIM is formulated, and the computational ability of CIM is evaluated by numerical simulation based on c-number stochastic differential equations. We also discuss the advanced CIM with quantum measurement-feedback control and various problems which can be solved by CIM.

  19. GUIDELINES FOR RATIONALIZATION OF MANAGEMENT OF PERFORMANCE OF LOGISTICS SYSTEM OF TRANSPORT MACHINE MANUFACTURING ENTERPRISES

    OpenAIRE

    Yulia A. Anankina

    2013-01-01

    The main problems that occurs in a process of movement of material flows in the enterprises of transport machine manufacturing enterprises are stated in the article. Particular attention is paid to the rational use of vehicles on the existing capacity of the material flow of the enterprise. Process of transport service of material flow is concerned step by step. The place of transport in the logistics enterprise system is determined by authors. We give guidelines for rationalization of manage...

  20. An Effective Performance Analysis of Machine Learning Techniques for Cardiovascular Disease

    Directory of Open Access Journals (Sweden)

    Vinitha DOMINIC

    2015-03-01

    Full Text Available Machine learning techniques will help in deriving hidden knowledge from clinical data which can be of great benefit for society, such as reduce the number of clinical trials required for precise diagnosis of a disease of a person etc. Various areas of study are available in healthcare domain like cancer, diabetes, drugs etc. This paper focuses on heart disease dataset and how machine learning techniques can help in understanding the level of risk associated with heart diseases. Initially, data is preprocessed then analysis is done in two stages, in first stage feature selection techniques are applied on 13 commonly used attributes and in second stage feature selection techniques are applied on 75 attributes which are related to anatomic structure of the heart like blood vessels of the heart, arteries etc. Finally, validation of the reduced set of features using an exhaustive list of classifiers is done.In parallel study of the anatomy of the heart is done using the identified features and the characteristics of each class is understood. It is observed that these reduced set of features are anatomically relevant. Thus, it can be concluded that, applying machine learning techniques on clinical data is beneficial and necessary.

  1. MITS machine operations

    International Nuclear Information System (INIS)

    Flinchem, J.

    1980-01-01

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

  2. Performance Comparison of Conventional Synchronous Reluctance Machines and PM-Assisted Types with Combined Star–Delta Winding

    Directory of Open Access Journals (Sweden)

    Mohamed Nabil Fathy Ibrahim

    2017-09-01

    Full Text Available This paper compares four prototype Synchronous Reluctance Motors (SynRMs having an identical geometry of iron lamination stacks in the stator and rotor. Two different stator winding layouts are employed: a conventional three-phase star connection and a combined star–delta winding. In addition, two rotors are considered: a conventional rotor without magnets and a rotor with ferrite magnets. The performance of the four SynRMs is evaluated using a two-dimensional (2D Finite Element Model (FEM. For the same copper volume and current, the combined star–delta-connected stator with Permanent Magnets (PMs in the rotor corresponds to an approximately 22% increase in the output torque at rated current and speed compared to the conventional machine. This improvement is mainly thanks to adding ferrite PMs in the rotor as well as to the improved winding factor of the combined star–delta winding. The torque gain increases up to 150% for low current. Moreover, the rated efficiency is 93.60% compared to 92.10% for the conventional machine. On the other hand, the impact on the power factor and losses of SynRM when using the star–delta windings instead of the star windings is merely negligible. The theoretical results are experimentally validated using four identical prototype machines with identical lamination stacks but different rotors and winding layouts.

  3. Performance Analysis and Simulation of a Novel Brushless Double Rotor Machine for Power-Split HEV Applications

    Directory of Open Access Journals (Sweden)

    Jingang Bai

    2012-01-01

    Full Text Available A new type of brushless double rotor machine (BDRM is proposed in this paper. The BDRM is an important component in compound-structure permanent-magnet synchronous machine (CS-PMSM systems, which are promising for power-split hybrid electric vehicle (HEV applications. The BDRM can realize the speed adjustment between claw-pole rotor and permanent-magnet rotor without brushes and slip rings. The structural characteristics of the BDRM are described and its magnetic circuit model is built. Reactance parameters of the BDRM are deduced by an analytical method. It is found that the size characteristics of the BDRM are different from those of conventional machines. The new sizing and torque equations are analyzed and the theoretical results are used in the optimization process. Studies of the analytical magnetic circuit and finite element method (FEM model show that the BDRM tends to have high leakage flux and low power factor, and then the method to obtain high power factor is discussed. Furthermore, a practical methodology of the BDRM design is developed, which includes an analytical tool, 2D field calculation and performance evaluation by 3D field calculation. Finally, different topologies of the BDRM are compared and an optimum prototype is designed.

  4. The Influence of Tool Geometry towards Cutting Performance in Machining Aluminium 7075

    Directory of Open Access Journals (Sweden)

    Muhammad Syafik Jumali

    2017-01-01

    Full Text Available Aerospace industries often use Computer Numerical Control (CNC machining in manufacturing aerospace parts. Aluminium 7075 is the most common material used as aircraft components. This research aims to produce end mill with optimum geometry in terms of the helix angle, primary radial relief angle and secondary relief angle. End mills with different geometry parameters are tested on Aluminium 7075 and data on surface roughness and tool wear were collected. The results were then analysed to determine which parameters brought the optimum result with regards to surface roughness and tool wear.

  5. Performance and optimization of support vector machines in high-energy physics classification problems

    Energy Technology Data Exchange (ETDEWEB)

    Sahin, Mehmet Oezguer; Kruecker, Dirk; Melzer-Pellmann, Isabell [DESY, Hamburg (Germany)

    2016-07-01

    In this talk, the use of Support Vector Machines (SVM) is promoted for new-physics searches in high-energy physics. We developed an interface, called SVM HEP Interface (SVM-HINT), for a popular SVM library, LibSVM, and introduced a statistical-significance based hyper-parameter optimization algorithm for the new-physics searches. As example case study, a search for Supersymmetry at the Large Hadron Collider is given to demonstrate the capabilities of SVM using SVM-HINT.

  6. On the Cutting Performance of Coated HSS Taps When Machining of Austenitic Steel

    Science.gov (United States)

    Sliwkova, Petra; Piska, Miroslav

    2014-12-01

    The paper deals with a quality of the PVD coated HSS taps when cutting the stainless austenitic chromiumnickel non-stabilized steel DIN 1.4301 (X5CrNi 18-10). The main attention is focused on the analysis of loading (cutting moment, specific energy) of the HSS taps by means of pieso-electrical dynamometer Kistler 9272 and the relation between the quality of duplex and triplex PVD coatings and their effects on the quality of machined thread surfaces and tool life of the taps. The results showed a safe and stabilized cutting with acceptable quality of threads for HSSE with the TiN+TiCN+DLC coating.

  7. Machine Protection

    International Nuclear Information System (INIS)

    Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

    2012-01-01

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

  8. Machine Protection

    CERN Document Server

    Zerlauth, Markus; Wenninger, Jörg

    2012-01-01

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

  9. Machine Protection

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-07-01

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

  10. Performance assessment of commercial relays for anti-islanding protection of rotating machine based distributed generation

    Energy Technology Data Exchange (ETDEWEB)

    Katiraei, F. [Quanta Technology, Houston, TX (United States); Abbey, C. [Natural Resources Canada, Ottawa, ON (Canada). CANMET Energy Technology Centre; Da Cunha, I. [LeapFrog Energy Technologies Inc., Mississauga, ON (Canada); Brisette, Y. [Hydro-Quebec, Montreal, PQ (Canada). Research Inst

    2008-07-01

    According to power industry standards, distributed generation must stop energizing the power grid upon loss of the main system. Either passive or active methods may be used to fulfill this requirement. Passive methods rely on locally measured signals to determine whether the main grid is present, while active methods inject a perturbation into the system that will manifest itself in locally measured signals if the main grid is not present. This paper compared simulation and experimental results for various commercially available relays for passive anti-islanding protection of small (below 500 kW) distributed generators using either synchronous or induction generators. A commercial multifunction relay and an application specific relay for rate-of-change-of-frequency and vector shift were modelled in simulation. Simulation results were compared with tests using a 25 kV induction generator. Results obtained for the induction machine based DG were in good agreement with trip times associated with under/overvoltage relays. The poor results with frequency based relays may be attributed to the method used for calculating frequency. Sensitivity analysis on the degree of capacitor compensation revealed a small non-detection zone, suggesting that this risk should be evaluated for induction machine based interconnections. These results showed that accurate relay modeling is challenging, particularly for frequency based techniques. Other methods for relay testing, such as hardware-in-the-loop, may be more appropriate than simulation, and are more practical in terms of cost effectiveness, than extensive field trials. 7 refs., 1 tab., 6 figs.

  11. Effects of rest interval length on Smith machine bench press performance and perceived exertion in trained men.

    Science.gov (United States)

    Tibana, Ramires A; Vieira, Denis C L; Tajra, Vitor; Bottaro, Martim; de Salles, Belmiro F; Willardson, Jeffrey M; Prestes, Jonato

    2013-12-01

    This study compared two different rest intervals (RI) between sets of resistance exercise. Ten resistance-trained men (M age = 24.3, SD = 3.5 yr.; M weigh t= 80.0 kg, SD = 15.3; M height = 1.75 m, SD = 0.04) performed five sets of Smith machine bench presses at 60% of one repetition maximum, either with 1.5 min. or 3 min. RI between sets. Their repetition performance, total training volume, velocity, fatigue, rating of perceived exertion, and muscular power were measured. All of these measures indicated that performance was significantly better and fatigue was significantly lower in the 3 min. RI as compared with the 1.5 min. RI, except the rating of perceived exertion which did not show a significant difference. A longer RI between sets promotes superior performance for the bench press.

  12. Effect of Built-Up Edge Formation during Stable State of Wear in AISI 304 Stainless Steel on Machining Performance and Surface Integrity of the Machined Part.

    Science.gov (United States)

    Ahmed, Yassmin Seid; Fox-Rabinovich, German; Paiva, Jose Mario; Wagg, Terry; Veldhuis, Stephen Clarence

    2017-10-25

    During machining of stainless steels at low cutting -speeds, workpiece material tends to adhere to the cutting tool at the tool-chip interface, forming built-up edge (BUE). BUE has a great importance in machining processes; it can significantly modify the phenomenon in the cutting zone, directly affecting the workpiece surface integrity, cutting tool forces, and chip formation. The American Iron and Steel Institute (AISI) 304 stainless steel has a high tendency to form an unstable BUE, leading to deterioration of the surface quality. Therefore, it is necessary to understand the nature of the surface integrity induced during machining operations. Although many reports have been published on the effect of tool wear during machining of AISI 304 stainless steel on surface integrity, studies on the influence of the BUE phenomenon in the stable state of wear have not been investigated so far. The main goal of the present work is to investigate the close link between the BUE formation, surface integrity and cutting forces in the stable sate of wear for uncoated cutting tool during the cutting tests of AISI 304 stainless steel. The cutting parameters were chosen to induce BUE formation during machining. X-ray diffraction (XRD) method was used for measuring superficial residual stresses of the machined surface through the stable state of wear in the cutting and feed directions. In addition, surface roughness of the machined surface was investigated using the Alicona microscope and Scanning Electron Microscopy (SEM) was used to reveal the surface distortions created during the cutting process, combined with chip undersurface analyses. The investigated BUE formation during the stable state of wear showed that the BUE can cause a significant improvement in the surface integrity and cutting forces. Moreover, it can be used to compensate for tool wear through changing the tool geometry, leading to the protection of the cutting tool from wear.

  13. Performance characteristics of tunnel boring machine in basalt and pyroclastic rocks of Deccan traps – A case study

    OpenAIRE

    Prasnna Jain; A.K. Naithani; T.N. Singh

    2014-01-01

    A 12.24 km long tunnel between Maroshi and Ruparel College is being excavated by tunnel boring machine (TBM) to improve the water supply system of Greater Mumbai, India. In this paper, attempt has been made to establish the relationship between various litho-units of Deccan traps, stability of tunnel and TBM performances during the construction of 5.83 km long tunnel between Maroshi and Vakola. The Maroshi–Vakola tunnel passes under the Mumbai Airport and crosses both runways with an overburd...

  14. Performance Comparison of Two Topologies Double-Fed Brushless Machine with 36 Slots for Low-Speed Applications

    Directory of Open Access Journals (Sweden)

    Yue Hao

    2014-12-01

    Full Text Available The performances of two topologies of low-speed double-fed brushless machine (DFBM with fractional slot windings are quantitatively compared and analyzed using two-dimensional (2-D finite element method (FEM. To fairly compare the torque capability and power efficiency of different DFBMs, the investigated DFBMs have the same outer diameter, the same axial stack length and the same iron core materials, and some comparison rules are presented. In order to maximize the torque density, several important structure parameters are optimized. The results of this paper reveal the torque density levels and power density levels of two kinds of DFBMs.

  15. Performance Evaluation of Machine Learning Methods for Leaf Area Index Retrieval from Time-Series MODIS Reflectance Data

    Science.gov (United States)

    Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang

    2017-01-01

    Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size. PMID:28045443

  16. A framework for evaluating the performance of automated teller machine in banking industries: A queuing model-cum-TOPSIS approach

    Directory of Open Access Journals (Sweden)

    Christopher Osita Anyaeche

    2018-04-01

    Full Text Available The improvement in the provision of banking services to customers enhances bank’s performance (profitability and productivity and the amounts of dividend declared to shareholders as well as bank’s competitiveness. One means of fast tracking the service time for bank customers is through the use of self-servicing machines, such as automated teller machine (ATM. Total service cost, expected waiting time in queue, ATM utilization and percentage of customer loss are some of the performance indices that are used to evaluate the service rendered by a bank’s ATM. This study proposes a framework for evaluating the performance of ATM by integrating queuing model and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS methodology. Applicability of the framework was tested using practical data obtained from four banks in Nigeria. It was observed that the average ATM usage in the study area was less than 50%. The TOPSIS results identified Bank A as the best ranked bank. In addition, the results obtained revealed that banks with two ATM were ranked higher than banks with more than two ATM

  17. Performance Optimization of Electrical Discharge Machining (Die Sinker for Al-6061 via Taguchi Approach

    Directory of Open Access Journals (Sweden)

    Muhammad Qaiser Saleem

    2015-04-01

    Full Text Available This paper parametrically optimizes the EDM (Electrical Discharge Machining process in die sinking mode for material removal rate, surface roughness and edge quality of aluminum alloy Al-6061. The effect of eight parameters namely discharge current, pulse on-time, pulse off-time, auxiliary current, working time, jump time distance, servo speed and work piece hardness are investigated. Taguchi's orthogonal array L18 is employed herein for experimentation. ANOVA (Analysis of Variance with F-ratio criterion at 95% confidence level is used for identification of significant parameters whereas SNR (Signal to Noise Ratio is used for determination of optimum levels. Optimization obtained for Al-6061 with parametric combination investigated herein is validated by the confirmation run.

  18. The Flavin Reductase MsuE Is a Novel Nitroreductase that Can Efficiently Activate Two Promising Next-Generation Prodrugs for Gene-Directed Enzyme Prodrug Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Green, Laura K.; Storey, Mathew A. [School of Biological Sciences, Victoria University of Wellington, Kelburn Parade, Wellington 6140 (New Zealand); Williams, Elsie M. [School of Biological Sciences, Victoria University of Wellington, Kelburn Parade, Wellington 6140 (New Zealand); Victoria University Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington 6140 (New Zealand); Patterson, Adam V.; Smaill, Jeff B. [Maurice Wilkins Centre for Molecular Biodiscovery, School of Biological Sciences, University of Auckland, Auckland 1142 (New Zealand); Auckland Cancer Society Research Centre, University of Auckland, Grafton, Auckland 1142 (New Zealand); Copp, Janine N.; Ackerley, David F., E-mail: david.ackerley@vuw.ac.nz [School of Biological Sciences, Victoria University of Wellington, Kelburn Parade, Wellington 6140 (New Zealand); Victoria University Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington 6140 (New Zealand); Maurice Wilkins Centre for Molecular Biodiscovery, School of Biological Sciences, University of Auckland, Auckland 1142 (New Zealand)

    2013-08-08

    Bacterial nitroreductase enzymes that can efficiently catalyse the oxygen-independent reduction of prodrugs originally developed to target tumour hypoxia offer great potential for expanding the therapeutic range of these molecules to aerobic tumour regions, via the emerging cancer strategy of gene-directed enzyme prodrug therapy (GDEPT). Two promising hypoxia prodrugs for GDEPT are the dinitrobenzamide mustard PR-104A, and the nitrochloromethylbenzindoline prodrug nitro-CBI-DEI. We describe here use of a nitro-quenched fluorogenic probe to identify MsuE from Pseudomonas aeruginosa as a novel nitroreductase candidate for GDEPT. In SOS and bacteria-delivered enzyme prodrug cytotoxicity assays MsuE was less effective at activating CB1954 (a first-generation GDEPT prodrug) than the “gold standard” nitroreductases NfsA and NfsB from Escherichia coli. However, MsuE exhibited comparable levels of activity with PR-104A and nitro-CBI-DEI, and is the first nitroreductase outside of the NfsA and NfsB enzyme families to do so. These in vitro findings suggest that MsuE is worthy of further evaluation in in vivo models of GDEPT.

  19. The Flavin Reductase MsuE Is a Novel Nitroreductase that Can Efficiently Activate Two Promising Next-Generation Prodrugs for Gene-Directed Enzyme Prodrug Therapy

    International Nuclear Information System (INIS)

    Green, Laura K.; Storey, Mathew A.; Williams, Elsie M.; Patterson, Adam V.; Smaill, Jeff B.; Copp, Janine N.; Ackerley, David F.

    2013-01-01

    Bacterial nitroreductase enzymes that can efficiently catalyse the oxygen-independent reduction of prodrugs originally developed to target tumour hypoxia offer great potential for expanding the therapeutic range of these molecules to aerobic tumour regions, via the emerging cancer strategy of gene-directed enzyme prodrug therapy (GDEPT). Two promising hypoxia prodrugs for GDEPT are the dinitrobenzamide mustard PR-104A, and the nitrochloromethylbenzindoline prodrug nitro-CBI-DEI. We describe here use of a nitro-quenched fluorogenic probe to identify MsuE from Pseudomonas aeruginosa as a novel nitroreductase candidate for GDEPT. In SOS and bacteria-delivered enzyme prodrug cytotoxicity assays MsuE was less effective at activating CB1954 (a first-generation GDEPT prodrug) than the “gold standard” nitroreductases NfsA and NfsB from Escherichia coli. However, MsuE exhibited comparable levels of activity with PR-104A and nitro-CBI-DEI, and is the first nitroreductase outside of the NfsA and NfsB enzyme families to do so. These in vitro findings suggest that MsuE is worthy of further evaluation in in vivo models of GDEPT

  20. First-guess dependence of a physically based set of temperature-humidity retrievals from HIRS2/MSU data. [High-resolution Infrared Radiation Sounder 2/Microwave Sounding Unit

    Science.gov (United States)

    Reuter, D.; Susskind, Joel; Pursch, Andrew

    1988-01-01

    The first-guess dependence of temperature and humidity fields retrieved from HIRS2/MSU data using the GLA (Goddard Laboratory for Atmospheres) physically based retrieval scheme is examined. Retrievals were performed over the ALPEX region for two successive synoptic periods, 1200 UTC March 4 and 00000 UTC March 5, 1982, using three different initial guesses for each period. Results show rather low first-guess dependence for the thickness fields and larger first-guess dependence for the precipitable water fields, especially close to the surface. The humidity retrieval algorithm used is described. The processing system has the property of maintaining the accuracy of a good guess and improving a poor one for both thickness and precipitable water at all levels.

  1. Assessing Scientific Practices Using Machine-Learning Methods: How Closely Do They Match Clinical Interview Performance?

    Science.gov (United States)

    Beggrow, Elizabeth P.; Ha, Minsu; Nehm, Ross H.; Pearl, Dennis; Boone, William J.

    2014-02-01

    The landscape of science education is being transformed by the new Framework for Science Education (National Research Council, A framework for K-12 science education: practices, crosscutting concepts, and core ideas. The National Academies Press, Washington, DC, 2012), which emphasizes the centrality of scientific practices—such as explanation, argumentation, and communication—in science teaching, learning, and assessment. A major challenge facing the field of science education is developing assessment tools that are capable of validly and efficiently evaluating these practices. Our study examined the efficacy of a free, open-source machine-learning tool for evaluating the quality of students' written explanations of the causes of evolutionary change relative to three other approaches: (1) human-scored written explanations, (2) a multiple-choice test, and (3) clinical oral interviews. A large sample of undergraduates (n = 104) exposed to varying amounts of evolution content completed all three assessments: a clinical oral interview, a written open-response assessment, and a multiple-choice test. Rasch analysis was used to compute linear person measures and linear item measures on a single logit scale. We found that the multiple-choice test displayed poor person and item fit (mean square outfit >1.3), while both oral interview measures and computer-generated written response measures exhibited acceptable fit (average mean square outfit for interview: person 0.97, item 0.97; computer: person 1.03, item 1.06). Multiple-choice test measures were more weakly associated with interview measures (r = 0.35) than the computer-scored explanation measures (r = 0.63). Overall, Rasch analysis indicated that computer-scored written explanation measures (1) have the strongest correspondence to oral interview measures; (2) are capable of capturing students' normative scientific and naive ideas as accurately as human-scored explanations, and (3) more validly detect understanding

  2. The Buttonhole Machine. Module 13.

    Science.gov (United States)

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

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

  3. Relationship between udder morphology traits, alveolar and cisternal milk compartments and machine milking performances of dairy camels (Camelus dromedarius

    Directory of Open Access Journals (Sweden)

    M. Ayadi

    2013-07-01

    Full Text Available A total of 22 dairy dromedary camels under intensive conditions in late lactation (275±24 days were used to study the relationship between external and internal udder morphology and machine milking performances. Measurements of udder and teat morphology were obtained immediately before milking and in duplicate. Individual milk yield, lag time and total milking time were recorded during milking, and milk samples were collected and analyzed for milk composition thereafter. Cisternal and alveolar milk volumes and composition were evaluated at 9 h milking interval. Results revealed that dairy camels had well developed udders and milk veins, with medium sized teats. On average, milk yield as well as milk fat and protein contents were 4.80±0.50 L d-1, 2.61±0.16% and 3.08±0.05%, respectively. The low fat values observed indicated incomplete milk letdown during machine milking. Lag time, and total milking time were 3.0±0.3, and 120.0±8.9s, on average, respectively. Positive correlations (p<0.05 were observed between milk yield and udder depth (r=0.37, distance between teats (r=0.57 and milk vein diameter (r=0.28, while a negative correlation was found with udder height (r=-0.25, p<0.05. Cisternal milk accounted for 11% of the total udder milk. Positive correlations were observed between total milk yield and volume of alveolar milk (r=0.98; p<0.001 as well as with volume of cisternal milk (r=0.63, p<0.05. Despite the low udder milk storage capacity observed in dairy camels, our study concluded that the evaluated dromedary sample had adequate udder morphology for machine milking. Finally, positive relationships were detected between milk yield and udder morphology traits of dairy camels.

  4. Optimizing man-machine performance of a personnel access restriction security system

    International Nuclear Information System (INIS)

    Banks, W.W.; Moore, J.W.

    1988-01-01

    This paper describes a human engineering design and analysis effort for a major security system upgrade at a DOE facility. This upgrade was accomplished by replacing an obsolete and poorly human engineered security screening both the with a new, user oriented, semiautomated, computer-based access control system. Human factors engineers assisted the designer staff in specifying a security access interface to physically and cognitively accommodate all employees which included handicapped individuals in wheel chairs, and several employees who were severely disabled, both visually and aurally. The new access system was intended to control entry into sensitive exclusion areas by requiring personnel to enter a security screening booth and interact with card reader devices and a-simple-to-operate access control panel system. Extensive man-machine testing with prototype mock-ups was conducted to assess human engineered design features and to illuminate potentially confusing or difficult-to-operated hardware placement, layout, and operation sequencing. These evaluations, along with the prototype mock-ups, provided input which resulted in a prototype which was easy to enter, operate, and understand by end users. This prototype later served as the design basis for the final systems design

  5. Performance evaluation for epileptic electroencephalogram (EEG) detection by using Neyman-Pearson criteria and a support vector machine

    Science.gov (United States)

    Wang, Chun-mei; Zhang, Chong-ming; Zou, Jun-zhong; Zhang, Jian

    2012-02-01

    The diagnosis of several neurological disorders is based on the detection of typical pathological patterns in electroencephalograms (EEGs). This is a time-consuming task requiring significant training and experience. A lot of effort has been devoted to developing automatic detection techniques which might help not only in accelerating this process but also in avoiding the disagreement among readers of the same record. In this work, Neyman-Pearson criteria and a support vector machine (SVM) are applied for detecting an epileptic EEG. Decision making is performed in two stages: feature extraction by computing the wavelet coefficients and the approximate entropy (ApEn) and detection by using Neyman-Pearson criteria and an SVM. Then the detection performance of the proposed method is evaluated. Simulation results demonstrate that the wavelet coefficients and the ApEn are features that represent the EEG signals well. By comparison with Neyman-Pearson criteria, an SVM applied on these features achieved higher detection accuracies.

  6. Study of TGEs and Gamma-Flashes from thunderstorms in 20-3000 keV energy range with SINP MSU Gamma-Ray spectrometers

    International Nuclear Information System (INIS)

    Bogomolov, V.V.; Svertilov, S.I.; Maximov, I.A.; Panasyuk, M.I.; Garipov, G.K.

    2016-01-01

    SINP MSU provided a number of experiments with scintillator gamma-spectrometers for study of spectral, temporal and spatial characteristics of TGEs as well as for search of fast hard x-ray and gamma-ray flashes probably appearing at the moment of lightning. The measurements were done in Moscow region and in Armenia at Aragats Mountain. Each instrument used in this work was able to record data in so called “event mode”: the time of each interaction was recorded with ∼15 mcs accuracy together with detailed spectral data. Such design allowed one to look for fast sequences of gamma-quanta, coming at the moments of discharges during thunderstorms. The pulse-shape analysis made by detector electronics was used to separate real gammaray events and possible imitations of flashes by electrical disturbances when discharges occur. During the time period from spring to autumn of 2015 a number of TGEs were detected. Spectral analysis of received data showed that the energy spectrum of coming radiation in 20-3000 kev range demonstrate a set of gamma-ray lines that can be interpreted as radiation from Rn-222 daughter isotopes. The increase of Rn-222 radiation was detected during rainfalls with thunderstorm as well as during rainy weather without thunderstorms. Variations of Rn-222 radiation dominate in low energies (<2.6MeV) and must be taken into account in the experiments performed to measure low energy gamma-radiation from the electrons accelerated in thunderclouds. In order to determine the direction from which the additional gamma-quanta come the experiment with collimated gamma-spectrometer placed on rotated platform was done. The results of this experiment realized in Moscow region from august, 2015 will be presented as well as the results of comparison of different TGEs measured in Moscow region and in Armenia. (author)

  7. Influence of Different Rotor Teeth Shapes on the Performance of Flux Switching Permanent Magnet Machines Used for Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Jing Zhao

    2014-12-01

    Full Text Available This paper investigated a 12-slot/11-pole flux switching permanent magnet (FSPM machine used for electric vehicles (EVs. Five novel rotor teeth shapes are proposed and researched to reduce the cogging torque and torque ripple of the FSPM machine. These rotor teeth shapes are notched teeth, stepped teeth, eccentric teeth, combination of notched and stepped teeth, and combination of notched and eccentric teeth. They are applied on the rotor and optimized, respectively. The influences of different rotor teeth shapes on cogging torque, torque ripple and electromagnetic torque are analyzed by the 2-D finite-element method (FEM. Then, the performance of FSPMs with different rotor teeth shapes are compared and evaluated comprehensively from the points of view of cogging torque, torque ripple, electromagnetic torque, flux linkage, back electromotive force (EMF, and so on. The results show that the presented rotor teeth shapes, especially the combination of stepped and notched teeth, can greatly reduce the cogging torque and torque ripple with only slight changes in the average electromagnetic torque.

  8. Exploring performance and power properties of modern multicore chips via simple machine models

    OpenAIRE

    Hager, Georg; Treibig, Jan; Habich, Johannes; Wellein, Gerhard

    2012-01-01

    Modern multicore chips show complex behavior with respect to performance and power. Starting with the Intel Sandy Bridge processor, it has become possible to directly measure the power dissipation of a CPU chip and correlate this data with the performance properties of the running code. Going beyond a simple bottleneck analysis, we employ the recently published Execution-Cache-Memory (ECM) model to describe the single- and multi-core performance of streaming kernels. The model refines the wel...

  9. New concept of tunnel boring machine: high performance using water jet and diamond wire as rock cutting technology

    Directory of Open Access Journals (Sweden)

    Rafael Pacheco dos Santos

    Full Text Available Abstract Tunnel boring machines are important tools in underground infrastructure projects. Although being well established equipment, these machinesare based on designsof more than 60 years ago and are characterized by big dimensions, enormous weight and high power consumption. Commercial aspects should be noted too. The model adopted by the TBM industry requires constant replacement of cutter discs and specific labor skills, usually offered by the same manufacturingcompany. In some cases the cost of replacement parts and technical assistance can be higher than the acquisition cost of an entire machine. These aspects are no longer compatible with the concept of sustainability that is an important aspect of currentsociety. While the technical characteristics require a large quantity of steel and several inputs, the adoptedmodel is not competitive. One alternative is looking for new technologies that break the old paradigms and allow the development of high performance concepts with lower social and environmental impact. This studydealswith this opportunity by proposing a high performance tunnel boring machine that makes use of high power water jet and diamond wire to compose a double shield cutter head. It works in two stages. In the fristone, an annular cut is executed by hydrodemolition,and in the second one, the diamond wire station slices the rock core. Only with the action of diamond wire is the rock core separated from the rock mass and the removal process is finished. A smart water jet nozzle movement system is described and non circular tunnels can be executed. The new technologies involved requirea different type of backup system, lighter and smaller. The non-existence of mechanical contact between the equipment and the rock mass at theexcavation front allows low power consumption. The advanced rate and primary excavation cost analyses can also be encountered herein. It shows that it is possible to reach an advanced rate of 174 m/day in

  10. Nanocomposites for Machining Tools

    Directory of Open Access Journals (Sweden)

    Daria Sidorenko

    2017-10-01

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

  11. Comparison of effects of machine performance parameters and energy indices of soybean production in conservation and conventional tillage systems

    Directory of Open Access Journals (Sweden)

    A Sharifi

    2016-09-01

    Full Text Available Introduction Nowadays, agricultural systems are seeking economic, ecological and bioenvironmental goals for production of agricultural crops with protection and sustainability of the environment. Therefore, there is need to extend sustainable agricultural systems such as conservation agriculture. One of the principles of conservation agriculture is conservation tillage. Conservation tillage is a kind of tillage that retains crop residues on the soil surface or mixes it with soil using related machines. It could also affect on machine performance parameters. Energy consumption for producing one kilogram crop could be studied for conservation tillage. Several researchers have conducted studies on this issue for production of different crops including wheat, sunflower and forage crops. This study conducted to assess machine performance parameters and energy indices of conservation tillage systems for soybean cultivation in Golestan province. Materials and Methods This study was conducted to investigate the effects of conservation tillage systems on machine performance and energy indices in soybean production at the Gorgan research station of Golestan Agricultural and Natural Resource Research Center in 2012. The precipitation was 450 mm. Soil texture was silty clay loam. Treatments were four tillage methods, including no-till using row crop direct planter, no-till using grain direct drill, conventional tillage usin a disk harrow with working depth of 10-15 cm and minimum tillage using chisel packer with a working depth of 20 cm. Machine performance parameters and energy indices studied in a farm covered by wheat residues in a randomized complete block design (RCBD with four treatments and four replications. Machine performance parameters consisted of field efficiency, field capacity, total field capacity and planting uniformity index were measured. Energy indices such as energy ratio, energy productivity, energy intensity and net energy gain were

  12. Tribological and Wear Performance of Carbide Tools with TiB2 PVD Coating under Varying Machining Conditions of TiAl6V4 Aerospace Alloy

    Directory of Open Access Journals (Sweden)

    Jose Mario Paiva

    2017-11-01

    Full Text Available Tribological phenomena and tool wear mechanisms during machining of hard-to-cut TiAl6V4 aerospace alloy have been investigated in detail. Since cutting tool wear is directly affected by tribological phenomena occurring between the surfaces of the workpiece and the cutting tool, the performance of the cutting tool is strongly associated with the conditions of the machining process. The present work shows the effect of different machining conditions on the tribological and wear performance of TiB2-coated cutting tools compared to uncoated carbide tools. FEM modeling of the temperature profile on the friction surface was performed for wet machining conditions under varying cutting parameters. Comprehensive characterization of the TiB2 coated vs. uncoated cutting tool wear performance was made using optical 3D imaging, SEM/EDX and XPS methods respectively. The results obtained were linked to the FEM modeling. The studies carried out show that during machining of the TiAl6V4 alloy, the efficiency of the TiB2 coating application for carbide cutting tools strongly depends on cutting conditions. The TiB2 coating is very efficient under roughing at low speeds (with strong buildup edge formation. In contrast, it shows similar wear performance to the uncoated tool under finishing operations at higher cutting speeds when cratering wear predominates.

  13. Cutting performance of TiCN–HSS cermet in dry machining

    OpenAIRE

    Canteli Fernández, José Antonio; Cantero Guisández, José Luis; Marín, N.C.; Gómez, B.; Gordo Odériz, Elena; Miguélez, Henar

    2010-01-01

    This work is focused on the cutting performance of a new cermet based on high-speed steel (HSS) matrix with hard phase TiCN. The processing route to manufacture the cermet M2+ 50 vol.% TiCN is described. Orthogonal cutting tests, carried out in a lathe showed the ability of the new cermet to achieve turning operations, showing reasonably wear resistance performing dry cutting operations. Tool life was significantly increased, when the cermet was compared with the reference materia...

  14. Impact of PSS and STATCOM Devices to the Dynamic Performance of a Multi-Machine Power System

    Directory of Open Access Journals (Sweden)

    G. Shahgholian

    2017-12-01

    Full Text Available This paper studies the impact of leveraging both static syn­ch­ron­ous compensator (STATCOM and power system stabilizer (PSS on multi-machine power systems. Considering a sta­ndard IEEE 9-bus test power network, classic and intelligent controllers are applied to achieve the desirable system performance. Simulated tests show the usefulness of STATCOM on network power quality in terms of voltage profile. In addition, it is shown that it can significantly improve the damping oscillations of synchronous generator under normal and abnormal network conditions. As shown, the PSS also contributes to improving the synch­ron­o­u­s generator parameters. It is also observed that using intelligent controllers with STATCOM and PSS leads to a better perfor­ma­nc­e relative to the classic controllers.

  15. A novel design and driving strategy for a hybrid electric machine with torque performance enhancement both taking reluctance and electromagnetic attraction effects into account

    International Nuclear Information System (INIS)

    Huang, W.-N.; Chen, W.-P.; Teng, C.-C.; Chen, M.-P.

    2006-01-01

    A novel design, the hybrid electric machine, that owns improved competence for the output torque regulation as well as enlarged power density comparing to the conventional brushless machines by making use of the simultaneous performance overlapping concept based on magnetism is proposed in this paper. The developed design concept is focused on electric machine structure and its counterpart drive for applying two main magnetic-power transmitting paths by combination of both features of magnetic tendencies of flux generation that may flow in the path with minimum reluctance and direction owning the electromagnetic motive attraction. The verifications demonstrate that the outputted torque owns effective improvement by the presented concept of the electric machine based on the equivalent 3-hp frame than the conventional brushless motors

  16. Effect of physical and mechanical properties of cassava tubers on the performance of an automated peeling machine

    Directory of Open Access Journals (Sweden)

    O.C. Ademosun

    2012-12-01

    Full Text Available Peeling of cassava tuber at all levels is still largely carried out manually; however, this work is presented with a view to investigate the effect of physical and mechanical properties of cassava tubers on mechanical peeling and hence provides a basis for cassava peeling mechanization. These properties include size of the tuber, tl, proportion by weight of peel, wp, average moisture content of the peel, map, peel thickness, tp, tuber diameter, td, tuber surface taper angle, α, peel penetration force, F, and peel shearing stress, ts. The results showed that for Slmhf; tl ranged from 140-460mm, wp ranged from 13.12-20.06%, map was 76.27%, tp ranged from 1.62-4.34mm, td ranged from 31.08-136.63mm, α ranged from 9.03-23.130, F ranged from 0.17-1.85N/mm, ts ranged from 0.85-9.25N/mm2 and quality performance of the machine, QPE, for this tuber ranged from 70.82-96.21%. Similarly, for Ssmlf; tl ranged from 125-362mm, wp ranged from 10.52-16.66%, map was 70.97%, tp ranged from 1.22-4.12mm, td ranged from 18.86-99.29mm, α ranged from 5.20-12.290, F ranged from 0.13-1.54N/mm, ts ranged from 0.65-7.70N/mm2 and quality performance of the machine, QPE, for this tuber ranged from 67.27-92.25 %. The results confirm influence of physico-mechanical properties of cassava tuber on mechanical peeling.

  17. Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening.

    Science.gov (United States)

    Ericksen, Spencer S; Wu, Haozhen; Zhang, Huikun; Michael, Lauren A; Newton, Michael A; Hoffmann, F Michael; Wildman, Scott A

    2017-07-24

    In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces target performance variability. Here we compare traditional consensus scoring methods with a novel, unsupervised gradient boosting approach. We also observed increased score variation among active ligands and developed a statistical mixture model consensus score based on combining score means and variances. To evaluate performance, we used the common performance metrics ROCAUC and EF1 on 21 benchmark targets from DUD-E. Traditional consensus methods, such as taking the mean of quantile normalized docking scores, outperformed individual docking methods and are more robust to target variation. The mixture model and gradient boosting provided further improvements over the traditional consensus methods. These methods are readily applicable to new targets in academic research and overcome the potentially poor performance of using a single docking method on a new target.

  18. Performance of Ruecking's Word-compression Method When Applied to Machine Retrieval from a Library Catalog

    Directory of Open Access Journals (Sweden)

    Ben-Ami Lipetz

    1969-12-01

    Full Text Available F. H. Ruecking's word-compression algorithm for retrieval of bibliographic data from computer stores was tested for performance in matching user-supplied, unedited bibliographic data to the bibliographic data contained in a library catalog. The algorithm was tested by manual simulation, using data derived from 126 case studies of successful manual searches of the card catalog at Sterling Memorial Library, Yale University. The algorithm achieved 70% recall in comparison to conventional searching. Its accepta- bility as a substitute for conventional catalog searching methods is ques- tioned unless recall performance can be improved, either by use of the algorithm alone or in combination with other algorithms.

  19. The Knife Machine. Module 15.

    Science.gov (United States)

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

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

  20. Machine Shop Grinding Machines.

    Science.gov (United States)

    Dunn, James

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

  1. Evaluation of Cutting Performance of Diamond Saw Machine Using Artificial Bee Colony (ABC Algorithm

    Directory of Open Access Journals (Sweden)

    Masoud Akhyani

    2017-12-01

    Full Text Available Artificial Intelligence (AI techniques are used for solving the intractable engineering problems. In this study, it is aimed to study the application of artificial bee colony algorithm for predicting the performance of circular diamond saw in sawing of hard rocks. For this purpose, varieties of fourteen types of hard rocks were cut in laboratory using a cutting rig at 5 mm depth of cut, 40 cm/min feed rate and 3000 rpm peripheral speed. Four major mechanical and physical properties of studied rocks such as uniaxial compressive strength (UCS, Schimazek abrasivity factor (SF-a, Mohs hardness (Mh, and Young’s modulus (Ym were determined in rock mechanic laboratory. Artificial bee colony (ABC was used to classify the performance of circular diamond saw based on mentioned mechanical properties of rocks. Ampere consumption and wear rate of diamond saw were selected as criteria to evaluate the result of ABC algorithm. Ampere consumption was determined during cutting process and the average wear rate of diamond saw was calculated from width, length and height loss. The results of comparison between ABC’s results and cutting performance (ampere consumption and wear rate of diamond saw indicated the ability of metaheuristic algorithm such as ABC to evaluate the cutting performance.

  2. The impact of policy on firms' performance: the case of CNC machine tool industry in India

    NARCIS (Netherlands)

    Kumar, A.

    2003-01-01

    This study is about understanding how the government policy actually works at firm level in the context of developing countries' industrialization. In the literature, the discussions on impact of government policy on corporate performance primarily stress on macroeconomic aspects of industrial

  3. Optimation of a Table Conveyor Type Grading Machine to Increase the Performance of Green Coffee Manual Sortation

    Directory of Open Access Journals (Sweden)

    Sukrisno Widyotomo

    2006-05-01

    Full Text Available Coffee consumers request a good quality of green coffee to get a good coffee cup taste. Defective beans e.g. black bean, brown bean and broken bean are associated to low coffee quality which give negative effects to final taste. To meet the standard export requirement, coffee beans have to be graded before being traded. Until now, grading process is generally carried out manually. The method gives better product, so the grading cost is very expensive about 40% of total processing cost. Meanwhile, shortage of skill workers is a limiting factor of the process. Therefore, improving the manual sorting by providing machine for grading of green coffee is good alternative to reduce the grading cost. Indonesian Coffee and Cocoa Research Institute has designed a table conveyor type grading machine in order to improve the performance of the manual grading productivity and consistent quality and to reduce the grading cost. The conveyor belt has a dimension of 5700 mm of length, 610 mm of width and 6 mm of thickness. The rotating of belt conveyor powered by an electro motor 3 HP, 3 phase and 1420 rpm. The result showed that the optimum capacity of grading machine was 390 kg/hour reached when the speed 16 rpm and 3 kg/m 2 of green beans on belt conveyor with productivity 1870 kg/man-day compared to the productivity full manually process 743 kg/man-day. Percentage of product in outlet 1 was 4.2% as broken beans, 0.26% as brown beans, 0.68% as one hole in beans and 0.61% as more than one hole in beans. Percentage of product in outlet 2 was 39.54% as broken beans, 4.23% as brown beans 7.19% as black beans, 4.47% as one hole in beans and 4.43% as more than one hole in beans. Cost of grading process per kg of green coffee is Rp20,-. Key words : Coffee, Grading, Conveyor table, Quality

  4. Induction Machine with Improved Operating Performances for Electric Trucks. A FEM-Based Analysis

    Directory of Open Access Journals (Sweden)

    MUNTEANU, A.

    2010-05-01

    Full Text Available The paper presents a study concerning the performance developed by induction motors destined for motorization of heavy electric vehicles such as trucks. Taking into consideration the imposed restrictions, one presents, in a comparative manner, the main geometrical parameters which come of the classical design algorithms. A special attention is dedicated to the winding design, since it has to ensure two synchronous speeds corresponding to 16 and 8 poles, respectively. Moreover, the influence of the rotor slots shape for the improvement of the start-up is analyzed. Finally, a FEM-based study (approach based on finite element method is performed to put in view specific torque and slip values such as rated, start-up and pull-out ones.

  5. Performance of Rotary Cutter Type Breaking Machine for Breakingand Deshelling Cocoa Roasted Beans

    OpenAIRE

    Sukrisno Widyotomo; Sri Mulato; Edi Suharyanto

    2005-01-01

    Conversion of cocoa beans to chocolate product is, therefore, one of the promising alternatives to increase the value added of dried cocoa beans. On the other hand, the development of chocolate industry requires an appropriate technology that is not available yet for small or medium scale of business. Breaking and deshelling cocoa roasted beans is one important steps in cocoa processing to ascertain good chocolate quality. The aim of this research is to study performance of rotary cutter type...

  6. Enhancing MINIX 3 Input/Output performance using a virtual machine approach

    OpenAIRE

    Pessolani, Pablo Andrés; González, César Daniel

    2010-01-01

    MINIX 3 is an open-source operating system designed to be highly reliable, flexible, and secure. The kernel is extremely small and user processes, specialized servers and device drivers run as user-mode insulated processes. These features, the tiny amount of kernel code, and other aspects greatly enhance system reliability. The drawbacks of running device drivers in usermode are the performance penalties on input/output ports access, kernel data structures access, interrupt indirect manage...

  7. Going beyond a First Reader: A Machine Learning Methodology for Optimizing Cost and Performance in Breast Ultrasound Diagnosis.

    Science.gov (United States)

    Venkatesh, Santosh S; Levenback, Benjamin J; Sultan, Laith R; Bouzghar, Ghizlane; Sehgal, Chandra M

    2015-12-01

    The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two independent feature sets consisting of visual features based on a radiologist's interpretation of images and computer-extracted features when used as first and second readers and combined by adaptive boosting (AdaBoost) and a pruning classifier resulted in a very high level of diagnostic performance (area under the receiver operating characteristic curve = 0.98) at a cost of pruning a fraction (20%) of the cases for further evaluation by independent methods. AdaBoost also improved the diagnostic performance of the individual human observers and increased the agreement between their analyses. Pairing AdaBoost with selective pruning is a principled methodology for achieving high diagnostic performance without the added cost of an additional reader for differentiating solid breast masses by ultrasound. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  8. Investigation of Coated Cutting Tool Performance during Machining of Super Duplex Stainless Steels through 3D Wear Evaluations

    Directory of Open Access Journals (Sweden)

    Yassmin Seid Ahmed

    2017-08-01

    Full Text Available In this study, the wear mechanisms and tribological performance of uncoated and coated carbide tools were investigated during the turning of super duplex stainless steel (SDSS—Grade UNS S32750, known commercially as SAF 2507. The tool wear was evaluated throughout the cutting tests and the wear mechanisms were investigated using an Alicona Infinite Focus microscope and a scanning electron microscope (SEM equipped with energy dispersive spectroscopy (EDS. Tribo-film formation on the worn rake surface of the tool was analyzed using X-ray Photoelectron Spectroscopy (XPS. In addition, tribological performance was evaluated by studying chip characteristics such as thickness, compression ratio, shear angle, and undersurface morphology. Finally, surface integrity of the machined surface was investigated using the Alicona microscope to measure surface roughness and SEM to reveal the surface distortions created during the cutting process, combined with cutting force analyses. The results obtained showed that the predominant wear mechanisms are adhesion and chipping for all tools investigated and that the AlTiN coating system exhibited better performance in all aspects when compared with CVD TiCN + Al2O3 coated cutting insert and uncoated carbide insert; in particular, built-up edge formation was significantly reduced.

  9. Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

    Science.gov (United States)

    Munsell, B C; Wu, G; Fridriksson, J; Thayer, K; Mofrad, N; Desisto, N; Shen, D; Bonilha, L

    2017-09-09

    Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks that support naming ability. Importantly, naming is frequently impaired in other neurological disorders and by contrasting the neuronal structures supporting naming in TLE with other diseases, it will become possible to elucidate the common systems supporting naming. We aimed to evaluate the neuronal networks that support naming in TLE by using a machine learning algorithm intended to predict naming performance in subjects with medication refractory TLE using only the structural brain connectome reconstructed from diffusion tensor imaging. A connectome-based prediction framework was developed using network properties from anatomically defined brain regions across the entire brain, which were used in a multi-task machine learning algorithm followed by support vector regression. Nodal eigenvector centrality, a measure of regional network integration, predicted approximately 60% of the variance in naming. The nodes with the highest regression weight were bilaterally distributed among perilimbic sub-networks involving mainly the medial and lateral temporal lobe regions. In the context of emerging evidence regarding the role of large structural networks that support language processing, our results suggest intact naming relies on the integration of sub-networks, as opposed to being dependent on isolated brain areas. In the case of TLE, these sub-networks may be disproportionately indicative naming processes that are dependent semantic integration from memory and lexical retrieval, as opposed to multi-modal perception or motor speech production. Copyright © 2017. Published by Elsevier Inc.

  10. Alpha band functional connectivity correlates with the performance of brain-machine interfaces to decode real and imagined movements

    Directory of Open Access Journals (Sweden)

    Hisato eSugata

    2014-08-01

    Full Text Available Brain signals recorded from the primary motor cortex (M1 are known to serve a significant role in coding the information brain-machine interfaces (BMIs need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beamforming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.

  11. High-Speed Computation using FPGA for Excellent Performance of Direct Torque Control of Induction Machines

    Directory of Open Access Journals (Sweden)

    Tole Sutikno

    2016-03-01

    Full Text Available The major problems in hysteresis-based DTC are high torque ripple and variable switching frequency. In order to minimize the torque ripple, high sampling time and fast digital realization should be applied. The high sampling and fast digital realization time can be achieved by utilizing high-speed processor where the operation of the discrete hysteresis regulator is becoming similar to the operation of analog-based comparator. This can be achieved by utilizing field programmable gate array (FPGA which can perform a sampling at a very high speed, compared to the fact that developing an ASIC chip is expensive and laborious.

  12. A performance indicator of the effectiveness of human-machine interfaces for nuclear power plants

    International Nuclear Information System (INIS)

    Moray, N.; Jones, B.J.; Rasmussen, J.; Lee, J.D.; Vicente, K.J.; Brock, R.; Djemil, T.

    1993-01-01

    Effective interfaces must call up operators' deep understanding of plant operation if operators are to deal effectively with normal operation and diagnosis of transients. The present research examines the ability of a memory recall task to indicate the ability of an interface to couple plant state to operator knowledge. Novices, people with intermediate experience, and experienced nuclear power plant operators viewed three kinds of displays. They watched nine simulated transients and tried to recall the values of variables, or the states through which the plant passed, and to detect and diagnose the nature of the transients. The displays were simulated analog instruments, simulated analog with pressure-temperature graphics, and an animated representation of the Rankine cycle. The recall tasks did not show promise as indirect performance indicators of the quality of the interfaces, but the diagnosis test detected differences in the quality of the displays and the levels of expertise

  13. Unsupervised machine-learning method for improving the performance of ambulatory fall-detection systems

    Directory of Open Access Journals (Sweden)

    Yuwono Mitchell

    2012-02-01

    Full Text Available Abstract Background Falls can cause trauma, disability and death among older people. Ambulatory accelerometer devices are currently capable of detecting falls in a controlled environment. However, research suggests that most current approaches can tend to have insufficient sensitivity and specificity in non-laboratory environments, in part because impacts can be experienced as part of ordinary daily living activities. Method We used a waist-worn wireless tri-axial accelerometer combined with digital signal processing, clustering and neural network classifiers. The method includes the application of Discrete Wavelet Transform, Regrouping Particle Swarm Optimization, Gaussian Distribution of Clustered Knowledge and an ensemble of classifiers including a multilayer perceptron and Augmented Radial Basis Function (ARBF neural networks. Results Preliminary testing with 8 healthy individuals in a home environment yields 98.6% sensitivity to falls and 99.6% specificity for routine Activities of Daily Living (ADL data. Single ARB and MLP classifiers were compared with a combined classifier. The combined classifier offers the greatest sensitivity, with a slight reduction in specificity for routine ADL and an increased specificity for exercise activities. In preliminary tests, the approach achieves 100% sensitivity on in-group falls, 97.65% on out-group falls, 99.33% specificity on routine ADL, and 96.59% specificity on exercise ADL. Conclusion The pre-processing and feature-extraction steps appear to simplify the signal while successfully extracting the essential features that are required to characterize a fall. The results suggest this combination of classifiers can perform better than MLP alone. Preliminary testing suggests these methods may be useful for researchers who are attempting to improve the performance of ambulatory fall-detection systems.

  14. Performance improvement of 64-QAM coherent optical communication system by optimizing symbol decision boundary based on support vector machine

    Science.gov (United States)

    Chen, Wei; Zhang, Junfeng; Gao, Mingyi; Shen, Gangxiang

    2018-03-01

    High-order modulation signals are suited for high-capacity communication systems because of their high spectral efficiency, but they are more vulnerable to various impairments. For the signals that experience degradation, when symbol points overlap on the constellation diagram, the original linear decision boundary cannot be used to distinguish the classification of symbol. Therefore, it is advantageous to create an optimum symbol decision boundary for the degraded signals. In this work, we experimentally demonstrated the 64-quadrature-amplitude modulation (64-QAM) coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimum symbol decision boundary for improving the system performance. We investigated the influence of various impairments on the 64-QAM coherent optical communication systems, such as the impairments caused by modulator nonlinearity, phase skew between in-phase (I) arm and quadrature-phase (Q) arm of the modulator, fiber Kerr nonlinearity and amplified spontaneous emission (ASE) noise. We measured the bit-error-ratio (BER) performance of 75-Gb/s 64-QAM signals in the back-to-back and 50-km transmission. By using SVM to optimize symbol decision boundary, the impairments caused by I/Q phase skew of the modulator, fiber Kerr nonlinearity and ASE noise are greatly mitigated.

  15. Development of a High-Performance Fin-and-Tube Heat Exchanger with Vortex Generators for a Vending Machine

    Science.gov (United States)

    Iwasaki, Masamichi; Saito, Hiroshi; Mochizuki, Sadanari; Murata, Akira

    The effect of delta-wing-vortex generators (combination of a delta wing and a delta winglet pair) on the heat transfer performance of fin-and-tube heat exchangers for vending machines has been investegated. Flow visualizations, numerical simulations and heat transfer experiments were conducted to find an optimum geometrical shape and arrangement of the vortex generators. Maximum heat transfer enhancement was achieved by the combination of (a) the delta wing with the apex angle of 86 degrees and (b) the delta winglet pair with the inline angle of 45 degrees. In relatively low Reynolds number range, about 40 % increase in heat transfer coefficient was attained with the above mentioned combination of the vortex generators compared to the ordinary heat exchangers with plain fins. It was revealed that the heat transfer enhancement was attributed to (1) the longitudinal vortexes generated by the delta wing and (2) the reduction of wake area behind the tube. It was also found that an increase in the apex angle of the delta wing brought about heat transfer enhancement, and the scale as well as the streggth of the induced longitudinal vortices played an important role in the heat transfer performance.

  16. Performance characteristics of tunnel boring machine in basalt and pyroclastic rocks of Deccan traps – A case study

    Directory of Open Access Journals (Sweden)

    Prasnna Jain

    2014-02-01

    Full Text Available A 12.24 km long tunnel between Maroshi and Ruparel College is being excavated by tunnel boring machine (TBM to improve the water supply system of Greater Mumbai, India. In this paper, attempt has been made to establish the relationship between various litho-units of Deccan traps, stability of tunnel and TBM performances during the construction of 5.83 km long tunnel between Maroshi and Vakola. The Maroshi–Vakola tunnel passes under the Mumbai Airport and crosses both runways with an overburden cover of around 70 m. The tunneling work was carried out without disturbance to the ground. The rock types encountered during excavation are fine compacted basalt, porphyritic basalt, amygdaloidal basalt, pyroclastic rocks with layers of red boles and intertrappean beds consisting of various types of shales. Relations between rock mass properties, physico-mechanical properties, TBM specifications and the corresponding TBM performance were established. A number of support systems installed in the tunnel during excavation were also discussed. The aim of this paper is to establish, with appropriate accuracy, the nature of subsurface rock mass condition and to study how it will react to or behave during underground excavation by TBM. The experiences gained from this project will increase the ability to cope with unexpected ground conditions during tunneling using TBM.

  17. Cutting Performance of Low Stress Thick TiAlN PVD Coatings during Machining of Compacted Graphite Cast Iron (CGI

    Directory of Open Access Journals (Sweden)

    Kenji Yamamoto

    2018-01-01

    Full Text Available A new family of physical vapor deposited (PVD coatings is presented in this paper. These coatings are deposited by a superfine cathode (SFC using the arc method. They combine a smooth surface, high hardness, and low residual stresses. This allows the production of PVD coatings as thick as 15 µm. In some applications, in particular for machining of such hard to cut material as compacted graphite iron (CGI, such coatings have shown better tool life compared to the conventional PVD coatings that have a lower thickness in the range of up to 5 μm. Finite element modeling of the temperature/stress profiles was done for the SFC coatings to present the temperature/stress profiles during cutting. Comprehensive characterization of the coatings was performed using XRD, TEM, SEM/EDS studies, nano-hardness, nano-impact measurements, and residual stress measurements. Application of the coating with this set of characteristics reduces the intensity of buildup edge formation during turning of CGI, leading to longer tool life. Optimization of the TiAlN-based coatings composition (Ti/Al ratio, architecture (mono vs. multilayer, and thickness were performed. Application of the optimized coating resulted in a 40–60% improvement in the cutting tool life under finishing turning of CGI.

  18. Virtual Machine in Automation Projects

    OpenAIRE

    Xing, Xiaoyuan

    2010-01-01

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

  19. 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.

  20. Effect of 8 weeks of free-weight and machine-based strength training on strength and power performance.

    Science.gov (United States)

    Wirth, Klaus; Keiner, Michael; Hartmann, Hagen; Sander, Andre; Mickel, Christoph

    2016-12-01

    The aim of this study was to evaluate the effectiveness of free-weight and machine-based exercises to increase different strength and speed-strength variables. One hundred twenty male participants (age: 23.8 ± 2.5 years; body height: 181.0 ± 6.8 cm; body mass: 80.2 ± 8.9 kg) joined the study. The 2 experimental groups completed an 8 week periodized strength training program that included 2 training sessions per week. The exercises that were used in the strength training programs were the parallel barbell squat and the leg press. Before and after the training period, the 1-repetition-maximum in the barbell squat and the leg press, the squat jump, the countermovement jump and unilateral isometric force (maximal isometric force and the rate of force development) were evaluated. To compare each group pre vs. post-intervention, analysis of variance with repeated measures and Scheffé post-hoc tests were used. The leg press group increased their 1-repetition-maximum significantly (p squat group such variables as 1-repetition-maximum, the squat jump and the countermovement jump increased significantly (p squat group even showed a statistically significant decrease. Differences between the 2 experimental groups were detected for the squat jump and the countermovement jump. In comparison with the leg press, the squat might be a better strength training exercise for the development of jump performance.

  1. Sipping machine control system new design to perform integrity of nuclear fuel test in Cofrentes power plant

    Energy Technology Data Exchange (ETDEWEB)

    Palomo, M., E-mail: mpalomo@iqn.upv.es [Departamento de Ingenieria Quimica y Nuclear. Universidad Politecnica de Valencia (Spain); Urrea, M., E-mail: Matias.urrea@iberdrola.es [C.N.Cofrentes - Iberdrola Generacion S.A., Cofrentes, Valencia (Spain); Curiel, M., E-mail: m.curiel@lainsa.com [LAINSA Grupo Dominguis, Valencia (Spain); Arnaldos, A., E-mail: a.arnaldos@titaniast.com [TITANIA Servicios Tecnologicos SL, Grupo Dominguis, Valencia (Spain)

    2011-07-01

    This paper we present is related to SIPPING machine control system new design to perform integrity of nuclear fuel test. This test is a non destructive technique used for evaluating the radiated nuclear fuel coating structural integrity. It is based on the radioactive emission detection of fission elements in the reactor cooling system, using the fuel inspection equipment (SIPPING). SIPPING equipment consists of one simultaneous test bell-shaped vessel of eight fuel elements, and another one for individual element test, a control workstation and some accessories (cables, thermocouples, hoses). SIPPING inspection is carried out by means of fuel element vessel. Through air injection, water flows around the element and heat evacuation is reduced, so fuel elements temperature increases. Those elements with faults shall expelled fission components dissolved in water and/or as a gas component. The project aim is the SIPPING system control design and software based on LabVIEW, for control, monitoring and documentation of the SIPPING Test. This project shall give a major functionality to the system and, at the same time, shall facilitate the user a friendlier and interactive environment allowing: to substitute the present work platform with a real-time electronic system based on cRIO and a control software ad-hoc designed for SIPPING system; to equip new system of a major redundancy for data storage, minimising loss probability of the same. (author)

  2. ERD-based online brain-machine interfaces (BMI) in the context of neurorehabilitation: optimizing BMI learning and performance.

    Science.gov (United States)

    Soekadar, Surjo R; Witkowski, Matthias; Mellinger, Jürgen; Ramos, Ander; Birbaumer, Niels; Cohen, Leonardo G

    2011-10-01

    Event-related desynchronization (ERD) of sensori-motor rhythms (SMR) can be used for online brain-machine interface (BMI) control, but yields challenges related to the stability of ERD and feedback strategy to optimize BMI learning.Here, we compared two approaches to this challenge in 20 right-handed healthy subjects (HS, five sessions each, S1-S5) and four stroke patients (SP, 15 sessions each, S1-S15). ERD was recorded from a 275-sensor MEG system. During daily training,motor imagery-induced ERD led to visual and proprioceptive feedback delivered through an orthotic device attached to the subjects' hand and fingers. Group A trained with a heterogeneous reference value (RV) for ERD detection with binary feedback and Group B with a homogenous RV and graded feedback (10 HS and 2 SP in each group). HS in Group B showed better BMI performance than Group A (p learning was significantly better (p learning relative to use of a heterogeneous RV and binary feedback.

  3. Evaluation of cleaning and disinfection performance of automatic washer disinfectors machines in programs presenting different cycle times and temperatures.

    Science.gov (United States)

    Bergo, Maria do Carmo Noronha Cominato

    2006-01-01

    Thermal washer-disinfectors represent a technology that brought about great advantages such as, establishment of protocols, standard operating procedures, reduction in occupational risk of a biological and environmental nature. The efficacy of the cleaning and disinfection obtained by automatic washer disinfectors machines in running programs with different times and temperatures determined by the different official agencies was validated according to recommendations from ISO Standards 15883-1/1999 and HTM2030 (NHS Estates, 1997) for the determining of the Minimum Lethality and DAL both theoretically and through the use with thermocouples. In order to determine the cleaning efficacy, the Soil Test, Biotrace Pro-tect and the Protein Test Kit were used. The procedure to verify the CFU count of viable microorganisms was performed before and after the thermal disinfection. This article shows that the results are in compliance with the ISO and HTM Standards. The validation steps confirmed the high efficacy level of the Medical Washer-Disinfectors. This protocol enabled the evaluation of the procedure based on evidence supported by scientific research, aiming at the support of the Supply Center multi-professional personnel with information and the possibility of developing further research.

  4. Sipping machine control system new design to perform integrity of nuclear fuel test in Cofrentes power plant

    Energy Technology Data Exchange (ETDEWEB)

    Curiel, M. [Logistica y Acondicionamientos Industriales SAU, Sorolla Center, local 10, Av. de las Cortes Valencianas No. 58, 46015 Valencia (Spain); Palomo, M. J. [ISIRYM, Universidad Politecnica de Valencia, Camino de Vera s/n, Valencia (Spain); Urrea, M. [Iberdrola Generacion S. A., Central Nuclear Cofrentes, Carretera Almansa Requena s/n, 04662 Cofrentes, Valencia (Spain); Vaquer, J., E-mail: m.curiel@lainsa.co [TITANIA Servicios Tecnologicos SL, Sorolla Center, local 10, Av. de las Cortes Valencianas No. 58, 46015 Valencia (Spain)

    2010-10-15

    This paper related to Sipping machine control system new design to perform integrity of nuclear fuel test. This test is a non destructive technique used for evaluating the radiated nuclear fuel coating structural integrity. It is based on the radioactive emission detection of fission elements in the reactor cooling system, using the fuel inspection equipment Sipping. The equipment consists of one simultaneous test bell-shaped vessel of eight fuel elements, and another one for individual element test, a control workstation and some accessories (cables, thermocouples, hoses). Sipping inspection is carried out by means of fuel element vessel. Through air injection, water flows around the element and heat evacuation is reduced, so fuel elements temperature increases. Those elements with faults shall expelled fission components dissolved in water and/or as a gas component. The project aim is the Sipping system control design and software based on LabVIEWTM, for control, monitoring and documentation of the Sipping test. This project shall give a major functionality to the system and, at the same time, shall facilitate the user a friendlier and interactive environment allowing: 1) To substitute the present work platform with a real-time electronic system based on cRIO and a control software ad-hoc designed for Sipping system. 2) To equip new system of a major redundancy for data storage, minimising loss probability of the same. (Author)

  5. Performance comparison of machine learning methods for prognosis of hormone receptor status in breast cancer tissue samples.

    Science.gov (United States)

    Kalinli, Adem; Sarikoc, Fatih; Akgun, Hulya; Ozturk, Figen

    2013-06-01

    We examined the classification and prognostic scoring performances of several computer methods on different feature sets to obtain objective and reproducible analysis of estrogen receptor status in breast cancer tissue samples. Radial basis function network, k-nearest neighborhood search, support vector machines, naive bayes, functional trees, and k-means clustering algorithm were applied to the test datasets. Several features were employed and the classification accuracies of each method for these features were examined. The assessment results of the methods on test images were also experimentally compared with those of two experts. According to the results of our experimental work, a combination of functional trees and the naive bayes classifier gave the best prognostic scores indicating very good kappa agreement values (κ=0.899 and κ=0.949, p<0.001) with the experts. This combination also gave the best dichotomization rate (96.3%) for assessment of estrogen receptor status. Wavelet color features provided better classification accuracy than Laws texture energy and co-occurrence matrix features. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. Sipping machine control system new design to perform integrity of nuclear fuel test in Cofrentes power plant

    International Nuclear Information System (INIS)

    Curiel, M.; Palomo, M. J.; Urrea, M.; Vaquer, J.

    2010-10-01

    This paper related to Sipping machine control system new design to perform integrity of nuclear fuel test. This test is a non destructive technique used for evaluating the radiated nuclear fuel coating structural integrity. It is based on the radioactive emission detection of fission elements in the reactor cooling system, using the fuel inspection equipment Sipping. The equipment consists of one simultaneous test bell-shaped vessel of eight fuel elements, and another one for individual element test, a control workstation and some accessories (cables, thermocouples, hoses). Sipping inspection is carried out by means of fuel element vessel. Through air injection, water flows around the element and heat evacuation is reduced, so fuel elements temperature increases. Those elements with faults shall expelled fission components dissolved in water and/or as a gas component. The project aim is the Sipping system control design and software based on LabVIEWTM, for control, monitoring and documentation of the Sipping test. This project shall give a major functionality to the system and, at the same time, shall facilitate the user a friendlier and interactive environment allowing: 1) To substitute the present work platform with a real-time electronic system based on cRIO and a control software ad-hoc designed for Sipping system. 2) To equip new system of a major redundancy for data storage, minimising loss probability of the same. (Author)

  7. Ground Reaction Force and Mechanical Differences Between the Interim Resistive Exercise Device (iRED) and Smith Machine While Performing a Squat

    Science.gov (United States)

    Amonette, William E.; Bentley, Jason R.; Lee, Stuart M. C.; Loehr, James A.; Schneider, Suzanne

    2004-01-01

    Musculoskeletal unloading in microgravity has been shown to induce losses in bone mineral density, muscle cross-sectional area, and muscle strength. Currently, an Interim Resistive Exercise Device (iRED) is being flown on board the ISS to help counteract these losses. Free weight training has shown successful positive musculoskeletal adaptations. In biomechanical research, ground reaction forces (GRF) trajectories are used to define differences between exercise devices. The purpose of this evaluation is to quantify the differences in GRF between the iRED and free weight exercise performed on a Smith machine during a squat. Due to the differences in resistance properties, inertial loading and load application to the body between the two devices, we hypothesize that subjects using iRED will produce GRF that are significantly different from the Smith machine. There will be differences in bar/harness range of motion and the time when peak GRF occurred in the ROMbar. Three male subjects performed three sets of ten squats on the iRED and on the Smith Machine on two separate days at a 2-second cadence. Statistically significant differences were found between the two devices in all measured GRF variables. Average Fz and Fx during the Smith machine squat were significantly higher than iRED. Average Fy (16.82 plus or minus.23; p less than .043) was significantly lower during the Smith machine squat. The mean descent/ascent ratio of the magnitude of the resultant force vector of all three axes for the Smith machine and iRED was 0.95 and 0.72, respectively. Also, the point at which maximum Fz occurred in the range of motion (Dzpeak) was at different locations with the two devices.

  8. Differentiation of several interstitial lung disease patterns in HRCT images using support vector machine: role of databases on performance

    Science.gov (United States)

    Kale, Mandar; Mukhopadhyay, Sudipta; Dash, Jatindra K.; Garg, Mandeep; Khandelwal, Niranjan

    2016-03-01

    Interstitial lung disease (ILD) is complicated group of pulmonary disorders. High Resolution Computed Tomography (HRCT) considered to be best imaging technique for analysis of different pulmonary disorders. HRCT findings can be categorised in several patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Nodular, Normal etc. based on their texture like appearance. Clinician often find it difficult to diagnosis these pattern because of their complex nature. In such scenario computer-aided diagnosis system could help clinician to identify patterns. Several approaches had been proposed for classification of ILD patterns. This includes computation of textural feature and training /testing of classifier such as artificial neural network (ANN), support vector machine (SVM) etc. In this paper, wavelet features are calculated from two different ILD database, publically available MedGIFT ILD database and private ILD database, followed by performance evaluation of ANN and SVM classifiers in terms of average accuracy. It is found that average classification accuracy by SVM is greater than ANN where trained and tested on same database. Investigation continued further to test variation in accuracy of classifier when training and testing is performed with alternate database and training and testing of classifier with database formed by merging samples from same class from two individual databases. The average classification accuracy drops when two independent databases used for training and testing respectively. There is significant improvement in average accuracy when classifiers are trained and tested with merged database. It infers dependency of classification accuracy on training data. It is observed that SVM outperforms ANN when same database is used for training and testing.

  9. Support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

    Science.gov (United States)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.

  10. 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 –...

  11. Nanocomposites for Machining Tools

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon

    2017-01-01

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

  12. 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.

  13. Improvement of the Longitudinal Beam Dynamics Tuning Procedure for the MSU RIA Driver Linac

    CERN Document Server

    Doleans, Marc; Grimm, Terry L; Marti, Felix; Wu, Xiaoyu; York, Richard

    2005-01-01

    The Rare Isotope Accelerator (RIA) driver linac will use a superconducting, cw linac with independently phased superconducting radio frequency cavities for acceleration and, for the heavier ions, utilize beams of multiple-charge-states (multi-q). Given the acceleration of multi-q beams and a stringent beam loss requirement in the RIA driver linac, a new beam envelope code capable of simulating nonlinearities of the multi-q beam envelopes in the longitudinal phase space was developed. Using optimization routines, the code is able to maximize the linearity of the longitudinal phase space motion and thereby minimizing beam loss by finding values for the amplitude and phase of the cavities for a given accelerating lattice. Relative motion of the multi-q beams is also taken into account so that superposition of the beam centroids and matching of their Twiss parameters are automatically controlled. As a result, the linac tuning procedure has been simplified and the longitudinal lattice performance has been improved...

  14. Effect of 8 weeks of free-weight and machine-based strength training on strength and power performance

    Directory of Open Access Journals (Sweden)

    Wirth Klaus

    2016-12-01

    Full Text Available The aim of this study was to evaluate the effectiveness of free-weight and machine-based exercises to increase different strength and speed-strength variables. One hundred twenty male participants (age: 23.8 ± 2.5 years; body height: 181.0 ± 6.8 cm; body mass: 80.2 ± 8.9 kg joined the study. The 2 experimental groups completed an 8 week periodized strength training program that included 2 training sessions per week. The exercises that were used in the strength training programs were the parallel barbell squat and the leg press. Before and after the training period, the 1-repetition-maximum in the barbell squat and the leg press, the squat jump, the countermovement jump and unilateral isometric force (maximal isometric force and the rate of force development were evaluated. To compare each group pre vs. post-intervention, analysis of variance with repeated measures and Scheffé post-hoc tests were used. The leg press group increased their 1-repetition-maximum significantly (p < 0.001, while in the squat group such variables as 1-repetition-maximum, the squat jump and the countermovement jump increased significantly (p < 0.001. The maximal isometric force showed no statistically significant result for the repeated measures factor, while the rate of force development of the squat group even showed a statistically significant decrease. Differences between the 2 experimental groups were detected for the squat jump and the countermovement jump. In comparison with the leg press, the squat might be a better strength training exercise for the development of jump performance.

  15. Investigation of Pear Drying Performance by Different Methods and Regression of Convective Heat Transfer Coefficient with Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Mehmet Das

    2018-01-01

    Full Text Available In this study, an air heated solar collector (AHSC dryer was designed to determine the drying characteristics of the pear. Flat pear slices of 10 mm thickness were used in the experiments. The pears were dried both in the AHSC dryer and under the sun. Panel glass temperature, panel floor temperature, panel inlet temperature, panel outlet temperature, drying cabinet inlet temperature, drying cabinet outlet temperature, drying cabinet temperature, drying cabinet moisture, solar radiation, pear internal temperature, air velocity and mass loss of pear were measured at 30 min intervals. Experiments were carried out during the periods of June 2017 in Elazig, Turkey. The experiments started at 8:00 a.m. and continued till 18:00. The experiments were continued until the weight changes in the pear slices stopped. Wet basis moisture content (MCw, dry basis moisture content (MCd, adjustable moisture ratio (MR, drying rate (DR, and convective heat transfer coefficient (hc were calculated with both in the AHSC dryer and the open sun drying experiment data. It was found that the values of hc in both drying systems with a range 12.4 and 20.8 W/m2 °C. Three different kernel models were used in the support vector machine (SVM regression to construct the predictive model of the calculated hc values for both systems. The mean absolute error (MAE, root mean squared error (RMSE, relative absolute error (RAE and root relative absolute error (RRAE analysis were performed to indicate the predictive model’s accuracy. As a result, the rate of drying of the pear was examined for both systems and it was observed that the pear had dried earlier in the AHSC drying system. A predictive model was obtained using the SVM regression for the calculated hc values for the pear in the AHSC drying system. The normalized polynomial kernel was determined as the best kernel model in SVM for estimating the hc values.

  16. Applying Multi-Class Support Vector Machines for performance assessment of shipping operations: The case of tanker vessels

    DEFF Research Database (Denmark)

    Pagoropoulos, Aris; Møller, Anders H.; McAloone, Tim C.

    2017-01-01

    of feature selection algorithms. Afterwards, a model based on Multi- Class Support Vector Machines (SVM) was constructed and the efficacy of the approach is shown through the application of a test set. The results demonstrate the importance and benefits of machine learning algorithms in driving energy....... Identifying the potential of behavioural savings can be challenging, due to the inherent difficulty in analysing the data and operationalizing energy efficiency within the dynamic operating environment of the vessels. This article proposes a supervised learning model for identifying the presence of energy...

  17. Sizing models and performance analysis of volumetric expansion machines for waste heat recovery through organic Rankine cycles on passenger cars

    OpenAIRE

    Guillaume, Ludovic; Legros, Arnaud; Quoilin, Sylvain; Declaye, Sébastien; Lemort, Vincent

    2013-01-01

    This paper aims at helping designers of waste heat recovery organic (or non-organic) Rankine cycles on internal combustion engines to best select the expander among the piston, scroll and screw machines, and the working fluids among R245fa, ethanol and water. The first part of the paper presents the technical constraints inherent to each machine through a state of the art of the three technologies. The second part of the paper deals with the modeling of such expanders. Finally, in the last pa...

  18. Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2016-09-01

    Full Text Available This study evaluates the performance of a Support Vector Machine (SVM classifier to learn and detect changes in single- and multi-temporal X- and L-band Synthetic Aperture Radar (SAR images under varying conditions. The purpose is to provide guidance on how to train a powerful learning machine for change detection in SAR images and to contribute to a better understanding of potentials and limitations of supervised change detection approaches. This becomes particularly important on the background of a rapidly growing demand for SAR change detection to support rapid situation awareness in case of natural disasters. The application environment of this study thus focuses on detecting changes caused by the 2011 Tohoku earthquake and tsunami disaster, where single polarized TerraSAR-X and ALOS PALSAR intensity images are used as input. An unprecedented reference dataset of more than 18,000 buildings that have been visually inspected by local authorities for damages after the disaster forms a solid statistical population for the performance experiments. Several critical choices commonly made during the training stage of a learning machine are being assessed for their influence on the change detection performance, including sampling approach, location and number of training samples, classification scheme, change feature space and the acquisition dates of the satellite images. Furthermore, the proposed machine learning approach is compared with the widely used change image thresholding. The study concludes that a well-trained and tuned SVM can provide highly accurate change detections that outperform change image thresholding. While good performance is achieved in the binary change detection case, a distinction between multiple change classes in terms of damage grades leads to poor performance in the tested experimental setting. The major drawback of a machine learning approach is related to the high costs of training. The outcomes of this study, however

  19. Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel.

    Science.gov (United States)

    Wacker, Soren; Noskov, Sergei Yu

    2018-05-01

    Drug-induced abnormal heart rhythm known as Torsades de Pointes (TdP) is a potential lethal ventricular tachycardia found in many patients. Even newly released anti-arrhythmic drugs, like ivabradine with HCN channel as a primary target, block the hERG potassium current in overlapping concentration interval. Promiscuous drug block to hERG channel may potentially lead to perturbation of the action potential duration (APD) and TdP, especially when with combined with polypharmacy and/or electrolyte disturbances. The example of novel anti-arrhythmic ivabradine illustrates clinically important and ongoing deficit in drug design and warrants for better screening methods. There is an urgent need to develop new approaches for rapid and accurate assessment of how drugs with complex interactions and multiple subcellular targets can predispose or protect from drug-induced TdP. One of the unexpected outcomes of compulsory hERG screening implemented in USA and European Union resulted in large datasets of IC 50 values for various molecules entering the market. The abundant data allows now to construct predictive machine-learning (ML) models. Novel ML algorithms and techniques promise better accuracy in determining IC 50 values of hERG blockade that is comparable or surpassing that of the earlier QSAR or molecular modeling technique. To test the performance of modern ML techniques, we have developed a computational platform integrating various workflows for quantitative structure activity relationship (QSAR) models using data from the ChEMBL database. To establish predictive powers of ML-based algorithms we computed IC 50 values for large dataset of molecules and compared it to automated patch clamp system for a large dataset of hERG blocking and non-blocking drugs, an industry gold standard in studies of cardiotoxicity. The optimal protocol with high sensitivity and predictive power is based on the novel eXtreme gradient boosting (XGBoost) algorithm. The ML-platform with XGBoost

  20. Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield.

    Science.gov (United States)

    Hassanpour, Saeed; Langlotz, Curtis P; Amrhein, Timothy J; Befera, Nicholas T; Lungren, Matthew P

    2017-04-01

    The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices. An NLP system that uses terms and patterns in manually classified narrative knee MRI reports was constructed. The NLP system was trained and tested on expert-classified knee MRI reports from two major health care organizations. Radiology reports were modeled in the training set as vectors, and a support vector machine framework was used to train the classifier. A separate test set from each organization was used to evaluate the performance of the system. We evaluated the performance of the system both within and across organizations. Standard evaluation metrics, such as accuracy, precision, recall, and F1 score (i.e., the weighted average of the precision and recall), and their respective 95% CIs were used to measure the efficacy of our classification system. The accuracy for radiology reports that belonged to the model's clinically significant concept classes after training data from the same institution was good, yielding an F1 score greater than 90% (95% CI, 84.6-97.3%). Performance of the classifier on cross-institutional application without institution-specific training data yielded F1 scores of 77.6% (95% CI, 69.5-85.7%) and 90.2% (95% CI, 84.5-95.9%) at the two organizations studied. The results show excellent accuracy by the NLP machine learning classifier in classifying free-text knee MRI reports, supporting the institution-independent reproducibility of knee MRI report classification. Furthermore, the machine learning classifier performed well on free-text knee MRI reports from another institution. These data support the feasibility of multiinstitutional classification of radiologic imaging text reports with a single machine learning classifier without requiring institution-specific training data.

  1. Short-wave radiation in a free-electron laser based on the racetrack microtron RM-100 of MSU NIIYaF

    International Nuclear Information System (INIS)

    Grishin, V.K.; Darenskaya, L.V.

    1991-01-01

    Possibility of producing electromagnetic radiation in a free-electron laser (FEL), using beam of the racetrack microtron RM-100 of MSU NIIYaF, is evaluated. Two modes of FEL operation are considered. Single-particle mode with minimal amplification factor is possible at assigned electron beam parameters and maximal energy up to 20-50 MeV. Device specifications are presented. Collective radiation mode becomes possible due to the affect of electromagnetic wave channeling. Channeling occurs under auxillary transverse compression of 10A electron beam, permitted by RM-100 parameters. Possible parameters of FEL in UV range are presented. 20 refs.; 4 figs.; 5 tabs

  2. Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer

    International Nuclear Information System (INIS)

    Wang, Jing; Wu, Chen-Jiang; Zhang, Jing; Wang, Xiao-Ning; Zhang, Yu-Dong; Bao, Mei-Ling

    2017-01-01

    To investigate whether machine learning-based analysis of MR radiomics can help improve the performance PI-RADS v2 in clinically relevant prostate cancer (PCa). This IRB-approved study included 54 patients with PCa undergoing multi-parametric (mp) MRI before prostatectomy. Imaging analysis was performed on 54 tumours, 47 normal peripheral (PZ) and 48 normal transitional (TZ) zone based on histological-radiological correlation. Mp-MRI was scored via PI-RADS, and quantified by measuring radiomic features. Predictive model was developed using a novel support vector machine trained with: (i) radiomics, (ii) PI-RADS scores, (iii) radiomics and PI-RADS scores. Paired comparison was made via ROC analysis. For PCa versus normal TZ, the model trained with radiomics had a significantly higher area under the ROC curve (Az) (0.955 [95% CI 0.923-0.976]) than PI-RADS (Az: 0.878 [0.834-0.914], p < 0.001). The Az between them was insignificant for PCa versus PZ (0.972 [0.945-0.988] vs. 0.940 [0.905-0.965], p = 0.097). When radiomics was added, performance of PI-RADS was significantly improved for PCa versus PZ (Az: 0.983 [0.960-0.995]) and PCa versus TZ (Az: 0.968 [0.940-0.985]). Machine learning analysis of MR radiomics can help improve the performance of PI-RADS in clinically relevant PCa. (orig.)

  3. The influence of the negative-positive ratio and screening database size on the performance of machine learning-based virtual screening.

    Science.gov (United States)

    Kurczab, Rafał; Bojarski, Andrzej J

    2017-01-01

    The machine learning-based virtual screening of molecular databases is a commonly used approach to identify hits. However, many aspects associated with training predictive models can influence the final performance and, consequently, the number of hits found. Thus, we performed a systematic study of the simultaneous influence of the proportion of negatives to positives in the testing set, the size of screening databases and the type of molecular representations on the effectiveness of classification. The results obtained for eight protein targets, five machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest), two types of molecular fingerprints (MACCS and CDK FP) and eight screening databases with different numbers of molecules confirmed our previous findings that increases in the ratio of negative to positive training instances greatly influenced most of the investigated parameters of the ML methods in simulated virtual screening experiments. However, the performance of screening was shown to also be highly dependent on the molecular library dimension. Generally, with the increasing size of the screened database, the optimal training ratio also increased, and this ratio can be rationalized using the proposed cost-effectiveness threshold approach. To increase the performance of machine learning-based virtual screening, the training set should be constructed in a way that considers the size of the screening database.

  4. Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jing [CFDA, Center for Medical Device Evaluation, Beijing (China); Wu, Chen-Jiang; Zhang, Jing; Wang, Xiao-Ning; Zhang, Yu-Dong [First Affiliated Hospital with Nanjing Medical University, Department of Radiology, Nanjing, Jiangsu Province (China); Bao, Mei-Ling [First Affiliated Hospital with Nanjing Medical University, Department of Pathology, Nanjing (China)

    2017-10-15

    To investigate whether machine learning-based analysis of MR radiomics can help improve the performance PI-RADS v2 in clinically relevant prostate cancer (PCa). This IRB-approved study included 54 patients with PCa undergoing multi-parametric (mp) MRI before prostatectomy. Imaging analysis was performed on 54 tumours, 47 normal peripheral (PZ) and 48 normal transitional (TZ) zone based on histological-radiological correlation. Mp-MRI was scored via PI-RADS, and quantified by measuring radiomic features. Predictive model was developed using a novel support vector machine trained with: (i) radiomics, (ii) PI-RADS scores, (iii) radiomics and PI-RADS scores. Paired comparison was made via ROC analysis. For PCa versus normal TZ, the model trained with radiomics had a significantly higher area under the ROC curve (Az) (0.955 [95% CI 0.923-0.976]) than PI-RADS (Az: 0.878 [0.834-0.914], p < 0.001). The Az between them was insignificant for PCa versus PZ (0.972 [0.945-0.988] vs. 0.940 [0.905-0.965], p = 0.097). When radiomics was added, performance of PI-RADS was significantly improved for PCa versus PZ (Az: 0.983 [0.960-0.995]) and PCa versus TZ (Az: 0.968 [0.940-0.985]). Machine learning analysis of MR radiomics can help improve the performance of PI-RADS in clinically relevant PCa. (orig.)

  5. The Chainstitch Machine. Module 18.

    Science.gov (United States)

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

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

  6. Performance analysis of single stage libr-water absorption machine operated by waste thermal energy of internal combustion engine: Case study

    Science.gov (United States)

    Sharif, Hafiz Zafar; Leman, A. M.; Muthuraman, S.; Salleh, Mohd Najib Mohd; Zakaria, Supaat

    2017-09-01

    Combined heating, cooling, and power is also known as Tri-generation. Tri-generation system can provide power, hot water, space heating and air -conditioning from single source of energy. The objective of this study is to propose a method to evaluate the characteristic and performance of a single stage lithium bromide-water (LiBr-H2O) absorption machine operated with waste thermal energy of internal combustion engine which is integral part of trigeneration system. Correlations for computer sensitivity analysis are developed in data fit software for (P-T-X), (H-T-X), saturated liquid (water), saturated vapor, saturation pressure and crystallization temperature curve of LiBr-H2O Solution. Number of equations were developed with data fit software and exported into excel work sheet for the evaluation of number of parameter concerned with the performance of vapor absorption machine such as co-efficient of performance, concentration of solution, mass flow rate, size of heat exchangers of the unit in relation to the generator, condenser, absorber and evaporator temperatures. Size of vapor absorption machine within its crystallization limits for cooling and heating by waste energy recovered from exhaust gas, and jacket water of internal combustion engine also presented in this study to save the time and cost for the facilities managers who are interested to utilize the waste thermal energy of their buildings or premises for heating and air conditioning applications.

  7. 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

  8. 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.

  9. 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.

  10. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

    Science.gov (United States)

    Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

    2018-01-01

    Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that

  11. Evaluation of cleaning and disinfection performance of automatic washer disinfectors machines in programs presenting different cycle times and temperatures

    OpenAIRE

    Bergo,Maria do Carmo Noronha Cominato

    2006-01-01

    Thermal washer-disinfectors represent a technology that brought about great advantages such as, establishment of protocols, standard operating procedures, reduction in occupational risk of a biological and environmental nature. The efficacy of the cleaning and disinfection obtained by automatic washer disinfectors machines in running programs with different times and temperatures determined by the different official agencies was validated according to recommendations from ISO Standards 15883-...

  12. Face machines

    Energy Technology Data Exchange (ETDEWEB)

    Hindle, D.

    1999-06-01

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

  13. 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.

  14. Machine Learning.

    Science.gov (United States)

    Kirrane, Diane E.

    1990-01-01

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

  15. Using Standard-Sole Cost Method for Performance Gestion Accounting and Calculation Cost in the Machine Building Industry

    Directory of Open Access Journals (Sweden)

    Cleopatra Sendroiu

    2006-07-01

    Full Text Available The main purpose of improving and varying cost calculation methods in the machine building industry is to make them more operational and efficient in supplying the information necessary to the management in taking its decisions. The present cost calculation methods used in the machine building plants - global method and the method per orders - by which a historical cost is determined a posteriori used in deducting and post factum justification of manufacturing expenses does not offer the management the possibility to fully satisfy its need for information. We are talking about a change of conception in applying certain systems, methods and work techniques, according to the needs of efficient administration of production and the plant seen as a whole. The standard-cost method best answers to the needs of the effective management of the value side of the manufacturing process and raising economic efficiency. We consider that, in the machine building industry, these objectives can be achieved by using the standard - sole cost alternative of the standard-cost method.

  16. Using Standard-Sole Cost Method for Performance Gestion Accounting and Calculation Cost in the Machine Building Industry

    Directory of Open Access Journals (Sweden)

    Aureliana Geta Roman

    2006-09-01

    Full Text Available The main purpose of improving and varying cost calculation methods in the machine building industry is to make them more operational and efficient in supplying the information necessary to the management in taking its decisions. The present cost calculation methods used in the machine building plants – global method and the method per orders – by which a historical cost is determined a posteriori used in deducting and post factum justification of manufacturing expenses does not offer the management the possibility to fully satisfy its need for information. We are talking about a change of conception in applying certain systems, methods and work techniques, according to the needs of efficient administration of production and the plant seen as a whole. The standard-cost method best answers to the needs of the effective management of the value side of the manufacturing process and raising economic efficiency. We consider that, in the machine building industry, these objectives can be achieved by using the standard - sole cost alternative of the standard-cost method.

  17. Analysis of SNL/MSU/DOE Fatigue Database Trends for Wind Turbine Blade Materials 2010-2015.

    Energy Technology Data Exchange (ETDEWEB)

    John F. Mandell; Daniel D. Samborsky; David A. Miller; Pancasatya Agastra; Aaron T. Sears

    2016-02-01

    Wind turbine blades are designed to several major structural conditions, including tip deflection, strength and b uckling during severe loading, as well as very high numbers of fatigue cycles and various service environments. The MSU Database Program has, since 1989, addressed the broad range of properties needed for current and potential blade materials through stati c and fatigue testing and test development in cooperation with Sandia National Laboratories and wind industry and supplier partners. This report is the latest in a series, giving test results and analysis for the period 2010 - 2015. Program data are compiled in a public database [1] and other reports and publications given in the cited references. The report begins with an executive summary and introductory material including background discussion of previous related studies. Section 3 describes experimental methods including processing, test methods, instrumentation and test development. Section 4 provides static tension, compression and shear stress - strain properties in three directions using coupons sectioned from a thick infused unidirectional glass/epoxy laminate. The nonlinear, shear dominated static properties were characterized with loading - u nloading - reloading (LUR) tests in tension and compression to increasing load levels, for +-45O laminates. Section 5 explores the origins of tensile fatigue sensitivity in glass fiber dominated laminates with variations in fabric architecture including speci ally prepared fabrics and aligned strand laminates. Several types of resins are considered, with variations in resin toughness and bonding to fibers, as well as cure cycle variations for an epoxy. Conclusions are drawn as to the limits of tensile fatigue r esistance and the effects of resin type and fabric architecture, including the behavior of a commercial aligned glass strand product. Interactions between cyclic fatigue response and creep are addressed for off - axis (+-45O) glass

  18. 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 ...

  19. An HTS machine laboratory prototype

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  20. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M

    1982-04-01

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

  1. Effect of 8 weeks of free-weight and machine-based strength training on strength and power performance

    OpenAIRE

    Wirth Klaus; Keiner Michael; Hartmann Hagen; Sander Andre; Mickel Christoph

    2016-01-01

    Abstract The aim of this study was to evaluate the effectiveness of free-weight and machine-based exercises to increase different strength and speed-strength variables. One hundred twenty male participants (age: 23.8 ? 2.5 years; body height: 181.0 ? 6.8 cm; body mass: 80.2 ? 8.9 kg) joined the study. The 2 experimental groups completed an 8 week periodized strength training program that included 2 training sessions per week. The exercises that were used in the strength training programs were...

  2. Machine Learning and Radiology

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M.

    2012-01-01

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

  3. Machine learning and radiology.

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M

    2012-07-01

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

  4. 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.

  5. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

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

  6. Machine Translation

    Indian Academy of Sciences (India)

    Research Mt System Example: The 'Janus' Translating Phone Project. The Janus ... based on laptops, and simultaneous translation of two speakers in a dialogue. For more ..... The current focus in MT research is on using machine learning.

  7. The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables

    Science.gov (United States)

    Taha, Zahari; Muazu Musa, Rabiu; Majeed, Anwar P. P. Abdul; Razali Abdullah, Mohamad; Amirul Abdullah, Muhammad; Hasnun Arif Hassan, Mohd; Khalil, Zubair

    2018-04-01

    The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of bio-physiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. The bio-physiological variables namely resting heart rate, resting respiratory rate, resting diastolic blood pressure, resting systolic blood pressure, as well as calories intake, were measured prior to their shooting tests. k-means cluster analysis was applied to cluster the archers based on their scores on variables assessed. SVM models i.e. linear, quadratic and cubic kernel functions, were trained on the aforementioned variables. The k-means clustered the archers into high (HPA) and low potential archers (LPA), respectively. It was demonstrated that the linear SVM exhibited good accuracy with a classification accuracy of 94% in comparison the other tested models. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected bio-physiological variables examined.

  8. DNA-based machines.

    Science.gov (United States)

    Wang, Fuan; Willner, Bilha; Willner, Itamar

    2014-01-01

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

  9. 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...

  10. Simultaneous consideration of TQM and TPM influence on production performance: A case study on multicolor offset machine using SD Model

    Directory of Open Access Journals (Sweden)

    Nagaraj H. Kamath

    2016-09-01

    Full Text Available An attempt is made in this research to show the relevance of System Dynamics (SD as a tool for simultaneously considering TQM and TPM environment in a offset machine of a commercial printing press. By controlling the TQM and TPM variables, this model will attempt to simulate or predict the behavior of an efficient printing operation. Identifying other scenarios pertaining to Human factors, affecting the socio-technical variables is the future research work of this paper. The practical implication concerns the efficient decision making system in multi-colour sheet feed offset printing, by controlling the socio-technical variables. This is a novel approach of combining different socio-technical variables SD and Cased based approach for obtaining a productive environment in print operation called “Total Production Management”.

  11. A Demonstration of an Improved Filtering Technique for Analyzing Climate Records via Comparisons of Satellite MSU/AMSU Instrument Temperature Products from Three Research Groups

    Science.gov (United States)

    Swanson, R. E.

    2017-12-01

    Climate data records typically exhibit considerable variation over short time scales both from natural variability and from instrumentation issues. The use of linear least squares regression can provide overall trend information from noisy data, however assessing intermediate time periods can also provide useful information unavailable from basic trend calculations. Extracting the short term information in these data for assessing changes to climate or for comparison of data series from different sources requires the application of filters to separate short period variations from longer period trends. A common method used to smooth data is the moving average, which is a simple digital filter that can distort the resulting series due to the aliasing of the sampling period into the output series. We utilized Hamming filters to compare MSU/AMSU satellite time series developed by three research groups (UAH, RSS and NOAA STAR), the results published in January 2017 [http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-16-0121.1]. Since the last release date (July 2016) for the data analyzed in that paper, some of these groups have updated their analytical procedures and additional months of data are available to extend the series. An updated analysis of these data using the latest data releases available from each group is to be presented. Improved graphics will be employed to provide a clearer visualization of the differences between each group's results. As in the previous paper, the greatest difference between the UAH TMT series and those from the RSS and NOAA data appears during the early period of data from the MSU instruments before about 2003, as shown in the attached figure, and preliminary results indicate this pattern continues. Also to be presented are other findings regarding seasonal changes which were not included in the previous study.

  12. 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.

  13. Expanding the human-machine interface model to address the effect of leadership and management on performance

    International Nuclear Information System (INIS)

    Briant, V.S.; Childress, J.R.; Hannaman, G.W.

    1988-01-01

    The US nuclear industry now focuses on improving plant performance in measurable areas such as availability, safety, and operations. Risk assessment and pioneering work in human reliability analysis (HRA) have provided methods to identify and prioritize numerous design improvements. Improvements such as control room design, training, and procedures have contributed positively to plant performance. Human performance is increasingly recognized as a fundamental contributor to safe, economic, and reliable operation. Industry leaders suggest that improved leadership and management are keys to enhanced plant performance. This paper identifies several critical aspects of individual and group behavior that, if managed, could significantly contribute to improved performance. Some existing tools for measuring performance are cited

  14. Teletherapy machine

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  15. Coil Optimization for HTS Machines

    DEFF Research Database (Denmark)

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

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

  16. Removal performance and water quality analysis of paper machine white water in a full-scale wastewater treatment plant.

    Science.gov (United States)

    Shi, Shuai; Wang, Can; Fang, Shuai; Jia, Minghao; Li, Xiaoguang

    2017-06-01

    Paper machine white water is generally characterized as a high concentration of suspended solids and organic matters. A combined physicochemical-biological and filtration process was used in the study for removing pollutants in the wastewater. The removal efficiency of the pollutant in physicochemical and biological process was evaluated, respectively. Furthermore, advanced technology was used to analyse the water quality before and after the process treatment. Experimental results showed that the removal efficiency of suspend solids (SS) of the system was above 99%, while the physicochemical treatment in the forepart of the system had achieved about 97%. The removal efficiency of chemical oxygen demand (COD) and colour had the similar trend after physicochemical treatment and were corresponding to the proportion of suspended and the near-colloidal organic matter in the wastewater. After biological treatment, the removal efficiency of COD and colour achieved were about 97% and 90%, respectively. Furthermore, molecular weight (MW) distribution analysis showed that after treatment low MW molecules (analysis showed that most humic-like substances were effectively removed during the treatment. The analyses of gas chromatography/mass spectrometry showed that the composition of organic matter in the wastewater was not complicated. Methylsiloxanes were the typical organic components in the raw wastewater and most of them were removed after treatment.

  17. Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

    Science.gov (United States)

    Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

    2014-01-01

    The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  18. Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

    Directory of Open Access Journals (Sweden)

    Mert Bal

    2014-01-01

    Full Text Available The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  19. 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.

  20. Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

    International Nuclear Information System (INIS)

    Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

    2014-01-01

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

  1. Machine learning techniques for optical communication system optimization

    DEFF Research Database (Denmark)

    Zibar, Darko; Wass, Jesper; Thrane, Jakob

    In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.......In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction....

  2. 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...

  3. Machine rates for selected forest harvesting machines

    Science.gov (United States)

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

    2002-01-01

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

  4. Joint Training of Deep Boltzmann Machines

    OpenAIRE

    Goodfellow, Ian; Courville, Aaron; Bengio, Yoshua

    2012-01-01

    We introduce a new method for training deep Boltzmann machines jointly. Prior methods require an initial learning pass that trains the deep Boltzmann machine greedily, one layer at a time, or do not perform well on classifi- cation tasks.

  5. LHC machine: Status and plan

    International Nuclear Information System (INIS)

    Pojer, M.

    2013-01-01

    The LHC Run I was successfully concluded in March 2012. An incredible amount of data has been collected and the performance continuously improved during these three years. Important information on the limitations of the machine also emerged, which will be used to further increase the potential of the machine in the coming years. (authors)

  6. Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine.

    Science.gov (United States)

    Silitonga, Arridina Susan; Hassan, Masjuki Haji; Ong, Hwai Chyuan; Kusumo, Fitranto

    2017-11-01

    The purpose of this study is to investigate the performance, emission and combustion characteristics of a four-cylinder common-rail turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends. A kernel-based extreme learning machine (KELM) model is developed in this study using MATLAB software in order to predict the performance, combustion and emission characteristics of the engine. To acquire the data for training and testing the KELM model, the engine speed was selected as the input parameter, whereas the performance, exhaust emissions and combustion characteristics were chosen as the output parameters of the KELM model. The performance, emissions and combustion characteristics predicted by the KELM model were validated by comparing the predicted data with the experimental data. The results show that the coefficient of determination of the parameters is within a range of 0.9805-0.9991 for both the KELM model and the experimental data. The mean absolute percentage error is within a range of 0.1259-2.3838. This study shows that KELM modelling is a useful technique in biodiesel production since it facilitates scientists and researchers to predict the performance, exhaust emissions and combustion characteristics of internal combustion engines with high accuracy.

  7. EDM machinability of SiCw/Al composites

    Science.gov (United States)

    Ramulu, M.; Taya, M.

    1989-01-01

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

  8. Maximal Strength Performance and Muscle Activation for the Bench Press and Triceps Extension Exercises Adopting Dumbbell, Barbell, and Machine Modalities Over Multiple Sets.

    Science.gov (United States)

    Farias, Déborah de Araújo; Willardson, Jeffrey M; Paz, Gabriel A; Bezerra, Ewertton de S; Miranda, Humberto

    2017-07-01

    Farias, DdA, Willardson, JM, Paz, GA, Bezerra, EdS, and Miranda, H. Maximal strength performance and muscle activation for the bench press and triceps extension exercises adopting dumbbell, barbell and machine modalities over multiple sets. J Strength Cond Res 31(7): 1879-1887, 2017-The purpose of this study was to investigate muscle activation, total repetitions, and training volume for 3 bench press (BP) exercise modes (Smith machine [SMBP], barbell [BBP], and dumbbell [DBP]) that were followed by a triceps extension (TE) exercise. Nineteen trained men performed 3 testing protocols in random order, which included: (P1) SMBP + TE; (P2) BBP + TE; and (P3) DBP + TE. Each protocol involved 4 sets with a 10-repetition maximum (RM) load, immediately followed by a TE exercise that was also performed for 4 sets with a 10RM load. A 2-minute rest interval was adopted between sets and exercises. Surface electromyographic activity was assessed for the pectoralis major (PM), anterior deltoid (AD), biceps brachii (BB), and triceps brachii (TB). The results indicated that significantly higher total repetitions were achieved for the DBP (31.2 ± 3.2) vs. the BBP (27.8 ± 4.8). For the TE, significantly greater volume was achieved when this exercise was performed after the BBP (1,204.4 ± 249.4 kg) and DBP (1,216.8 ± 287.5 kg) vs. the SMBP (1,097.5 ± 193 kg). The DBP elicited significantly greater PM activity vs. the BBP. The SMBP elicited significantly greater AD activity vs. the BBP and DBP. During the different BP modes, the SMBP and BBP elicited significantly greater TB activity vs. the DBP. However, the DBP elicited significantly greater BB activity vs. the SMBP and BBP, respectively. During the succeeding TE exercise, significantly greater activity of the TB was observed when this exercise was performed after the BBP vs. the SMBP and DBP. Therefore, it seems that the variation in BP modes does influence both repetition performance and muscle activation patterns during the

  9. Machine learning systems

    Energy Technology Data Exchange (ETDEWEB)

    Forsyth, R

    1984-05-01

    With the dramatic rise of expert systems has come a renewed interest in the fuel that drives them-knowledge. For it is specialist knowledge which gives expert systems their power. But extracting knowledge from human experts in symbolic form has proved arduous and labour-intensive. So the idea of machine learning is enjoying a renaissance. Machine learning is any automatic improvement in the performance of a computer system over time, as a result of experience. Thus a learning algorithm seeks to do one or more of the following: cover a wider range of problems, deliver more accurate solutions, obtain answers more cheaply, and simplify codified knowledge. 6 references.

  10. Melting of major Glaciers in the western Himalayas: evidence of climatic changes from long term MSU derived tropospheric temperature trend (1979–2008

    Directory of Open Access Journals (Sweden)

    A. K. Prasad

    2009-12-01

    Full Text Available Global warming or the increase of the surface and atmospheric temperatures of the Earth, is increasingly discernible in the polar, sub-polar and major land glacial areas. The Himalayan and Tibetan Plateau Glaciers, which are the largest glaciers outside of the Polar Regions, are showing a large-scale decrease of snow cover and an extensive glacial retreat. These glaciers such as Siachen and Gangotri are a major water resource for Asia as they feed major rivers such as the Indus, Ganga and Brahmaputra. Due to scarcity of ground measuring stations, the long-term observations of atmospheric temperatures acquired from the Microwave Sounding Unit (MSU since 1979–2008 is highly useful. The lower and middle tropospheric temperature trend based on 30 years of MSU data shows warming of the Northern Hemisphere's mid-latitude regions. The mean month-to-month warming (up to 0.048±0.026°K/year or 1.44°K over 30 years of the mid troposphere (near surface over the high altitude Himalayas and Tibetan Plateau is prominent and statistically significant at a 95% confidence interval. Though the mean annual warming trend over the Himalayas (0.016±0.005°K/year, and Tibetan Plateau (0.008±0.006°K/year is positive, the month to month warming trend is higher (by 2–3 times, positive and significant only over a period of six months (December to May. The factors responsible for the reversal of this trend from June to November are discussed here. The inequality in the magnitude of the warming trends of the troposphere between the western and eastern Himalayas and the IG (Indo-Gangetic plains is attributed to the differences in increased aerosol loading (due to dust storms over these regions. The monthly mean lower-tropospheric MSU-derived temperature trend over the IG plains (dust sink region; up to 0.032±0.027°K/year and dust source regions (Sahara desert, Middle East, Arabian region, Afghanistan-Iran-Pakistan and Thar Desert regions; up to 0.068±0.033

  11. Electric machines

    CERN Document Server

    Gross, Charles A

    2006-01-01

    BASIC ELECTROMAGNETIC CONCEPTSBasic Magnetic ConceptsMagnetically Linear Systems: Magnetic CircuitsVoltage, Current, and Magnetic Field InteractionsMagnetic Properties of MaterialsNonlinear Magnetic Circuit AnalysisPermanent MagnetsSuperconducting MagnetsThe Fundamental Translational EM MachineThe Fundamental Rotational EM MachineMultiwinding EM SystemsLeakage FluxThe Concept of Ratings in EM SystemsSummaryProblemsTRANSFORMERSThe Ideal n-Winding TransformerTransformer Ratings and Per-Unit ScalingThe Nonideal Three-Winding TransformerThe Nonideal Two-Winding TransformerTransformer Efficiency and Voltage RegulationPractical ConsiderationsThe AutotransformerOperation of Transformers in Three-Phase EnvironmentsSequence Circuit Models for Three-Phase Transformer AnalysisHarmonics in TransformersSummaryProblemsBASIC MECHANICAL CONSIDERATIONSSome General PerspectivesEfficiencyLoad Torque-Speed CharacteristicsMass Polar Moment of InertiaGearingOperating ModesTranslational SystemsA Comprehensive Example: The ElevatorP...

  12. Charging machine

    International Nuclear Information System (INIS)

    Medlin, J.B.

    1976-01-01

    A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine. 3 claims, 11 drawing figures

  13. 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.

  14. Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.

    Science.gov (United States)

    Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S

    2011-05-15

    Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.

  15. Advanced SLARette delivery machine

    International Nuclear Information System (INIS)

    Bodner, R.R.

    1995-01-01

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

  16. Support vector machine in machine condition monitoring and fault diagnosis

    Science.gov (United States)

    Widodo, Achmad; Yang, Bo-Suk

    2007-08-01

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

  17. The 1/3-scale aerodynamics performance test of helium compressor for GTHTR300 turbo machine of JAERI (step 1)

    International Nuclear Information System (INIS)

    Takada, Shoji; Takizuka, Takakazu; Kunitomi, Kazuhiko; Xing, Yan

    2003-01-01

    A program for research and development on aerodynamics in a helium gas compressor was planned for the power conversion system of the Gas Turbine High Temperature Reactor (GTHTR300). The three-dimensional aerodynamic design of the compressor achieved a high polytropic efficiency of 90%, keeping a sufficient surge margin over 30%. To validate the design of the helium gas compressor of GTHTR300, aerodynamic performance tests were planned, and a 1/3-scale, 4-stage compressor model was designed. In the tests, the performance data of the helium gas compressor model will be acquired by using helium gas as a working fluid. The maximum design pressure at the model inlet is 0.88 MPa, which allows the Reynolds number to be sufficiently high. The present study is entrusted from the Ministry of Education, Culture, Sports, Science and Technology of Japan. (author)

  18. Development of a performance indicator of the effectiveness of human-machine interfaces for nuclear power plants

    International Nuclear Information System (INIS)

    Moray, N.

    1990-01-01

    With the development of computer graphic displays being increasingly proposed for NPP control rooms it becomes very important to be able to assess the degree to which they support improved operator performance. Three questions can be asked. (1) Will a new interface improve the existing level of performance so that even operators with relatively low levels of skill can have their performance dramatically improved? (2) Which display does this most effectively? and (3) Is it possible to assess the level of skill of an operator when using a new or existing interface design? The work to be described makes use of a well established phenomenon in cognitive psychology. In many fields of knowledge experts are able to recall displayed information and use it for decisions with a very much greater efficiency than novices or those of lower skill levels. This is however only true when the way in which the information is displayed maps the intrinsic relations among the variables in a way which matches the cognitive functions of the operator and his mental model of the controlled process. In this paper the conceptual background of the research is described and preliminary experimental work outlined

  19. On the suitability of Elekta’s Agility 160 MLC for tracked radiation delivery: closed-loop machine performance

    International Nuclear Information System (INIS)

    Glitzner, M; Crijns, S P M; De Senneville, B Denis; Lagendijk, J J W; Raaymakers, B W

    2015-01-01

    For motion adaptive radiotherapy, dynamic multileaf collimator tracking can be employed to reduce treatment margins by steering the beam according to the organ motion. The Elekta Agility 160 MLC has hitherto not been evaluated for its tracking suitability. Both dosimetric performance and latency are key figures and need to be assessed generically, independent of the used motion sensor. In this paper, we propose the use of harmonic functions directly fed to the MLC to determine its latency during continuous motion. Furthermore, a control variable is extracted from a camera system and fed to the MLC. Using this setup, film dosimetry and subsequent γ statistics are performed, evaluating the response when tracking (MRI)-based physiologic motion in a closed-loop. The delay attributed to the MLC itself was shown to be a minor contributor to the overall feedback chain as compared to the impact of imaging components such as MRI sequences. Delay showed a linear phase behaviour of the MLC employed in continuously dynamic applications, which enables a general MLC-characterization. Using the exemplary feedback chain, dosimetry showed a vast increase in pass rate employing γ statistics. In this early stage, the tracking performance of the Agility using the test bench yielded promising results, making the technique eligible for translation to tracking using clinical imaging modalities. (paper)

  20. GPK heading machine

    Energy Technology Data Exchange (ETDEWEB)

    Krmasek, J.; Novosad, K.

    1981-01-01

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

  1. Representational Machines

    DEFF Research Database (Denmark)

    Photography not only represents space. Space is produced photographically. Since its inception in the 19th century, photography has brought to light a vast array of represented subjects. Always situated in some spatial order, photographic representations have been operatively underpinned by social...... 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...... possibilities, and genre distinctions. Presenting several distinct ways of producing space photographically, this book opens a new and important field of inquiry for photography research....

  2. Shear machines

    International Nuclear Information System (INIS)

    Astill, M.; Sunderland, A.; Waine, M.G.

    1980-01-01

    A shear machine for irradiated nuclear fuel elements has a replaceable shear assembly comprising a fuel element support block, a shear blade support and a clamp assembly which hold the fuel element to be sheared in contact with the support block. A first clamp member contacts the fuel element remote from the shear blade and a second clamp member contacts the fuel element adjacent the shear blade and is advanced towards the support block during shearing to compensate for any compression of the fuel element caused by the shear blade (U.K.)

  3. Machine parameters and characteristic features

    International Nuclear Information System (INIS)

    Le Duff, J.

    1979-01-01

    The design and operating characteristics of LEP are presented. Its probable performance, possible improvements and cost are discussed and some comparisons are drawn with machines currently in operation. (W.D.L.)

  4. The Button Sew Machine. Module 12.

    Science.gov (United States)

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

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

  5. The Zig Zag Machine. Module 14.

    Science.gov (United States)

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

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

  6. The Bar Tack Machine. Module 16.

    Science.gov (United States)

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

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

  7. Electricity of machine tool

    International Nuclear Information System (INIS)

    Gijeon media editorial department

    1977-10-01

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

  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. Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models

    Directory of Open Access Journals (Sweden)

    LeDonne Norman C

    2011-02-01

    Full Text Available Abstract Background Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI curves via the SALI curve integral (SCI as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. Results The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. Conclusion The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

  10. Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models.

    Science.gov (United States)

    Ledonne, Norman C; Rissolo, Kevin; Bulgarelli, James; Tini, Leonard

    2011-02-07

    Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI) curves via the SALI curve integral (SCI) as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

  11. 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 ...

  12. Environmental diagnosis of the washing machine motor

    DEFF Research Database (Denmark)

    Erichsen, Hanne K. Linnet

    1997-01-01

    An environmental diagnosis of the washing machine focusing on the motor is performed. The goal of the diagnosis is to designate environmental focus points in the product. The LCA of the washing machine showed impact potentials from the life cycle of the product (see: LCA of a washing machine). Th...... up 2%, Manually disassembling and recycling of metals, Reuse of motor in a new washing machine, aluminium wire instead of copper wire in the motor....

  13. Permutation parity machines for neural cryptography.

    Science.gov (United States)

    Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

    2010-06-01

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

  14. Permutation parity machines for neural cryptography

    International Nuclear Information System (INIS)

    Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

    2010-01-01

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

  15. Determining the Particle Size of Debris from a Tunnel Boring Machine Through Photographic Analysis and Comparison Between Excavation Performance and Rock Mass Properties

    Science.gov (United States)

    Rispoli, A.; Ferrero, A. M.; Cardu, M.; Farinetti, A.

    2017-10-01

    This paper presents the results of a study carried out on a 6.3-m-diameter exploratory tunnel excavated in hard rock by an open tunnel boring machine (TBM). The study provides a methodology, based on photographic analysis, for the evaluation of the particle size distribution of debris produced by the TBM. A number of tests were carried out on the debris collected during the TBM advancement. In order to produce a parameter indicative of the particle size of the debris, the coarseness index (CI) was defined and compared with some parameters representative of the TBM performance [i.e. the excavation specific energy (SE) and field penetration index (FPI)] and rock mass features, such as RMR, GSI, uniaxial compression strength and joint spacing. The results obtained showed a clear trend between the CI and some TBM performance parameters, such as SE and FPI. On the contrary, due to the rock mass fracturing, a clear relationship between the CI and rock mass characteristics was not found.

  16. Performance of Ultrasound in the Diagnosis of Gout in a Multi-Center Study

    DEFF Research Database (Denmark)

    Ogdie, Alexis; Taylor, William J; Neogi, Tuhina

    2017-01-01

    OBJECTIVES: To examine the performance of ultrasound for the diagnosis of gout using presence of monosodium urate (MSU) crystals as the gold standard. METHODS: We analyzed data from the Study for Updated Gout Classification Criteria (SUGAR), a large, multi-center observational cross-sectional stu...

  17. 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...

  18. Machine Protection

    International Nuclear Information System (INIS)

    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 interlock system providing the glue between these systems. The most recent accelerator, the LHC, will operate with about 3 × 10 14 protons per beam, corresponding to an energy stored in each beam of 360 MJ. This energy can cause massive damage to accelerator equipment in case of uncontrolled beam loss, and a single accident damaging vital parts of the accelerator could interrupt operation for years. This article provides an overview of the requirements for protection of accelerator equipment and introduces the various protection systems. Examples are mainly from LHC, SNS and ESS

  19. Machine terms dictionary

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1979-04-15

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

  20. Performance Analysis of Machine-Learning Approaches for Modeling the Charging/Discharging Profiles of Stationary Battery Systems with Non-Uniform Cell Aging

    Directory of Open Access Journals (Sweden)

    Nandha Kumar Kandasamy

    2017-06-01

    Full Text Available The number of Stationary Battery Systems (SBS connected to various power distribution networks across the world has increased drastically. The increase in the integration of renewable energy sources is one of the major contributors to the increase in the number of SBS. SBS are also used in other applications such as peak load management, load-shifting, voltage regulation and power quality improvement. Accurately modeling the charging/discharging characteristics of such SBS at various instances (charging/discharging profile is vital for many applications. Capacity loss due to the aging of the batteries is an important factor to be considered for estimating the charging/discharging profile of SBS more accurately. Empirical modeling is a common approach used in the literature for estimating capacity loss, which is further used for estimating the charging/discharging profiles of SBS. However, in the case of SBS used for renewable integration and other grid related applications, machine-learning (ML based models provide extreme flexibility and require minimal resources for implementation. The models can even leverage existing smart meter data to estimate the charging/discharging profile of SBS. In this paper, an analysis on the performance of different ML approaches that can be applied for lithium iron phosphate battery systems and vanadium redox flow battery systems used as SBS is presented for the scenarios where the aging of individual cells is non-uniform.

  1. Determination of efficiencies, loss mechanisms, and performance degradation factors in chopper controlled dc vehical motors. Section 2: The time dependent finite element modeling of the electromagnetic field in electrical machines: Methods and applications. Ph.D. Thesis

    Science.gov (United States)

    Hamilton, H. B.; Strangas, E.

    1980-01-01

    The time dependent solution of the magnetic field is introduced as a method for accounting for the variation, in time, of the machine parameters in predicting and analyzing the performance of the electrical machines. The method of time dependent finite element was used in combination with an also time dependent construction of a grid for the air gap region. The Maxwell stress tensor was used to calculate the airgap torque from the magnetic vector potential distribution. Incremental inductances were defined and calculated as functions of time, depending on eddy currents and saturation. The currents in all the machine circuits were calculated in the time domain based on these inductances, which were continuously updated. The method was applied to a chopper controlled DC series motor used for electric vehicle drive, and to a salient pole sychronous motor with damper bars. Simulation results were compared to experimentally obtained ones.

  2. 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

  3. Novel biofuel formulations for enhanced vehicle performance

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Dennis [Michigan State Univ., East Lansing, MI (United States); Narayan, Ramani [Michigan State Univ., East Lansing, MI (United States); Berglund, Kris [Michigan State Univ., East Lansing, MI (United States); Lira, Carl [Michigan State Univ., East Lansing, MI (United States); Schock, Harold [Michigan State Univ., East Lansing, MI (United States); Jaberi, Farhad [Michigan State Univ., East Lansing, MI (United States); Lee, Tonghun [Michigan State Univ., East Lansing, MI (United States); Anderson, James [Michigan State Univ., East Lansing, MI (United States); Wallington, Timothy [Michigan State Univ., East Lansing, MI (United States); Kurtz, Eric [Michigan State Univ., East Lansing, MI (United States); Ruona, Will; Hass, Heinz

    2013-08-30

    This interdisciplinary research program at Michigan State University, in collaboration with Ford Motor Company, has explored the application of tailored or designed biofuels for enhanced vehicle performance and reduced emissions. The project has included a broad range of experimental research, from chemical and biological formation of advanced biofuel components to multicylinder engine testing of blended biofuels to determine engine performance parameters. In addition, the project included computation modeling of biofuel physical and combustion properties, and simulation of advanced combustion modes in model engines and in single cylinder engines. Formation of advanced biofuel components included the fermentation of five-carbon and six-carbon sugars to n-butanol and to butyric acid, two four-carbon building blocks. Chemical transformations include the esterification of the butyric acid produced to make butyrate esters, and the esterification of succinic acid with n-butanol to make dibutyl succinate (DBS) as attractive biofuel components. The conversion of standard biodiesel, made from canola or soy oil, from the methyl ester to the butyl ester (which has better fuel properties), and the ozonolysis of biodiesel and the raw oil to produce nonanoate fuel components were also examined in detail. Physical and combustion properties of these advanced biofuel components were determined during the project. Physical properties such as vapor pressure, heat of evaporation, density, and surface tension, and low temperature properties of cloud point and cold filter plugging point were examined for pure components and for blends of components with biodiesel and standard petroleum diesel. Combustion properties, particularly emission delay that is the key parameter in compression ignition engines, was measured in the MSU Rapid Compression Machine (RCM), an apparatus that was designed and constructed during the project simulating the compression stroke of an internal combustion

  4. RISMA: A Rule-based Interval State Machine Algorithm for Alerts Generation, Performance Analysis and Monitoring Real-Time Data Processing

    Science.gov (United States)

    Laban, Shaban; El-Desouky, Aly

    2013-04-01

    The monitoring of real-time systems is a challenging and complicated process. So, there is a continuous need to improve the monitoring process through the use of new intelligent techniques and algorithms for detecting exceptions, anomalous behaviours and generating the necessary alerts during the workflow monitoring of such systems. The interval-based or period-based theorems have been discussed, analysed, and used by many researches in Artificial Intelligence (AI), philosophy, and linguistics. As explained by Allen, there are 13 relations between any two intervals. Also, there have also been many studies of interval-based temporal reasoning and logics over the past decades. Interval-based theorems can be used for monitoring real-time interval-based data processing. However, increasing the number of processed intervals makes the implementation of such theorems a complex and time consuming process as the relationships between such intervals are increasing exponentially. To overcome the previous problem, this paper presents a Rule-based Interval State Machine Algorithm (RISMA) for processing, monitoring, and analysing the behaviour of interval-based data, received from real-time sensors. The proposed intelligent algorithm uses the Interval State Machine (ISM) approach to model any number of interval-based data into well-defined states as well as inferring them. An interval-based state transition model and methodology are presented to identify the relationships between the different states of the proposed algorithm. By using such model, the unlimited number of relationships between similar large numbers of intervals can be reduced to only 18 direct relationships using the proposed well-defined states. For testing the proposed algorithm, necessary inference rules and code have been designed and applied to the continuous data received in near real-time from the stations of International Monitoring System (IMS) by the International Data Centre (IDC) of the Preparatory

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

    International Nuclear Information System (INIS)

    Abdul Hafid

    2008-01-01

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

  6. Addiction Machines

    Directory of Open Access Journals (Sweden)

    James Godley

    2011-10-01

    Full Text Available Entry into the crypt William Burroughs shared with his mother opened and shut around a failed re-enactment of William Tell’s shot through the prop placed upon a loved one’s head. The accidental killing of his wife Joan completed the installation of the addictation machine that spun melancholia as manic dissemination. An early encryptment to which was added the audio portion of abuse deposited an undeliverable message in WB. Wil- liam could never tell, although his corpus bears the in- scription of this impossibility as another form of pos- sibility. James Godley is currently a doctoral candidate in Eng- lish at SUNY Buffalo, where he studies psychoanalysis, Continental philosophy, and nineteenth-century litera- ture and poetry (British and American. His work on the concept of mourning and “the dead” in Freudian and Lacanian approaches to psychoanalytic thought and in Gothic literature has also spawned an essay on zombie porn. Since entering the Academy of Fine Arts Karlsruhe in 2007, Valentin Hennig has studied in the classes of Sil- via Bächli, Claudio Moser, and Corinne Wasmuht. In 2010 he spent a semester at the Dresden Academy of Fine Arts. His work has been shown in group exhibi- tions in Freiburg and Karlsruhe.

  7. Smart Machine Protection System

    International Nuclear Information System (INIS)

    Clark, S.; Nelson, D.; Grillo, A.; Spencer, N.; Hutchinson, D.; Olsen, J.; Millsom, D.; White, G.; Gromme, T.; Allison, S.; Underwood, K.; Zelazny, M.; Kang, H.

    1991-11-01

    A Machine Protection System implemented on the SLC automatically controls the beam repetition rates in the accelerator so that radiation or temperature faults slow the repetition rate to bring the fault within tolerance without shutting down the machine. This process allows the accelerator to aid in the fault diagnostic process, and the protection system automatically restores the beams back to normal rates when the fault is diagnosed and corrected. The user interface includes facilities to monitor the performance of the system, and track rate limits, faults, and recoveries. There is an edit facility to define the devices to be included in the protection system, along with their set points, limits, and trip points. This set point and limit data is downloaded into the CAMAC modules, and the configuration data is compiled into a logical decision tree for the 68030 processor. 3 figs

  8. Smart machine protection system

    International Nuclear Information System (INIS)

    Clark, S.; Nelson, D.; Grillo, A.

    1992-01-01

    A Machine Protection System implemented on the SLC automatically controls the beam repetition rates in the accelerator so that radiation or temperature faults slow the repetition rate to bring the fault within tolerance without shutting down the machine. This process allows the accelerators to aid in the fault diagnostic process, and the protection system automatically restores the beams back to normal rates when the fault is diagnosed and corrected. The user interface includes facilities to monitor the performance of the system, and track rate limits, faults, and recoveries. There is an edit facility to define the devices to be included in the protection system, along with their set points, limits, and trip points. This set point and limit data is downloaded into the CAMAC modules, and the configuration data is complied into a logical decision tree for the 68030 processor. (author)

  9. Investigating the performance of support vector machine and artificial neural networks in predicting solar radiation on a tilted surface: Saudi Arabia case study

    International Nuclear Information System (INIS)

    Ramli, Makbul A.M.; Twaha, Ssennoga; Al-Turki, Yusuf A.

    2015-01-01

    Highlights: • The performance of SVM and ANN in predicting solar radiation was investigated. • Optimum result was obtained with 16° and 37.5° tilt angles for Jeddah and Qassim. • RMSE, CC, and MRE statistical measures have been used to evaluate the performance. • SVM has significantly higher accuracy, is faster and robust during computation. - Abstract: In this paper, investigation of the performance of a support vector machine (SVM) and artificial neural networks (ANN) in predicting solar radiation on PV panel surfaces with particular tilt angles was carried out on two sites in Saudi Arabia. The diffuse, direct, and global solar radiation data on a horizontal surface were used as the basis for predicting the radiation on a tilted surface. The amount of data used is equivalent to 360 days, averaged from the 5-min basis data. By solving the tilt angle equation, an optimum value of solar radiation was obtained using a tilt angle of 16° and 37.5° for Jeddah and Qassim locations, respectively. The evaluation of performance and comparison of results of ANN as well as SVM and the measured/calculated data are made on the basis of statistical measures including the root mean square error (RMSE), coefficient of correlation (CC), and magnitude of relative error (MRE). The speed of computation of the algorithms is also considered for comparison. Results indicate that for Jeddah, the CC for SVM is between 0.918 and 0.967 for training and in the range of 0.91981–0.97641 for testing while that of ANN is in the range of 0.517–0.9692 for training and 0.0361–0.0961 for testing. For Qassim, the results are even better with CC of 0.999 for training and 0.987 for testing ANN showed higher values of MRE ranging between 0.19 and 1.16 and SVM is between 0.33 and 0.51 for training and testing respectively. In terms of speed of computation, it is observed that SVM is faster than ANN in predicting solar radiation data with a lower speed of 2.15 s compared to 4.56 s for ANN

  10. 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.

  11. Deep learning: Using machine learning to study biological vision

    OpenAIRE

    Majaj, Najib; Pelli, Denis

    2017-01-01

    Today most vision-science presentations mention machine learning. Many neuroscientists use machine learning to decode neural responses. Many perception scientists try to understand recognition by living organisms. To them, machine learning offers a reference of attainable performance based on learned stimuli. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions.

  12. 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.

  13. Machine technology: a survey

    International Nuclear Information System (INIS)

    Barbier, M.M.

    1981-01-01

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

  14. Machine Shop Lathes.

    Science.gov (United States)

    Dunn, James

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

  15. Superconducting rotating machines

    International Nuclear Information System (INIS)

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

    1975-01-01

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

  16. NASA Partnership with JSU and MSU to Promote Remote Sensing Applications and Global Climate Change Education: 2013 Summer Course/Workshop

    Science.gov (United States)

    Reddy, S. R.

    2014-12-01

    NASA Innovations in Climate Education (NICE) is a competitive project to promote climate and Earth system science literacy and seeks to increase the access of underrepresented minority groups to science careers and educational opportunities. A three year funding was received from NASA to partnership with JSU and MSU under cooperative agreement "Strengthening Global Climate Change education through Remote Sensing Application in Coastal Environment using NASA Satellite Data and Models". The goal is to increase the number of undergraduate students at Jackson State University, a Historically Black University, who are prepared to pursue higher academic degrees and careers in the fields relevant to earth system science global climate change, marine and environmental sciences. A two week summer course/workshop was held during May 20-31, 2013 at JSU, focusing on historical and technical concepts of remote sensing technology and applications to climate and global climate change. Nine students from meteorology, biology, industrial technology and computer science/engineering of JSU participated in the course/workshop. The lecture topics include: introduction to remote sensing and GIS, introduction to atmospheric science and climate, introduction to NASA innovations in climate education, introduction to remote sensing technology for bio-geosphere, introduction to earth system science, principles of paleoclimatology and global change, daily weather briefing, satellite image interpretation and so on. In addition to lectures, lab sessions were held for hand-on experiences for remote sensing applications to atmosphere, biosphere, earth system science and climate change using ERDAS/ENVI GIS software and satellite tools. Field trip to Barnett reservoir and National weather Service (NWS) was part of the workshop. Some of the activities of the sessions will be presented. Basics of Earth System Science is a non-mathematical introductory course designed for high school seniors, high

  17. The radio-MSU network

    International Nuclear Information System (INIS)

    Frese, H.; Berezhnev, S.F.; Avdeyev, D.A.

    1994-01-01

    A combined satellite/microwave network has been set up between three High Energy Physics institutes in the Moscow region and DESY. 2 Mbps microwave links are used for Moscow local loops. The hub is connected to DESY via a 256 Kbps satellite channel

  18. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Science.gov (United States)

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  19. Precision Machining

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    moving away from the empirical work of Taylor (1906) that resulted in a new cutting tool ... conditions that bring about partial ductile mode grinding, a primary process that ... innovative research work performed by my group in Malaysia. It was a ...

  20. Émissions azotées au champ et performances des machines lors de l'épandage de boues issues du traitement des eaux usées

    OpenAIRE

    Pradel, M.; Pacaud, T.; Cariolle, M.

    2011-01-01

    / Ce document est un rapport de synthèse des travaux réalisés dans le cadre du projet Ecodefi sur l'estimation des émissions azotées lors de l'épandage de boues issues du traitement des eaux usées en lien avec les performances technologiques des machines utilisées à cet effet.

  1. Session 2: Machine studies

    International Nuclear Information System (INIS)

    Assmann, R.W.; Papotti, G.

    2012-01-01

    This document summarizes the talks and discussion that took place in the second session of the Chamonix 2012 workshop concerning results from machine studies performed in 2011. The session consisted of the following presentations: -) LHC experience with different bunch spacings by G. Rumolo; -) Observations of beam-beam effects in MDs in 2011 by W. Herr; -) Beam-induced heating/ bunch length/RF and lessons for 2012 by E. Metral; -) Lessons in beam diagnostics by R. Jones; -) Quench margins by M. Sapinski; and -) First demonstration with beam of the Achromatic Telescopic Squeeze (ATS) by S. Fartoukh. (authors)

  2. Electric machines with axial magnetic flux

    Science.gov (United States)

    Nuca, I.; Ambros, T.; Burduniuc, M.; Deaconu, S. I.; Turcanu, A.

    2018-01-01

    The paper contains information on the performance of axial machines compared to cylindrical ones. At the same time, various constructive schemes of synchronous electromechanical converters with permanent magnets and asynchronous with short-circuited rotor are presented. In the developed constructions, the aim is to maximize the usage of the material of the stator windings. The design elements of the axial machine magnetic system are presented. The FEMM application depicted the array of the magnetic field of an axial machine.

  3. vSphere virtual machine management

    CERN Document Server

    Fitzhugh, Rebecca

    2014-01-01

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

  4. 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

  5. Machine Protection System response in 2011

    CERN Document Server

    Zerlauth, M; Wenninger, J

    2012-01-01

    The performance of the machine protection system during the 2011 run is summarized in this paper. Following an analysis of the beam dump causes in comparison to the previous 2010 run, special emphasis will be given to analyse events which risked to exposed parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems as well as in the change management will be evaluated along with their impact on the 2012 run. The role of the restricted Machine Protection Panel ( rMPP ) during the various operational phases such as commissioning, the intensity ramp up and Machine Developments is being discussed.

  6. 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

  7. 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.

  8. 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.

  9. Machine medical ethics

    CERN Document Server

    Pontier, Matthijs

    2015-01-01

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

  10. Molecular machines with bio-inspired mechanisms.

    Science.gov (United States)

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

    2018-02-26

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

  11. Robotic refueling machine

    International Nuclear Information System (INIS)

    Challberg, R.C.; Jones, C.R.

    1996-01-01

    One of the longest critical path operations performed during the outage is removing and replacing the fuel. A design is currently under development for a refueling machine which would allow faster, fully automated operation and would also allow the handling of two fuel assemblies at the same time. This design is different from current designs, (a) because of its lighter weight, making increased acceleration and speed possible, (b) because of its control system which makes locating the fuel assembly more dependable and faster, and (c) because of its dual handling system allowing simultaneous fuel movements. The new design uses two robotic arms to span a designated area of the vessel and the fuel storage area. Attached to the end of each robotic arm is a lightweight telescoping mast with a pendant attached to the end of each mast. The pendant acts as the base unit, allowing attachment of any number of end effectors depending on the servicing or inspection operation. Housed within the pendant are two television cameras used for the positioning control system. The control system is adapted from the robotics field using the technology known as machine vision, which provides both object and character recognition techniques to enable relative position control rather than absolute position control as in past designs. The pendant also contains thrusters that are used for fast, short distance, precise positioning. The new refueling machine system design is capable of a complete off load and reload of an 872 element core in about 5.3 days compared to 13 days for a conventional system

  12. Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

    Science.gov (United States)

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

    2011-01-01

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

  13. Machine protection systems

    CERN Document Server

    Macpherson, A L

    2010-01-01

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

  14. Refueling machine for a nuclear reactor

    International Nuclear Information System (INIS)

    Kowalski, E.F.; Hornak, L.P.; Swidwa, K.J.

    1981-01-01

    An improved refuelling machine for inserting and removing fuel assemblies from a nuclear reactor is described which has been designed to increase the reliability of such machines. The system incorporates features which enable the refuelling operation to be performed more efficiently and economically. (U.K.)

  15. Human factors and man-machine-interaction

    International Nuclear Information System (INIS)

    Bohr-Bruckmayr, E.

    1985-01-01

    Definitions of the man-machine-interface concept are given. The importance of ergonomics in planning, construction, start-up and operation of a nuclear power plant is highlighted. A comprehensive task analysis is the basis of man-machine-interaction. Personnel performance, work shaping and security are discussed

  16. High Temperature Superconductor Machine Prototype

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  17. Linac boosters for electrostatic machines

    International Nuclear Information System (INIS)

    Ben-Zvi, I.; Brookhaven National Lab., Upton, NY

    1990-01-01

    A survey of linacs which are used as boosters to electrostatic accelerators is presented. Machines both operating and under construction, copper and superconducting, are reviewed. The review includes data on the accelerating structures, performance, rf and control, beam optics, budget, vacuum and cryogenics. (orig.)

  18. Dictionary of machine terms

    International Nuclear Information System (INIS)

    1990-06-01

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

  19. Mankind, machines and people

    Energy Technology Data Exchange (ETDEWEB)

    Hugli, A

    1984-01-01

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

  20. 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...

  1. HTS machine laboratory prototype

    DEFF Research Database (Denmark)

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

  2. Your Sewing Machine.

    Science.gov (United States)

    Peacock, Marion E.

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

  3. Human-machine interface upgrade

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  4. 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.

  5. 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.    

  6. INVESTIGATION OF MAGNESIUM ALLOYS MACHINABILITY

    Directory of Open Access Journals (Sweden)

    Berat Barıs BULDUM

    2013-01-01

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

  7. CANDU 9 fuelling machine carriage

    Energy Technology Data Exchange (ETDEWEB)

    Ullrich, D J; Slavik, J F [Atomic Energy of Canada Ltd., Saskatoon, SK (Canada)

    1997-12-31

    Continuous, on-power refuelling is a key feature of all CANDU reactor designs and is essential to maintaining high station capacity factors. The concept of a fuelling machine carriage can be traced to the early CANDU designs, such as the Douglas Point Nuclear Generating Station. In the CANDU 9 480NU unit, the combination of a mobile carriage and a proven fuelling machine head design comprises an effective means of transporting fuel between the reactor and the fuel transfer ports. It is a suitable alternative to the fuelling machine bridge system that has been utilized in the CANDU 6 reactor units. The CANDU 9 480NU fuel handling system successfully combines features that meet the project requirements with respect to fuelling performance, functionality, seismic qualification and the use of proven components. The design incorporates improvements based on experience and applicable current technologies. (author). 4 figs.

  8. CANDU 9 fuelling machine carriage

    International Nuclear Information System (INIS)

    Ullrich, D.J.; Slavik, J.F.

    1996-01-01

    Continuous, on-power refuelling is a key feature of all CANDU reactor designs and is essential to maintaining high station capacity factors. The concept of a fuelling machine carriage can be traced to the early CANDU designs, such as the Douglas Point Nuclear Generating Station. In the CANDU 9 480NU unit, the combination of a mobile carriage and a proven fuelling machine head design comprises an effective means of transporting fuel between the reactor and the fuel transfer ports. It is a suitable alternative to the fuelling machine bridge system that has been utilized in the CANDU 6 reactor units. The CANDU 9 480NU fuel handling system successfully combines features that meet the project requirements with respect to fuelling performance, functionality, seismic qualification and the use of proven components. The design incorporates improvements based on experience and applicable current technologies. (author). 4 figs

  9. Machine and plasma diagnostic instrumentation systems for the Tandem Mirror Experiment Upgrade

    International Nuclear Information System (INIS)

    Coutts, G.W.; Coffield, F.E.; Lang, D.D.; Hornady, R.S.

    1981-01-01

    To evaluate performance of a second generation Tandem Mirror Machine, an extensive instrumentation system is being designed and installed as part of the major device fabrication. The systems listed will be operational during the start-up phase of the TMX Upgrade machine and provide bench marks for future performance data. In addition to plasma diagnostic instrumentation, machine parameter monitoring systems will be installed prior to machine operation. Simultaneous recording of machine parameters will permit evaluation of plasma parameters sensitive to machine conditions

  10. Development of a Committee of Artificial Neural Networks for the Performance Testing of Compressors for Thermal Machines in Very Reduced Times

    Directory of Open Access Journals (Sweden)

    Coral Rodrigo

    2015-03-01

    Full Text Available This paper presents a new test method able to infer - in periods of less than 7 seconds - the refrigeration capacity of a compressor used in thermal machines, which represents a time reduction of approximately 99.95% related to the standardized traditional methods. The method was developed aiming at its application on compressor manufacture lines and on 100% of the units produced. Artificial neural networks (ANNs were used to establish a model able to infer the refrigeration capacity based on the data collected directly on the production line. The proposed method does not make use of refrigeration systems and also does not require using the compressor oil.

  11. 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.

  12. 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

  13. Investigation the gas film in micro scale induced error on the performance of the aerostatic spindle in ultra-precision machining

    Science.gov (United States)

    Chen, Dongju; Huo, Chen; Cui, Xianxian; Pan, Ri; Fan, Jinwei; An, Chenhui

    2018-05-01

    The objective of this work is to study the influence of error induced by gas film in micro-scale on the static and dynamic behavior of a shaft supported by the aerostatic bearings. The static and dynamic balance models of the aerostatic bearing are presented by the calculated stiffness and damping in micro scale. The static simulation shows that the deformation of aerostatic spindle system in micro scale is decreased. For the dynamic behavior, both the stiffness and damping in axial and radial directions are increased in micro scale. The experiments of the stiffness and rotation error of the spindle show that the deflection of the shaft resulting from the calculating parameters in the micro scale is very close to the deviation of the spindle system. The frequency information in transient analysis is similar to the actual test, and they are also higher than the results from the traditional case without considering micro factor. Therefore, it can be concluded that the value considering micro factor is closer to the actual work case of the aerostatic spindle system. These can provide theoretical basis for the design and machining process of machine tools.

  14. Machine assisted histogram classification

    Science.gov (United States)

    Benyó, B.; Gaspar, C.; Somogyi, P.

    2010-04-01

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

  15. Machine assisted histogram classification

    Energy Technology Data Exchange (ETDEWEB)

    Benyo, B; Somogyi, P [BME-IIT, H-1117 Budapest, Magyar tudosok koerutja 2. (Hungary); Gaspar, C, E-mail: Peter.Somogyi@cern.c [CERN-PH, CH-1211 Geneve 23 (Switzerland)

    2010-04-01

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

  16. Dynamic thermal analysis of machines in running state

    CERN Document Server

    Wang, Lihui

    2014-01-01

    With the increasing complexity and dynamism in today’s machine design and development, more precise, robust and practical approaches and systems are needed to support machine design. Existing design methods treat the targeted machine as stationery. Analysis and simulation are mostly performed at the component level. Although there are some computer-aided engineering tools capable of motion analysis and vibration simulation etc., the machine itself is in the dry-run state. For effective machine design, understanding its thermal behaviours is crucial in achieving the desired performance in real situation. Dynamic Thermal Analysis of Machines in Running State presents a set of innovative solutions to dynamic thermal analysis of machines when they are put under actual working conditions. The objective is to better understand the thermal behaviours of a machine in real situation while at the design stage. The book has two major sections, with the first section presenting a broad-based review of the key areas of ...

  17. Surface mining machines problems of maintenance and modernization

    CERN Document Server

    Rusiński, Eugeniusz; Moczko, Przemysław; Pietrusiak, Damian

    2017-01-01

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

  18. Macroscopic transport by synthetic molecular machines

    NARCIS (Netherlands)

    Berna, J; Leigh, DA; Lubomska, M; Mendoza, SM; Perez, EM; Rudolf, P; Teobaldi, G; Zerbetto, F

    Nature uses molecular motors and machines in virtually every significant biological process, but demonstrating that simpler artificial structures operating through the same gross mechanisms can be interfaced with - and perform physical tasks in - the macroscopic world represents a significant hurdle

  19. Design and Development of a tomato Slicing Machine

    OpenAIRE

    Kamaldeen Oladimeji Salaudeen; Awagu E. F.

    2012-01-01

    Principle of slicing was reviewed and tomato slicing machine was developed based on appropriate technology. Locally available materials like wood, stainless steel and mild steel were used in the fabrication. The machine was made to cut tomatoes in 2cm thickness. The capacity of the machine is 540.09g per minute and its performance efficiency is 70%.

  20. Online transfer learning with extreme learning machine

    Science.gov (United States)

    Yin, Haibo; Yang, Yun-an

    2017-05-01

    In this paper, we propose a new transfer learning algorithm for online training. The proposed algorithm, which is called Online Transfer Extreme Learning Machine (OTELM), is based on Online Sequential Extreme Learning Machine (OSELM) while it introduces Semi-Supervised Extreme Learning Machine (SSELM) to transfer knowledge from the source to the target domain. With the manifold regularization, SSELM picks out instances from the source domain that are less relevant to those in the target domain to initialize the online training, so as to improve the classification performance. Experimental results demonstrate that the proposed OTELM can effectively use instances in the source domain to enhance the learning performance.

  1. Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods

    International Nuclear Information System (INIS)

    Yahya, Noorazrul; Ebert, Martin A.; Bulsara, Max; House, Michael J.; Kennedy, Angel; Joseph, David J.; Denham, James W.

    2016-01-01

    Purpose: Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strategies for prediction of urinary symptoms following external beam radiotherapy of the prostate. Methods: The performance of logistic regression, elastic-net, support-vector machine, random forest, neural network, and multivariate adaptive regression splines (MARS) to predict urinary symptoms was analyzed using data from 754 participants accrued by TROG03.04-RADAR. Predictive features included dose-surface data, comorbidities, and medication-intake. Four symptoms were analyzed: dysuria, haematuria, incontinence, and frequency, each with three definitions (grade ≥ 1, grade ≥ 2 and longitudinal) with event rate between 2.3% and 76.1%. Repeated cross-validations producing matched models were implemented. A synthetic minority oversampling technique was utilized in endpoints with rare events. Parameter optimization was performed on the training data. Area under the receiver operating characteristic curve (AUROC) was used to compare performance using sample size to detect differences of ≥0.05 at the 95% confidence level. Results: Logistic regression, elastic-net, random forest, MARS, and support-vector machine were the highest-performing statistical-learning strategies in 3, 3, 3, 2, and 1 endpoints, respectively. Logistic regression, MARS, elastic-net, random forest, neural network, and support-vector machine were the best, or were not significantly worse than the best, in 7, 7, 5, 5, 3, and 1 endpoints. The best-performing statistical model was for dysuria grade ≥ 1 with AUROC ± standard deviation of 0.649 ± 0.074 using MARS. For longitudinal frequency and dysuria grade ≥ 1, all strategies produced AUROC>0.6 while all haematuria endpoints and longitudinal incontinence models produced AUROC<0.6. Conclusions

  2. Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods

    Energy Technology Data Exchange (ETDEWEB)

    Yahya, Noorazrul, E-mail: noorazrul.yahya@research.uwa.edu.au [School of Physics, University of Western Australia, Western Australia 6009, Australia and School of Health Sciences, National University of Malaysia, Bangi 43600 (Malaysia); Ebert, Martin A. [School of Physics, University of Western Australia, Western Australia 6009, Australia and Department of Radiation Oncology, Sir Charles Gairdner Hospital, Western Australia 6008 (Australia); Bulsara, Max [Institute for Health Research, University of Notre Dame, Fremantle, Western Australia 6959 (Australia); House, Michael J. [School of Physics, University of Western Australia, Western Australia 6009 (Australia); Kennedy, Angel [Department of Radiation Oncology, Sir Charles Gairdner Hospital, Western Australia 6008 (Australia); Joseph, David J. [Department of Radiation Oncology, Sir Charles Gairdner Hospital, Western Australia 6008, Australia and School of Surgery, University of Western Australia, Western Australia 6009 (Australia); Denham, James W. [School of Medicine and Public Health, University of Newcastle, New South Wales 2308 (Australia)

    2016-05-15

    Purpose: Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strategies for prediction of urinary symptoms following external beam radiotherapy of the prostate. Methods: The performance of logistic regression, elastic-net, support-vector machine, random forest, neural network, and multivariate adaptive regression splines (MARS) to predict urinary symptoms was analyzed using data from 754 participants accrued by TROG03.04-RADAR. Predictive features included dose-surface data, comorbidities, and medication-intake. Four symptoms were analyzed: dysuria, haematuria, incontinence, and frequency, each with three definitions (grade ≥ 1, grade ≥ 2 and longitudinal) with event rate between 2.3% and 76.1%. Repeated cross-validations producing matched models were implemented. A synthetic minority oversampling technique was utilized in endpoints with rare events. Parameter optimization was performed on the training data. Area under the receiver operating characteristic curve (AUROC) was used to compare performance using sample size to detect differences of ≥0.05 at the 95% confidence level. Results: Logistic regression, elastic-net, random forest, MARS, and support-vector machine were the highest-performing statistical-learning strategies in 3, 3, 3, 2, and 1 endpoints, respectively. Logistic regression, MARS, elastic-net, random forest, neural network, and support-vector machine were the best, or were not significantly worse than the best, in 7, 7, 5, 5, 3, and 1 endpoints. The best-performing statistical model was for dysuria grade ≥ 1 with AUROC ± standard deviation of 0.649 ± 0.074 using MARS. For longitudinal frequency and dysuria grade ≥ 1, all strategies produced AUROC>0.6 while all haematuria endpoints and longitudinal incontinence models produced AUROC<0.6. Conclusions

  3. Implementing Machine Learning in the PCWG Tool

    Energy Technology Data Exchange (ETDEWEB)

    Clifton, Andrew; Ding, Yu; Stuart, Peter

    2016-12-13

    The Power Curve Working Group (www.pcwg.org) is an ad-hoc industry-led group to investigate the performance of wind turbines in real-world conditions. As part of ongoing experience-sharing exercises, machine learning has been proposed as a possible way to predict turbine performance. This presentation provides some background information about machine learning and how it might be implemented in the PCWG exercises.

  4. Using a vision cognitive algorithm to schedule virtual machines

    OpenAIRE

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

    2014-01-01

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

  5. 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, ...

  6. 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.

  7. The Newest Machine Material

    International Nuclear Information System (INIS)

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

    2005-08-01

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

  8. Introduction to machine learning

    OpenAIRE

    Baştanlar, Yalın; Özuysal, Mustafa

    2014-01-01

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

  9. Machinability of advanced materials

    CERN Document Server

    Davim, J Paulo

    2014-01-01

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

  10. 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.

  11. 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

  12. 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

  13. Chaotic Boltzmann machines

    Science.gov (United States)

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

    2013-01-01

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

  14. 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

  15. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  16. 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

  17. 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

  18. Machinability of IPS Empress 2 framework ceramic.

    Science.gov (United States)

    Schmidt, C; Weigl, P

    2000-01-01

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

  19. Are there intelligent Turing machines?

    OpenAIRE

    Bátfai, Norbert

    2015-01-01

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

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

    International Nuclear Information System (INIS)

    Leuch, M

    2011-01-01

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

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

    Science.gov (United States)

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

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

  2. Lessons from 2011 - Machine protection

    International Nuclear Information System (INIS)

    Zerlauth, M.; Schmidt, R.; Wenninger, J.

    2012-01-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. The LHC Machine Protection and Equipment Systems have been working extremely well during the 2011 run. Ever more failures are captured before effects on the particle beams are seen (i.e. no beam losses or orbit changes are observed). An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

  3. Variable geometry Darrieus wind machine

    Science.gov (United States)

    Pytlinski, J. T.; Serrano, D.

    1983-08-01

    A variable geometry Darrieus wind machine is proposed. The lower attachment of the blades to the rotor can move freely up and down the axle allowing the blades of change shape during rotation. Experimental data for a 17 m. diameter Darrieus rotor and a theoretical model for multiple streamtube performance prediction were used to develop a computer simulation program for studying parameters that affect the machine's performance. This new variable geometry concept is described and interrelated with multiple streamtube theory through aerodynamic parameters. The computer simulation study shows that governor behavior of a Darrieus turbine can not be attained by a standard turbine operating within normally occurring rotational velocity limits. A second generation variable geometry Darrieus wind turbine which uses a telescopic blade is proposed as a potential improvement on the studied concept.

  4. Comparative Performance Analysis of Support Vector Machine, Random Forest, Logistic Regression and k-Nearest Neighbours in Rainbow Trout (Oncorhynchus Mykiss) Classification Using Image-Based Features.

    Science.gov (United States)

    Saberioon, Mohammadmehdi; Císař, Petr; Labbé, Laurent; Souček, Pavel; Pelissier, Pablo; Kerneis, Thierry

    2018-03-29

    The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based features. In total, one-hundred and sixty rainbow trout ( Oncorhynchus mykiss ) were fed either a fish-meal based diet (80 fish) or a 100% plant-based diet (80 fish) and photographed using consumer-grade digital camera. Twenty-three colour features and four texture features were extracted. Four different classification methods were used to evaluate fish diets including Random forest (RF), Support vector machine (SVM), Logistic regression (LR) and k -Nearest neighbours ( k -NN). The SVM with radial based kernel provided the best classifier with correct classification rate (CCR) of 82% and Kappa coefficient of 0.65. Although the both LR and RF methods were less accurate than SVM, they achieved good classification with CCR 75% and 70% respectively. The k -NN was the least accurate (40%) classification model. Overall, it can be concluded that consumer-grade digital cameras could be employed as the fast, accurate and non-invasive sensor for classifying rainbow trout based on their diets. Furthermore, these was a close association between image-based features and fish diet received during cultivation. These procedures can be used as non-invasive, accurate and precise approaches for monitoring fish status during the cultivation by evaluating diet's effects on fish skin.

  5. Comparative Performance Analysis of Support Vector Machine, Random Forest, Logistic Regression and k-Nearest Neighbours in Rainbow Trout (Oncorhynchus Mykiss Classification Using Image-Based Features

    Directory of Open Access Journals (Sweden)

    Mohammadmehdi Saberioon

    2018-03-01

    Full Text Available The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based features. In total, one-hundred and sixty rainbow trout (Oncorhynchus mykiss were fed either a fish-meal based diet (80 fish or a 100% plant-based diet (80 fish and photographed using consumer-grade digital camera. Twenty-three colour features and four texture features were extracted. Four different classification methods were used to evaluate fish diets including Random forest (RF, Support vector machine (SVM, Logistic regression (LR and k-Nearest neighbours (k-NN. The SVM with radial based kernel provided the best classifier with correct classification rate (CCR of 82% and Kappa coefficient of 0.65. Although the both LR and RF methods were less accurate than SVM, they achieved good classification with CCR 75% and 70% respectively. The k-NN was the least accurate (40% classification model. Overall, it can be concluded that consumer-grade digital cameras could be employed as the fast, accurate and non-invasive sensor for classifying rainbow trout based on their diets. Furthermore, these was a close association between image-based features and fish diet received during cultivation. These procedures can be used as non-invasive, accurate and precise approaches for monitoring fish status during the cultivation by evaluating diet’s effects on fish skin.

  6. Conveyor belt nuclear weighing machine

    International Nuclear Information System (INIS)

    Anon.

    1977-01-01

    In many industries the flow of materials on conveyor belts must be measured and controlled. Electromechanical weighing devices have high accuracy but are complicated and expensive to install and maintain. For many applications the nuclear weighing machine has sufficient accuracy but is considerably simpler, cheaper and more robust and is easier to maintain. The rating and performance of a gamma ray balance on the mar ket are detailed. (P.G.R.)

  7. Galaxy Classification using Machine Learning

    Science.gov (United States)

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

    2017-01-01

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

  8. Microsoft Azure machine learning

    CERN Document Server

    Mund, Sumit

    2015-01-01

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

  9. The Hooey Machine.

    Science.gov (United States)

    Scarnati, James T.; Tice, Craig J.

    1992-01-01

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

  10. A nucleonic weighing machine

    International Nuclear Information System (INIS)

    Anon.

    1978-01-01

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

  11. An asymptotical machine

    Science.gov (United States)

    Cristallini, Achille

    2016-07-01

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

  12. 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.

  13. The deleuzian abstract machines

    DEFF Research Database (Denmark)

    Werner Petersen, Erik

    2005-01-01

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

  14. 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…

  15. Precision machining commercialization

    International Nuclear Information System (INIS)

    1978-01-01

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

  16. High speed operation of permanent magnet machines

    Science.gov (United States)

    El-Refaie, Ayman M.

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

  17. Transition Towards Energy Efficient Machine Tools

    CERN Document Server

    Zein, André

    2012-01-01

    Energy efficiency represents a cost-effective and immediate strategy of a sustainable development. Due to substantial environmental and economic implications, a strong emphasis is put on the electrical energy requirements of machine tools for metalworking processes. The improvement of energy efficiency is however confronted with diverse barriers, which sustain an energy efficiency gap of unexploited potential. The deficiencies lie in the lack of information about the actual energy requirements of machine tools, a minimum energy reference to quantify improvement potential and the possible actions to improve the energy demand. Therefore, a comprehensive concept for energy performance management of machine tools is developed which guides the transition towards energy efficient machine tools. It is structured in four innovative concept modules, which are embedded into step-by-step workflow models. The capability of the performance management concept is demonstrated in an automotive manufacturing environment. The ...

  18. Collaborative Systems – Finite State Machines

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2011-01-01

    Full Text Available In this paper the finite state machines are defined and formalized. There are presented the collaborative banking systems and their correspondence is done with finite state machines. It highlights the role of finite state machines in the complexity analysis and performs operations on very large virtual databases as finite state machines. It builds the state diagram and presents the commands and documents transition between the collaborative systems states. The paper analyzes the data sets from Collaborative Multicash Servicedesk application and performs a combined analysis in order to determine certain statistics. Indicators are obtained, such as the number of requests by category and the load degree of an agent in the collaborative system.

  19. A double-sided linear primary permanent magnet vernier machine.

    Science.gov (United States)

    Du, Yi; Zou, Chunhua; Liu, Xianxing

    2015-01-01

    The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.

  20. INFLUENCE OF STRUCTURE COMPONENTS ON MACHINE TOOL ACCURACY

    Directory of Open Access Journals (Sweden)

    ConstantinSANDU

    2017-11-01

    Full Text Available For machine tools, the accuracy of the parts of the machine tool structure (after roughing should be subject to relief and natural or artificial aging. The performance of the current accuracy of machine tools as linearity or flatness was higher than 5 μm/m. Under this value there are great difficulties. The performance of the structure of the machine tools in the manufacture of structural parts of machine tools, with a flatness accuracy that the linearity of about 2 μm/m, are significant deviations form of their half-finished. This article deals with the influence of errors of form of semifinished and machined parts on them, on their shape and especially what happens to structure machine tools when the components of the structure were assembling this.

  1. Quiescent plasma machine for plasma investigation

    International Nuclear Information System (INIS)

    Ferreira, J.L.

    1993-01-01

    A large volume quiescent plasma device is being developed at INPE to study Langmuir waves and turbulence generated by electron beams (E b ≤ 500 e V) interacting with plasma. This new quiescent plasma machine was designed to allow the performance of several experiments specially those related with laboratory space plasma simulation experiments. Current-driven instabilities and related phenomena such as double-layers along magnetic field lines are some of the many experiments planned for this machine. (author)

  2. 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 ...

  3. Scikit-learn: Machine Learning in Python

    OpenAIRE

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

    2012-01-01

    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 and commercial settings....

  4. Density Based Support Vector Machines for Classification

    OpenAIRE

    Zahra Nazari; Dongshik Kang

    2015-01-01

    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 cl...

  5. Methods and systems for micro machines

    Energy Technology Data Exchange (ETDEWEB)

    Stalford, Harold L.

    2018-03-06

    A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

  6. Ergonomics for enhancing detection of machine abnormalities.

    Science.gov (United States)

    Illankoon, Prasanna; Abeysekera, John; Singh, Sarbjeet

    2016-10-17

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

  7. Fundamentals of machine design

    CERN Document Server

    Karaszewski, Waldemar

    2011-01-01

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

  8. Machine 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

  9. Creativity in Machine Learning

    OpenAIRE

    Thoma, Martin

    2016-01-01

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

  10. 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.

  11. Transition towards energy efficient machine tools

    Energy Technology Data Exchange (ETDEWEB)

    Zein, Andre [Technische Univ. Braunschweig (Germany). Inst. fuer Werkzeugmaschinen und Fertigungstechnik

    2012-07-01

    Provides unique data about industrial trends affecting the energy demand of machine tools. Presents a comprehensive methodology to assess the energy efficiency of machining processes. Contains an integrated management concept to implement energy performance measures into existing industrial systems. Includes an industrial case study with two exemplary applications. Energy efficiency represents a cost-effective and immediate strategy of a sustainable development. Due to substantial environmental and economic implications, a strong emphasis is put on the electrical energy requirements of machine tools for metalworking processes. The improvement of energy efficiency is however confronted with diverse barriers, which sustain an energy efficiency gap of unexploited potential. The deficiencies lie in the lack of information about the actual energy requirements of machine tools, a minimum energy reference to quantify improvement potential and the possible actions to improve the energy demand. Therefore, a comprehensive concept for energy performance management of machine tools is developed which guides the transition towards energy efficient machine tools. It is structured in four innovative concept modules, which are embedded into step-by-step workflow models. The capability of the performance management concept is demonstrated in an automotive manufacturing environment. The target audience primarily comprises researchers and practitioners challenged to enhance energy efficiency in manufacturing. The book may also be beneficial for graduate students who want to specialize in this field.

  12. Size reduction machine

    International Nuclear Information System (INIS)

    Fricke, V.

    1999-01-01

    The Size Reduction Machine (SRM) is a mobile platform capable of shearing various shapes and types of metal components at a variety of elevations. This shearing activity can be performed without direct physical movement and placement of the shear head by the operator. The base unit is manually moved and roughly aligned to each cut location. The base contains the electronics: hydraulic pumps, servos, and actuators needed to move the shear-positioning arm. The movable arm allows the shear head to have six axes of movement and to cut to within 4 inches of a wall surface. The unit has a slick electrostatic capture coating to assist in external decontamination. Internal contamination of the unit is controlled by a high-efficiency particulate air (HEPA) filter on the cooling inlet fan. The unit is compact enough to access areas through a 36-inch standard door opening. This paper is an Innovative Technology Summary Report designed to provide potential users with the information they need to quickly determine if a technology would apply to a particular environmental management problem. They also are designed for readers who may recommend that a technology be considered by prospective users

  13. Metal release from coffee machines and electric kettles.

    Science.gov (United States)

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

    2015-01-01

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

  14. Desempenho de uma semeadora-adubadora no estabelecimento e na produtividade da cultura do milho sob plantio direto Performance of a sowing-fertilizer machine for corn crop establishment and grain yield under no-tillage system

    Directory of Open Access Journals (Sweden)

    José Geraldo da Silva

    2000-03-01

    machine displacement velocity and no significant damage to corn seeds passing through the horizontal disk device was observed, even at the higher speeds. Seed spacing in the sowing line was considered excellent, regular or unsatisfactory when the machine operated at 3 km/h, 6-9 km/h and 11.2 km/h, respectively. Displacement velocities up to 6 km/h and deeper soil fertilization, performed at 10 cm depth, provided increased plant and ear stands as well as the highest corn yields.

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

  16. 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...

  17. Enter the machine

    Science.gov (United States)

    Palittapongarnpim, Pantita; Sanders, Barry C.

    2018-05-01

    Quantum tomography infers quantum states from measurement data, but it becomes infeasible for large systems. Machine learning enables tomography of highly entangled many-body states and suggests a new powerful approach to this problem.

  18. Introduction to AC machine design

    CERN Document Server

    Lipo, Thomas A

    2018-01-01

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

  19. Metalworking and machining fluids

    Science.gov (United States)

    Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

    2010-10-12

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

  20. Superconducting machines. Chapter 4

    International Nuclear Information System (INIS)

    Appleton, A.D.

    1977-01-01

    A brief account is given of the principles of superconductivity and superconductors. The properties of Nb-Ti superconductors and the method of flux stabilization are described. The basic features of superconducting d.c. machines are illustrated by the use of these machines for ship propulsion, steel-mill drives, industrial drives, aluminium production, and other d.c. power supplies. Superconducting a.c. generators and their design parameters are discussed. (U.K.)

  1. Quantum Machine Learning

    OpenAIRE

    Romero García, Cristian

    2017-01-01

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

  2. Human-machine interactions

    Science.gov (United States)

    Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

    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.

  3. Some relations between quantum Turing machines and Turing machines

    OpenAIRE

    Sicard, Andrés; Vélez, Mario

    1999-01-01

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

  4. Reactor refueling machine simulator

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  5. Dynamics and Thermodynamics of Molecular Machines

    DEFF Research Database (Denmark)

    Golubeva, Natalia

    2014-01-01

    to their microscopic size, molecular motors are governed by principles fundamentally different from those describing the operation of man-made motors such as car engines. In this dissertation the dynamic and thermodynamic properties of molecular machines are studied using the tools of nonequilibrium statistical......Molecular machines, or molecular motors, are small biophysical devices that perform a variety of essential metabolic processes such as DNA replication, protein synthesis and intracellular transport. Typically, these machines operate by converting chemical energy into motion and mechanical work. Due...... mechanics. The first part focuses on noninteracting molecular machines described by a paradigmatic continuum model with the aim of comparing and contrasting such a description to the one offered by the widely used discrete models. Many molecular motors, for example, kinesin involved in cellular cargo...

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

    Science.gov (United States)

    Iwasaki, N

    2001-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Anyuan

    2011-01-15

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

  8. Characterisation of Dynamic Mechanical Properties of Resistance Welding Machines

    DEFF Research Database (Denmark)

    Wu, Pei; Zhang, Wenqi; Bay, Niels

    2005-01-01

    characterizing the dynamic mechanical characteristics of resistance welding machines is suggested, and a test set-up is designed determining the basic, independent machine parameters required in the model. The model is verified by performing a series of mechanical tests as well as real projection welds.......The dynamic mechanical properties of a resistance welding machine have significant influence on weld quality, which must be considered when simulating the welding process numerically. However, due to the complexity of the machine structure and the mutual coupling of components of the machine system......, it is very difficult to measure or calculate the basic, independent machine parameters required in a mathematical model of the machine dynamics, and no test method has so far been presented in literature, which can be applied directly in an industrial environment. In this paper, a mathematical model...

  9. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

    Science.gov (United States)

    Haenssle, H A; Fink, C; Schneiderbauer, R; Toberer, F; Buhl, T; Blum, A; Kalloo, A; Hassen, A Ben Hadj; Thomas, L; Enk, A; Uhlmann, L

    2018-05-28

    Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking. Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge. In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P = 0.19) and specificity to 75.7% (±11.7%, P < 0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P < 0.01) and level-II (75.7%, P < 0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P < 0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge. For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists

  10. Nano Mechanical Machining Using AFM Probe

    Science.gov (United States)

    Mostofa, Md. Golam

    and burr formations through intermittent cutting. Combining the AFM probe based machining with vibration-assisted machining enhanced nano mechanical machining processes by improving the accuracy, productivity and surface finishes. In this study, several scratching tests are performed with a single crystal diamond AFM probe to investigate the cutting characteristics and model the ploughing cutting forces. Calibration of the probe for lateral force measurements, which is essential, is also extended through the force balance method. Furthermore, vibration-assisted machining system is developed and applied to fabricate different materials to overcome some of the limitations of the AFM probe based single point nano mechanical machining. The novelty of this study includes the application of vibration-assisted AFM probe based nano scale machining to fabricate micro/nano scale features, calibration of an AFM by considering different factors, and the investigation of the nano scale material removal process from a different perspective.

  11. Maintenance strategies to reduce downtime due to machine positional errors

    OpenAIRE

    Shagluf, Abubaker; Longstaff, A.P.; Fletcher, S.

    2014-01-01

    Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014 Manufacturing strives to reduce waste and increase Overall Equipment Effectiveness (OEE). When managing machine tool maintenance a manufacturer must apply an appropriate decision technique in order to reveal hidden costs associated with production losses, reduce equipment downtime competentely and similiarly identify the machines performance. Total productive maintenance (TPM) is a maintenance progr...

  12. Optimization of the Development of a Plastic Recycling Machine ...

    African Journals Online (AJOL)

    Nigerian Journal of Technology ... The performance test analysis carried out defines the characteristics of the machine and shows that at a speed of 268 rpm the machine functions effectively and efficiently in performing its task producing a high finishing recycling efficiency or recyclability of 97%, takes 2 minutes to recycle a ...

  13. Trunnion Collar Removal Machine - Gap Analysis Table

    International Nuclear Information System (INIS)

    Johnson, M.

    2005-01-01

    The purpose of this document is to review the existing the trunnion collar removal machine against the ''Nuclear Safety Design Bases for License Application'' (NSDB) [Ref. 10] requirements and to identify codes and standards and supplemental requirements to meet these requirements. If these codes and standards can not fully meet these requirements then a ''gap'' is identified. These gaps will be identified here and addressed using the ''Trunnion Collar Removal Machine Design Development Plan'' [Ref. 15]. The codes and standards, supplemental requirements, and design development requirements for the trunnion collar removal machine are provided in the gap analysis table (Appendix A, Table 1). Because the trunnion collar removal machine is credited with performing functions important to safety (ITS) in the NSDB [Ref. 10], design basis requirements are applicable to ensure equipment is available and performs required safety functions when needed. The gap analysis table is used to identify design objectives and provide a means to satisfy safety requirements. To ensure that the trunnion collar removal machine performs required safety functions and meets performance criteria, this portion of the gap analysis tables supplies codes and standards sections and the supplemental requirements and identifies design development requirements, if needed

  14. 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...

  15. Hydraulic Power Plant Machine Dynamic Diagnosis

    Directory of Open Access Journals (Sweden)

    Hans Günther Poll

    2006-01-01

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

  16. 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.

  17. Development of cutting machine for disposal of highly activated equipments

    International Nuclear Information System (INIS)

    Iimura, Katumichi; Kitajima, Toshio; Hosokawa, Jinsaku; Abe, Shinichi; Takahashi, Kiyoshi; Ogawa, Mituhiro; Iwai, Takashi

    1994-01-01

    JMTR (Japan Materials Testing Reactor) Project has developed a cutting machine which can cut a highly activated in-pile tube under water and its performance and safety have been confirmed. This machine is for the purpose of cutting a multiplet structure pipe and made possible to cut it under water by adopting under-water discharge method. Furthermore, contamination of canal water and atmosphere is prevented by combining a filter with this machine. This report describes the outline and performance of the developed cutting machine and also results of cutting highly activated in-pile tubes. (author)

  18. The Bearingless Electrical Machine

    Science.gov (United States)

    Bichsel, J.

    1992-01-01

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

  19. Asymmetric quantum cloning machines

    International Nuclear Information System (INIS)

    Cerf, N.J.

    1998-01-01

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

  20. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms

    Science.gov (United States)

    Schädler, Marc R.; Warzybok, Anna; Kollmeier, Birger

    2018-01-01

    The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than −20 dB could not be predicted. PMID:29692200

  1. Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

    Science.gov (United States)

    Schädler, Marc R; Warzybok, Anna; Kollmeier, Birger

    2018-01-01

    The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than -20 dB could not be predicted.

  2. A Semi-Automated Machine Learning Algorithm for Tree Cover Delineation from 1-m Naip Imagery Using a High Performance Computing Architecture

    Science.gov (United States)

    Basu, S.; Ganguly, S.; Nemani, R. R.; Mukhopadhyay, S.; Milesi, C.; Votava, P.; Michaelis, A.; Zhang, G.; Cook, B. D.; Saatchi, S. S.; Boyda, E.

    2014-12-01

    Accurate tree cover delineation is a useful instrument in the derivation of Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) satellite imagery data. Numerous algorithms have been designed to perform tree cover delineation in high to coarse resolution satellite imagery, but most of them do not scale to terabytes of data, typical in these VHR datasets. In this paper, we present an automated probabilistic framework for the segmentation and classification of 1-m VHR data as obtained from the National Agriculture Imagery Program (NAIP) for deriving tree cover estimates for the whole of Continental United States, using a High Performance Computing Architecture. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field (CRF), which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by incorporating expert knowledge through the relabeling of misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the state of California, which covers a total of 11,095 NAIP tiles and spans a total geographical area of 163,696 sq. miles. Our framework produced correct detection rates of around 85% for fragmented forests and 70% for urban tree cover areas, with false positive rates lower than 3% for both regions. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR high-resolution canopy height model shows the effectiveness of our algorithm in generating accurate high-resolution tree cover maps.

  3. A novel improved fuzzy support vector machine based stock price trend forecast model

    OpenAIRE

    Wang, Shuheng; Li, Guohao; Bao, Yifan

    2018-01-01

    Application of fuzzy support vector machine in stock price forecast. Support vector machine is a new type of machine learning method proposed in 1990s. It can deal with classification and regression problems very successfully. Due to the excellent learning performance of support vector machine, the technology has become a hot research topic in the field of machine learning, and it has been successfully applied in many fields. However, as a new technology, there are many limitations to support...

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

    Science.gov (United States)

    Hsiao, Ming-Chih; Su, Ling-Huey

    2018-02-01

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

  5. Plug into 'the modernizing machine'!

    DEFF Research Database (Denmark)

    Krejsler, John B.

    2013-01-01

    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...... before and after this law are productions of those struggles that change what it means to work as an academic subject at a university. This is staged through a host of new social technologies such as development contracts, appraisal interviews, individual performance reviews and so forth. Individual...

  6. DESIGN ANALYSIS OF ELECTRICAL MACHINES THROUGH INTEGRATED NUMERICAL APPROACH

    Directory of Open Access Journals (Sweden)

    ARAVIND C.V.

    2016-02-01

    Full Text Available An integrated design platform for the newer type of machines is presented in this work. The machine parameters are evaluated out using developed modelling tool. With the machine parameters, the machine is modelled using computer aided tool. The designed machine is brought to simulation tool to perform electromagnetic and electromechanical analysis. In the simulation, conditions setting are performed to setup the materials, meshes, rotational speed and the excitation circuit. Electromagnetic analysis is carried out to predict the behavior of the machine based on the movement of flux in the machines. Besides, electromechanical analysis is carried out to analyse the speed-torque characteristic, the current-torque characteristic and the phase angle-torque characteristic. After all the results are analysed, the designed machine is used to generate S block function that is compatible with MATLAB/SIMULINK tool for the dynamic operational characteristics. This allows the integration of existing drive system into the new machines designed in the modelling tool. An example of the machine design is presented to validate the usage of such a tool.

  7. A Method for Design of Modular Reconfigurable Machine Tools

    Directory of Open Access Journals (Sweden)

    Zhengyi Xu

    2017-02-01

    Full Text Available Presented in this paper is a method for the design of modular reconfigurable machine tools (MRMTs. An MRMT is capable of using a minimal number of modules through reconfiguration to perform the required machining tasks for a family of parts. The proposed method consists of three steps: module identification, module determination, and layout synthesis. In the first step, the module components are collected from a family of general-purpose machines to establish a module library. In the second step, for a given family of parts to be machined, a set of needed modules are selected from the module library to construct a desired reconfigurable machine tool. In the third step, a final machine layout is decided though evaluation by considering a number of performance indices. Based on this method, a software package has been developed that can design an MRMT for a given part family.

  8. Human-Machine Communication

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  9. 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.

  10. Machine Learning for Security

    CERN Multimedia

    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 ...

  11. 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.

  12. Magnetic field-assisted electrochemical discharge machining

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  13. Machine Learning Techniques in Clinical Vision Sciences.

    Science.gov (United States)

    Caixinha, Miguel; Nunes, Sandrina

    2017-01-01

    This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

  14. 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.

  15. Machine tool evaluation

    International Nuclear Information System (INIS)

    Lunsford, B.E.

    1976-01-01

    Continued improvement in numerical control (NC) units and the mechanical components used in the construction of today's machine tools, necessitate the use of more precise instrumentation to calibrate and determine the capabilities of these systems. It is now necessary to calibrate most tape-control lathes to a tool-path positioning accuracy of +-300 microinches in the full slide travel and, on some special turning and boring machines, a capability of +-100 microinches must be achieved. The use of a laser interferometer to determine tool-path capabilities is described

  16. 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

  17. 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

  18. 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

  19. Neutron irradiation therapy machine

    International Nuclear Information System (INIS)

    1980-01-01

    Conventional neutron irradiation therapy machines, based on the use of cyclotrons for producing neutron beams, use a superconducting magnet for the cyclotron's magnetic field. This necessitates complex liquid He equipment and presents problems in general hospital use. If conventional magnets are used, the weight of the magnet poles considerably complicates the design of the rotating gantry. Such a therapy machine, gantry and target facilities are described in detail. The use of protons and deuterons to produce the neutron beams is compared and contrasted. (U.K.)

  20. 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.