WorldWideScience

Sample records for machine building automatic

  1. A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    H. Y. Gu

    2017-09-01

    Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  2. Automatic welding machine for piping

    International Nuclear Information System (INIS)

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

    1978-01-01

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

  3. Automatic Evaluation of Machine Translation

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  4. Improvement of automatic fish feeder machine design

    Science.gov (United States)

    Chui Wei, How; Salleh, S. M.; Ezree, Abdullah Mohd; Zaman, I.; Hatta, M. H.; Zain, B. A. Md; Mahzan, S.; Rahman, M. N. A.; Mahmud, W. A. W.

    2017-10-01

    Nation Plan of action for management of fishing is target to achieve an efficient, equitable and transparent management of fishing capacity in marine capture fisheries by 2018. However, several factors influence the fishery production and efficiency of marine system such as automatic fish feeder machine could be taken in consideration. Two latest fish feeder machines have been chosen as the reference for this study. Based on the observation, it has found that the both machine was made with heavy structure, low water and temperature resistance materials. This research’s objective is to develop the automatic feeder machine to increase the efficiency of fish feeding. The experiment has conducted to testing the new design of machine. The new machine with maximum storage of 5 kg and functioning with two DC motors. This machine able to distribute 500 grams of pellets within 90 seconds and longest distance of 4.7 meter. The higher speed could reduce time needed and increase the distance as well. The minimum speed range for both motor is 110 and 120 with same full speed range of 255.

  5. Support vector machine for automatic pain recognition

    Science.gov (United States)

    Monwar, Md Maruf; Rezaei, Siamak

    2009-02-01

    Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

  6. Fully automatic CNC machining production system

    Directory of Open Access Journals (Sweden)

    Lee Jeng-Dao

    2017-01-01

    Full Text Available Customized manufacturing is increasing years by years. The consumption habits change has been cause the shorter of product life cycle. Therefore, many countries view industry 4.0 as a target to achieve more efficient and more flexible automated production. To develop an automatic loading and unloading CNC machining system via vision inspection is the first step in industrial upgrading. CNC controller is adopted as the main controller to command to the robot, conveyor, and other equipment in this study. Moreover, machine vision systems are used to detect position of material on the conveyor and the edge of the machining material. In addition, Open CNC and SCADA software will be utilized to make real-time monitor, remote system of control, alarm email notification, and parameters collection. Furthermore, RFID has been added to employee classification and management. The machine handshaking has been successfully proposed to achieve automatic vision detect, edge tracing measurement, machining and system parameters collection for data analysis to accomplish industrial automation system integration with real-time monitor.

  7. Build your own time machine

    CERN Document Server

    Clegg, Brian

    2012-01-01

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

  8. Gram staining with an automatic machine.

    Science.gov (United States)

    Felek, S; Arslan, A

    1999-01-01

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

  9. Automatic Anthropometric System Development Using Machine Learning

    Directory of Open Access Journals (Sweden)

    Long The Nguyen

    2016-08-01

    Full Text Available The contactless automatic anthropometric system is proposed for the reconstruction of the 3D-model of the human body using the conventional smartphone. Our approach involves three main steps. The first step is the extraction of 12 anthropological features. Then we determine the most important features. Finally, we employ these features to build the 3D model of the human body and classify them according to gender and the commonly used sizes. 

  10. A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)

    Science.gov (United States)

    Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon

    1990-01-01

    Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

  11. FRICTION - WELDING MACHINE AUTOMATIC CONTROL CIRCUIT DESIGN AND APPLICATION

    OpenAIRE

    Hakan ATEŞ; Ramazan BAYINDIR

    2003-01-01

    In this work, automatic controllability of a laboratory-sized friction-welding machine has been investigated. The laboratory-sized friction-welding machine was composed of motor, brake, rotary and constant samples late pliers, and hydraulic unit. In automatic method, welding parameters such as friction time, friction pressure, forge time and forge pressure can be applied sensitively using time relays and contactors. At the end of the experimental study it's observed that automatic control sys...

  12. Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

    Directory of Open Access Journals (Sweden)

    Peng Song

    2012-01-01

    Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

  13. Restrictions of process machine retooling at machine-building enterprises

    OpenAIRE

    Kuznetsova Elena; Tipner Ludmila; Ershov Alexey

    2017-01-01

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

  14. Design of Control System for Kiwifruit Automatic Grading Machine

    Directory of Open Access Journals (Sweden)

    Xingjian Zuo

    2013-05-01

    Full Text Available The kiwifruit automatic grading machine is an important machine for postharvest processing of kiwifruit, and the control system ensures that the machine realizes intelligence. The control system for the kiwifruit automatic grading machine designed in this paper comprises a host computer and a slave microcontroller. The host computer provides a visual grading interface for the machine with a LabVIEW software, the slave microcontroller adopts an STC89C52 microcontroller as its core, and C language is used to write programs for controlling a position sensor module, push-pull type electromagnets, motor driving modules and a power supply for controlling the operation of the machine as well as the rise or descend of grading baffle plates. The ideal control effect is obtained through test, and the intelligent operation of the machine is realized.

  15. Control System Design for Automatic Cavity Tuning Machines

    Energy Technology Data Exchange (ETDEWEB)

    Carcagno, R.; Khabiboulline, T.; Kotelnikov, S.; Makulski, A.; Nehring, R.; Nogiec, J.; Ross, M.; Schappert, W.; /Fermilab; Goessel, A.; Iversen, J.; Klinke, D.; /DESY

    2009-05-01

    A series of four automatic tuning machines for 9-cell TESLA-type cavities are being developed and fabricated in a collaborative effort among DESY, FNAL, and KEK. These machines are intended to support high-throughput cavity fabrication for construction of large SRF-based accelerator projects. Two of these machines will be delivered to cavity vendors for the tuning of XFEL cavities. The control system for these machines must support a high level of automation adequate for industrial use by non-experts operators. This paper describes the control system hardware and software design for these machines.

  16. Control System Design for Automatic Cavity Tuning Machines

    International Nuclear Information System (INIS)

    Carcagno, R.; Khabiboulline, T.; Kotelnikov, S.; Makulski, A.; Nehring, R.; Nogiec, J.; Ross, M.; Schappert, W.; Goessel, A.; Iversen, J.; Klinke, D.

    2009-01-01

    A series of four automatic tuning machines for 9-cell TESLA-type cavities are being developed and fabricated in a collaborative effort among DESY, FNAL, and KEK. These machines are intended to support high-throughput cavity fabrication for construction of large SRF-based accelerator projects. Two of these machines will be delivered to cavity vendors for the tuning of XFEL cavities. The control system for these machines must support a high level of automation adequate for industrial use by non-experts operators. This paper describes the control system hardware and software design for these machines.

  17. FRICTION - WELDING MACHINE AUTOMATIC CONTROL CIRCUIT DESIGN AND APPLICATION

    Directory of Open Access Journals (Sweden)

    Hakan ATEŞ

    2003-02-01

    Full Text Available In this work, automatic controllability of a laboratory-sized friction-welding machine has been investigated. The laboratory-sized friction-welding machine was composed of motor, brake, rotary and constant samples late pliers, and hydraulic unit. In automatic method, welding parameters such as friction time, friction pressure, forge time and forge pressure can be applied sensitively using time relays and contactors. At the end of the experimental study it's observed that automatic control system has been worked successfully.

  18. A consideration of the operation of automatic production machines.

    Science.gov (United States)

    Hoshi, Toshiro; Sugimoto, Noboru

    2015-01-01

    At worksites, various automatic production machines are in use to release workers from muscular labor or labor in the detrimental environment. On the other hand, a large number of industrial accidents have been caused by automatic production machines. In view of this, this paper considers the operation of automatic production machines from the viewpoint of accident prevention, and points out two types of machine operation - operation for which quick performance is required (operation that is not permitted to be delayed) - and operation for which composed performance is required (operation that is not permitted to be performed in haste). These operations are distinguished by operation buttons of suitable colors and shapes. This paper shows that these characteristics are evaluated as "asymmetric on the time-axis". Here, in order for workers to accept the risk of automatic production machines, it is preconditioned in general that harm should be sufficiently small or avoidance of harm is easy. In this connection, this paper shows the possibility of facilitating the acceptance of the risk of automatic production machines by enhancing the asymmetric on the time-axis.

  19. Restrictions of process machine retooling at machine-building enterprises

    Directory of Open Access Journals (Sweden)

    Kuznetsova Elena

    2017-01-01

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

  20. An obstacle to building a time machine

    International Nuclear Information System (INIS)

    Carroll, S.M.; Farhi, E.; Guth, A.H.

    1992-01-01

    Gott has shown that a spacetime with two infinite parallel cosmic strings passing each other with sufficient velocity contains closed timelike curves. We discuss an attempt to build such a time machine. Using the energy-momentum conservation laws in the equivalent (2+1)-dimensional theory, we explicitly construct the spacetime representing the decay of one gravitating particle into two. We find that there is never enough mass in an open universe to build the time machine from the products of decays of stationary particles. More generally, the Gott time machine cannot exist in any open (2+1)-dimensional universe for which the total momentum is timelike

  1. Automatic turbot fish cutting using machine vision

    OpenAIRE

    Martín Rodríguez, Fernando; Barral Martínez, Mónica

    2015-01-01

    This paper is about the design of an automated machine to cut turbot fish specimens. Machine vision is a key part of this project as it is used to compute a cutting curve for specimen’s head. This task is impossible to be carried out by mechanical means. Machine vision is used to detect head boundary and a robot is used to cut the head. Afterwards mechanical systems are used to slice fish to get an easy presentation for end consumer (as fish fillets than can be easily marketed ...

  2. Building machine learning systems with Python

    CERN Document Server

    Richert, Willi

    2013-01-01

    This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro

  3. COMPONENTS PROVISION MANAGEMENT FOR MACHINE BUILDING MANUFACTURER

    Directory of Open Access Journals (Sweden)

    Ekaterina P. Bochkareva

    2014-01-01

    Full Text Available In the paper is given an approach to themanagement of components provision formachine building manufacturer based uponinternational standards and best practicesof leading international companies. Thecomplex expertise methods are used forthe development of the proposed machinebuilding manufacturer suppliers’ operational management method. At a strategic level is proposed a tool for planning the suppliers’portfolio and a machine building manufacturer supplier development methodology.

  4. Design of electric control system for automatic vegetable bundling machine

    Science.gov (United States)

    Bao, Yan

    2017-06-01

    A design can meet the requirements of automatic bale food structure and has the advantages of simple circuit, and the volume is easy to enhance the electric control system of machine carrying bunch of dishes and low cost. The bundle of vegetable machine should meet the sensor to detect and control, in order to meet the control requirements; binding force can be adjusted by the button to achieve; strapping speed also can be adjusted, by the keys to set; sensors and mechanical line connection, convenient operation; can be directly connected with the plug, the 220V power supply can be connected to a power source; if, can work, by the transmission signal sensor, MCU to control the motor, drive and control procedures for small motor. The working principle of LED control circuit and temperature control circuit is described. The design of electric control system of automatic dish machine.

  5. Welding process automation in power machine building

    International Nuclear Information System (INIS)

    Mel'bard, S.N.; Shakhnov, A.F.; Shergov, I.V.

    1977-01-01

    The level of welding automation operations in power engineering and ways of its enhancement are highlighted. Used as the examples of comlex automation are an apparatus for the horizontal welding of turbine rotors, remotely controlled automatic machine for welding ring joint of large-sized vessels, equipment for the electron-beam welding of steam turbine assemblies of alloyed steels. The prospects of industrial robots are noted. The importance of the complex automation of technological process, including stocking, assemblying, transportation and auxiliary operations, is emphasized

  6. Design and Fabrication of Automatic Glass Cutting Machine

    Science.gov (United States)

    Veena, T. R.; Kadadevaramath, R. S.; Nagaraj, P. M.; Madhusudhan, S. V.

    2016-09-01

    This paper deals with the design and fabrication of the automatic glass or mirror cutting machine. In order to increase the accuracy of cut and production rate; and decrease the production time and accidents caused due to manual cutting of mirror or glass, this project aims at development of an automatic machine which uses a programmable logic controller (PLC) for controlling the movement of the conveyer and also to control the pneumatic circuit. In this machine, the work of the operator is to load and unload the mirror. The cutter used in this machine is carbide wheel with its cutting edge ground to a V-shaped profile. The PLC controls the pneumatic cylinder and intern actuates the cutter along the glass, a fracture layer is formed causing a mark to be formed below the fracture layer and a crack to be formed below the rib mark. The machine elements are designed using CATIA V5R20 and pneumatic circuit are designed using FESTO FLUID SIM software.

  7. Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

    Energy Technology Data Exchange (ETDEWEB)

    Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha (China)

    2006-10-15

    Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method.

  8. Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

    International Nuclear Information System (INIS)

    Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P

    2006-01-01

    Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method

  9. An automatic taxonomy of galaxy morphology using unsupervised machine learning

    Science.gov (United States)

    Hocking, Alex; Geach, James E.; Sun, Yi; Davey, Neil

    2018-01-01

    We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy we use no pre-selection or pre-filtering of target galaxy type to identify galaxies that are similar. We demonstrate the technique on the Hubble Space Telescope (HST) Frontier Fields. By training the algorithm using galaxies from one field (Abell 2744) and applying the result to another (MACS 0416.1-2403), we show how the algorithm can cleanly separate early and late type galaxies without any form of pre-directed training for what an 'early' or 'late' type galaxy is. We then apply the technique to the HST Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) fields, creating a catalogue of approximately 60 000 classifications. We show how the automatic classification groups galaxies of similar morphological (and photometric) type and make the classifications public via a catalogue, a visual catalogue and galaxy similarity search. We compare the CANDELS machine-based classifications to human-classifications from the Galaxy Zoo: CANDELS project. Although there is not a direct mapping between Galaxy Zoo and our hierarchical labelling, we demonstrate a good level of concordance between human and machine classifications. Finally, we show how the technique can be used to identify rarer objects and present lensed galaxy candidates from the CANDELS imaging.

  10. Automatic Task Classification via Support Vector Machine and Crowdsourcing

    Directory of Open Access Journals (Sweden)

    Hyungsik Shin

    2018-01-01

    Full Text Available Automatic task classification is a core part of personal assistant systems that are widely used in mobile devices such as smartphones and tablets. Even though many industry leaders are providing their own personal assistant services, their proprietary internals and implementations are not well known to the public. In this work, we show through real implementation and evaluation that automatic task classification can be implemented for mobile devices by using the support vector machine algorithm and crowdsourcing. To train our task classifier, we collected our training data set via crowdsourcing using the Amazon Mechanical Turk platform. Our classifier can classify a short English sentence into one of the thirty-two predefined tasks that are frequently requested while using personal mobile devices. Evaluation results show high prediction accuracy of our classifier ranging from 82% to 99%. By using large amount of crowdsourced data, we also illustrate the relationship between training data size and the prediction accuracy of our task classifier.

  11. A tape-controlled remote automatic diameter measurement machine

    International Nuclear Information System (INIS)

    Jennison, W.; Salmon, A.M.

    1978-01-01

    The machine is designed for the automatic measurement of fuel pins after irradiation in the fast reactors and is a modified version of a machine which has been in use for several years. These modifications consist of mechanical improvements and solid state control circuitry but the design criteria are unchanged. Irradiated fuel pins with diameters up to 0.875 in. are measured at fixed axial positions and angular intervals. Axial stepping of either 1 cm or 1 in. with a standard deviation of 5 x 10 -4 in. and angular rotation by multiples of 18 0 with a non-cumulative error of 1 0 can be selected. Data on axial position to 0.1 in. or 0.1 cm and fuel element diameter to 5 x 10 -5 in. are both punched and printed out for computer evaluation. The standard deviation of a single measurement on cylindrical specimens with an eccentricity of up to at least 0.1 in. should be no worse than 1 x 10 -4 in. No operator attention is required after the pin is positioned in the machine and 40 sets of 10 diameter readings at 36 0 intervals can be performed in an hour. Switches can be set between 1 and 99 to terminate an examination when power is switched off with the machine in its rest position. (author)

  12. Design and construction of automatic sorting station with machine vision

    Directory of Open Access Journals (Sweden)

    Oscar D. Velasco-Delgado

    2014-01-01

    Full Text Available This article presents the design, construction and testing of an automatic product sorting system in belt conveyor with machine vision that integrates Free and Open Source Software technology and Allen Bradley commercial equipment. Requirements are defined to determine features such as: mechanics of manufacturing station, an app of product sorting with machine vision and for automation system. For the app of machine vision a library is used for optical digital image processing Open CV, for the mechanical design of the manufacturing station is used the CAD tool Solid Edge and for the design and implementation of automation ISA standards are used along with an automation engineering project methodology integrating a PLC, an inverter, a Panel View and a DeviceNet Network. Performance tests are shown by classifying bottles and PVC pieces in four established types, the behavior of the integrated system is checked so as the efficiency of the same. The processing time on machine vision is 0.290 s on average for a piece of PVC, a capacity of 206 accessories per minute, for bottles was obtained a processing time of 0.267 s, a capacity of 224 bottles per minute. A maximum mechanical performance is obtained with 32 products per minute (1920 products/hour with the conveyor to 22 cm/s and 40 cm of distance between products obtaining an average error of 0.8%.

  13. Automatic Generation of Machine Emulators: Efficient Synthesis of Robust Virtual Machines for Legacy Software Migration

    DEFF Research Database (Denmark)

    Franz, Michael; Gal, Andreas; Probst, Christian

    2006-01-01

    As older mainframe architectures become obsolete, the corresponding le- gacy software is increasingly executed via platform emulators running on top of more modern commodity hardware. These emulators are virtual machines that often include a combination of interpreters and just-in-time compilers....... Implementing interpreters and compilers for each combination of emulated and target platform independently of each other is a redundant and error-prone task. We describe an alternative approach that automatically synthesizes specialized virtual-machine interpreters and just-in-time compilers, which...... then execute on top of an existing software portability platform such as Java. The result is a considerably reduced implementation effort....

  14. Automatic Generation of 3D Building Models with Multiple Roofs

    Institute of Scientific and Technical Information of China (English)

    Kenichi Sugihara; Yoshitugu Hayashi

    2008-01-01

    Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

  15. Automatic tea service machine with instantaneous cooling unit; Shunkan reikyaku kiko tosai jido kyuchaki

    Energy Technology Data Exchange (ETDEWEB)

    Sato, T.; Nishiyama, A. [Fuji Denki Reiki Co. Ltd., Tokyo (Japan)

    1999-08-10

    The market of automatic tea service machines demands sanitation, reduction in time required for pouring tea, feeding the material, cleaning the inside of the machine, the maintenance and service of the machine, and excellent design. To meet these demands, Fuji Electric has changed the former configuration and components for functions and has developed a new series of instantaneous automatic tea service machines based on a new concept. This paper outlines the advantages of the instantaneous cooling tank and improvements in handling. (author)

  16. The application of automatic chemiluminescence machine in rapid immune detection

    International Nuclear Information System (INIS)

    Lin Aizhen; Li Xuanwei; Chen Binhong; Li Zhenqian; Chen Zhaoxuan

    2004-01-01

    Objective: To provide high-quality, rapid and dependable result for clinical practice, and give satisfactory service to patients of different economical status by supplementation with other labeling immune examination. With an innovative attitude, we carried out efficient technical reform on ACS180 automatic chemiluminescence machine, making it possible for patients to complete the whole process including examination, check-out, diagnosis and getting drugs. The reported will be issued within an hour, thus a rapid immune detection service was established in out-patients department. Methods: 1. ACS-180 automatic chemiluminescence machine is used based on the principle of chemiluminescence immune methods. 2. The reagents are provided by Ciba-Comig Company of USA, composed of anti acridinium ester antibody of liquid phase and particulate antigen of solid phase wrapped in magnetic powder. 3. Calibration and quality control: high and low concentration are set for each calibration fluid with attached standard curve. Product for quality controlling includes three concentration of low, moderate and high. Results: 1. rapid machine detection for sample: serum is replaced with plasma coagulated by heparin, and comparison among series of methods using serum or plasma suggest no significant difference exists. 2. The problem about fasting detection: chemiluminescence machine measure optical density directly, with the results hardly being influenced by turbidity. But attention should be paid to the treatment of lipid turbid samples. 3. Other innovations: (1) direct placement of sample tube on machine: a cushion is placed on sample plate to transfer sample to machine directly after centrifugation, saving time and reducing the accident in sample transference. (2) for HCG quantification in blood and urine, 'gold criteria' is used firstly in screening to determine approximately the dilution range, with an advantage of saving time and reagent as well as accuracy. (3) we design a

  17. Automatic pellet density checking machine using vision technique

    International Nuclear Information System (INIS)

    Kumar, Suman; Raju, Y.S.; Raj Kumar, J.V.; Sairam, S.; Sheela; Hemantha Rao, G.V.S.

    2012-01-01

    Uranium di-oxide powder prepared through chemical process is converted to green pellets through the powder metallurgy route of precompaction and final compaction operations. These green pellets are kept in a molybdenum boat, which consists of a molybdenum base and a shroud. The boats are passed through the high temperature sintering furnaces to achieve required density of pellets. At present MIL standard 105 E is followed for measuring density of sintered pellets in the boat. As per AQL 2.5 of MIL standard, five pellets are collected from each boat, which contains approximately 800 nos of pellets. The densities of these collected pellets are measured. If anyone pellet density is less than the required value, the entire boat of pellets are rejected and sent back for dissolution for further processing. An Automatic Pellet Density Checking Machine (APDCM) was developed to salvage the acceptable density pellets from the rejected boat of pellets

  18. Machine learning for the automatic detection of anomalous events

    Science.gov (United States)

    Fisher, Wendy D.

    In this dissertation, we describe our research contributions for a novel approach to the application of machine learning for the automatic detection of anomalous events. We work in two different domains to ensure a robust data-driven workflow that could be generalized for monitoring other systems. Specifically, in our first domain, we begin with the identification of internal erosion events in earth dams and levees (EDLs) using geophysical data collected from sensors located on the surface of the levee. As EDLs across the globe reach the end of their design lives, effectively monitoring their structural integrity is of critical importance. The second domain of interest is related to mobile telecommunications, where we investigate a system for automatically detecting non-commercial base station routers (BSRs) operating in protected frequency space. The presence of non-commercial BSRs can disrupt the connectivity of end users, cause service issues for the commercial providers, and introduce significant security concerns. We provide our motivation, experimentation, and results from investigating a generalized novel data-driven workflow using several machine learning techniques. In Chapter 2, we present results from our performance study that uses popular unsupervised clustering algorithms to gain insights to our real-world problems, and evaluate our results using internal and external validation techniques. Using EDL passive seismic data from an experimental laboratory earth embankment, results consistently show a clear separation of events from non-events in four of the five clustering algorithms applied. Chapter 3 uses a multivariate Gaussian machine learning model to identify anomalies in our experimental data sets. For the EDL work, we used experimental data from two different laboratory earth embankments. Additionally, we explore five wavelet transform methods for signal denoising. The best performance is achieved with the Haar wavelets. We achieve up to 97

  19. Automatic inspection of surface defects in die castings after machining

    Directory of Open Access Journals (Sweden)

    S. J. Świłło

    2011-07-01

    Full Text Available A new camera based machine vision system for the automatic inspection of surface defects in aluminum die casting was developed by the authors. The problem of surface defects in aluminum die casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. The casting surfaces are the most highly loaded regions of materials and components. Mechanical and thermal loads as well as corrosion or irradiation attacks are directed primarily at the surface of the castings. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks or tears, inclusions due to chemical reactions or foreign material in the molten metal, and pores that greatly influence the material ability to withstand these loads. Surface defects may act as a stress concentrator initiating a fracture point. If a pressure is applied in this area, the casting can fracture. The human visual system is well adapted to perform in areas of variety and change; the visual inspection processes, on the other hand, require observing the same type of image repeatedly to detect anomalies. Slow, expensive, erratic inspection usually is the result. Computer based visual inspection provides a viable alternative to human inspectors. Developed by authors machine vision system uses an image processing algorithm based on modified Laplacian of Gaussian edge detection method to detect defects with different sizes and shapes. The defect inspection algorithm consists of three parameters. One is a parameter of defects sensitivity, the second parameter is a threshold level and the third parameter is to identify the detected defects size and shape. The machine vision system has been successfully tested for the different types of defects on the surface of castings.

  20. A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)

    Science.gov (United States)

    Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

    1992-01-01

    Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

  1. Automatic inspection of textured surfaces by support vector machines

    Science.gov (United States)

    Jahanbin, Sina; Bovik, Alan C.; Pérez, Eduardo; Nair, Dinesh

    2009-08-01

    Automatic inspection of manufactured products with natural looking textures is a challenging task. Products such as tiles, textile, leather, and lumber project image textures that cannot be modeled as periodic or otherwise regular; therefore, a stochastic modeling of local intensity distribution is required. An inspection system to replace human inspectors should be flexible in detecting flaws such as scratches, cracks, and stains occurring in various shapes and sizes that have never been seen before. A computer vision algorithm is proposed in this paper that extracts local statistical features from grey-level texture images decomposed with wavelet frames into subbands of various orientations and scales. The local features extracted are second order statistics derived from grey-level co-occurrence matrices. Subsequently, a support vector machine (SVM) classifier is trained to learn a general description of normal texture from defect-free samples. This algorithm is implemented in LabVIEW and is capable of processing natural texture images in real-time.

  2. Building machine learning systems with Python

    CERN Document Server

    Coelho, Luis Pedro

    2015-01-01

    This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.

  3. Automatic fitting of Gaussian peaks using abductive machine learning

    Science.gov (United States)

    Abdel-Aal, R. E.

    1998-02-01

    Analytical techniques have been used for many years for fitting Gaussian peaks in nuclear spectroscopy. However, the complexity of the approach warrants looking for machine-learning alternatives where intensive computations are required only once (during training), while actual analysis on individual spectra is greatly simplified and quickened. This should allow the use of simple portable systems for fast and automated analysis of large numbers of spectra, particularly in situations where accuracy may be traded for speed and simplicity. This paper proposes the use of abductive networks machine learning for this purpose. The Abductory Induction Mechanism (AIM) tool was used to build models for analyzing both single and double Gaussian peaks in the presence of noise depicting statistical uncertainties in collected spectra. AIM networks were synthesized by training on 1000 representative simulated spectra and evaluated on 500 new spectra. A classifier network determines the multiplicity of single/double peaks with an accuracy of 5.8%. With statistical uncertainties corresponding to a peak count of 100, average percentage absolute errors for the height, position, and width of single peaks are 4.9, 2.9, and 4.2%, respectively. For double peaks, these average errors are within 7.0, 3.1, and 5.9%, respectively. Models have been developed which account for the effect of a linear background on a single peak. Performance is compared with a neural network application and with an analytical curve-fitting routine, and the new technique is applied to actual data of an alpha spectrum.

  4. Automatic fitting of Gaussian peaks using abductive machine learning

    International Nuclear Information System (INIS)

    Abdel-Aal, R.E.

    1998-01-01

    Analytical techniques have been used for many years for fitting Gaussian peaks in nuclear spectroscopy. However, the complexity of the approach warrants looking for machine-learning alternatives where intensive computations are required only once (during training), while actual analysis on individual spectra is greatly simplified and quickened. This should allow the use of simple portable systems for fast and automated analysis of large numbers of spectra, particularly in situations where accuracy may be traded for speed and simplicity. This paper proposes the use of abductive networks machine learning for this purpose. The Abductory Induction Mechanism (AIM) tool was used to build models for analyzing both single and double Gaussian peaks in the presence of noise depicting statistical uncertainties in collected spectra. AIM networks were synthesized by training on 1,000 representative simulated spectra and evaluated on 500 new spectra. A classifier network determines the multiplicity of single/double peaks with an accuracy of 98%. With statistical uncertainties corresponding to a peak count of 100, average percentage absolute errors for the height, position, and width of single peaks are 4.9, 2.9, and 4.2%, respectively. For double peaks, these average errors are within 7.0, 3.1, and 5.9%, respectively. Models have been developed which account for the effect of a linear background on a single peak. Performance is compared with a neural network application and with an analytical curve-fitting routine, and the new technique is applied to actual data of an alpha spectrum

  5. Towards an automatic model transformation mechanism from UML state machines to DEVS models

    Directory of Open Access Journals (Sweden)

    Ariel González

    2015-08-01

    Full Text Available The development of complex event-driven systems requires studies and analysis prior to deployment with the goal of detecting unwanted behavior. UML is a language widely used by the software engineering community for modeling these systems through state machines, among other mechanisms. Currently, these models do not have appropriate execution and simulation tools to analyze the real behavior of systems. Existing tools do not provide appropriate libraries (sampling from a probability distribution, plotting, etc. both to build and to analyze models. Modeling and simulation for design and prototyping of systems are widely used techniques to predict, investigate and compare the performance of systems. In particular, the Discrete Event System Specification (DEVS formalism separates the modeling and simulation; there are several tools available on the market that run and collect information from DEVS models. This paper proposes a model transformation mechanism from UML state machines to DEVS models in the Model-Driven Development (MDD context, through the declarative QVT Relations language, in order to perform simulations using tools, such as PowerDEVS. A mechanism to validate the transformation is proposed. Moreover, examples of application to analyze the behavior of an automatic banking machine and a control system of an elevator are presented.

  6. PECULIARITIES OF THE TECHNOLOGY OF CONTINUOUS CASTING OF SLUGS OF MACHINE- AND MACHINE-TOOL-BUILDING

    OpenAIRE

    E. B. Demchenko; E. I. Marukovich

    2006-01-01

    The peculiarities of technology of continuous casting of ingots of machine- and machine tool building are shown. At development of technology it is necessary to subject the nomenclature of ingots to analysis in order to reveal expediency of their production by means of continuous casting.

  7. GRAPHITIZED STEELS IN MACHINE-BUILDING

    Directory of Open Access Journals (Sweden)

    I. V. Akimov

    2010-01-01

    Full Text Available It is shown that graphitized steels in some cases due to its intermediate disposition by structure and characteristics among low-carbon steels and cast irons, can provide the necessary combination of characteristics of construction material and consequently to increase safety and durability of details of metallurgical and machinebuilding industry machines.

  8. Crowd-sourced data collection to support automatic classification of building footprint data

    Science.gov (United States)

    Hecht, Robert; Kalla, Matthias; Krüger, Tobias

    2018-05-01

    Human settlements are mainly formed by buildings with their different characteristics and usage. Despite the importance of buildings for the economy and society, complete regional or even national figures of the entire building stock and its spatial distribution are still hardly available. Available digital topographic data sets created by National Mapping Agencies or mapped voluntarily through a crowd via Volunteered Geographic Information (VGI) platforms (e.g. OpenStreetMap) contain building footprint information but often lack additional information on building type, usage, age or number of floors. For this reason, predictive modeling is becoming increasingly important in this context. The capabilities of machine learning allow for the prediction of building types and other building characteristics and thus, the efficient classification and description of the entire building stock of cities and regions. However, such data-driven approaches always require a sufficient amount of ground truth (reference) information for training and validation. The collection of reference data is usually cost-intensive and time-consuming. Experiences from other disciplines have shown that crowdsourcing offers the possibility to support the process of obtaining ground truth data. Therefore, this paper presents the results of an experimental study aiming at assessing the accuracy of non-expert annotations on street view images collected from an internet crowd. The findings provide the basis for a future integration of a crowdsourcing component into the process of land use mapping, particularly the automatic building classification.

  9. Interface unit and software of X-ray television automatic machine

    International Nuclear Information System (INIS)

    Molodykh, V.A.; Yamanaev, M.S.

    1983-01-01

    Description of the interface unit and specialized software of X-ray television automatic machine is presented. An algorithm for automatic defect survey, measuring of defect geometric parameters with a successive estimate of control quality in accordance with technical norms is proposed. Experimental investigation results on the quality of welded joints of steel tubes obtained using the above system are summarized

  10. Automatic reel controls filler wire in welding machines

    Science.gov (United States)

    Millett, A. V.

    1966-01-01

    Automatic reel on automatic welding equipment takes up slack in the reel-fed filler wire when welding operation is terminated. The reel maintains constant, adjustable tension on the wire during the welding operation and rewinds the wire from the wire feed unit when the welding is completed.

  11. Evaluating automatically parallelized versions of the support vector machine

    NARCIS (Netherlands)

    Codreanu, V.; Dröge, B.; Williams, D.; Yasar, B.; Yang, P.; Liu, B.; Dong, F.; Surinta, O.; Schomaker, L.R.B.; Roerdink, J.B.T.M.; Wiering, M.A.

    2016-01-01

    The support vector machine (SVM) is a supervised learning algorithm used for recognizing patterns in data. It is a very popular technique in machine learning and has been successfully used in applications such as image classification, protein classification, and handwriting recognition. However, the

  12. Evaluating automatically parallelized versions of the support vector machine

    NARCIS (Netherlands)

    Codreanu, Valeriu; Droge, Bob; Williams, David; Yasar, Burhan; Yang, Fo; Liu, Baoquan; Dong, Feng; Surinta, Olarik; Schomaker, Lambertus; Roerdink, Jos; Wiering, Marco

    2014-01-01

    The support vector machine (SVM) is a supervised learning algorithm used for recognizing patterns in data. It is a very popular technique in machine learning and has been successfully used in applications such as image classification, protein classification, and handwriting recognition. However, the

  13. AUTOMATIC BUILDING OUTLINING FROM MULTI-VIEW OBLIQUE IMAGES

    Directory of Open Access Journals (Sweden)

    J. Xiao

    2012-07-01

    Full Text Available Automatic building detection plays an important role in many applications. Multiple overlapped airborne images as well as lidar point clouds are among the most popular data sources used for this purpose. Multi-view overlapped oblique images bear both height and colour information, and additionally we explicitly have access to the vertical extent of objects, therefore we explore the usability of this data source solely to detect and outline buildings in this paper. The outline can then be used for further 3D modelling. In the previous work, building hypotheses are generated using a box model based on detected façades from four directions. In each viewing direction, façade edges extracted from images and height information by stereo matching from an image pair is used for the façade detection. Given that many façades were missing due to occlusion or lack of texture whilst building roofs can be viewed in most images, this work mainly focuses on improve the building box outline by adding roof information. Stereo matched point cloud generated from oblique images are combined with the features from images. Initial roof patches are located in the point cloud. Then AdaBoost is used to integrate geometric and radiometric attributes extracted from oblique image on grid pixel level with the aim to refine the roof area. Generalized contours of the roof pixels are taken as building outlines. The preliminary test has been done by training with five buildings and testing around sixty building clusters. The proposed method performs well concerning covering the irregular roofs as well as improve the sides location of slope roof buildings. Outline result comparing with cadastral map shows almost all above 70% completeness and correctness in an area-based assessment, as well as 20% to 40% improvement in correctness with respect to our previous work.

  14. Estimating building energy consumption using extreme learning machine method

    International Nuclear Information System (INIS)

    Naji, Sareh; Keivani, Afram; Shamshirband, Shahaboddin; Alengaram, U. Johnson; Jumaat, Mohd Zamin; Mansor, Zulkefli; Lee, Malrey

    2016-01-01

    The current energy requirements of buildings comprise a large percentage of the total energy consumed around the world. The demand of energy, as well as the construction materials used in buildings, are becoming increasingly problematic for the earth's sustainable future, and thus have led to alarming concern. The energy efficiency of buildings can be improved, and in order to do so, their operational energy usage should be estimated early in the design phase, so that buildings are as sustainable as possible. An early energy estimate can greatly help architects and engineers create sustainable structures. This study proposes a novel method to estimate building energy consumption based on the ELM (Extreme Learning Machine) method. This method is applied to building material thicknesses and their thermal insulation capability (K-value). For this purpose up to 180 simulations are carried out for different material thicknesses and insulation properties, using the EnergyPlus software application. The estimation and prediction obtained by the ELM model are compared with GP (genetic programming) and ANNs (artificial neural network) models for accuracy. The simulation results indicate that an improvement in predictive accuracy is achievable with the ELM approach in comparison with GP and ANN. - Highlights: • Buildings consume huge amounts of energy for operation. • Envelope materials and insulation influence building energy consumption. • Extreme learning machine is used to estimate energy usage of a sample building. • The key effective factors in this study are insulation thickness and K-value.

  15. Automatic testing in the integration phase of mobile work machine (TINAT) - MASIT31

    Energy Technology Data Exchange (ETDEWEB)

    Multanen, P.; Hyvoenen, M. (Tampere University of Technology, Department of Intelligent Hydraulics and Automation, Tampere (Finland)); Ellman, A. (Tampere University of Technology, Department of Mechanics and Design, Tampere (Finland)); Rantala, S.; Alanen, J. (VTT Technical Research Centre of Finland, Espoo (Finland))

    2008-07-01

    Abstract The performance and reliability of mobile work machines are significantly affected by control systems of machines and their characteristics. Currently the testing of control systems and verification of their properties is often carried out just in the integration phase of controls and mechanical structure of machine. This is very time consuming, requires a lot of test personnel and is not extensive enough. In TINAT project a test concept will be developed for the testing of entire control systems of work machines without real the mechanical structures of the machines by utilizing modelling and real-time hardware-in-the-loop simulation. The simulator system enables automatic generation of test scenarios and automatic analysis and reporting of test results. (orig.)

  16. Machine Learning Classification of Buildings for Map Generalization

    Directory of Open Access Journals (Sweden)

    Jaeeun Lee

    2017-10-01

    Full Text Available A critical problem in mapping data is the frequent updating of large data sets. To solve this problem, the updating of small-scale data based on large-scale data is very effective. Various map generalization techniques, such as simplification, displacement, typification, elimination, and aggregation, must therefore be applied. In this study, we focused on the elimination and aggregation of the building layer, for which each building in a large scale was classified as “0-eliminated,” “1-retained,” or “2-aggregated.” Machine-learning classification algorithms were then used for classifying the buildings. The data of 1:1000 scale and 1:25,000 scale digital maps obtained from the National Geographic Information Institute were used. We applied to these data various machine-learning classification algorithms, including naive Bayes (NB, decision tree (DT, k-nearest neighbor (k-NN, and support vector machine (SVM. The overall accuracies of each algorithm were satisfactory: DT, 88.96%; k-NN, 88.27%; SVM, 87.57%; and NB, 79.50%. Although elimination is a direct part of the proposed process, generalization operations, such as simplification and aggregation of polygons, must still be performed for buildings classified as retained and aggregated. Thus, these algorithms can be used for building classification and can serve as preparatory steps for building generalization.

  17. Point card compatible automatic vending machine for canned drink; Point card taio kan jido hanbaiki

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-01-10

    A point card compatible automatic vending machine for canned drinks is developed, which provides drink manufacturers with a powerful tool to acquire selling sites and attract consumers. Since the machine is equipped with a device to handle point cards, regular customers have increased and sales have picked up. A point card issuing device is also installed, and the new machine issues a point card whenever a customer wants. The drink manufacturers are evaluating high of the vending machine because it will contribute to the diffusion of the point card system and because a sales promotion campaign may be conducted through the vending machine for instance by exchanging a fully marked card with a giveaway on the spot. In the future, a bill validator (paper money identifier) will be integrated even with small size machines for the diffusion of point card compatible machines. (translated by NEDO)

  18. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

    Science.gov (United States)

    Zeng, Xueqiang; Luo, Gang

    2017-12-01

    Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

  19. Innovative model of business process reengineering at machine building enterprises

    Science.gov (United States)

    Nekrasov, R. Yu; Tempel, Yu A.; Tempel, O. A.

    2017-10-01

    The paper provides consideration of business process reengineering viewed as amanagerial innovation accepted by present day machine building enterprises, as well as waysto improve its procedure. A developed innovative model of reengineering measures isdescribed and is based on the process approach and other principles of company management.

  20. Automated mapping of building facades by machine learning

    DEFF Research Database (Denmark)

    Höhle, Joachim

    2014-01-01

    Facades of buildings contain various types of objects which have to be recorded for information systems. The article describes a solution for this task focussing on automated classification by means of machine learning techniques. Stereo pairs of oblique images are used to derive 3D point clouds...

  1. System approach to machine building enterprise innovative activity management

    Directory of Open Access Journals (Sweden)

    І.V. Levytska

    2016-12-01

    Full Text Available The company, which operates in a challenging competitive environment should focus on new products and provide innovative services that enhance their innovation to maintain the company’s market position. The article deals with the peculiarities of such an activity in the company. The authors analyze the various approaches used in the management, and supply the advantages and disadvantages of each. It is determine that the most optimal approach among them is a system approach. The definition of the consepts "a system" and "a systematic approach to innovative activity management" are suggested. The article works out the system of machine building enterprise innovative activity management, the organization of machine building enterprise innovative activity; the planning of machine building enterprise innovative activity; the control in the system of machine building enterprise innovative activity management; the elements of the control subsystem. The properties, typical for the system of innovative management, are supplied. The managers, engaged in enterprise innovative activity management, must perform a number of the suggested tasks, which affect the efficiency of the enterprise as a whole. These exact tasks are performed using the systematic approach, providing the enterprise competitive operation and quick adaptation to changes in the external environment.

  2. Building machine learning force fields for nanoclusters

    Science.gov (United States)

    Zeni, Claudio; Rossi, Kevin; Glielmo, Aldo; Fekete, Ádám; Gaston, Nicola; Baletto, Francesca; De Vita, Alessandro

    2018-06-01

    We assess Gaussian process (GP) regression as a technique to model interatomic forces in metal nanoclusters by analyzing the performance of 2-body, 3-body, and many-body kernel functions on a set of 19-atom Ni cluster structures. We find that 2-body GP kernels fail to provide faithful force estimates, despite succeeding in bulk Ni systems. However, both 3- and many-body kernels predict forces within an ˜0.1 eV/Å average error even for small training datasets and achieve high accuracy even on out-of-sample, high temperature structures. While training and testing on the same structure always provide satisfactory accuracy, cross-testing on dissimilar structures leads to higher prediction errors, posing an extrapolation problem. This can be cured using heterogeneous training on databases that contain more than one structure, which results in a good trade-off between versatility and overall accuracy. Starting from a 3-body kernel trained this way, we build an efficient non-parametric 3-body force field that allows accurate prediction of structural properties at finite temperatures, following a newly developed scheme [A. Glielmo et al., Phys. Rev. B 95, 214302 (2017)]. We use this to assess the thermal stability of Ni19 nanoclusters at a fractional cost of full ab initio calculations.

  3. An Automatic Decision-Making Mechanism for Virtual Machine Live Migration in Private Clouds

    Directory of Open Access Journals (Sweden)

    Ming-Tsung Kao

    2014-01-01

    Full Text Available Due to the increasing number of computer hosts deployed in an enterprise, automatic management of electronic applications is inevitable. To provide diverse services, there will be increases in procurement, maintenance, and electricity costs. Virtualization technology is getting popular in cloud computing environment, which enables the efficient use of computing resources and reduces the operating cost. In this paper, we present an automatic mechanism to consolidate virtual servers and shut down the idle physical machines during the off-peak hours, while activating more machines at peak times. Through the monitoring of system resources, heavy system loads can be evenly distributed over physical machines to achieve load balancing. By integrating the feature of load balancing with virtual machine live migration, we successfully develop an automatic private cloud management system. Experimental results demonstrate that, during the off-peak hours, we can save power consumption of about 69 W by consolidating the idle virtual servers. And the load balancing implementation has shown that two machines with 80% and 40% CPU loads can be uniformly balanced to 60% each. And, through the use of preallocated virtual machine images, the proposed mechanism can be easily applied to a large amount of physical machines.

  4. Improving Automation Routines for Automatic Heating Load Detection in Buildings

    Directory of Open Access Journals (Sweden)

    Stephen Timlin

    2012-11-01

    Full Text Available Energy managers use weather compensation data and heating system cut off routines to reduce heating energy consumption in buildings and improve user comfort. These routines are traditionally based on the calculation of an estimated building load that is inferred from the external dry bulb temperature at any point in time. While this method does reduce heating energy consumption and accidental overheating, it can be inaccurate under some weather conditions and therefore has limited effectiveness. There remains considerable scope to improve on the accuracy and relevance of the traditional method by expanding the calculations used to include a larger range of environmental metrics. It is proposed that weather compensation and automatic shut off routines that are commonly used could be improved notably with little additional cost by the inclusion of additional weather metrics. This paper examines the theoretical relationship between various external metrics and building heating loads. Results of the application of an advanced routine to a recently constructed building are examined, and estimates are made of the potential savings that can be achieved through the use of the routines proposed.

  5. A Development of Automatic Audit System for Written Informed Consent using Machine Learning.

    Science.gov (United States)

    Yamada, Hitomi; Takemura, Tadamasa; Asai, Takahiro; Okamoto, Kazuya; Kuroda, Tomohiro; Kuwata, Shigeki

    2015-01-01

    In Japan, most of all the university and advanced hospitals have implemented both electronic order entry systems and electronic charting. In addition, all medical records are subjected to inspector audit for quality assurance. The record of informed consent (IC) is very important as this provides evidence of consent from the patient or patient's family and health care provider. Therefore, we developed an automatic audit system for a hospital information system (HIS) that is able to evaluate IC automatically using machine learning.

  6. Automated Classification of Heritage Buildings for As-Built Bim Using Machine Learning Techniques

    Science.gov (United States)

    Bassier, M.; Vergauwen, M.; Van Genechten, B.

    2017-08-01

    Semantically rich three dimensional models such as Building Information Models (BIMs) are increasingly used in digital heritage. They provide the required information to varying stakeholders during the different stages of the historic buildings life cyle which is crucial in the conservation process. The creation of as-built BIM models is based on point cloud data. However, manually interpreting this data is labour intensive and often leads to misinterpretations. By automatically classifying the point cloud, the information can be proccesed more effeciently. A key aspect in this automated scan-to-BIM process is the classification of building objects. In this research we look to automatically recognise elements in existing buildings to create compact semantic information models. Our algorithm efficiently extracts the main structural components such as floors, ceilings, roofs, walls and beams despite the presence of significant clutter and occlusions. More specifically, Support Vector Machines (SVM) are proposed for the classification. The algorithm is evaluated using real data of a variety of existing buildings. The results prove that the used classifier recognizes the objects with both high precision and recall. As a result, entire data sets are reliably labelled at once. The approach enables experts to better document and process heritage assets.

  7. Automatic microseismic event picking via unsupervised machine learning

    Science.gov (United States)

    Chen, Yangkang

    2018-01-01

    Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

  8. Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Zhiling Guo

    2016-03-01

    Full Text Available In this study, a method based on supervised machine learning is proposed to identify village buildings from open high-resolution remote sensing images. We select Google Earth (GE RGB images to perform the classification in order to examine its suitability for village mapping, and investigate the feasibility of using machine learning methods to provide automatic classification in such fields. By analyzing the characteristics of GE images, we design different features on the basis of two kinds of supervised machine learning methods for classification: adaptive boosting (AdaBoost and convolutional neural networks (CNN. To recognize village buildings via their color and texture information, the RGB color features and a large number of Haar-like features in a local window are utilized in the AdaBoost method; with multilayer trained networks based on gradient descent algorithms and back propagation, CNN perform the identification by mining deeper information from buildings and their neighborhood. Experimental results from the testing area at Savannakhet province in Laos show that our proposed AdaBoost method achieves an overall accuracy of 96.22% and the CNN method is also competitive with an overall accuracy of 96.30%.

  9. Automatic fuel charging machine for nuclear power plants

    International Nuclear Information System (INIS)

    Neda, Toshikazu; Aoki, Shigeo.

    1978-01-01

    Purpose: To enable smooth, safety and rapid refueling by automatically conducting a series of fuel exchange steps through the combination of calculations for fuel control and refueling works. Constitution: Processing operations are conducted based on various data from the memory unit of a computer that processes and stores various data inputted from a nuclear power plant, calculation systems stored in the memory unit of another computer, peripheral units such as typewriters and process input units. A refueling platform is operated by way of a platform control device and a platform driving device, and fuel exchange is conducted by the operation of a channel mounting and demounting device. (Yoshino, Y.)

  10. Novel Automatic Filter-Class Feature Selection for Machine Learning Regression

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Hallam, John; Jørgensen, Bo Nørregaard

    2017-01-01

    With the increased focus on application of Big Data in all sectors of society, the performance of machine learning becomes essential. Efficient machine learning depends on efficient feature selection algorithms. Filter feature selection algorithms are model-free and therefore very fast, but require...... model in the feature selection process. PCA is often used in machine learning litterature and can be considered the default feature selection method. RDESF outperformed PCA in both experiments in both prediction error and computational speed. RDESF is a new step into filter-based automatic feature...

  11. An Automatic Instruction-Level Parallelization of Machine Code

    Directory of Open Access Journals (Sweden)

    MARINKOVIC, V.

    2018-02-01

    Full Text Available Prevailing multicores and novel manycores have made a great challenge of modern day - parallelization of embedded software that is still written as sequential. In this paper, automatic code parallelization is considered, focusing on developing a parallelization tool at the binary level as well as on the validation of this approach. The novel instruction-level parallelization algorithm for assembly code which uses the register names after SSA to find independent blocks of code and then to schedule independent blocks using METIS to achieve good load balance is developed. The sequential consistency is verified and the validation is done by measuring the program execution time on the target architecture. Great speedup, taken as the performance measure in the validation process, and optimal load balancing are achieved for multicore RISC processors with 2 to 16 cores (e.g. MIPS, MicroBlaze, etc.. In particular, for 16 cores, the average speedup is 7.92x, while in some cases it reaches 14x. An approach to automatic parallelization provided by this paper is useful to researchers and developers in the area of parallelization as the basis for further optimizations, as the back-end of a compiler, or as the code parallelization tool for an embedded system.

  12. A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

    Science.gov (United States)

    D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

    1993-01-01

    A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

  13. Automatic visual grading of grain products by machine vision

    Science.gov (United States)

    Dubosclard, Pierre; Larnier, Stanislas; Konik, Hubert; Herbulot, Ariane; Devy, Michel

    2015-11-01

    This paper presents two automatic methods for visual grading, deterministic and probabilistic, designed to solve the industrial problem of evaluation of seed lots from the characterization of a representative sample. The sample is thrown in bulk onto a tray placed in a chamber for acquiring color image in a controlled and reproducible manner. Two image-processing methods have been developed to separate and then characterize each seed present in the image. A shape learning is performed on isolated seeds. Collected information is used for the segmentation. The first approach adopted for the segmentation step is based on simple criteria such as regions, edges, and normals to the boundary. Marked point processes are used in the second approach, leading to tackling of the problem by a technique of energy minimization. In both approaches, an active contour with prior shape is performed to improve the results. A classification is done on shape or color descriptors to evaluate the quality of the sample.

  14. Automatic Detection of Retinal Exudates using a Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Nualsawat HIRANSAKOLWONG

    2013-02-01

    Full Text Available Retinal exudates are among the preliminary signs of diabetic retinopathy, a major cause of vision loss in diabetic patients. Correct and efficient screening of exudates is very expensive in professional time and may cause human error. Nowadays, the digital retinal image is frequently used to follow-up and diagnoses eye diseases. Therefore, the retinal image is crucial and essential for experts to detect exudates. Unfortunately, it is a normal situation that retinal images in Thailand are poor quality images. In this paper, we present a series of experiments on feature selection and exudates classification using the support vector machine classifiers. The retinal images are segmented following key preprocessing steps, i.e., color normalization, contrast enhancement, noise removal and color space selection. On data sets of poor quality images, sensitivity, specificity and accuracy is 94.46%, 89.52% and 92.14%, respectively.

  15. Automatic Indoor Building Reconstruction from Mobile Laser Scanning Data

    Science.gov (United States)

    Xie, L.; Wang, R.

    2017-09-01

    Indoor reconstruction from point clouds is a hot topic in photogrammetry, computer vision and computer graphics. Reconstructing indoor scene from point clouds is challenging due to complex room floorplan and line-of-sight occlusions. Most of existing methods deal with stationary terrestrial laser scanning point clouds or RGB-D point clouds. In this paper, we propose an automatic method for reconstructing indoor 3D building models from mobile laser scanning point clouds. The method includes 2D floorplan generation, 3D building modeling, door detection and room segmentation. The main idea behind our approach is to separate wall structure into two different types as the inner wall and the outer wall based on the observation of point distribution. Then we utilize a graph cut based optimization method to solve the labeling problem and generate the 2D floorplan based on the optimization result. Subsequently, we leverage an ?-shape based method to detect the doors on the 2D projected point clouds and utilize the floorplan to segment the individual room. The experiments show that this door detection method can achieve a recognition rate at 97% and the room segmentation method can attain the correct segmentation results. We also evaluate the reconstruction accuracy on the synthetic data, which indicates the accuracy of our method is comparable to the state-of-the art.

  16. An artificial molecular machine that builds an asymmetric catalyst

    Science.gov (United States)

    De Bo, Guillaume; Gall, Malcolm A. Y.; Kuschel, Sonja; De Winter, Julien; Gerbaux, Pascal; Leigh, David A.

    2018-05-01

    Biomolecular machines perform types of complex molecular-level tasks that artificial molecular machines can aspire to. The ribosome, for example, translates information from the polymer track it traverses (messenger RNA) to the new polymer it constructs (a polypeptide)1. The sequence and number of codons read determines the sequence and number of building blocks incorporated into the biomachine-synthesized polymer. However, neither control of sequence2,3 nor the transfer of length information from one polymer to another (which to date has only been accomplished in man-made systems through template synthesis)4 is easily achieved in the synthesis of artificial macromolecules. Rotaxane-based molecular machines5-7 have been developed that successively add amino acids8-10 (including β-amino acids10) to a growing peptide chain by the action of a macrocycle moving along a mono-dispersed oligomeric track derivatized with amino-acid phenol esters. The threaded macrocycle picks up groups that block its path and links them through successive native chemical ligation reactions11 to form a peptide sequence corresponding to the order of the building blocks on the track. Here, we show that as an alternative to translating sequence information, a rotaxane molecular machine can transfer the narrow polydispersity of a leucine-ester-derivatized polystyrene chain synthesized by atom transfer radical polymerization12 to a molecular-machine-made homo-leucine oligomer. The resulting narrow-molecular-weight oligomer folds to an α-helical secondary structure13 that acts as an asymmetric catalyst for the Juliá-Colonna epoxidation14,15 of chalcones.

  17. Possibilities for Automatic Control of Hydro-Mechanical Transmission and Birotating Electric Machine

    Directory of Open Access Journals (Sweden)

    V. V. Mikhailov

    2014-01-01

    Full Text Available The paper presents mathematical models and results of virtual investigations pertaining to the selected motion parameters of a mobile machine equipped with hydro mechanical and modernized transmissions. The machine has been tested in similar technological cycles and it has been equipped with a universal automatic control system. Changes in structure and type of power transmission have been obtained with the help of a control algorithm including an extra reversible electric machine which is switched in at some operational modes.Implementation of the proposed  concept makes it possible to obtain and check the improved C-code of the control system and enhance operational parameters of the transmission and machine efficiency, reduce slippage and tire wear while using braking energy for its later beneficial use which is usually considered as a consumable element.

  18. A modern automatic Carriage-Trolley Position Control System for Dhruva fuelling machine

    International Nuclear Information System (INIS)

    Agrawal, Ankit; Hari Balakrishna; Narvekar, J.P.; Sanadhya, Vivek

    2014-01-01

    A fully automatic absolute encoder based position control system has been designed developed implemented and commissioned for the Dhruva Fuelling Machine A (FM/A). This supports both the coarse and fine positioning modes. Provision for fully manual positioning as a standby system has been retained. This system replaces the ageing peg counting based incremental positioner used briefly during the early period after the Dhruva FM/A was commissioned. The older system suffered from peg detection skipping problems; hence it was not being used. Only full manual positioning was being carried out. This paper describes the automatic Carriage Trolley Position Control System (CTPCS). (author)

  19. Automatically explaining machine learning prediction results: a demonstration on type 2 diabetes risk prediction.

    Science.gov (United States)

    Luo, Gang

    2016-01-01

    Predictive modeling is a key component of solutions to many healthcare problems. Among all predictive modeling approaches, machine learning methods often achieve the highest prediction accuracy, but suffer from a long-standing open problem precluding their widespread use in healthcare. Most machine learning models give no explanation for their prediction results, whereas interpretability is essential for a predictive model to be adopted in typical healthcare settings. This paper presents the first complete method for automatically explaining results for any machine learning predictive model without degrading accuracy. We did a computer coding implementation of the method. Using the electronic medical record data set from the Practice Fusion diabetes classification competition containing patient records from all 50 states in the United States, we demonstrated the method on predicting type 2 diabetes diagnosis within the next year. For the champion machine learning model of the competition, our method explained prediction results for 87.4 % of patients who were correctly predicted by the model to have type 2 diabetes diagnosis within the next year. Our demonstration showed the feasibility of automatically explaining results for any machine learning predictive model without degrading accuracy.

  20. The testing report of the development for the lithium grains and lithium rod automatic machine

    International Nuclear Information System (INIS)

    Qian Zongkui; Kong Xianghong; Huang Yong

    2008-06-01

    With the development of lithium industry, the lithium grains and lithium rod, as additive or catalyzer, having a big comparatively acreage and a strong activated feature, have a broad application. The lithium grains and lithium rod belong to the kind of final machining materials. The principle of the lithium grains and lithium rod that how to take shape through the procedures of extrusion, cutting, anti-conglutination, threshing and so on are analysed, A sort of lithium grains and lithium rod automatic machine is developed. (authors)

  1. Integrating Automatic Speech Recognition and Machine Translation for Better Translation Outputs

    DEFF Research Database (Denmark)

    Liyanapathirana, Jeevanthi

    translations, combining machine translation with computer assisted translation has drawn attention in current research. This combines two prospects: the opportunity of ensuring high quality translation along with a significant performance gain. Automatic Speech Recognition (ASR) is another important area......, which caters important functionalities in language processing and natural language understanding tasks. In this work we integrate automatic speech recognition and machine translation in parallel. We aim to avoid manual typing of possible translations as dictating the translation would take less time...... to the n-best list rescoring, we also use word graphs with the expectation of arriving at a tighter integration of ASR and MT models. Integration methods include constraining ASR models using language and translation models of MT, and vice versa. We currently develop and experiment different methods...

  2. Component simulation in problems of calculated model formation of automatic machine mechanisms

    Directory of Open Access Journals (Sweden)

    Telegin Igor

    2017-01-01

    Full Text Available The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gaps in kinematic pairs, friction forces, design and technological loads. As an example in the paper there are considered a formalization of stages in the computer model formation of the cutting mechanism in cold stamping automatic machine AV1818 and methods of for the computation of their parameters on the basis of its solid-state model.

  3. a Method for the Seamlines Network Automatic Selection Based on Building Vector

    Science.gov (United States)

    Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

    2018-04-01

    In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

  4. Component simulation in problems of calculated model formation of automatic machine mechanisms

    OpenAIRE

    Telegin Igor; Kozlov Alexander; Zhirkov Alexander

    2017-01-01

    The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gap...

  5. Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

    OpenAIRE

    Shang-Liang Chen; Yin-Ting Cheng; Chin-Fa Su

    2015-01-01

    Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as ...

  6. Automated Biometric Voice-Based Access Control in Automatic Teller Machine (ATM)

    OpenAIRE

    Yekini N.A.; Itegboje A.O.; Oyeyinka I.K.; Akinwole A.K.

    2012-01-01

    An automatic teller machine requires a user to pass an identity test before any transaction can be granted. The current method available for access control in ATM is based on smartcard. Efforts were made to conduct an interview with structured questions among the ATM users and the result proofed that a lot of problems was associated with ATM smartcard for access control. Among the problems are; it is very difficult to prevent another person from attaining and using a legitimate persons card, ...

  7. Building machines that learn and think like people.

    Science.gov (United States)

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

    2017-01-01

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

  8. An Automatic Assembling System for Sealing Rings Based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Mingyu Gao

    2017-01-01

    Full Text Available In order to grab and place the sealing rings of battery lid quickly and accurately, an automatic assembling system for sealing rings based on machine vision is developed in this paper. The whole system is composed of the light sources, cameras, industrial control units, and a 4-degree-of-freedom industrial robot. Specifically, the sealing rings are recognized and located automatically with the machine vision module. Then industrial robot is controlled for grabbing the sealing rings dynamically under the joint work of multiple control units and visual feedback. Furthermore, the coordinates of the fast-moving battery lid are tracked by the machine vision module. Finally the sealing rings are placed on the sealing ports of battery lid accurately and automatically. Experimental results demonstrate that the proposed system can grab the sealing rings and place them on the sealing port of the fast-moving battery lid successfully. More importantly, the proposed system can improve the efficiency of the battery production line obviously.

  9. Process acceptance and adjustment techniques for Swiss automatic screw machine parts. Final report

    International Nuclear Information System (INIS)

    Robb, J.M.

    1976-01-01

    Product tolerance requirements for small, cylindrical, piece parts produced on swiss automatic screw machines have progressed to the reliability limits of inspection equipment. The miniature size, configuration, and tolerance requirements (plus or minus 0.0001 in.) (0.00254 mm) of these parts preclude the use of screening techniques to accept product or adjust processes during setup and production runs; therefore, existing means of product acceptance and process adjustment must be refined or new techniques must be developed. The purpose of this endeavor has been to determine benefits gained through the implementation of a process acceptance technique (PAT) to swiss automatic screw machine processes. PAT is a statistical approach developed for the purpose of accepting product and centering processes for parts produced by selected, controlled processes. Through this endeavor a determination has been made of the conditions under which PAT can benefit a controlled process and some specific types of screw machine processes upon which PAT could be applied. However, it was also determined that PAT, if used indiscriminately, may become a record keeping burden when applied to more than one dimension at a given machining operation

  10. Comparative Analysis of Automatic Exudate Detection between Machine Learning and Traditional Approaches

    Science.gov (United States)

    Sopharak, Akara; Uyyanonvara, Bunyarit; Barman, Sarah; Williamson, Thomas

    To prevent blindness from diabetic retinopathy, periodic screening and early diagnosis are neccessary. Due to lack of expert ophthalmologists in rural area, automated early exudate (one of visible sign of diabetic retinopathy) detection could help to reduce the number of blindness in diabetic patients. Traditional automatic exudate detection methods are based on specific parameter configuration, while the machine learning approaches which seems more flexible may be computationally high cost. A comparative analysis of traditional and machine learning of exudates detection, namely, mathematical morphology, fuzzy c-means clustering, naive Bayesian classifier, Support Vector Machine and Nearest Neighbor classifier are presented. Detected exudates are validated with expert ophthalmologists' hand-drawn ground-truths. The sensitivity, specificity, precision, accuracy and time complexity of each method are also compared.

  11. A method for the automatic separation of the images of galaxies and stars from measurements made with the COSMOS machine

    International Nuclear Information System (INIS)

    MacGillivray, H.T.; Martin, R.; Pratt, N.M.; Reddish, V.C.; Seddon, H.; Alexander, L.W.G.; Walker, G.S.; Williams, P.R.

    1976-01-01

    A method has been developed which allows the computer to distinguish automatically between the images of galaxies and those of stars from measurements made with the COSMOS automatic plate-measuring machine at the Royal Observatory, Edinburgh. Results have indicated that a 90 to 95 per cent separation between galaxies and stars is possible. (author)

  12. Structural capacity assessment of machine-building enterprises and associations

    Directory of Open Access Journals (Sweden)

    Prilutskay Maria

    2017-01-01

    Full Text Available Multidirectional tendencies of machine-building enterprises integration and disintegration resulted in the emergence of the formal and informal associations. These associations consist of the obviously and/or implicitly affiliated legal entities. Thus, a new element appears in the direct enterprise environment, i.e a management company or a head enterprise. The management company influences the participants even in an informal association. New environment restrictions led to the changes in the management structure. The paper considers the enterprise structures interrelation: organizational, financial, production, resource, and others. The authors draw a conclusion that the structures are hierarchy, and there are the coherence structures assessment criteria. The coordinated structures form the structural capacity of the enterprise. The suggested assessment coherence criteria (for example resource and functional structures allow estimating the structural potential and defining the directions of the enterprise efficiency increase.

  13. Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

    Science.gov (United States)

    Kong, Xiangyi; Gong, Shun; Su, Lijuan; Howard, Newton; Kong, Yanguo

    2018-01-01

    Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  14. Intelligent buildings, automatic fire alarm and fire-protection control system

    International Nuclear Information System (INIS)

    Tian Deyuan

    1999-01-01

    The author describes in brief the intelligent buildings, and the automatic fire alarm and fire-protection control system. On the basis of the four-bus, three-bus and two-bus, a new transfer technique was developed

  15. LARA. Localization of an automatized refueling machine by acoustical sounding in breeder reactors - implementation of artificial intelligence techniques

    International Nuclear Information System (INIS)

    Lhuillier, C.; Malvache, P.

    1987-01-01

    The automatic control of the machine which handles the nuclear subassemblies in fast neutron reactors requires autonomous perception and decision tools. An acoustical device allows the machine to position in the work area. Artificial intelligence techniques are implemented to interpret the data: pattern recognition, scene analysis. The localization process is managed by an expert system. 6 refs.; 8 figs

  16. Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Jennum, Poul; Sorensen, Helge B. D.

    2013-01-01

    an automatic sleep stage detector, which can separate wakefulness, rapid-eye-movement (REM) sleep and non-REM (NREM) sleep using only EEG and EOG. Most sleep events, which define the sleep stages, are reduced with age. This is addressed by focusing on the amplitude of the clinical EEG bands......Aging is a process that is inevitable, and makes our body vulnerable to age-related diseases. Age is the most consistent factor affecting the sleep structure. Therefore, new automatic sleep staging methods, to be used in both of young and elderly patients, are needed. This study proposes......, and not the affected sleep events. The age-related influences are then reduced by robust subject-specific scaling. The classification of the three sleep stages are achieved by a multi-class support vector machine using the one-versus-rest scheme. It was possible to obtain a high classification accuracy of 0...

  17. Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

    Science.gov (United States)

    Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

    2017-12-01

    In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to

  18. Applying machine-learning techniques to Twitter data for automatic hazard-event classification.

    Science.gov (United States)

    Filgueira, R.; Bee, E. J.; Diaz-Doce, D.; Poole, J., Sr.; Singh, A.

    2017-12-01

    The constant flow of information offered by tweets provides valuable information about all sorts of events at a high temporal and spatial resolution. Over the past year we have been analyzing in real-time geological hazards/phenomenon, such as earthquakes, volcanic eruptions, landslides, floods or the aurora, as part of the GeoSocial project, by geo-locating tweets filtered by keywords in a web-map. However, not all the filtered tweets are related with hazard/phenomenon events. This work explores two classification techniques for automatic hazard-event categorization based on tweets about the "Aurora". First, tweets were filtered using aurora-related keywords, removing stop words and selecting the ones written in English. For classifying the remaining between "aurora-event" or "no-aurora-event" categories, we compared two state-of-art techniques: Support Vector Machine (SVM) and Deep Convolutional Neural Networks (CNN) algorithms. Both approaches belong to the family of supervised learning algorithms, which make predictions based on labelled training dataset. Therefore, we created a training dataset by tagging 1200 tweets between both categories. The general form of SVM is used to separate two classes by a function (kernel). We compared the performance of four different kernels (Linear Regression, Logistic Regression, Multinomial Naïve Bayesian and Stochastic Gradient Descent) provided by Scikit-Learn library using our training dataset to build the SVM classifier. The results shown that the Logistic Regression (LR) gets the best accuracy (87%). So, we selected the SVM-LR classifier to categorise a large collection of tweets using the "dispel4py" framework.Later, we developed a CNN classifier, where the first layer embeds words into low-dimensional vectors. The next layer performs convolutions over the embedded word vectors. Results from the convolutional layer are max-pooled into a long feature vector, which is classified using a softmax layer. The CNN's accuracy

  19. 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.

  20. Connection of control circuits of machine for automatic measurement of radioactive samples

    International Nuclear Information System (INIS)

    Vorlicek, J.

    1984-01-01

    A windowless through-flow gas detector is used for measurement. The automatic machine is controlled by four flip-flops defining the following states: the dish replacement in the measuring space, washing, measurement, measured value print-out, and resetting. The first and second outputs of the first, second and third flip-flops are connected to six inputs of a block whose four outputs provide counter reset and stop-watch reset, washing, measurement, and print-out. Such machine control eliminates measurement errors by disabling sample measurement until air is removed from the measurement space, introduced on an unwashed dish or on several dishes passed under the detector. The elimination of this error is also guaranteed in manual operation. (M.D.)

  1. Automatic optical detection and classification of marine animals around MHK converters using machine vision

    Energy Technology Data Exchange (ETDEWEB)

    Brunton, Steven [Univ. of Washington, Seattle, WA (United States)

    2018-01-15

    Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robust principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.

  2. Automatic Detection of P and S Phases by Support Vector Machine

    Science.gov (United States)

    Jiang, Y.; Ning, J.; Bao, T.

    2017-12-01

    Many methods in seismology rely on accurately picked phases. A well performed program on automatically phase picking will assure the application of these methods. Related researches before mostly focus on finding different characteristics between noise and phases, which are all not enough successful. We have developed a new method which mainly based on support vector machine to detect P and S phases. In it, we first input some waveform pieces into the support vector machine, then employ it to work out a hyper plane which can divide the space into two parts: respectively noise and phase. We further use the same method to find a hyper plane which can separate the phase space into P and S parts based on the three components' cross-correlation matrix. In order to further improve the ability of phase detection, we also employ array data. At last, we show that the overall effect of our method is robust by employing both synthetic and real data.

  3. MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

    International Nuclear Information System (INIS)

    Chang, X; Yang, D

    2015-01-01

    Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was used to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System

  4. MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chang, X; Yang, D [Washington University in St Louis, St Louis, MO (United States)

    2015-06-15

    Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was used to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.

  5. Automatized welding equipment for manufacturing steel cells for special buildings

    International Nuclear Information System (INIS)

    Weikert, F.; Winter, K.P.

    1986-01-01

    In GDR's nuclear power plant construction, reinforced concrete wall cells are used to construct pressure and full pressure containments for WWER-440 and WWER-1000 reactors, respectively. Welding processes for the prefabrication of steel cells as reinforcement have been automatized in order to increase both labor productivity and quality assurance. 11 figs

  6. Model design and simulation of automatic sorting machine using proximity sensor

    Directory of Open Access Journals (Sweden)

    Bankole I. Oladapo

    2016-09-01

    Full Text Available The automatic sorting system has been reported to be complex and a global problem. This is because of the inability of sorting machines to incorporate flexibility in their design concept. This research therefore designed and developed an automated sorting object of a conveyor belt. The developed automated sorting machine is able to incorporate flexibility and separate species of non-ferrous metal objects and at the same time move objects automatically to the basket as defined by the regulation of the Programmable Logic Controllers (PLC with a capacitive proximity sensor to detect a value range of objects. The result obtained shows that plastic, wood, and steel were sorted into their respective and correct position with an average, sorting, time of 9.903 s, 14.072 s and 18.648 s respectively. The proposed developed model of this research could be adopted at any institution or industries, whose practices are based on mechatronics engineering systems. This is to guide the industrial sector in sorting of object and teaching aid to institutions and hence produce the list of classified materials according to the enabled sorting program commands.

  7. AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA

    Directory of Open Access Journals (Sweden)

    N. Yastikli

    2017-11-01

    Full Text Available LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified

  8. Automatic 3d Building Model Generations with Airborne LiDAR Data

    Science.gov (United States)

    Yastikli, N.; Cetin, Z.

    2017-11-01

    LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D

  9. Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

    Science.gov (United States)

    Lajnef, Tarek; Chaibi, Sahbi; Ruby, Perrine; Aguera, Pierre-Emmanuel; Eichenlaub, Jean-Baptiste; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

    2015-07-30

    Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k-fold cross-validation. The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts' scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. The DSVM framework outperforms classification with more standard multi-class "one-against-all" SVM and linear-discriminant analysis. The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Raw Milk Hygiene at Local Markets and Automatic Milk Dispenser Machines

    Directory of Open Access Journals (Sweden)

    Gheorghe Şteţca

    2014-11-01

    Full Text Available In Romania, direct sales of raw milk to the final consumer is developed based on the local regulations. These are in accordance to European Regulation that must meet some quality requirements for the total number of germs, somatic cells, without antibiotics, coming from healthy animals who did not suffer from diseases that can be transmitted to humans through milk. Raw milk is sold in Romania in local markets and by automatic milk dispenser machines. Based on these regulations, a study regarding the quality and security to human health of raw milk was conducted on the commercialized milk in local markets and automatic milk dispensers. During May-June 2014 samples of raw milk were collected from Cluj-Napoca local markets and automatic milk dispensers. All samples were kept to refrigeration conditions until the moment of analyze which took place at the sampling day. The following parameters were taken into account: fat content, protein, casein, lactose, nonfat dry matter, pH, milk freezing point, added water, antibiotics residues, milk urea, number of germ cells and somatic cells. All obtained results were verified by the validated methods applied. Our research can be forward conducted in order to verify the hygiene and composition of milk from the whole dairy chain. 

  11. Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.

    Science.gov (United States)

    Tuyisenge, Viateur; Trebaul, Lena; Bhattacharjee, Manik; Chanteloup-Forêt, Blandine; Saubat-Guigui, Carole; Mîndruţă, Ioana; Rheims, Sylvain; Maillard, Louis; Kahane, Philippe; Taussig, Delphine; David, Olivier

    2018-03-01

    Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features. The features quantified signals' variance, spatial-temporal correlation and nonlinear properties. Because the number of bad channels is usually much lower than the number of good channels, we implemented an ensemble bagging classifier known to be optimal in terms of stability and predictive accuracy for datasets with imbalanced class distributions. This method was applied on stereo-electroencephalographic (SEEG) signals recording during low frequency stimulations performed in 206 patients from 5 clinical centers. We found that the classification accuracy was extremely good: It increased with the number of subjects used to train the classifier and reached a plateau at 99.77% for 110 subjects. The classification performance was thus not impacted by the multicentric nature of data. The proposed method to automatically detect bad channels demonstrated convincing results and can be envisaged to be used on larger datasets for automatic quality control of iEEG data. This is the first method proposed to classify bad channels in iEEG and should allow to improve the data selection when reviewing iEEG signals. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  12. Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning

    Science.gov (United States)

    Nguyen, Tan H.; Sridharan, Shamira; Macias, Virgilia; Kajdacsy-Balla, Andre; Melamed, Jonathan; Do, Minh N.; Popescu, Gabriel

    2017-03-01

    We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason grading of prostate specimens. The imaging system operates on the principle of interferometry and, as a result, reports on the nanoscale architecture of the unlabeled specimen. We use these data to train a random forest classifier to learn textural behaviors of prostate samples and classify each pixel in the image into different classes. Automatic diagnosis results were computed from the segmented regions. By combining morphological features with quantitative information from the glands and stroma, logistic regression was used to discriminate regions with Gleason grade 3 versus grade 4 cancer in prostatectomy tissue. The overall accuracy of this classification derived from a receiver operating curve was 82%, which is in the range of human error when interobserver variability is considered. We anticipate that our approach will provide a clinically objective and quantitative metric for Gleason grading, allowing us to corroborate results across instruments and laboratories and feed the computer algorithms for improved accuracy.

  13. Design and Assessment of a Machine Vision System for Automatic Vehicle Wheel Alignment

    Directory of Open Access Journals (Sweden)

    Rocco Furferi

    2013-05-01

    Full Text Available Abstract Wheel alignment, consisting of properly checking the wheel characteristic angles against vehicle manufacturers' specifications, is a crucial task in the automotive field since it prevents irregular tyre wear and affects vehicle handling and safety. In recent years, systems based on Machine Vision have been widely studied in order to automatically detect wheels' characteristic angles. In order to overcome the limitations of existing methodologies, due to measurement equipment being mounted onto the wheels, the present work deals with design and assessment of a 3D machine vision-based system for the contactless reconstruction of vehicle wheel geometry, with particular reference to characteristic planes. Such planes, properly referred to as a global coordinate system, are used for determining wheel angles. The effectiveness of the proposed method was tested against a set of measurements carried out using a commercial 3D scanner; the absolute average error in measuring toe and camber angles with the machine vision system resulted in full compatibility with the expected accuracy of wheel alignment systems.

  14. Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

    Directory of Open Access Journals (Sweden)

    Shang-Liang Chen

    2015-12-01

    Full Text Available Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as vibration meter, signal acquisition card, data processing platform, and machine control program. Meanwhile, based on the difference between the mechanical configuration and the desired characteristics, it is difficult for a vibration detection system to directly choose the commercially available kits. For this reason, it was also selected as an item for self-development research, along with the exploration of a significant parametric study that is sufficient to represent the machine characteristics and states. However, we also launched the development of functional parts of the system simultaneously. Finally, we entered the conditions and the parameters generated from both the states and the characteristics into the developed system to verify its feasibility.

  15. Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

    Science.gov (United States)

    Imbalzano, Giulio; Anelli, Andrea; Giofré, Daniele; Klees, Sinja; Behler, Jörg; Ceriotti, Michele

    2018-06-01

    Machine learning of atomic-scale properties is revolutionizing molecular modeling, making it possible to evaluate inter-atomic potentials with first-principles accuracy, at a fraction of the costs. The accuracy, speed, and reliability of machine learning potentials, however, depend strongly on the way atomic configurations are represented, i.e., the choice of descriptors used as input for the machine learning method. The raw Cartesian coordinates are typically transformed in "fingerprints," or "symmetry functions," that are designed to encode, in addition to the structure, important properties of the potential energy surface like its invariances with respect to rotation, translation, and permutation of like atoms. Here we discuss automatic protocols to select a number of fingerprints out of a large pool of candidates, based on the correlations that are intrinsic to the training data. This procedure can greatly simplify the construction of neural network potentials that strike the best balance between accuracy and computational efficiency and has the potential to accelerate by orders of magnitude the evaluation of Gaussian approximation potentials based on the smooth overlap of atomic positions kernel. We present applications to the construction of neural network potentials for water and for an Al-Mg-Si alloy and to the prediction of the formation energies of small organic molecules using Gaussian process regression.

  16. A relevance vector machine technique for the automatic detection of clustered microcalcifications (Honorable Mention Poster Award)

    Science.gov (United States)

    Wei, Liyang; Yang, Yongyi; Nishikawa, Robert M.

    2005-04-01

    Microcalcification (MC) clusters in mammograms can be important early signs of breast cancer in women. Accurate detection of MC clusters is an important but challenging problem. In this paper, we propose the use of a recently developed machine learning technique -- relevance vector machine (RVM) -- for automatic detection of MCs in digitized mammograms. RVM is based on Bayesian estimation theory, and as a feature it can yield a decision function that depends on only a very small number of so-called relevance vectors. We formulate MC detection as a supervised-learning problem, and use RVM to classify if an MC object is present or not at each location in a mammogram image. MC clusters are then identified by grouping the detected MC objects. The proposed method is tested using a database of 141 clinical mammograms, and compared with a support vector machine (SVM) classifier which we developed previously. The detection performance is evaluated using the free-response receiver operating characteristic (FROC) curves. It is demonstrated that the RVM classifier matches closely with the SVM classifier in detection performance, and does so with a much sparser kernel representation than the SVM classifier. Consequently, the RVM classifier greatly reduces the computational complexity, making it more suitable for real-time processing of MC clusters in mammograms.

  17. Criteria of the effectiveness of a liaison center for the machine building industry

    International Nuclear Information System (INIS)

    Hofer, P.; Wolff, H.; Franzen, D.

    1977-06-01

    The study aimed at working out a catalogue of criteria for the effective work of a liaison center for the machine building industry within the planned system of information and documentation of the German Government. By selecting this objective, the investigation methodically demanded a continuous change between theoretical analysis (study of literature, analytical deduction of the framework for a user-oriented information system) and empirical observation of information behaviour in the machine building industry (personal interviews with enterprises and important information sources for the machine building industries). An information system keyed to the information needs of the machine building industry must cover three main phases: Collection and documentation of information, selecting and procuring the needed information as well as encouraging and consulting the clients on the use of information. These different tasks complement one another, they correspond to different functions within enterprises: management, staff, and information function. Central point of a liaison center must be the task of selecting the required information (making information available, selling good information, analysing the information needs of clients), completed by fields of activity in documenting information (specifically for the machine building industry) and consulting clients on the use of information (agency for contacts, drawing the clients' attention to the complexity of machine building problems). A concrete catalogue of criteria for an effective conception of a liaison center for the machine building industry has been worked out. (orig.) [de

  18. Criteria of the effectiveness of a liaison center for the machine building industry

    International Nuclear Information System (INIS)

    Hofer, P.; Wolff, H.; Franzen, D.; Schlichting, J.; Weidig, I.

    1978-04-01

    The study aimed at working out a catalogue of criteria for the effective work of a liaison center for the machine building industry within the planned system of information and documentation of the German Government. By selecting this objective, the investigation methodically demanded a continuous change between theoretical analysis (study of literature, analytical deduction of the framework for a user-oriented information system) and empirical observation of information behaviour in the machine building industry (personal interviews with enterprises and important information sources for the machine building industries). An information system keyed to the information needs of the machine building industry must cover three main phases: Collection and documentation of information, selecting and procuring the needed information as well as encouraging and consulting the clients on the use of information. These different tasks complement one another, they correspond to different functions within enterprises: management, staff, and information function. Central point of a liaison center must be the task of selecting the required information (making information available, selling good information, analysing the information needs of clients), completed by fields of activity in documenting information (specifically for the machine building industry) and consulting clients on the use of information (agency for contacts, drawing the client's attention to the complexity of machine building problems). A concrete catalogue of criteria for an effective conception of a liaison center for the machine building industry has been worked out. (orig.) [de

  19. Automatic vetting of planet candidates from ground based surveys: Machine learning with NGTS

    Science.gov (United States)

    Armstrong, David J.; Günther, Maximilian N.; McCormac, James; Smith, Alexis M. S.; Bayliss, Daniel; Bouchy, François; Burleigh, Matthew R.; Casewell, Sarah; Eigmüller, Philipp; Gillen, Edward; Goad, Michael R.; Hodgkin, Simon T.; Jenkins, James S.; Louden, Tom; Metrailler, Lionel; Pollacco, Don; Poppenhaeger, Katja; Queloz, Didier; Raynard, Liam; Rauer, Heike; Udry, Stéphane; Walker, Simon R.; Watson, Christopher A.; West, Richard G.; Wheatley, Peter J.

    2018-05-01

    State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary candidates, achieving an AUC score of 97.6% in ranking 12368 injected planets against 27496 false positives in the NGTS data. We build on past examples by using injected transit signals to form a training set, a necessary development for applying similar methods to upcoming surveys. We also make the autovet code used to implement the algorithm publicly accessible. autovet is designed to perform machine learned vetting of planetary candidates, and can utilise a variety of methods. The apparent robustness of machine learning techniques, whether on space-based or the qualitatively different ground-based data, highlights their importance to future surveys such as TESS and PLATO and the need to better understand their advantages and pitfalls in an exoplanetary context.

  20. Automatic assessment of average diaphragm motion trajectory from 4DCT images through machine learning.

    Science.gov (United States)

    Li, Guang; Wei, Jie; Huang, Hailiang; Gaebler, Carl Philipp; Yuan, Amy; Deasy, Joseph O

    2015-12-01

    To automatically estimate average diaphragm motion trajectory (ADMT) based on four-dimensional computed tomography (4DCT), facilitating clinical assessment of respiratory motion and motion variation and retrospective motion study. We have developed an effective motion extraction approach and a machine-learning-based algorithm to estimate the ADMT. Eleven patients with 22 sets of 4DCT images (4DCT1 at simulation and 4DCT2 at treatment) were studied. After automatically segmenting the lungs, the differential volume-per-slice (dVPS) curves of the left and right lungs were calculated as a function of slice number for each phase with respective to the full-exhalation. After 5-slice moving average was performed, the discrete cosine transform (DCT) was applied to analyze the dVPS curves in frequency domain. The dimensionality of the spectrum data was reduced by using several lowest frequency coefficients ( f v ) to account for most of the spectrum energy (Σ f v 2 ). Multiple linear regression (MLR) method was then applied to determine the weights of these frequencies by fitting the ground truth-the measured ADMT, which are represented by three pivot points of the diaphragm on each side. The 'leave-one-out' cross validation method was employed to analyze the statistical performance of the prediction results in three image sets: 4DCT1, 4DCT2, and 4DCT1 + 4DCT2. Seven lowest frequencies in DCT domain were found to be sufficient to approximate the patient dVPS curves ( R = 91%-96% in MLR fitting). The mean error in the predicted ADMT using leave-one-out method was 0.3 ± 1.9 mm for the left-side diaphragm and 0.0 ± 1.4 mm for the right-side diaphragm. The prediction error is lower in 4DCT2 than 4DCT1, and is the lowest in 4DCT1 and 4DCT2 combined. This frequency-analysis-based machine learning technique was employed to predict the ADMT automatically with an acceptable error (0.2 ± 1.6 mm). This volumetric approach is not affected by the presence of the lung tumors

  1. SILOS, Reused Machine-Buildings: A Proposal for Its Transformation

    Science.gov (United States)

    Garrido-Cifuentes, María; Santiago-Zaragoza, Juan Manuel; Lafuente-Bolívar, Francisco Javier

    2017-10-01

    Second half of the 20th century: The Spanish rural landscape changes with the imposing profile of Silos. In the urban edge, next to the railroad, they are risen competing in height with church steeples. Today they are inseparable elements of the image of many peoples of cereal geography of any region of Spain. They are consequence of the autarkic economy of that time (storage of grain and state control over distribution and price) Silos were the answer given by the engineering efficiency and economy of means: A type of store operated by screw-conveyor moved with electricity, transport grain to fill high slender square plant cells. Hydraulic push offset between cells that form a matrix-walled plates constructed of thin sheets of brick or concrete block, armed only horizontally. And huge vertical loads carried by thick foundation reinforced concrete pillars. The political regime change and the energy crisis of the late seventies caused these magnificent building-machines stopped being used. Its radical specialization led them to death. After years of neglect and transfer of ownership between administrations, a consciousness has emerged in Spain (National Plan of Industrial Heritage, 2000) that has prevented its demolition, and recognize the values they bring to the landscape and structural-construction of its own, as beautiful works of Engineering which are worth cataloguing / protection. Hence this proposal tries to intervene these giants through new uses, transforming, allowing their conservation. This process investigates various structural types and implements strict standards of construction resolved with efficient construction solutions. The result is returned to society by publishing their work, while stressing heritage values, demonstrates the new strength of these local systems.

  2. Automatic Energy Control And Monitoring System For Building

    Directory of Open Access Journals (Sweden)

    Hnin Nu Thaung

    2015-08-01

    Full Text Available The use of smart home technology in the home or building offers significant potential for energy savings. In this paper an energy management system based on wireless sensor networks. The proposed system is composed of two main components a wireless sensor network and monitoring terminal. Wireless sensors are used for sensing and transmitting electricity data and remote monitoring and control of appliances are provided to users through computer. The system enables users to save energy by monitoring and controlling appliances through terminal. This paper gives an overview of sensor technology and wireless networks in the development of an intelligent energy management system for buildings. This technology has ample potential to change the way live and work. ZigBee is used as a communication medium in building intelligent energy management system in this paper. From the prototype setup it is shown that ZigBee is a suitable technology to be adopted as the communication infrastructure in energy management system for buildings .The proposed system can be installed and maintained in residential environments with ease.

  3. Two years of experience with an automatic milking system: 1. Time on machine and successful attachments

    Directory of Open Access Journals (Sweden)

    M. Speroni

    2011-03-01

    Full Text Available The installation of an automatic milking system (AMS is not simply the replacement of an old traditional milking parlour with a new milking machine, but it requires a deeply modification of herd management (Spahr et al., 1997. Robotic milking is now considered fairly reliable and friendly and more than 1100 commercial farmers have installed at least one milking unit (De Koning et al., 2002. A lot of studies have been carried out on the interactions between milking robot, cows and farmer, but most of them referred to farm in the Northern Europe. On December 2000, an AMS (Voluntary Milking System, VMSTM, De Laval was installed at the Experimental Farm of Istituto Sperimentale per la Zootecnia in Cremona (Italy......

  4. Procedural and developmental aspects of a multielement automatic radiochemical machine, applied to neutron irradiated biomedical samples

    International Nuclear Information System (INIS)

    Iyengar, G.V.

    1976-06-01

    This report is intended to serve as a practical guide, elaborately describing the working details and some developmental work connected with an automatic multielement radiochemical machine based on thermal neutron activation analysis using ion exchange and partition chromatography. Some of the practical aspects and personal observations after much experience with this versatile multielement method, applied to investigate the elemental composition of different biomedical matrices, are summarized. Standard reference materials are analyzed, and the data are presented with a set of gamma-spectra obtained before and after chemical separation into convenient groups suitable for gamma spectroscopy. The samples analyzed included various human and animal tissues, body fluids, IAEA biological standard reference materials, and samples from the WHO/IAEA project on 'Trace elements in relation to cardiovascular diseases'. Simplified modifications of the radiochemical processing, suitable for fast and routine analysis of clinical samples have also been discussed. (orig.) [de

  5. Semi-Automatic Modelling of Building FAÇADES with Shape Grammars Using Historic Building Information Modelling

    Science.gov (United States)

    Dore, C.; Murphy, M.

    2013-02-01

    This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.

  6. A support vector machine approach to the automatic identification of fluorescence spectra emitted by biological agents

    Science.gov (United States)

    Gelfusa, M.; Murari, A.; Lungaroni, M.; Malizia, A.; Parracino, S.; Peluso, E.; Cenciarelli, O.; Carestia, M.; Pizzoferrato, R.; Vega, J.; Gaudio, P.

    2016-10-01

    Two of the major new concerns of modern societies are biosecurity and biosafety. Several biological agents (BAs) such as toxins, bacteria, viruses, fungi and parasites are able to cause damage to living systems either humans, animals or plants. Optical techniques, in particular LIght Detection And Ranging (LIDAR), based on the transmission of laser pulses and analysis of the return signals, can be successfully applied to monitoring the release of biological agents into the atmosphere. It is well known that most of biological agents tend to emit specific fluorescence spectra, which in principle allow their detection and identification, if excited by light of the appropriate wavelength. For these reasons, the detection of the UVLight Induced Fluorescence (UV-LIF) emitted by BAs is particularly promising. On the other hand, the stand-off detection of BAs poses a series of challenging issues; one of the most severe is the automatic discrimination between various agents which emit very similar fluorescence spectra. In this paper, a new data analysis method, based on a combination of advanced filtering techniques and Support Vector Machines, is described. The proposed approach covers all the aspects of the data analysis process, from filtering and denoising to automatic recognition of the agents. A systematic series of numerical tests has been performed to assess the potential and limits of the proposed methodology. The first investigations of experimental data have already given very encouraging results.

  7. Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

    Science.gov (United States)

    Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

    2017-05-01

    Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

  8. Alan Turing's Automatic Computing Engine The Master Codebreaker's Struggle to build the Modern Computer

    CERN Document Server

    Copeland, B Jack

    2005-01-01

    The mathematical genius Alan Turing (1912-1954) was one of the greatest scientists and thinkers of the 20th century. Now well known for his crucial wartime role in breaking the ENIGMA code, he was the first to conceive of the fundamental principle of the modern computer-the idea of controlling a computing machine's operations by means of a program of coded instructions, stored in the machine's 'memory'. In 1945 Turing drew up his revolutionary design for an electronic computingmachine-his Automatic Computing Engine ('ACE'). A pilot model of the ACE ran its first program in 1950 and the product

  9. Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

    Science.gov (United States)

    Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M

    2016-01-01

    Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as

  10. Automatic Test Pattern Generator for Fuzzing Based on Finite State Machine

    Directory of Open Access Journals (Sweden)

    Ming-Hung Wang

    2017-01-01

    Full Text Available With the rapid development of the Internet, several emerging technologies are adopted to construct fancy, interactive, and user-friendly websites. Among these technologies, HTML5 is a popular one and is widely used in establishing modern sites. However, the security issues in the new web technologies are also raised and are worthy of investigation. For vulnerability investigation, many previous studies used fuzzing and focused on generation-based approaches to produce test cases for fuzzing; however, these methods require a significant amount of knowledge and mental efforts to develop test patterns for generating test cases. To decrease the entry barrier of conducting fuzzing, in this study, we propose a test pattern generation algorithm based on the concept of finite state machines. We apply graph analysis techniques to extract paths from finite state machines and use these paths to construct test patterns automatically. According to the proposal, fuzzing can be completed through inputting a regular expression corresponding to the test target. To evaluate the performance of our proposal, we conduct an experiment in identifying vulnerabilities of the input attributes in HTML5. According to the results, our approach is not only efficient but also effective for identifying weak validators in HTML5.

  11. CERN awards "Gold CMS Award" to Savyolovsk machine-building Plant

    CERN Multimedia

    2007-01-01

    "The contribution pf Savyolovsk machine-building Plant OJSC into the international program to develop an CMS unit was recognized by the European Nuclear Research Center with "Gold Prize"for 2007. (1 small paragraph)

  12. Automatic generation of medium-detailed 3D models of buildings based on CAD data

    NARCIS (Netherlands)

    Dominguez-Martin, B.; Van Oosterom, P.; Feito-Higueruela, F.R.; Garcia-Fernandez, A.L.; Ogayar-Anguita, C.J.

    2015-01-01

    We present the preliminary results of a work in progress which aims to obtain a software system able to automatically generate a set of diverse 3D building models with a medium level of detail, that is, more detailed that a mere parallelepiped, but not as detailed as a complete geometric

  13. Applying machine learning to build a website interface adaptation system

    OpenAIRE

    MATESHUK EGOR; CHERNYSHEV ALEXANDER

    2015-01-01

    In this article we present the architecture and model of a website interface optimization system. We describe how we use clustering and genetic algorithms to automatically select a website interface with the highest conversion from website visitor to website user. In particular, we describe an algorithm for streamed clustering, which allows for real-time analysis of high traffic website users.

  14. AUTOMATIC LUNG NODULE DETECTION BASED ON STATISTICAL REGION MERGING AND SUPPORT VECTOR MACHINES

    Directory of Open Access Journals (Sweden)

    Elaheh Aghabalaei Khordehchi

    2017-06-01

    Full Text Available Lung cancer is one of the most common diseases in the world that can be treated if the lung nodules are detected in their early stages of growth. This study develops a new framework for computer-aided detection of pulmonary nodules thorough a fully-automatic analysis of Computed Tomography (CT images. In the present work, the multi-layer CT data is fed into a pre-processing step that exploits an adaptive diffusion-based smoothing algorithm in which the parameters are automatically tuned using an adaptation technique. After multiple levels of morphological filtering, the Regions of Interest (ROIs are extracted from the smoothed images. The Statistical Region Merging (SRM algorithm is applied to the ROIs in order to segment each layer of the CT data. Extracted segments in consecutive layers are then analyzed in such a way that if they intersect at more than a predefined number of pixels, they are labeled with a similar index. The boundaries of the segments in adjacent layers which have the same indices are then connected together to form three-dimensional objects as the nodule candidates. After extracting four spectral, one morphological, and one textural feature from all candidates, they are finally classified into nodules and non-nodules using the Support Vector Machine (SVM classifier. The proposed framework has been applied to two sets of lung CT images and its performance has been compared to that of nine other competing state-of-the-art methods. The considerable efficiency of the proposed approach has been proved quantitatively and validated by clinical experts as well.

  15. Automatically annotating topics in transcripts of patient-provider interactions via machine learning.

    Science.gov (United States)

    Wallace, Byron C; Laws, M Barton; Small, Kevin; Wilson, Ira B; Trikalinos, Thomas A

    2014-05-01

    Annotated patient-provider encounters can provide important insights into clinical communication, ultimately suggesting how it might be improved to effect better health outcomes. But annotating outpatient transcripts with Roter or General Medical Interaction Analysis System (GMIAS) codes is expensive, limiting the scope of such analyses. We propose automatically annotating transcripts of patient-provider interactions with topic codes via machine learning. We use a conditional random field (CRF) to model utterance topic probabilities. The model accounts for the sequential structure of conversations and the words comprising utterances. We assess predictive performance via 10-fold cross-validation over GMIAS-annotated transcripts of 360 outpatient visits (>230,000 utterances). We then use automated in place of manual annotations to reproduce an analysis of 116 additional visits from a randomized trial that used GMIAS to assess the efficacy of an intervention aimed at improving communication around antiretroviral (ARV) adherence. With respect to 6 topic codes, the CRF achieved a mean pairwise kappa compared with human annotators of 0.49 (range: 0.47-0.53) and a mean overall accuracy of 0.64 (range: 0.62-0.66). With respect to the RCT reanalysis, results using automated annotations agreed with those obtained using manual ones. According to the manual annotations, the median number of ARV-related utterances without and with the intervention was 49.5 versus 76, respectively (paired sign test P = 0.07). When automated annotations were used, the respective numbers were 39 versus 55 (P = 0.04). While moderately accurate, the predicted annotations are far from perfect. Conversational topics are intermediate outcomes, and their utility is still being researched. This foray into automated topic inference suggests that machine learning methods can classify utterances comprising patient-provider interactions into clinically relevant topics with reasonable accuracy.

  16. German Machine Building: A New Benchmark before World War I

    NARCIS (Netherlands)

    Fremdling, Rainer

    2009-01-01

    The figure most commonly used as benchmark for the output of machinery before WW I is based on an estimate by the Association of German Machinery Producers (VDMA). It estimated that all German firms in total had sold machines worth 2800 million Marks in 1913.Using a recently detected detailed

  17. THE FORMATION OF THE COMPETITIVENESS OF THE ENTERPRISES OF MACHINE-BUILDING COMPLEX OF UKRAINE

    Directory of Open Access Journals (Sweden)

    Oksana Zbyrannyk

    2016-11-01

    Full Text Available The purpose is to analyse the existing approaches to determine the value of the production of innovative products and innovation in enterprises of machine-building complex of Ukraine in order to improve their level of competitiveness. Methodology. Statistical analysis and generalization of scientific approaches to the formation of the competitiveness of machine-building enterprises. Results of the of the analyzed approaches allowed to identify the cause of the imperfection of innovation policy in engineering. According to the research, the number of machine-building enterprises engaged in innovation activity, constantly shrinks; the share of innovative products in the total is only 3.5-4%, and the volume of imports of high-tech products exceeding the size of own production; the level of knowledge-intensive industrial production is only 0.3%. All this slows down the process of creating competitive products and as a result, the failure to provide highly own products to other industries, take a niche world of mechanical engineering. Practical implications. Ensure accelerated economic growth of the country as the defining condition for implementation of the European integration aspirations of Ukraine in the short term requires the intensification of innovative activity of the machine-building enterprises. The current state of innovation activity of enterprises in Ukraine is characterized by a number of negative factors: the internal environment of the majority of machine-building enterprises does not correspond to the market conditions of managing: high energy productions, the growth of the degree of wear and tear of fixed assets and reduce investment to update them, the lack of introduction of advanced production and resource-saving technologies, reducing innovation activity due to lack of financial resources significantly affect the level of the competitive machine-building enterprises. Value/ originality systematic approaches to determining the

  18. Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

    Directory of Open Access Journals (Sweden)

    Jun Yi Wang

    Full Text Available Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation to 0.978 (for SegAdapter-corrected segmentation for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large

  19. Automatic generation of smart earthquake-resistant building system: Hybrid system of base-isolation and building-connection

    Directory of Open Access Journals (Sweden)

    M. Kasagi

    2016-02-01

    Full Text Available A base-isolated building may sometimes exhibit an undesirable large response to a long-duration, long-period earthquake ground motion and a connected building system without base-isolation may show a large response to a near-fault (rather high-frequency earthquake ground motion. To overcome both deficiencies, a new hybrid control system of base-isolation and building-connection is proposed and investigated. In this new hybrid building system, a base-isolated building is connected to a stiffer free wall with oil dampers. It has been demonstrated in a preliminary research that the proposed hybrid system is effective both for near-fault (rather high-frequency and long-duration, long-period earthquake ground motions and has sufficient redundancy and robustness for a broad range of earthquake ground motions.An automatic generation algorithm of this kind of smart structures of base-isolation and building-connection hybrid systems is presented in this paper. It is shown that, while the proposed algorithm does not work well in a building without the connecting-damper system, it works well in the proposed smart hybrid system with the connecting damper system.

  20. Automatic Assignment of Methyl-NMR Spectra of Supramolecular Machines Using Graph Theory.

    Science.gov (United States)

    Pritišanac, Iva; Degiacomi, Matteo T; Alderson, T Reid; Carneiro, Marta G; Ab, Eiso; Siegal, Gregg; Baldwin, Andrew J

    2017-07-19

    Methyl groups are powerful probes for the analysis of structure, dynamics and function of supramolecular assemblies, using both solution- and solid-state NMR. Widespread application of the methodology has been limited due to the challenges associated with assigning spectral resonances to specific locations within a biomolecule. Here, we present Methyl Assignment by Graph Matching (MAGMA), for the automatic assignment of methyl resonances. A graph matching protocol examines all possibilities for each resonance in order to determine an exact assignment that includes a complete description of any ambiguity. MAGMA gives 100% accuracy in confident assignments when tested against both synthetic data, and 9 cross-validated examples using both solution- and solid-state NMR data. We show that this remarkable accuracy enables a user to distinguish between alternative protein structures. In a drug discovery application on HSP90, we show the method can rapidly and efficiently distinguish between possible ligand binding modes. By providing an exact and robust solution to methyl resonance assignment, MAGMA can facilitate significantly accelerated studies of supramolecular machines using methyl-based NMR spectroscopy.

  1. Automatic detection of ischemic stroke based on scaling exponent electroencephalogram using extreme learning machine

    Science.gov (United States)

    Adhi, H. A.; Wijaya, S. K.; Prawito; Badri, C.; Rezal, M.

    2017-03-01

    Stroke is one of cerebrovascular diseases caused by the obstruction of blood flow to the brain. Stroke becomes the leading cause of death in Indonesia and the second in the world. Stroke also causes of the disability. Ischemic stroke accounts for most of all stroke cases. Obstruction of blood flow can cause tissue damage which results the electrical changes in the brain that can be observed through the electroencephalogram (EEG). In this study, we presented the results of automatic detection of ischemic stroke and normal subjects based on the scaling exponent EEG obtained through detrended fluctuation analysis (DFA) using extreme learning machine (ELM) as the classifier. The signal processing was performed with 18 channels of EEG in the range of 0-30 Hz. Scaling exponents of the subjects were used as the input for ELM to classify the ischemic stroke. The performance of detection was observed by the value of accuracy, sensitivity and specificity. The result showed, performance of the proposed method to classify the ischemic stroke was 84 % for accuracy, 82 % for sensitivity and 87 % for specificity with 120 hidden neurons and sine as the activation function of ELM.

  2. Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

    International Nuclear Information System (INIS)

    Chen, Yixing; Hong, Tianzhen; Piette, Mary Ann

    2017-01-01

    Highlights: •Developed methods and used data models to integrate city’s public building records. •Shading from neighborhood buildings strongly influences urban building performance. •A case study demonstrated the workflow, simulation and analysis of building retrofits. •CityBES retrofit analysis feature provides actionable information for decision making. •Discussed significance and challenges of urban building energy modeling. -- Abstract: Buildings in cities consume 30–70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23–38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Francisco due to the city’s mild

  3. Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

    Science.gov (United States)

    Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

    2018-04-30

    Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Trends in the structures development of the regional machine-building complex

    Directory of Open Access Journals (Sweden)

    Ershova I.V.

    2017-01-01

    Full Text Available In the process of market reforms of the Russian machine-building complex several distinct periods can be revealed. In this article the authors define periods of mass disintegration and spontaneous integration (since the beginning of the reforms until the financial crisis of 1996, post-crisis stabilization, directional specialization (2000-2008 and evolutionary development (since 2010. The economic consequences of the enterprises mergers and divisions are shown on the example of machine-building enterprises of the Middle Urals. The aim of this study is to substantiate the methodical approach to the selection of the optimal organizational structure for the machine-building business. The necessity of taking into account the extent of the personnel diversification and the production volume has been revealed for the optimum organizational structure determination in the machine-building associations. The authors have analyzed sales profitability of the 2745 machine-building enterprises, depending on the production scale and industry sector. The factors affecting the development of cooperative ties and outsourcing have been defined. The authors have made a conclusion that it is necessary to form technological chains as a new kind of business associations.

  5. Another Method of Building 2D Entropy to Realize Automatic Segmentation

    International Nuclear Information System (INIS)

    Zhang, Y F; Zhang, Y

    2006-01-01

    2D entropy formed during the process of building 2D histogram can realize automatic segmentation. Traditional method utilizes central pixel grey value and the others or all of pixels grey mean value in 4-neighbor to build 2D histogram. In fact, the change of the greyscale value between two ''invariable position vectors'' cannot represent the total characteristics among neighbour pixels very well. A new method is proposed which makes use of minimum grey value in the 4-neighbor and of maximum grey value in the 3x3 neighbour except pixels of the 4-neighbor. New method and traditional one are used in contrast to realize image automatic segmentation. The experimental results of the classical image prove the new method is effective

  6. Automatic Generation of Structural Building Descriptions from 3D Point Cloud Scans

    DEFF Research Database (Denmark)

    Ochmann, Sebastian; Vock, Richard; Wessel, Raoul

    2013-01-01

    We present a new method for automatic semantic structuring of 3D point clouds representing buildings. In contrast to existing approaches which either target the outside appearance like the facade structure or rather low-level geometric structures, we focus on the building’s interior using indoor...... scans to derive high-level architectural entities like rooms and doors. Starting with a registered 3D point cloud, we probabilistically model the affiliation of each measured point to a certain room in the building. We solve the resulting clustering problem using an iterative algorithm that relies...

  7. 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-...

  8. USAGE OF CONSTRUCTION-ORIENTED SOFTWARE SCAD FOR ANALYSIS OF WORK OF MACHINE-BUILDING STRUCTURES

    Directory of Open Access Journals (Sweden)

    D. О. Bannikov

    2018-02-01

    Full Text Available Purpose. In the case of analysis of work of the machine-building structures, the direct usage of construction-oriented software developments is impossible, since ideology and methodology for solving various tasks in construction and machine-building are different. Therefore, in the conducting of practical calculations, there is a need for a certain adjustment of the approaches put in the program complexes and their adaptation to the engineering industry. The presentation of the author's experience of the construction-oriented software SCAD usage for Windows for analyzing the work of various machine-building structures, their components and assemblies is the immediate purpose of the publication. Methodology. During a long period of time the author was engaged in analyzing the work of building, mainly thin-walled, steel structures using the Finite Element Method based on the SCAD for Windows software package. At the same time, a considerable number of machine-building structures were considered, including railroad rolling stock units. Most of these tasks grew into a scientific and research problem that needed to be thoroughly researched and analyzed before giving design recommendations. Findings. The publication presents more than a dozen different tasks, typical for the machine-building industry, which the author had to deal with. Static and quasi-static problems, the problem of motion in time, the contact problem, the problem of the cracks deve-lopment, the physical and geometric non-linearity are among them. Accordingly, for each of these problems the main challenges, features and practical techniques developed during the work are presented, as well as the constructed finite element models are presented as an illustration. Originality. The experience of construction-oriented software product usage on the basis of the Finite Element Method for analyzing of the work of machine-building structures is generalized. A number of practical methods and

  9. Study on granulated material automatic weighing machine%颗粒状物料自动称量机研究

    Institute of Scientific and Technical Information of China (English)

    贾丽娜; 张辉; 陈文庆

    2012-01-01

    In order to solve the problems of the granulated material automatic weighing, according to the characteristics of granulated material, the granulated material automatic weighing machine based on PLC was established. A method was presented to improve the automatic weighing machine speed and accuracy effectively, that used frequency conversion motor driving synchronous belt rough charging and vibrating feeder fine dosing. The weighing experiments were evaluated on the granulated material automatic weighing machine, the several kinds of drug were tested. The experimental results show that the equipment has high weighing accuracy and weighing speed, the characteristics of the operation is stable and reliable, and the equipment can satisfy different granulated drug automatic weighing requirements.%为了解决颗粒状物料自动称量的问题,根据颗粒状物料特性,研制了一种基于PLC的颗粒状物料自动称量机,该系统采用变频电机驱动同步带进行粗加料和振动给料机精加料结合的方式,有效提高了自动称量机的速度和精度.对不同种类的颗粒状药品进行了称量试验,试验结果表明,该称量设备具有精度高、称量速度快、运行稳定可靠的特点,且可以满足不同颗粒药品的自动称量要求.

  10. Building Better Ecological Machines: Complexity Theory and Alternative Economic Models

    Directory of Open Access Journals (Sweden)

    Jess Bier

    2016-12-01

    Full Text Available Computer models of the economy are regularly used to predict economic phenomena and set financial policy. However, the conventional macroeconomic models are currently being reimagined after they failed to foresee the current economic crisis, the outlines of which began to be understood only in 2007-2008. In this article we analyze the most prominent of this reimagining: Agent-Based models (ABMs. ABMs are an influential alternative to standard economic models, and they are one focus of complexity theory, a discipline that is a more open successor to the conventional chaos and fractal modeling of the 1990s. The modelers who create ABMs claim that their models depict markets as ecologies, and that they are more responsive than conventional models that depict markets as machines. We challenge this presentation, arguing instead that recent modeling efforts amount to the creation of models as ecological machines. Our paper aims to contribute to an understanding of the organizing metaphors of macroeconomic models, which we argue is relevant conceptually and politically, e.g., when models are used for regulatory purposes.

  11. From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings

    Directory of Open Access Journals (Sweden)

    Hélène Macher

    2017-10-01

    Full Text Available The creation of as-built Building Information Models requires the acquisition of the as-is state of existing buildings. Laser scanners are widely used to achieve this goal since they permit to collect information about object geometry in form of point clouds and provide a large amount of accurate data in a very fast way and with a high level of details. Unfortunately, the scan-to-BIM (Building Information Model process remains currently largely a manual process which is time consuming and error-prone. In this paper, a semi-automatic approach is presented for the 3D reconstruction of indoors of existing buildings from point clouds. Several segmentations are performed so that point clouds corresponding to grounds, ceilings and walls are extracted. Based on these point clouds, walls and slabs of buildings are reconstructed and described in the IFC format in order to be integrated into BIM software. The assessment of the approach is proposed thanks to two datasets. The evaluation items are the degree of automation, the transferability of the approach and the geometric quality of results of the 3D reconstruction. Additionally, quality indexes are introduced to inspect the results in order to be able to detect potential errors of reconstruction.

  12. Discrete data processing from a scintillation sensor for exposure automatic machine in medical radiography

    International Nuclear Information System (INIS)

    Karadimov, D.; Petukhov, N.; Dimitrova, S.; Vasilev, M.

    1983-01-01

    An exposure automatic machine with a thin plastic scintillator plate collimated by light guide with a photoconverter is described. Due to the physical processes nature in the scintillator accounted by the photomultiplier there is a possibility of a radiation analysis as well as of a digital processing of the results. Two alternative devices are shown. In the first of them the photomultiplier output signal is fed to a pulse-height selector at the output of which standard logical level pulses are obtained. These pulses are fed to a data register and then to a digital comparator where they are compared with a preset quantity selected depending on X-ray film sensitivity and foil combinations as well as on the desired film darkening. The ionizing radiation interruption is controlled by a switch unit. The detector spectral sensitivity correction is accomplished changing the photomultiplier supply voltage. In the second alternative a noise and ionizing radiation discriminator is used where a pulse-height selection according to the radiant energy is carried out. A digital comparator and a switching circuit control the ionizing radiation. By a second switching circuit the spectral distributed pulses from the discriminator are fed to a spectral analyser controlling dinamically the digital comparator compensating for the ionizing radiation spectral response influence. The second alternative advantage is that it allows for the radiation parameters control both in radiograph mode and X-ray examination mode. Due to the system fast-acting the device can be used to measure very short exposures as well as in serial examinations

  13. A multi-label learning based kernel automatic recommendation method for support vector machine.

    Science.gov (United States)

    Zhang, Xueying; Song, Qinbao

    2015-01-01

    Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

  14. Building machines that learn and think like people

    OpenAIRE

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

    2016-01-01

    Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitiv...

  15. Building a Mechanism for the Function of an Innovation-Oriented Machine-Building Enterprise in Operating the Development

    Directory of Open Access Journals (Sweden)

    Boiarynova Кateryna О.

    2017-07-01

    Full Text Available The article is aimed at developing and substantiating a mechanism for the function of an innovation-oriented machine-building enterprise in operating the development in order to increase effectuality in the space of ecosystem of operation and to satisfy the economic interests of development. The article proposes a mechanism for the function of an innovation-oriented machine-building enterprise in operating the development, its structure and building based on a business model; operating the development through responsibility centers; functional transformation of economic interest of actors in the ecosystem of function into the economic interest of enterprise; use of economic-institutional regulators and management technologies. Implementation of the mechanism would ensure the value of enterprise, the ability to manage development with the prolonged satisfaction of the joint economic interest, the ability to operate the economic interest of actors in the ecosystem, and maintenance the development mode in the operating process. Prospect for further research will be development of technologies for implementation of the proposed mechanism in the machine-building enterprises.

  16. SEMI-AUTOMATIC CO-REGISTRATION OF PHOTOGRAMMETRIC AND LIDAR DATA USING BUILDINGS

    Directory of Open Access Journals (Sweden)

    C. Armenakis

    2012-07-01

    Full Text Available In this work, the co-registration steps between LiDAR and photogrammetric DSM 3Ddata are analyzed and a solution based on automated plane matching is proposed and implemented. For a robust 3D geometric transformation both planes and points are used. Initially planes are chosen as the co-registration primitives. To confine the search space for the plane matching a sequential automatic building matching is performed first. For matching buildings from the LiDAR and the photogrammetric data, a similarity objective function is formed based on the roof height difference (RHD, the 3D histogram of the building attributes, and the building boundary area of a building. A region growing algorithm based on a Triangulated Irregular Network (TIN is implemented to extract planes from both datasets. Next, an automatic successive process for identifying and matching corresponding planes from the two datasets has been developed and implemented. It is based on the building boundary region and determines plane pairs through a robust matching process thus eliminating outlier pairs. The selected correct plane pairs are the input data for the geometric transformation process. The 3D conformal transformation method in conjunction with the attitude quaternion is applied to obtain the transformation parameters using the normal vectors of the corresponding plane pairs. Following the mapping of one dataset onto the coordinate system of the other, the Iterative Closest Point (ICP algorithm is then applied, using the corresponding building point clouds to further refine the transformation solution. The results indicate that the combination of planes and points improve the co-registration outcomes.

  17. Electron-cloud build-up in hadron machines

    International Nuclear Information System (INIS)

    Furman, M.A.

    2004-01-01

    The first observations of electron-proton coupling effect for coasting beams and for long-bunch beams were made at the earliest proton storage rings at the Budker Institute of Nuclear Physics (BINP) in the mid-60's [1]. The effect was mainly a form of the two-stream instability. This phenomenon reappeared at the CERN ISR in the early 70's, where it was accompanied by an intense vacuum pressure rise. When the ISR was operated in bunched-beam mode while testing aluminum vacuum chambers, a resonant effect was observed in which the electron traversal time across the chamber was comparable to the bunch spacing [2]. This effect (''beam-induced multipacting''), being resonant in nature, is a dramatic manifestation of an electron cloud sharing the vacuum chamber with a positively-charged beam. An electron-cloud-induced instability has been observed since the mid-80's at the PSR (LANL) [3]; in this case, there is a strong transverse instability accompanied by fast beam losses when the beam current exceeds a certain threshold. The effect was observed for the first time for a positron beam in the early 90's at the Photon Factory (PF) at KEK, where the most prominent manifestation was a coupled-bunch instability that was absent when the machine was operated with an electron beam under otherwise identical conditions [4]. Since then, with the advent of ever more intense positron and hadron beams, and the development and deployment of specialized electron detectors [5-9], the effect has been observed directly or indirectly, and sometimes studied systematically, at most lepton and hadron machines when operated with sufficiently intense beams. The effect is expected in various forms and to various degrees in accelerators under design or construction. The electron-cloud effect (ECE) has been the subject of various meetings [10-15]. Two excellent reviews, covering the phenomenology, measurements, simulations and historical development, have been recently given by Frank Zimmermann [16

  18. Issues of Application of Machine Learning Models for Virtual and Real-Life Buildings

    Directory of Open Access Journals (Sweden)

    Young Min Kim

    2016-06-01

    Full Text Available The current Building Energy Performance Simulation (BEPS tools are based on first principles. For the correct use of BEPS tools, simulationists should have an in-depth understanding of building physics, numerical methods, control logics of building systems, etc. However, it takes significant time and effort to develop a first principles-based simulation model for existing buildings—mainly due to the laborious process of data gathering, uncertain inputs, model calibration, etc. Rather than resorting to an expert’s effort, a data-driven approach (so-called “inverse” approach has received growing attention for the simulation of existing buildings. This paper reports a cross-comparison of three popular machine learning models (Artificial Neural Network (ANN, Support Vector Machine (SVM, and Gaussian Process (GP for predicting a chiller’s energy consumption in a virtual and a real-life building. The predictions based on the three models are sufficiently accurate compared to the virtual and real measurements. This paper addresses the following issues for the successful development of machine learning models: reproducibility, selection of inputs, training period, outlying data obtained from the building energy management system (BEMS, and validation of the models. From the result of this comparative study, it was found that SVM has a disadvantage in computation time compared to ANN and GP. GP is the most sensitive to a training period among the three models.

  19. A topological insight into restricted Boltzmann machines

    NARCIS (Netherlands)

    Mocanu, D.C.; Mocanu, E.; Nguyen, H.P.; Gibescu, M.; Liotta, A.

    Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep artificial neural networks for automatic features extraction, unsupervised weights initialization, but also as density estimators. Thus, their generative and discriminative

  20. Possibilities of radiation technique application in machine-building industry of Bulgaria

    International Nuclear Information System (INIS)

    Petrov, A.; Avramov, D.; Kostov, St.

    1979-01-01

    In last ten years, in development of machine-building industry, tendency has been outlined for creation of machines and constructions having minimum weight and elevated reliability from one side due to improvement of design and technology of production and from the other side due to application of materials with improved parameters. Solution of these problems is closely connected with application of the radiation methods. State-of-art of the radiation technology application in the machine-building industry is analyzed and mainly for investigation of wear resistance of friction machineparts. Use of spatial radioactive labelling in investigation of materials and application of radiation methods for optimization of technological processes in metallurgy, foundry and so on is considered. Estimation is give of perspectives of further growth of introduction of radiation methods in Bulgaria [ru

  1. An Automatic Building Extraction and Regularisation Technique Using LiDAR Point Cloud Data and Orthoimage

    Directory of Open Access Journals (Sweden)

    Syed Ali Naqi Gilani

    2016-03-01

    Full Text Available The development of robust and accurate methods for automatic building detection and regularisation using multisource data continues to be a challenge due to point cloud sparsity, high spectral variability, urban objects differences, surrounding complexity, and data misalignment. To address these challenges, constraints on object’s size, height, area, and orientation are generally benefited which adversely affect the detection performance. Often the buildings either small in size, under shadows or partly occluded are ousted during elimination of superfluous objects. To overcome the limitations, a methodology is developed to extract and regularise the buildings using features from point cloud and orthoimagery. The building delineation process is carried out by identifying the candidate building regions and segmenting them into grids. Vegetation elimination, building detection and extraction of their partially occluded parts are achieved by synthesising the point cloud and image data. Finally, the detected buildings are regularised by exploiting the image lines in the building regularisation process. Detection and regularisation processes have been evaluated using the ISPRS benchmark and four Australian data sets which differ in point density (1 to 29 points/m2, building sizes, shadows, terrain, and vegetation. Results indicate that there is 83% to 93% per-area completeness with the correctness of above 95%, demonstrating the robustness of the approach. The absence of over- and many-to-many segmentation errors in the ISPRS data set indicate that the technique has higher per-object accuracy. While compared with six existing similar methods, the proposed detection and regularisation approach performs significantly better on more complex data sets (Australian in contrast to the ISPRS benchmark, where it does better or equal to the counterparts.

  2. Towards automatic lithological classification from remote sensing data using support vector machines

    Science.gov (United States)

    Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

    2010-05-01

    Remote sensing data can be effectively used as a mean to build geological knowledge for poorly mapped terrains. Spectral remote sensing data from space- and air-borne sensors have been widely used to geological mapping, especially in areas of high outcrop density in arid regions. However, spectral remote sensing information by itself cannot be efficiently used for a comprehensive lithological classification of an area due to (1) diagnostic spectral response of a rock within an image pixel is conditioned by several factors including the atmospheric effects, spectral and spatial resolution of the image, sub-pixel level heterogeneity in chemical and mineralogical composition of the rock, presence of soil and vegetation cover; (2) only surface information and is therefore highly sensitive to the noise due to weathering, soil cover, and vegetation. Consequently, for efficient lithological classification, spectral remote sensing data needs to be supplemented with other remote sensing datasets that provide geomorphological and subsurface geological information, such as digital topographic model (DEM) and aeromagnetic data. Each of the datasets contain significant information about geology that, in conjunction, can potentially be used for automated lithological classification using supervised machine learning algorithms. In this study, support vector machine (SVM), which is a kernel-based supervised learning method, was applied to automated lithological classification of a study area in northwestern India using remote sensing data, namely, ASTER, DEM and aeromagnetic data. Several digital image processing techniques were used to produce derivative datasets that contained enhanced information relevant to lithological discrimination. A series of SVMs (trained using k-folder cross-validation with grid search) were tested using various combinations of input datasets selected from among 50 datasets including the original 14 ASTER bands and 36 derivative datasets (including 14

  3. Convective Heat Transfer Coefficients of Automatic Transmission Fluid Jets with Implications for Electric Machine Thermal Management: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Bennion, Kevin; Moreno, Gilberto

    2015-09-29

    Thermal management for electric machines (motors/ generators) is important as the automotive industry continues to transition to more electrically dominant vehicle propulsion systems. Cooling of the electric machine(s) in some electric vehicle traction drive applications is accomplished by impinging automatic transmission fluid (ATF) jets onto the machine's copper windings. In this study, we provide the results of experiments characterizing the thermal performance of ATF jets on surfaces representative of windings, using Ford's Mercon LV ATF. Experiments were carried out at various ATF temperatures and jet velocities to quantify the influence of these parameters on heat transfer coefficients. Fluid temperatures were varied from 50 degrees C to 90 degrees C to encompass potential operating temperatures within an automotive transaxle environment. The jet nozzle velocities were varied from 0.5 to 10 m/s. The experimental ATF heat transfer coefficient results provided in this report are a useful resource for understanding factors that influence the performance of ATF-based cooling systems for electric machines.

  4. The microbiological quality of pasteurized milk sold by automatic vending machines.

    Science.gov (United States)

    Angelidis, A S; Tsiota, S; Pexara, A; Govaris, A

    2016-06-01

    The microbiological quality of pasteurized milk samples (n = 39) collected during 13 weekly intervals from three automatic vending machines (AVM) in Greece was investigated. Microbiological counts (total aerobic (TAC), total psychrotrophic (TPC), Enterobacteriaceae (EC), and psychrotrophic aerobic bacterial spore counts (PABSC)) were obtained at the time of sampling and at the end of shelf-life (3 days) after storage of the samples at 4 or 8°C. TAC were found to be below the 10(7 ) CFU ml(-1) limit of pasteurized milk spoilage both during sampling as well as when milk samples were stored at either storage temperature for 3 days. Enterobacteriaceae populations were below 1 CFU ml(-1) in 69·2% of the samples tested at the time of sampling, whereas the remaining samples contained low numbers, typically less than 10 CFU ml(-1) . All samples tested negative for the presence of Listeria monocytogenes. Analogous microbiological data were also obtained by sampling and testing prepackaged, retail samples of pasteurized milk from two dairy companies in Greece (n = 26). From a microbiological standpoint, the data indicate that the AVM milk samples meet the quality standards of pasteurized milk. However, the prepackaged, retail milk samples yielded better results in terms of TAC, TPC and EC, compared to the AVM samples at the end of shelf-life. Recently, Greek dairy farmers organized in cooperatives launched the sale of pasteurized milk via AVM and this study reports on the microbiological quality of this product. The data show that AVM milk is sold at proper refrigeration temperatures and meets the quality standards of pasteurized milk throughout the manufacturer's specified shelf-life. However, based on the microbiological indicators tested, the keeping quality of the tested prepackaged, retail samples of pasteurized milk at the end of shelf-life upon storage under suboptimal refrigeration temperature (8°C) was better. © 2016 The Society for Applied

  5. Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques

    Science.gov (United States)

    Tellaeche, A.; Arana, R.; Ibarguren, A.; Martínez-Otzeta, J. M.

    The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

  6. AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

    Directory of Open Access Journals (Sweden)

    J. Tao

    2012-09-01

    Full Text Available Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM. Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc. can be automatically indicated in SAR image.

  7. Automatic thermographic scanning with the creation of 3D panoramic views of buildings

    Science.gov (United States)

    Ferrarini, G.; Cadelano, G.; Bortolin, A.

    2016-05-01

    Infrared thermography is widely applied to the inspection of building, enabling the identification of thermal anomalies due to the presence of hidden structures, air leakages, and moisture. One of the main advantages of this technique is the possibility to acquire rapidly a temperature map of a surface. However, due to the actual low-resolution of thermal camera and the necessity of scanning surfaces with different orientation, during a building survey it is necessary to take multiple images. In this work a device based on quantitative infrared thermography, called aIRview, has been applied during building surveys to automatically acquire thermograms with a camera mounted on a robotized pan tilt unit. The goal is to perform a first rapid survey of the building that could give useful information for the successive quantitative thermal investigations. For each data acquisition, the instrument covers a rotational field of view of 360° around the vertical axis and up to 180° around the horizontal one. The obtained images have been processed in order to create a full equirectangular projection of the ambient. For this reason the images have been integrated into a web visualization tool, working with web panorama viewers such as Google Street View, creating a webpage where it is possible to have a three dimensional virtual visit of the building. The thermographic data are embedded with the visual imaging and with other sensor data, facilitating the understanding of the physical phenomena underlying the temperature distribution.

  8. SEMI-AUTOMATIC BUILDING MODELS AND FAÇADE TEXTURE MAPPING FROM MOBILE PHONE IMAGES

    Directory of Open Access Journals (Sweden)

    J. Jeong

    2016-06-01

    Full Text Available Research on 3D urban modelling has been actively carried out for a long time. Recently the need of 3D urban modelling research is increased rapidly due to improved geo-web services and popularized smart devices. Nowadays 3D urban models provided by, for example, Google Earth use aerial photos for 3D urban modelling but there are some limitations: immediate update for the change of building models is difficult, many buildings are without 3D model and texture, and large resources for maintaining and updating are inevitable. To resolve the limitations mentioned above, we propose a method for semi-automatic building modelling and façade texture mapping from mobile phone images and analyze the result of modelling with actual measurements. Our method consists of camera geometry estimation step, image matching step, and façade mapping step. Models generated from this method were compared with actual measurement value of real buildings. Ratios of edge length of models and measurements were compared. Result showed 5.8% average error of length ratio. Through this method, we could generate a simple building model with fine façade textures without expensive dedicated tools and dataset.

  9. Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.

    Science.gov (United States)

    Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio

    2018-02-01

    Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially important as these systems are pervasively being introduced to critical domains, such as the medical field. Representation Learning techniques are general methods for automatic feature computation. Nevertheless, these techniques are regarded as uninterpretable "black boxes". In this paper, we propose a methodology to enhance the interpretability of automatically extracted machine learning features. The proposed system is composed of a Restricted Boltzmann Machine for unsupervised feature learning, and a Random Forest classifier, which are combined to jointly consider existing correlations between imaging data, features, and target variables. We define two levels of interpretation: global and local. The former is devoted to understanding if the system learned the relevant relations in the data correctly, while the later is focused on predictions performed on a voxel- and patient-level. In addition, we propose a novel feature importance strategy that considers both imaging data and target variables, and we demonstrate the ability of the approach to leverage the interpretability of the obtained representation for the task at hand. We evaluated the proposed methodology in brain tumor segmentation and penumbra estimation in ischemic stroke lesions. We show the ability of the proposed methodology to unveil information regarding relationships between imaging modalities and extracted features and their usefulness for the task at hand. In both clinical scenarios, we demonstrate that the proposed methodology enhances the interpretability of automatically learned features, highlighting specific learning patterns that resemble how an expert extracts relevant data from medical images. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Design of an ARM-based Automatic Rice-Selling Machine for Cafeterias

    Directory of Open Access Journals (Sweden)

    Zhiliang Kang

    2016-02-01

    Full Text Available To address the problems of low selling efficiency, poor sanitation conditions, labor-intensive requirement, and quick rice cooling speed in manual rice selling in cafeterias, especially in colleges and secondary schools, this paper presented an Advanced RISC Machines (ARM microprocessor-based rice-selling machine for cafeterias. The machines consisted of a funnel-shaped rice bin, a thermal insulation box, and a conveying and scattering mechanism. Moreover, this machine exerts fuzzy control over stepper motor rpm, and the motor drives the conveyor belt with a scraper to scatter rice, deliver it, and keep it warm. Apart from an external 4*4 keyboard, a point of sale (POS machine, an ARM process and a pressure sensor, the machine is also equipped with card swiping and weighting mechanisms to achieve functions of card swiping payment and precise measurement, respectively. In addition, detection of the right amount of rice and the alarm function are achieved using an ultrasonic sensor and a beeper, respectively. The presence of the rice container on the rice outlet is detected by an optoelectronic switch. Results show that this rice-selling machine achieves precise measurement, quick card swiping, fast rice selling, stable operation, and good rice heat preservation. Therefore, the mechanical design enables the machine to achieve its goals.

  11. Automatic extraction of Manhattan-World building masses from 3D laser range scans.

    Science.gov (United States)

    Vanegas, Carlos A; Aliaga, Daniel G; Benes, Bedrich

    2012-10-01

    We propose a novel approach for the reconstruction of urban structures from 3D point clouds with an assumption of Manhattan World (MW) building geometry; i.e., the predominance of three mutually orthogonal directions in the scene. Our approach works in two steps. First, the input points are classified according to the MW assumption into four local shape types: walls, edges, corners, and edge corners. The classified points are organized into a connected set of clusters from which a volume description is extracted. The MW assumption allows us to robustly identify the fundamental shape types, describe the volumes within the bounding box, and reconstruct visible and occluded parts of the sampled structure. We show results of our reconstruction that has been applied to several synthetic and real-world 3D point data sets of various densities and from multiple viewpoints. Our method automatically reconstructs 3D building models from up to 10 million points in 10 to 60 seconds.

  12. Automatic Generation of Structural Building Descriptions from 3D Point Cloud Scans

    DEFF Research Database (Denmark)

    Ochmann, Sebastian; Vock, Richard; Wessel, Raoul

    2013-01-01

    We present a new method for automatic semantic structuring of 3D point clouds representing buildings. In contrast to existing approaches which either target the outside appearance like the facade structure or rather low-level geometric structures, we focus on the building’s interior using indoor...... scans to derive high-level architectural entities like rooms and doors. Starting with a registered 3D point cloud, we probabilistically model the affiliation of each measured point to a certain room in the building. We solve the resulting clustering problem using an iterative algorithm that relies...... on the estimated visibilities between any two locations within the point cloud. With the segmentation into rooms at hand, we subsequently determine the locations and extents of doors between adjacent rooms. In our experiments, we demonstrate the feasibility of our method by applying it to synthetic as well...

  13. RAW MILK IN AUTOMATIC SALE MACHINES: MONITORING PLAN IN PIEDEMONT REGION

    Directory of Open Access Journals (Sweden)

    S. Gallina

    2010-06-01

    Full Text Available Raw milk at vending machine is surging in popularity amongst consumers of Northern Italy; indeed in Piedmont Region there are more than 100 vending machines. In June 2008 Piedmont Region set out a specific monitoring plan to check the milk quality. From June to December 2008, 113 raw milk samples were collected at vending machines. Samples were analysed for Listeria monocytogenes, Salmonella spp., coagulase positive staphylococci, Staphylococcus aureus and Campylobacter. Moreover, 100 samples were analysed for the quantification of aflatoxin M1. 26 samples have been resulted Not Conform for the hygienic criteria and 1 exceeded the aflatoxin M1 limit.

  14. AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE

    Directory of Open Access Journals (Sweden)

    E. Kwak

    2012-07-01

    Full Text Available Digital Building Model is an important component in many applications such as city modelling, natural disaster planning, and aftermath evaluation. The importance of accurate and up-to-date building models has been discussed by many researchers, and many different approaches for efficient building model generation have been proposed. They can be categorised according to the data source used, the data processing strategy, and the amount of human interaction. In terms of data source, due to the limitations of using single source data, integration of multi-senor data is desired since it preserves the advantages of the involved datasets. Aerial imagery and LiDAR data are among the commonly combined sources to obtain 3D building models with good vertical accuracy from laser scanning and good planimetric accuracy from aerial images. The most used data processing strategies are data-driven and model-driven ones. Theoretically one can model any shape of buildings using data-driven approaches but practically it leaves the question of how to impose constraints and set the rules during the generation process. Due to the complexity of the implementation of the data-driven approaches, model-based approaches draw the attention of the researchers. However, the major drawback of model-based approaches is that the establishment of representative models involves a manual process that requires human intervention. Therefore, the objective of this research work is to automatically generate building models using the Minimum Bounding Rectangle algorithm and sequentially adjusting them to combine the advantages of image and LiDAR datasets.

  15. Modeling of industrial stream and resources of machine-building enterpriser complex of wood preparation

    Science.gov (United States)

    Sereda, T. G.; Kostarev, S. N.

    2018-03-01

    Theoretical bases of linkage of material streams of the machine-building enterprise and the automated system of decision-making are developed. The process of machine-building manufacture is submitted by the existential system. The equation of preservation of movement is based on calculation of volume of manufacture. The basis of resource variables includes capacities and operators of the equipment. Indignations such as a defect and failure are investigated in the existential basis. The equation of a stream of details on a manufacturing route is made. The received analytical expression expresses a condition of a stream of movement of details in view of influence of work of the equipment and traumatism of the personnel.

  16. Micro-CernVM: slashing the cost of building and deploying virtual machines

    International Nuclear Information System (INIS)

    Blomer, J; Berzano, D; Buncic, P; Charalampidis, I; Ganis, G; Lestaris, G; Meusel, R; Nicolaou, V

    2014-01-01

    The traditional virtual machine (VM) building and and deployment process is centered around the virtual machine hard disk image. The packages comprising the VM operating system are carefully selected, hard disk images are built for a variety of different hypervisors, and images have to be distributed and decompressed in order to instantiate a virtual machine. Within the HEP community, the CernVM File System (CernVM-FS) has been established in order to decouple the distribution from the experiment software from the building and distribution of the VM hard disk images. We show how to get rid of such pre-built hard disk images altogether. Due to the high requirements on POSIX compliance imposed by HEP application software, CernVM-FS can also be used to host and boot a Linux operating system. This allows the use of a tiny bootable CD image that comprises only a Linux kernel while the rest of the operating system is provided on demand by CernVM-FS. This approach speeds up the initial instantiation time and reduces virtual machine image sizes by an order of magnitude. Furthermore, security updates can be distributed instantaneously through CernVM-FS. By leveraging the fact that CernVM-FS is a versioning file system, a historic analysis environment can be easily re-spawned by selecting the corresponding CernVM-FS file system snapshot.

  17. Innovative technologies of outsourcing at the machine-building enterprises of Sverdlovsk area

    OpenAIRE

    Petr Krylatkov

    2010-01-01

    The analysis of the basic problems connected with infringements of integrity of the machine-building enterprises of Sverdlovsk area is lead in the article. The specified problems are considered from a position of the complete approach developed by the author. Display of infringements of integrity of some the enterprises are illustrated by data of their inspection. As the effective tool of increase of integrity of the enterprises — expansion use of attitudes of outsourcing is offered. The co...

  18. Forming the management model in industrial partnerships of the machine-building complex of Ukraine

    OpenAIRE

    Reshetilova, T.; Kuvaieva, T.

    2016-01-01

    Stages of development the processes of forming the industrial networks, technological and logistic chains, partnership and their varieties are analyzed. Factors that determine the rate and scale of the process of forming the partnerships in the machine-building complex of Ukraine are established. A group of the factors that lead to forming the vertical partnership based on Partner Relationship Management (PRM) in mining machinery and mining industry are determined and analyzed. It is possible...

  19. Machine-Building for Fuel and Energy Complex: Perspective Forms of Interaction

    Science.gov (United States)

    Nikitenko, S. M.; Goosen, E. V.; Pakhomova, E. A.; Rozhkova, O. V.; Mesyats, M. A.

    2017-10-01

    The article is devoted to the study of the existing forms of cooperation between the authorities, business and science in the fuel and energy complex and the machine-building industry at the regional level. The possibilities of applying the concept of the “triple helix” and its multi-helix modifications for the implementation of the import substitution program for high- tech products have been considered.

  20. Formation of competitive potential of the machine-building complex of the region

    Directory of Open Access Journals (Sweden)

    Oleg Ivanovich Botkin

    2014-03-01

    Full Text Available The article describes the features of competitive potential of regional machine-building complex in a globalized world economy. The purpose of the research is the development of theoretically reasonable economic basis of the machine-building complex considering  the  features of business in the conditions of the WTO. In the work, the hypothesis of a special role of the external economic factors locates in development of the enterprises of regional industrial complexes. The study of the theoretical provisions defining the development of the region revealed the factors determining influence of the international trade agreements on spatial localization of the industry. The main attention is paid to an analytical assessment of the current state and the trends, which have developed in the period of post-crisis economic recovery. Analysis of the main indicators of attractiveness has revealed the weak position of local industrial enterprises in the WTO. The directions of strengthening of the competitive capacity of the local industrial enterprises are defined. The obtained results allow us to increase the sustainability of the industry by means of effective management mechanism improvements and to create favorable operating conditions of a machine-building complex of the region

  1. Machine Beats Experts: Automatic Discovery of Skill Models for Data-Driven Online Course Refinement

    Science.gov (United States)

    Matsuda, Noboru; Furukawa, Tadanobu; Bier, Norman; Faloutsos, Christos

    2015-01-01

    How can we automatically determine which skills must be mastered for the successful completion of an online course? Large-scale online courses (e.g., MOOCs) often contain a broad range of contents frequently intended to be a semester's worth of materials; this breadth often makes it difficult to articulate an accurate set of skills and knowledge…

  2. Innovation on structure of all automatic multi-studs four synchronous installing machine used in PWR

    International Nuclear Information System (INIS)

    Zhu Qirong; Zou Xiyang

    2002-01-01

    First of all from structure bring forth many new ideas. New stud, nut and a brand-new installing machine have been designed. In main machine, the integrated gear mechanism simple in structure achieves synchronous turning function, instead of the precision, complicated, expensive manipulator or robot. In aspect of supervising and controlling, computer electro-hydraulic proportional control and advanced examine measure system have been designed to measure stress and extension of stud as tensioning. Mathematics model and transmit function have been built using theory of modern times fluid transmission and control. As a result four synchronous installing has been achieved

  3. Automatic Generation of Building Models with Levels of Detail 1-3

    Science.gov (United States)

    Nguatem, W.; Drauschke, M.; Mayer, H.

    2016-06-01

    We present a workflow for the automatic generation of building models with levels of detail (LOD) 1 to 3 according to the CityGML standard (Gröger et al., 2012). We start with orienting unsorted image sets employing (Mayer et al., 2012), we compute depth maps using semi-global matching (SGM) (Hirschmüller, 2008), and fuse these depth maps to reconstruct dense 3D point clouds (Kuhn et al., 2014). Based on planes segmented from these point clouds, we have developed a stochastic method for roof model selection (Nguatem et al., 2013) and window model selection (Nguatem et al., 2014). We demonstrate our workflow up to the export into CityGML.

  4. Building the Knowledge Base to Support the Automatic Animation Generation of Chinese Traditional Architecture

    Science.gov (United States)

    Wei, Gongjin; Bai, Weijing; Yin, Meifang; Zhang, Songmao

    We present a practice of applying the Semantic Web technologies in the domain of Chinese traditional architecture. A knowledge base consisting of one ontology and four rule bases is built to support the automatic generation of animations that demonstrate the construction of various Chinese timber structures based on the user's input. Different Semantic Web formalisms are used, e.g., OWL DL, SWRL and Jess, to capture the domain knowledge, including the wooden components needed for a given building, construction sequence, and the 3D size and position of every piece of wood. Our experience in exploiting the current Semantic Web technologies in real-world application systems indicates their prominent advantages (such as the reasoning facilities and modeling tools) as well as the limitations (such as low efficiency).

  5. Research on the automatic laser navigation system of the tunnel boring machine

    Science.gov (United States)

    Liu, Yake; Li, Yueqiang

    2011-12-01

    By establishing relevant coordinates of the Automatic Laser Navigation System, the basic principle of the system which accesses the TBM three-dimensional reference point and yawing angle by mathematical transformation between TBM, target prism and earth coordinate systems is discussed deeply in details. According to the way of rigid body descriptions of its posture, TBM attitude parameters measurement and data acquisition methods are proposed, and measures to improve the accuracy of the Laser Navigation System are summarized.

  6. Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    SONG Le; LIN Yuchi; HAO Liguo

    2008-01-01

    Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope (UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation (BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dynamically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.

  7. Food Safety by Using Machine Learning for Automatic Classification of Seeds of the South-American Incanut Plant

    International Nuclear Information System (INIS)

    Lemanzyk, Thomas; Anding, Katharina; Linss, Gerhard; Hernández, Jorge Rodriguez; Theska, René

    2015-01-01

    The following paper deals with the classification of seeds and seed components of the South-American Incanut plant and the modification of a machine to handle this task. Initially the state of the art is being illustrated. The research was executed in Germany and with a relevant part in Peru and Ecuador. Theoretical considerations for the solution of an automatically analysis of the Incanut seeds were specified. The optimization of the analyzing software and the separation unit of the mechanical hardware are carried out with recognition results. In a final step the practical application of the analysis of the Incanut seeds is held on a trial basis and rated on the bases of statistic values

  8. Automatic fitting of conical envelopes to free-form surfaces for flank CNC machining

    OpenAIRE

    Bo P.; Bartoň M.; Pottmann H.

    2017-01-01

    We propose a new algorithm to detect patches of free-form surfaces that can be well approximated by envelopes of a rotational cone under a rigid body motion. These conical envelopes are a preferable choice from the manufacturing point of view as they are, by-definition, manufacturable by computer numerically controlled (CNC) machining using the efficient flank (peripheral) method with standard conical tools. Our geometric approach exploits multi-valued vector fields that consist of vectors in...

  9. Automatic ice-cream characterization by impedance measurements for optimal machine setting

    OpenAIRE

    Grossi , Marco; Lanzoni , Massimo; Lazzarini , Roberto; Riccò , Bruno

    2012-01-01

    International audience; Electrical characterization of products is gaining increasing interest in the food industry for quality monitoring and control. In particular, this is the case in the ice-cream industry, where machines dedicated to store ice-cream mixes are programmed ''ad hoc'' for different groups of products. To this purpose, the present work shows that essential product classification (discrimination between milk based and fruit based ice-cream mixes) can be done by means of a tech...

  10. Lamb wave based automatic damage detection using matching pursuit and machine learning

    International Nuclear Information System (INIS)

    Agarwal, Sushant; Mitra, Mira

    2014-01-01

    In this study, matching pursuit (MP) has been tested with machine learning algorithms such as artificial neural networks (ANNs) and support vector machines (SVMs) to automate the process of damage detection in metallic plates. Here, damage detection is done using the Lamb wave response in a thin aluminium plate simulated using a finite element (FE) method. To reduce the complexity of the Lamb wave response, only the A 0 mode is excited and sensed. The procedure adopted for damage detection consists of three major steps, involving signal processing and machine learning (ML). In the first step, MP is used for de-noising and enhancing the sparsity of the database. In the existing literature, MP is used to decompose any signal into a linear combination of waveforms that are selected from a redundant dictionary. In this work, MP is deployed in two stages to make the database sparse as well as to de-noise it. After using MP on the database, it is then passed as input data for ML classifiers. ANN and SVM are used to detect the location of the potential damage from the reduced data. The study demonstrates that the SVM is a robust classifier in the presence of noise and is more efficient than the ANN. Out-of-sample data are used for the validation of the trained and tested classifier. Trained classifiers are found to be successful in the detection of damage with a detection rate of more than 95%. (paper)

  11. Fully automatic time-window selection using machine learning for global adjoint tomography

    Science.gov (United States)

    Chen, Y.; Hill, J.; Lei, W.; Lefebvre, M. P.; Bozdag, E.; Komatitsch, D.; Tromp, J.

    2017-12-01

    Selecting time windows from seismograms such that the synthetic measurements (from simulations) and measured observations are sufficiently close is indispensable in a global adjoint tomography framework. The increasing amount of seismic data collected everyday around the world demands "intelligent" algorithms for seismic window selection. While the traditional FLEXWIN algorithm can be "automatic" to some extent, it still requires both human input and human knowledge or experience, and thus is not deemed to be fully automatic. The goal of intelligent window selection is to automatically select windows based on a learnt engine that is built upon a huge number of existing windows generated through the adjoint tomography project. We have formulated the automatic window selection problem as a classification problem. All possible misfit calculation windows are classified as either usable or unusable. Given a large number of windows with a known selection mode (select or not select), we train a neural network to predict the selection mode of an arbitrary input window. Currently, the five features we extract from the windows are its cross-correlation value, cross-correlation time lag, amplitude ratio between observed and synthetic data, window length, and minimum STA/LTA value. More features can be included in the future. We use these features to characterize each window for training a multilayer perceptron neural network (MPNN). Training the MPNN is equivalent to solve a non-linear optimization problem. We use backward propagation to derive the gradient of the loss function with respect to the weighting matrices and bias vectors and use the mini-batch stochastic gradient method to iteratively optimize the MPNN. Numerical tests show that with a careful selection of the training data and a sufficient amount of training data, we are able to train a robust neural network that is capable of detecting the waveforms in an arbitrary earthquake data with negligible detection error

  12. Automatically quantifying the scientific quality and sensationalism of news records mentioning pandemics: validating a maximum entropy machine-learning model.

    Science.gov (United States)

    Hoffman, Steven J; Justicz, Victoria

    2016-07-01

    To develop and validate a method for automatically quantifying the scientific quality and sensationalism of individual news records. After retrieving 163,433 news records mentioning the Severe Acute Respiratory Syndrome (SARS) and H1N1 pandemics, a maximum entropy model for inductive machine learning was used to identify relationships among 500 randomly sampled news records that correlated with systematic human assessments of their scientific quality and sensationalism. These relationships were then computationally applied to automatically classify 10,000 additional randomly sampled news records. The model was validated by randomly sampling 200 records and comparing human assessments of them to the computer assessments. The computer model correctly assessed the relevance of 86% of news records, the quality of 65% of records, and the sensationalism of 73% of records, as compared to human assessments. Overall, the scientific quality of SARS and H1N1 news media coverage had potentially important shortcomings, but coverage was not too sensationalizing. Coverage slightly improved between the two pandemics. Automated methods can evaluate news records faster, cheaper, and possibly better than humans. The specific procedure implemented in this study can at the very least identify subsets of news records that are far more likely to have particular scientific and discursive qualities. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. HAVmS: Highly Available Virtual Machine Computer System Fault Tolerant with Automatic Failback and Close to Zero Downtime

    Directory of Open Access Journals (Sweden)

    Memmo Federici

    2014-12-01

    Full Text Available In scientic computing, systems often manage computations that require continuous acquisition of of satellite data and the management of large databases, as well as the execution of analysis software and simulation models (e.g. Monte Carlo or molecular dynamics cell simulations which may require several weeks of continuous run. These systems, consequently, should ensure the continuity of operation even in case of serious faults. HAVmS (High Availability Virtual machine System is a highly available, "fault tolerant" system with zero downtime in case of fault. It is based on the use of Virtual Machines and implemented by two servers with similar characteristics. HAVmS, thanks to the developed software solutions, is unique in its kind since it automatically failbacks once faults have been fixed. The system has been designed to be used both with professional or inexpensive hardware and supports the simultaneous execution of multiple services such as: web, mail, computing and administrative services, uninterrupted computing, data base management. Finally the system is cost effective adopting exclusively open source solutions, is easily manageable and for general use.

  14. Machine learning approach for automatic quality criteria detection of health web pages.

    Science.gov (United States)

    Gaudinat, Arnaud; Grabar, Natalia; Boyer, Célia

    2007-01-01

    The number of medical websites is constantly growing [1]. Owing to the open nature of the Web, the reliability of information available on the Web is uneven. Internet users are overwhelmed by the quantity of information available on the Web. The situation is even more critical in the medical area, as the content proposed by health websites can have a direct impact on the users' well being. One way to control the reliability of health websites is to assess their quality and to make this assessment available to users. The HON Foundation has defined a set of eight ethical principles. HON's experts are working in order to manually define whether a given website complies with s the required principles. As the number of medical websites is constantly growing, manual expertise becomes insufficient and automatic systems should be used in order to help medical experts. In this paper we present the design and the evaluation of an automatic system conceived for the categorisation of medical and health documents according to he HONcode ethical principles. A first evaluation shows promising results. Currently the system shows 0.78 micro precision and 0.73 F-measure, with 0.06 errors.

  15. As-Built Verification Plan Spent Nuclear Fuel Canister Storage Building MCO Handling Machine

    International Nuclear Information System (INIS)

    SWENSON, C.E.

    2000-01-01

    This as-built verification plan outlines the methodology and responsibilities that will be implemented during the as-built field verification activity for the Canister Storage Building (CSB) MCO HANDLING MACHINE (MHM). This as-built verification plan covers THE ELECTRICAL PORTION of the CONSTRUCTION PERFORMED BY POWER CITY UNDER CONTRACT TO MOWAT. The as-built verifications will be performed in accordance Administrative Procedure AP 6-012-00, Spent Nuclear Fuel Project As-Built Verification Plan Development Process, revision I. The results of the verification walkdown will be documented in a verification walkdown completion package, approved by the Design Authority (DA), and maintained in the CSB project files

  16. The Model of Information Support for Management of Investment Attractiveness of Machine-Building Enterprises

    Directory of Open Access Journals (Sweden)

    Chernetska Olga V.

    2016-11-01

    Full Text Available The article discloses the content of the definition of “information support”, identifies basic approaches to the interpretation of this economic category. The main purpose of information support for management of enterprise investment attractiveness is determined. The key components of information support for management of enterprise investment attractiveness are studied. The main types of automated information systems for management of the investment attractiveness of enterprises are identified and characterized. The basic computer programs for assessing the level of investment attractiveness of enterprises are considered. A model of information support for management of investment attractiveness of machine-building enterprises is developed.

  17. Reagent precipitation of copper ions from wastewater of machine-building factories

    Science.gov (United States)

    Porozhnyuk, L. A.; Lupandina, N. S.; Porozhnyuk, E. V.

    2018-03-01

    The article presents the results of reagent removal of copper ions from wastewater of machine-building factories. The urgency of the study is conditioned by the widening of the range of effective reagents through the implementation of industrial waste. The investigation covers mineralogical and fractional composition of chalk enrichment waste. In the work, the conditions of thermal activation of chalk enrichment waste used for reagent removal of copper ions from wastewater were elaborated. It was shown that the thermal activation of waste facilitates the increased treatment efficacy up to the set sanitation, hygiene and technological standards.

  18. Automatic Creation of Machine Learning Workflows with Strongly Typed Genetic Programming

    Czech Academy of Sciences Publication Activity Database

    Křen, T.; Pilát, M.; Neruda, Roman

    2017-01-01

    Roč. 26, č. 5 (2017), č. článku 1760020. ISSN 0218-2130 R&D Projects: GA ČR GA15-19877S Grant - others:GA MŠk(CZ) LM2015042 Institutional support: RVO:67985807 Keywords : genetic programming * machine learning workflows * asynchronous evolutionary algorithm Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.778, year: 2016

  19. Building a semi-automatic ontology learning and construction system for geosciences

    Science.gov (United States)

    Babaie, H. A.; Sunderraman, R.; Zhu, Y.

    2013-12-01

    We are developing an ontology learning and construction framework that allows continuous, semi-automatic knowledge extraction, verification, validation, and maintenance by potentially a very large group of collaborating domain experts in any geosciences field. The system brings geoscientists from the side-lines to the center stage of ontology building, allowing them to collaboratively construct and enrich new ontologies, and merge, align, and integrate existing ontologies and tools. These constantly evolving ontologies can more effectively address community's interests, purposes, tools, and change. The goal is to minimize the cost and time of building ontologies, and maximize the quality, usability, and adoption of ontologies by the community. Our system will be a domain-independent ontology learning framework that applies natural language processing, allowing users to enter their ontology in a semi-structured form, and a combined Semantic Web and Social Web approach that lets direct participation of geoscientists who have no skill in the design and development of their domain ontologies. A controlled natural language (CNL) interface and an integrated authoring and editing tool automatically convert syntactically correct CNL text into formal OWL constructs. The WebProtege-based system will allow a potentially large group of geoscientists, from multiple domains, to crowd source and participate in the structuring of their knowledge model by sharing their knowledge through critiquing, testing, verifying, adopting, and updating of the concept models (ontologies). We will use cloud storage for all data and knowledge base components of the system, such as users, domain ontologies, discussion forums, and semantic wikis that can be accessed and queried by geoscientists in each domain. We will use NoSQL databases such as MongoDB as a service in the cloud environment. MongoDB uses the lightweight JSON format, which makes it convenient and easy to build Web applications using

  20. Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

    Science.gov (United States)

    Zdravevski, Eftim; Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

    2017-01-01

    Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from

  1. Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

    Directory of Open Access Journals (Sweden)

    Eftim Zdravevski

    Full Text Available Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position.The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers.The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be

  2. Automatic Color Sorting Machine Using TCS230 Color Sensor And PIC Microcontroller

    Directory of Open Access Journals (Sweden)

    Kunhimohammed C K

    2015-12-01

    Full Text Available Sorting of products is a very difficult industrial process. Continuous manual sorting creates consistency issues. This paper describes a working prototype designed for automatic sorting of objects based on the color. TCS230 sensor was used to detect the color of the product and the PIC16F628A microcontroller was used to control the overall process. The identification of the color is based on the frequency analysis of the output of TCS230 sensor. Two conveyor belts were used, each controlled by separate DC motors. The first belt is for placing the product to be analyzed by the color sensor, and the second belt is for moving the container, having separated compartments, in order to separate the products. The experimental results promise that the prototype will fulfill the needs for higher production and precise quality in the field of automation.

  3. Automatic control of the preload in adaptive friction drives of chemical production machines

    Science.gov (United States)

    Balakin, P. D.

    2017-08-01

    Being based on the principle of providing the systems with adaptation property to the real parameters and operational condition, the energy effective mechanical system constructed on the base of friction gear with automated preload is offered and this allows keeping mechanical efficiency value adequate transforming drive path to in the terms of multimode operation. This is achieved by integrated control loop, operating on the basis of the laws of motion with the energy of the main power flow by changing automatically the kinematic dimension of the section and, hence, the value of preload in the friction contact. The given ratios of forces and deformations in the control loop are required at the stage of conceptual design to determine design dimensions of power transmission elements with new properties.

  4. Method of Automatic Ontology Mapping through Machine Learning and Logic Mining

    Institute of Scientific and Technical Information of China (English)

    王英林

    2004-01-01

    Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.

  5. Big Data Analysis for Personalized Health Activities: Machine Learning Processing for Automatic Keyword Extraction Approach

    Directory of Open Access Journals (Sweden)

    Jun-Ho Huh

    2018-04-01

    Full Text Available The obese population is increasing rapidly due to the change of lifestyle and diet habits. Obesity can cause various complications and is becoming a social disease. Nonetheless, many obese patients are unaware of the medical treatments that are right for them. Although a variety of online and offline obesity management services have been introduced, they are still not enough to attract the attention of users and are not much of help to solve the problem. Obesity healthcare and personalized health activities are the important factors. Since obesity is related to lifestyle habits, eating habits, and interests, I concluded that the big data analysis of these factors could deduce the problem. Therefore, I collected big data by applying the machine learning and crawling method to the unstructured citizen health data in Korea and the search data of Naver, which is a Korean portal company, and Google for keyword analysis for personalized health activities. It visualized the big data using text mining and word cloud. This study collected and analyzed the data concerning the interests related to obesity, change of interest on obesity, and treatment articles. The analysis showed a wide range of seasonal factors according to spring, summer, fall, and winter. It also visualized and completed the process of extracting the keywords appropriate for treatment of abdominal obesity and lower body obesity. The keyword big data analysis technique for personalized health activities proposed in this paper is based on individual’s interests, level of interest, and body type. Also, the user interface (UI that visualizes the big data compatible with Android and Apple iOS. The users can see the data on the app screen. Many graphs and pictures can be seen via menu, and the significant data values are visualized through machine learning. Therefore, I expect that the big data analysis using various keywords specific to a person will result in measures for personalized

  6. Innovative technologies of outsourcing at the machine-building enterprises of Sverdlovsk area

    Directory of Open Access Journals (Sweden)

    P. P. Krylatkov

    2010-09-01

    Full Text Available The analysis of the basic problems connected with infringements of integrity of the machine-building enterprises of Sverdlovsk area is lead in the article. The specified problems are considered from a position of the complete approach developed by the author. Display of infringements of integrity of some the enterprises are illustrated by data of their inspection. As the effective tool of increase of integrity of the enterprises — expansion use of attitudes of outsourcing is offered. The comparative given applications of outsourcing in developed the country of the West and at the domestic enterprises, and also its benefits and risks are cited. Outsourcing, insoursing and subcontracting are considered by the author as the innovative tool of the decision of many serious problems of the machine-building enterprises of region. As an example practice of work of «The Sverdlovsk regional center of industrial cooperation» on coordination of attitudes of outsourcing, subcontracting and cooperation is offered. The author recommends the tabulated form, with the instruction of kinds of works for which performance the method of allocation or attraction outsourcing of the companies can be used.

  7. The Organizational-Economic Provision of Reengineering of Marketing Activity of Ukrainian Machine-Building Enterprises

    Directory of Open Access Journals (Sweden)

    Kobyzskyi Denys S.

    2018-02-01

    Full Text Available The article is aimed at developing an organizational mechanism to provide reengineering of the marketing activities of machine-building enterprise for further development of the appropriate methodical recommendations. The meaning and role of organizational structure in the sphere of reengineering are disclosed, the key aspects and principles of its construction are defined; the key elements, in particular business processes, and their role in organizational structure as well as properties of the organizational system are researched; content of the basic components of the organizational mechanism of the provision, their role and peculiarities of communication between them are analyzed. The new attitude to the principles of construction, functional content and content of the constituents of organization of enterprises allows to realize the wide functional potential of organizational possibilities within the terms of reengineering, as well as to form an organizational mechanism of post-reengineering company. Certain aspects of development of the organizational mechanism create the preconditions and disclose a potential instrumentarium for effective and efficient methodical recommendations as to reengineering of marketing activities of Ukrainian machine-building enterprises.

  8. Infrared machine vision system for the automatic detection of olive fruit quality.

    Science.gov (United States)

    Guzmán, Elena; Baeten, Vincent; Pierna, Juan Antonio Fernández; García-Mesa, José A

    2013-11-15

    External quality is an important factor in the extraction of olive oil and the marketing of olive fruits. The appearance and presence of external damage are factors that influence the quality of the oil extracted and the perception of consumers, determining the level of acceptance prior to purchase in the case of table olives. The aim of this paper is to report on artificial vision techniques developed for the online estimation of olive quality and to assess the effectiveness of these techniques in evaluating quality based on detecting external defects. This method of classifying olives according to the presence of defects is based on an infrared (IR) vision system. Images of defects were acquired using a digital monochrome camera with band-pass filters on near-infrared (NIR). The original images were processed using segmentation algorithms, edge detection and pixel value intensity to classify the whole fruit. The detection of the defect involved a pixel classification procedure based on nonparametric models of the healthy and defective areas of olives. Classification tests were performed on olives to assess the effectiveness of the proposed method. This research showed that the IR vision system is a useful technology for the automatic assessment of olives that has the potential for use in offline inspection and for online sorting for defects and the presence of surface damage, easily distinguishing those that do not meet minimum quality requirements. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.

  9. Semi-Automatic Registration of Airborne and Terrestrial Laser Scanning Data Using Building Corner Matching with Boundaries as Reliability Check

    Directory of Open Access Journals (Sweden)

    Liang Cheng

    2013-11-01

    Full Text Available Data registration is a prerequisite for the integration of multi-platform laser scanning in various applications. A new approach is proposed for the semi-automatic registration of airborne and terrestrial laser scanning data with buildings without eaves. Firstly, an automatic calculation procedure for thresholds in density of projected points (DoPP method is introduced to extract boundary segments from terrestrial laser scanning data. A new algorithm, using a self-extending procedure, is developed to recover the extracted boundary segments, which then intersect to form the corners of buildings. The building corners extracted from airborne and terrestrial laser scanning are reliably matched through an automatic iterative process in which boundaries from two datasets are compared for the reliability check. The experimental results illustrate that the proposed approach provides both high reliability and high geometric accuracy (average error of 0.44 m/0.15 m in horizontal/vertical direction for corresponding building corners for the final registration of airborne laser scanning (ALS and tripod mounted terrestrial laser scanning (TLS data.

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

    Directory of Open Access Journals (Sweden)

    A. V. Romanenko

    2014-01-01

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

  11. AES Cardless Automatic Teller Machine (ATM) Biometric Security System Design Using FPGA Implementation

    Science.gov (United States)

    Ahmad, Nabihah; Rifen, A. Aminurdin M.; Helmy Abd Wahab, Mohd

    2016-11-01

    Automated Teller Machine (ATM) is an electronic banking outlet that allows bank customers to complete a banking transactions without the aid of any bank official or teller. Several problems are associated with the use of ATM card such card cloning, card damaging, card expiring, cast skimming, cost of issuance and maintenance and accessing customer account by third parties. The aim of this project is to give a freedom to the user by changing the card to biometric security system to access the bank account using Advanced Encryption Standard (AES) algorithm. The project is implemented using Field Programmable Gate Array (FPGA) DE2-115 board with Cyclone IV device, fingerprint scanner, and Multi-Touch Liquid Crystal Display (LCD) Second Edition (MTL2) using Very High Speed Integrated Circuit Hardware (VHSIC) Description Language (VHDL). This project used 128-bits AES for recommend the device with the throughput around 19.016Gbps and utilized around 520 slices. This design offers a secure banking transaction with a low rea and high performance and very suited for restricted space environments for small amounts of RAM or ROM where either encryption or decryption is performed.

  12. Hour-Glass Neural Network Based Daily Money Flow Estimation for Automatic Teller Machines

    Science.gov (United States)

    Karungaru, Stephen; Akashi, Takuya; Nakano, Miyoko; Fukumi, Minoru

    Monetary transactions using Automated Teller Machines (ATMs) have become a normal part of our daily lives. At ATMs, one can withdraw, send or debit money and even update passbooks among many other possible functions. ATMs are turning the banking sector into a ubiquitous service. However, while the advantages for the ATM users (financial institution customers) are many, the financial institution side faces an uphill task in management and maintaining the cash flow in the ATMs. On one hand, too much money in a rarely used ATM is wasteful, while on the other, insufficient amounts would adversely affect the customers and may result in a lost business opportunity for the financial institution. Therefore, in this paper, we propose a daily cash flow estimation system using neural networks that enables better daily forecasting of the money required at the ATMs. The neural network used in this work is a five layered hour glass shaped structure that achieves fast learning, even for the time series data for which seasonality and trend feature extraction is difficult. Feature extraction is carried out using the Akamatsu Integral and Differential transforms. This work achieves an average estimation accuracy of 92.6%.

  13. Machine learning approach to automatic exudate detection in retinal images from diabetic patients

    Science.gov (United States)

    Sopharak, Akara; Dailey, Matthew N.; Uyyanonvara, Bunyarit; Barman, Sarah; Williamson, Tom; Thet Nwe, Khine; Aye Moe, Yin

    2010-01-01

    Exudates are among the preliminary signs of diabetic retinopathy, a major cause of vision loss in diabetic patients. Early detection of exudates could improve patients' chances to avoid blindness. In this paper, we present a series of experiments on feature selection and exudates classification using naive Bayes and support vector machine (SVM) classifiers. We first fit the naive Bayes model to a training set consisting of 15 features extracted from each of 115,867 positive examples of exudate pixels and an equal number of negative examples. We then perform feature selection on the naive Bayes model, repeatedly removing features from the classifier, one by one, until classification performance stops improving. To find the best SVM, we begin with the best feature set from the naive Bayes classifier, and repeatedly add the previously-removed features to the classifier. For each combination of features, we perform a grid search to determine the best combination of hyperparameters ν (tolerance for training errors) and γ (radial basis function width). We compare the best naive Bayes and SVM classifiers to a baseline nearest neighbour (NN) classifier using the best feature sets from both classifiers. We find that the naive Bayes and SVM classifiers perform better than the NN classifier. The overall best sensitivity, specificity, precision, and accuracy are 92.28%, 98.52%, 53.05%, and 98.41%, respectively.

  14. 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.

  15. Automatic Sleep Staging using Multi-dimensional Feature Extraction and Multi-kernel Fuzzy Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yanjun Zhang

    2014-01-01

    Full Text Available This paper employed the clinical Polysomnographic (PSG data, mainly including all-night Electroencephalogram (EEG, Electrooculogram (EOG and Electromyogram (EMG signals of subjects, and adopted the American Academy of Sleep Medicine (AASM clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM were learned and the multi-kernel FSVM (MK-FSVM was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

  16. Effect of Extended State Observer and Automatic Voltage Regulator on Synchronous Machine Connected to Infinite Bus Power System

    Science.gov (United States)

    Angu, Rittu; Mehta, R. K.

    2018-04-01

    This paper presents a robust controller known as Extended State Observer (ESO) in order to improve the stability and voltage regulation of a synchronous machine connected to an infinite bus power system through a transmission line. The ESO-based control scheme is implemented with an automatic voltage regulator in conjunction with an excitation system to enhance the damping of low frequency power system oscillations, as the Power System Stabilizer (PSS) does. The implementation of PSS excitation control techniques however requires reliable information about the entire states, though they are not always directly measureable. To address this issue, the proposed ESO provides the estimate of system states as well as disturbance state together in order to improve not only the damping but also compensates system efficiently in presence of parameter uncertainties and external disturbances. The Closed-Loop Poles (CLPs) of the system have been assigned by the symmetric root locus technique, with the desired level of system damping provided by the dominant CLPs. The performance of the system is analyzed through simulating at different operating conditions. The control method is not only capable of providing zero estimation error in steady-state, but also shows robustness in tracking the reference command under parametric variations and external disturbances. Illustrative examples have been provided to demonstrate the effectiveness of the developed methodology.

  17. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    Science.gov (United States)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  18. How to build a time machine: the real science of time travel

    CERN Document Server

    Clegg, Brian

    2013-01-01

    A pop science look at time travel technology, from Einstein to Ronald Mallett to present day experiments. Forget fiction: time travel is real.In How to Build a Time Machine, Brian Clegg provides an understanding of what time is and how it can be manipulated. He explores the fascinating world of physics and the remarkable possibilities of real time travel that emerge from quantum entanglement, superluminal speeds, neutron star cylinders and wormholes in space. With the fascinating paradoxes of time travel echoing in our minds will we realize that travel into the future might never be possible? Or will we realize there is no limit on what can be achieved, and take on this ultimate challenge? Only time will tell.

  19. Study on the Feasibility of RGB Substitute CIR for Automatic Removal Vegetation Occlusion Based on Ground Close-Range Building Images

    Science.gov (United States)

    Li, C.; Li, F.; Liu, Y.; Li, X.; Liu, P.; Xiao, B.

    2012-07-01

    Building 3D reconstruction based on ground remote sensing data (image, video and lidar) inevitably faces the problem that buildings are always occluded by vegetation, so how to automatically remove and repair vegetation occlusion is a very important preprocessing work for image understanding, compute vision and digital photogrammetry. In the traditional multispectral remote sensing which is achieved by aeronautics and space platforms, the Red and Near-infrared (NIR) bands, such as NDVI (Normalized Difference Vegetation Index), are useful to distinguish vegetation and clouds, amongst other targets. However, especially in the ground platform, CIR (Color Infra Red) is little utilized by compute vision and digital photogrammetry which usually only take true color RBG into account. Therefore whether CIR is necessary for vegetation segmentation or not has significance in that most of close-range cameras don't contain such NIR band. Moreover, the CIE L*a*b color space, which transform from RGB, seems not of much interest by photogrammetrists despite its powerfulness in image classification and analysis. So, CIE (L, a, b) feature and support vector machine (SVM) is suggested for vegetation segmentation to substitute for CIR. Finally, experimental results of visual effect and automation are given. The conclusion is that it's feasible to remove and segment vegetation occlusion without NIR band. This work should pave the way for texture reconstruction and repair for future 3D reconstruction.

  20. General collaboration offer of Johnson Controls regarding the performance of air conditioning automatic control systems and other buildings` automatic control systems

    Energy Technology Data Exchange (ETDEWEB)

    Gniazdowski, J.

    1995-12-31

    JOHNSON CONTROLS manufactures measuring and control equipment (800 types) and is as well a {open_quotes}turn-key{close_quotes} supplier of complete automatic controls systems for heating, air conditioning, ventilation and refrigerating engineering branches. The Company also supplies Buildings` Computer-Based Supervision and Monitoring Systems that may be applied in both small and large structures. Since 1990 the company has been performing full-range trade and contracting activities on the Polish market. We have our own well-trained technical staff and we collaborate with a series of designing and contracting enterprises that enable us to have our projects carried out all over Poland. The prices of our supplies and services correspond with the level of the Polish market.

  1. Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper

    Science.gov (United States)

    Luo, Gang

    2017-01-01

    For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022

  2. Automatic Recognition of Acute Myelogenous Leukemia in Blood Microscopic Images Using K-means Clustering and Support Vector Machine.

    Science.gov (United States)

    Kazemi, Fatemeh; Najafabadi, Tooraj Abbasian; Araabi, Babak Nadjar

    2016-01-01

    Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is characterized by the accumulation of myeloid blasts in the bone marrow. Careful microscopic examination of stained blood smear or bone marrow aspirate is still the most significant diagnostic methodology for initial AML screening and considered as the first step toward diagnosis. It is time-consuming and due to the elusive nature of the signs and symptoms of AML; wrong diagnosis may occur by pathologists. Therefore, the need for automation of leukemia detection has arisen. In this paper, an automatic technique for identification and detection of AML and its prevalent subtypes, i.e., M2-M5 is presented. At first, microscopic images are acquired from blood smears of patients with AML and normal cases. After applying image preprocessing, color segmentation strategy is applied for segmenting white blood cells from other blood components and then discriminative features, i.e., irregularity, nucleus-cytoplasm ratio, Hausdorff dimension, shape, color, and texture features are extracted from the entire nucleus in the whole images containing multiple nuclei. Images are classified to cancerous and noncancerous images by binary support vector machine (SVM) classifier with 10-fold cross validation technique. Classifier performance is evaluated by three parameters, i.e., sensitivity, specificity, and accuracy. Cancerous images are also classified into their prevalent subtypes by multi-SVM classifier. The results show that the proposed algorithm has achieved an acceptable performance for diagnosis of AML and its common subtypes. Therefore, it can be used as an assistant diagnostic tool for pathologists.

  3. Assessment of Machine Learning Algorithms for Automatic Benthic Cover Monitoring and Mapping Using Towed Underwater Video Camera and High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Hassan Mohamed

    2018-05-01

    Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.

  4. Automatic discovery of the communication network topology for building a supercomputer model

    Science.gov (United States)

    Sobolev, Sergey; Stefanov, Konstantin; Voevodin, Vadim

    2016-10-01

    The Research Computing Center of Lomonosov Moscow State University is developing the Octotron software suite for automatic monitoring and mitigation of emergency situations in supercomputers so as to maximize hardware reliability. The suite is based on a software model of the supercomputer. The model uses a graph to describe the computing system components and their interconnections. One of the most complex components of a supercomputer that needs to be included in the model is its communication network. This work describes the proposed approach for automatically discovering the Ethernet communication network topology in a supercomputer and its description in terms of the Octotron model. This suite automatically detects computing nodes and switches, collects information about them and identifies their interconnections. The application of this approach is demonstrated on the "Lomonosov" and "Lomonosov-2" supercomputers.

  5. AN OPTIMALIZATION OF NATURAL LIGHTING BY APPLYING AUTOMATIC LIGHTING USING MOTION SENSOR AND LUX SENSOR FOR HISTORICAL OLD BUILDINGS

    Directory of Open Access Journals (Sweden)

    Saeful Bahri

    2016-07-01

    Full Text Available ABSTRACT One of the problems that occurs within city centres, particularly within capital cities, is the existence of many historical old buildings. Historical old buildings within city centres, that have abandoned for years because of their condition, suffer from a lack of utilities, infrastructure and facilities [2][3]. These conditions occur because of low levels of maintenance arising as a consequence of a lack of finance of the owner of a building, be they government or private sector. To solve the problem of abandoned historical old buildings, the concept of adaptive reuse can be adopted and applied. This concept of adaptive reuse may continously cover the cost of building maintenance. The adaptive reuse concept usually covers the interior of a building and its utilities, though the need for utilities depends on the function of a building [4]. By adopting a concept of adaptive reuse, new building functions will be designed as the needs and demand of the market dictate, and which is appropriate for feasibility study. One utility element that has to be designed for historical old buildings is the provision of lighting within a building. To minimize the cost of building maintenance, one of the solutions is to optimize natural lighting and to minimize the use of artificial lighting such as lamps. This paper will discuss the extent to which artificial lighting can be minimized by using automatic lighting; the automatic lighting types discussed in this paper are lighting controlled by motion sensor and lux sensor. Keywords: Natural lighting, automatic lighting, motion sensor, lux sensor, historical old buildings ABSTRAK Salah satu permasalahan yang muncul dalam sebuah kota metropolitan, khususnya sebuah ibukota adalah keberadaan dari banyaknya bangunan-bangunan tua bersejarah. Bangunan-bangunan tua bersejarah dalam sebuah kota besar terutama yang diabaikan selama bertahun-tahun biasanya disebabkan karena kondisinya yang menua, minimnya utilitas

  6. Enhancing Three-dimensional Movement Control System for Assemblies of Machine-Building Facilities

    Science.gov (United States)

    Kuzyakov, O. N.; Andreeva, M. A.

    2018-01-01

    Aspects of enhancing three-dimensional movement control system are given in the paper. Such system is to be used while controlling assemblies of machine-building facilities, which is a relevant issue. The base of the system known is three-dimensional movement control device with optical principle of action. The device consists of multi point light emitter and light receiver matrix. The processing of signals is enhanced to increase accuracy of measurements by switching from discrete to analog signals. Light receiver matrix is divided into four areas, and the output value of each light emitter in each matrix area is proportional to its luminance level. Thus, determing output electric signal value of each light emitter in corresponding area leads to determing position of multipoint light emitter and position of object tracked. This is done by using Case-based reasoning method, the precedent in which is described as integral signal value of each matrix area, coordinates of light receivers, which luminance level is high, and decision to be made in this situation.

  7. Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid and Building-to-Grid Interface

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, Emma M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hendrix, Val [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Deka, Deepjyoti [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-16

    This white paper introduces the application of advanced data analytics to the modernized grid. In particular, we consider the field of machine learning and where it is both useful, and not useful, for the particular field of the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid and the building-to-grid interface. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. Machine learning is a subfield of computer science that studies and constructs algorithms that can learn from data and make predictions and improve forecasts. Incorporation of machine learning in grid monitoring and analysis tools may have the potential to solve data and operational challenges that result from increasing penetration of distributed and behind-the-meter energy resources. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors – such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals – such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis

  8. Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis.

    Science.gov (United States)

    Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

    2014-01-01

    Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. The aims were to describe how to:(i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and(ii) automatically identify the features that best distinguish the groups. The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described - simple or complex; presentation order - which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo 18 were used,which included 200 healthy Brazilians of both genders. A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods.

  9. Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis

    Directory of Open Access Journals (Sweden)

    Cíntia Matsuda Toledo

    Full Text Available Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario.OBJECTIVE: The aims were to describe how to: (i develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and (ii automatically identify the features that best distinguish the groups.METHODS: The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described - simple or complex; presentation order - which type of picture was described first; and age. In this study, the descriptions by 144 of the subjects studied in Toledo18 were used, which included 200 healthy Brazilians of both genders.RESULTS AND CONCLUSION:A Support Vector Machine (SVM with a radial basis function (RBF kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS is a strong candidate to replace manual feature selection methods.

  10. Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

    Science.gov (United States)

    Parida, G.; Rajan, K. S.

    2017-05-01

    The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

  11. LOCALIZED SEGMENT BASED PROCESSING FOR AUTOMATIC BUILDING EXTRACTION FROM LiDAR DATA

    Directory of Open Access Journals (Sweden)

    G. Parida

    2017-05-01

    Full Text Available The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

  12. a New Approach for the Semi-Automatic Texture Generation of the Buildings Facades, from Terrestrial Laser Scanner Data

    Science.gov (United States)

    Oniga, E.

    2012-07-01

    The result of the terrestrial laser scanning is an impressive number of spatial points, each of them being characterized as position by the X, Y and Z co-ordinates, by the value of the laser reflectance and their real color, expressed as RGB (Red, Green, Blue) values. The color code for each LIDAR point is taken from the georeferenced digital images, taken with a high resolution panoramic camera incorporated in the scanner system. In this article I propose a new algorithm for the semiautomatic texture generation, using the color information, the RGB values of every point that has been taken by terrestrial laser scanning technology and the 3D surfaces defining the buildings facades, generated with the Leica Cyclone software. The first step is when the operator defines the limiting value, i.e. the minimum distance between a point and the closest surface. The second step consists in calculating the distances, or the perpendiculars drawn from each point to the closest surface. In the third step we associate the points whose 3D coordinates are known, to every surface, depending on the limiting value. The fourth step consists in computing the Voronoi diagram for the points that belong to a surface. The final step brings automatic association between the RGB value of the color code and the corresponding polygon of the Voronoi diagram. The advantage of using this algorithm is that we can obtain, in a semi-automatic manner, a photorealistic 3D model of the building.

  13. Diagnostic information system dynamics in the evaluation of machine learning algorithms for the supervision of energy efficiency of district heating-supplied buildings

    International Nuclear Information System (INIS)

    Kiluk, Sebastian

    2017-01-01

    Highlights: • Energy efficiency classification sustainability benefits from knowledge prediction. • Diagnostic classification can be validated with its dynamics and current data. • Diagnostic classification dynamics provides novelty extraction for knowledge update. • Data mining comparison can be performed with knowledge dynamics and uncertainty. • Diagnostic information refinement benefits form comparing classifiers dynamics. - Abstract: Modern ways of exploring the diagnostic knowledge provided by data mining and machine learning raise some concern about the ways of evaluating the quality of output knowledge, usually represented by information systems. Especially in district heating, the stationarity of efficiency models, and thus the relevance of diagnostic classification system, cannot be ensured due to the impact of social, economic or technological changes, which are hard to identify or predict. Therefore, data mining and machine learning have become an attractive strategy for automatically and continuously absorbing such dynamics. This paper presents a new method of evaluation and comparison of diagnostic information systems gathered algorithmically in district heating efficiency supervision based on exploring the evolution of information system and analyzing its dynamic features. The process of data mining and knowledge discovery was applied to the data acquired from district heating substations’ energy meters to provide the automated discovery of diagnostic knowledge base necessary for the efficiency supervision of district heating-supplied buildings. The implemented algorithm consists of several steps of processing the billing data, including preparation, segmentation, aggregation and knowledge discovery stage, where classes of abstract models representing energy efficiency constitute an information system representing diagnostic knowledge about the energy efficiency of buildings favorably operating under similar climate conditions and

  14. Building Automatic Grading Tools for Basic of Programming Lab in an Academic Institution

    Science.gov (United States)

    Harimurti, Rina; Iwan Nurhidayat, Andi; Asmunin

    2018-04-01

    The skills of computer programming is a core competency that must be mastered by students majoring in computer sciences. The best way to improve this skill is through the practice of writing many programs to solve various problems from simple to complex. It takes hard work and a long time to check and evaluate the results of student labs one by one, especially if the number of students a lot. Based on these constrain, web proposes Automatic Grading Tools (AGT), the application that can evaluate and deeply check the source code in C, C++. The application architecture consists of students, web-based applications, compilers, and operating systems. Automatic Grading Tools (AGT) is implemented MVC Architecture and using open source software, such as laravel framework version 5.4, PostgreSQL 9.6, Bootstrap 3.3.7, and jquery library. Automatic Grading Tools has also been tested for real problems by submitting source code in C/C++ language and then compiling. The test results show that the AGT application has been running well.

  15. Semi-automatic building extraction in informal settlements from high-resolution satellite imagery

    Science.gov (United States)

    Mayunga, Selassie David

    The extraction of man-made features from digital remotely sensed images is considered as an important step underpinning management of human settlements in any country. Man-made features and buildings in particular are required for varieties of applications such as urban planning, creation of geographical information systems (GIS) databases and Urban City models. The traditional man-made feature extraction methods are very expensive in terms of equipment, labour intensive, need well-trained personnel and cannot cope with changing environments, particularly in dense urban settlement areas. This research presents an approach for extracting buildings in dense informal settlement areas using high-resolution satellite imagery. The proposed system uses a novel strategy of extracting building by measuring a single point at the approximate centre of the building. The fine measurement of the building outlines is then effected using a modified snake model. The original snake model on which this framework is based, incorporates an external constraint energy term which is tailored to preserving the convergence properties of the snake model; its use to unstructured objects will negatively affect their actual shapes. The external constrained energy term was removed from the original snake model formulation, thereby, giving ability to cope with high variability of building shapes in informal settlement areas. The proposed building extraction system was tested on two areas, which have different situations. The first area was Tungi in Dar Es Salaam, Tanzania where three sites were tested. This area is characterized by informal settlements, which are illegally formulated within the city boundaries. The second area was Oromocto in New Brunswick, Canada where two sites were tested. Oromocto area is mostly flat and the buildings are constructed using similar materials. Qualitative and quantitative measures were employed to evaluate the accuracy of the results as well as the performance

  16. The Scenario Approach to the Development of Strategy of Prevention of Raider Seizure for Machine-Building Enterprise

    Directory of Open Access Journals (Sweden)

    Momot Tetiana V.

    2017-12-01

    Full Text Available The article proposes the methodical approach to the choice and substantiation of efficiency of managerial decisions on ensuring economic safety at counteraction of raiding, based on an intellectual instrumental analysis. The ranking of alternatives of managerial decisions on the basis of the received weighted estimates and their fuzzy composition is used. A graphical interpretation of the membership functions of the calculated fuzzy expected utilities of management alternatives for the machine-building enterprises has been constructed and is presented.

  17. 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.

  18. 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.

  19. From Laser Scanning to Finite Element Analysis of Complex Buildings by Using a Semi-Automatic Procedure.

    Science.gov (United States)

    Castellazzi, Giovanni; D'Altri, Antonio Maria; Bitelli, Gabriele; Selvaggi, Ilenia; Lambertini, Alessandro

    2015-07-28

    In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sections. The complexity of the clouds is arbitrary, since the procedure is designed for terrestrial laser scanner surveys applied to buildings with irregular geometry, such as historical buildings. The procedure aims at solving the problems connected to the generation of finite element models of these complex structures by constructing a fine discretized geometry with a reduced amount of time and ready to be used with structural analysis. If the starting clouds represent the inner and outer surfaces of the structure, the resulting finite element model will accurately capture the whole three-dimensional structure, producing a complex solid made by voxel elements. A comparison analysis with a CAD-based model is carried out on a historical building damaged by a seismic event. The results indicate that the proposed procedure is effective and obtains comparable models in a shorter time, with an increased level of automation.

  20. Automatic Construction by Contour Crafting Technology

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Khorramshahi

    2017-07-01

    Full Text Available Contour Crafting is a novel technology in construction industry based on 3D printing that uses robotics to construct free form building structures by repeatedly laying down layers of material such as concrete. It is actually an approach to scale up automatic fabrication from building small industrial parts to constructing buildings. However, there are little information about contour crafting (CC in current use; present paper aims to describe the operational steps of creating a whole building by the machine reviewing relevant literature. Furthermore, it will represent the advantages of CC usage compared to traditional construction methods, as well as its applicability in construction industry.

  1. Automatic building extraction from LiDAR data fusion of point and grid-based features

    Science.gov (United States)

    Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

    2017-08-01

    This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

  2. Automatic Classification of Sub-Techniques in Classical Cross-Country Skiing Using a Machine Learning Algorithm on Micro-Sensor Data

    Directory of Open Access Journals (Sweden)

    Ole Marius Hoel Rindal

    2017-12-01

    Full Text Available The automatic classification of sub-techniques in classical cross-country skiing provides unique possibilities for analyzing the biomechanical aspects of outdoor skiing. This is currently possible due to the miniaturization and flexibility of wearable inertial measurement units (IMUs that allow researchers to bring the laboratory to the field. In this study, we aimed to optimize the accuracy of the automatic classification of classical cross-country skiing sub-techniques by using two IMUs attached to the skier’s arm and chest together with a machine learning algorithm. The novelty of our approach is the reliable detection of individual cycles using a gyroscope on the skier’s arm, while a neural network machine learning algorithm robustly classifies each cycle to a sub-technique using sensor data from an accelerometer on the chest. In this study, 24 datasets from 10 different participants were separated into the categories training-, validation- and test-data. Overall, we achieved a classification accuracy of 93.9% on the test-data. Furthermore, we illustrate how an accurate classification of sub-techniques can be combined with data from standard sports equipment including position, altitude, speed and heart rate measuring systems. Combining this information has the potential to provide novel insight into physiological and biomechanical aspects valuable to coaches, athletes and researchers.

  3. Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks

    International Nuclear Information System (INIS)

    Li Qiong; Meng Qinglin; Cai Jiejin; Yoshino, Hiroshi; Mochida, Akashi

    2009-01-01

    This study presents four modeling techniques for the prediction of hourly cooling load in the building. In addition to the traditional back propagation neural network (BPNN), the radial basis function neural network (RBFNN), general regression neural network (GRNN) and support vector machine (SVM) are considered. All the prediction models have been applied to an office building in Guangzhou, China. Evaluation of the prediction accuracy of the four models is based on the root mean square error (RMSE) and mean relative error (MRE). The simulation results demonstrate that the four discussed models can be effective for building cooling load prediction. The SVM and GRNN methods can achieve better accuracy and generalization than the BPNN and RBFNN methods

  4. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    Science.gov (United States)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  5. APPRAISAL OF ECONOMICAL EFFICIENCY OF APPLICATION OF FIBROUS LINING IN THERMAL GASPLASMA FURNACES AND FURNACES OF RESISTANCE OF MACHINE-BUILDING PRODUCTION

    Directory of Open Access Journals (Sweden)

    V. I. Timoshpolskij

    2011-01-01

    Full Text Available The carried out calculations showed that partial modernization of thermal furnaces of machine building production by means of replacement of chamotte by fibrous fettling is economically reasonable and has rather short period of payback.

  6. Manufacturing of cast fittings for power machine building using improved CO2-process

    International Nuclear Information System (INIS)

    Shuvalov, V.G.; Borodin, M.A.

    1984-01-01

    Technique for manufacturing of rods for casting fittings for power machines of heat and nuclear power plants using liquid-glass mixtures solidified by CO 2 is described. Optimal composition of mixtures and their basic technological properties were determined

  7. Support vector machine in prediction of building energy demand using pseudo dynamic approach

    NARCIS (Netherlands)

    Paudel, S.; Nguyen, H.P.; Kling, W.L.; Elmitri, Mohamed; Lacarriere, B.; Corre, le O.

    2015-01-01

    Building’s energy consumption prediction is a major concern in the recent years and many efforts have been achieved in order to improve the energy management of buildings. In particular, the prediction of energy consumption in building is essential for the energy operator to build an optimal

  8. Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

    Science.gov (United States)

    Zare, Marzieh; Rezvani, Zahra; Benasich, April A

    2016-07-01

    This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  9. Building Customer Churn Prediction Models in Fitness Industry with Machine Learning Methods

    OpenAIRE

    Shan, Min

    2017-01-01

    With the rapid growth of digital systems, churn management has become a major focus within customer relationship management in many industries. Ample research has been conducted for churn prediction in different industries with various machine learning methods. This thesis aims to combine feature selection and supervised machine learning methods for defining models of churn prediction and apply them on fitness industry. Forward selection is chosen as feature selection methods. Support Vector ...

  10. Determining the Efficiency of Adaptation of Foreign Economic Activity of Machine-Building Enterprises in Conditions of Deepening the European Integration Process of Ukraine

    Directory of Open Access Journals (Sweden)

    Semeniuk Iryna Yu.

    2018-02-01

    Full Text Available The article determines that introduction and implementation of the mechanism for foreign economic adaptation of machine-building enterprises to the conditions of the European integration processes requires constant monitoring of the processes of export-import operations and the adaptation activities to identify current problems and avoid risks. It has been found that one of the monitoring instruments is the system of indicators, which provides to evaluate the efficiency of use of the mechanism for foreign economic adaptation of a machine-building enterprise by comparing the values of the obtained indicators after accomplishing adaptation changes with the values of the indicators of previous periods. It is suggested to determine efficiency of adaptation of foreign economic activity of machine-building enterprises to conditions of deepening of the European integration process of Ukraine by means of: index of change of volume of exported production of a machine-building enterprise to the EU countries; weighted average of the change in the share of the European market, which is covered by the enterprise’s products; indicator of efficiency of exports of production of a machine-building enterprise to the European Union countries; indicator of the index of changes in the volume of permanent orders from European partners; integral indicator of efficiency of use of adaptive potential of a machine-building enterprise in conditions of integration processes.

  11. The development of damage identification methods for buildings with image recognition and machine learning techniques utilizing aerial photographs of the 2016 Kumamoto earthquake

    Science.gov (United States)

    Shohei, N.; Nakamura, H.; Fujiwara, H.; Naoichi, M.; Hiromitsu, T.

    2017-12-01

    It is important to get schematic information of the damage situation immediately after the earthquake utilizing photographs shot from an airplane in terms of the investigation and the decision-making for authorities. In case of the 2016 Kumamoto earthquake, we have acquired more than 1,800 orthographic projection photographs adjacent to damaged areas. These photos have taken between April 16th and 19th by airplanes, then we have distinguished damages of all buildings with 4 levels, and organized as approximately 296,000 GIS data corresponding to the fundamental Geospatial data published by Geospatial Information Authority of Japan. These data have organized by effort of hundreds of engineers. However, it is not considered practical for more extensive disasters like the Nankai Trough earthquake by only human powers. So, we have been developing the automatic damage identification method utilizing image recognition and machine learning techniques. First, we have extracted training data of more than 10,000 buildings which have equally damage levels divided in 4 grades. With these training data, we have been raster scanning in each scanning ranges of entire images, then clipping patch images which represents damage levels each. By utilizing these patch images, we have been developing discriminant models by two ways. One is a model using the Support Vector Machine (SVM). First, extract a feature quantity of each patch images. Then, with these vector values, calculate the histogram density as a method of Bag of Visual Words (BoVW), then classify borders with each damage grades by SVM. The other one is a model using the multi-layered Neural Network. First, design a multi-layered Neural Network. Second, input patch images and damage levels based on a visual judgement, and then, optimize learning parameters with error backpropagation method. By use of both discriminant models, we are going to discriminate damage levels in each patches, then create the image that shows

  12. Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

    Science.gov (United States)

    Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

    2017-01-01

    Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

  13. A Usability Study of the Automatic Ticket Vending Machines for the Middle-aged and Elderly Patrons: The Case of the Taipei Mass Rapid Transit System

    Directory of Open Access Journals (Sweden)

    Ming-Hsin Lu

    2015-12-01

    Full Text Available This study explores the usability problems for the middle-aged and elderly users of the automatic ticket vending machines of Taipei Mass Rapid Transit System. Thirty two middle-aged and elderly users (16 men and 16 females were observed in their actual uses of the machines, and 9 of them (6 men and 3 women were interviewed afterwards. The results show that, first, most senior users observed in this study made mistakes at the first step of touching the screen that initiates the ticket buying process. Second, the feedback and voice guidance design need further improvement to facilitate the senior users’ operation of the machines. Based on the findings, this study recommends that: (1 the operation instruction may be improved by enhancing the color contrast and graphics complementing of caption and voice guidance; (2 the transaction interface should be simplified, avoiding using button symbol to show information, and the visual instruction should be supplemented with voice instructions; (3 operation feedback should be strengthened and in line with previous use experience. [Article content in Chinese

  14. Building automatic customer complaints filtering application based on Twitter in Bahasa Indonesia

    Science.gov (United States)

    Gunawan, D.; Siregar, R. P.; Rahmat, R. F.; Amalia, A.

    2018-03-01

    Twitter has become a media to provide communication between a company with its customers. The average number of Twitter active users monthly is 330 million. A lot of companies realize the potential of Twitter to establish good relationship with their customers. Therefore, they usually have one official Twitter account to act as customer care division. In Indonesia, one of the company that utilizes the potential of Twitter to reach their customers is PT Telkom. PT Telkom has an official customer service account (called @TelkomCare) to receive customers’ problem. However, because of this account is open for public, Twitter users might post all kind of messages (not only complaints) to Telkom Care account. This leads to a problem that the Telkom Care account contains not only the customer complaints but also compliment and ordinary message. Furthermore, the complaints should be distributed to relevant division such as “Indihome”, “Telkomsel”, “UseeTV”, and “Telepon” based on the content of the message. This research built the application that automatically filter twitter post messages into several pre-defined categories (based on existing divisions) using Naïve Bayes algorithm. This research is done by collecting Twitter message, data cleaning, data pre-processing, training and testing data, and evaluate the classification result. This research yields 97% accuracy to classify Twitter message into the categories mentioned earlier.

  15. Automatic 3D building reconstruction from airbornelaser scanning and cadastral data using hough transform

    DEFF Research Database (Denmark)

    Bodum, Lars; Overby, Jens; Kjems, Erik

    2004-01-01

    degree of details. However, it is possible to create virtual 3D models of buildings, by processing these data. Roof polygons are generated using airborne laser scanning of 1x1 meter grid and ground plans (footprints) extracted from technical feature maps. An effective algorithm is used for fixing...... might lead to multiple slightly differing planes. Such planes are detected and merged. Intersecting planes are identified, and a polygon mesh of the roof is constructed. Due to the low precision of the laser scanning, a rule-based postprocessing of the roof is applied before adding the walls....

  16. Eddy-current guidance of the automatic inspection machine for the main vessel of the superphenix reactor

    International Nuclear Information System (INIS)

    David, B.; Pigeon, M.

    1985-01-01

    The weld detector device is an eddy-current measurement system consisting of four dual sensors (absolute + differential types), and a control cabinet with eight analog channels. The system delivers all the signals required for computing the correct track of the MIR machine along the welds, irrespective of bend, temperature, width and type of the seam, junctions of seams

  17. Automatic recognition of damaged town buildings caused by earthquake using remote sensing information: Taking the 2001 Bhuj, India, earthquake and the 1976 Tangshan, China, earthquake as examples

    Science.gov (United States)

    Liu, Jia-Hang; Shan, Xin-Jian; Yin, Jing-Yuan

    2004-11-01

    In the high-resolution images, the undamaged buildings generally show a natural textural feature, while the damaged or semi-damaged buildings always exhibit some low-grayscale blocks because of their coarsely damaged sections. If we use a proper threshold to classify the grayscale of image, some independent holes will appear in the damaged regions. By using such statistical information as the number of holes in every region, or the ratio between the area of holes and that of the region, etc, the damaged buildings can be separated from the undamaged, thus automatic detection of damaged buildings can be realized. Based on these characteristics, a new method to automatically detect the damage buildings by using regional structure and statistical information of texture is presented in the paper. In order to test its validity, 1-m-resolution iKonos merged image of the 2001 Bhuj earthquake and grayscale aerial photos of the 1976 Tangshan earthquake are selected as two examples to automatically detect the damaged buildings. Satisfied results are obtained.

  18. Building a Global Catalog of Nonvolcanic Tremor Events Using an Automatic Detection Algorithm

    Science.gov (United States)

    Bagley, B. C.; Revenaugh, J.

    2009-12-01

    Nonvolcanic tremor is characterized by a long-period seismic event containing a series of low-frequency earthquakes (LFEs). Tremor has been detected in regions of subduction (e.g. Kao et. al. 2007, 2008; Shelly 2006) and beneath the San Andreas fault near Cholame, California (e.g. Nadeau and Dolenc, 2005). In some cases tremor events seem to have periodicity, and these are often referred to as episodic tremor and slip (ETS). The origin of nonvolcanic tremor has been ascribed to shear slip along plate boundaries and/or high pore-fluid pressure. The apparent periodicity and tectonic setting associated with ETS has led to the suggestion that there may be a link between ETS and megathrust earthquakes. Until recently tremor detection has been a manual process requiring visual inspection of seismic data. In areas that have dense seismic arrays (e.g. Japan) waveform cross correlation techniques have been successfully employed (e.g. Obara, 2002). Kao et al. (2007) developed an algorithm for automatic detection of seismic tremor that can be used in regions without dense arrays. This method has been used to create the Tremor Activity Monitoring System (TAMS), which is used by the Geologic Survey of Canada to monitor northern Cascadia. So far the study of nonvolcanic tremor has been limited to regions of subduction or along major transform faults. It is unknown if tremor events occur in other tectonic settings, or if the current detection schemes will be useful for finding them. We propose to look for tremor events in non-subduction regions. It is possible that if tremor exists in other regions it will have different characteristics and may not trigger the TAMS system or be amenable to other existing detection schemes. We are developing algorithms for searching sparse array data sets for quasi-harmonic energy bursts in hopes of recognizing and cataloging nonvolcanic tremor in an expanded tectonic setting. Statistical comparisons against the TAMS algorithm will be made if

  19. Social collective intelligence: combining the powers of humans and machines to build a smarter society

    NARCIS (Netherlands)

    Miorandi, Daniele; Maltese, Vincenzo; Rovatsos, Michael; Nijholt, Antinus; Stewart, James

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and

  20. Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

    International Nuclear Information System (INIS)

    Chou, Jui-Sheng; Ngo, Ngoc-Tri

    2016-01-01

    Highlights: • This study develops a novel time-series sliding window forecast system. • The system integrates metaheuristics, machine learning and time-series models. • Site experiment of smart grid infrastructure is installed to retrieve real-time data. • The proposed system accurately predicts energy consumption in residential buildings. • The forecasting system can help users minimize their electricity usage. - Abstract: Smart grids are a promising solution to the rapidly growing power demand because they can considerably increase building energy efficiency. This study developed a novel time-series sliding window metaheuristic optimization-based machine learning system for predicting real-time building energy consumption data collected by a smart grid. The proposed system integrates a seasonal autoregressive integrated moving average (SARIMA) model and metaheuristic firefly algorithm-based least squares support vector regression (MetaFA-LSSVR) model. Specifically, the proposed system fits the SARIMA model to linear data components in the first stage, and the MetaFA-LSSVR model captures nonlinear data components in the second stage. Real-time data retrieved from an experimental smart grid installed in a building were used to evaluate the efficacy and effectiveness of the proposed system. A k-week sliding window approach is proposed for employing historical data as input for the novel time-series forecasting system. The prediction system yielded high and reliable accuracy rates in 1-day-ahead predictions of building energy consumption, with a total error rate of 1.181% and mean absolute error of 0.026 kW h. Notably, the system demonstrates an improved accuracy rate in the range of 36.8–113.2% relative to those of the linear forecasting model (i.e., SARIMA) and nonlinear forecasting models (i.e., LSSVR and MetaFA-LSSVR). Therefore, end users can further apply the forecasted information to enhance efficiency of energy usage in their buildings, especially

  1. 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.

  2. Generalized synthetic aperture radar automatic target recognition by convolutional neural network with joint use of two-dimensional principal component analysis and support vector machine

    Science.gov (United States)

    Zheng, Ce; Jiang, Xue; Liu, Xingzhao

    2017-10-01

    Convolutional neural network (CNN), as a vital part of the deep learning research field, has shown powerful potential for automatic target recognition (ATR) of synthetic aperture radar (SAR). However, the high complexity caused by the deep structure of CNN makes it difficult to generalize. An improved form of CNN with higher generalization capability and less probability of overfitting, which further improves the efficiency and robustness of the SAR ATR system, is proposed. The convolution layers of CNN are combined with a two-dimensional principal component analysis algorithm. Correspondingly, the kernel support vector machine is utilized as the classifier layer instead of the multilayer perceptron. The verification experiments are implemented using the moving and stationary target acquisition and recognition database, and the results validate the efficiency of the proposed method.

  3. Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

    Science.gov (United States)

    Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

    2015-11-01

    In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

  4. Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

    International Nuclear Information System (INIS)

    Gloger, Oliver; Völzke, Henry; Tönnies, Klaus; Mensel, Birger

    2015-01-01

    In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches. (paper)

  5. MO-G-BRE-04: Automatic Verification of Daily Treatment Deliveries and Generation of Daily Treatment Reports for a MR Image-Guided Treatment Machine

    International Nuclear Information System (INIS)

    Yang, D; Li, X; Li, H; Wooten, H; Green, O; Rodriguez, V; Mutic, S

    2014-01-01

    Purpose: Two aims of this work were to develop a method to automatically verify treatment delivery accuracy immediately after patient treatment and to develop a comprehensive daily treatment report to provide all required information for daily MR-IGRT review. Methods: After systematically analyzing the requirements for treatment delivery verification and understanding the available information from a novel MR-IGRT treatment machine, we designed a method to use 1) treatment plan files, 2) delivery log files, and 3) dosimetric calibration information to verify the accuracy and completeness of daily treatment deliveries. The method verifies the correctness of delivered treatment plans and beams, beam segments, and for each segment, the beam-on time and MLC leaf positions. Composite primary fluence maps are calculated from the MLC leaf positions and the beam-on time. Error statistics are calculated on the fluence difference maps between the plan and the delivery. We also designed the daily treatment delivery report by including all required information for MR-IGRT and physics weekly review - the plan and treatment fraction information, dose verification information, daily patient setup screen captures, and the treatment delivery verification results. Results: The parameters in the log files (e.g. MLC positions) were independently verified and deemed accurate and trustable. A computer program was developed to implement the automatic delivery verification and daily report generation. The program was tested and clinically commissioned with sufficient IMRT and 3D treatment delivery data. The final version has been integrated into a commercial MR-IGRT treatment delivery system. Conclusion: A method was developed to automatically verify MR-IGRT treatment deliveries and generate daily treatment reports. Already in clinical use since December 2013, the system is able to facilitate delivery error detection, and expedite physician daily IGRT review and physicist weekly chart

  6. Study of electric arc welding of castings for nuclear power machine-building

    International Nuclear Information System (INIS)

    Rymkevich, A.I.; Korsunov, P.M.

    1977-01-01

    Mechanical and corrosion-resistance properties are studied of the welded joints of cast billets from steel 00Kh12N3DL by automatic submerged arc welding. It is shown by testing the joints made with preheating up to 100 deg C and subsequent tempering (620 deg C for 25 h + 640 deg C for 16 h) that in the temperature range of 20-350 deg C they possess fairly good strength, ductility, impact viscosity, and corrosion-resistance properties approximating the corresponding characteristics of the base metal. The welding technology developed can be used to make pump casings for atomic power equipment

  7. Modified automatic teller machine prototype for older adults: a case study of participative approach to inclusive design.

    Science.gov (United States)

    Chan, Chetwyn C H; Wong, Alex W K; Lee, Tatia M C; Chi, Iris

    2009-03-01

    The goal of this study was to enhance an existing automated teller machine (ATM) human-machine interface in order to accommodate the needs of older adults. Older adults were involved in the design and field test of the modified ATM prototype. The design of the user interface and functionality took the cognitive and physical abilities of older adults into account. The modified ATM system included only "cash withdrawal" and "transfer" functions based on the task demands and needs for services of older adults. One hundred and forty-one older adults (aged 60 or above) participated in the field test by operating modified or existing ATM systems. Those who operated the modified system were found to have significantly higher success rates than those who operated the existing system. The enhancement was most significant among older adults who had lower ATM-related abilities, a lower level of education, and no prior experience of using ATMs. This study demonstrates the usefulness of using a universal design and participatory approach to modify the existing ATM system for use by older adults. However, it also leads to a reduction in functionality of the enhanced system. Future studies should explore ways to develop a universal design ATM system which can satisfy the abilities and needs of all users in the entire population.

  8. Spread of `Eco-vendor`, an energy-saving type automatic vending machine for beverages with a peak cut function; Shoenegata seiryo inryoyo jido hanbaiki (peak cut kino tsuki) `eko benda` no fukyu ni tsuite

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-05-01

    `Eco-vendor`, an energy-saving type automatic vending machine for beverages with a peak cut function has been developed in 1995 through cooperation by Tokyo Electric Power Company, Coca-Cola Japan, and Fuji Electric Co., Ltd. It can cut 90 percent of the power consumption during 13:00 to 16:00 on weekdays in summer, and can save 10 to 15 percent of annual power consumption. Since the heat insulation performance has been improved to keep beverages at the set temperature during the peak cut operation, the energy-saving effect for cold products in summer and for hot products in winter has been enhanced. For the manufacturing of `Eco-vendor`, Fuji Electric Co., Ltd. has offered its technical know-how to five manufacturers of automatic vending machine for beverages without compensation, and each manufacturer has accepted the offer. Electric power companies of Japan have cooperated to pay incident of 10,000 yen per an `Eco-vendor` to the manufacturers. Japan`s automatic vending machine industries and nationwide beverage industries have positively cooperated. Consequently, Tokyo Electric Power Company has successfully spread 2,600 machines up to the end of fiscal 1995, and aims at the spread of 16,000 machines in fiscal 1996. 2 figs.

  9. Social collective intelligence combining the powers of humans and machines to build a smarter society

    CERN Document Server

    Miorandi, Daniele; Rovatsos, Michael

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT.Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education

  10. GAPscreener: An automatic tool for screening human genetic association literature in PubMed using the support vector machine technique

    Directory of Open Access Journals (Sweden)

    Khoury Muin J

    2008-04-01

    Full Text Available Abstract Background Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM, a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. Results The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. Conclusion GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.

  11. Issues of human resources management in the enterprises of the machine-building complex of the Tyumen region

    Directory of Open Access Journals (Sweden)

    Lez’er Victoria

    2018-01-01

    Full Text Available This article, the authors have considered theoretical-methodological and practical aspects of human resource management in the process of restructuring enterprises of the machine-building complex of the Tyumen region. Based on the study of the evolution of theories concerning the human factor in the economy, the systematization and generalization of the provisions contained therein, the system of categories in the field of human resource management is substantiated. The basic principles of such management have been identified and supplemented, the tasks facing the enterprise management have been clarified, new tools for human resource management have been proposed, to ensure the completeness, continuity and validity of the decisions made in the field of human resources management in the restructuring of industrial enterprises.

  12. LiDAR The Generation of Automatic Mapping for Buildings, Using High Spatial Resolution Digital Vertical Aerial Photography and LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    William Barragán Zaque

    2015-06-01

    Full Text Available The aim of this paper is to generate photogrammetrie products and to automatically map buildings in the area of interest in vector format. The research was conducted Bogotá using high resolution digital vertical aerial photographs and point clouds obtained using LIDAR technology. Image segmentation was also used, alongside radiometric and geometric digital processes. The process took into account aspects including building height, segmentation algorithms, and spectral band combination. The results had an effectiveness of 97.2 % validated through ground-truthing.

  13. A topological insight into restricted Boltzmann machines (extented abstract)

    NARCIS (Netherlands)

    Mocanu, D.C.; Mocanu, E.; Nguyen, H.P.; Gibescu, M.; Liotta, A.

    2016-01-01

    Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep neural networks for automatic features extraction, unsupervised weights initialization, but also as standalone models for density estimation, activity recognition and so on.

  14. WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

    Directory of Open Access Journals (Sweden)

    A. Taravat

    2013-09-01

    Full Text Available As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method, synthetic aperture radar (SAR can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  15. Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

    Science.gov (United States)

    Taravat, A.; Del Frate, F.

    2013-09-01

    As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  16. Building an asynchronous web-based tool for machine learning classification.

    Science.gov (United States)

    Weber, Griffin; Vinterbo, Staal; Ohno-Machado, Lucila

    2002-01-01

    Various unsupervised and supervised learning methods including support vector machines, classification trees, linear discriminant analysis and nearest neighbor classifiers have been used to classify high-throughput gene expression data. Simpler and more widely accepted statistical tools have not yet been used for this purpose, hence proper comparisons between classification methods have not been conducted. We developed free software that implements logistic regression with stepwise variable selection as a quick and simple method for initial exploration of important genetic markers in disease classification. To implement the algorithm and allow our collaborators in remote locations to evaluate and compare its results against those of other methods, we developed a user-friendly asynchronous web-based application with a minimal amount of programming using free, downloadable software tools. With this program, we show that classification using logistic regression can perform as well as other more sophisticated algorithms, and it has the advantages of being easy to interpret and reproduce. By making the tool freely and easily available, we hope to promote the comparison of classification methods. In addition, we believe our web application can be used as a model for other bioinformatics laboratories that need to develop web-based analysis tools in a short amount of time and on a limited budget.

  17. Building a protein name dictionary from full text: a machine learning term extraction approach

    Directory of Open Access Journals (Sweden)

    Campagne Fabien

    2005-04-01

    Full Text Available Abstract Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

  18. Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: an annotation and machine learning study.

    Science.gov (United States)

    Skeppstedt, Maria; Kvist, Maria; Nilsson, Gunnar H; Dalianis, Hercules

    2014-06-01

    Automatic recognition of clinical entities in the narrative text of health records is useful for constructing applications for documentation of patient care, as well as for secondary usage in the form of medical knowledge extraction. There are a number of named entity recognition studies on English clinical text, but less work has been carried out on clinical text in other languages. This study was performed on Swedish health records, and focused on four entities that are highly relevant for constructing a patient overview and for medical hypothesis generation, namely the entities: Disorder, Finding, Pharmaceutical Drug and Body Structure. The study had two aims: to explore how well named entity recognition methods previously applied to English clinical text perform on similar texts written in Swedish; and to evaluate whether it is meaningful to divide the more general category Medical Problem, which has been used in a number of previous studies, into the two more granular entities, Disorder and Finding. Clinical notes from a Swedish internal medicine emergency unit were annotated for the four selected entity categories, and the inter-annotator agreement between two pairs of annotators was measured, resulting in an average F-score of 0.79 for Disorder, 0.66 for Finding, 0.90 for Pharmaceutical Drug and 0.80 for Body Structure. A subset of the developed corpus was thereafter used for finding suitable features for training a conditional random fields model. Finally, a new model was trained on this subset, using the best features and settings, and its ability to generalise to held-out data was evaluated. This final model obtained an F-score of 0.81 for Disorder, 0.69 for Finding, 0.88 for Pharmaceutical Drug, 0.85 for Body Structure and 0.78 for the combined category Disorder+Finding. The obtained results, which are in line with or slightly lower than those for similar studies on English clinical text, many of them conducted using a larger training data set, show that

  19. Expanding Options. A Model to Attract Secondary Students into Nontraditional Vocational Programs. For Emphasis in: Building Trades, Electronics, Health Services, Machine Shop, Welding.

    Science.gov (United States)

    Good, James D.; DeVore, Mary Ann

    This model has been designed for use by Missouri secondary schools in attracting females and males into nontraditional occupational programs. The research-based strategies are intended for implementation in the following areas: attracting females into building trades, electronics, machine shop, and welding; and males into secondary health…

  20. Machine Assistance in Collection Building: New Tools, Research, Issues, and Reflections

    Directory of Open Access Journals (Sweden)

    Steve Mitchell

    2006-12-01

    Full Text Available Digital tool making offers many challenges, involving much trial and error. Developing machine learning and assistance in automated and semi-automated Internet resource discovery, metadata generation, and rich-text identification provides opportunities for great discovery, innovation, and the potential for transformation of the library community. The areas of computer science involved, as applied to the library applications addressed, are among that discipline’s leading edges. Making applied research practical and applicable, through placement within library/collection-management systems and services, involves equal parts computer scientist, research librarian, and legacy-systems archaeologist. Still, the early harvest is there for us now, with a large harvest pending. Data Fountains and iVia, the projects discussed, demonstrate this. Clearly, then, the present would be a good time for the library community to more proactively and significantly engage with this technology and research, to better plan for its impacts, to more proactively take up the challenges involved in its exploration, and to better and more comprehensively guide effort in this new territory. The alternative to doing this is that others will develop this territory for us, do it not as well, and sell it back to us at a premium. Awareness of this technology and its current capabilities, promises, limitations, and probable major impacts needs to be generalized throughout the library management, metadata, and systems communities. This article charts recent work, promising avenues for new research and development, and issues the library community needs to understand.

  1. Building

    OpenAIRE

    Seavy, Ryan

    2014-01-01

    Building for concrete is temporary. The building of wood and steel stands against the concrete to give form and then gives way, leaving a trace of its existence behind. Concrete is not a building material. One does not build with concrete. One builds for concrete. MARCH

  2. RESEARCH OF THE LEVEL OF THE INNOVATIVE DEVELOPMENT OF THE MACHINE BUILDING ENTERPRISES OF UKRAINE IN KHARKOV REGION

    Directory of Open Access Journals (Sweden)

    Kateryna Koliedina

    2015-11-01

    Full Text Available In today’s world of the science and new technologies development all the countries including Ukraine are entrusted with a task of refocusing on the innovative way of evolution. The level of innovativeness of the country depends on the development of enterprises in this regard since exactly the industrial enterprises are able to induce the innovative process and be a multiplier of other economic sectors. Thus it is expedient to re-equip the industry of the state and encourage exactly the high-tech branches thereof. In this regard the goal of this paper is to explore and assess the influence of the criteria of innovative activity of the industrial enterprises on the level of the innovative development thereof. To reach the mentioned goal the criteria of innovative activity of the leading machine building enterprises of Ukraine in Kharkov region are chosen as the object of research. The studied enterprises are innovatively active in Kharkov region according to the criteria of the work thereof. The following criteria of innovative activity of the enterprises are chosen for analysis: the volume of the sold innovative products; the charges for innovation; the research intensity of the innovative products; the share of the studied enterprises in the total volume of the products sold in this region; the quantity of the new technological processes; the quantity of the new innovative kinds of products. The chosen criteria are important for enterprise in relation to the innovative activity and in case of changes have a substantial influence on its development and stability. Methodology. To research the level of innovative development of the machine building enterprises of Ukraine in Kharkov region the author prop: 1 Formation of the matrix of the basic data; 2 Standardization of the basic data; 3 Differentiation of the characteristics on inciters and disincentives; 4 Construction of the etalon; 5 Determination of the distance between the objects and

  3. Beyond the scope of Free-Wilson analysis: building interpretable QSAR models with machine learning algorithms.

    Science.gov (United States)

    Chen, Hongming; Carlsson, Lars; Eriksson, Mats; Varkonyi, Peter; Norinder, Ulf; Nilsson, Ingemar

    2013-06-24

    A novel methodology was developed to build Free-Wilson like local QSAR models by combining R-group signatures and the SVM algorithm. Unlike Free-Wilson analysis this method is able to make predictions for compounds with R-groups not present in a training set. Eleven public data sets were chosen as test cases for comparing the performance of our new method with several other traditional modeling strategies, including Free-Wilson analysis. Our results show that the R-group signature SVM models achieve better prediction accuracy compared with Free-Wilson analysis in general. Moreover, the predictions of R-group signature models are also comparable to the models using ECFP6 fingerprints and signatures for the whole compound. Most importantly, R-group contributions to the SVM model can be obtained by calculating the gradient for R-group signatures. For most of the studied data sets, a significant correlation with that of a corresponding Free-Wilson analysis is shown. These results suggest that the R-group contribution can be used to interpret bioactivity data and highlight that the R-group signature based SVM modeling method is as interpretable as Free-Wilson analysis. Hence the signature SVM model can be a useful modeling tool for any drug discovery project.

  4. Giro form reading machine

    Science.gov (United States)

    Minh Ha, Thien; Niggeler, Dieter; Bunke, Horst; Clarinval, Jose

    1995-08-01

    Although giro forms are used by many people in daily life for money remittance in Switzerland, the processing of these forms at banks and post offices is only partly automated. We describe an ongoing project for building an automatic system that is able to recognize various items printed or written on a giro form. The system comprises three main components, namely, an automatic form feeder, a camera system, and a computer. These components are connected in such a way that the system is able to process a bunch of forms without any human interactions. We present two real applications of our system in the field of payment services, which require the reading of both machine printed and handwritten information that may appear on a giro form. One particular feature of giro forms is their flexible layout, i.e., information items are located differently from one form to another, thus requiring an additional analysis step to localize them before recognition. A commercial optical character recognition software package is used for recognition of machine-printed information, whereas handwritten information is read by our own algorithms, the details of which are presented. The system is implemented by using a client/server architecture providing a high degree of flexibility to change. Preliminary results are reported supporting our claim that the system is usable in practice.

  5. Strategies for energy saving in buildings by means of automatic control; Estrategias de ahorro de energia en inmuebles mediante el control automatico

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Trujillo, Oscar [Johnson Controls de Mexico S. A. de C. V., Mexico, D. F. (Mexico)

    1998-12-31

    In this paper some of the measures and strategies for energy saving that can be applied in different types of buildings, mainly in hotels and office buildings, are presented. The proposed actions are accomplished with the aid of the automatic control equipment and the operation and/or maintenance personnel that supervises and establishes the control parameters of each one of the strategies than are focused to the appropriate utilization of the electric energy. [Espanol] En este documento se presentan algunas de las medidas y estrategias de ahorro de energia que pueden ser aplicadas en diferentes tipos de inmuebles, principalmente en hoteles y en edificios de oficinas. Las acciones propuestas son realizadas con la ayuda del equipo de control automatico y del personal de operacion y/o mantenimiento quien supervisa y establece los parametros de control de cada una de las estrategias que son destinadas a la buena utilizacion de la energia electrica.

  6. Strategies for energy saving in buildings by means of automatic control; Estrategias de ahorro de energia en inmuebles mediante el control automatico

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Trujillo, Oscar [Johnson Controls de Mexico S. A. de C. V., Mexico, D. F. (Mexico)

    1999-12-31

    In this paper some of the measures and strategies for energy saving that can be applied in different types of buildings, mainly in hotels and office buildings, are presented. The proposed actions are accomplished with the aid of the automatic control equipment and the operation and/or maintenance personnel that supervises and establishes the control parameters of each one of the strategies than are focused to the appropriate utilization of the electric energy. [Espanol] En este documento se presentan algunas de las medidas y estrategias de ahorro de energia que pueden ser aplicadas en diferentes tipos de inmuebles, principalmente en hoteles y en edificios de oficinas. Las acciones propuestas son realizadas con la ayuda del equipo de control automatico y del personal de operacion y/o mantenimiento quien supervisa y establece los parametros de control de cada una de las estrategias que son destinadas a la buena utilizacion de la energia electrica.

  7. 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

  8. Models of evaluating efficiency and risks on integration of cloud-base IT-services of the machine-building enterprise: a system approach

    Science.gov (United States)

    Razumnikov, S.; Kurmanbay, A.

    2016-04-01

    The present paper suggests a system approach to evaluation of the effectiveness and risks resulted from the integration of cloud-based services in a machine-building enterprise. This approach makes it possible to estimate a set of enterprise IT applications and choose the applications to be migrated to the cloud with regard to specific business requirements, a technological strategy and willingness to risk.

  9. RDFBuilder: a tool to automatically build RDF-based interfaces for MAGE-OM microarray data sources.

    Science.gov (United States)

    Anguita, Alberto; Martin, Luis; Garcia-Remesal, Miguel; Maojo, Victor

    2013-07-01

    This paper presents RDFBuilder, a tool that enables RDF-based access to MAGE-ML-compliant microarray databases. We have developed a system that automatically transforms the MAGE-OM model and microarray data stored in the ArrayExpress database into RDF format. Additionally, the system automatically enables a SPARQL endpoint. This allows users to execute SPARQL queries for retrieving microarray data, either from specific experiments or from more than one experiment at a time. Our system optimizes response times by caching and reusing information from previous queries. In this paper, we describe our methods for achieving this transformation. We show that our approach is complementary to other existing initiatives, such as Bio2RDF, for accessing and retrieving data from the ArrayExpress database. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  10. Automatic shading effects on the energetic performance of building systems; Efeito do sombreamento automatico no desempenho de sistemas prediais

    Energy Technology Data Exchange (ETDEWEB)

    Prado, Racine Tadeu Araujo

    1997-12-31

    This thesis develops a theoretic-experimental study dealing with the effects of an automatic shading device on the energetic performance of a dimmable lighting system and a cooling equipment. Some equations related to fenestration optical and thermal properties are rebuilt, while some others are created, under a theoretical approach. In order to collect field data, the energy demand-and other variables - was measured in two distinct stories, with the same fenestration features, of the Test Tower. New data was gathered after adding an automatic shading device to the window of one story. The comparison of the collected data allows the energetic performance evaluation of the shading device. (author) 136 refs., 55 figs., 6 tabs.

  11. Automatic shading effects on the energetic performance of building systems; Efeito do sombreamento automatico no desempenho de sistemas prediais

    Energy Technology Data Exchange (ETDEWEB)

    Prado, Racine Tadeu Araujo

    1996-12-31

    This thesis develops a theoretic-experimental study dealing with the effects of an automatic shading device on the energetic performance of a dimmable lighting system and a cooling equipment. Some equations related to fenestration optical and thermal properties are rebuilt, while some others are created, under a theoretical approach. In order to collect field data, the energy demand-and other variables - was measured in two distinct stories, with the same fenestration features, of the Test Tower. New data was gathered after adding an automatic shading device to the window of one story. The comparison of the collected data allows the energetic performance evaluation of the shading device. (author) 136 refs., 55 figs., 6 tabs.

  12. THE RESTRUCTURING AS STRATEGIC INSTRUMENT IN MANAGEMENT INDUSTRIAL ENTERPRISE RISK (ON EXAMPLE OF THE MACHINE-BUILDING ASSOCIATION «TRUD PLANT»

    Directory of Open Access Journals (Sweden)

    Vyzhitovich A. M.

    2015-06-01

    Full Text Available The Article is dedicated to questions of the analysis of the processes restructuring enterprise of machine building. The Presented problems to activity enterprise machine building. Studied the innovative experience of restructuring of one of the leading enterprises - «Machine-building “Trud Plant”» JSC. Restructuring is considered in the study as an important tool in risk management loss of competitiveness and financial stability. Possibility of refining the solution of actual problems of defining approaches to identify the main potential risks and threats to businesses that use restructuring to create a long-term competitive advantage in modern conditions. As the main tools for exploring the internal and external environment of the company proposed a method of SWOT-analysis, a method of grouping projects depending on the location of customers products based on publicly available sources of information. The research led to a number of conclusions: proposed methods help to identify key risks and threats, competitive advantage, the ability of enterprises in the light of the results of past and planned restructuring; study and synthesis of work experience of enterprises with the use of these methods generates suggestions on directions of the State support measures; restructuring strategy of risk management as a tool to retain relevance in the context of import substitution.

  13. Tendency of the 18-8 type corrosion-resistant steel to cracking in automatic building-up of copper and copper base alloys in argon

    International Nuclear Information System (INIS)

    Abramovich, V.R.; Andronik, V.A.

    1978-01-01

    Studied was the tendency of the 18-8 type corrosion-resistant steel to cracking during automatic building-up of copper and bronze in argon. The investigation was carried out on the 0kh18n10t steel in argon. It had been established, that the degree of copper penetration into the steel inceases with the increase in the time of the 0Kh18n10t steel contact with liquid copper. Liquid copper and copper base alloys have a detrimental effect on mechanical properties of the steel under external tensile load during intercontant. It is shown that in building-up of copper base alloys on the steel-0Kh18n10t, tendency of the steel to cracking decreases with increase in stiffness of a surfaced weld metal plate and with decrease in building-up energy per unit length. The causes of macrocracking in steel at building-up non-ferrous metals are explained. The technological procedures to avoid cracking are suggested

  14. Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

    Science.gov (United States)

    Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

    2017-09-01

    The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

  15. Semi-automatic identification of punching areas for tissue microarray building: the tubular breast cancer pilot study

    Directory of Open Access Journals (Sweden)

    Beltrame Francesco

    2010-11-01

    Full Text Available Abstract Background Tissue MicroArray technology aims to perform immunohistochemical staining on hundreds of different tissue samples simultaneously. It allows faster analysis, considerably reducing costs incurred in staining. A time consuming phase of the methodology is the selection of tissue areas within paraffin blocks: no utilities have been developed for the identification of areas to be punched from the donor block and assembled in the recipient block. Results The presented work supports, in the specific case of a primary subtype of breast cancer (tubular breast cancer, the semi-automatic discrimination and localization between normal and pathological regions within the tissues. The diagnosis is performed by analysing specific morphological features of the sample such as the absence of a double layer of cells around the lumen and the decay of a regular glands-and-lobules structure. These features are analysed using an algorithm which performs the extraction of morphological parameters from images and compares them to experimentally validated threshold values. Results are satisfactory since in most of the cases the automatic diagnosis matches the response of the pathologists. In particular, on a total of 1296 sub-images showing normal and pathological areas of breast specimens, algorithm accuracy, sensitivity and specificity are respectively 89%, 84% and 94%. Conclusions The proposed work is a first attempt to demonstrate that automation in the Tissue MicroArray field is feasible and it can represent an important tool for scientists to cope with this high-throughput technique.

  16. Do you want to build such a machine? : Designing a high energy proton accelerator for Argonne National Laboratory

    International Nuclear Information System (INIS)

    Paris, E.

    2004-01-01

    Argonne National Laboratory's efforts toward researching, proposing and then building a high-energy proton accelerator have been discussed in a handful of studies. In the main, these have concentrated on the intense maneuvering amongst politicians, universities, government agencies, outside corporations, and laboratory officials to obtain (or block) approval and/or funds or to establish who would have control over budgets and research programs. These ''top-down'' studies are very important but they can also serve to divorce such proceedings from the individuals actually involved in the ground-level research which physically served to create theories, designs, machines, and experiments. This can lead to a skewed picture, on the one hand, of a lack of effect that so-called scientific and technological factors exert and, on the other hand, of the apparent separation of the so-called social or political from the concrete practice of doing physics. An exception to this approach can be found in the proceedings of a conference on ''History of the ZGS'' held at Argonne at the time of the Zero Gradient Synchrotron's decommissioning in 1979. These accounts insert the individuals quite literally as they are, for the most part, personal reminiscences of those who took part in these efforts on the ground level. As such, they are invaluable raw material for historical inquiry but generally lack the rigor and perspective expected in a finished historical work. The session on ''Constructing Cold War Physics'' at the 2002 annual History of Science Society Meeting served to highlight new approaches circulating towards history of science and technology in the post-WWII period, especially in the 1950s. There is new attention towards the effects of training large numbers of scientists and engineers as well as the caution not to equate ''national security'' with military preparedness, but rather more broadly--at certain points--with the explicit ''struggle for the hearts and minds of

  17. Commercial effectiveness assessment of implementation the energy efficiency raising of the building project due to introduction of automatic heat consumption control

    Directory of Open Access Journals (Sweden)

    Zvonareva Yu.N.

    2017-01-01

    Full Text Available Introduction of the automated metering stations and regulation (AUU located directly in the heated building besides creation of comfortable conditions indoors leads to decrease in consumption of thermal energy. The annual expected effect of realization of the offered actions (installation of metering stations and automatic control can make up to 22% consumed and that isn–t less important, the paid thermal energy. In general, efficiency of implementation of the project on introduction of AUU can be characterized by considerable decrease in heat consumption of the building and, respectively, reduction of a payment for the consumed energy resources. In this paper we evaluated the effectiveness of implementation of increase of energy efficiency of the building investment project (hereinafter SP. We calculated the ratio of expenses and the results considered actions for inhabitants of an apartment house located in Kazan after installation of a weather-dependent regulation. As a result of calculation of the imitating model created on the basis of basic data and the investment project plan the main results of determination of economic efficiency of the Project have been received. For the analysis and increase of reliability of a settlement assessment of efficiency of the investment project calculations at different options of a set of basic data are executed.

  18. A study of the utility of heat collectors in reducing the response time of automatic fire sprinklers located in production modules of Building 707

    International Nuclear Information System (INIS)

    Shanley, J.H. Jr.; Budnick, E.K. Jr.

    1990-01-01

    Several of the ten production Modules in Building 707 at the Department of Energy Rocky Flats Plant recently underwent an alteration which can adversely affect the performance of the installed automatic fire sprinkler systems. The Modules have an approximate floor to ceiling height of 17.5 ft. The alterations involved removing the drop ceilings in the Modules which had been at a height of 12 ft above the floor. The sprinkler systems were originally installed with the sprinkler heads located below the drop ceiling in accordance with the nationally recognized NFPA 13, Standard for the Installation of Automatic Sprinkler Systems. The ceiling removal affects the sprinkler's response time and also violates NFPA 13. The scope of this study included evaluation of the feasibility of utilizing heat collectors to reduce the delays in sprinkler response created by the removal of the drop ceilings. The study also includes evaluation of substituting quick response sprinklers for the standard sprinklers currently in place, in combination with a heat collector

  19. 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.

  20. Machine learning: Trends, perspectives, and prospects.

    Science.gov (United States)

    Jordan, M I; Mitchell, T M

    2015-07-17

    Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.

  1. Do you want to build such a machine? : Designing a high energy proton accelerator for Argonne National Laboratory.

    Energy Technology Data Exchange (ETDEWEB)

    Paris, E.

    2004-04-05

    Argonne National Laboratory's efforts toward researching, proposing and then building a high-energy proton accelerator have been discussed in a handful of studies. In the main, these have concentrated on the intense maneuvering amongst politicians, universities, government agencies, outside corporations, and laboratory officials to obtain (or block) approval and/or funds or to establish who would have control over budgets and research programs. These ''top-down'' studies are very important but they can also serve to divorce such proceedings from the individuals actually involved in the ground-level research which physically served to create theories, designs, machines, and experiments. This can lead to a skewed picture, on the one hand, of a lack of effect that so-called scientific and technological factors exert and, on the other hand, of the apparent separation of the so-called social or political from the concrete practice of doing physics. An exception to this approach can be found in the proceedings of a conference on ''History of the ZGS'' held at Argonne at the time of the Zero Gradient Synchrotron's decommissioning in 1979. These accounts insert the individuals quite literally as they are, for the most part, personal reminiscences of those who took part in these efforts on the ground level. As such, they are invaluable raw material for historical inquiry but generally lack the rigor and perspective expected in a finished historical work. The session on ''Constructing Cold War Physics'' at the 2002 annual History of Science Society Meeting served to highlight new approaches circulating towards history of science and technology in the post-WWII period, especially in the 1950s. There is new attention towards the effects of training large numbers of scientists and engineers as well as the caution not to equate ''national security'' with military preparedness, but rather

  2. Automatic indexing, compiling and classification

    International Nuclear Information System (INIS)

    Andreewsky, Alexandre; Fluhr, Christian.

    1975-06-01

    A review of the principles of automatic indexing, is followed by a comparison and summing-up of work by the authors and by a Soviet staff from the Moscou INFORM-ELECTRO Institute. The mathematical and linguistic problems of the automatic building of thesaurus and automatic classification are examined [fr

  3. ESIP's Earth Science Knowledge Graph (ESKG) Testbed Project: An Automatic Approach to Building Interdisciplinary Earth Science Knowledge Graphs to Improve Data Discovery

    Science.gov (United States)

    McGibbney, L. J.; Jiang, Y.; Burgess, A. B.

    2017-12-01

    Big Earth observation data have been produced, archived and made available online, but discovering the right data in a manner that precisely and efficiently satisfies user needs presents a significant challenge to the Earth Science (ES) community. An emerging trend in information retrieval community is to utilize knowledge graphs to assist users in quickly finding desired information from across knowledge sources. This is particularly prevalent within the fields of social media and complex multimodal information processing to name but a few, however building a domain-specific knowledge graph is labour-intensive and hard to keep up-to-date. In this work, we update our progress on the Earth Science Knowledge Graph (ESKG) project; an ESIP-funded testbed project which provides an automatic approach to building a dynamic knowledge graph for ES to improve interdisciplinary data discovery by leveraging implicit, latent existing knowledge present within across several U.S Federal Agencies e.g. NASA, NOAA and USGS. ESKG strengthens ties between observations and user communities by: 1) developing a knowledge graph derived from various sources e.g. Web pages, Web Services, etc. via natural language processing and knowledge extraction techniques; 2) allowing users to traverse, explore, query, reason and navigate ES data via knowledge graph interaction. ESKG has the potential to revolutionize the way in which ES communities interact with ES data in the open world through the entity, spatial and temporal linkages and characteristics that make it up. This project enables the advancement of ESIP collaboration areas including both Discovery and Semantic Technologies by putting graph information right at our fingertips in an interactive, modern manner and reducing the efforts to constructing ontology. To demonstrate the ESKG concept, we will demonstrate use of our framework across NASA JPL's PO.DAAC, NOAA's Earth Observation Requirements Evaluation System (EORES) and various USGS

  4. Genesis machines

    CERN Document Server

    Amos, Martyn

    2014-01-01

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

  5. Construction and final assembly of an automatic arc welding machine; Construccion y puesta a punto de una maquina automatica para soldadura remota por arco bajo atmosfera inerte

    Energy Technology Data Exchange (ETDEWEB)

    Herrero Alvarez, J; Diaz Diaz, J; Diaz Diaz, J L

    1972-07-01

    It has been constructed a remote are welding machine, wholly transistorized, to be used in a Hot Cell of 1.000 Cu. In this work are presented the different parts of the equipment and its electronic description. Finally, some works of final preparation are shown such as ending of irradiation capsules, thermocouples welding, stainless steel cover welding. For these types of welding are quoted its relative programs. (Author)

  6. 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.

  7. Automatic garment template sewing technology based on machine identification%基于机器识别的全自动服装模板缝纫技术

    Institute of Scientific and Technical Information of China (English)

    张华玲; 戴斌辉; 原竞杰

    2016-01-01

    In view of the low efficiency of the traditional garment sewing process and dependence on the manual operation and other issues,a kind of automatic sewing technology of intelligent garment templates is put forward based on visual technology.The X/Y/Z direction of the three freedom mo-tion of the mechanical body is designed to complete the cutting and molding of the fabric,PVC,leath-er and other different materials.Then by using the teaching acquisition intelligent vision technology, the sample is automaticly generated to complete intelligent traj ectory planning,and drive sequential action of mechanical body through the embedded platform.The automation of garment sewing clothing is realized,improving the streamlined,standardized and efficient operations,decreasing the depend-ence of garment factory on skilled workers.%针对传统服装缝制工艺效率低且依赖于人工操作等问题,提出一种基于智能视觉技术的全自动服装模板缝纫技术。设计一个可沿 X/Y/Z 3个方向自由运动的机械本体,完成对面料、PVC、皮革等不同材料的裁剪和制模;运用智能视觉技术软件进行视教采集,自动生成样片完成智能轨迹规划并通过嵌入式平台驱动机械本体的顺序动作,实现服装缝制自动化,提高服装作业的流水化、标准化、高效化,降低服装厂对熟练工的依赖性。

  8. Comparing artificial neural networks, general linear models and support vector machines in building predictive models for small interfering RNAs.

    Directory of Open Access Journals (Sweden)

    Kyle A McQuisten

    2009-10-01

    Full Text Available Exogenous short interfering RNAs (siRNAs induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models.Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs, General Linear Models (GLMs and Support Vector Machines (SVMs. Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation.The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features found to result in maximally predictive models are

  9. Machine Learning examples on Invenio

    CERN Document Server

    CERN. Geneva

    2017-01-01

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

  10. 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...

  11. Automatic Training of Rat Cyborgs for Navigation.

    Science.gov (United States)

    Yu, Yipeng; Wu, Zhaohui; Xu, Kedi; Gong, Yongyue; Zheng, Nenggan; Zheng, Xiaoxiang; Pan, Gang

    2016-01-01

    A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat's behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs.

  12. Automatic Imitation

    Science.gov (United States)

    Heyes, Cecilia

    2011-01-01

    "Automatic imitation" is a type of stimulus-response compatibility effect in which the topographical features of task-irrelevant action stimuli facilitate similar, and interfere with dissimilar, responses. This article reviews behavioral, neurophysiological, and neuroimaging research on automatic imitation, asking in what sense it is "automatic"…

  13. Numerical simulator of the CANDU fueling machine driving desk

    International Nuclear Information System (INIS)

    Doca, Cezar

    2008-01-01

    As a national and European premiere, in the 2003 - 2005 period, at the Institute for Nuclear Research Pitesti two CANDU fueling machine heads, no.4 and no.5, for the Nuclear Power Plant Cernavoda - Unit 2 were successfully tested. To perform the tests of these machines, a special CANDU fueling machine testing rig was built and was (and is) available for this goal. The design of the CANDU fueling machine test rig from the Institute for Nuclear Research Pitesti is a replica of the similar equipment operating in CANDU 6 type nuclear power plants. High technical level of the CANDU fueling machine tests required the using of an efficient data acquisition and processing Computer Control System. The challenging goal was to build a computer system (hardware and software) designed and engineered to control the test and calibration process of these fuel handling machines. The design takes care both of the functionality required to correctly control the CANDU fueling machine and of the additional functionality required to assist the testing process. Both the fueling machine testing rig and staff had successfully assessed by the AECL representatives during two missions. At same the time, at the Institute for Nuclear Research Pitesti was/is developed a numerical simulator for the CANDU fueling machine operators training. The paper presents the numerical simulator - a special PC program (software) which simulates the graphics and the functions and the operations at the main desk of the computer control system. The simulator permits 'to drive' a CANDU fueling machine in two manners: manual or automatic. The numerical simulator is dedicated to the training of operators who operate the CANDU fueling machine in a nuclear power plant with CANDU reactor. (author)

  14. Machine Tool Software

    Science.gov (United States)

    1988-01-01

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

  15. 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

  16. 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.

  17. Development of a Model for Quantitative Assessment of Risks and Identification of Threats in Anti-Crisis Management of a Machine-Building Enterprise

    Directory of Open Access Journals (Sweden)

    Kozyk Vasyl V.

    2017-03-01

    Full Text Available The aim of the article is to develop a model for quantitative assessment of risks in anti-crisis management of a machine-building enterprise. The quantitative assessment will allow to identify among the risks the threats that can be considered as catastrophic risks. To assess the integral risk of anti-crisis management of the enterprise, there used a process approach distinguishing the process of anti-crisis management activity and the process of implementation of the anti-crisis program. Within the framework of the process the types of activity are singled out, for each of them risks are identified with revealing their reasons. There built a fuzzy hierarchical model comprising the following elements: terminal nodes — indicators (factors of risks; non-terminal nodes — separate risks that are characteristic for the processes and risks of each process as a whole; root of the tree — the integral risk of anti-crisis management. The expediency of building a hierarchical fuzzy model, within which conclusions are formed for intermediate variables, is substantiated. Based on the own research and taking into account the opinion of experts, the parameters of the trapezoidal membership functions for assessing indicators and risks are determined. Fuzzy bases of knowledge about the correlation are formed using the Mamdani algorithm. The adequacy of the model is estimated on the basis of the learning sample. The built fuzzy model makes it possible to obtain risk assessment based on the set values of the indicators, thus providing an analysis of the sensitivity of risks to various factors. It is easily adjusted to other conditions and types of economic activity of the enterprise.

  18. Classification of jet fuel properties by near-infrared spectroscopy using fuzzy rule-building expert systems and support vector machines.

    Science.gov (United States)

    Xu, Zhanfeng; Bunker, Christopher E; Harrington, Peter de B

    2010-11-01

    Monitoring the changes of jet fuel physical properties is important because fuel used in high-performance aircraft must meet rigorous specifications. Near-infrared (NIR) spectroscopy is a fast method to characterize fuels. Because of the complexity of NIR spectral data, chemometric techniques are used to extract relevant information from spectral data to accurately classify physical properties of complex fuel samples. In this work, discrimination of fuel types and classification of flash point, freezing point, boiling point (10%, v/v), boiling point (50%, v/v), and boiling point (90%, v/v) of jet fuels (JP-5, JP-8, Jet A, and Jet A1) were investigated. Each physical property was divided into three classes, low, medium, and high ranges, using two evaluations with different class boundary definitions. The class boundaries function as the threshold to alarm when the fuel properties change. Optimal partial least squares discriminant analysis (oPLS-DA), fuzzy rule-building expert system (FuRES), and support vector machines (SVM) were used to build the calibration models between the NIR spectra and classes of physical property of jet fuels. OPLS-DA, FuRES, and SVM were compared with respect to prediction accuracy. The validation of the calibration model was conducted by applying bootstrap Latin partition (BLP), which gives a measure of precision. Prediction accuracy of 97 ± 2% of the flash point, 94 ± 2% of freezing point, 99 ± 1% of the boiling point (10%, v/v), 98 ± 2% of the boiling point (50%, v/v), and 96 ± 1% of the boiling point (90%, v/v) were obtained by FuRES in one boundaries definition. Both FuRES and SVM obtained statistically better prediction accuracy over those obtained by oPLS-DA. The results indicate that combined with chemometric classifiers NIR spectroscopy could be a fast method to monitor the changes of jet fuel physical properties.

  19. Energy management systems in buildings

    Energy Technology Data Exchange (ETDEWEB)

    Lush, D. M.

    1979-07-01

    An investigation is made of the range of possibilities available from three types of systems (automatic control devices, building envelope, and the occupants) in buildings. The following subjects are discussed: general (buildings, design and personnel); new buildings (envelope, designers, energy and load calculations, plant design, general design parameters); existing buildings (conservation measures, general energy management, air conditioned buildings, industrial buildings); man and motivation (general, energy management and documentation, maintenance, motivation); automatic energy management systems (thermostatic controls, optimized plant start up, air conditioned and industrial buildings, building automatic systems). (MCW)

  20. HUMAN MACHINE COOPERATIVE TELEROBOTICS

    International Nuclear Information System (INIS)

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

    2003-01-01

    The remediation and deactivation and decommissioning (D and D) of nuclear waste storage tanks using telerobotics is one of the most challenging tasks faced in environmental cleanup. Since a number of tanks have reached the end of their design life and some of them have leaks, the unstructured, uncertain and radioactive environment makes the work inefficient and expensive. However, the execution time of teleoperation consumes ten to hundred times that of direct contact with an associated loss in quality. Thus, a considerable effort has been expended to improve the quality and efficiency of telerobotics by incorporating into teleoperation and robotic control functions such as planning, trajectory generation, vision, and 3-D modeling. One example is the Robot Task Space Analyzer (RTSA), which has been developed at the Robotics and Electromechanical Systems Laboratory (REMSL) at the University of Tennessee in support of the D and D robotic work at the Oak Ridge National Laboratory and the National Energy Technology Laboratory. This system builds 3-D models of the area of interest in task space through automatic image processing and/or human interactive manual modeling. The RTSA generates a task plan file, which describes the execution of a task including manipulator and tooling motions. The high level controller of the manipulator interprets the task plan file and executes the task automatically. Thus, if the environment is not highly unstructured, a tooling task, which interacts with environment, will be executed in the autonomous mode. Therefore, the RTSA not only increases the system efficiency, but also improves the system reliability because the operator will act as backstop for safe operation after the 3-D models and task plan files are generated. However, unstructured conditions of environment and tasks necessitate that the telerobot operates in the teleoperation mode for successful execution of task. The inefficiency in the teleoperation mode led to the

  1. HUMAN MACHINE COOPERATIVE TELEROBOTICS

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-06-30

    The remediation and deactivation and decommissioning (D&D) of nuclear waste storage tanks using telerobotics is one of the most challenging tasks faced in environmental cleanup. Since a number of tanks have reached the end of their design life and some of them have leaks, the unstructured, uncertain and radioactive environment makes the work inefficient and expensive. However, the execution time of teleoperation consumes ten to hundred times that of direct contact with an associated loss in quality. Thus, a considerable effort has been expended to improve the quality and efficiency of telerobotics by incorporating into teleoperation and robotic control functions such as planning, trajectory generation, vision, and 3-D modeling. One example is the Robot Task Space Analyzer (RTSA), which has been developed at the Robotics and Electromechanical Systems Laboratory (REMSL) at the University of Tennessee in support of the D&D robotic work at the Oak Ridge National Laboratory and the National Energy Technology Laboratory. This system builds 3-D models of the area of interest in task space through automatic image processing and/or human interactive manual modeling. The RTSA generates a task plan file, which describes the execution of a task including manipulator and tooling motions. The high level controller of the manipulator interprets the task plan file and executes the task automatically. Thus, if the environment is not highly unstructured, a tooling task, which interacts with environment, will be executed in the autonomous mode. Therefore, the RTSA not only increases the system efficiency, but also improves the system reliability because the operator will act as backstop for safe operation after the 3-D models and task plan files are generated. However, unstructured conditions of environment and tasks necessitate that the telerobot operates in the teleoperation mode for successful execution of task. The inefficiency in the teleoperation mode led to the research

  2. Grinding Parts For Automatic Welding

    Science.gov (United States)

    Burley, Richard K.; Hoult, William S.

    1989-01-01

    Rollers guide grinding tool along prospective welding path. Skatelike fixture holds rotary grinder or file for machining large-diameter rings or ring segments in preparation for welding. Operator grasps handles to push rolling fixture along part. Rollers maintain precise dimensional relationship so grinding wheel cuts precise depth. Fixture-mounted grinder machines surface to quality sufficient for automatic welding; manual welding with attendant variations and distortion not necessary. Developed to enable automatic welding of parts, manual welding of which resulted in weld bead permeated with microscopic fissures.

  3. Decomposition of the Strategic Plan for Restructuring a Machine-Building Enterprise in View of Continuity of the Plans for Adjacent Periods

    Directory of Open Access Journals (Sweden)

    Kozyr-Chepurna Mariia A.

    2017-09-01

    Full Text Available The aim of the article is to practically approve the authors’ multi-level hierarchical approach to the strategic planning of industrial enterprise restructuring using the example of solving the problem of disaggregating the strategic plan for restructuring a machine-building enterprise of the electrical industry providing for organization of production of railroad freight cars at the enterprise. Besides, there demonstrated the effectiveness of the mechanisms of coordinating the plans for adjacent hierarchical and time periods included in the corresponding mathematical support. In the course of the practical approval, different variants of formulating the problem of decomposing the strategic plan into plans of lower hierarchical levels differing in terms of coordination of the plans of adjacent hierarchical levels and adjacent planning periods are considered, and the solutions of corresponding optimal planning problems are analyzed. It is shown that the developed methodological approach, which is based on the methods of statistical optimization, demonstrates quite satisfactory performance characteristics in solving the problem of coordinating the plans of adjacent time periods in the mode of sliding planning in the process of decomposition of the strategic plan into lower-level plans.

  4. Automatic Earthquake Detection by Active Learning

    Science.gov (United States)

    Bergen, K.; Beroza, G. C.

    2017-12-01

    In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

  5. 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

  6. Massively collaborative machine learning

    NARCIS (Netherlands)

    Rijn, van J.N.

    2016-01-01

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

  7. AUTOMATIC ARCHITECTURAL STYLE RECOGNITION

    Directory of Open Access Journals (Sweden)

    M. Mathias

    2012-09-01

    Full Text Available Procedural modeling has proven to be a very valuable tool in the field of architecture. In the last few years, research has soared to automatically create procedural models from images. However, current algorithms for this process of inverse procedural modeling rely on the assumption that the building style is known. So far, the determination of the building style has remained a manual task. In this paper, we propose an algorithm which automates this process through classification of architectural styles from facade images. Our classifier first identifies the images containing buildings, then separates individual facades within an image and determines the building style. This information could then be used to initialize the building reconstruction process. We have trained our classifier to distinguish between several distinct architectural styles, namely Flemish Renaissance, Haussmannian and Neoclassical. Finally, we demonstrate our approach on various street-side images.

  8. Annual review in automatic programming

    CERN Document Server

    Goodman, Richard

    2014-01-01

    Annual Review in Automatic Programming, Volume 4 is a collection of papers that deals with the GIER ALGOL compiler, a parameterized compiler based on mechanical linguistics, and the JOVIAL language. A couple of papers describes a commercial use of stacks, an IBM system, and what an ideal computer program support system should be. One paper reviews the system of compilation, the development of a more advanced language, programming techniques, machine independence, and program transfer to other machines. Another paper describes the ALGOL 60 system for the GIER machine including running ALGOL pro

  9. Tool set for distributed real-time machine control

    Science.gov (United States)

    Carrott, Andrew J.; Wright, Christopher D.; West, Andrew A.; Harrison, Robert; Weston, Richard H.

    1997-01-01

    Demands for increased control capabilities require next generation manufacturing machines to comprise intelligent building elements, physically located at the point where the control functionality is required. Networks of modular intelligent controllers are increasingly designed into manufacturing machines and usable standards are slowly emerging. To implement a control system using off-the-shelf intelligent devices from multi-vendor sources requires a number of well defined activities, including (a) the specification and selection of interoperable control system components, (b) device independent application programming and (c) device configuration, management, monitoring and control. This paper briefly discusses the support for the above machine lifecycle activities through the development of an integrated computing environment populated with an extendable software toolset. The toolset supports machine builder activities such as initial control logic specification, logic analysis, machine modeling, mechanical verification, application programming, automatic code generation, simulation/test, version control, distributed run-time support and documentation. The environment itself consists of system management tools and a distributed object-oriented database which provides storage for the outputs from machine lifecycle activities and specific target control solutions.

  10. Self-Improving CNC Milling Machine

    OpenAIRE

    Spilling, Torjus

    2014-01-01

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

  11. 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...

  12. Low Speed Control for Automatic Welding

    Science.gov (United States)

    Iceland, W. E.

    1982-01-01

    Amplifier module allows rotating positioner of automatic welding machine to operate at speeds below normal range. Low speeds are precisely regulated by a servomechanism as are normal-range speeds. Addition of module to standard welding machine makes it unnecessary to purchase new equipment for low-speed welding.

  13. Cleaning and can end chamfering special machine MSCS-04

    International Nuclear Information System (INIS)

    Negulescu, D.; Rusu, A.; Dragomir, I.; Turcanu, V.; Bailescu, V.; Burcea, Gh.; Chitu, I.

    2001-01-01

    The MSCS-04 machine executes cleaning and can end chamfering of the CANDU 6 fuel element can through the following technologic chain: - manual positioning of the workpiece in the transporter feeding location; - the transport of the workpiece in front of the cleaning machine and workpiece orientation checking; - automatic loading of the workpiece in the cleaning machine; - bonding the workpiece in the cleaning machine; - cleaning the ends of the workpiece with graphite dust aspiration; - automatic disconnection of the workpiece from the cleaning machine; - automatic unloading of the cleaning machine; - disposal of the workpiece on the transporter in front of cleaning machine; workpiece's transport in front of the chamfering machine; - automatic checking of the workpiece orientation; - automatic loading of the workpiece in the chamfering machine; - axial positioning and bounding of the workpiece in the chamfering machine; chamfering the workpiece's ends with graphite dust and splinter aspiration; - disconnecting the workpiece from the chamfering machine; - automatic unloading of the workpiece from the chamfering machine with splinter blow from the workpiece interior; - workpiece disposal on transporter and the piece transport to the outlet. Details about the technological system, transport system, manipulators, cleaning and chamfering machines are given. Novel elements are highlighted and the technical characteristics are presented

  14. Optics, illumination, and image sensing for machine vision II

    International Nuclear Information System (INIS)

    Svetkoff, D.J.

    1987-01-01

    These proceedings collect papers on the general subject of machine vision. Topics include illumination and viewing systems, x-ray imaging, automatic SMT inspection with x-ray vision, and 3-D sensing for machine vision

  15. A method of numerically controlled machine part programming

    Science.gov (United States)

    1970-01-01

    Computer program is designed for automatically programmed tools. Preprocessor computes desired tool path and postprocessor computes actual commands causing machine tool to follow specific path. It is used on a Cincinnati ATC-430 numerically controlled machine tool.

  16. Theory and practice in machining systems

    CERN Document Server

    Ito, Yoshimi

    2017-01-01

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

  17. 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.

  18. 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…

  19. Hybrid genetic algorithm for minimizing non productive machining ...

    African Journals Online (AJOL)

    Minimization of non-productive time of tool during machining for 2.5 D milling significantly reduces the machining cost. The tool gets retracted and repositioned several times in multi pocket jobs during rough machining which consumes 15 to 30% of total machining time depending on the complexity of job. The automatic ...

  20. 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

  1. 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)

  2. Machine Translation from Text

    Science.gov (United States)

    Habash, Nizar; Olive, Joseph; Christianson, Caitlin; McCary, John

    Machine translation (MT) from text, the topic of this chapter, is perhaps the heart of the GALE project. Beyond being a well defined application that stands on its own, MT from text is the link between the automatic speech recognition component and the distillation component. The focus of MT in GALE is on translating from Arabic or Chinese to English. The three languages represent a wide range of linguistic diversity and make the GALE MT task rather challenging and exciting.

  3. MDSplus automated build and distribution system

    Energy Technology Data Exchange (ETDEWEB)

    Fredian, T., E-mail: twf@psfc.mit.edu [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States); Stillerman, J. [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States); Manduchi, G. [Consorzio RFX, Euratom-ENEA Association, Corso Stati Uniti 4, Padova 35127 (Italy)

    2014-05-15

    Support of the MDSplus data handling system has been enhanced by the addition of an automated build system which does nightly builds of MDSplus for many computer platforms producing software packages which can now be downloaded using a web browser or via package repositories suitable for automatic updating. The build system was implemented using an extensible continuous integration server product called Hudson which schedules software builds on a collection of VMware based virtual machines. New releases are created based on updates via the MDSplus cvs code repository and versioning are managed using cvs tags and branches. Currently stable, beta and alpha releases of MDSplus are maintained for eleven different platforms including Windows, MacOSX, RedHat Enterprise Linux, Fedora, Ubuntu and Solaris. For some of these platforms, MDSplus packaging has been broken into functional modules so users can pick and choose which MDSplus features they want to install. An added feature to the latest Linux based platforms is the use of package dependencies. When installing MDSplus from the package repositories, any additional required packages used by MDSplus will be installed automatically greatly simplifying the installation of MDSplus. This paper will describe the MDSplus package automated build and distribution system.

  4. MDSplus automated build and distribution system

    International Nuclear Information System (INIS)

    Fredian, T.; Stillerman, J.; Manduchi, G.

    2014-01-01

    Support of the MDSplus data handling system has been enhanced by the addition of an automated build system which does nightly builds of MDSplus for many computer platforms producing software packages which can now be downloaded using a web browser or via package repositories suitable for automatic updating. The build system was implemented using an extensible continuous integration server product called Hudson which schedules software builds on a collection of VMware based virtual machines. New releases are created based on updates via the MDSplus cvs code repository and versioning are managed using cvs tags and branches. Currently stable, beta and alpha releases of MDSplus are maintained for eleven different platforms including Windows, MacOSX, RedHat Enterprise Linux, Fedora, Ubuntu and Solaris. For some of these platforms, MDSplus packaging has been broken into functional modules so users can pick and choose which MDSplus features they want to install. An added feature to the latest Linux based platforms is the use of package dependencies. When installing MDSplus from the package repositories, any additional required packages used by MDSplus will be installed automatically greatly simplifying the installation of MDSplus. This paper will describe the MDSplus package automated build and distribution system

  5. Alignment of Custom Standards by Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Adela Sirbu

    2010-09-01

    Full Text Available Building an efficient model for automatic alignment of terminologies would bring a significant improvement to the information retrieval process. We have developed and compared two machine learning based algorithms whose aim is to align 2 custom standards built on a 3 level taxonomy, using kNN and SVM classifiers that work on a vector representation consisting of several similarity measures. The weights utilized by the kNN were optimized with an evolutionary algorithm, while the SVM classifier's hyper-parameters were optimized with a grid search algorithm. The database used for train was semi automatically obtained by using the Coma++ tool. The performance of our aligners is shown by the results obtained on the test set.

  6. 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...

  7. Build and Execute Environment

    Energy Technology Data Exchange (ETDEWEB)

    2017-04-21

    At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate

  8. Automatic operation of CSR Drayton coal stockyard. [Australia

    Energy Technology Data Exchange (ETDEWEB)

    Fauerbach, R

    1985-12-01

    The automatic remote control of the stackers and reclaimer at the coal stockyard of the CSR Drayton opencast coal mine in Australia is described. Each machine is controlled by an on-board programmable logic controller (PLC) which monitors the machine location in its working section in relation to the other machines and can halt operations should any danger of a collision be imminent.

  9. Annual review in automatic programming

    CERN Document Server

    Goodman, Richard

    2014-01-01

    Annual Review in Automatic Programming focuses on the techniques of automatic programming used with digital computers. Topics covered range from the design of machine-independent programming languages to the use of recursive procedures in ALGOL 60. A multi-pass translation scheme for ALGOL 60 is described, along with some commercial source languages. The structure and use of the syntax-directed compiler is also considered.Comprised of 12 chapters, this volume begins with a discussion on the basic ideas involved in the description of a computing process as a program for a computer, expressed in

  10. 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.

  11. Remote filter handling machine for Sizewell B

    International Nuclear Information System (INIS)

    Barker, D.

    1993-01-01

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

  12. The construction of the CMS electromagnetic calorimeter: automatic measurements of the physics parameters of PWO crystals

    CERN Multimedia

    2005-01-01

    Crystal properties (dimensions, optical transmission, light yield) are automatically measured. The pictures show different measurement stations of the automatic machine. Crystals are measured on trays containing five crystals each.

  13. Empirical Studies On Machine Learning Based Text Classification Algorithms

    OpenAIRE

    Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

    2011-01-01

    Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

  14. Semi-automatic fluoroscope

    International Nuclear Information System (INIS)

    Tarpley, M.W.

    1976-10-01

    Extruded aluminum-clad uranium-aluminum alloy fuel tubes must pass many quality control tests before irradiation in Savannah River Plant nuclear reactors. Nondestructive test equipment has been built to automatically detect high and low density areas in the fuel tubes using x-ray absorption techniques with a video analysis system. The equipment detects areas as small as 0.060-in. dia with 2 percent penetrameter sensitivity. These areas are graded as to size and density by an operator using electronic gages. Video image enhancement techniques permit inspection of ribbed cylindrical tubes and make possible the testing of areas under the ribs. Operation of the testing machine, the special low light level television camera, and analysis and enhancement techniques are discussed

  15. Principles of control automation of soil compacting machine operating mechanism

    Science.gov (United States)

    Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly

    2018-03-01

    The relevance of the qualitative compaction of soil bases in the erection of embankment and foundations in building and structure construction is given.The quality of the compactible gravel and sandy soils provides the bearing capability and, accordingly, the strength and durability of constructed buildings.It has been established that the compaction quality depends on many external actions, such as surface roughness and soil moisture; granulometry, chemical composition and degree of elasticity of originalfilled soil for compaction.The analysis of technological processes of soil bases compaction of foreign and domestic information sources showed that the solution of such important problem as a continuous monitoring of soil compaction actual degree in the process of machine operation carry out only with the use of modern means of automation. An effective vibrodynamic method of gravel and sand material sealing for the building structure foundations for various applications was justified and suggested.The method of continuous monitoring the soil compaction by measurement of the amplitudes and frequencies of harmonic oscillations on the compactible surface was determined, which allowed to determine the basic elements of facilities of soil compacting machine monitoring system of operating, etc. mechanisms: an accelerometer, a bandpass filter, a vibro-harmonics, an on-board microcontroller. Adjustable parameters have been established to improve the soil compaction degree and the soil compacting machine performance, and the adjustable parameter dependences on the overall indexhave been experimentally determined, which is the soil compaction degree.A structural scheme of automatic control of the soil compacting machine control mechanism and theoperation algorithm has been developed.

  16. Towards Automatic Classification of Exoplanet-Transit-Like Signals: A Case Study on Kepler Mission Data

    Science.gov (United States)

    Valizadegan, Hamed; Martin, Rodney; McCauliff, Sean D.; Jenkins, Jon Michael; Catanzarite, Joseph; Oza, Nikunj C.

    2015-08-01

    Building new catalogues of planetary candidates, astrophysical false alarms, and non-transiting phenomena is a challenging task that currently requires a reviewing team of astrophysicists and astronomers. These scientists need to examine more than 100 diagnostic metrics and associated graphics for each candidate exoplanet-transit-like signal to classify it into one of the three classes. Considering that the NASA Explorer Program's TESS mission and ESA's PLATO mission survey even a larger area of space, the classification of their transit-like signals is more time-consuming for human agents and a bottleneck to successfully construct the new catalogues in a timely manner. This encourages building automatic classification tools that can quickly and reliably classify the new signal data from these missions. The standard tool for building automatic classification systems is the supervised machine learning that requires a large set of highly accurate labeled examples in order to build an effective classifier. This requirement cannot be easily met for classifying transit-like signals because not only are existing labeled signals very limited, but also the current labels may not be reliable (because the labeling process is a subjective task). Our experiments with using different supervised classifiers to categorize transit-like signals verifies that the labeled signals are not rich enough to provide the classifier with enough power to generalize well beyond the observed cases (e.g. to unseen or test signals). That motivated us to utilize a new category of learning techniques, so-called semi-supervised learning, that combines the label information from the costly labeled signals, and distribution information from the cheaply available unlabeled signals in order to construct more effective classifiers. Our study on the Kepler Mission data shows that semi-supervised learning can significantly improve the result of multiple base classifiers (e.g. Support Vector Machines, Ada

  17. 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

  18. Using support vector machines to improve elemental ion identification in macromolecular crystal structures

    Energy Technology Data Exchange (ETDEWEB)

    Morshed, Nader [University of California, Berkeley, CA 94720 (United States); Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Echols, Nathaniel, E-mail: nechols@lbl.gov [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Adams, Paul D., E-mail: nechols@lbl.gov [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); University of California, Berkeley, CA 94720 (United States)

    2015-05-01

    A method to automatically identify possible elemental ions in X-ray crystal structures has been extended to use support vector machine (SVM) classifiers trained on selected structures in the PDB, with significantly improved sensitivity over manually encoded heuristics. In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific knowledge of metal-binding chemistry and scattering properties and is prone to error. A method has previously been described to identify ions based on manually chosen criteria for a number of elements. Here, the use of support vector machines (SVMs) to automatically classify isolated atoms as either solvent or one of various ions is described. Two data sets of protein crystal structures, one containing manually curated structures deposited with anomalous diffraction data and another with automatically filtered, high-resolution structures, were constructed. On the manually curated data set, an SVM classifier was able to distinguish calcium from manganese, zinc, iron and nickel, as well as all five of these ions from water molecules, with a high degree of accuracy. Additionally, SVMs trained on the automatically curated set of high-resolution structures were able to successfully classify most common elemental ions in an independent validation test set. This method is readily extensible to other elemental ions and can also be used in conjunction with previous methods based on a priori expectations of the chemical environment and X-ray scattering.

  19. Evaluation of automatic vacuum- assisted compaction solutions

    Directory of Open Access Journals (Sweden)

    M. Brzeziński

    2011-01-01

    Full Text Available Currently on the mould-making machines market the companies like: DiSA, KUENKEL WAGNER, HAFLINGER, HEINRICH WAGNER SINTO, HUNTER, SAVELLI AND TECHNICAL play significant role. These companies are the manufacturers of various solutions in machines and instalations applied in foundry engineering. Automatic foundry machines for compaction of green sand have the major role in mechanisation and automation processes of making the mould. The concept of operation of automatic machines is based on the static and dynamic methods of compacting the green sand. The method which gains the importance is the compacting method by using the energy of the air pressure. It's the initial stage or the supporting process of compacting the green sand. However in the automatic mould making machines using this method it's essential to use the additional compaction of the mass in order to receive the final parameters of the form. In the constructional solutions of the machines there is the additional division which concerns the method of putting the sand into the mould box. This division distinquishes the transport of the sand with simultaneous compaction or the putting of the sand without the pre-compaction. As the solutions of the major manufacturers are often the subject for application in various foundries, the authors of the paper would like/have the confidence to present their own evaluation process confirmed by their own researches and independent analysis of the producers' solutions.

  20. 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.

  1. 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.

  2. 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)

  3. 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

  4. 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.

  5. Tangent: Automatic Differentiation Using Source Code Transformation in Python

    OpenAIRE

    van Merriënboer, Bart; Wiltschko, Alexander B.; Moldovan, Dan

    2017-01-01

    Automatic differentiation (AD) is an essential primitive for machine learning programming systems. Tangent is a new library that performs AD using source code transformation (SCT) in Python. It takes numeric functions written in a syntactic subset of Python and NumPy as input, and generates new Python functions which calculate a derivative. This approach to automatic differentiation is different from existing packages popular in machine learning, such as TensorFlow and Autograd. Advantages ar...

  6. Machine Learning Approaches Toward Building Predictive Models for Small Molecule Modulators of miRNA and Its Utility in Virtual Screening of Molecular Databases.

    Science.gov (United States)

    Periwal, Vinita; Scaria, Vinod

    2017-01-01

    The ubiquitous role of microRNAs (miRNAs) in a number of pathological processes has suggested that they could act as potential drug targets. RNA-binding small molecules offer an attractive means for modulating miRNA function. The availability of bioassay data sets for a variety of biological assays and molecules in public domain provides a new opportunity toward utilizing them to create models and further utilize them for in silico virtual screening approaches to prioritize or assign potential functions for small molecules. Here, we describe a computational strategy based on machine learning for creation of predictive models from high-throughput biological screens for virtual screening of small molecules with the potential to inhibit microRNAs. Such models could be potentially used for computational prioritization of small molecules before performing high-throughput biological assay.

  7. Current Technologies and its Trends of Machine Vision in the Field of Security and Disaster Prevention

    Science.gov (United States)

    Hashimoto, Manabu; Fujino, Yozo

    Image sensing technologies are expected as useful and effective way to suppress damages by criminals and disasters in highly safe and relieved society. In this paper, we describe current important subjects, required functions, technical trends, and a couple of real examples of developed system. As for the video surveillance, recognition of human trajectory and human behavior using image processing techniques are introduced with real examples about the violence detection for elevators. In the field of facility monitoring technologies as civil engineering, useful machine vision applications such as automatic detection of concrete cracks on walls of a building or recognition of crowded people on bridge for effective guidance in emergency are shown.

  8. Research on wireless communication technology based on automatic logistics system of welder

    Directory of Open Access Journals (Sweden)

    Sun Xuan

    2018-01-01

    Full Text Available In order to meet the requirements of high real-time and high stability of data transmission in automatic welding system, RTU data format and real-time communication mechanism are adopted in this system. In the automatic logistics system through the Ethernet and wireless WIFI technology will palletizer, stacker, AGV car organically together to complete the palletizer automatic crawling the goods, AGV car automatic delivery, stacking machine automatically out of the Dimensional warehouse. .

  9. Research on wireless communication technology based on automatic logistics system of welder

    OpenAIRE

    Sun Xuan; Wang Zhi-yong; Ma Zhe-dong

    2018-01-01

    In order to meet the requirements of high real-time and high stability of data transmission in automatic welding system, RTU data format and real-time communication mechanism are adopted in this system. In the automatic logistics system through the Ethernet and wireless WIFI technology will palletizer, stacker, AGV car organically together to complete the palletizer automatic crawling the goods, AGV car automatic delivery, stacking machine automatically out of the Dimensional warehouse. .

  10. 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 ...

  11. Reversible machine code and its abstract processor architecture

    DEFF Research Database (Denmark)

    Axelsen, Holger Bock; Glück, Robert; Yokoyama, Tetsuo

    2007-01-01

    A reversible abstract machine architecture and its reversible machine code are presented and formalized. For machine code to be reversible, both the underlying control logic and each instruction must be reversible. A general class of machine instruction sets was proven to be reversible, building...

  12. 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.

  13. 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.

  14. Game-powered machine learning.

    Science.gov (United States)

    Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

    2012-04-24

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

  15. 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.

  16. First neutrons from new machine

    International Nuclear Information System (INIS)

    Gray, D.A.

    1985-01-01

    Nimrod, the last weak focusing proton machine to be built, provided its first 7 GeV proton beam in 1963 and provided the research fuel for several generations of UK particle physicists. With the decision to build the SNS, the task was to transform the existing facility into a high repetition rate, high intensity machine furnishing the protons to bombard a neutron production target. As well as equipment from Nimrod, the SNS synchrotron also makes use of components from the old NINA electron machine at Daresbury, closed down in 1977. (orig./HSI).

  17. Automatic building LOD copies for multitextured objects

    Science.gov (United States)

    Souetov, Andrew E.

    2000-01-01

    This article is dedicated to the research of geometry level of detail technology for systems of real-time 3D visualization. The article includes the conditions of applicability of the method, overview of existing approaches, their drawbacks and advantages. New technology guidelines are suggested as an alternative to existing methods.

  18. Automatic extraction of drug indications from FDA drug labels.

    Science.gov (United States)

    Khare, Ritu; Wei, Chih-Hsuan; Lu, Zhiyong

    2014-01-01

    Extracting computable indications, i.e. drug-disease treatment relationships, from narrative drug resources is the key for building a gold standard drug indication repository. The two steps to the extraction problem are disease named-entity recognition (NER) to identify disease mentions from a free-text description and disease classification to distinguish indications from other disease mentions in the description. While there exist many tools for disease NER, disease classification is mostly achieved through human annotations. For example, we recently resorted to human annotations to prepare a corpus, LabeledIn, capturing structured indications from the drug labels submitted to FDA by pharmaceutical companies. In this study, we present an automatic end-to-end framework to extract structured and normalized indications from FDA drug labels. In addition to automatic disease NER, a key component of our framework is a machine learning method that is trained on the LabeledIn corpus to classify the NER-computed disease mentions as "indication vs. non-indication." Through experiments with 500 drug labels, our end-to-end system delivered 86.3% F1-measure in drug indication extraction, with 17% improvement over baseline. Further analysis shows that the indication classifier delivers a performance comparable to human experts and that the remaining errors are mostly due to disease NER (more than 50%). Given its performance, we conclude that our end-to-end approach has the potential to significantly reduce human annotation costs.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

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

  5. Automatic EEG spike detection.

    Science.gov (United States)

    Harner, Richard

    2009-10-01

    Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

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

    Science.gov (United States)

    Hildebrandt, Mireille

    2017-01-01

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

  7. 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...

  8. SRV-automatic handling device

    International Nuclear Information System (INIS)

    Yamada, Koji

    1987-01-01

    Automatic handling device for the steam relief valves (SRV's) is developed in order to achieve a decrease in exposure of workers, increase in availability factor, improvement in reliability, improvement in safety of operation, and labor saving. A survey is made during a periodical inspection to examine the actual SVR handling operation. An SRV automatic handling device consists of four components: conveyor, armed conveyor, lifting machine, and control/monitoring system. The conveyor is so designed that the existing I-rail installed in the containment vessel can be used without any modification. This is employed for conveying an SRV along the rail. The armed conveyor, designed for a box rail, is used for an SRV installed away from the rail. By using the lifting machine, an SRV installed away from the I-rail is brought to a spot just below the rail so that the SRV can be transferred by the conveyor. The control/monitoring system consists of a control computer, operation panel, TV monitor and annunciator. The SRV handling device is operated by remote control from a control room. A trial equipment is constructed and performance/function testing is carried out using actual SRV's. As a result, is it shown that the SRV handling device requires only two operators to serve satisfactorily. The required time for removal and replacement of one SRV is about 10 minutes. (Nogami, K.)

  9. 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...

  10. On The Subject of Thinking Machines

    OpenAIRE

    Olafenwa , John ,; Olafenwa , Moses

    2018-01-01

    An investigation of the concepts of thoughts, imagination and consciousness in learning machines.; 68 years ago, Alan Turing proposed the question "Can Machines Think" in his seminal paper [1] titled "Computing Machinery and Intelligence" and he formulated the "Imitation Game" also known as the Turing test as a way to answer this question without referring to a rather ambiguous dictionary definition of the word "Think" We have come a long way to building intelligent machines, in fact, the rat...

  11. The Three Pillars of Machine Programming

    OpenAIRE

    Gottschlich, Justin; Solar-Lezama, Armando; Tatbul, Nesime; Carbin, Michael; Rinard, Martin; Barzilay, Regina; Amarasinghe, Saman; Tenenbaum, Joshua B; Mattson, Tim

    2018-01-01

    In this position paper, we describe our vision of the future of machine programming through a categorical examination of three pillars of research. Those pillars are: (i) intention, (ii) invention, and(iii) adaptation. Intention emphasizes advancements in the human-to-computer and computer-to-machine-learning interfaces. Invention emphasizes the creation or refinement of algorithms or core hardware and software building blocks through machine learning (ML). Adaptation emphasizes advances in t...

  12. 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.

  13. Machine en theater : ontwerpconcepten van winkelgebouwen

    NARCIS (Netherlands)

    Kooyman, D.

    1999-01-01

    Machine and Theater. Design Concepts for Shop Buildings Most retail trade takes place in shops. For retailers a shop is the physical context for their commercial activities. Consumers spend a substantial amount of their time there, making essential purchases and also window shopping. Machine and

  14. Remote handling machines

    International Nuclear Information System (INIS)

    Sato, Shinri

    1985-01-01

    In nuclear power facilities, the management of radioactive wastes is made with its technology plus the automatic techniques. Under the radiation field, the maintenance or aid of such systems is important. To cope with this situation, MF-2 system, MF-3 system and a manipulator system as remote handling machines are described. MF-2 system consists of an MF-2 carrier truck, a control unit and a command trailer. It is capable of handling heavy-weight objects. The system is not by hydraulic but by electrical means. MF-3 system consists of a four-crawler truck and a manipulator. The truck is versatile in its posture by means of the four independent crawlers. The manipulator system is bilateral in operation, so that the delicate handling is made possible. (Mori, K.)

  15. Machine en theater : ontwerpconcepten van winkelgebouwen

    OpenAIRE

    Kooyman, D.

    1999-01-01

    Machine and Theater. Design Concepts for Shop Buildings Most retail trade takes place in shops. For retailers a shop is the physical context for their commercial activities. Consumers spend a substantial amount of their time there, making essential purchases and also window shopping. Machine and theatre, design concepts for shop buildings investigates the function and the significance of shop space. The arcade, the department store, the supermarket, the shopping centre, the big-box retail par...

  16. Operating System For Numerically Controlled Milling Machine

    Science.gov (United States)

    Ray, R. B.

    1992-01-01

    OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

  17. Probabilistic machine learning and artificial intelligence.

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-28

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

  18. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

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

  19. The Engineering Of PCB Processing Machine

    International Nuclear Information System (INIS)

    Handoyo, Demon; Satmoko, Ari; T, Sapta; Heru, G. B.

    2001-01-01

    The engineering of PCB processing machine had been done. Purposes of the engineering of PCB processing machine are used to process PCB and to get the data's of characteristic of PCB processing. Further, these data's will be used as setting point when processing of PCB is done with manual and automatic control. The method of processing of PCB are inserting and pulling of the PCB rack to and from Ferro chlorite using electrical motor to corrosive Cu shield parts witch is not used. The experiment have result that the characteristic of operation of PCB processing machine as we hope when designing

  20. 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...

  1. 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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  3. Document Classification Using Distributed Machine Learning

    OpenAIRE

    Aydin, Galip; Hallac, Ibrahim Riza

    2018-01-01

    In this paper, we investigate the performance and success rates of Na\\"ive Bayes Classification Algorithm for automatic classification of Turkish news into predetermined categories like economy, life, health etc. We use Apache Big Data technologies such as Hadoop, HDFS, Spark and Mahout, and apply these distributed technologies to Machine Learning.

  4. Finding weak points automatically

    International Nuclear Information System (INIS)

    Archinger, P.; Wassenberg, M.

    1999-01-01

    Operators of nuclear power stations have to carry out material tests at selected components by regular intervalls. Therefore a full automaticated test, which achieves a clearly higher reproducibility, compared to part automaticated variations, would provide a solution. In addition the full automaticated test reduces the dose of radiation for the test person. (orig.) [de

  5. Behind the machines

    CERN Multimedia

    Laëtitia Pedroso

    2010-01-01

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

  6. Refining Automatically Extracted Knowledge Bases Using Crowdsourcing

    OpenAIRE

    Li, Chunhua; Zhao, Pengpeng; Sheng, Victor S.; Xian, Xuefeng; Wu, Jian; Cui, Zhiming

    2017-01-01

    Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality i...

  7. 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....

  8. 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.)

  9. Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

    Science.gov (United States)

    Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

    2017-07-01

    Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

  10. Automatic incrementalization of Prolog based static analyses

    DEFF Research Database (Denmark)

    Eichberg, Michael; Kahl, Matthias; Saha, Diptikalyan

    2007-01-01

    Modem development environments integrate various static analyses into the build process. Analyses that analyze the whole project whenever the project changes are impractical in this context. We present an approach to automatic incrementalization of analyses that are specified as tabled logic prog...

  11. Oocytes Polar Body Detection for Automatic Enucleation

    Directory of Open Access Journals (Sweden)

    Di Chen

    2016-02-01

    Full Text Available Enucleation is a crucial step in cloning. In order to achieve automatic blind enucleation, we should detect the polar body of the oocyte automatically. The conventional polar body detection approaches have low success rate or low efficiency. We propose a polar body detection method based on machine learning in this paper. On one hand, the improved Histogram of Oriented Gradient (HOG algorithm is employed to extract features of polar body images, which will increase success rate. On the other hand, a position prediction method is put forward to narrow the search range of polar body, which will improve efficiency. Experiment results show that the success rate is 96% for various types of polar bodies. Furthermore, the method is applied to an enucleation experiment and improves the degree of automatic enucleation.

  12. Automatic welding of stainless steel tubing

    Science.gov (United States)

    Clautice, W. E.

    1978-01-01

    The use of automatic welding for making girth welds in stainless steel tubing was investigated as well as the reduction in fabrication costs resulting from the elimination of radiographic inspection. Test methodology, materials, and techniques are discussed, and data sheets for individual tests are included. Process variables studied include welding amperes, revolutions per minute, and shielding gas flow. Strip chart recordings, as a definitive method of insuring weld quality, are studied. Test results, determined by both radiographic and visual inspection, are presented and indicate that once optimum welding procedures for specific sizes of tubing are established, and the welding machine operations are certified, then the automatic tube welding process produces good quality welds repeatedly, with a high degree of reliability. Revised specifications for welding tubing using the automatic process and weld visual inspection requirements at the Kennedy Space Center are enumerated.

  13. Building Artificial Vision Systems with Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    LeCun, Yann [New York University

    2011-02-23

    Three questions pose the next challenge for Artificial Intelligence (AI), robotics, and neuroscience. How do we learn perception (e.g. vision)? How do we learn representations of the perceptual world? How do we learn visual categories from just a few examples?

  14. Evolution of the ATLAS Nightly Build System

    International Nuclear Information System (INIS)

    Undrus, A

    2012-01-01

    The ATLAS Nightly Build System is a major component in the ATLAS collaborative software organization, validation, and code approval scheme. For over 10 years of development it has evolved into a factory for automatic release production and grid distribution. The 50 multi-platform branches of ATLAS releases provide vast opportunities for testing new packages, verification of patches to existing software, and migration to new platforms and compilers for ATLAS code that currently contains 2200 packages with 4 million C++ and 1.4 million python scripting lines written by about 1000 developers. Recent development was focused on the integration of ATLAS Nightly Build and Installation systems. The nightly releases are distributed and validated and some are transformed into stable releases used for data processing worldwide. The ATLAS Nightly System is managed by the NICOS control tool on a computing farm with 50 powerful multiprocessor nodes. NICOS provides the fully automated framework for the release builds, testing, and creation of distribution kits. The ATN testing framework of the Nightly System runs unit and integration tests in parallel suites, fully utilizing the resources of multi-core machines, and provides the first results even before compilations complete. The NICOS error detection system is based on several techniques and classifies the compilation and test errors according to their severity. It is periodically tuned to place greater emphasis on certain software defects by highlighting the problems on NICOS web pages and sending automatic e-mail notifications to responsible developers. These and other recent developments will be presented and future plans will be described.

  15. Machine en Theater. Ontwerpconcepten van winkelgebouwen

    NARCIS (Netherlands)

    Kooijman, D.C.

    1999-01-01

    Machine and Theater, Design Concepts for Shop Buildings is a richly illustrated study of the architectural and urban development of retail buildings, focusing on six essential shop types: the passage and the department store in particular in Germany and France in the nineteenth century; supermarkets

  16. Building Automation Systems.

    Science.gov (United States)

    Honeywell, Inc., Minneapolis, Minn.

    A number of different automation systems for use in monitoring and controlling building equipment are described in this brochure. The system functions include--(1) collection of information, (2) processing and display of data at a central panel, and (3) taking corrective action by sounding alarms, making adjustments, or automatically starting and…

  17. In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

    Science.gov (United States)

    Singla, Neeru; Srivastava, Vishal; Singh Mehta, Dalip

    2018-02-01

    We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.

  18. 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.

  19. Machine Protection

    CERN Document Server

    Schmidt, R

    2014-01-01

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

  20. Machine-vision-based identification of broken inserts in edge profile milling heads

    NARCIS (Netherlands)

    Fernandez Robles, Laura; Azzopardi, George; Alegre, Enrique; Petkov, Nicolai

    This paper presents a reliable machine vision system to automatically detect inserts and determine if they are broken. Unlike the machining operations studied in the literature, we are dealing with edge milling head tools for aggressive machining of thick plates (up to 12 centimetres) in a single

  1. Using the TED Talks to Evaluate Spoken Post-editing of Machine Translation

    DEFF Research Database (Denmark)

    Liyanapathirana, Jeevanthi; Popescu-Belis, Andrei

    2016-01-01

    This paper presents a solution to evaluate spoken post-editing of imperfect machine translation output by a human translator. We compare two approaches to the combination of machine translation (MT) and automatic speech recognition (ASR): a heuristic algorithm and a machine learning method...

  2. Computerized automatic tip scanning operation

    International Nuclear Information System (INIS)

    Nishikawa, K.; Fukushima, T.; Nakai, H.; Yanagisawa, A.

    1984-01-01

    In BWR nuclear power stations the Traversing Incore Probe (TIP) system is one of the most important components in reactor monitoring and control. In previous TIP systems, however, operators have suffered from the complexity of operation and long operation time required. The system presented in this paper realizes the automatic operation of the TIP system by monitoring and driving it with a process computer. This system significantly reduces the burden on customer operators and improves plant efficiency by simplifying the operating procedure, augmenting the accuracy of the measured data, and shortening operating time. The process computer is one of the PODIA (Plant Operation by Displayed Information Automation) systems. This computer transfers control signals to the TIP control panel, which in turn drives equipment by microprocessor control. The process computer contains such components as the CRT/KB unit, the printer plotter, the hard copier, and the message typers required for efficient man-machine communications. Its operation and interface properties are described

  3. Automatic creation of simulation configuration

    International Nuclear Information System (INIS)

    Oudot, G.; Poizat, F.

    1993-01-01

    SIPA, which stands for 'Simulator for Post Accident', includes: 1) a sophisticated software oriented workshop SWORD (which stands for 'Software Workshop Oriented towards Research and Development') designed in the ADA language including integrated CAD system and software tools for automatic generation of simulation software and man-machine interface in order to operate run-time simulation; 2) a 'simulator structure' based on hardware equipment and software for supervision and communications; 3) simulation configuration generated by SWORD, operated under the control of the 'simulator structure' and run on a target computer. SWORD has already been used to generate two simulation configurations (French 900 MW and 1300 MW nuclear power plants), which are now fully operational on the SIPA training simulator. (Z.S.) 1 ref

  4. Machine learning a probabilistic perspective

    CERN Document Server

    Murphy, Kevin P

    2012-01-01

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

  5. 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...

  6. 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

  7. An Automatic Car Counting System Using OverFeat Framework

    OpenAIRE

    Biswas, Debojit; Su, Hongbo; Wang, Chengyi; Blankenship, Jason; Stevanovic, Aleksandar

    2017-01-01

    Automatic car counting is an important component in the automated traffic system. Car counting is very important to understand the traffic load and optimize the traffic signals. In this paper, we implemented the Gaussian Background Subtraction Method and OverFeat Framework to count cars. OverFeat Framework is a combination of Convolution Neural Network (CNN) and one machine learning classifier (like Support Vector Machines (SVM) or Logistic Regression). With this study, we showed another poss...

  8. Automatic Photoelectric Telescope Service

    International Nuclear Information System (INIS)

    Genet, R.M.; Boyd, L.J.; Kissell, K.E.; Crawford, D.L.; Hall, D.S.; BDM Corp., McLean, VA; Kitt Peak National Observatory, Tucson, AZ; Dyer Observatory, Nashville, TN)

    1987-01-01

    Automatic observatories have the potential of gathering sizable amounts of high-quality astronomical data at low cost. The Automatic Photoelectric Telescope Service (APT Service) has realized this potential and is routinely making photometric observations of a large number of variable stars. However, without observers to provide on-site monitoring, it was necessary to incorporate special quality checks into the operation of the APT Service at its multiple automatic telescope installation on Mount Hopkins. 18 references

  9. Automatic Fiscal Stabilizers

    Directory of Open Access Journals (Sweden)

    Narcis Eduard Mitu

    2013-11-01

    Full Text Available Policies or institutions (built into an economic system that automatically tend to dampen economic cycle fluctuations in income, employment, etc., without direct government intervention. For example, in boom times, progressive income tax automatically reduces money supply as incomes and spendings rise. Similarly, in recessionary times, payment of unemployment benefits injects more money in the system and stimulates demand. Also called automatic stabilizers or built-in stabilizers.

  10. Machine learning for evolution strategies

    CERN Document Server

    Kramer, Oliver

    2016-01-01

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

  11. 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.

  12. Automatic differentiation bibliography

    Energy Technology Data Exchange (ETDEWEB)

    Corliss, G.F. [comp.

    1992-07-01

    This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

  13. Perspex machine: V. Compilation of C programs

    Science.gov (United States)

    Spanner, Matthew P.; Anderson, James A. D. W.

    2006-01-01

    The perspex machine arose from the unification of the Turing machine with projective geometry. The original, constructive proof used four special, perspective transformations to implement the Turing machine in projective geometry. These four transformations are now generalised and applied in a compiler, implemented in Pop11, that converts a subset of the C programming language into perspexes. This is interesting both from a geometrical and a computational point of view. Geometrically, it is interesting that program source can be converted automatically to a sequence of perspective transformations and conditional jumps, though we find that the product of homogeneous transformations with normalisation can be non-associative. Computationally, it is interesting that program source can be compiled for a Reduced Instruction Set Computer (RISC), the perspex machine, that is a Single Instruction, Zero Exception (SIZE) computer.

  14. 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.

  15. Pattern-Driven Automatic Parallelization

    Directory of Open Access Journals (Sweden)

    Christoph W. Kessler

    1996-01-01

    Full Text Available This article describes a knowledge-based system for automatic parallelization of a wide class of sequential numerical codes operating on vectors and dense matrices, and for execution on distributed memory message-passing multiprocessors. Its main feature is a fast and powerful pattern recognition tool that locally identifies frequently occurring computations and programming concepts in the source code. This tool also works for dusty deck codes that have been "encrypted" by former machine-specific code transformations. Successful pattern recognition guides sophisticated code transformations including local algorithm replacement such that the parallelized code need not emerge from the sequential program structure by just parallelizing the loops. It allows access to an expert's knowledge on useful parallel algorithms, available machine-specific library routines, and powerful program transformations. The partially restored program semantics also supports local array alignment, distribution, and redistribution, and allows for faster and more exact prediction of the performance of the parallelized target code than is usually possible.

  16. Automatic incrementalization of Prolog based static analyses

    DEFF Research Database (Denmark)

    Eichberg, Michael; Kahl, Matthias; Saha, Diptikalyan

    2007-01-01

    Modem development environments integrate various static analyses into the build process. Analyses that analyze the whole project whenever the project changes are impractical in this context. We present an approach to automatic incrementalization of analyses that are specified as tabled logic...... programs and evaluated using incremental tabled evaluation, a technique for efficiently updating memo tables in response to changes in facts and rules. The approach has been implemented and integrated into the Eclipse IDE. Our measurements show that this technique is effective for automatically...

  17. Towards Automatic Semantic Labelling of 3D City Models

    Science.gov (United States)

    Rook, M.; Biljecki, F.; Diakité, A. A.

    2016-10-01

    The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research.

  18. 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.

  19. 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.

  20. Virtual NC machine model with integrated knowledge data

    International Nuclear Information System (INIS)

    Sidorenko, Sofija; Dukovski, Vladimir

    2002-01-01

    The concept of virtual NC machining was established for providing a virtual product that could be compared with an appropriate designed product, in order to make NC program correctness evaluation, without real experiments. This concept is applied in the intelligent CAD/CAM system named VIRTUAL MANUFACTURE. This paper presents the first intelligent module that enables creation of the virtual models of existed NC machines and virtual creation of new ones, applying modular composition. Creation of a virtual NC machine is carried out via automatic knowledge data saving (features of the created NC machine). (Author)

  1. Design principles of metal-cutting machine tools

    CERN Document Server

    Koenigsberger, F

    1964-01-01

    Design Principles of Metal-Cutting Machine Tools discusses the fundamentals aspects of machine tool design. The book covers the design consideration of metal-cutting machine, such as static and dynamic stiffness, operational speeds, gearboxes, manual, and automatic control. The text first details the data calculation and the general requirements of the machine tool. Next, the book discusses the design principles, which include stiffness and rigidity of the separate constructional elements and their combined behavior under load, as well as electrical, mechanical, and hydraulic drives for the op

  2. Drinking water quality concerns and water vending machines

    International Nuclear Information System (INIS)

    McSwane, D.Z.; Oleckno, W.A.; Eils, L.M.

    1994-01-01

    Drinking water quality is a vital public health concern to consumers and regulators alike. This article describes some of the current microbiological, chemical, and radiological concerns about drinking water and the evolution of water vending machines. Also addressed are the typical treatment processes used in water vending machines and their effectiveness, as well as a brief examination of a certification program sponsored by the National Automatic Merchandising Association (NAMA), which provides a uniform standard for the design and construction of food and beverage vending machines. For some consumers, the water dispensed from vending machines is an attractive alternative to residential tap water which may be objectionable for aesthetic or other reasons

  3. Neural Bases of Automaticity

    Science.gov (United States)

    Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.

    2018-01-01

    Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

  4. Automatic control systems engineering

    International Nuclear Information System (INIS)

    Shin, Yun Gi

    2004-01-01

    This book gives descriptions of automatic control for electrical electronics, which indicates history of automatic control, Laplace transform, block diagram and signal flow diagram, electrometer, linearization of system, space of situation, state space analysis of electric system, sensor, hydro controlling system, stability, time response of linear dynamic system, conception of root locus, procedure to draw root locus, frequency response, and design of control system.

  5. Automatic Camera Control

    DEFF Research Database (Denmark)

    Burelli, Paolo; Preuss, Mike

    2014-01-01

    Automatically generating computer animations is a challenging and complex problem with applications in games and film production. In this paper, we investigate howto translate a shot list for a virtual scene into a series of virtual camera configurations — i.e automatically controlling the virtual...

  6. Automatic differentiation of functions

    International Nuclear Information System (INIS)

    Douglas, S.R.

    1990-06-01

    Automatic differentiation is a method of computing derivatives of functions to any order in any number of variables. The functions must be expressible as combinations of elementary functions. When evaluated at specific numerical points, the derivatives have no truncation error and are automatically found. The method is illustrated by simple examples. Source code in FORTRAN is provided

  7. Empirical evaluation of three machine learning method for automatic classification of neoplastic diagnoses Evaluación empírica de tres métodos de aprendizaje automático para clasificar automáticamente diagnósticos de neoplasias

    Directory of Open Access Journals (Sweden)

    José Luis Jara

    2011-12-01

    Full Text Available Diagnoses are a valuable source of information for evaluating a health system. However, they are not used extensively by information systems because diagnoses are normally written in natural language. This work empirically evaluates three machine learning methods to automatically assign codes from the International Classification of Diseases (10th Revision to 3,335 distinct diagnoses of neoplasms obtained from UMLS®. This evaluation is conducted on three different types of preprocessing. The results are encouraging: a well-known rule induction method and maximum entropy models achieve 90% accuracy in a balanced cross-validation experiment.Los diagnósticos médicos son una fuente valiosa de información para evaluar el funcionamiento de un sistema de salud. Sin embargo, su utilización en sistemas de información se ve dificultada porque éstos se encuentran normalmente escritos en lenguaje natural. Este trabajo evalúa empíricamente tres métodos de Aprendizaje Automático para asignar códigos de acuerdo a la Clasificación Internacional de Enfermedades (décima versión a 3.335 diferentes diagnósticos de neoplasias extraídos desde UMLS®. Esta evaluación se realiza con tres tipos distintos de preprocesamiento. Los resultados son alentadores: un conocido método de inducción de reglas de decisión y modelos de entropía máxima obtienen alrededor de 90% accuracy en una validación cruzada balanceada.

  8. An enhanced model for automatically extracting topic phrase from ...

    African Journals Online (AJOL)

    The key benefit foreseen from this automatic document classification is not only related to search engines, but also to many other fields like, document organization, text filtering and semantic index managing. Key words: Keyphrase extraction, machine learning, search engine snippet, document classification, topic tracking ...

  9. SPARCHS: Symbiotic, Polymorphic, Automatic, Resilient, Clean-Slate, Host Security

    Science.gov (United States)

    2016-03-01

    SPARCHS: SYMBIOTIC , POLYMORPHIC, AUTOMATIC, RESILIENT, CLEAN-SLATE, HOST SECURITY COLUMBIA UNIVERSITY MARCH 2016 FINAL... SYMBIOTIC , POLYMORPHIC, AUTOTOMIC, RESILIENT, CLEAN-SLATE, HOST SECURITY 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER FA8750-10-2-0253 5c. PROGRAM...17 4.2.3 SYMBIOTIC EMBEDDED MACHINES

  10. OptiCentric lathe centering machine

    Science.gov (United States)

    Buß, C.; Heinisch, J.

    2013-09-01

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

  11. Bootstrapped neural nets versus regression kriging in the digital mapping of pedological attributes: the automatic and time-consuming perspectives

    Science.gov (United States)

    Langella, Giuliano; Basile, Angelo; Bonfante, Antonello; Manna, Piero; Terribile, Fabio

    2013-04-01

    Digital soil mapping procedures are widespread used to build two-dimensional continuous maps about several pedological attributes. Our work addressed a regression kriging (RK) technique and a bootstrapped artificial neural network approach in order to evaluate and compare (i) the accuracy of prediction, (ii) the susceptibility of being included in automatic engines (e.g. to constitute web processing services), and (iii) the time cost needed for calibrating models and for making predictions. Regression kriging is maybe the most widely used geostatistical technique in the digital soil mapping literature. Here we tried to apply the EBLUP regression kriging as it is deemed to be the most statistically sound RK flavor by pedometricians. An unusual multi-parametric and nonlinear machine learning approach was accomplished, called BAGAP (Bootstrap aggregating Artificial neural networks with Genetic Algorithms and Principal component regression). BAGAP combines a selected set of weighted neural nets having specified characteristics to yield an ensemble response. The purpose of applying these two particular models is to ascertain whether and how much a more cumbersome machine learning method could be much promising in making more accurate/precise predictions. Being aware of the difficulty to handle objects based on EBLUP-RK as well as BAGAP when they are embedded in environmental applications, we explore the susceptibility of them in being wrapped within Web Processing Services. Two further kinds of aspects are faced for an exhaustive evaluation and comparison: automaticity and time of calculation with/without high performance computing leverage.

  12. microcontroller based automatic control for water pumping machine

    African Journals Online (AJOL)

    user

    60% of the human body [1, 3, 4]. Although water ... systems such as dams, reservoirs, wells, artificial lakes, etc. ... Human intelligence ... maximization of the performance and life span of the ... reduced water quality due to contamination of the.

  13. microcontroller based automatic control for water pumping machine

    African Journals Online (AJOL)

    The MBACWPMLI uses ultrasonic sensor installed at the top of a tank to send and receive sound waves, and the time taken is converted to distance by the microcontroller to give corresponding digital outputs which turns ON LEDs that indicate the level of water in the storage tank. The microcontroller also gives digital output ...

  14. 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.

  15. 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…

  16. 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

  17. Automatic Emotional State Detection using Facial Expression Dynamic in Videos

    Directory of Open Access Journals (Sweden)

    Hongying Meng

    2014-11-01

    Full Text Available In this paper, an automatic emotion detection system is built for a computer or machine to detect the emotional state from facial expressions in human computer communication. Firstly, dynamic motion features are extracted from facial expression videos and then advanced machine learning methods for classification and regression are used to predict the emotional states. The system is evaluated on two publicly available datasets, i.e. GEMEP_FERA and AVEC2013, and satisfied performances are achieved in comparison with the baseline results provided. With this emotional state detection capability, a machine can read the facial expression of its user automatically. This technique can be integrated into applications such as smart robots, interactive games and smart surveillance systems.

  18. Automatic tuning of free electron lasers

    Energy Technology Data Exchange (ETDEWEB)

    Agapov, Ilya; Zagorodnov, Igor [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Geloni, Gianluca [European XFEL, Schenefeld (Germany); Tomin, Sergey [European XFEL, Schenefeld (Germany); NRC Kurchatov Institute, Moscow (Russian Federation)

    2017-04-07

    Existing FEL facilities often suffer from stability issues: so electron orbit, transverse electron optics, electron bunch compression and other parameters have to be readjusted often to account for drifts in performance of various components. The tuning procedures typically employed in operation are often manual and lengthy. We have been developing a combination of model-free and model-based automatic tuning methods to meet the needs of present and upcoming XFEL facilities. Our approach has been implemented at FLASH to achieve automatic SASE tuning using empirical control of orbit, electron optics and bunch compression. In this paper we describe our approach to empirical tuning, the software which implements it, and the results of using it at FLASH.We also discuss the potential of using machine learning and model-based techniques in tuning methods.

  19. Automatic tuning of free electron lasers

    International Nuclear Information System (INIS)

    Agapov, Ilya; Zagorodnov, Igor; Geloni, Gianluca; Tomin, Sergey

    2017-01-01

    Existing FEL facilities often suffer from stability issues: so electron orbit, transverse electron optics, electron bunch compression and other parameters have to be readjusted often to account for drifts in performance of various components. The tuning procedures typically employed in operation are often manual and lengthy. We have been developing a combination of model-free and model-based automatic tuning methods to meet the needs of present and upcoming XFEL facilities. Our approach has been implemented at FLASH to achieve automatic SASE tuning using empirical control of orbit, electron optics and bunch compression. In this paper we describe our approach to empirical tuning, the software which implements it, and the results of using it at FLASH.We also discuss the potential of using machine learning and model-based techniques in tuning methods.

  20. Thai Automatic Speech Recognition

    National Research Council Canada - National Science Library

    Suebvisai, Sinaporn; Charoenpornsawat, Paisarn; Black, Alan; Woszczyna, Monika; Schultz, Tanja

    2005-01-01

    .... We focus on the discussion of the rapid deployment of ASR for Thai under limited time and data resources, including rapid data collection issues, acoustic model bootstrap, and automatic generation of pronunciations...

  1. Automatic Payroll Deposit System.

    Science.gov (United States)

    Davidson, D. B.

    1979-01-01

    The Automatic Payroll Deposit System in Yakima, Washington's Public School District No. 7, directly transmits each employee's salary amount for each pay period to a bank or other financial institution. (Author/MLF)

  2. Automatic Test Systems Aquisition

    National Research Council Canada - National Science Library

    1994-01-01

    We are providing this final memorandum report for your information and use. This report discusses the efforts to achieve commonality in standards among the Military Departments as part of the DoD policy for automatic test systems (ATS...

  3. Automatic Differentiation and Deep Learning

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Statistical learning has been getting more and more interest from the particle-physics community in recent times, with neural networks and gradient-based optimization being a focus. In this talk we shall discuss three things: automatic differention tools: tools to quickly build DAGs of computation that are fully differentiable. We shall focus on one such tool "PyTorch".  Easy deployment of trained neural networks into large systems with many constraints: for example, deploying a model at the reconstruction phase where the neural network has to be integrated into CERN's bulk data-processing C++-only environment Some recent models in deep learning for segmentation and generation that might be useful for particle physics problems.

  4. Automatic generation of data merging program codes.

    OpenAIRE

    Hyensook, Kim; Oussena, Samia; Zhang, Ying; Clark, Tony

    2010-01-01

    Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level. Our formalized transformation described using ATL (ATLAS Transformation Language) enables automatic g...

  5. Brand and automaticity

    OpenAIRE

    Liu, J.

    2008-01-01

    A presumption of most consumer research is that consumers endeavor to maximize the utility of their choices and are in complete control of their purchasing and consumption behavior. However, everyday life experience suggests that many of our choices are not all that reasoned or conscious. Indeed, automaticity, one facet of behavior, is indispensable to complete the portrait of consumers. Despite its importance, little attention is paid to how the automatic side of behavior can be captured and...

  6. Position automatic determination technology

    International Nuclear Information System (INIS)

    1985-10-01

    This book tells of method of position determination and characteristic, control method of position determination and point of design, point of sensor choice for position detector, position determination of digital control system, application of clutch break in high frequency position determination, automation technique of position determination, position determination by electromagnetic clutch and break, air cylinder, cam and solenoid, stop position control of automatic guide vehicle, stacker crane and automatic transfer control.

  7. Automatic intelligent cruise control

    OpenAIRE

    Stanton, NA; Young, MS

    2006-01-01

    This paper reports a study on the evaluation of automatic intelligent cruise control (AICC) from a psychological perspective. It was anticipated that AICC would have an effect upon the psychology of driving—namely, make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but might reduce the workload and make driving might less stressful. Drivers were asked to drive in a driving simulator under manual and automatic inte...

  8. Exploring cluster Monte Carlo updates with Boltzmann machines

    Science.gov (United States)

    Wang, Lei

    2017-11-01

    Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

  9. Exploring cluster Monte Carlo updates with Boltzmann machines.

    Science.gov (United States)

    Wang, Lei

    2017-11-01

    Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

  10. Building Savings and Investments Culture among Nigerians

    African Journals Online (AJOL)

    DR Nneka

    Rivers State University of Science and Technology, Port Harcourt. Rivers State, Nigeria. & .... assets, such as expensive cars, landed property, building etc. (3) For speculatory ... develop an automatic way of doing this. May be, mandating your ...

  11. Personality in speech assessment and automatic classification

    CERN Document Server

    Polzehl, Tim

    2015-01-01

    This work combines interdisciplinary knowledge and experience from research fields of psychology, linguistics, audio-processing, machine learning, and computer science. The work systematically explores a novel research topic devoted to automated modeling of personality expression from speech. For this aim, it introduces a novel personality assessment questionnaire and presents the results of extensive labeling sessions to annotate the speech data with personality assessments. It provides estimates of the Big 5 personality traits, i.e. openness, conscientiousness, extroversion, agreeableness, and neuroticism. Based on a database built on the questionnaire, the book presents models to tell apart different personality types or classes from speech automatically.

  12. The Employment Effects of High-Technology: A Case Study of Machine Vision. Research Report No. 86-19.

    Science.gov (United States)

    Chen, Kan; Stafford, Frank P.

    A case study of machine vision was conducted to identify and analyze the employment effects of high technology in general. (Machine vision is the automatic acquisition and analysis of an image to obtain desired information for use in controlling an industrial activity, such as the visual sensor system that gives eyes to a robot.) Machine vision as…

  13. Stability of the CAE of a digital mammography machine; Estabilidad del CAE de un mamografo digital

    Energy Technology Data Exchange (ETDEWEB)

    Fernandez Lara, A. A.; Ruiz Morales, C.; Buades Forner, M. J.; Tobarra, B. M.

    2013-07-01

    We analyzed the long-term reproducibility automatic exposure control (CAE) of a digital mammography machine for possible drifts and the factors that have led to changes in its baseline are discussed. (Author)

  14. Machine learning in updating predictive models of planning and scheduling transportation projects

    Science.gov (United States)

    1997-01-01

    A method combining machine learning and regression analysis to automatically and intelligently update predictive models used in the Kansas Department of Transportations (KDOTs) internal management system is presented. The predictive models used...

  15. Machine learning techniques for persuasion dectection in conversation

    OpenAIRE

    Ortiz, Pedro.

    2010-01-01

    Approved for public release; distribution is unlimited We determined that it is possible to automatically detect persuasion in conversations using three traditional machine learning techniques, naive bayes, maximum entropy, and support vector machine. These results are the first of their kind and serve as a baseline for all future work in this field. The three techniques consistently outperformed the baseline F-score, but not at a level that would be useful for real world applications. The...

  16. Machine en Theater. Ontwerpconcepten van winkelgebouwen

    OpenAIRE

    Kooijman, D.C.

    1999-01-01

    Machine and Theater, Design Concepts for Shop Buildings is a richly illustrated study of the architectural and urban development of retail buildings, focusing on six essential shop types: the passage and the department store in particular in Germany and France in the nineteenth century; supermarkets and malls and their relation to the suburbanisation and the emerging car use; and the peripheral retail park and location-free virtual store as the most recent developments. On the basis of a larg...

  17. Future Smart Cooking Machine System Design

    Directory of Open Access Journals (Sweden)

    Dewi Agushinta R.

    2013-11-01

    Full Text Available There are many tools make human task get easier. Cooking has become a basic necessity for human beings, since food is one of basic human needs. Until now, the cooking equipment being used is still a hand tool. However everyone has slightly high activity. The presence of cooking tools that can do the cooking work by itself is now necessary. Future Smart Cooking Machine is an artificial intelligence machine that can do cooking work automatically. With this system design, the time is minimized and the ease of work is expected to be achieved. The development of this system is carried out with System Development Life Cycle (SDLC methods. Prototyping method used in this system is a throw-away prototyping approach. At the end of this research there will be produced a cooking machine system design including physical design engine and interface design.

  18. Some experimental results for an automatic helium liquefier

    International Nuclear Information System (INIS)

    Watanabe, T.; Kudo, T.; Kuraoka, Y.; Sakura, K.; Tsuruga, H.; Watanabe, T.

    1984-01-01

    This chapter describes the testing of an automatic cooldown system. The liquefying machine examined is a CTi Model 1400. The automatic helium gas liquefying system is operated by using sequence control with a programmable controller. The automatic mode is carried out by operation of two compressors. The monitoring system consists of 41 remote sensors. Liquid level is measured by a superconducting level meter. The J-T valve and return valve, which require precise control, are operated by pulse motors. The advantages of the automatic cooldown system are reduced operator man power; temperatures and pressures are changed smoothly, so that the flow chart of automation is simple; and the system makes continuous liquefier operation possible

  19. Cost-benefit analysis of the ATM automatic deposit service

    Directory of Open Access Journals (Sweden)

    Ivica Županović

    2015-03-01

    Full Text Available Bankers and other financial experts have analyzed the value of automated teller machines (ATM in terms of growing consumer demand, rising costs of technology development, decreasing profitability and market share. This paper presents a step-by-step cost-benefit analysis of the ATM automatic deposit service. The first step is to determine user attitudes towards using ATM automatic deposit service by using the Technology Acceptance Model (TAM. The second step is to determine location priorities for ATMs that provide automatic deposit services using the Analytic Hierarchy Process (AHP model. The results of the previous steps enable a highly efficient application of cost-benefit analysis for evaluating costs and benefits of automatic deposit services. To understand fully the proposed procedure outside of theoretical terms, a real-world application of a case study is conducted.

  20. Use of MCAM in creating 3D neutronics model for ITER building

    International Nuclear Information System (INIS)

    Zeng Qin; Wang Guozhong; Dang Tongqiang; Long Pengcheng; Loughlin, Michael

    2012-01-01

    Highlights: ► We created a 3D neutronics model of the ITER building. ► The model was produced from the engineering CAD model by MCAM software. ► The neutron flux map in the ITER building was calculated. - Abstract: The three dimensional (3D) neutronics reference model of International Thermonuclear Experimental Reactor (ITER) only defines the tokamak machine and extends to the bio-shield. In order to meet further 3D neutronics analysis needs, it is necessary to create a 3D reference model of the ITER building. Monte Carlo Automatic Modeling Program for Radiation Transport Simulation (MCAM) was developed as a computer aided design (CAD) based bi-directional interface program between general CAD systems and Monte Carlo radiation transport simulation codes. With the help of MCAM version 4.8, the 3D neutronics model of ITER building was created based on the engineering CAD model. The calculation of the neutron flux map in ITER building during operation showed the correctness and usability of the model. This model is the first detailed ITER building 3D neutronics model and it will be made available to all international organization collaborators as a reference model.

  1. Use of MCAM in creating 3D neutronics model for ITER building

    Energy Technology Data Exchange (ETDEWEB)

    Zeng Qin [Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei, Anhui 230031 (China); School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027 (China); Wang Guozhong, E-mail: mango33@mail.ustc.edu.cn [School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027 (China); Dang Tongqiang [School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027 (China); Long Pengcheng [Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei, Anhui 230031 (China); School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027 (China); Loughlin, Michael [ITER Organization, Route de Vinon sur Verdon, 13115 St. Paul-Lz-Durance (France)

    2012-08-15

    Highlights: Black-Right-Pointing-Pointer We created a 3D neutronics model of the ITER building. Black-Right-Pointing-Pointer The model was produced from the engineering CAD model by MCAM software. Black-Right-Pointing-Pointer The neutron flux map in the ITER building was calculated. - Abstract: The three dimensional (3D) neutronics reference model of International Thermonuclear Experimental Reactor (ITER) only defines the tokamak machine and extends to the bio-shield. In order to meet further 3D neutronics analysis needs, it is necessary to create a 3D reference model of the ITER building. Monte Carlo Automatic Modeling Program for Radiation Transport Simulation (MCAM) was developed as a computer aided design (CAD) based bi-directional interface program between general CAD systems and Monte Carlo radiation transport simulation codes. With the help of MCAM version 4.8, the 3D neutronics model of ITER building was created based on the engineering CAD model. The calculation of the neutron flux map in ITER building during operation showed the correctness and usability of the model. This model is the first detailed ITER building 3D neutronics model and it will be made available to all international organization collaborators as a reference model.

  2. 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

  3. Automatic Encoding and Language Detection in the GSDL

    Directory of Open Access Journals (Sweden)

    Otakar Pinkas

    2014-10-01

    Full Text Available Automatic detection of encoding and language of the text is part of the Greenstone Digital Library Software (GSDL for building and distributing digital collections. It is developed by the University of Waikato (New Zealand in cooperation with UNESCO. The automatic encoding and language detection in Slavic languages is difficult and it sometimes fails. The aim is to detect cases of failure. The automatic detection in the GSDL is based on n-grams method. The most frequent n-grams for Czech are presented. The whole process of automatic detection in the GSDL is described. The input documents to test collections are plain texts encoded in ISO-8859-1, ISO-8859-2 and Windows-1250. We manually evaluated the quality of automatic detection. To the causes of errors belong the improper language model predominance and the incorrect switch to Windows-1250. We carried out further tests on documents that were more complex.

  4. Trustless Machine Learning Contracts; Evaluating and Exchanging Machine Learning Models on the Ethereum Blockchain

    OpenAIRE

    Kurtulmus, A. Besir; Daniel, Kenny

    2018-01-01

    Using blockchain technology, it is possible to create contracts that offer a reward in exchange for a trained machine learning model for a particular data set. This would allow users to train machine learning models for a reward in a trustless manner. The smart contract will use the blockchain to automatically validate the solution, so there would be no debate about whether the solution was correct or not. Users who submit the solutions won't have counterparty risk that they won't get paid fo...

  5. LHCb Dockerized Build Environment

    Science.gov (United States)

    Clemencic, M.; Belin, M.; Closier, J.; Couturier, B.

    2017-10-01

    Used as lightweight virtual machines or as enhanced chroot environments, Linux containers, and in particular the Docker abstraction over them, are more and more popular in the virtualization communities. The LHCb Core Software team decided to investigate how to use Docker containers to provide stable and reliable build environments for the different supported platforms, including the obsolete ones which cannot be installed on modern hardware, to be used in integration builds, releases and by any developer. We present here the techniques and procedures set up to define and maintain the Docker images and how these images can be used to develop on modern Linux distributions for platforms otherwise not accessible.

  6. Study on ultra-fine w-EDM with on-machine measurement-assisted

    International Nuclear Information System (INIS)

    Chen Shuntong; Yang Hongye

    2011-01-01

    The purpose of this study was to develop the on-machine measurement techniques so as to precisely fabricate micro intricate part using ultra-fine w-EDM. The measurement-assisted approach which employs an automatic optical inspection (AOI) is incorporated to ultra-fine w-EDM process to on-machine detect the machining error for next re-machining. The AOI acquires the image through a high resolution CCD device from the contour of the workpiece after roughing in order to further process and recognize the image for determining the residual. This facilitates the on-machine error detection and compensation re-machining. The micro workpiece and electrode are not repositioned during machining. A fabrication for a micro probe of 30-μm diameter is rapidly machined and verified successfully. Based on the proposed technique, on-machine measurement with AOI has been realized satisfactorily.

  7. Learning scikit-learn machine learning in Python

    CERN Document Server

    Garreta, Raúl

    2013-01-01

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

  8. Construction and operation of a support facilities (Building 729) for operation/testing of a prototype accelerator/storage ring (XLS) and machine shop for the National Synchrotron Light Source at Brookhaven National Laboratory, Upton, New York

    International Nuclear Information System (INIS)

    1992-06-01

    Proposed action is to construct at BNL a 5,600-ft 2 support building, install and operate a prototypic 200 MeV accelerator and a prototypic 700 MeV storage ring within, and to construct and operate a 15 kV substation to power the building. The accelerator and storage ring would comprise the x-ray lithography source or XLS

  9. 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

  10. Automatic Program Development

    DEFF Research Database (Denmark)

    Automatic Program Development is a tribute to Robert Paige (1947-1999), our accomplished and respected colleague, and moreover our good friend, whose untimely passing was a loss to our academic and research community. We have collected the revised, updated versions of the papers published in his...... honor in the Higher-Order and Symbolic Computation Journal in the years 2003 and 2005. Among them there are two papers by Bob: (i) a retrospective view of his research lines, and (ii) a proposal for future studies in the area of the automatic program derivation. The book also includes some papers...... by members of the IFIP Working Group 2.1 of which Bob was an active member. All papers are related to some of the research interests of Bob and, in particular, to the transformational development of programs and their algorithmic derivation from formal specifications. Automatic Program Development offers...

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. Automatic text summarization

    CERN Document Server

    Torres Moreno, Juan Manuel

    2014-01-01

    This new textbook examines the motivations and the different algorithms for automatic document summarization (ADS). We performed a recent state of the art. The book shows the main problems of ADS, difficulties and the solutions provided by the community. It presents recent advances in ADS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several exemples are included in order to clarify the theoretical concepts.  The books currently available in the area of Automatic Document Summarization are not recent. Powerful algorithms have been develop

  19. Automatic Ultrasound Scanning

    DEFF Research Database (Denmark)

    Moshavegh, Ramin

    on the user adjustments on the scanner interface to optimize the scan settings. This explains the huge interest in the subject of this PhD project entitled “AUTOMATIC ULTRASOUND SCANNING”. The key goals of the project have been to develop automated techniques to minimize the unnecessary settings...... on the scanners, and to improve the computer-aided diagnosis (CAD) in ultrasound by introducing new quantitative measures. Thus, four major issues concerning automation of the medical ultrasound are addressed in this PhD project. They touch upon gain adjustments in ultrasound, automatic synthetic aperture image...

  20. Automatic NAA. Saturation activities

    International Nuclear Information System (INIS)

    Westphal, G.P.; Grass, F.; Kuhnert, M.

    2008-01-01

    A system for Automatic NAA is based on a list of specific saturation activities determined for one irradiation position at a given neutron flux and a single detector geometry. Originally compiled from measurements of standard reference materials, the list may be extended also by the calculation of saturation activities from k 0 and Q 0 factors, and f and α values of the irradiation position. A systematic improvement of the SRM approach is currently being performed by pseudo-cyclic activation analysis, to reduce counting errors. From these measurements, the list of saturation activities is recalculated in an automatic procedure. (author)