Energy-efficient electrical machines by new materials. Superconductivity in large electrical machines

International Nuclear Information System (INIS)

Frauenhofer, Joachim; Arndt, Tabea; Grundmann, Joern

2013-01-01

The implementation of superconducting materials in high-power electrical machines results in significant advantages regarding efficiency, size and dynamic behavior when compared to conventional machines. The application of HTS (high-temperature superconductors) in electrical machines allows significantly higher power densities to be achieved for synchronous machines. In order to gain experience with the new technology, Siemens carried out a series of development projects. A 400 kW model motor for the verification of a concept for the new technology was followed by a 4000 kV A generator as highspeed machine - as well as a low-speed 4000 kW propeller motor with high torque. The 4000 kVA generator is still employed to carry out long-term tests and to check components. Superconducting machines have significantly lower weight and envelope dimensions compared to conventional machines, and for this reason alone, they utilize resources better. At the same time, operating losses are slashed to about half and the efficiency increases. Beyond this, they set themselves apart as a result of their special features in operation, such as high overload capability, stiff alternating load behavior and low noise. HTS machines provide significant advantages where the reduction of footprint, weight and losses or the improved dynamic behavior results in significant improvements of the overall system. Propeller motors and generators,for ships, offshore plants, in wind turbine and hydroelectric plants and in large power stations are just some examples. HTS machines can therefore play a significant role when it comes to efficiently using resources and energy as well as reducing the CO 2 emissions.

Using Overall Equipment Effectiveness indicator to measure the level of planned production time usage of sewing machine

Directory of Open Access Journals (Sweden)

Marek Krynke

2014-12-01

Full Text Available The chapter presents the results of utilization of the OEE indicator to measure the level of operating time usage of sewing machine production of air bags. The idea of an OEE indictor, which is a key metrics in Total Productive Maintenance (TPM program, is presented. The goals and benefits of its calculation are included. The research object – KL 110 air bags sewing machine - what for the machine is used. The calculation of TPM indicators for the analysed machine is presented. The calculation of TPM indicators was undertaken over a period of six months of the machine’s working time. It was indicated that the overall effectiveness of the machine is at a level of 65,7%, the time losses were 34,3%. Most of the losses were related to low performance. Only Availability indicator reaches a word class level, if other indicators such as Performance, Quality and OEE should be improved, their value should be increased. Activities to improve the effectiveness of the machine utilization were determined.

Estimation of the resource buffers in the assembly process of a shearer machine in the CPPM method

Directory of Open Access Journals (Sweden)

Gwiazda Aleksander

2017-01-01

Full Text Available Dynamic development of scheduling systems allows significantly improving currently realized tasks. Critical Chain Project Management (CCPM is one of the methods of project management basing on network planning. In this method is utilized the concept of a critical chain derived from the Theory of Constraints. This method allows avoiding losses considered project time and resources. It results in quicker project implementation (20-30%, and in reducing the risk level considered with tasks realization. The projects are cheaper, and the risk of cost overruns is significantly reduced. Factors that distinguish CCPM method from traditional network planning methods are: the balance of resources and the introduction of buffers. Moreover in the CCPM method key elements are: times of tasks that are reduced from traditional estimates to realistic ones. Activities associated with the task start as late as possible in accordance with the ALAP principle (As Late As Possible. This work presents the process of managing the assembly of a shearer machine taking into account the process of safety buffers utilization and the whole project optimization. It is presented the estimation of buffers capacity to obtain the improvement of project realization task.

Study of Acrylamide Level in Food from Vending Machines.

Science.gov (United States)

Haouet, Naceur; Pistolese, Simona; Branciari, Raffaella; Ranucci, David; Altissimi, Maria Serena

2016-09-20

Acrylamide is a by-product of the Maillard reaction and is potentially carcinogenic to humans. It is found in a number of foods with higher concentrations in carbohydrate-rich foods and moderate levels of protein-rich foods such as meat, fish and seafood. Acrylamide levels in food distributed in vending machines placed in public areas of the city of Perugia were analysed by high-performance liquid chromatography. Samples included five different categories, depending on the characteristics of the products: i) potato chips; ii) salted bakery products; iii) biscuits and wafers; iv) sweet bakery products; v) sandwiches. A high variability in acrylamide level among different foods and within the same category was detected. Potato chips showed the highest amount of acrylamide (1781±637 μg/kg) followed by salted bakery products (211 ±245 μg/kg), biscuits and wafers (184±254 μg/kg), sweet bakery products (100±72 μg/kg) and sandwiches (42±10 μg/kg). In the potato chips and sandwiches categories, all of the samples revealed the presence of acrylamide, while different prevalence was registered in the other foods considered. The data of this study highlight the presence of acrylamide in different foods sold in vending machines and this data could be useful to understand the contribution of this type of consumption to human exposure to this compound.

Study of acrylamide level in food from vending machines

Directory of Open Access Journals (Sweden)

Naceur Haouet

2016-11-01

Full Text Available Acrylamide is a by-product of the Maillard reaction and is potentially carcinogenic to humans. It is found in a number of foods with higher concentrations in carbohydrate-rich foods and moderate levels of protein-rich foods such as meat, fish and seafood. Acrylamide levels in food distributed in vending machines placed in public areas of the city of Perugia were analysed by high-performance liquid chromatography. Samples included five different categories, depending on the characteristics of the products: i potato chips; ii salted bakery products; iii biscuits and wafers; iv sweet bakery products; v sandwiches. A high variability in acrylamide level among different foods and within the same category was detected. Potato chips showed the highest amount of acrylamide (1781±637 μg/kg followed by salted bakery products (211±245 μg/kg, biscuits and wafers (184±254 μg/kg, sweet bakery products (100±72 μg/kg and sandwiches (42±10 μg/kg. In the potato chips and sandwiches categories, all of the samples revealed the presence of acrylamide, while different prevalence was registered in the other foods considered. The data of this study highlight the presence of acrylamide in different foods sold in vending machines and this data could be useful to understand the contribution of this type of consumption to human exposure to this compound.

Influence of Machine Exploitation Effectiveness on Furniture Production Quality Level

Directory of Open Access Journals (Sweden)

Stasiak-Betlejewska Renata

2015-12-01

Full Text Available One of the most important factors determining the company‘s capacity to produce high quality products is the level of machinery operation effectiveness. Companies having modern machinery are characterized by high productivity. To obtain a high quality product, the equipment should be properly used, without any failure, which contributes significantly to the exploitation level increase. The modernity level and the exploitation effectiveness level for chosen machine producing furniture components in relation to the product quality level were analysed in the paper. As a result of the research findings analysis, proposals for corrective actions with regard to machinery maintenance and production processes were presented.

Using machine-coded event data for the micro-level study of political violence

Directory of Open Access Journals (Sweden)

Jesse Hammond

2014-07-01

Full Text Available Machine-coded datasets likely represent the future of event data analysis. We assess the use of one of these datasets—Global Database of Events, Language and Tone (GDELT—for the micro-level study of political violence by comparing it to two hand-coded conflict event datasets. Our findings indicate that GDELT should be used with caution for geo-spatial analyses at the subnational level: its overall correlation with hand-coded data is mediocre, and at the local level major issues of geographic bias exist in how events are reported. Overall, our findings suggest that due to these issues, researchers studying local conflict processes may want to wait for a more reliable geocoding method before relying too heavily on this set of machine-coded data.

Precision machining commercialization

International Nuclear Information System (INIS)

1978-01-01

To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

Multi-level machine learning prediction of protein–protein interactions in Saccharomyces cerevisiae

Directory of Open Access Journals (Sweden)

Julian Zubek

2015-07-01

Full Text Available Accurate identification of protein–protein interactions (PPI is the key step in understanding proteins’ biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein–protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein–protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC. Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent.

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.

Exploiting the ALICE HLT for PROOF by scheduling of Virtual Machines

International Nuclear Information System (INIS)

Meoni, Marco; Boettger, Stefan; Zelnicek, Pierre; Kebschull, Udo; Lindenstruth, Volker

2011-01-01

The HLT (High-Level Trigger) group of the ALICE experiment at the LHC has prepared a virtual Parallel ROOT Facility (PROOF) enabled cluster (HAF - HLT Analysis Facility) for fast physics analysis, detector calibration and reconstruction of data samples. The HLT-Cluster currently consists of 2860 CPU cores and 175TB of storage. Its purpose is the online filtering of the relevant part of data produced by the particle detector. However, data taking is not running continuously and exploiting unused cluster resources for other applications is highly desirable and improves the usage-cost ratio of the HLT cluster. As such, unused computing resources are dedicated to a PROOF-enabled virtual cluster available to the entire collaboration. This setup is especially aimed at the prototyping phase of analyses that need a high number of development iterations and a short response time, e.g. tuning of analysis cuts, calibration and alignment. HAF machines are enabled and disabled upon user request to start or complete analysis tasks. This is achieved by a virtual machine scheduling framework which dynamically assigns and migrates virtual machines running PROOF workers to unused physical resources. Using this approach we extend the HLT usage scheme to running both online and offline computing, thereby optimizing the resource usage.

Dictionary Based Machine Translation from Kannada to Telugu

Science.gov (United States)

Sindhu, D. V.; Sagar, B. M.

2017-08-01

Machine Translation is a task of translating from one language to another language. For the languages with less linguistic resources like Kannada and Telugu Dictionary based approach is the best approach. This paper mainly focuses on Dictionary based machine translation for Kannada to Telugu. The proposed methodology uses dictionary for translating word by word without much correlation of semantics between them. The dictionary based machine translation process has the following sub process: Morph analyzer, dictionary, transliteration, transfer grammar and the morph generator. As a part of this work bilingual dictionary with 8000 entries is developed and the suffix mapping table at the tag level is built. This system is tested for the children stories. In near future this system can be further improved by defining transfer grammar rules.

30 CFR 57.14115 - Stationary grinding machines.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Stationary grinding machines. 57.14115 Section... and Equipment Safety Devices and Maintenance Requirements § 57.14115 Stationary grinding machines. Stationary grinding machines, other than special bit grinders, shall be equipped with— (a) Peripheral hoods...

Engagement techniques and playing level impact the biomechanical demands on rugby forwards during machine-based scrummaging

OpenAIRE

Preatoni, Ezio; Stokes, Keith A.; England, Michael E.; Trewartha, Grant

2014-01-01

Objectives This cross-sectional study investigated the factors that may influence the physical loading on rugby forwards performing a scrum by studying the biomechanics of machine-based scrummaging under different engagement techniques and playing levels.Methods 34 forward packs from six playing levels performed repetitions of five different types of engagement techniques against an instrumented scrum machine under realistic training conditions. Applied forces and body movements were recorded...

Introduction to AC machine design

CERN Document Server

Lipo, Thomas A

2018-01-01

AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

30 CFR 56.14115 - Stationary grinding machines.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Stationary grinding machines. 56.14115 Section... Equipment Safety Devices and Maintenance Requirements § 56.14115 Stationary grinding machines. Stationary grinding machines, other than special bit grinders, shall be equipped with— (a) Peripheral hoods capable of...

30 CFR 56.14107 - Moving machine parts.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Moving machine parts. 56.14107 Section 56.14107... Safety Devices and Maintenance Requirements § 56.14107 Moving machine parts. (a) Moving machine parts... takeup pulleys, flywheels, couplings, shafts, fan blades, and similar moving parts that can cause injury...

30 CFR 57.14107 - Moving machine parts.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Moving machine parts. 57.14107 Section 57.14107... Equipment Safety Devices and Maintenance Requirements § 57.14107 Moving machine parts. (a) Moving machine parts shall be guarded to protect persons from contacting gears, sprockets, chains, drive, head, tail...

Computing Bounds on Resource Levels for Flexible Plans

Science.gov (United States)

Muscvettola, Nicola; Rijsman, David

2009-01-01

A new algorithm efficiently computes the tightest exact bound on the levels of resources induced by a flexible activity plan (see figure). Tightness of bounds is extremely important for computations involved in planning because tight bounds can save potentially exponential amounts of search (through early backtracking and detection of solutions), relative to looser bounds. The bound computed by the new algorithm, denoted the resource-level envelope, constitutes the measure of maximum and minimum consumption of resources at any time for all fixed-time schedules in the flexible plan. At each time, the envelope guarantees that there are two fixed-time instantiations one that produces the minimum level and one that produces the maximum level. Therefore, the resource-level envelope is the tightest possible resource-level bound for a flexible plan because any tighter bound would exclude the contribution of at least one fixed-time schedule. If the resource- level envelope can be computed efficiently, one could substitute looser bounds that are currently used in the inner cores of constraint-posting scheduling algorithms, with the potential for great improvements in performance. What is needed to reduce the cost of computation is an algorithm, the measure of complexity of which is no greater than a low-degree polynomial in N (where N is the number of activities). The new algorithm satisfies this need. In this algorithm, the computation of resource-level envelopes is based on a novel combination of (1) the theory of shortest paths in the temporal-constraint network for the flexible plan and (2) the theory of maximum flows for a flow network derived from the temporal and resource constraints. The measure of asymptotic complexity of the algorithm is O(N O(maxflow(N)), where O(x) denotes an amount of computing time or a number of arithmetic operations proportional to a number of the order of x and O(maxflow(N)) is the measure of complexity (and thus of cost) of a maximumflow

Analysis of labor employment assessment on production machine to minimize time production

Science.gov (United States)

Hernawati, Tri; Suliawati; Sari Gumay, Vita

2018-03-01

Every company both in the field of service and manufacturing always trying to pass efficiency of it’s resource use. One resource that has an important role is labor. Labor has different efficiency levels for different jobs anyway. Problems related to the optimal allocation of labor that has different levels of efficiency for different jobs are called assignment problems, which is a special case of linear programming. In this research, Analysis of Labor Employment Assesment on Production Machine to Minimize Time Production, in PT PDM is done by using Hungarian algorithm. The aim of the research is to get the assignment of optimal labor on production machine to minimize time production. The results showed that the assignment of existing labor is not suitable because the time of completion of the assignment is longer than the assignment by using the Hungarian algorithm. By applying the Hungarian algorithm obtained time savings of 16%.

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.

Effect of Machining Velocity in Nanoscale Machining Operations

International Nuclear Information System (INIS)

Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

2015-01-01

The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

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

Automated Analysis of ARM Binaries using the Low-Level Virtual Machine Compiler Framework

Science.gov (United States)

2011-03-01

Maintenance ABACAS offers a level of flexibility in software development that would be very useful later in the software engineering life cycle. New... Blackjacking : security threats to blackberry devices, PDAs and cell phones in the enterprise. Indianapolis, Indiana, U.S.A.: Wiley Publishing, 2007...AUTOMATED ANALYSIS OF ARM BINARIES USING THE LOW- LEVEL VIRTUAL MACHINE COMPILER FRAMEWORK THESIS Jeffrey B. Scott

Market-based autonomous resource and application management in private clouds

KAUST Repository

Costache, Stefania; Kortas, Samuel; Morin, Christine; Parlavantzas, Nikos

2016-01-01

High Performance Computing (HPC) clouds need to be efficiently shared between selfish tenants having applications with different resource requirements and Service Level Objectives (SLOs). The main difficulty relies on providing concurrent resource access to such tenants while maximizing the resource utilization. To overcome this challenge, we propose Merkat, a market-based SLO-driven cloud platform. Merkat relies on a market-based model specifically designed for on-demand fine-grain resource allocation to maximize resource utilization and it uses a combination of currency distribution and dynamic resource pricing to ensure proper resource distribution among tenants. To meet the tenant’s SLO, Merkat uses autonomous controllers, which apply adaptation policies that: (i) dynamically tune the application’s provisioned CPU and memory per virtual machine in contention periods, or (ii) dynamically change the number of virtual machines. Our evaluation with simulation and on the Grid’5000 testbed shows that Merkat provides flexible support for different application types and SLOs and good tenant satisfaction compared to existing centralized systems, while the infrastructure resource utilization is improved.

Market-based autonomous resource and application management in private clouds

KAUST Repository

Costache, Stefania

2016-10-12

High Performance Computing (HPC) clouds need to be efficiently shared between selfish tenants having applications with different resource requirements and Service Level Objectives (SLOs). The main difficulty relies on providing concurrent resource access to such tenants while maximizing the resource utilization. To overcome this challenge, we propose Merkat, a market-based SLO-driven cloud platform. Merkat relies on a market-based model specifically designed for on-demand fine-grain resource allocation to maximize resource utilization and it uses a combination of currency distribution and dynamic resource pricing to ensure proper resource distribution among tenants. To meet the tenant’s SLO, Merkat uses autonomous controllers, which apply adaptation policies that: (i) dynamically tune the application’s provisioned CPU and memory per virtual machine in contention periods, or (ii) dynamically change the number of virtual machines. Our evaluation with simulation and on the Grid’5000 testbed shows that Merkat provides flexible support for different application types and SLOs and good tenant satisfaction compared to existing centralized systems, while the infrastructure resource utilization is improved.

GeoDeepDive: Towards a Machine Reading-Ready Digital Library and Information Integration Resource

Science.gov (United States)

Husson, J. M.; Peters, S. E.; Livny, M.; Ross, I.

2015-12-01

Recent developments in machine reading and learning approaches to text and data mining hold considerable promise for accelerating the pace and quality of literature-based data synthesis, but these advances have outpaced even basic levels of access to the published literature. For many geoscience domains, particularly those based on physical samples and field-based descriptions, this limitation is significant. Here we describe a general infrastructure to support published literature-based machine reading and learning approaches to information integration and knowledge base creation. This infrastructure supports rate-controlled automated fetching of original documents, along with full bibliographic citation metadata, from remote servers, the secure storage of original documents, and the utilization of considerable high-throughput computing resources for the pre-processing of these documents by optical character recognition, natural language parsing, and other document annotation and parsing software tools. New tools and versions of existing tools can be automatically deployed against original documents when they are made available. The products of these tools (text/XML files) are managed by MongoDB and are available for use in data extraction applications. Basic search and discovery functionality is provided by ElasticSearch, which is used to identify documents of potential relevance to a given data extraction task. Relevant files derived from the original documents are then combined into basic starting points for application building; these starting points are kept up-to-date as new relevant documents are incorporated into the digital library. Currently, our digital library stores contains more than 360K documents supplied by Elsevier and the USGS and we are actively seeking additional content providers. By focusing on building a dependable infrastructure to support the retrieval, storage, and pre-processing of published content, we are establishing a foundation for

30 CFR 75.1723 - Stationary grinding machines; protective devices.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Stationary grinding machines; protective....1723 Stationary grinding machines; protective devices. (a) Stationary grinding machines other than... the wheel. (3) Safety washers. (b) Grinding wheels shall be operated within the specifications of the...

Resource Leveling Based on Backward Controlling Activity in Line of Balance

Directory of Open Access Journals (Sweden)

Lihui Zhang

2017-01-01

Full Text Available The line of balance method that provides continuous and uninterrupted use of resources is one of the best methods for repetitive project resource management. This paper develops a resource leveling algorithm based on the backward controlling activity in line of balance. The backward controlling activity is a kind of special activity, and if its duration is prolonged the project duration could be reduced. It brings two advantages to the resource leveling: both the resource allocated on the backward activity and the project duration are reduced. A resource leveling algorithm is presented which permits the number of crews of the backward controlling activity to be reduced until the terminal situation is reached, where the backward controlling activity does not exist or the number of crews cannot be reduced. That adjustment enables the productivity of all activities to be consistent. An illustrative pipeline project demonstrates the improvement in resource leveling. And this study designed a MATLAB program to execute the design algorithm. The proposed model could help practitioners to achieve the goals of both resource leveling and project duration reduction without increasing any resource.

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.

Dynamic virtual machine allocation policy in cloud computing complying with service level agreement using CloudSim

Science.gov (United States)

Aneri, Parikh; Sumathy, S.

2017-11-01

Cloud computing provides services over the internet and provides application resources and data to the users based on their demand. Base of the Cloud Computing is consumer provider model. Cloud provider provides resources which consumer can access using cloud computing model in order to build their application based on their demand. Cloud data center is a bulk of resources on shared pool architecture for cloud user to access. Virtualization is the heart of the Cloud computing model, it provides virtual machine as per application specific configuration and those applications are free to choose their own configuration. On one hand, there is huge number of resources and on other hand it has to serve huge number of requests effectively. Therefore, resource allocation policy and scheduling policy play very important role in allocation and managing resources in this cloud computing model. This paper proposes the load balancing policy using Hungarian algorithm. Hungarian Algorithm provides dynamic load balancing policy with a monitor component. Monitor component helps to increase cloud resource utilization by managing the Hungarian algorithm by monitoring its state and altering its state based on artificial intelligent. CloudSim used in this proposal is an extensible toolkit and it simulates cloud computing environment.

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…

30 CFR 77.401 - Stationary grinding machines; protective devices.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Stationary grinding machines; protective... OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment § 77.401 Stationary grinding machines; protective devices. (a) Stationary grinding machines other than special bit grinders shall be equipped with...

30 CFR 75.1719-4 - Mining machines, cap lamps; requirements.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mining machines, cap lamps; requirements. 75... Mining machines, cap lamps; requirements. (a) Paint used on exterior surfaces of mining machines shall... frames or reflecting tape shall be installed on each end of mining machines, except that continuous...

30 CFR 18.54 - High-voltage continuous mining machines.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false High-voltage continuous mining machines. 18.54... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

Improving the Assessment of the Level of Regional Resources Management

Directory of Open Access Journals (Sweden)

Taraday Vladimir N.

2017-12-01

Full Text Available The work improves the assessment of the level of managing development resources by regions of Ukraine, which is based on the use of a comprehensive assessment — multidimensional comparative analysis (namely the rank-sum test and allows comparing the effectiveness of managing resource development in regions of Ukraine using the available data, on their status on the basis of a unified system of indicators, as well as comparing the level of managing development resources by each region of Ukraine in time. The uneven development of regions of the country is investigated, the growth of inter-regional socio-economic disproportions is revealed. It is determined that, having a fundamentally different composition and volume of natural, human, financial resources, the state and effectiveness of managing development resources by regions of Ukraine is significantly different. The level of managing development resources by regions of Ukraine is proposed to be assessed by the aggregate indicators characterizing the increase in the productivity of the regional economy, profitability of local business, and level of incomes of the population; general increase in social standards, quality of life and business environment.

An Effective Mechanism for Virtual Machine Placement using Aco in IAAS Cloud

Science.gov (United States)

Shenbaga Moorthy, Rajalakshmi; Fareentaj, U.; Divya, T. K.

2017-08-01

Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.

Cost-Benefit Analysis of Computer Resources for Machine Learning

Science.gov (United States)

Champion, Richard A.

2007-01-01

Machine learning describes pattern-recognition algorithms - in this case, probabilistic neural networks (PNNs). These can be computationally intensive, in part because of the nonlinear optimizer, a numerical process that calibrates the PNN by minimizing a sum of squared errors. This report suggests efficiencies that are expressed as cost and benefit. The cost is computer time needed to calibrate the PNN, and the benefit is goodness-of-fit, how well the PNN learns the pattern in the data. There may be a point of diminishing returns where a further expenditure of computer resources does not produce additional benefits. Sampling is suggested as a cost-reduction strategy. One consideration is how many points to select for calibration and another is the geometric distribution of the points. The data points may be nonuniformly distributed across space, so that sampling at some locations provides additional benefit while sampling at other locations does not. A stratified sampling strategy can be designed to select more points in regions where they reduce the calibration error and fewer points in regions where they do not. Goodness-of-fit tests ensure that the sampling does not introduce bias. This approach is illustrated by statistical experiments for computing correlations between measures of roadless area and population density for the San Francisco Bay Area. The alternative to training efficiencies is to rely on high-performance computer systems. These may require specialized programming and algorithms that are optimized for parallel performance.

STUDY OF THE VIBRATION LEVEL IN CASE OF MANUFACTURING ON A CNC MACHINE-TOOL

Directory of Open Access Journals (Sweden)

Ioan Călin ROȘCA

2015-12-01

Full Text Available The paper presents the results of an experimental research performed on a CNC machine tool type ISEL-GFV considering the vibration level developed during the manufacturing of different pieces of particleboard at six processing regimes. There were recorded signals on both time and frequency domains on the three main directions. Based on recorded data there are presented the main conclusions referring to the level of vibrations and the frequencies associated to the highest levels.

Virtual machine migration in an over-committed cloud

KAUST Repository

Zhang, Xiangliang

2012-04-01

While early emphasis of Infrastructure as a Service (IaaS) clouds was on providing resource elasticity to end users, providers are increasingly interested in over-committing their resources to maximize the utilization and returns of their capital investments. In principle, over-committing resources hedges that users - on average - only need a small portion of their leased resources. When such hedge fails (i.e., resource demand far exceeds available physical capacity), providers must mitigate this provider-induced overload, typically by migrating virtual machines (VMs) to underutilized physical machines. Recent works on VM placement and migration assume the availability of target physical machines [1], [2]. However, in an over-committed cloud data center, this is not the case. VM migration can even trigger cascading overloads if performed haphazardly. In this paper, we design a new VM migration algorithm (called Scattered) that minimizes VM migrations in over-committed data centers. Compared to a traditional implementation, our algorithm can balance host utilization across all time epochs. Using real-world data traces from an enterprise cloud, we show that our migration algorithm reduces the risk of overload, minimizes the number of needed migrations, and has minimal impact on communication cost between VMs. © 2012 IEEE.

Electrical machines & drives

CERN Document Server

Hammond, P

1985-01-01

Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

30 CFR 18.49 - Connection boxes on machines.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Connection boxes on machines. 18.49 Section 18..., AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.49 Connection boxes on machines. Connection boxes used to facilitate replacement...

Resource variation in colorectal surgery: a national centre level analysis.

Science.gov (United States)

Drake, T M; Lee, M J; Senapati, A; Brown, S R

2017-07-01

Delivery of quality colorectal surgery requires adequate resources. We set out to assess the relationship between resources and outcomes in English colorectal units. Data were extracted from the Association of Coloproctology of Great Britain and Ireland resource questionnaire to profile resources. This was correlated with Hospital Episode Statistics outcome data including 90-day mortality and readmissions. Patient satisfaction measures were extracted from the Cancer Experience Patient Survey and compared at unit level. Centres were divided by workload into low, middle and top tertile. Completed questionnaires were received from 75 centres in England. Service resources were similar between low and top tertiles in access to Confidential Enquiry into Patient Outcome and Death (CEPOD) theatre, level two or three beds per 250 000 population or the likelihood of having a dedicated colorectal ward. There was no difference in staffing levels per 250 000 unit of population. Each 10% increase in the proportion of cases attempted laparoscopically was associated with reduced 90-day unplanned readmission (relative risk 0.94, 95% CI 0.91-0.97, P colorectal ward (relative risk 0.85, 95% CI 0.73-0.99, P = 0.040) was also associated with a significant reduction in unplanned readmissions. There was no association between staffing or service factors and patient satisfaction. Resource levels do not vary based on unit of population. There is benefit associated with increased use of laparoscopy and a dedicated surgical ward. Alternative measures to assess the relationship between resources and outcome, such as failure to rescue, should be explored in UK practice. Colorectal Disease © 2017 The Association of Coloproctology of Great Britain and Ireland.

Enhancing Cloud Resource Utilisation using Statistical Analysis

OpenAIRE

Sijin He; Li Guo; Yike Guo

2014-01-01

Resource provisioning based on virtual machine (VM) has been widely accepted and adopted in cloud computing environments. A key problem resulting from using static scheduling approaches for allocating VMs on different physical machines (PMs) is that resources tend to be not fully utilised. Although some existing cloud reconfiguration algorithms have been developed to address the problem, they normally result in high migration costs and low resource utilisation due to ignoring the multi-dimens...

Reverse engineering of wörner type drilling machine structure.

Science.gov (United States)

Wibowo, A.; Belly, I.; llhamsyah, R.; Indrawanto; Yuwana, Y.

2018-03-01

A product design needs to be modified based on the conditions of production facilities and existing resource capabilities without reducing the functional aspects of the product itself. This paper describes the reverse engineering process of the main structure of the wörner type drilling machine to obtain a machine structure design that can be made by resources with limited ability by using simple processes. Some structural, functional and the work mechanism analyzes have been performed to understand the function and role of each basic components. The process of dismantling of the drilling machine and measuring each of the basic components was performed to obtain sets of the geometry and size data of each component. The geometric model of each structure components and the machine assembly were built to facilitate the simulation process and machine performance analysis that refers to ISO standard of drilling machine. The tolerance stackup analysis also performed to determine the type and value of geometrical and dimensional tolerances, which could affect the ease of the components to be manufactured and assembled

Predicting genome-wide redundancy using machine learning

Directory of Open Access Journals (Sweden)

Shasha Dennis E

2010-11-01

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

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

OpenAIRE

Pahlevan, Ali; Qu, Xiaoyu; Zapater Sancho, Marina; Atienza Alonso, David

2017-01-01

Modern cloud data centers (DCs) need to tackle efficiently the increasing demand for computing resources and address the energy efficiency challenge. Therefore, it is essential to develop resource provisioning policies that are aware of virtual machine (VM) characteristics, such as CPU utilization and data communication, and applicable in dynamic scenarios. Traditional approaches fall short in terms of flexibility and applicability for large-scale DC scenarios. In this paper we propose a heur...

30 CFR 18.97 - Inspection of machines; minimum requirements.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Inspection of machines; minimum requirements... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.97 Inspection of machines; minimum...

Impact of implant–abutment connection and positioning of the machined collar/microgap on crestal bone level changes: a systematic review

Science.gov (United States)

Schwarz, Frank; Hegewald, Andrea; Becker, Jürgen

2014-01-01

Objectives To address the following focused question: What is the impact of implant–abutment configuration and the positioning of the machined collar/microgap on crestal bone level changes? Material and methods Electronic databases of the PubMed and the Web of Knowledge were searched for animal and human studies reporting on histological/radiological crestal bone level changes (CBL) at nonsubmerged one-/two-piece implants (placed in healed ridges) exhibiting different abutment configurations, positioning of the machined collar/microgap (between 1992 and November 2012: n = 318 titles). Quality assessment of selected full-text articles was performed according to the ARRIVE and CONSORT statement guidelines. Results A total of 13 publications (risk of bias: high) were eligible for the review. The weighted mean difference (WMD) (95% CI) between machined collars placed either above or below the bone crest amounted to 0.835 mm favoring an epicrestal positioning of the rough/smooth border (P abutment configurations. Due to a high heterogeneity, a meta-analysis was not feasible. Conclusions While the positioning of the machined neck and microgap may limit crestal bone level changes at nonsubmerged implants, the impact of the implant–abutment connection lacks documentation. PMID:23782338

THE AGGREGATE IMPLICATIONS OF MACHINE REPLACEMENT: THEORY AND EVIDENCE

OpenAIRE

John Haltiwanger; Russell Cooper

1992-01-01

The authors study an economy in which producers incur resource costs to replace depreciated machines. The process of costly replacement and depreciation creates endogenous fluctuations in productivity, employment, and output of a single producer. The authors explore the spillover effects of machine replacement on other sectors of the economy and provide conditions for synchronized machine replacement by multiple independent producers. The implications of their model are generally consistent w...

Quantum machine learning for quantum anomaly detection

Science.gov (United States)

Liu, Nana; Rebentrost, Patrick

2018-04-01

Anomaly detection is used for identifying data that deviate from "normal" data patterns. Its usage on classical data finds diverse applications in many important areas such as finance, fraud detection, medical diagnoses, data cleaning, and surveillance. With the advent of quantum technologies, anomaly detection of quantum data, in the form of quantum states, may become an important component of quantum applications. Machine-learning algorithms are playing pivotal roles in anomaly detection using classical data. Two widely used algorithms are the kernel principal component analysis and the one-class support vector machine. We find corresponding quantum algorithms to detect anomalies in quantum states. We show that these two quantum algorithms can be performed using resources that are logarithmic in the dimensionality of quantum states. For pure quantum states, these resources can also be logarithmic in the number of quantum states used for training the machine-learning algorithm. This makes these algorithms potentially applicable to big quantum data applications.

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

OpenAIRE

Hamed Hassanzadeh; MohammadReza Keyvanpour

2011-01-01

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as ...

A Virtual Machine Migration Strategy Based on Time Series Workload Prediction Using Cloud Model

Directory of Open Access Journals (Sweden)

Yanbing Liu

2014-01-01

Full Text Available Aimed at resolving the issues of the imbalance of resources and workloads at data centers and the overhead together with the high cost of virtual machine (VM migrations, this paper proposes a new VM migration strategy which is based on the cloud model time series workload prediction algorithm. By setting the upper and lower workload bounds for host machines, forecasting the tendency of their subsequent workloads by creating a workload time series using the cloud model, and stipulating a general VM migration criterion workload-aware migration (WAM, the proposed strategy selects a source host machine, a destination host machine, and a VM on the source host machine carrying out the task of the VM migration. Experimental results and analyses show, through comparison with other peer research works, that the proposed method can effectively avoid VM migrations caused by momentary peak workload values, significantly lower the number of VM migrations, and dynamically reach and maintain a resource and workload balance for virtual machines promoting an improved utilization of resources in the entire data center.

Energy-efficient electrical machines by new materials. Superconductivity in large electrical machines; Energieeffiziente elektrische Maschinen durch neue Materialien. Supraleitung in grossen elektrischen Maschinen

Energy Technology Data Exchange (ETDEWEB)

Frauenhofer, Joachim [Siemens, Nuernberg (Germany); Arndt, Tabea; Grundmann, Joern [Siemens, Erlangen (Germany)

2013-07-01

The implementation of superconducting materials in high-power electrical machines results in significant advantages regarding efficiency, size and dynamic behavior when compared to conventional machines. The application of HTS (high-temperature superconductors) in electrical machines allows significantly higher power densities to be achieved for synchronous machines. In order to gain experience with the new technology, Siemens carried out a series of development projects. A 400 kW model motor for the verification of a concept for the new technology was followed by a 4000 kV A generator as highspeed machine - as well as a low-speed 4000 kW propeller motor with high torque. The 4000 kVA generator is still employed to carry out long-term tests and to check components. Superconducting machines have significantly lower weight and envelope dimensions compared to conventional machines, and for this reason alone, they utilize resources better. At the same time, operating losses are slashed to about half and the efficiency increases. Beyond this, they set themselves apart as a result of their special features in operation, such as high overload capability, stiff alternating load behavior and low noise. HTS machines provide significant advantages where the reduction of footprint, weight and losses or the improved dynamic behavior results in significant improvements of the overall system. Propeller motors and generators,for ships, offshore plants, in wind turbine and hydroelectric plants and in large power stations are just some examples. HTS machines can therefore play a significant role when it comes to efficiently using resources and energy as well as reducing the CO{sub 2} emissions.

Demand Forecasting at Low Aggregation Levels using Factored Conditional Restricted Boltzmann Machine

DEFF Research Database (Denmark)

Mocanu, Elena; Nguyen, Phuong H.; Gibescu, Madeleine

2016-01-01

electric power consumption, local price and meteorological data collected from 1900 customers. The households are equipped with local generation and smart appliances capable of responding to realtime pricing signals. The results show that for the short-term (5 minute to 1 day ahead) prediction problems......The electrical demand forecasting problem can be regarded as a nonlinear time series prediction problem depending on many complex factors since it is required at various aggregation levels and at high temporal resolution. To solve this challenging problem, various time series and machine learning...... developed deep learning model for time series prediction, namely Factored Conditional Restricted Boltzmann Machine (FCRBM), and extend it for electrical demand forecasting. The assessment is made on the EcoGrid dataset, originating from the Bornholm island experiment in Denmark, consisting of aggregated...

PMLB: a large benchmark suite for machine learning evaluation and comparison.

Science.gov (United States)

Olson, Randal S; La Cava, William; Orzechowski, Patryk; Urbanowicz, Ryan J; Moore, Jason H

2017-01-01

The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. From this study, we find that existing benchmarks lack the diversity to properly benchmark machine learning algorithms, and there are several gaps in benchmarking problems that still need to be considered. This work represents another important step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future.

Optimal Placement Algorithms for Virtual Machines

OpenAIRE

Bellur, Umesh; Rao, Chetan S; SD, Madhu Kumar

2010-01-01

Cloud computing provides a computing platform for the users to meet their demands in an efficient, cost-effective way. Virtualization technologies are used in the clouds to aid the efficient usage of hardware. Virtual machines (VMs) are utilized to satisfy the user needs and are placed on physical machines (PMs) of the cloud for effective usage of hardware resources and electricity in the cloud. Optimizing the number of PMs used helps in cutting down the power consumption by a substantial amo...

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Preparation of machines for inspection... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection...

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...

Renewable material resource potential

NARCIS (Netherlands)

van Weenen, H.; Wever, R.; Quist, J.; Tukker, A.; Woudstra, J.; Boons, F.A.A.; Beute, N.

2010-01-01

Renewable material resources, consist of complex systems and parts. Their sub-systems and sub-sub-systems, have unique, specific, general and common properties. The character of the use that is made of these resources, depends on the availability of knowledge, experience, methods, tools, machines

Individual and group-level job resources and their relationships with individual work engagement.

Science.gov (United States)

Füllemann, Désirée; Brauchli, Rebecca; Jenny, Gregor J; Bauer, Georg F

2016-06-16

This study adds a multilevel perspective to the well-researched individual-level relationship between job resources and work engagement. In addition, we explored whether individual job resources cluster within work groups because of a shared psychosocial environment and investigated whether a resource-rich psychosocial work group environment is beneficial for employee engagement over and above the beneficial effect of individual job resources and independent of their variability within groups. Data of 1,219 employees nested in 103 work groups were obtained from a baseline employee survey of a large stress management intervention project implemented in six medium and large-sized organizations in diverse sectors. A variety of important job resources were assessed and grouped to an overall job resource factor with three subfactors (manager behavior, peer behavior, and task-related resources). Data were analyzed using multilevel random coefficient modeling. The results indicated that job resources cluster within work groups and can be aggregated to a group-level job resources construct. However, a resource-rich environment, indicated by high group-level job resources, did not additionally benefit employee work engagement but on the contrary, was negatively related to it. On the basis of this unexpected result, replication studies are encouraged and suggestions for future studies on possible underlying within-group processes are discussed. The study supports the presumed value of integrating work group as a relevant psychosocial environment into the motivational process and indicates a need to further investigate emergent processes involved in aggregation procedures across levels.

30 CFR 18.21 - Machines equipped with powered dust collectors.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Machines equipped with powered dust collectors... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.21 Machines equipped with powered dust collectors. Powered dust...

Towards green lubrication in machining

CERN Document Server

Liew Yun Hsien, Willey

2014-01-01

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

TSNA levels in machine-generated mainstream cigarette smoke: 35 years of data.

Science.gov (United States)

Appleton, Scott; Olegario, Raquel M; Lipowicz, Peter J

2013-07-01

This paper characterizes historical and current tobacco specific nitrosamine (TSNA) levels in mainstream (MS) cigarette smoke of US commercial cigarettes. To conduct this analysis, we gathered 35 years of published data of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N-nitrosonornicotine (NNN) levels in MS cigarette smoke. We also assessed internal data of MS smoke NNK and NNN levels generated from various market monitoring initiatives and from control cigarettes used in a multi-year program for testing cigarette ingredients. In all, we analyzed machine smoking data from 401 cigarette samples representing a wide range of products and design characteristics from multiple manufacturers and market leaders. There was no indication that TSNA levels systematically increased in cigarette MS smoke over the 35-year analysis period. In particular, TSNA levels expressed as either per cigarette or normalized for tar suggest a downward trend in MS smoke over the past 10 years. The apparent downward trend in TSNA levels in MS smoke may reflect industry and agricultural community efforts to reduce levels of TSNAs in tobacco and cigarette smoke. Copyright © 2013 Elsevier Inc. All rights reserved.

Machine learning based Intelligent cognitive network using fog computing

Science.gov (United States)

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

2017-05-01

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

Developing Probabilistic Operating Rules for Real-time Conjunctive Use of Surface and Groundwater Resources:Application of Support Vector Machines

Directory of Open Access Journals (Sweden)

Mohammad Reza Bazargan-Lari

2011-01-01

Full Text Available Developing optimal operating policies for conjunctive use of surface and groundwater resources when different decision makers and stakeholders with conflicting objectives are involved is usually a challenging task. This problem would be more complex when objectives related to surface and groundwater quality are taken into account. In this paper, a new methodology is developed for real time conjunctive use of surface and groundwater resources. In the proposed methodology, a well-known multi-objective genetic algorithm, namely Non-dominated Sorting Genetic Algorithm II (NSGA-II is employed to develop a Pareto front among the objectives. The Young conflict resolution theory is also used for resolving the conflict of interests among decision makers. To develop the real time conjunctive use operating rules, the Probabilistic Support Vector Machines (PSVMs, which are capable of providing probability distribution functions of decision variables, are utilized. The proposed methodology is applied to Tehran Aquifer inTehran metropolitan area,Iran. Stakeholders in the study area have some conflicting interests including supplying water with acceptable quality, reducing pumping costs, improving groundwater quality and controlling the groundwater table fluctuations. In the proposed methodology, MODFLOW and MT3D groundwater quantity and quality simulation models are linked with NSGA-II optimization model to develop Pareto fronts among the objectives. The best solutions on the Pareto fronts are then selected using the Young conflict resolution theory. The selected solution (optimal monthly operating policies is used to train and verify a PSVM. The results show the significance of applying an integrated conflict resolution approach and the capability of support vector machines for the real time conjunctive use of surface and groundwater resources in the study area. It is also shown that the validation accuracy of the proposed operating rules is higher that 80

A Four-Level Hierarchy for Organizing Wildland Stream Resource Information

Science.gov (United States)

Harry Parrott; Daniel A. Marion; R. Douglas Perkinson

1989-01-01

An analysis of current USDA Forest Service methods of collecting and using wildland stream resource data indicates that required information can be organized into a four-level hierarchy. Information at each level is tiered with information at the preceding level. Level 1 is the ASSOCIATION, which is differentiated by stream size and flow regime. Level 2, STREAM TYPE,...

The scheme machine: A case study in progress in design derivation at system levels

Science.gov (United States)

Johnson, Steven D.

1995-01-01

The Scheme Machine is one of several design projects of the Digital Design Derivation group at Indiana University. It differs from the other projects in its focus on issues of system design and its connection to surrounding research in programming language semantics, compiler construction, and programming methodology underway at Indiana and elsewhere. The genesis of the project dates to the early 1980's, when digital design derivation research branched from the surrounding research effort in programming languages. Both branches have continued to develop in parallel, with this particular project serving as a bridge. However, by 1990 there remained little real interaction between the branches and recently we have undertaken to reintegrate them. On the software side, researchers have refined a mathematically rigorous (but not mechanized) treatment starting with the fully abstract semantic definition of Scheme and resulting in an efficient implementation consisting of a compiler and virtual machine model, the latter typically realized with a general purpose microprocessor. The derivation includes a number of sophisticated factorizations and representations and is also deep example of the underlying engineering methodology. The hardware research has created a mechanized algebra supporting the tedious and massive transformations often seen at lower levels of design. This work has progressed to the point that large scale devices, such as processors, can be derived from first-order finite state machine specifications. This is roughly where the language oriented research stops; thus, together, the two efforts establish a thread from the highest levels of abstract specification to detailed digital implementation. The Scheme Machine project challenges hardware derivation research in several ways, although the individual components of the system are of a similar scale to those we have worked with before. The machine has a custom dual-ported memory to support garbage collection

The Advanced Labs Website: resources for upper-level laboratories

Science.gov (United States)

Torres-Isea, Ramon

2012-03-01

The Advanced Labs web resource collection is an effort to create a central, comprehensive information base for college/university faculty who teach upper-level undergraduate laboratories. The website is produced by the American Association of Physics Teachers (AAPT). It is a part of ComPADRE, the online collection of resources in physics and astronomy education, which itself is a part of the National Science Foundation-funded National Science Digital Library (NSDL). After a brief review of its history, we will discuss the current status of the website while describing the various types of resources available at the site and presenting examples of each. We will detail a step-by-step procedure for submitting resources to the website. The resource collection is designed to be a community effort and thus welcomes input and contributions from its users. We will also present plans, and will seek audience feedback, for additional website services and features. The constraints, roadblocks, and rewards of this project will also be addressed.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

Science.gov (United States)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Engagement techniques and playing level impact the biomechanical demands on rugby forwards during machine-based scrummaging.

Science.gov (United States)

Preatoni, Ezio; Stokes, Keith A; England, Michael E; Trewartha, Grant

2015-04-01

This cross-sectional study investigated the factors that may influence the physical loading on rugby forwards performing a scrum by studying the biomechanics of machine-based scrummaging under different engagement techniques and playing levels. 34 forward packs from six playing levels performed repetitions of five different types of engagement techniques against an instrumented scrum machine under realistic training conditions. Applied forces and body movements were recorded in three orthogonal directions. The modification of the engagement technique altered the load acting on players. These changes were in a similar direction and of similar magnitude irrespective of the playing level. Reducing the dynamics of the initial engagement through a fold-in procedure decreased the peak compression force, the peak downward force and the engagement speed in excess of 30%. For example, peak compression (horizontal) forces in the professional teams changed from 16.5 (baseline technique) to 8.6 kN (fold-in procedure). The fold-in technique also reduced the occurrence of combined high forces and head-trunk misalignment during the absorption of the impact, which was used as a measure of potential hazard, by more than 30%. Reducing the initial impact did not decrease the ability of the teams to produce sustained compression forces. De-emphasising the initial impact against the scrum machine decreased the mechanical stresses acting on forward players and may benefit players' welfare by reducing the hazard factors that may induce chronic degeneration of the spine. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Using the CMS high level trigger as a cloud resource

International Nuclear Information System (INIS)

Colling, David; Huffman, Adam; Bauer, Daniela; McCrae, Alison; Cinquilli, Mattia; Gowdy, Stephen; Coarasa, Jose Antonio; Ozga, Wojciech; Chaze, Olivier; Lahiff, Andrew; Grandi, Claudio; Tiradani, Anthony; Sgaravatto, Massimo

2014-01-01

The CMS High Level Trigger is a compute farm of more than 10,000 cores. During data taking this resource is heavily used and is an integral part of the experiment's triggering system. However, outside of data taking periods this resource is largely unused. We describe why CMS wants to use the HLT as a cloud resource (outside of data taking periods) and how this has been achieved. In doing this we have turned a single-use cluster into an agile resource for CMS production computing. While we are able to use the HLT as a production cloud resource, there is still considerable further work that CMS needs to carry out before this resource can be used with the desired agility. This report, therefore, represents a snapshot of this activity at the time of CHEP 2013.

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.

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

Science.gov (United States)

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Wireless Device-to-Device (D2D) Links for Machine-to-Machine (M2M) Communication

DEFF Research Database (Denmark)

Pratas, Nuno; Popovski, Petar

2017-01-01

Device-to-Device (D2D) communications will play an important role in the fifth generation (5G) cellular networks, by increasing the spatial reuse of spectrum resources and enabling communication links with low latency. D2D is composed of two fundamental building blocks: proximity discovery...... and direct communication between nearby users. Another emerging trend in wireless cellular systems is Machine-to-Machine (M2M) communications, often characterized by fixed, low transmission rates. In this chapter we motivate the synergy between D2D and M2M, and present technologies that enable M2M-via-D2D...

Advances Towards Synthetic Machines at the Molecular and Nanoscale Level

Directory of Open Access Journals (Sweden)

Kristina Konstas

2010-06-01

Full Text Available The fabrication of increasingly smaller machines to the nanometer scale can be achieved by either a “top-down” or “bottom-up” approach. While the former is reaching its limits of resolution, the latter is showing promise for the assembly of molecular components, in a comparable approach to natural systems, to produce functioning ensembles in a controlled and predetermined manner. In this review we focus on recent progress in molecular systems that act as molecular machine prototypes such as switches, motors, vehicles and logic operators.

Transposition and national level resources

DEFF Research Database (Denmark)

Vasev, Nikolay Rumenov; Vrangbæk, Karsten

2014-01-01

Several recent papers have summarised the status of EU implementation studies. In this paper we suggest that the issue of sector specific resources has received too little attention in previous studies. Sector specific resources include “health sector resources” and “state administrative resources......”. Our theoretical contribution is thus to add an explicit and more detailed concern for "sector specific resources" in national transposition. This can refine the understanding of resources, for example in the multi-variable models that are emerging as the state of the art in the field of EU...... implementation studies. To illustrate these points we have chosen an empirical design focusing on a directive with a potentially high impact on system resources and several ambiguous components (the Cross Border Health Care Directive). We have further chosen to focus on two Eastern European countries (Bulgaria...

Language Model Adaptation Using Machine-Translated Text for Resource-Deficient Languages

Directory of Open Access Journals (Sweden)

Sadaoki Furui

2009-01-01

Full Text Available Text corpus size is an important issue when building a language model (LM. This is a particularly important issue for languages where little data is available. This paper introduces an LM adaptation technique to improve an LM built using a small amount of task-dependent text with the help of a machine-translated text corpus. Icelandic speech recognition experiments were performed using data, machine translated (MT from English to Icelandic on a word-by-word and sentence-by-sentence basis. LM interpolation using the baseline LM and an LM built from either word-by-word or sentence-by-sentence translated text reduced the word error rate significantly when manually obtained utterances used as a baseline were very sparse.

A computer architecture for intelligent machines

Science.gov (United States)

Lefebvre, D. R.; Saridis, G. N.

1992-01-01

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Machine function based control code algebras

NARCIS (Netherlands)

Bergstra, J.A.

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

Findings From the National Machine Guarding Program-A Small Business Intervention: Machine Safety.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Xi, Min; Brosseau, Lisa M; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2016-09-01

The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P increase in LOTO program scores (P < 0.0001). Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees.

Creativity in Machine Learning

OpenAIRE

Thoma, Martin

2016-01-01

Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as text and as audio. This paper gives a high level overview of how they are created and gives some examples. It is meant to be a summary of the current work and give people who are new to machine learning some starting points.

Candu 600 fuelling machine testing, the romanian experience

International Nuclear Information System (INIS)

Valeca, S.; Doca, C.; Iorga, C.

2013-01-01

The Candu 600 Fuelling Machine is a complex mechanism which must run in safety conditions and with high reliability in the Candu Reactor. The testing and commissioning process of this nuclear equipment meets the high standards of NPPs requirements using special technological facilities, modern measurement instruments as well the appropriate IT resources for data acquisition and processing. The paper presents the experience of the Institute for Nuclear Research Pitesti, Romania, in testing Candu 600 Fuelling Machines, inclusive the implied facilities, and in development of four simulators: two dedicated for the training of the Candu 600 Fuelling Machine Operators, and another two to simulate some process signals and actions. (authors)

County-Level Population Economic Status and Medicare Imaging Resource Consumption.

Science.gov (United States)

Rosenkrantz, Andrew B; Hughes, Danny R; Prabhakar, Anand M; Duszak, Richard

2017-06-01

The aim of this study was to assess relationships between county-level variation in Medicare beneficiary imaging resource consumption and measures of population economic status. The 2013 CMS Geographic Variation Public Use File was used to identify county-level per capita Medicare fee-for-service imaging utilization and nationally standardized costs to the Medicare program. The County Health Rankings public data set was used to identify county-level measures of population economic status. Regional variation was assessed, and multivariate regressions were performed. Imaging events per 1,000 Medicare beneficiaries varied 1.8-fold (range, 2,723-4,843) at the state level and 5.3-fold (range, 1,228-6,455) at the county level. Per capita nationally standardized imaging costs to Medicare varied 4.2-fold (range, $84-$353) at the state level and 14.1-fold (range, $33-$471) at the county level. Within individual states, county-level utilization varied on average 2.0-fold (range, 1.1- to 3.1-fold), and costs varied 2.8-fold (range, 1.1- to 6.4-fold). For both large urban populations and small rural states, Medicare imaging resource consumption was heterogeneously variable at the county level. Adjusting for county-level gender, ethnicity, rural status, and population density, countywide unemployment rates showed strong independent positive associations with Medicare imaging events (β = 26.96) and costs (β = 4.37), whereas uninsured rates showed strong independent positive associations with Medicare imaging costs (β = 2.68). Medicare imaging utilization and costs both vary far more at the county than at the state level. Unfavorable measures of county-level population economic status in the non-Medicare population are independently associated with greater Medicare imaging resource consumption. Future efforts to optimize Medicare imaging use should consider the influence of local indigenous socioeconomic factors outside the scope of traditional beneficiary-focused policy

Findings from the National Machine Guarding Program–A Small Business Intervention: Machine Safety

Science.gov (United States)

Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 – 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of OSHA citations and may result in serious traumatic injury. Methods Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits and a twelve-month follow-up evaluation. Results The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10-percentage point increase in business-level machine scores (p< 0.0001) and a 33-percentage point increase in LOTO program scores (p <0.0001). Conclusions Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:26716850

Machine learning for network-based malware detection

DEFF Research Database (Denmark)

Stevanovic, Matija

and based on different, mutually complementary, principles of traffic analysis. The proposed approaches rely on machine learning algorithms (MLAs) for automated and resource-efficient identification of the patterns of malicious network traffic. We evaluated the proposed methods through extensive evaluations...

Utvärdering av Amazon Machine Learning för taggsystem

OpenAIRE

Madosh, Farzana; Lundsten, Erik

2017-01-01

How companies deal with machine learning is currently a highly-discussed topic, as it can facilitate corporate manual work by training computers to recognize patterns and thus automate the working procedure. However, this requires resources and knowledge in the field. As a result, various companies like Amazon and Google provide machine learning services without requiring the user to have deep knowledge in the area. This study evaluates Amazon Machine Learning program for a tag system with da...

Machine learning with R cookbook

CERN Document Server

Chiu, Yu-Wei

2015-01-01

If you want to learn how to use R for machine learning and gain insights from your data, then this book is ideal for you. Regardless of your level of experience, this book covers the basics of applying R to machine learning through to advanced techniques. While it is helpful if you are familiar with basic programming or machine learning concepts, you do not require prior experience to benefit from this book.

Strategic Uncertainty in Markets for Nonrenewable Resources: A Level-k Approach

Directory of Open Access Journals (Sweden)

Ingmar Vierhaus

2017-01-01

Full Text Available Existing models of nonrenewable resources assume that sophisticated agents compete with other sophisticated agents. This study instead uses a level-k approach to examine cases where the focal agent is uncertain about the strategy of his opponent or predicts that the opponent will act in a nonsophisticated manner. Level-0 players are randomized uniformly across all possible actions, and level-k players best respond to the action of player k-1. We study a dynamic nonrenewable resource game with a large number of actions. We are able to solve for the level-1 strategy by reducing the averaging problem to an optimization problem against a single action. We show that lower levels of strategic reasoning are close to the Walras and collusive benchmark, whereas higher level strategies converge to the Nash-Hotelling equilibrium. These results are then fitted to experimental data, suggesting that the level of sophistication of participants increased over the course of the experiment.

30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Boring-type machines equipped for auxiliary..., DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for...

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.

Proactive condition monitoring of low-speed machines

CERN Document Server

Stamboliska, Zhaklina; Moczko, Przemyslaw

2015-01-01

This book broadens readers’ understanding of proactive condition monitoring of low-speed machines in heavy industries. It focuses on why low-speed machines are different than others and how maintenance of these machines should be implemented with particular attention. The authors explain the best available monitoring techniques for various equipment and the principle of how to get proactive information from each technique. They further put forward possible strategies for application of FEM for detection of faults and technical assessment of machinery. Implementation phases are described and industrial case-studies of proactive condition monitoring are included. Proactive Condition Monitoring of Low-Speed Machines is an essential resource for engineers and technical managers across a range of industries as well as design engineers working in industrial product development. This book also: ·         Explains the practice of proactive condition monitoring and illustrates implementation phases ·   ...

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...

Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levels

Science.gov (United States)

Dral, Pavlo O.; Owens, Alec; Yurchenko, Sergei N.; Thiel, Walter

2017-06-01

We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to automatically assign nuclear configurations from a pre-defined grid to the training and prediction sets, respectively. Accurate high-level ab initio energies are required only for the points in the training set, while the energies for the remaining points are provided by the ML model with negligible computational cost. The proposed sampling procedure is shown to be superior to random sampling and also eliminates the need for training several ML models. Self-correcting machine learning has been implemented such that each additional layer corrects errors from the previous layer. The performance of our approach is demonstrated in a case study on a published high-level ab initio PES of methyl chloride with 44 819 points. The ML model is trained on sets of different sizes and then used to predict the energies for tens of thousands of nuclear configurations within seconds. The resulting datasets are utilized in variational calculations of the vibrational energy levels of CH3Cl. By using both structure-based sampling and self-correction, the size of the training set can be kept small (e.g., 10% of the points) without any significant loss of accuracy. In ab initio rovibrational spectroscopy, it is thus possible to reduce the number of computationally costly electronic structure calculations through structure-based sampling and self-correcting KRR-based machine learning by up to 90%.

Formal modeling of virtual machines

Science.gov (United States)

Cremers, A. B.; Hibbard, T. N.

1978-01-01

Systematic software design can be based on the development of a 'hierarchy of virtual machines', each representing a 'level of abstraction' of the design process. The reported investigation presents the concept of 'data space' as a formal model for virtual machines. The presented model of a data space combines the notions of data type and mathematical machine to express the close interaction between data and control structures which takes place in a virtual machine. One of the main objectives of the investigation is to show that control-independent data type implementation is only of limited usefulness as an isolated tool of program development, and that the representation of data is generally dictated by the control context of a virtual machine. As a second objective, a better understanding is to be developed of virtual machine state structures than was heretofore provided by the view of the state space as a Cartesian product.

Effective Management of Human Resources for Business and ...

African Journals Online (AJOL)

Manpower is one of the many resources of an organization. Its relevance cannot be over emphasized as it combines other resources such as capital, materials, and machines, together to achieve organizational goal. Therefore effective management of human resources is pertinent for business and church growth.

Molecular machines with bio-inspired mechanisms.

Science.gov (United States)

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

2018-02-26

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

Function Concepts for Machine Parts

DEFF Research Database (Denmark)

Mortensen, Niels Henrik

1999-01-01

The majority of resources, like time and costs, consumed in industrial product development can be related to detailed design, i.e. the materialisation of machine parts (German Maschinenteile). Existing design theories based on a systems approach, e.g. Haberfellner [5] all have function, i.......e. transformation from input to output or ability to deliver purposeful effects as the core concept. The units in a product which posses functions are the organs (German: Funktionsträgern). Because individual parts do not posses functions, one could argue that the design theories based on a systems approach...... to be identification of a purposeful behaviour concept, i.e. function for a machine part. The contribution is based on the theory of technical systems, Hubka and the domain theory, Andreasen....

LHCb experience with running jobs in virtual machines

Science.gov (United States)

McNab, A.; Stagni, F.; Luzzi, C.

2015-12-01

The LHCb experiment has been running production jobs in virtual machines since 2013 as part of its DIRAC-based infrastructure. We describe the architecture of these virtual machines and the steps taken to replicate the WLCG worker node environment expected by user and production jobs. This relies on the uCernVM system for providing root images for virtual machines. We use the CernVM-FS distributed filesystem to supply the root partition files, the LHCb software stack, and the bootstrapping scripts necessary to configure the virtual machines for us. Using this approach, we have been able to minimise the amount of contextualisation which must be provided by the virtual machine managers. We explain the process by which the virtual machine is able to receive payload jobs submitted to DIRAC by users and production managers, and how this differs from payloads executed within conventional DIRAC pilot jobs on batch queue based sites. We describe our operational experiences in running production on VM based sites managed using Vcycle/OpenStack, Vac, and HTCondor Vacuum. Finally we show how our use of these resources is monitored using Ganglia and DIRAC.

Socio–economic benefits and pollution levels of water resources ...

African Journals Online (AJOL)

Communities are dependent on wetlands resources for income generation. However, anthropogenic activities that result into pollution of water are one of the major public health problems. Assessment of socio–economic activities and pollution levels of domestic water sources in Gulu Municipality, Pece wetland was done.

A real-time Java tool chain for resource constrained platforms

DEFF Research Database (Denmark)

Korsholm, Stephan Erbs; Søndergaard, Hans; Ravn, Anders P.

2013-01-01

The Java programming language was originally developed for embedded systems, but the resource requirements of previous and current Java implementations - especially memory consumption - tend to exclude them from being used on a significant class of resource constrained embedded platforms. The con......The Java programming language was originally developed for embedded systems, but the resource requirements of previous and current Java implementations - especially memory consumption - tend to exclude them from being used on a significant class of resource constrained embedded platforms...... by integrating: (1) a lean virtual machine (HVM) without any external dependencies on POSIX-like libraries or other OS functionalities, (2) a hardware abstraction layer, implemented almost entirely in Java through the use of hardware objects, first level interrupt handlers, and native variables, and (3....... An evaluation of the presented solution shows that the miniCDj benchmark gets reduced to a size where it can run on resource constrained platforms....

Some Considerations about Modern Database Machines

Directory of Open Access Journals (Sweden)

Manole VELICANU

2010-01-01

Full Text Available Optimizing the two computing resources of any computing system - time and space - has al-ways been one of the priority objectives of any database. A current and effective solution in this respect is the computer database. Optimizing computer applications by means of database machines has been a steady preoccupation of researchers since the late seventies. Several information technologies have revolutionized the present information framework. Out of these, those which have brought a major contribution to the optimization of the databases are: efficient handling of large volumes of data (Data Warehouse, Data Mining, OLAP – On Line Analytical Processing, the improvement of DBMS – Database Management Systems facilities through the integration of the new technologies, the dramatic increase in computing power and the efficient use of it (computer networks, massive parallel computing, Grid Computing and so on. All these information technologies, and others, have favored the resumption of the research on database machines and the obtaining in the last few years of some very good practical results, as far as the optimization of the computing resources is concerned.

Resource-level QoS metric for CPU-based guarantees in cloud providers

OpenAIRE

Goiri Presa, Íñigo; Julià Massó, Ferran; Fitó, Josep Oriol; Macías Lloret, Mario; Guitart Fernández, Jordi

2010-01-01

Success of Cloud computing requires that both customers and providers can be confident that signed Service Level Agreements (SLA) are supporting their respective business activities to their best extent. Currently used SLAs fail in providing such confidence, especially when providers outsource resources to other providers. These resource providers typically support very simple metrics, or metrics that hinder an efficient exploitation of their resources. In this paper, we propose a re...

Experimental comparison of support vector machines with random ...

Indian Academy of Sciences (India)

dient method, support vector machines, and random forests to improve producer accuracy and overall classification accuracy. The performance comparison of these classifiers is valuable for a decision maker ... ping, surveillance system, resource management, tracking ... rocks, water bodies, and anthropogenic elements,.

Towards a durability test for washing-machines.

Science.gov (United States)

Stamminger, Rainer; Tecchio, Paolo; Ardente, Fulvio; Mathieux, Fabrice; Niestrath, Phoebe

2018-04-01

Durability plays a key role in enhancing resource conservation and contributing to waste minimization. The washing-machine product group represents a relevant case study for the development of a durability test and as a potential trigger to systematically address durability in the design of products. We developed a procedure to test the durability performance of washing-machines as a main objective of this research. The research method consisted of an analysis of available durability standards and procedures to test products and components, followed by an analysis of relevant references related to frequent failures. Finally, we defined the criteria and the conditions for a repeatable, relatively fast and relevant endurance test. The durability test considered the whole product tested under conditions of stress. A series of spinning cycles with fixed imbalanced loads was run on two washing-machines to observe failures and performance changes during the test. Even though no hard failures occurred, results clearly showed that not all washing-machines can sustain such a test without abrasion or performance deterioration. However, the attempt to reproduce the stress induced on a washing-machine by carrying out a high number of pure spinning cycles with fixed loads did not allow equal testing conditions: the actions of the control procedure regarding imbalanced loads differ from machine to machine. The outcomes of this research can be used as grounds to develop standardised durability tests and to, hence, contribute to the development of future product policy measures.

Spatial variability of noise level in agricultural machines Variabilidade espacial do nível de ruído em máquinas agrícolas

OpenAIRE

Tadayuki Yanagi Junior; Leonardo Schiassi; Diogo F. Rossoni; Patrícia F. Ponciano; Renato R. de Lima

2012-01-01

The knowledge of the spatial variability of noise levels and the build of kriging maps can help the evaluation of the salubrity of environments occupied by agricultural workers. Therefore, the objective of this research was to characterize the spatial variability of the noise level generated by four agricultural machines, using geostatistics, and to verify if the values are within the limits of human comfort. The evaluated machines were: harvester, chainsaw, brushcutter and tractor. The data ...

Individual and group-level job resources and their relationships with individual work engagement

OpenAIRE

F?llemann, D?sir?e; Brauchli, Rebecca; Jenny, Gregor J.; Bauer, Georg F.

2016-01-01

Objectives: This study adds a multilevel perspective to the well-researched individual-level relationship between job resources and work engagement. In addition, we explored whether individual job resources cluster within work groups because of a shared psychosocial environment and investigated whether a resource-rich psychosocial work group environment is beneficial for employee engagement over and above the beneficial effect of individual job resources and independent of their variability w...

Machine-learned and codified synthesis parameters of oxide materials

Science.gov (United States)

Kim, Edward; Huang, Kevin; Tomala, Alex; Matthews, Sara; Strubell, Emma; Saunders, Adam; McCallum, Andrew; Olivetti, Elsa

2017-09-01

Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine learning techniques have recently been harnessed to generate synthesis strategies for select materials of interest. Still, a community-accessible, autonomously-compiled synthesis planning resource which spans across materials systems has not yet been developed. In this work, we present a collection of aggregated synthesis parameters computed using the text contained within over 640,000 journal articles using state-of-the-art natural language processing and machine learning techniques. We provide a dataset of synthesis parameters, compiled autonomously across 30 different oxide systems, in a format optimized for planning novel syntheses of materials.

30 CFR 75.703-3 - Approved methods of grounding offtrack mobile, portable and stationary direct-current machines.

Science.gov (United States)

2010-07-01

..., portable and stationary direct-current machines. 75.703-3 Section 75.703-3 Mineral Resources MINE SAFETY... stationary direct-current machines. In grounding offtrack direct-current machines and the enclosures of their... requirements: (1) Installation of silicon diodes shall be restricted to electric equipment receiving power from...

Very-high-level neutral-beam control system

International Nuclear Information System (INIS)

Elischer, V.; Jacobson, V.; Theil, E.

1981-10-01

As increasing numbers of neutral beams are added to fusion machines, their operation can consume a significant fraction of a facility's total resources. LBL has developed a very high level control system that allows a neutral beam injector to be treated as a black box with just 2 controls: one to set the beam power and one to set the pulse duration. This 2 knob view allows simple operation and provides a natural base for implementing even higher level controls such as automatic source conditioning

Identification of variables and their influence on the human resources planning in the territorial level

Energy Technology Data Exchange (ETDEWEB)

Martínez Vivar, R.; Sánchez Rodríguez, A.; Pérez Campdesuñer, R.; García Vidal, G.

2016-07-01

The purpose of this paper lies in the use of experimental way through empirical tools for identification of the set of variables and their interrelationships and influences on the human resources planning at the territorial level. The methodology used to verify the existence of the variables that affect the planning of human resources at the territorial level consists of two phases: a qualitative study of the variables that influence the planning of human resources, where the explicit variables are measured and / or implied raised in the literature analyzing the main contributions and limitations expressed by each of the authors consulted. Then it proceeds to confirmatory phase (quantitative) to prove the existence of the dimensions of the planning of human resources in the territorial level through the use of multivariate statistics through the combination of expert analysis and techniques of factorial grouping. Identification is achieved by using empirical methods, variables that affect human resources planning at the territorial level, as well as their grouping essential dimensions, while the description of a theoretical model that integrates the dimensions is made essential and relationships that affect human resource planning at the regional level, which is characterized by the existence of systemic and prospective nature. The literature shows two streams that address a wide range of approaches to human resources planning. The first is oriented from the business object and the second part of the management in highlighting a limited territorial level to address this latest theoretical development, an element that has contributed to the fragmented treatment of human resources planning and management in general at this level. The originality of this paper is part of the creation and adaptation, on a scientific basis of a theoretical model developed from the conceptual contribution of this process at the territorial level where the key variables that affect this

Theoretical Aspects of Optimizing the Allocation of Public Financial Resources at Local Level

OpenAIRE

Eugen DOGARIU

2010-01-01

The allocation of financial resources at local, but also at central level, is an issue especially since in times of crisis, finding the optimum way to spend public funds concerns all authorities. This paper aims to identify the ways in which, by leaving from the division of powers based on the allocation of resources and tools available, the local authorities can identify an optimal level of public expenditure so as to achieve a maximum level of using them. Also, the paper seeks to identify t...

30 CFR 18.80 - Approval of machines assembled with certified or explosion-proof components.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approval of machines assembled with certified... ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Machines Assembled With Certified or Explosion-Proof Components, Field...

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...

Hybrid resource provisioning for clouds

International Nuclear Information System (INIS)

Rahman, Mahfuzur; Graham, Peter

2012-01-01

Flexible resource provisioning, the assignment of virtual machines (VMs) to physical machine, is a key requirement for cloud computing. To achieve 'provisioning elasticity', the cloud needs to manage its available resources on demand. A-priori, static, VM provisioning introduces no runtime overhead but fails to deal with unanticipated changes in resource demands. Dynamic provisioning addresses this problem but introduces runtime overhead. To reduce VM management overhead so more useful work can be done and to also avoid sub-optimal provisioning we propose a hybrid approach that combines static and dynamic provisioning. The idea is to adapt a good initial static placement of VMs in response to evolving load characteristics, using live migration, as long as the overhead of doing so is low and the effectiveness is high. When this is no longer so, we trigger a revised static placement. (Thus, we are essentially applying local multi-objective optimization to tune a global optimization with reduced overhead.) This approach requires a complicated migration decision algorithm based on current and predicted:future workloads, power consumptions and memory usage in the host machines as well as network burst characteristics for the various possible VM multiplexings (combinations of VMs on a host). A further challenge is to identify those characteristics of the dynamic provisioning that should trigger static re-provisioning.

Management of business economic growth as function of resource rents

Science.gov (United States)

Prljić, Stefan; Nikitović, Zorana; Stojanović, Aleksandra Golubović; Cogoljević, Dušan; Pešić, Gordana; Alizamir, Meysam

2018-02-01

Economic profit could be influenced by economic rents. However natural resource rents provided different impact on the economic growth or economic profit. The main focus of the study was to evaluate the economic growth as function of natural resource rents. For such a purpose machine learning approach, artificial neural network, was used. The used natural resource rents were coal rents, forest rents, mineral rents, natural gas rents and oil rents. Based on the results it is concluded that the machine learning approach could be used as the tool for the economic growth evaluation as function of natural resource rents. Moreover the more advanced approaches should be incorporated to improve more the forecasting accuracy.

A real-time Java tool chain for resource constrained platforms

DEFF Research Database (Denmark)

Korsholm, Stephan E.; Søndergaard, Hans; Ravn, Anders Peter

2014-01-01

The Java programming language was originally developed for embedded systems, but the resource requirements of previous and current Java implementations – especially memory consumption – tend to exclude them from being used on a significant class of resource constrained embedded platforms. The con......The Java programming language was originally developed for embedded systems, but the resource requirements of previous and current Java implementations – especially memory consumption – tend to exclude them from being used on a significant class of resource constrained embedded platforms...... by integrating the following: (1) a lean virtual machine without any external dependencies on POSIX-like libraries or other OS functionalities; (2) a hardware abstraction layer, implemented almost entirely in Java through the use of hardware objects, first level interrupt handlers, and native variables; and (3....... An evaluation of the presented solution shows that the miniCDj benchmark gets reduced to a size where it can run on resource constrained platforms....

Seeing is Believing: Simulating Resource-Extraction Problems With Gams Ide and Microsoft Excel in an Intermediate-Level Natural-Resource Economics Course

OpenAIRE

Caplan, Arthur J.

2004-01-01

In this paper we provide several GAMS- and Excel-based resource-extraction models that can be used in an intermediate-level natural-resource economics course to numerically solve a host of exhaustible- and replenishable-resource problems, and thereby help verify the intuition and symbolic solutions provided in the textbook. The specific textbook from which the examples are drawn is Tietenberg (2003).

Towards energy and resource efficient manufacturing: A processes and systems approach

DEFF Research Database (Denmark)

Duflou, Joost R.; Sutherland, John W.; Dornfeld, David

2012-01-01

, distinguishing different system scale levels, is applied: starting from a unit process focus, respectively the multi-machine, factory, multi-facility and supply chain levels are covered. Determined by the research contributions reported in literature, the de facto focus of the paper is mainly on energy related......This paper aims to provide a systematic overview of the state of the art in energy and resource efficiency increasing methods and techniques in the domain of discrete part manufacturing, with attention for the effectiveness of the available options. For this purpose a structured approach...

Assisting the Tooling and Machining Industry to Become Energy Efficient

Energy Technology Data Exchange (ETDEWEB)

Curry, Bennett [Arizona Commerce Authority, Phoenix, AZ (United States)

2016-12-30

The Arizona Commerce Authority (ACA) conducted an Innovation in Advanced Manufacturing Grant Competition to support and grow southern and central Arizona’s Aerospace and Defense (A&D) industry and its supply chain. The problem statement for this grant challenge was that many A&D machining processes utilize older generation CNC machine tool technologies that can result an inefficient use of resources – energy, time and materials – compared to the latest state-of-the-art CNC machines. Competitive awards funded projects to develop innovative new tools and technologies that reduce energy consumption for older generation machine tools and foster working relationships between industry small to medium-sized manufacturing enterprises and third-party solution providers. During the 42-month term of this grant, 12 competitive awards were made. Final reports have been included with this submission.

Experimental analysis of electro-pneumatic optimization of hot stamping machine control systems with on-delay timer

OpenAIRE

Bankole I. Oladapo; Vincent A. Balogun; Adeyinka O.M. Adeoye; Ige E. Olubunmi; Samuel O. Afolabi

2017-01-01

The sustainability criterion in the manufacturing industries is imperative, especially in the automobile industries. Currently, efforts are being made by the industries to mitigate CO2 emission by the total vehicle weight optimization, machine utilization and resource efficiency. In lieu of this, it is important to understudy the manufacturing machines adopted in the automobile industries. One of such machine is the hot stamping machine that is used for about 35% of the manufacturing operatio...

Machine learning a Bayesian and optimization perspective

CERN Document Server

Theodoridis, Sergios

2015-01-01

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...

Virtual Machine Language 2.1

Science.gov (United States)

Riedel, Joseph E.; Grasso, Christopher A.

2012-01-01

VML (Virtual Machine Language) is an advanced computing environment that allows spacecraft to operate using mechanisms ranging from simple, time-oriented sequencing to advanced, multicomponent reactive systems. VML has developed in four evolutionary stages. VML 0 is a core execution capability providing multi-threaded command execution, integer data types, and rudimentary branching. VML 1 added named parameterized procedures, extensive polymorphism, data typing, branching, looping issuance of commands using run-time parameters, and named global variables. VML 2 added for loops, data verification, telemetry reaction, and an open flight adaptation architecture. VML 2.1 contains major advances in control flow capabilities for executable state machines. On the resource requirements front, VML 2.1 features a reduced memory footprint in order to fit more capability into modestly sized flight processors, and endian-neutral data access for compatibility with Intel little-endian processors. Sequence packaging has been improved with object-oriented programming constructs and the use of implicit (rather than explicit) time tags on statements. Sequence event detection has been significantly enhanced with multi-variable waiting, which allows a sequence to detect and react to conditions defined by complex expressions with multiple global variables. This multi-variable waiting serves as the basis for implementing parallel rule checking, which in turn, makes possible executable state machines. The new state machine feature in VML 2.1 allows the creation of sophisticated autonomous reactive systems without the need to develop expensive flight software. Users specify named states and transitions, along with the truth conditions required, before taking transitions. Transitions with the same signal name allow separate state machines to coordinate actions: the conditions distributed across all state machines necessary to arm a particular signal are evaluated, and once found true, that

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.

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.

Machine Learning Approaches in Cardiovascular Imaging.

Science.gov (United States)

Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

2017-10-01

Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

[A new machinability test machine and the machinability of composite resins for core built-up].

Science.gov (United States)

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

Machine learning for micro-tomography

Science.gov (United States)

Parkinson, Dilworth Y.; Pelt, Daniël. M.; Perciano, Talita; Ushizima, Daniela; Krishnan, Harinarayan; Barnard, Harold S.; MacDowell, Alastair A.; Sethian, James

2017-09-01

Machine learning has revolutionized a number of fields, but many micro-tomography users have never used it for their work. The micro-tomography beamline at the Advanced Light Source (ALS), in collaboration with the Center for Applied Mathematics for Energy Research Applications (CAMERA) at Lawrence Berkeley National Laboratory, has now deployed a series of tools to automate data processing for ALS users using machine learning. This includes new reconstruction algorithms, feature extraction tools, and image classification and recommen- dation systems for scientific image. Some of these tools are either in automated pipelines that operate on data as it is collected or as stand-alone software. Others are deployed on computing resources at Berkeley Lab-from workstations to supercomputers-and made accessible to users through either scripting or easy-to-use graphical interfaces. This paper presents a progress report on this work.

Learning Machines Implemented on Non-Deterministic Hardware

OpenAIRE

Gupta, Suyog; Sindhwani, Vikas; Gopalakrishnan, Kailash

2014-01-01

This paper highlights new opportunities for designing large-scale machine learning systems as a consequence of blurring traditional boundaries that have allowed algorithm designers and application-level practitioners to stay -- for the most part -- oblivious to the details of the underlying hardware-level implementations. The hardware/software co-design methodology advocated here hinges on the deployment of compute-intensive machine learning kernels onto compute platforms that trade-off deter...

2015 International Conference on Machine Learning and Signal Processing

CERN Document Server

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

2016-01-01

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

Minimizing Total Busy Time with Application to Energy-efficient Scheduling of Virtual Machines in IaaS clouds

OpenAIRE

Quang-Hung, Nguyen; Thoai, Nam

2016-01-01

Infrastructure-as-a-Service (IaaS) clouds have become more popular enabling users to run applications under virtual machines. Energy efficiency for IaaS clouds is still challenge. This paper investigates the energy-efficient scheduling problems of virtual machines (VMs) onto physical machines (PMs) in IaaS clouds along characteristics: multiple resources, fixed intervals and non-preemption of virtual machines. The scheduling problems are NP-hard. Most of existing works on VM placement reduce ...

Development of Web-based Virtual Training Environment for Machining

Science.gov (United States)

Yang, Zhixin; Wong, S. F.

2010-05-01

With the booming in the manufacturing sector of shoe, garments and toy, etc. in pearl region, training the usage of various facilities and design the facility layout become crucial for the success of industry companies. There is evidence that the use of virtual training may provide benefits in improving the effect of learning and reducing risk in the physical work environment. This paper proposed an advanced web-based training environment that could demonstrate the usage of a CNC machine in terms of working condition and parameters selection. The developed virtual environment could provide training at junior level and advanced level. Junior level training is to explain machining knowledge including safety factors, machine parameters (ex. material, speed, feed rate). Advanced level training enables interactive programming of NG coding and effect simulation. Operation sequence was used to assist the user to choose the appropriate machining condition. Several case studies were also carried out with animation of milling and turning operations.

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 ...

30 CFR 75.205 - Installation of roof support using mining machines with integral roof bolters.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Installation of roof support using mining... Roof Support § 75.205 Installation of roof support using mining machines with integral roof bolters. When roof bolts are installed by a continuous mining machine with intregal roof bolting equipment: (a...

Magnet management in electric machines

Science.gov (United States)

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

2017-03-21

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

A Fuzzy Max–Min Decision Bi-Level Fuzzy Programming Model for Water Resources Optimization Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Chongfeng Ren

2018-04-01

Full Text Available Water competing conflict among water competing sectors from different levels should be taken under consideration during the optimization allocation of water resources. Furthermore, uncertainties are inevitable in the optimization allocation of water resources. In order to deal with the above problems, this study developed a fuzzy max–min decision bi-level fuzzy programming model. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, the net benefit and yield were regarded as the upper-level and lower-level objectives, respectively. Optimal water resource plans were obtained under different possibility levels of fuzzy parameters, which could deal with water competing conflict between the upper level and the lower level effectively. The obtained results are expected to make great contribution in helping local decision-makers to make decisions on dealing with the water competing conflict between the upper and lower level and the optimal use of water resources under uncertainty.

High power linear electric machine - made possible by gas springs

Energy Technology Data Exchange (ETDEWEB)

Hoff, E.; Brennvall, J.E.; Nilssen, R.; Norum, L.

2004-07-01

In some applications, such as compressors, free piston linear machines have several advantages compared to rotating machines. The power level of linear machines has been limited, mainly due to difficulties with the spring. A solution for this has now been found and will be described in this paper. It can open up new areas of applications, where the power level exceeds the present power limit of about 2 kW. This machine needs special regulators in order to work efficiently. Two regulator algorithms for piston phase and one for position amplitude are therefore implemented for this prototype. (author)

Electrical Quality Assurance of the Superconducting Circuits during LHC Machine Assembly

CERN Document Server

Bozzini, D; Desebe, O; Mess, K H; Russenschuck, Stephan; Bednarek, M; Dworak, D; Górnicki, E; Jurkiewicz, P; Kapusta, P; Kotarba, A; Ludwin, J; Olek, S; Talach, M; Zieblinski, M; Klisch, M; Prochal, B

2008-01-01

Based on the LHC powering reference database, all-together 1750 superconducting circuits were connected in the various cryogenic transfer lines of the LHC machine. Testing the continuity, magnet polarity, and the quality of the electrical insulation were the main tasks of the Electrical Quality Assurance (ELQA) activities during the LHC machine assembly. With the assembly of the LHC now complete, the paper reviews the work flow, resources, and the qualification results including the different types of electrical non-conformities.

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…

Radiofrequency (RF) radiation measurement for diathermy machine

International Nuclear Information System (INIS)

Rozaimah Abdul Rahim; Roha Tukimin; Mohd Amirul Nizam; Ahmad Fadzli; Mohd Azizi

2010-01-01

Full-text: Diathermy machine is one of medical device that use widely in hospital and clinic. During the diathermy treatment, high radiofrequency (RF) currents (shortwave and microwave) are used to heat deep muscular tissues through electromagnetic energy to body tissues. The heat increases blood flow, relieve pain and speeding up recovery. The stray RF radiation from the machine can exposes to unintended tissue of the patient, to the operator (physical therapist) and also can cause electromagnetic interference (EMI) effect to medical devices around the machine. The main objective of this study is to establish a database of the RF radiation exposure levels experienced by the operator and patient during the treatments. RF radiation (electric and magnetic field) produced by the diathermy machines were measured using special RF survey meters. The finding of this study confirms that radiation levels on the surface and near the applicator of the diathermy machine much more elevated due to the much closer distance to the source and they exceeding the occupational and general public exposure limit. The results also shows the field strengths drop very significantly when the distance of measurement increase. (author)

Determination of the level of resource-use efficiency in Quality ...

African Journals Online (AJOL)

The study aimed at determining the level of resource use efficiency in Quality Protein Maize (QPM) production in Kaduna State. Multi stage sampling technique was used to sample 170 respondents from four L.G.As. where QPM is mostly produced. Data were collected through questionnaire administration during the 2009 ...

Access to environmental resources and physical activity levels of adults in Hawaii.

Science.gov (United States)

Geller, Karly S; Nigg, Claudio R; Ollberding, Nicholas J; Motl, Robert W; Horwath, Caroline; Dishman, Rodney K

2015-03-01

Examine associations between physical activity (PA) and spatial accessibility to environmental PA resources in Hawaii. Metabolic equivalents (METs) of mild, moderate, and strenuous PA were compared for accessibility with environmental PA resources within a population-based sample of Hawaiian adults (n = 381). Multiple linear regression estimated differences in PA levels for residing further from a PA resource or residing in an area with a greater number of resources. No associations were found in the total sample. Analyses within subsamples stratified by ethnicity revealed that greater spatial accessibility to a PA resource was positively associated with strenuous PA among Caucasians (P = .04) but negatively associated with moderate PA among Native Hawaiians (P = .00). The lack of association in the total sample may be a consequence of Hawaii's unique environment. Results of stratified sample analyses are unique, providing groundwork for future examinations within parallel environments and among similar ethnic groups. © 2012 APJPH.

Taking it to another level: do personality-based human capital resources matter to firm performance?

Science.gov (United States)

Oh, In-Sue; Kim, Seongsu; Van Iddekinge, Chad H

2015-05-01

Drawing on the attraction-selection-attrition perspective, strategic human resource management (SHRM) scholarship, and recent human capital research, this study explores organization-level emergence of personality (i.e., personality-based human capital resources) and its direct, interactive, and (conditional) indirect effects on organization-level outcomes based on data from 6,709 managers across 71 firms. Results indicate that organization-level mean emotional stability, extraversion, and conscientiousness are positively related to organization-level managerial job satisfaction and labor productivity but not to financial performance. Furthermore, organization-level mean and variance in emotional stability interact to predict all three organization-level outcomes, and organization-level mean and variance in extraversion interact to predict firm financial performance. Specifically, the positive effects of organization-level mean emotional stability and extraversion are stronger when organization-level variance in these traits is lower. Finally, organization-level mean emotional stability, extraversion, and conscientiousness are all positively related to firm financial performance indirectly via labor productivity, and the indirect effects are more positive when organization-level variance in those personality traits is lower. Overall, the findings suggest that personality-based human capital resources demonstrate tangible effects on organization-level outcomes. Theoretical and practical implications of these findings are discussed along with study limitations and future research directions. (c) 2015 APA, all rights reserved.

Local electricity market design for the coordination of distributed energy resources at district level

NARCIS (Netherlands)

Ampatzis, M.; Nguyen, P.H.; Kling, W.L.

2014-01-01

The increasing penetration of distributed energy resources at the distribution grid level creates concerns about their successful integration in the existing electric grid, designed for centralized generation by large power plants. Failure to the proper integration of distributed energy resources

Dynamic thermal analysis of machines in running state

CERN Document Server

Wang, Lihui

2014-01-01

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

Deep Support Vector Machines for Regression Problems

NARCIS (Netherlands)

Wiering, Marco; Schutten, Marten; Millea, Adrian; Meijster, Arnold; Schomaker, Lambertus

2013-01-01

In this paper we describe a novel extension of the support vector machine, called the deep support vector machine (DSVM). The original SVM has a single layer with kernel functions and is therefore a shallow model. The DSVM can use an arbitrary number of layers, in which lower-level layers contain

Guest Editorial Electric Machines in Renewable Energy Applications

Energy Technology Data Exchange (ETDEWEB)

Aliprantis, Dionysios; El-Sharkawi, Mohamed; Muljadi, Eduard; Brown, Ian; Chiba, Akira; Dorrell, David; Erlich, Istvan; Kerszenbaum, Isidor Izzy; Levi, Emil; Mayor, Kevin; Mohammed, Osama; Papathanassiou, Stavros; Popescu, Mircea; Qiao, Wei; Wu, Dezheng

2015-12-01

The main objective of this special issue is to collect and disseminate publications that highlight recent advances and breakthroughs in the area of renewable energy resources. The use of these resources for production of electricity is increasing rapidly worldwide. As of 2015, a majority of countries have set renewable electricity targets in the 10%-40% range to be achieved by 2020-2030, with a few notable exceptions aiming for 100% generation by renewables. We are experiencing a truly unprecedented transition away from fossil fuels, driven by environmental, energy security, and socio-economic factors.Electric machines can be found in a wide range of renewable energy applications, such as wind turbines, hydropower and hydrokinetic systems, flywheel energy storage devices, and low-power energy harvesting systems. Hence, the design of reliable, efficient, cost-effective, and controllable electric machines is crucial in enabling even higher penetrations of renewable energy systems in the smart grid of the future. In addition, power electronic converter design and control is critical, as they provide essential controllability, flexibility, grid interface, and integration functions.

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

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

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Observing invisible machines with invisible light: The mechanics of molecular machines

NARCIS (Netherlands)

Panman, M.R.

2013-01-01

Over the past few decades, chemists have designed and constructed a large variety of artificial molecular machines. Understanding of the fundamental principles behind motion at the molecular scale is key to the development of such devices. Motion at the molecular level is very different from that

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

Directory of Open Access Journals (Sweden)

Haejoon Jung

2018-01-01

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

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

Science.gov (United States)

Jung, Haejoon; Lee, In-Ho

2018-01-12

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

TMI-2 core boring machine

International Nuclear Information System (INIS)

Croft, K.M.; Helbert, H.J.; Laney, W.M.

1986-01-01

An important and essential aspect of the TMI-2 defueling effort is to determine what occurred in the core region during the accident. Remote cameras and probes only portray a portion of the overall picture. What lies beneath the rubble bed and solidified sublayer is, as yet, unknown. This paper discusses the TMI-2 Core Boring Machine, which has been developed to drill into the damaged core of the TMI-2 reactor and extract stratified samples of the core. This machine, its unique support structure, positioning and leveling systems, and specially designed drill bits, combine to provide a unique mechanical system. In addition, the machine is controlled by a microprocessor; which actually controls the drilling operation, allowing relatively inexperienced operators to drill the core samples. A data acquisition system is data integral with the controlling system and collects data relative to system conditions and monitored parameters during drilling. Data obtained during the actual drilling operations are collected in a data base which will be used for actual mapping of the core region, identifying materials and stratification levels that are present

Flexible Job-Shop Scheduling with Dual-Resource Constraints to Minimize Tardiness Using Genetic Algorithm

Science.gov (United States)

Paksi, A. B. N.; Ma'ruf, A.

2016-02-01

In general, both machines and human resources are needed for processing a job on production floor. However, most classical scheduling problems have ignored the possible constraint caused by availability of workers and have considered only machines as a limited resource. In addition, along with production technology development, routing flexibility appears as a consequence of high product variety and medium demand for each product. Routing flexibility is caused by capability of machines that offers more than one machining process. This paper presents a method to address scheduling problem constrained by both machines and workers, considering routing flexibility. Scheduling in a Dual-Resource Constrained shop is categorized as NP-hard problem that needs long computational time. Meta-heuristic approach, based on Genetic Algorithm, is used due to its practical implementation in industry. Developed Genetic Algorithm uses indirect chromosome representative and procedure to transform chromosome into Gantt chart. Genetic operators, namely selection, elitism, crossover, and mutation are developed to search the best fitness value until steady state condition is achieved. A case study in a manufacturing SME is used to minimize tardiness as objective function. The algorithm has shown 25.6% reduction of tardiness, equal to 43.5 hours.

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.

Resource Optimization Techniques and Security Levels for Wireless Sensor Networks Based on the ARSy Framework

Science.gov (United States)

Kitagawa, Akio

2018-01-01

Wireless Sensor Networks (WSNs) with limited battery, central processing units (CPUs), and memory resources are a widely implemented technology for early warning detection systems. The main advantage of WSNs is their ability to be deployed in areas that are difficult to access by humans. In such areas, regular maintenance may be impossible; therefore, WSN devices must utilize their limited resources to operate for as long as possible, but longer operations require maintenance. One method of maintenance is to apply a resource adaptation policy when a system reaches a critical threshold. This study discusses the application of a security level adaptation model, such as an ARSy Framework, for using resources more efficiently. A single node comprising a Raspberry Pi 3 Model B and a DS18B20 temperature sensor were tested in a laboratory under normal and stressful conditions. The result shows that under normal conditions, the system operates approximately three times longer than under stressful conditions. Maintaining the stability of the resources also enables the security level of a network’s data output to stay at a high or medium level. PMID:29772773

30 CFR 18.95 - Approval of machines constructed of components approved, accepted or certified under Bureau of...

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approval of machines constructed of components... APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.95 Approval of machines constructed of components approved...

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

OpenAIRE

Fang, Ruijie; Liu, Siqi

2016-01-01

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

Final project memorandum: sea-level rise modeling handbook: resource guide for resource managers, engineers, and scientists

Science.gov (United States)

Doyle, Thomas W.

2015-01-01

Coastal wetlands of the Southeastern United States are undergoing retreat and migration from increasing tidal inundation and saltwater intrusion attributed to climate variability and sea-level rise. Much of the literature describing potential sea-level rise projections and modeling predictions are found in peer-reviewed academic journals or government technical reports largely suited to reading by other Ph.D. scientists who are more familiar or engaged in the climate change debate. Various sea-level rise and coastal wetland models have been developed and applied of different designs and scales of spatial and temporal complexity for predicting habitat and environmental change that have not heretofore been synthesized to aid natural resource managers of their utility and limitations. Training sessions were conducted with Federal land managers with U.S. Fish and Wildlife Service, National Park Service, and NOAA National Estuarine Research Reserves as well as state partners and nongovernmental organizations across the northern Gulf Coast from Florida to Texas to educate and to evaluate user needs and understanding of concepts, data, and modeling tools for projecting sea-level rise and its impact on coastal habitats and wildlife. As a result, this handbook was constructed from these training and feedback sessions with coastal managers and biologists of published decision-support tools and simulation models for sea-level rise and climate change assessments. A simplified tabular context was developed listing the various kinds of decision-support tools and ecological models along with criteria to distinguish the source, scale, and quality of information input and geographic data sets, physical and biological constraints and relationships, datum characteristics of water and land elevation components, utility options for setting sea-level rise and climate change scenarios, and ease or difficulty of storing, displaying, or interpreting model output. The handbook is designed

Increasing energy efficiency level of building production based on applying modern mechanization facilities

Science.gov (United States)

Prokhorov, Sergey

2017-10-01

Building industry in a present day going through the hard times. Machine and mechanism exploitation cost, on a field of construction and installation works, takes a substantial part in total building construction expenses. There is a necessity to elaborate high efficient method, which allows not only to increase production, but also to reduce direct costs during machine fleet exploitation, and to increase its energy efficiency. In order to achieve the goal we plan to use modern methods of work production, hi-tech and energy saving machine tools and technologies, and use of optimal mechanization sets. As the optimization criteria there are exploitation prime cost and set efficiency. During actual task-solving process we made a conclusion, which shows that mechanization works, energy audit with production juxtaposition, prime prices and costs for energy resources allow to make complex machine fleet supply, improve ecological level and increase construction and installation work quality.

Engineered Surface Properties of Porous Tungsten from Cryogenic Machining

Science.gov (United States)

Schoop, Julius Malte

Porous tungsten is used to manufacture dispenser cathodes due to it refractory properties. Surface porosity is critical to functional performance of dispenser cathodes because it allows for an impregnated ceramic compound to migrate to the emitting surface, lowering its work function. Likewise, surface roughness is important because it is necessary to ensure uniform wetting of the molten impregnate during high temperature service. Current industry practice to achieve surface roughness and surface porosity requirements involves the use of a plastic infiltrant during machining. After machining, the infiltrant is baked and the cathode pellet is impregnated. In this context, cryogenic machining is investigated as a substitutionary process for the current plastic infiltration process. Along with significant reductions in cycle time and resource use, surface quality of cryogenically machined un-infiltrated (as-sintered) porous tungsten has been shown to significantly outperform dry machining. The present study is focused on examining the relationship between machining parameters and cooling condition on the as-machined surface integrity of porous tungsten. The effects of cryogenic pre-cooling, rake angle, cutting speed, depth of cut and feed are all taken into consideration with respect to machining-induced surface morphology. Cermet and Polycrystalline diamond (PCD) cutting tools are used to develop high performance cryogenic machining of porous tungsten. Dry and pre-heated machining were investigated as a means to allow for ductile mode machining, yet severe tool-wear and undesirable smearing limited the feasibility of these approaches. By using modified PCD cutting tools, high speed machining of porous tungsten at cutting speeds up to 400 m/min is achieved for the first time. Beyond a critical speed, brittle fracture and built-up edge are eliminated as the result of a brittle to ductile transition. A model of critical chip thickness ( hc ) effects based on cutting

Controls and Machine Protection Systems

CERN Document Server

Carrone, E.

2016-01-01

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

Throughput centered prioritization of machines in transfer lines

Energy Technology Data Exchange (ETDEWEB)

Pascual, R., E-mail: rpascual@ing.puc.cl [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Godoy, D. [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Louit, D.M. [Komatsu Chile S.A., Av. Americo Vespucio 0631, Quilicura, Santiago (Chile)

2011-10-15

In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: > We propose a graphical technique to prioritize machines in production lines. > The tool is called 'system efficiency influence diagram' (SEID). > It helps setting prioritized maintenance policies and/or redesign of buffers. > The SEID technique focuses on system efficiency and throughput. > We illustrate its applicability using three case studies.

Household-level heterogeneity of water resources within common-pool resource systems

NARCIS (Netherlands)

McCord, Paul; Dell'angelo, Jampel; Gower, Drew; Caylor, Kelly K.; Evans, Tom

2017-01-01

Prior work has demonstrated the ability of common property systems to sustain institutional arrangements governing natural resources over long periods of time. Much of this work has focused on irrigation systems where upstream users agree to management arrangements that distribute water resources

Association between addiction treatment staff professional and educational levels and perceptions of organizational climate and resources.

Science.gov (United States)

Krull, Ivy; Lundgren, Lena; Beltrame, Clelia

2014-01-01

Research studies have identified addiction treatment staff who have higher levels of education as having more positive attitudes about evidence-based treatment practices, science-based training, and the usefulness of evidence-based practices. This study examined associations between addiction treatment staff level of education and their perceptions of 3 measures of organizational change: organizational stress, training resources and staffing resources in their treatment unit. The sample included 588 clinical staff from community-based substance abuse treatment organizations who received Substance Abuse and Mental Health Services Administration (SAMHSA) funding (2003-2008) to implement evidence-based practices (EBPs). Bivariate analysis and regression modeling methods examined the relationship between staff education level (no high school education, high school education, some college, associate's degree, bachelor's degree, master's degree, doctoral degree, and other type of degree such as medical assistant, registered nurse [RN], or postdoctoral) and attitudes about organizational climate (stress), training resources, and staffing resources while controlling for staff and treatment unit characteristics. Multivariable models identified staff with lower levels of education as having significantly more positive attitudes about their unit's organizational capacity. These results contradict findings that addiction treatment staff with higher levels of education work in units with greater levels of organizational readiness for change. It cannot be inferred that higher levels of education among treatment staff is necessarily associated with high levels of organizational readiness for change.

Metal release from coffee machines and electric kettles.

Science.gov (United States)

Müller, Frederic D; Hackethal, Christin; Schmidt, Roman; Kappenstein, Oliver; Pfaff, Karla; Luch, Andreas

2015-01-01

The release of elemental ions from 8 coffee machines and 11 electric kettles into food simulants was investigated. Three different types of coffee machines were tested: portafilter espresso machines, pod machines and capsule machines. All machines were tested subsequently on 3 days before and on 3 days after decalcification. Decalcification of the machines was performed with agents according to procedures as specified in the respective manufacturer's manuals. The electric kettles showed only a low release of the elements analysed. For the coffee machines decreasing concentrations of elements were found from the first to the last sample taken in the course of 1 day. Metal release on consecutive days showed a decreasing trend as well. After decalcification a large increase in the amounts of elements released was encountered. In addition, the different machine types investigated clearly differed in their extent of element release. By far the highest leaching, both quantitatively and qualitatively, was found for the portafilter machines. With these products releases of Pb, Ni, Mn, Cr and Zn were in the range and beyond the release limits as proposed by the Council of Europe. Therefore, a careful rinsing routine, especially after decalcification, is recommended for these machines. The comparably lower extent of release of one particular portafilter machine demonstrates that metal release at levels above the threshold that triggers health concerns are technically avoidable.

Hybrid machining processes perspectives on machining and finishing

CERN Document Server

Gupta, Kapil; Laubscher, R F

2016-01-01

This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

Estimating the complexity of 3D structural models using machine learning methods

Science.gov (United States)

Mejía-Herrera, Pablo; Kakurina, Maria; Royer, Jean-Jacques

2016-04-01

Quantifying the complexity of 3D geological structural models can play a major role in natural resources exploration surveys, for predicting environmental hazards or for forecasting fossil resources. This paper proposes a structural complexity index which can be used to help in defining the degree of effort necessary to build a 3D model for a given degree of confidence, and also to identify locations where addition efforts are required to meet a given acceptable risk of uncertainty. In this work, it is considered that the structural complexity index can be estimated using machine learning methods on raw geo-data. More precisely, the metrics for measuring the complexity can be approximated as the difficulty degree associated to the prediction of the geological objects distribution calculated based on partial information on the actual structural distribution of materials. The proposed methodology is tested on a set of 3D synthetic structural models for which the degree of effort during their building is assessed using various parameters (such as number of faults, number of part in a surface object, number of borders, ...), the rank of geological elements contained in each model, and, finally, their level of deformation (folding and faulting). The results show how the estimated complexity in a 3D model can be approximated by the quantity of partial data necessaries to simulated at a given precision the actual 3D model without error using machine learning algorithms.

The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine

OpenAIRE

Wolff, J Gerard

2016-01-01

This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence. The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from...

Scikit-learn: Machine Learning in Python

OpenAIRE

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

2011-01-01

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

Scikit-learn: Machine Learning in Python

OpenAIRE

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

2012-01-01

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

Throughput centered prioritization of machines in transfer lines

International Nuclear Information System (INIS)

Pascual, R.; Godoy, D.; Louit, D.M.

2011-01-01

In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: → We propose a graphical technique to prioritize machines in production lines. → The tool is called 'system efficiency influence diagram' (SEID). → It helps setting prioritized maintenance policies and/or redesign of buffers. → The SEID technique focuses on system efficiency and throughput. → We illustrate its applicability using three case studies.

Gaussian processes for machine learning.

Science.gov (United States)

Seeger, Matthias

2004-04-01

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.

GPK heading machine

Energy Technology Data Exchange (ETDEWEB)

Krmasek, J.; Novosad, K.

1981-01-01

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

Classifying smoking urges via machine learning.

Science.gov (United States)

Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

2016-12-01

Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights

Power of Doubling: Population Growth and Resource Consumption

OpenAIRE

Sarika Bahadure

2017-01-01

Sustainability starts with conserving resources for future generations. Since human’s existence on this earth, he has been consuming natural resources. The resource consumption pace in the past was very slow, but industrialization in 18th century brought a change in the human lifestyle. New inventions and discoveries upgraded the human workforce to machines. The mass manufacture of goods provided easy access to products. In the last few decades, the globalization and change in technologies br...

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.

An incremental anomaly detection model for virtual machines.

Directory of Open Access Journals (Sweden)

Hancui Zhang

Full Text Available Self-Organizing Map (SOM algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform.

An incremental anomaly detection model for virtual machines

Science.gov (United States)

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform. PMID:29117245

Cybernics fusion of human, machine and information systems

CERN Document Server

Suzuki, Kenji; Hasegawa, Yasuhisa

2014-01-01

Cybernics plays a significant role in coping with an aging society using state-of-the-art technologies from engineering, clinical medicine and humanities. This new interdisciplinary field studies technologies that enhance, strengthen, and support physical and cognitive functions of human beings, based on the fusion of human, machine, and information systems. The design of a seamless interface for interaction between the interior and exterior of the human body is described in this book from diverse aspects such as the physical, neurophysiological, and cognitive levels. It is the first book to cover the many aspects of cybernics, allowing readers to understand the life support robotics technology for the elderly, including remote, in-home, hospital, institutional, community medical welfare, and vital-sensing systems. Serving as a valuable resource, this volume will interest not only graduate students, scientists, and engineers but also newcomers to the field of cybernics.

Efficient Hybrid Genetic Based Multi Dimensional Host Load Aware Algorithm for Scheduling and Optimization of Virtual Machines

OpenAIRE

Thiruvenkadam, T; Karthikeyani, V

2014-01-01

Mapping the virtual machines to the physical machines cluster is called the VM placement. Placing the VM in the appropriate host is necessary for ensuring the effective resource utilization and minimizing the datacenter cost as well as power. Here we present an efficient hybrid genetic based host load aware algorithm for scheduling and optimization of virtual machines in a cluster of Physical hosts. We developed the algorithm based on two different methods, first initial VM packing is done by...

The Relevance of Resources for Resilience at Different Organizational Levels within the Military Deployment Cycle

NARCIS (Netherlands)

Kamphuis, W.; Delahaij, R.

2014-01-01

In the current study, the relative importance of different resources for psychological resilience of service members is investigated. The study employs a model of psychological resilience developed for the Netherlands Armed Forces, which identifies 25 resources for resilience at 5 different levels

ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

Science.gov (United States)

Kayala, Matthew A; Baldi, Pierre

2012-10-22

Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of Reaction

MAINTENANCE PLANNING OF THE SEWING NEEDLES OF SIMPLE SEWING MACHINES

Directory of Open Access Journals (Sweden)

ŞUTEU Marius Darius

2017-05-01

Full Text Available The effectiveness of simple sewing machines can be increased through the planning of predictive maintenance activities. The monitoring of the technical condition of the sewing needles of simple sewing machines was based on the measurement of their noise level. For this purpose a Center 322 sonometer was used, while the data obtained during the monitoring process was analyzed through the E322 software. The working speed of the simple sewing machine that was used for obtaining the experimental results varied from 200 stitches/minute to 4000 stitches/minute. The noise levels of a new needle at the working speed of 200 stitches/minute and 4000 stitches/minute were measured. The noise levels for a fault needle at the same working speed of 200 stitches/minute, respectively 4000 stitches/minute were also measured. Using Fuzzy Logic Toolbox ™ module of Matlab®, a decision-making system for determining when replacement of the sewing needles of simple sewing machines should be performed was developed. A case study illustrates the employment of the decision-making system based on fuzzy logic for a simple sewing machine. By replacing the sewing needles of simple sewing machines at the time specified through the decision-making system based on fuzzy logic, the occurrence of the failure can be prevented and the quality of textile products can be improved.

Model checking coalitional games in shortage resource scenarios

Directory of Open Access Journals (Sweden)

Dario Della Monica

2013-07-01

Full Text Available Verification of multi-agents systems (MAS has been recently studied taking into account the need of expressing resource bounds. Several logics for specifying properties of MAS have been presented in quite a variety of scenarios with bounded resources. In this paper, we study a different formalism, called Priced Resource-Bounded Alternating-time Temporal Logic (PRBATL, whose main novelty consists in moving the notion of resources from a syntactic level (part of the formula to a semantic one (part of the model. This allows us to track the evolution of the resource availability along the computations and provides us with a formalisms capable to model a number of real-world scenarios. Two relevant aspects are the notion of global availability of the resources on the market, that are shared by the agents, and the notion of price of resources, depending on their availability. In a previous work of ours, an initial step towards this new formalism was introduced, along with an EXPTIME algorithm for the model checking problem. In this paper we better analyze the features of the proposed formalism, also in comparison with previous approaches. The main technical contribution is the proof of the EXPTIME-hardness of the the model checking problem for PRBATL, based on a reduction from the acceptance problem for Linearly-Bounded Alternating Turing Machines. In particular, since the problem has multiple parameters, we show two fixed-parameter reductions.

Some relations between quantum Turing machines and Turing machines

OpenAIRE

Sicard, Andrés; Vélez, Mario

1999-01-01

For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

Local and Regional Partnerships in Natural Resource Management: The Challenge of Bridging Institutional Levels

Science.gov (United States)

Prager, Katrin

2010-11-01

Although collaboration and multi-stakeholder partnerships have become a common feature in natural resource management throughout the world, various problems are associated with attempts to up-scale community-based natural resource management from the local to the regional level. To analyze the reasons behind these problems, this article reports on two examples of collaboratives in Australia: local Landcare groups, and regional natural resource management (NRM) bodies. Recent government-induced changes have shifted the focus from local Landcare group action to strategic planning and implementation by regional NRM bodies. Two typologies of collaboratives are applied to analyze the characteristics of both these groups. The study uses data from 52 qualitative interviews with key informants at the local and regional level in Victoria and Tasmania, participant observation, as well as literature and document analysis. The article illustrates how the groups’ distinct characteristics can cause conflicts when the different types of collaboratives operate in parallel. In addition, the article reports how stakeholders perceive the level of community participation in decision-making processes. The key message is that the benefits of community participation and collaboration that arise at the local level can be lost when these approaches are up-scaled to the regional level unless there is an intermediary or ‘mediating structure’ to facilitate communication and create the link between different types of collaboratives.

The application of machine learning techniques in the clinical drug therapy.

Science.gov (United States)

Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan

2018-05-25

The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Dynamic provisioning of local and remote compute resources with OpenStack

Science.gov (United States)

Giffels, M.; Hauth, T.; Polgart, F.; Quast, G.

2015-12-01

Modern high-energy physics experiments rely on the extensive usage of computing resources, both for the reconstruction of measured events as well as for Monte-Carlo simulation. The Institut fur Experimentelle Kernphysik (EKP) at KIT is participating in both the CMS and Belle experiments with computing and storage resources. In the upcoming years, these requirements are expected to increase due to growing amount of recorded data and the rise in complexity of the simulated events. It is therefore essential to increase the available computing capabilities by tapping into all resource pools. At the EKP institute, powerful desktop machines are available to users. Due to the multi-core nature of modern CPUs, vast amounts of CPU time are not utilized by common desktop usage patterns. Other important providers of compute capabilities are classical HPC data centers at universities or national research centers. Due to the shared nature of these installations, the standardized software stack required by HEP applications cannot be installed. A viable way to overcome this constraint and offer a standardized software environment in a transparent manner is the usage of virtualization technologies. The OpenStack project has become a widely adopted solution to virtualize hardware and offer additional services like storage and virtual machine management. This contribution will report on the incorporation of the institute's desktop machines into a private OpenStack Cloud. The additional compute resources provisioned via the virtual machines have been used for Monte-Carlo simulation and data analysis. Furthermore, a concept to integrate shared, remote HPC centers into regular HEP job workflows will be presented. In this approach, local and remote resources are merged to form a uniform, virtual compute cluster with a single point-of-entry for the user. Evaluations of the performance and stability of this setup and operational experiences will be discussed.

An object-oriented extension for debugging the virtual machine

Energy Technology Data Exchange (ETDEWEB)

Pizzi, Jr, Robert G. [Univ. of California, Davis, CA (United States)

1994-12-01

A computer is nothing more then a virtual machine programmed by source code to perform a task. The program`s source code expresses abstract constructs which are compiled into some lower level target language. When a virtual machine breaks, it can be very difficult to debug because typical debuggers provide only low-level target implementation information to the software engineer. We believe that the debugging task can be simplified by introducing aspects of the abstract design and data into the source code. We introduce OODIE, an object-oriented extension to programming languages that allows programmers to specify a virtual environment by describing the meaning of the design and data of a virtual machine. This specification is translated into symbolic information such that an augmented debugger can present engineers with a programmable debugging environment specifically tailored for the virtual machine that is to be debugged.

Support vector machine in machine condition monitoring and fault diagnosis

Science.gov (United States)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

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

Individual-level social capital and self-rated health in Japan: an application of the Resource Generator.

Science.gov (United States)

Kobayashi, Tomoko; Kawachi, Ichiro; Iwase, Toshihide; Suzuki, Etsuji; Takao, Soshi

2013-05-01

Despite accumulating evidence of associations between social capital and health in public health research, a criticism of the field has been that researchers have exclusively focused on concepts of social cohesion to the exclusion of individual-level approaches. In the present study, we evaluated the association between social capital measured by the Resource Generator (an individual-level assessment of access to social capital) and self-rated health among Japanese population in a cross-sectional study. A postal survey of 4000 randomly selected residents in Okayama City (western Japan) was conducted in February 2009. We divided the overall scores from the Resource Generator Japan scale into quartiles. Odds ratios (ORs) and 95% confidence intervals (CIs) for self-rated health were calculated separately by sex. Individuals with the highest quartile of scores had significantly lower odds of poor health compared to the lowest group after covariate adjustment among both men and women (men; OR: 0.45, 95% CI: 0.24-0.86, women; OR: 0.44, 95% CI: 0.25-0.79, respectively) and there were also significant dose-response relationships. In the sub-domains of Resource Generator Japan scale, a differential pattern was observed by sex. Women showed a clear dose-response relationship with health across all four sub-scales (domestic resources, expert advice, personal skills, and problem solving resources). In contrast, only the domain of expert advice exhibited a strong association with men's health. Among both men and women individual-level social capital measured by the Resource Generator was related to reduced odds of poor health even after taking into account individual confounders. Although we cannot exclude reverse causation due to the cross-sectional design, our study adds to the accumulating evidence of the potential utility of the Resource Generator for evaluating the relationship between individual-level access to social capital and health. Copyright © 2013 Elsevier Ltd

Virtual Machine Images Management in Cloud Environments

CERN Multimedia

CERN. Geneva

2017-01-01

Nowadays, the demand for scalability in distributed systems has led a design philosophy in which virtual resources need to be configured in a flexible way to provide services to a large number of users. The configuration and management of such an architecture is challenging (e.g.: 100,000 compute cores on the private cloud together with thousands of cores on external cloud resources). There is the need to process CPU intensive work whilst ensuring that the resources are shared fairly between different users of the system, and guarantee that all nodes are up to date with new images containing the latest software configurations. Different types of automated systems can be used to facilitate the orchestration. CERN’s current system, composed of different technologies such as OpenStack, Packer, Puppet, Rundeck and Docker will be introduced and explained, together with the process used to create new Virtual Machines images at CERN.

Combining Formal Logic and Machine Learning for Sentiment Analysis

DEFF Research Database (Denmark)

Petersen, Niklas Christoffer; Villadsen, Jørgen

2014-01-01

This paper presents a formal logical method for deep structural analysis of the syntactical properties of texts using machine learning techniques for efficient syntactical tagging. To evaluate the method it is used for entity level sentiment analysis as an alternative to pure machine learning...

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

Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

OpenAIRE

Qiu, Daowen

2005-01-01

As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing ma...

Towards Measuring the Abstractness of State Machines based on Mutation Testing

Directory of Open Access Journals (Sweden)

Thomas Baar

2017-01-01

Full Text Available Abstract. The notation of state machines is widely adopted as a formalism to describe the behaviour of systems. Usually, multiple state machine models can be developed for the very same software system. Some of these models might turn out to be equivalent, but, in many cases, different state machines describing the same system also differ in their level of abstraction. In this paper, we present an approach to actually measure the abstractness level of state machines w.r.t. a given implemented software system. A state machine is considered to be less abstract when it is conceptionally closer to the implemented system. In our approach, this distance between state machine and implementation is measured by applying coverage criteria known from software mutation testing. Abstractness of state machines can be considered as a new metric. As for other metrics as well, a known value for the abstractness of a given state machine allows to assess its quality in terms of a simple number. In model-based software development projects, the abstract metric can help to prevent model degradation since it can actually measure the semantic distance from the behavioural specification of a system in form of a state machine to the current implementation of the system. In contrast to other metrics for state machines, the abstractness cannot be statically computed based on the state machine’s structure, but requires to execute both state machine and corresponding system implementation. The article is published in the author’s wording. 

Extreme Learning Machine to Analyze the Level of Default in Spanish Deposit Institutions || Análisis de la morosidad de las entidades financieras españolas mediante Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Becerra-Alonso, David

2012-01-01

Full Text Available The level of default in financial institutions is a key piece of information in the activity of these organizations and reveals their level of risk. This in turn explains the growing attention given to variables of this kind, during the crisis of these last years. This paper presents a method to estimate the default rate using the non-linear model defined by standard Multilayer Perceptron (MLP neural networks trained with a novel methodology called Extreme Learning Machine (ELM. The experimental results are promising, and show a good performance when comparing the MLP model trained with the Leverberg-Marquard algorithm. || La morosidad en las entidades financieras es un dato muy importante de la actividad de estas instituciones pues permite conocer el nivel de riesgo asumido por éstas. Esto a su vez explica la creciente atención otorgada a esta variable, especialmente en los últimos años de crisis. Este artículo presenta un método para estimar el nivel de la tasa de morosidad por medio de un modelo no lineal definido por la red neuronal Multilayer Perceptron (MLP entrenada con una nueva metodología llamada Extreme Learning Machine (ELM. Los resultados experimentales son prometedores, mostrando un buen resultado si se compara con el modelo MLP entrenado con el algoritmo de Leverberg-Marquard.

Protection of Mission-Critical Applications from Untrusted Execution Environment: Resource Efficient Replication and Migration of Virtual Machines

Science.gov (United States)

2015-09-28

in the same LAN ; this setup resembles the typical setup in a virtualized datacenter where protected and backup hosts are connected by an internal LAN ... Virtual Machines 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-10-1-0393 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Kang G. Shin 5d. PROJECT...Distribution A - Approved for Public Release 13. SUPPLEMENTARY NOTES None 14. ABSTRACT Continuous replication and live migration of Virtual Machines (VMs

Python for probability, statistics, and machine learning

CERN Document Server

Unpingco, José

2016-01-01

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...

Making molecular machines work

NARCIS (Netherlands)

Browne, Wesley R.; Feringa, Ben L.

2006-01-01

In this review we chart recent advances in what is at once an old and very new field of endeavour the achievement of control of motion at the molecular level including solid-state and surface-mounted rotors, and its natural progression to the development of synthetic molecular machines. Besides a

A Turing Machine Simulator.

Science.gov (United States)

Navarro, Aaron B.

1981-01-01

Presents a program in Level II BASIC for a TRS-80 computer that simulates a Turing machine and discusses the nature of the device. The program is run interactively and is designed to be used as an educational tool by computer science or mathematics students studying computational or automata theory. (MP)

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

СALCULATION OF INDIVIDUAL TECHNOLOGICAL NORMS PERTAINING TO EXPENDITURE OF FUEL AND POWER RESOURCES IN CONSTRUCTION INDUSTRY

Directory of Open Access Journals (Sweden)

A. A. Lozovsky

2011-01-01

Full Text Available The paper considers private methods for calculation of individual technological norms pertaining to expenditure of fuel and power resources in  respect of main types of construction and installation works and technological processes whish are executed with the help of various machines, mechanisms, technological equipment etc. Analytical expressions that take into account various factors influencing on the power consumption level are presented in the paper.

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

Science.gov (United States)

Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

2017-11-01

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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...

Virtual machine performance benchmarking.

Science.gov (United States)

Langer, Steve G; French, Todd

2011-10-01

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

A Study of the Resolution of Dental Intraoral X-Ray Machines

International Nuclear Information System (INIS)

Kim, Seon Ju; Chung, Hyon De

1990-01-01

The purpose of this study was to assess the resolution and focal spot size of dental X-ray machines. Fifty dental X-ray machines were selected for measuring resolution and focal spot size. These machines were used in general dental clinics. The time on installation of the X-ray machine varies from 1 years to 10 years. The resolution of these machines was measured with the test pattern. The focal spot size of these machines was measured with the star test pattern. The following results were obtained: 1. The resolution of dental intraoral X-ray machines was not significantly changed in ten years. 2. The focal spot size of dental intraoral X-ray machines was not significantly increased in ten years. The statistical analysis between the mean focal spot size and nominal focal spot size was significant at the 0.05 level about the more than 3 years used machines.

Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

International Nuclear Information System (INIS)

Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron; Arnold, Dorian

2017-01-01

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation at scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.

Empirical Research on Ecological Development Level of Resource-based Industries-Base on the data of the Silk Road Economic Belt Core Zone

Science.gov (United States)

Wang, Lei; Yan, Min

2017-11-01

Industrial ecology is the epitome of sustainable development in industry level, is one effective gateway to realizing green transformation. On the basis of industrial ecology development, including resource efficiency and environmental efficiency of ecological evaluation index system, this paper evaluates the level of industrial ecology development of resource-based industries in Xinjiang using entropy method. Research shows that the overall ecological development level of resource-based industries has remained at continuous improved trend with slow improvement in resource efficiency, and relative faster improvement in environmental efficiency. With economic development entering into the period of new normal at the end of the “twelfth five year plan”, the resource efficiency of ecological development of resource-based industries demonstrated a downward trend. The overall level of industrial ecology also faced with certain fluctuations, various ecological development level of resource-based industries also presented a downward trend. To promote ecological development of resource-based industries in Xinjiang, countermeasures and suggestions are initiated.

Applications of machine learning in cancer prediction and prognosis.

Science.gov (United States)

Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Gambling revenues as a public administration issue: electronic gaming machines in Victoria.

Science.gov (United States)

Pickernell, David; Keast, Robyn; Brown, Kerry; Yousefpour, Nina; Miller, Chris

2013-12-01

Gambling activities and the revenues derived have been seen as a way to increase economic development in deprived areas. There are also, however, concerns about the effects of gambling in general and electronic gaming machines (EGMs) in particular, on the resources available to the localities in which they are situated. This paper focuses on the factors that determine the extent and spending of community benefit-related EGM-generated resources within Victoria, Australia, focusing in particular on the relationships between EGM activity and socio-economic and social capital indicators, and how this relates to the community benefit resources generated by gaming.

Semiautomatic machine for turning inside out industrial leather gloves

International Nuclear Information System (INIS)

Aragón-Gonzalez, G; Cano-Blanco, M; León-Galicia, A; Medrano-Sierra, L F; Morales-Gómez, J R

2015-01-01

The last step in the industrial leather gloves manufacturing is to turn the inside out so that the sewing be in the inside of the glove. This work presents the design and testing of a machine for that purpose. In order to quantify the relevant variables, testing was performed with a prototype glove. The employed devices and the testing proceeding were developed experimentally. The obtained information was used to build the turning inside out machine. This machine works with pneumatic power to carry the inside out turning by means of double effect lineal actuators. It has two independent work stations that could be operated simultaneously by two persons, one in each station or in single mode operating one station by one person. The turning inside out cycle is started by means of directional control valves operated with pedals. The velocity and developed force by the actuators is controlled with typical pneumatic resources. The geometrical dimensions of the machine are: 1.15 m length; 0.71 m width and 2.15 m high. Its approximated weight is 120 kg. The air consumption is 5.4 fps by each working station with 60 psig work pressure. The turning inside out operation is 40 s for each industrial leather glove

Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks

Directory of Open Access Journals (Sweden)

Tao Chen

2016-01-01

Full Text Available Virtualization has been an efficient method to fully utilize computing resources such as servers. The way of placing virtual machines (VMs among a large pool of servers greatly affects the performance of data center networks (DCNs. As network resources have become a main bottleneck of the performance of DCNs, we concentrate on VM placement with Traffic-Aware Balancing to evenly utilize the links in DCNs. In this paper, we first proposed a Virtual Machine Placement Problem with Traffic-Aware Balancing (VMPPTB and then proved it to be NP-hard and designed a Longest Processing Time Based Placement algorithm (LPTBP algorithm to solve it. To take advantage of the communication locality, we proposed Locality-Aware Virtual Machine Placement Problem with Traffic-Aware Balancing (LVMPPTB, which is a multiobjective optimization problem of simultaneously minimizing the maximum number of VM partitions of requests and minimizing the maximum bandwidth occupancy on uplinks of Top of Rack (ToR switches. We also proved it to be NP-hard and designed a heuristic algorithm (Least-Load First Based Placement algorithm, LLBP algorithm to solve it. Through extensive simulations, the proposed heuristic algorithm is proven to significantly balance the bandwidth occupancy on uplinks of ToR switches, while keeping the number of VM partitions of each request small enough.

A Matchmaking Strategy Of Mixed Resource On Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Wisam Elshareef

2015-08-01

Full Text Available Abstract Today cloud computing has become a key technology for online allotment of computing resources and online storage of user data in a lower cost where computing resources are available all the time over the Internet with pay per use concept. Recently there is a growing need for resource management strategies in a cloud computing environment that encompass both end-users satisfaction and a high job submission throughput with appropriate scheduling. One of the major and essential issues in resource management is related to allocate incoming tasks to suitable virtual machine matchmaking. The main objective of this paper is to propose a matchmaking strategy between the incoming requests and various resources in the cloud environment to satisfy the requirements of users and to load balance the workload on resources. Load Balancing is an important aspect of resource management in a cloud computing environment. So this paper proposes a dynamic weight active monitor DWAM load balance algorithm which allocates on the fly the incoming requests to the all available virtual machines in an efficient manner in order to achieve better performance parameters such as response time processing time and resource utilization. The feasibility of the proposed algorithm is analyzed using Cloudsim simulator which proves the superiority of the proposed DWAM algorithm over its counterparts in literature. Simulation results demonstrate that proposed algorithm dramatically improves response time data processing time and more utilized of resource compared Active monitor and VM-assign algorithms.

Control rooms and man-machine interface in nuclear power plants

International Nuclear Information System (INIS)

1990-08-01

The importance of man-machine interface for ensuring safe and reliable operation of nuclear power plants has always been recognized. Since the early 1970's, the concepts of operator support and human factors have been increasingly used to better define the role of control rooms. In the late 1970's, the lessons learned from experience considerably accelerated the development of recommendations and regulatory requirements governing the resources and data available to operators in nuclear power plant control rooms, and specified the expertise required to assist them in case of need. This document summarizes the steps which have been taken and are being planned around the world to improve the man-machine interface for safe and economic power generation. It intends to present to the reader useful examples on some selected control room design and man-machine interface practices for operation and surveillance of nuclear power plants. 53 refs, 94 figs, 27 tabs

Machine performance assessment and enhancement for a hexapod machine

Energy Technology Data Exchange (ETDEWEB)

Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

1998-03-19

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

Adaptive motion of animals and machines

National Research Council Canada - National Science Library

Kimura, Hiroshi

2006-01-01

... single function in a control system and mechanism. That is, adaptation in motion is induced at every level from the central nervous system to the musculoskeletal system. Thus, we organized the International Symposium on Adaptive Motion in Animals and Machines (AMAM) for scientists and engineers concerned with adaptation on various levels to be broug...

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

Extremely Randomized Machine Learning Methods for Compound Activity Prediction

Directory of Open Access Journals (Sweden)

Wojciech M. Czarnecki

2015-11-01

Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

A hybrid human and machine resource curation pipeline for the Neuroscience Information Framework.

Science.gov (United States)

Bandrowski, A E; Cachat, J; Li, Y; Müller, H M; Sternberg, P W; Ciccarese, P; Clark, T; Marenco, L; Wang, R; Astakhov, V; Grethe, J S; Martone, M E

2012-01-01

The breadth of information resources available to researchers on the Internet continues to expand, particularly in light of recently implemented data-sharing policies required by funding agencies. However, the nature of dense, multifaceted neuroscience data and the design of contemporary search engine systems makes efficient, reliable and relevant discovery of such information a significant challenge. This challenge is specifically pertinent for online databases, whose dynamic content is 'hidden' from search engines. The Neuroscience Information Framework (NIF; http://www.neuinfo.org) was funded by the NIH Blueprint for Neuroscience Research to address the problem of finding and utilizing neuroscience-relevant resources such as software tools, data sets, experimental animals and antibodies across the Internet. From the outset, NIF sought to provide an accounting of available resources, whereas developing technical solutions to finding, accessing and utilizing them. The curators therefore, are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping the contents current. In the initial phases of the project, all aspects of the registration and curation processes were manual. However, as the number of resources grew, manual curation became impractical. This report describes our experiences and successes with developing automated resource discovery and semiautomated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. We also describe the DISCO framework, a suite of automated web services that significantly reduce manual curation efforts to periodically check for resource updates. Lastly, we discuss DOMEO, a semi-automated annotation tool that improves the discovery and curation of resources that are not necessarily website-based (i.e. reagents, software tools). Although the ultimate goal of automation was to

Joint Machine Learning and Game Theory for Rate Control in High Efficiency Video Coding.

Science.gov (United States)

Gao, Wei; Kwong, Sam; Jia, Yuheng

2017-08-25

In this paper, a joint machine learning and game theory modeling (MLGT) framework is proposed for inter frame coding tree unit (CTU) level bit allocation and rate control (RC) optimization in High Efficiency Video Coding (HEVC). First, a support vector machine (SVM) based multi-classification scheme is proposed to improve the prediction accuracy of CTU-level Rate-Distortion (R-D) model. The legacy "chicken-and-egg" dilemma in video coding is proposed to be overcome by the learning-based R-D model. Second, a mixed R-D model based cooperative bargaining game theory is proposed for bit allocation optimization, where the convexity of the mixed R-D model based utility function is proved, and Nash bargaining solution (NBS) is achieved by the proposed iterative solution search method. The minimum utility is adjusted by the reference coding distortion and frame-level Quantization parameter (QP) change. Lastly, intra frame QP and inter frame adaptive bit ratios are adjusted to make inter frames have more bit resources to maintain smooth quality and bit consumption in the bargaining game optimization. Experimental results demonstrate that the proposed MLGT based RC method can achieve much better R-D performances, quality smoothness, bit rate accuracy, buffer control results and subjective visual quality than the other state-of-the-art one-pass RC methods, and the achieved R-D performances are very close to the performance limits from the FixedQP method.

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

Directory of Open Access Journals (Sweden)

Ming Cheng

2015-09-01

Full Text Available The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs. Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG. Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

Asynchronized synchronous machines

CERN Document Server

Botvinnik, M M

1964-01-01

Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

Optimizing virtual machine placement for energy and SLA in clouds using utility functions

Directory of Open Access Journals (Sweden)

Abdelkhalik Mosa

2016-10-01

Full Text Available Abstract Cloud computing provides on-demand access to a shared pool of computing resources, which enables organizations to outsource their IT infrastructure. Cloud providers are building data centers to handle the continuous increase in cloud users’ demands. Consequently, these cloud data centers consume, and have the potential to waste, substantial amounts of energy. This energy consumption increases the operational cost and the CO2 emissions. The goal of this paper is to develop an optimized energy and SLA-aware virtual machine (VM placement strategy that dynamically assigns VMs to Physical Machines (PMs in cloud data centers. This placement strategy co-optimizes energy consumption and service level agreement (SLA violations. The proposed solution adopts utility functions to formulate the VM placement problem. A genetic algorithm searches the possible VMs-to-PMs assignments with a view to finding an assignment that maximizes utility. Simulation results using CloudSim show that the proposed utility-based approach reduced the average energy consumption by approximately 6 % and the overall SLA violations by more than 38 %, using fewer VM migrations and PM shutdowns, compared to a well-known heuristics-based approach.

Applications of Machine Learning in Cancer Prediction and Prognosis

Directory of Open Access Journals (Sweden)

Joseph A. Cruz

2006-01-01

Full Text Available Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25% improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

A level set methodology for predicting the effect of mask wear on surface evolution of features in abrasive jet micro-machining

International Nuclear Information System (INIS)

Burzynski, T; Papini, M

2012-01-01

A previous implementation of narrow-band level set methodology developed by the authors was extended to allow for the modelling of mask erosive wear in abrasive jet micro-machining (AJM). The model permits the prediction of the surface evolution of both the mask and the target simultaneously, by representing them as a hybrid and continuous mask–target surface. The model also accounts for the change in abrasive mass flux incident to both the target surface and, for the first time, the eroding mask edge, that is brought about by the presence of the mask edge itself. The predictions of the channel surface and eroded mask profiles were compared with measurements on channels machined in both glass and poly-methyl-methacrylate (PMMA) targets at both normal and oblique incidence, using tempered steel and elastomeric masks. A much better agreement between the predicted and measured profiles was found when mask wear was taken into account. Mask wear generally resulted in wider and deeper glass target profiles and wider PMMA target profiles, respectively, when compared to cases where no mask wear was present. This work has important implications for the AJM of complex MEMS and microfluidic devices that require longer machining times. (paper)

Joint optimization of maintenance, buffers and machines in manufacturing lines

Science.gov (United States)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

Modeling the Virtual Machine Launching Overhead under Fermicloud

Energy Technology Data Exchange (ETDEWEB)

Garzoglio, Gabriele [Fermilab; Wu, Hao [Fermilab; Ren, Shangping [IIT, Chicago; Timm, Steven [Fermilab; Bernabeu, Gerard [Fermilab; Noh, Seo-Young [KISTI, Daejeon

2014-11-12

FermiCloud is a private cloud developed by the Fermi National Accelerator Laboratory for scientific workflows. The Cloud Bursting module of the FermiCloud enables the FermiCloud, when more computational resources are needed, to automatically launch virtual machines to available resources such as public clouds. One of the main challenges in developing the cloud bursting module is to decide when and where to launch a VM so that all resources are most effectively and efficiently utilized and the system performance is optimized. However, based on FermiCloud’s system operational data, the VM launching overhead is not a constant. It varies with physical resource (CPU, memory, I/O device) utilization at the time when a VM is launched. Hence, to make judicious decisions as to when and where a VM should be launched, a VM launch overhead reference model is needed. The paper is to develop a VM launch overhead reference model based on operational data we have obtained on FermiCloud and uses the reference model to guide the cloud bursting process.

Support Vector Machine Untuk Klasifikasi Citra Jenis Daging Berdasarkan Tekstur Menggunakan Ekstraksi Ciri Gray Level Co-Occurrence Matrices (GLCM

Directory of Open Access Journals (Sweden)

Neneng Neneng

2016-11-01

Full Text Available Texture is one of the most important features for image analysis, which provides informations such as the composition of texture on the surface structure, changes of the intensity, or brightness. Gray level co-occurence matrix (GLCM is a method that can be used for statistical texture analysis. GLCM has proven to be the most powerful texture descriptors used in image analysis. This study uses the four-way GLCM 0o, 45o, 90o, and 135o. Support vector machine (SVM is a machine learning that can be used for image classification. SVM has a high generalization capability without any requirement of additional knowledge, even with the high dimension of the input space. The data used in this study are the image of goat meat, buffalo meat, horse meat, and beef with shooting distance 20 cm, 30 cm and 40 cm. The result of this study shows that the best recognition rate of 87.5% was taken at a distance of 20 cm with neighboring pixels distance d = 2 in the direction GLCM 135o.

Beam interlock system and safe machine parameters system 2010 and beyond

CERN Document Server

Todd, B

2010-01-01

The Beam Interlock System (BIS) and Safe Machine Parameters (SMP) system are central to the protection of the Large Hadron Collider (LHC) machine. The BIS has been critical for the safe operation of LHC from the first day of operation. It has been installed and commissioned, only minor enhancements are required in order to accommodate all future LHC machine protection requirements. At reduced intensity, the SMP system is less critical for LHC operation. As such, the current system satisfies the 2010 operational requirements. Further developments are required, both at the SMP Controller level, and at the system level, in order to accommodate the requirements of the LHC beyond 2010.

Resource Guide for Persons with Learning Impairments.

Science.gov (United States)

IBM, Atlanta, GA. National Support Center for Persons with Disabilities.

The resource guide identifies products which assist learning disabled and mentally retarded individuals in accessing IBM (International Business Machine) Personal Computers or the IBM Personal System/2 family of products. An introduction provides a general overview of ways computers can help learning disabled or retarded persons. The document then…

A linear bi-level multi-objective program for optimal allocation of water resources.

Directory of Open Access Journals (Sweden)

Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Staffing Levels and Inpatient Outcomes at Military Health Care Facilities: A Resource-Based View

National Research Council Canada - National Science Library

Yap, Glenn

2004-01-01

Using a Resource-Based Theory/View of the firm, this study examined if increased inpatient staffing levels at military hospitals can generate a competitive advantage based on better patient quality outcomes...

Population-level resource selection by sympatric brown and American black bears in Alaska

Science.gov (United States)

Belant, Jerrold L.; Griffith, Brad; Zhang, Yingte; Follmann, Erich H.; Adams, Layne G.

2010-01-01

Distribution theory predicts that for two species living in sympatry, the subordinate species would be constrained from using the most suitable resources (e.g., habitat), resulting in its use of less suitable habitat and spatial segregation between species. We used negative binomial generalized linear mixed models with fixed effects to estimate seasonal population-level resource selection at two spatial resolutions for female brown bears (Ursus arctos) and female American black bears (U. americanus) in southcentral Alaska during May–September 2000. Black bears selected areas occupied by brown bears during spring which may be related to spatially restricted (i.e., restricted to low elevations) but dispersed or patchy availability of food. In contrast, black bears avoided areas occupied by brown bears during summer. Brown bears selected areas near salmon streams during summer, presumably to access spawning salmon. Use of areas with high berry production by black bears during summer appeared in response to avoidance of areas containing brown bears. Berries likely provided black bears a less nutritious, but adequate food source. We suggest that during summer, black bears were displaced by brown bears, which supports distribution theory in that black bears appeared to be partially constrained from areas containing salmon, resulting in their use of areas containing less nutritious forage. Spatial segregation of brown and American black bears apparently occurs when high-quality resources are spatially restricted and alternate resources are available to the subordinate species. This and previous work suggest that individual interactions between species can result in seasonal population-level responses.

Adaptive multi-objective Optimization scheme for cognitive radio resource management

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2014-01-01

configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance

Machining of Machine Elements Made of Polymer Composite Materials

Science.gov (United States)

Baurova, N. I.; Makarov, K. A.

2017-12-01

The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

Reliability analysis in intelligent machines

Science.gov (United States)

Mcinroy, John E.; Saridis, George N.

1990-01-01

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

Effect of Machine Smoking Intensity and Filter Ventilation Level on Gas-Phase Temperature Distribution Inside a Burning Cigarette

Directory of Open Access Journals (Sweden)

Li Bin

2015-01-01

Full Text Available Accurate measurements of cigarette coal temperature are essential to understand the thermophysical and thermo-chemical processes in a burning cigarette. The last system-atic studies of cigarette burning temperature measurements were conducted in the mid-1970s. Contemporary cigarettes have evolved in design features and multiple standard machine-smoking regimes have also become available, hence there is a need to re-examine cigarette combustion. In this work, we performed systematic measurements on gas-phase temperature of burning cigarettes using an improved fine thermocouple technique. The effects of machine-smoking parameters (puff volume and puff duration and filter ventilation levels were studied with high spatial and time resolutions during single puffs. The experimental results were presented in a number of differ-ent ways to highlight the dynamic and complex thermal processes inside a burning coal. A mathematical distribution equation was used to fit the experimental temperature data. Extracting and plotting the distribution parameters against puffing time revealed complex temperature profiles under different coal volume as a function of puffing intensities or filter ventilation levels. By dividing the coal volume prior to puffing into three temperature ranges (low-temperature from 200 to 400 °C, medium-temperature from 400 to 600 °C, and high-temperature volume above 600 °C by following their development at different smoking regimes, useful mechanistic details were obtained. Finally, direct visualisation of the gas-phase temperature through detailed temperature and temperature gradient contour maps provided further insights into the complex thermo-physics of the burning coal. [Beitr. Tabakforsch. Int. 26 (2014 191-203

An Open-Source Web-Based Tool for Resource-Agnostic Interactive Translation Prediction

Directory of Open Access Journals (Sweden)

Daniel Torregrosa

2014-09-01

Full Text Available We present a web-based open-source tool for interactive translation prediction (ITP and describe its underlying architecture. ITP systems assist human translators by making context-based computer-generated suggestions as they type. Most of the ITP systems in literature are strongly coupled with a statistical machine translation system that is conveniently adapted to provide the suggestions. Our system, however, follows a resource-agnostic approach and suggestions are obtained from any unmodified black-box bilingual resource. This paper reviews our ITP method and describes the architecture of Forecat, a web tool, partly based on the recent technology of web components, that eases the use of our ITP approach in any web application requiring this kind of translation assistance. We also evaluate the performance of our method when using an unmodified Moses-based statistical machine translation system as the bilingual resource.

Cobalt-60 Machines and Medical Linear Accelerators: Competing Technologies for External Beam Radiotherapy.

Science.gov (United States)

Healy, B J; van der Merwe, D; Christaki, K E; Meghzifene, A

2017-02-01

Medical linear accelerators (linacs) and cobalt-60 machines are both mature technologies for external beam radiotherapy. A comparison is made between these two technologies in terms of infrastructure and maintenance, dosimetry, shielding requirements, staffing, costs, security, patient throughput and clinical use. Infrastructure and maintenance are more demanding for linacs due to the complex electric componentry. In dosimetry, a higher beam energy, modulated dose rate and smaller focal spot size mean that it is easier to create an optimised treatment with a linac for conformal dose coverage of the tumour while sparing healthy organs at risk. In shielding, the requirements for a concrete bunker are similar for cobalt-60 machines and linacs but extra shielding and protection from neutrons are required for linacs. Staffing levels can be higher for linacs and more staff training is required for linacs. Life cycle costs are higher for linacs, especially multi-energy linacs. Security is more complex for cobalt-60 machines because of the high activity radioactive source. Patient throughput can be affected by source decay for cobalt-60 machines but poor maintenance and breakdowns can severely affect patient throughput for linacs. In clinical use, more complex treatment techniques are easier to achieve with linacs, and the availability of electron beams on high-energy linacs can be useful for certain treatments. In summary, there is no simple answer to the question of the choice of either cobalt-60 machines or linacs for radiotherapy in low- and middle-income countries. In fact a radiotherapy department with a combination of technologies, including orthovoltage X-ray units, may be an option. Local needs, conditions and resources will have to be factored into any decision on technology taking into account the characteristics of both forms of teletherapy, with the primary goal being the sustainability of the radiotherapy service over the useful lifetime of the equipment

Study on on-Line Measurement and Controlling System of the Foundation Trench-Leveling Machine

International Nuclear Information System (INIS)

Yi, J G; Jiang, H Y; Xing, Y Z; Chen, J; Liu, J T

2006-01-01

Research the system software and hardware composing, the control mode, the online measurement and control principle based on the laser receiver and the inclination sensor as the signal source. After the laser receiver accepts the laser signal, the laser signal is carried through the light filter treatment so as to reduce the sunlight interference, and then amplified and modulated, last transmitted to the control unit. The inclination sensor adapts XWQJ02-01S, measure the slope angle the x and y verticality direction. The error adjusting range is ±0.05 0 . The separate time treatment avoids simultaneously adjusting the laser and inclination signal to each other interfere. The on-line measurement and control system realizes the parts to work on the plane that parallels with the datum plane of the laser beam scan. The trench-leveling machine must retain ±0.05 0 with the datum plane. Adapting the least square method to fit the linear curve, the movement trend of the work parts on the work plane is judged through the slope number. The test result shows that thought the combination measurement and control of the laser and slope angle the leveling precision are ±5mm/100. Its can satisfy with the construction criterion request

Who Should Decide How Machines Make Morally Laden Decisions?

Science.gov (United States)

Martin, Dominic

2017-08-01

Who should decide how a machine will decide what to do when it is driving a car, performing a medical procedure, or, more generally, when it is facing any kind of morally laden decision? More and more, machines are making complex decisions with a considerable level of autonomy. We should be much more preoccupied by this problem than we currently are. After a series of preliminary remarks, this paper will go over four possible answers to the question raised above. First, we may claim that it is the maker of a machine that gets to decide how it will behave in morally laden scenarios. Second, we may claim that the users of a machine should decide. Third, that decision may have to be made collectively or, fourth, by other machines built for this special purpose. The paper argues that each of these approaches suffers from its own shortcomings, and it concludes by showing, among other things, which approaches should be emphasized for different types of machines, situations, and/or morally laden decisions.

Machine-Learning Algorithms to Code Public Health Spending Accounts.

Science.gov (United States)

Brady, Eoghan S; Leider, Jonathon P; Resnick, Beth A; Alfonso, Y Natalia; Bishai, David

Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

The achievements of the Z-machine; Les exploits de la Z-machine

Energy Technology Data Exchange (ETDEWEB)

Larousserie, D

2008-03-15

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Handling machine breakdown for dynamic scheduling by a colony of cognitive agents in a holonic manufacturing framework

Directory of Open Access Journals (Sweden)

T. K. Jana

2015-09-01

Full Text Available There is an ever increasing need of providing quick, yet improved solution to dynamic scheduling by better responsiveness following simple coordination mechanism to better adapt to the changing environments. In this endeavor, a cognitive agent based approach is proposed to deal with machine failure. A Multi Agent based Holonic Adaptive Scheduling (MAHoAS architecture is developed to frame the schedule by explicit communication between the product holons and the resource holons in association with the integrated process planning and scheduling (IPPS holon under normal situation. In the event of breakdown of a resource, the cooperation is sought by implicit communication. Inspired by the cognitive behavior of human being, a cognitive decision making scheme is proposed that reallocates the incomplete task to another resource in the most optimized manner and tries to expedite the processing in view of machine failure. A metamorphic algorithm is developed and implemented in Oracle 9i to identify the best candidate resource for task re-allocation. Integrated approach to process planning and scheduling realized under Multi Agent System (MAS framework facilitates dynamic scheduling with improved performance under such situations. The responsiveness of the resources having cognitive capabilities helps to overcome the adverse consequences of resource failure in a better way.

Integration of Cloud resources in the LHCb Distributed Computing

Science.gov (United States)

Úbeda García, Mario; Méndez Muñoz, Víctor; Stagni, Federico; Cabarrou, Baptiste; Rauschmayr, Nathalie; Charpentier, Philippe; Closier, Joel

2014-06-01

This contribution describes how Cloud resources have been integrated in the LHCb Distributed Computing. LHCb is using its specific Dirac extension (LHCbDirac) as an interware for its Distributed Computing. So far, it was seamlessly integrating Grid resources and Computer clusters. The cloud extension of DIRAC (VMDIRAC) allows the integration of Cloud computing infrastructures. It is able to interact with multiple types of infrastructures in commercial and institutional clouds, supported by multiple interfaces (Amazon EC2, OpenNebula, OpenStack and CloudStack) - instantiates, monitors and manages Virtual Machines running on this aggregation of Cloud resources. Moreover, specifications for institutional Cloud resources proposed by Worldwide LHC Computing Grid (WLCG), mainly by the High Energy Physics Unix Information Exchange (HEPiX) group, have been taken into account. Several initiatives and computing resource providers in the eScience environment have already deployed IaaS in production during 2013. Keeping this on mind, pros and cons of a cloud based infrasctructure have been studied in contrast with the current setup. As a result, this work addresses four different use cases which represent a major improvement on several levels of our infrastructure. We describe the solution implemented by LHCb for the contextualisation of the VMs based on the idea of Cloud Site. We report on operational experience of using in production several institutional Cloud resources that are thus becoming integral part of the LHCb Distributed Computing resources. Furthermore, we describe as well the gradual migration of our Service Infrastructure towards a fully distributed architecture following the Service as a Service (SaaS) model.

Integration of cloud resources in the LHCb distributed computing

International Nuclear Information System (INIS)

García, Mario Úbeda; Stagni, Federico; Cabarrou, Baptiste; Rauschmayr, Nathalie; Charpentier, Philippe; Closier, Joel; Muñoz, Víctor Méndez

2014-01-01

This contribution describes how Cloud resources have been integrated in the LHCb Distributed Computing. LHCb is using its specific Dirac extension (LHCbDirac) as an interware for its Distributed Computing. So far, it was seamlessly integrating Grid resources and Computer clusters. The cloud extension of DIRAC (VMDIRAC) allows the integration of Cloud computing infrastructures. It is able to interact with multiple types of infrastructures in commercial and institutional clouds, supported by multiple interfaces (Amazon EC2, OpenNebula, OpenStack and CloudStack) – instantiates, monitors and manages Virtual Machines running on this aggregation of Cloud resources. Moreover, specifications for institutional Cloud resources proposed by Worldwide LHC Computing Grid (WLCG), mainly by the High Energy Physics Unix Information Exchange (HEPiX) group, have been taken into account. Several initiatives and computing resource providers in the eScience environment have already deployed IaaS in production during 2013. Keeping this on mind, pros and cons of a cloud based infrasctructure have been studied in contrast with the current setup. As a result, this work addresses four different use cases which represent a major improvement on several levels of our infrastructure. We describe the solution implemented by LHCb for the contextualisation of the VMs based on the idea of Cloud Site. We report on operational experience of using in production several institutional Cloud resources that are thus becoming integral part of the LHCb Distributed Computing resources. Furthermore, we describe as well the gradual migration of our Service Infrastructure towards a fully distributed architecture following the Service as a Service (SaaS) model.

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.

Management system of ELHEP cluster machine for FEL photonics design

Science.gov (United States)

Zysik, Jacek; Poźniak, Krzysztof; Romaniuk, Ryszard

2006-10-01

A multipurpose, distributed MatLab calculations oriented, cluster machine was assembled in PERG/ELHEP laboratory at ISE/WUT. It is predicted mainly for advanced photonics and FPGA/DSP based systems design for Free Electron Laser. It will be used also for student projects for superconducting accelerator and FEL. Here we present one specific side of cluster design. For an intense, distributed daily work with the cluster, it is important to have a good interface and practical access to all machine resources. A complex management system was implemented in PERG laboratory. It helps all registered users to work using all necessary applications, communicate with other logged in people, check all the news and gather all necessary information about what is going on in the system, how it is utilized, etc. The system is also very practical for administrator purposes, it helps to keep controlling who is using the resources and for how long. It provides different privileges for different applications and many more. The system is introduced as a freeware, using open source code and can be modified by system operators or super-users who are interested in nonstandard system configuration.

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

Science.gov (United States)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Principal Components of Superhigh-Dimensional Statistical Features and Support Vector Machine for Improving Identification Accuracies of Different Gear Crack Levels under Different Working Conditions

Directory of Open Access Journals (Sweden)

Dong Wang

2015-01-01

Full Text Available Gears are widely used in gearbox to transmit power from one shaft to another. Gear crack is one of the most frequent gear fault modes found in industry. Identification of different gear crack levels is beneficial in preventing any unexpected machine breakdown and reducing economic loss because gear crack leads to gear tooth breakage. In this paper, an intelligent fault diagnosis method for identification of different gear crack levels under different working conditions is proposed. First, superhigh-dimensional statistical features are extracted from continuous wavelet transform at different scales. The number of the statistical features extracted by using the proposed method is 920 so that the extracted statistical features are superhigh dimensional. To reduce the dimensionality of the extracted statistical features and generate new significant low-dimensional statistical features, a simple and effective method called principal component analysis is used. To further improve identification accuracies of different gear crack levels under different working conditions, support vector machine is employed. Three experiments are investigated to show the superiority of the proposed method. Comparisons with other existing gear crack level identification methods are conducted. The results show that the proposed method has the highest identification accuracies among all existing methods.

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.

A Review of Design Optimization Methods for Electrical Machines

Directory of Open Access Journals (Sweden)

Gang Lei

2017-11-01

Full Text Available Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines.

Applicability of Machine-Learning Enabled LIBS in Post Irradiation Nuclear Forensic Analysis of High Level Waste

International Nuclear Information System (INIS)

Onkongi, J.; Maina, D.; Angeyo, H.K.

2017-01-01

Nuclear Forensics seeks Information to determine; Chemical Composition, Routes of transit, Origin (Provenance) and Intended use. Post Irradiation/Post detonation NF In a post-detonation event could you get clues/signatures from glass debris, minute sample sizes? Nuclear Forensic Technique Should be State-of -the art that is Rapid, Non-invasive, Remote ability and Non-destructive. Laser Induced Breakdown Spectroscopy (LIBS) unlike other Analytic Techniques that require tedious sample preparations such as Dissolution, digestion & matrix removal, which generate additional nuclear wastes that require proper Procedures for handling, storage & ultimate disposal, LIBS overcomes these limitations. Utility of Machine Learning Techniques employed include; Artificial Neural Networks, ANN (Regression/Modelling), Principal component Analysis, PCA (Classification) and Support Vector Machine SVM (Comparative study/Classification Machine Learning coupled with LIBS gives a state of the art analytic method. Utility of the technic in safeguards security and non-proliferation

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

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

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

Linear electric machines, drives, and MAGLEVs handbook

CERN Document Server

Boldea, Ion

2013-01-01

Based on author Ion Boldea's 40 years of experience and the latest research, Linear Electric Machines, Drives, and Maglevs Handbook provides a practical and comprehensive resource on the steady improvement in this field. The book presents in-depth reviews of basic concepts and detailed explorations of complex subjects, including classifications and practical topologies, with sample results based on an up-to-date survey of the field. Packed with case studies, this state-of-the-art handbook covers topics such as modeling, steady state, and transients as well as control, design, and testing of li

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

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

Beam-related machine protection for the CERN Large Hadron Collider experiments

Directory of Open Access Journals (Sweden)

R. B. Appleby

2010-06-01

Full Text Available The Large Hadron Collider at CERN, Geneva stores 360 MJ per beam of protons at the top machine energy. This amount of energy storage presents a considerable challenge to the machine protection systems designed to protect both the machine and the six LHC experiments. This paper provides an overview of the machine protection systems relevant to the protection of the experiments, and demonstrates their operation and level of protection through a series of injection and stored beam failure scenarios. We conclude that the systems provide sufficient coverage for the protection of the experiments as far as reasonably possible.

Non-conventional electrical machines

CERN Document Server

Rezzoug, Abderrezak

2013-01-01

The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

Multi-level governance of forest resources (Editorial to the special feature

Directory of Open Access Journals (Sweden)

Esther Mwangi

2012-08-01

Full Text Available A major challenge for many researchers and practitioners relates to how to recognize and address cross-scale dynamics in space and over time in order to design and implement effective governance arrangements. This editorial provides an overview of the concept of multi-level governance (MLG. In particular we highlight definitional issues, why the concept matters as well as more practical concerns related to the processes and structure of multi-level governance. It is increasingly clear that multi-level governance of forest resources involves complex interactions of state, private and civil society actors at various levels, and institutions linking higher levels of social and political organization. Local communities are increasingly connected to global networks and influences. This creates new opportunities to learn and address problems but may also introduce new pressures and risks. We conclude by stressing the need for a much complex approach to the varieties of MLG to better understand how policies work as instruments of governance and to organize communities within systems of power and authority.

High-level methodologies for grammar engineering, introduction to the special issue

Directory of Open Access Journals (Sweden)

Denys Duchier

2015-06-01

Full Text Available Grammar Engineering is the task of designing and implementing linguistically motivated electronic descriptions of natural language (so-called grammars. These grammars are expressed within well-defined theoretical frameworks, and offer a fine-grained description of natural language. While grammars were first used to describe syntax, that is to say, the relations between constituents in a sentence, they often go beyond syntax and include semantic information. Grammar engineering provides precise descriptions which can be used for natural language understanding and generation, making these valuable resources for various natural language applications, including textual entailment, dialogue systems, or machine translation. The first attempts at designing large-scale resource grammars were costly because of the complexity of the task (Erbach et al. 1990 and of the number of persons that were needed (see e.g. Doran et al. 1997. Advances in the field have led to the development of environments for semi-automatic grammar engineering, borrowing ideas from compilation (grammar engineering is compared with software development and machine learning. This special issue reports on new trends in the field, where grammar engineering benefits from elaborate high-level methodologies and techniques, dealing with various issues (both theoretical and practical.

Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

Directory of Open Access Journals (Sweden)

Supriya Kinger

2014-01-01

Full Text Available Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

Prediction based proactive thermal virtual machine scheduling in green clouds.

Science.gov (United States)

Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

2014-01-01

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

Science.gov (United States)

Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

2014-01-01

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated. PMID:24737962

A Flattened Hierarchical Scheduler for Real-Time Virtual Machines

OpenAIRE

Drescher, Michael Stuart

2015-01-01

The recent trend of migrating legacy computer systems to a virtualized, cloud-based environment has expanded to real-time systems. Unfortunately, modern hypervisors have no mechanism in place to guarantee the real-time performance of applications running on virtual machines. Past solutions to this problem rely on either spatial or temporal resource partitioning, both of which under-utilize the processing capacity of the host system. Paravirtualized solutions in which the guest communicates it...

Availability, Level of Use and Constraints to Use of Electronic Resources by Law Lecturers in Public Universities in Nigeria

Science.gov (United States)

Amusa, Oyintola Isiaka; Atinmo, Morayo

2016-01-01

(Purpose) This study surveyed the level of availability, use and constraints to use of electronic resources among law lecturers in Nigeria. (Methodology) Five hundred and fifty-two law lecturers were surveyed and four hundred and forty-two responded. (Results) Data analysis revealed that the level of availability of electronic resources for the…

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

2014-08-15

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

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

International Nuclear Information System (INIS)

Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

2014-01-01

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

SLA-based optimisation of virtualised resource for multi-tier web applications in cloud data centres

Science.gov (United States)

Bi, Jing; Yuan, Haitao; Tie, Ming; Tan, Wei

2015-10-01

Dynamic virtualised resource allocation is the key to quality of service assurance for multi-tier web application services in cloud data centre. In this paper, we develop a self-management architecture of cloud data centres with virtualisation mechanism for multi-tier web application services. Based on this architecture, we establish a flexible hybrid queueing model to determine the amount of virtual machines for each tier of virtualised application service environments. Besides, we propose a non-linear constrained optimisation problem with restrictions defined in service level agreement. Furthermore, we develop a heuristic mixed optimisation algorithm to maximise the profit of cloud infrastructure providers, and to meet performance requirements from different clients as well. Finally, we compare the effectiveness of our dynamic allocation strategy with two other allocation strategies. The simulation results show that the proposed resource allocation method is efficient in improving the overall performance and reducing the resource energy cost.

Discrimination against Latina/os: A Meta-Analysis of Individual-Level Resources and Outcomes

Science.gov (United States)

Lee, Debbiesiu L.; Ahn, Soyeon

2012-01-01

This meta-analysis synthesizes the findings of 60 independent samples from 51 studies examining racial/ethnic discrimination against Latina/os in the United States. The purpose was to identify individual-level resources and outcomes that most strongly relate to discrimination. Discrimination against Latina/os significantly results in outcomes…

Living systematic reviews: 2. Combining human and machine effort.

Science.gov (United States)

Thomas, James; Noel-Storr, Anna; Marshall, Iain; Wallace, Byron; McDonald, Steven; Mavergames, Chris; Glasziou, Paul; Shemilt, Ian; Synnot, Anneliese; Turner, Tari; Elliott, Julian

2017-11-01

New approaches to evidence synthesis, which use human effort and machine automation in mutually reinforcing ways, can enhance the feasibility and sustainability of living systematic reviews. Human effort is a scarce and valuable resource, required when automation is impossible or undesirable, and includes contributions from online communities ("crowds") as well as more conventional contributions from review authors and information specialists. Automation can assist with some systematic review tasks, including searching, eligibility assessment, identification and retrieval of full-text reports, extraction of data, and risk of bias assessment. Workflows can be developed in which human effort and machine automation can each enable the other to operate in more effective and efficient ways, offering substantial enhancement to the productivity of systematic reviews. This paper describes and discusses the potential-and limitations-of new ways of undertaking specific tasks in living systematic reviews, identifying areas where these human/machine "technologies" are already in use, and where further research and development is needed. While the context is living systematic reviews, many of these enabling technologies apply equally to standard approaches to systematic reviewing. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Exploiting the Dynamics of Soft Materials for Machine Learning.

Science.gov (United States)

Nakajima, Kohei; Hauser, Helmut; Li, Tao; Pfeifer, Rolf

2018-06-01

Soft materials are increasingly utilized for various purposes in many engineering applications. These materials have been shown to perform a number of functions that were previously difficult to implement using rigid materials. Here, we argue that the diverse dynamics generated by actuating soft materials can be effectively used for machine learning purposes. This is demonstrated using a soft silicone arm through a technique of multiplexing, which enables the rich transient dynamics of the soft materials to be fully exploited as a computational resource. The computational performance of the soft silicone arm is examined through two standard benchmark tasks. Results show that the soft arm compares well to or even outperforms conventional machine learning techniques under multiple conditions. We then demonstrate that this system can be used for the sensory time series prediction problem for the soft arm itself, which suggests its immediate applicability to a real-world machine learning problem. Our approach, on the one hand, represents a radical departure from traditional computational methods, whereas on the other hand, it fits nicely into a more general perspective of computation by way of exploiting the properties of physical materials in the real world.

Calibrators measurement system for headlamp tester of motor vehicle base on machine vision

Science.gov (United States)

Pan, Yue; Zhang, Fan; Xu, Xi-ping; Zheng, Zhe

2014-09-01

With the development of photoelectric detection technology, machine vision has a wider use in the field of industry. The paper mainly introduces auto lamps tester calibrator measuring system, of which CCD image sampling system is the core. Also, it shows the measuring principle of optical axial angle and light intensity, and proves the linear relationship between calibrator's facula illumination and image plane illumination. The paper provides an important specification of CCD imaging system. Image processing by MATLAB can get flare's geometric midpoint and average gray level. By fitting the statistics via the method of the least square, we can get regression equation of illumination and gray level. It analyzes the error of experimental result of measurement system, and gives the standard uncertainty of synthesis and the resource of optical axial angle. Optical axial angle's average measuring accuracy is controlled within 40''. The whole testing process uses digital means instead of artificial factors, which has higher accuracy, more repeatability and better mentality than any other measuring systems.

Impact of Machine Breakdowns on Productivity

Directory of Open Access Journals (Sweden)

Anwaruddin Tanwari

2011-10-01

Full Text Available This paper reports the machine breakdowns and their impact on the total productivity for the FMCGs (Fast Moving Consumer Goods industry because higher productivity rate is important factor on which the customer services largely depend in this competitive business world. This paper also suggests that the machine breakdowns and other related problems within the plant are due to improper care, keeping the plant operative for twenty four hours a day, seven days a week without any break and lack of management\\'s concentration towards these issues. These break-downs results in un-timely closure of the plant and very poor production performance is achieved in the plant that affects the service level at great level. Realising the importance of maintenance in improving productivity and service, an attempt has been made in this paper to study the scope of maintenance with the help of a case study.

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...

Man-machine interface for the MFTF

International Nuclear Information System (INIS)

Speckert, G.C.

1979-01-01

In any complex system, the interesting problems occur at the interface of dissimilar subsystems. Control of the Mirror Fusion Test Facility (MFTF) begins with the US Congress, which controls the dollars, which control the people, who control the nine top-level minicomputers, which control the 65 microprocessors, which control the hardware that controls the physics experiment. There are many interesting boundaries across which control must pass, and the one that this paper addresses is the man-machine one. For the MFTF, the man-machine interface consists of a system of seven control consoles, each allowing one operator to communicate with one minicomputer. These consoles are arranged in a hierarchical manner, and both hardware and software were designed in a top-down fashion. This paper describes the requirements and the design of the console system as a whole, as well as the design and operation of the hardware and software of each console, and examines the possible form of a future man-machine interface

Man-machine interface for the MFTF

Energy Technology Data Exchange (ETDEWEB)

Speckert, G.C.

1979-11-09

In any complex system, the interesting problems occur at the interface of dissimilar subsystems. Control of the Mirror Fusion Test Facility (MFTF) begins with the US Congress, which controls the dollars, which control the people, who control the nine top-level minicomputers, which control the 65 microprocessors, which control the hardware that controls the physics experiment. There are many interesting boundaries across which control must pass, and the one that this paper addresses is the man-machine one. For the MFTF, the man-machine interface consists of a system of seven control consoles, each allowing one operator to communicate with one minicomputer. These consoles are arranged in a hierarchical manner, and both hardware and software were designed in a top-down fashion. This paper describes the requirements and the design of the console system as a whole, as well as the design and operation of the hardware and software of each console, and examines the possible form of a future man-machine interface.

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

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

Modelling of human-machine interaction in equipment design of manufacturing cells

Science.gov (United States)

Cochran, David S.; Arinez, Jorge F.; Collins, Micah T.; Bi, Zhuming

2017-08-01

This paper proposes a systematic approach to model human-machine interactions (HMIs) in supervisory control of machining operations; it characterises the coexistence of machines and humans for an enterprise to balance the goals of automation/productivity and flexibility/agility. In the proposed HMI model, an operator is associated with a set of behavioural roles as a supervisor for multiple, semi-automated manufacturing processes. The model is innovative in the sense that (1) it represents an HMI based on its functions for process control but provides the flexibility for ongoing improvements in the execution of manufacturing processes; (2) it provides a computational tool to define functional requirements for an operator in HMIs. The proposed model can be used to design production systems at different levels of an enterprise architecture, particularly at the machine level in a production system where operators interact with semi-automation to accomplish the goal of 'autonomation' - automation that augments the capabilities of human beings.

A 5-year prospective radiographic evaluation of marginal bone levels adjacent to parallel-screw cylinder machined-neck implants and rough-surfaced microthreaded implants using digitized panoramic radiographs.

Science.gov (United States)

Nickenig, Hans-Joachim; Wichmann, Manfred; Happe, Arndt; Zöller, Joachim E; Eitner, Stephan

2013-10-01

The purpose of this split-mouth study was to compare macro- and microstructure implant surfaces at the marginal bone level over five years of functional loading. From January to February 2006, 133 implants (70 rough-surfaced microthreaded implants and 63 machined-neck implants) were inserted in the mandible of 34 patients with Kennedy Class I residual dentitions and followed until December 2011. Marginal bone level was radiographically determined at six time points: implant placement (baseline), after the healing period, after six months, and at two years, three years, and five years follow-up. Median follow-up time was 5.2 years (range: 5.1-5.4). The machined-neck group had a mean crestal bone loss of 0.5 mm (0.0-2.3) after the healing period, 1.1 mm (0.0-3.0) at two years follow-up, and 1.4 mm (0.0-2.9) at five years follow-up. The rough-surfaced microthreaded implant group had a mean bone loss of 0.1 mm (-0.4 to 2.0) after the healing period, 0.5 mm (0.0-2.1) at two years follow-up, and 0.7 mm (0.0-2.3) at five years follow-up. The two implant types showed significant differences in marginal bone levels. Rough-surfaced microthreaded design caused significantly less loss of crestal bone levels under long-term functional loading in the mandible when compared to machined-neck implants. Copyright © 2012 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

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.

Correlation between use time of machine and decline curve for emerging enterprise information systems

Science.gov (United States)

Chang, Yao-Chung; Lai, Chin-Feng; Chuang, Chi-Cheng; Hou, Cheng-Yu

2018-04-01

With the progress of science and technology, more and more machines are adpot to help human life better and more convenient. When the machines have been used for a longer period of time so that the machine components are getting old, the amount of power comsumption will increase and easily cause the machine to overheat. This also causes a waste of invisible resources. If the Internet of Everything (IoE) technologies are able to be applied into the enterprise information systems for monitoring the machines use time, it can not only make energy can be effectively used, but aslo create a safer living environment. To solve the above problem, the correlation predict model is established to collect the data of power consumption converted into power eigenvalues. This study takes the power eigenvalue as the independent variable and use time as the dependent variable in order to establish the decline curve. Ultimately, the scoring and estimation modules are employed to seek the best power eigenvalue as the independent variable. To predict use time, the correlation is discussed between the use time and the decline curve to improve the entire behavioural analysis of the facilitate recognition of the use time of machines.

An Evaluation of a Human Machine Interface based on Attentional-resources Effectiveness

International Nuclear Information System (INIS)

Ha, Jun Su; Seong, Poong Hyun

2008-01-01

Measures of attentional-resource effectiveness during monitoring and detection tasks in nuclear power plants (NPPs) have been developed based on cost-benefit principle and validated with experimental studies. The underlying principle of the measures is that information sources should be selectively attended according to their informational importance. One of two measures is Fixation to Importance Ratio (FIR) which represents attentional-resources (eye fixations) spent on an information source compared to importance of the information source

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

Science.gov (United States)

2014-11-01

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

Overhead-Aware-Best-Fit (OABF) Resource Allocation Algorithm for Minimizing VM Launching Overhead

Energy Technology Data Exchange (ETDEWEB)

Wu, Hao [IIT; Garzoglio, Gabriele [Fermilab; Ren, Shangping [IIT, Chicago; Timm, Steven [Fermilab; Noh, Seo Young [KISTI, Daejeon

2014-11-11

FermiCloud is a private cloud developed in Fermi National Accelerator Laboratory to provide elastic and on-demand resources for different scientific research experiments. The design goal of the FermiCloud is to automatically allocate resources for different scientific applications so that the QoS required by these applications is met and the operational cost of the FermiCloud is minimized. Our earlier research shows that VM launching overhead has large variations. If such variations are not taken into consideration when making resource allocation decisions, it may lead to poor performance and resource waste. In this paper, we show how we may use an VM launching overhead reference model to minimize VM launching overhead. In particular, we first present a training algorithm that automatically tunes a given refer- ence model to accurately reflect FermiCloud environment. Based on the tuned reference model for virtual machine launching overhead, we develop an overhead-aware-best-fit resource allocation algorithm that decides where and when to allocate resources so that the average virtual machine launching overhead is minimized. The experimental results indicate that the developed overhead-aware-best-fit resource allocation algorithm can significantly improved the VM launching time when large number of VMs are simultaneously launched.

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

Science.gov (United States)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

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)

Induction machine handbook

CERN Document Server

Boldea, Ion

2002-01-01

Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

Chaotic Boltzmann machines

Science.gov (United States)

Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

2013-01-01

The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

Rotating electrical machines

CERN Document Server

Le Doeuff, René

2013-01-01

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

RAM analysis of earth pressure balance tunnel boring machines: A case study

Directory of Open Access Journals (Sweden)

Hasel Amini Khoshalan

2015-12-01

Full Text Available Earth pressure balance tunnel boring machines (EPB-TBMs are favorably applied in urban tunneling projects. Despite their numerous advantages, considerable delays and high maintenance cost are the main disadvantages these machines suffer from. Reliability, availability, and maintainability (RAM analysis is a practical technique that uses failure and repair dataset obtained over a reasonable time for dealing with proper machine operation, maintenance scheduling, cost control, and improving the availability and performance of such machines. In the present study, a database of failures and repairs of an EBP-TBM was collected in line 1 of Tabriz subway project over a 26-month interval of machine operation. In order to model the reliability of the TBM, this machine was divided into five distinct subsystems including mechanical, electrical, hydraulic, pneumatic, and water systems in a series configuration. According to trend and serial correlation tests, the renewal processes were applied, for analysis of all subsystems. After calculating the reliability and maintainability functions for all subsystems, it was revealed that the mechanical subsystem with the highest failure frequency has the lowest reliability and maintainability. Similarly, estimating the availability of all subsystems indicated that the mechanical subsystem has a relatively low availability level of 52.6%, while other subsystems have acceptable availability level of 97%. Finally, the overall availability of studied machine was calculated as 48.3%.

Your Sewing Machine.

Science.gov (United States)

Peacock, Marion E.

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

Underground roadway drivage with heading machines in Indian coal industry

Energy Technology Data Exchange (ETDEWEB)

Mukherjee, T.K.

1983-03-01

Heading machines have assumed a very important place in underground roadway drivage. They are not only a compromise between ''drill-and-blast'' technique and full-face machines, but are also an economic and versatile form of mechanised roadway drivage. Since the advantages gained by heading machines are considerable, the use of these machines is becoming popular in underground roadway drivage. Experience with continuous miner and heading machines in Indian coal mines is very limited compared to that of Western countries. In 1964-65, for the first time, two units of Lee Norse Miner were used at Kunostoria Colliery of Bengal Coal Company. In 1966, two units of Joy Continuous Miner were introduced at Chalkari Colliery of National Coal Development Corporation, but had to be adandoned because of heavy make of water at the installation site. A Russian PK-3 heading machine was used limitedly during the development of Banki Colliery, Madhya Pradesh. A Demag Unicorn VS-1 machine operated for the development of roadways at Jitpur and Chasnala Collieries of IISCO between 1967-70. With this machine, progress of 7 m per day was attained in level roadways and of about 2 m per day in steep raises.

Electronic gaming machines: are they the 'crack-cocaine' of gambling?

Science.gov (United States)

Dowling, Nicki; Smith, David; Thomas, Trang

2005-01-01

There is a general view that electronic gaming is the most 'addictive' form of gambling, in that it contributes more to causing problem gambling than any other gambling activity. As such, electronic gaming machines have been referred to as the 'crack-cocaine' of gambling. While this analogy has popular appeal, it is only recently that the scientific community has begun to investigate its validity. In line with the belief that electronic gambling has a higher 'addictive' potential than other forms of gambling, research has also begun to focus on identifying the characteristics of gaming machines that may be associated with problem gambling behaviour. This paper will review the different types of modern electronic gaming machines, and will use the introduction of gaming machines to Australia to examine the association between electronic gaming and problem gambling, with particular reference to the characteristics of modern electronic gaming machines. Despite overwhelming acceptance that gaming machines are associated with the highest level of problem gambling, the empirical literature provides inconclusive evidence to support the analogy linking electronic gaming to 'crack-cocaine'. Rigorous and systematic evaluation is required to establish definitively the absolute 'addictive' potential of gaming machines and the degree to which machine characteristics influence the development and maintenance of problem gambling behaviour.

Investigation of the Machining Stability of a Milling Machine with Hybrid Guideway Systems

Directory of Open Access Journals (Sweden)

Jui-Pin Hung

2016-03-01

Full Text Available This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

Loads as a Resource: Frequency Responsive Demand

Energy Technology Data Exchange (ETDEWEB)

Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhang, Wei [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moya, Christian [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2014-10-08

Frequency control plays an important role in preserving the power balance of a multi-machine power system. Generators modify their power output when a non-zero frequency deviation is presented in order to restore power balance across the network. However, with plans for large-scale penetration of renewable energy resources, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive, but also technically difficult. Frequency control from the demand side or load control presents a novel and viable way for providing the desired frequency response. Loads can measure frequency locally and change their power consumption after a non-zero frequency deviation is presented in order to achieve power balance between generation and consumption. The specific objectives of this project are to: •Provide a framework to facilitate large-scale deployment of frequency responsive end-use devices •Systematically design decentralized frequency-based load control strategies for enhanced stability performance •Ensure applicability over wide range of operating conditions while accounting for unpredictable end-use behavior and physical device constraints •Test and validate control strategy using large-scale simulations and field demonstrations •Create a level-playing field for smart grid assets with conventional generators

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

Science.gov (United States)

Mehmood, Shahid; Shah, Masood; Pasha, Riffat Asim; Sultan, Amir

2017-10-01

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

Are there intelligent Turing machines?

OpenAIRE

Bátfai, Norbert

2015-01-01

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

Radiographic evaluation of marginal bone levels adjacent to parallel-screw cylinder machined-neck implants and rough-surfaced microthreaded implants using digitized panoramic radiographs.

Science.gov (United States)

Nickenig, Hans-Joachim; Wichmann, Manfred; Schlegel, Karl Andreas; Nkenke, Emeka; Eitner, Stephan

2009-06-01

The purpose of this split-mouth study was to compare macro- and microstructure implant surfaces at the marginal bone level during a stress-free healing period and under functional loading. From January to February 2006, 133 implants (70 rough-surfaced microthreaded implants and 63 machined-neck implants) were inserted in the mandible of 34 patients with Kennedy Class I residual dentitions and followed until February 2008. The marginal bone level was radiographically determined, using digitized panoramic radiographs, at four time points: at implant placement (baseline level), after the healing period, after 6 months of functional loading, and at the end of follow-up. The median follow-up time was 1.9 (range: 1.9-2.1) years. The machined-neck group had a mean crestal bone loss of 0.5 mm (range: 0-2.3) after the healing period, 0.8 mm after 6 months (range: 0-2.4), and 1.1 mm (range: 0-3) at the end of follow-up. The rough-surfaced microthreaded implant group had a mean bone loss of 0.1 mm (range: -0.4-2) after the healing period, 0.4 mm (range: 0-2.1) after 6 months, and 0.5 mm (range: 0-2.1) at the end of follow-up. The two implant types showed significant differences in marginal bone levels (healing period: P=0.01; end of follow-up: Pimplants showed that implants with the microthreaded design caused minimal changes in crestal bone levels during healing (stress-free) and under functional loading.

High Accuracy Nonlinear Control and Estimation for Machine Tool Systems

DEFF Research Database (Denmark)

Papageorgiou, Dimitrios

Component mass production has been the backbone of industry since the second industrial revolution, and machine tools are producing parts of widely varying size and design complexity. The ever-increasing level of automation in modern manufacturing processes necessitates the use of more...... sophisticated machine tool systems that are adaptable to different workspace conditions, while at the same time being able to maintain very narrow workpiece tolerances. The main topic of this thesis is to suggest control methods that can maintain required manufacturing tolerances, despite moderate wear and tear....... The purpose is to ensure that full accuracy is maintained between service intervals and to advice when overhaul is needed. The thesis argues that quality of manufactured components is directly related to the positioning accuracy of the machine tool axes, and it shows which low level control architectures...

Coldness production and heat revalorization: particular machines; Production de froid et revalorisation de la chaleur: machines particulieres

Energy Technology Data Exchange (ETDEWEB)

Feidt, M. [Universite Henri Poincare - Nancy-1, 54 - Nancy (France)

2003-10-01

The machines presented in this article are not the common reverse cycle machines. They use some systems based on different physical principles which have some consequences on the analysis of cycles: 1 - permanent gas machines (thermal separators, pulse gas tube, thermal-acoustic machines); 2 - phase change machines (mechanical vapor compression machines, absorption machines, ejection machines, adsorption machines); 3 - thermoelectric machines (thermoelectric effects, thermodynamic model of a thermoelectric machine). (J.S.)

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

Science.gov (United States)

Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

‘Machinic Trajectories’: Appropriated Devices as Post-Digital Drawing Machines

Directory of Open Access Journals (Sweden)

Andres Wanner

2014-12-01

Full Text Available This article presents a series of works called Machinic Trajectories, consisting of domestic devices appropriated as mechanical drawing machines. These are contextualized within the post-digital discourse, which integrates messy analog conditions into the digital realm. The role of eliciting and examining glitches for investigating a technology is pointed out. Glitches are defined as short-lived, unpremeditated aesthetic results of a failure; they are mostly known as digital phenomena, but I argue that the concept is equally applicable to the output of mechanical machines. Three drawing machines will be presented: The Opener, The Mixer and The Ventilator. In analyzing their drawings, emergent patterns consisting of unpremeditated visual artifacts will be identified and connected to irregularities of the specific technologies. Several other artists who work with mechanical and robotic drawing machines are introduced, to situate the presented works and reflections in a larger context of practice and to investigate how glitch concepts are applicable to such mechanical systems. 

Resource conservation through beverage container recycling

Energy Technology Data Exchange (ETDEWEB)

Gaines, L L; Wolsky, A M

1983-01-01

This paper compares resource use for new and recycled polyester soft drink bottles with the glass bottles they displace, to determine the alternatives with minimum resource burden. A mechanism is then suggested for encouraging one efficient alternative. Since the introduction of plastic soft-drink bottles in 1977, the 2 1. container has captured almost the entire U.S. market. The number of PET bottles used in 1981 was 2.4 billion, and could grow to 14 billion by 1990 if the penetration into the 0.5 1. market is as rapid as some experts predict (2). Consumers value the PET bottle's light weight and unbreakability. However, plastic bottles are made from oil and gas feedstocks which are imported and becoming more expensive. Recycling drastically reduces the oil and gas required to supply these bottles; recycling PET from bottles to other uses could save on the order of six million barrels of oil equivalent per year by 1990. A simple and economic technology is available for performing this recovery, yet only 5% of the bottles used in 1980 were returned. What is missing is an effective inducement for bottle return. The reverse-vending machines that we propose can provide part of that inducement by eliminating the inconvenience that now surrounds the sale of empty bottles to recyclers. These machines would dispense coins in return for empty PET bottles, and could be located in supermarkets or their parking lots. We believe the design, construction, and use of such machines is an opportunity that has been overlooked.

The development of machine technology processing for earth resource survey

Science.gov (United States)

Landgrebe, D. A.

1970-01-01

The following technologies are considered for automatic processing of earth resources data: (1) registration of multispectral and multitemporal images, (2) digital image display systems, (3) data system parameter effects on satellite remote sensing systems, and (4) data compression techniques based on spectral redundancy. The importance of proper spectral band and compression algorithm selections is pointed out.

Musical feedback during exercise machine workout enhances mood

Directory of Open Access Journals (Sweden)

Thomas Hans Fritz

2013-12-01

Full Text Available Music making has a number of beneficial effects for motor tasks compared to passive music listening. Given that recent research suggests that high energy musical activities elevate positive affect more strongly than low energy musical activities, we here investigated a recent method that combined music making with systematically increasing physiological arousal by exercise machine workout. We compared mood and anxiety after two exercise conditions on non-cyclical exercise machines, one with passive music listening and the other with musical feedback (where participants could make music with the exercise machines. The results showed that agency during exercise machine workout (an activity we previously labeled jymmin—a cross between jammin and gym had an enhancing effect on mood compared to workout with passive music listening. Furthermore, the order in which the conditions were presented mediated the effect of musical agency for this subscale When participants first listened passively, the difference in mood between the two conditions was greater, suggesting that a stronger increase in hormone levels (e.g. endorphins during the active condition may have caused the observed effect. Given an enhanced mood after training with musical feedback compared to passively listening to the same type of music during workout, the results suggest that exercise machine workout with musical feedback (jymmin makes the act of exercise machine training more desirable.

Comparison of Models Needed for Conceptual Design of Man-Machine Systems in Different Application Domains

DEFF Research Database (Denmark)

Rasmussen, Jens

1986-01-01

and subjective preferences. For design of man-machine systems in process control, a framework has been developed in terms of separate representation of the problem domain, the decision task, and the information processing strategies required. The author analyzes the application of this framework to a number......For systematic and computer-aided design of man-machine systems, a consistent framework is needed, i. e. , a set of models which allows the selection of system characteristics which serve the individual user not only to satisfy his goal, but also to select mental processes that match his resources...

Integration of Openstack cloud resources in BES III computing cluster

Science.gov (United States)

Li, Haibo; Cheng, Yaodong; Huang, Qiulan; Cheng, Zhenjing; Shi, Jingyan

2017-10-01

Cloud computing provides a new technical means for data processing of high energy physics experiment. However, the resource of each queue is fixed and the usage of the resource is static in traditional job management system. In order to make it simple and transparent for physicist to use, we developed a virtual cluster system (vpmanager) to integrate IHEPCloud and different batch systems such as Torque and HTCondor. Vpmanager provides dynamic virtual machines scheduling according to the job queue. The BES III use case results show that resource efficiency is greatly improved.

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.

Improving ATLAS computing resource utilization with HammerCloud

CERN Document Server

Schovancova, Jaroslava; The ATLAS collaboration

2018-01-01

HammerCloud is a framework to commission, test, and benchmark ATLAS computing resources and components of various distributed systems with realistic full-chain experiment workflows. HammerCloud contributes to ATLAS Distributed Computing (ADC) Operations and automation efforts, providing the automated resource exclusion and recovery tools, that help re-focus operational manpower to areas which have yet to be automated, and improve utilization of available computing resources. We present recent evolution of the auto-exclusion/recovery tools: faster inclusion of new resources in testing machinery, machine learning algorithms for anomaly detection, categorized resources as master vs. slave for the purpose of blacklisting, and a tool for auto-exclusion/recovery of resources triggered by Event Service job failures that is being extended to other workflows besides the Event Service. We describe how HammerCloud helped commissioning various concepts and components of distributed systems: simplified configuration of qu...

Scheduling preemptable jobs on identical processors under varying availability of an additional continuous resource

Directory of Open Access Journals (Sweden)

Różycki Rafał

2016-09-01

Full Text Available In this work we consider a problem of scheduling preemptable, independent jobs, characterized by the fact that their processing speeds depend on the amounts of a continuous, renewable resource allocated to jobs at a time. Jobs are scheduled on parallel, identical machines, with the criterion of minimization of the schedule length. Since two categories of resources occur in the problem: discrete (set of machines and continuous, it is generally called a discrete-continuous scheduling problem. The model studied in this paper allows the total available amount of the continuous resource to vary over time, which is a practically important generalization that has not been considered yet for discrete-continuous scheduling problems. For this model we give some properties of optimal schedules on a basis of which we propose a general methodology for solving the considered class of problems. The methodology uses a two-phase approach in which, firstly, an assignment of machines to jobs is defined and, secondly, for this assignment an optimal continuous resource allocation is found by solving an appropriate mathematical programming problem. In the approach various cases are considered, following from assumptions made on the form of the processing speed functions of jobs. For each case an iterative algorithm is designed, leading to an optimal solution in a finite number of steps.

Balancing public health and resource limitations: A role for ethical low-level risk communication

International Nuclear Information System (INIS)

McGinn, R.E.

1991-01-01

Recognition of the pervasiveness of risk in everyday life in modern industrial society has elicited calls for greater efforts to protect individual and public health. Yet, it is increasingly clear that decisions to do so must often be made in the context of significant limits in the amounts of financial resources available for achieving that protection. Achieving risk-free work, residential, and community environments may be so expensive as to render a private business unit uncompetitive or as to divert resources from or prelude commencing with other governmental projects with equal or greater health benefit potential. Ethical low-level risk communication (LLRC) is something risk-generating entities are morally obligated to do. However, such communication also offers important opportunities for such entities to move toward achieving better balances between health and the costs of protecting it. In this paper, the authors elaborate on several features of an ethically ideal LLRC process, focusing on those with aspects they hope are not obvious or common knowledge. In discussing these features, they provide examples of conflicts between health risks and resource limits at the level of the individual private firm, the local community, or the national government, such that LLRC with the feature in question provides an opportunity for mitigating or at least clarifying the conflict in question

Determining optimum levels of DSM [demand-side management] as a supply-side resource

International Nuclear Information System (INIS)

Giles, S.H.; Mitchell, E.D.

1990-01-01

San Diego Gas and Electric Company (SDGE) recommends the evaluation of demand-side management as a supply-side resource. The advantages of concurrent economic analysis of DSM options with other traditional sources represents a significant improvement over analysis either before or after the development of a resource plan. The evaluation of utility-sponsored DSM programs that provide system benefits that include deferment of capacity additions and improvements in more efficient system operation should be evaluated side-by-side with traditional resources that provide similar benefits. The utility decision to either provide capital costs to construct a power plant or make demand payments for a power purchase is directly analogous to the decision to provide funding for a DSM program that would defer these same investments. Both types of decision represent utility control over investment decisions that allow the utility to provide reliable, low-cost power to its customers. SDGE has also had experience with using generation expansion scenarios to test different levels of pre-selected packages of DSM programs, attempting to evaluate the total costs of system expansion for each of the different packages. This method was fraught with problems, and the best information that could be gained was if the selection of DSM packages happened to bracket a lower cost scenario, when it could reasonably be assumed that both smaller and larger levels of DSM were not as cost effective as the intermediate level. However, in many cases the selection of DSM programs did not produce this result and the important question of whether individual DSM programs were worthwhile when evaluated individually, or whether the lowest cost scenario would be improved with more or less DSM, could not be answered

Performance of a Horizontal Triple Cylinder Type Pulping Machine

Directory of Open Access Journals (Sweden)

Sukrisno Widyotomo

2011-05-01

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

Physical education resources, class management, and student physical activity levels: a structure-process-outcome approach to evaluating physical education effectiveness.

Science.gov (United States)

Bevans, Katherine B; Fitzpatrick, Leslie-Anne; Sanchez, Betty M; Riley, Anne W; Forrest, Christopher

2010-12-01

This study was conducted to empirically evaluate specific human, curricular, and material resources that maximize student opportunities for physical activity during physical education (PE) class time. A structure-process-outcome model was proposed to identify the resources that influence the frequency of PE and intensity of physical activity during PE. The proportion of class time devoted to management was evaluated as a potential mediator of the relations between resource availability and student activity levels. Data for this cross-sectional study were collected from interviews conducted with 46 physical educators and the systematic observation of 184 PE sessions in 34 schools. Regression analyses were conducted to test for the main effects of resource availability and the mediating role of class management. Students who attended schools with a low student-to-physical educator ratio had more PE time and engaged in higher levels of physical activity during class time. Access to adequate PE equipment and facilities was positively associated with student activity levels. The availability of a greater number of physical educators per student was found to impact student activity levels by reducing the amount of session time devoted to class management. The identification of structure and process predictors of student activity levels in PE will support the allocation of resources and encourage instructional practices that best support increased student activity levels in the most cost-effective way possible. Implications for PE policies and programs are discussed. © 2010, American School Health Association.

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...

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)

Machining of Metal Matrix Composites

CERN Document Server

2012-01-01

Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

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

Characteristics of laser assisted machining for silicon nitride ceramic according to machining parameters

International Nuclear Information System (INIS)

Kim, Jong Do; Lee, Su Jin; Suh, Jeong

2011-01-01

This paper describes the Laser Assisted Machining (LAM) that cuts and removes softened parts by locally heating the ceramic with laser. Silicon nitride ceramics can be machined with general machining tools as well, because YSiAlON, which was made up ceramics, is soften at about 1,000 .deg. C. In particular, the laser, which concentrates on highly dense energy, can locally heat materials and very effectively control the temperature of the heated part of specimen. Therefore, this paper intends to propose an efficient machining method of ceramic by deducing the machining governing factors of laser assisted machining and understanding its mechanism. While laser power is the machining factor that controls the temperature, the CBN cutting tool could cut the material more easily as the material gets deteriorated from the temperature increase by increasing the laser power, but excessive oxidation can negatively affect the quality of the material surface after machining. As the feed rate and cutting depth increase, the cutting force increases and tool lifespan decreases, but surface oxidation also decreases. In this experiment, the material can be cut to 3 mm of cutting depth. And based on the results of the experiment, the laser assisted machining mechanism is clarified

High-level Programming and Symbolic Reasoning on IoT Resource Constrained Devices

Directory of Open Access Journals (Sweden)

Sal vatore Gaglio

2015-05-01

Full Text Available While the vision of Internet of Things (IoT is rather inspiring, its practical implementation remains challenging. Conventional programming approaches prove unsuitable to provide IoT resource constrained devices with the distributed processing capabilities required to implement intelligent, autonomic, and self-organizing behaviors. In our previous work, we had already proposed an alternative programming methodology for such systems that is characterized by high-level programming and symbolic expressions evaluation, and developed a lightweight middleware to support it. Our approach allows for interactive programming of deployed nodes, and it is based on the simple but e ective paradigm of executable code exchange among nodes. In this paper, we show how our methodology can be used to provide IoT resource constrained devices with reasoning abilities by implementing a Fuzzy Logic symbolic extension on deployed nodes at runtime.

Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

Directory of Open Access Journals (Sweden)

Gatis Špats

2016-07-01

Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

Development of a machine treating removed shells and others in thermal and nuclear power stations

International Nuclear Information System (INIS)

Daiho, Koichi; Iwao, Takenobu

1981-01-01

The living things removed form the cooling water systems in thermal and nuclear power stations, such as shells and jelly fish, have been disposed by burying in the premises, but it is the actual situation that the occurrence of bad smell and the securing of land for burying are the worries. Accordingly, a machine for deodorizing the removed living things was manufactured for trial, and the treatment experiment was carried out in Chita Power Station. This treating machine dries the removed living things around 200 deg C, and makes the deodorizing treatment. The treated products can be utilized effectively as fertilizer, and the prospect to put this machine in practical use as a waste treatment machine of resource re-utilization type was obtained. General Technical Research Institute, Chubu Electric Power Co., Inc., has developed a machine treating abandoned fish for making organic fertilizer, and its principle was applied to the development of this treating machine. The treating capacity of this machine is 1 t/day, and the power consumption is 9.3 kW. The waste oil from power stations of about 15 l/h is used as the fuel. A crusher, a constant feed screw conveyer and a rotary kiln for drying are used. In the treating experiment, about 30 t of shells and others were treated during 51 days. The results are reported. (Kako, I.)

Vibration transmitted to operator’s back by machines with back-pack power unit: a case study on blower and spraying machines

Directory of Open Access Journals (Sweden)

Roberto Deboli

2013-09-01

Full Text Available To correctly evaluate the vibration transmitted to the operators, it is necessary to consider each body’s point interested by the vibratory stimulus produced by machines. All the body’s part in contact to the vibration, when a portable device with internal combustion engine is used, are: hands, back and shoulders. Some information for wholebody vibration are available in the ISO 2631-1997 standard, which otherwise refers to a seated operator. ‘C’ type standards for the vibration analysis exist for some portable machines with an internal combustion engine which is comprehensive in the machine (chainsaw, brush-cutter, blower. If the engine is not inside the machine, but it is on the operator’s back, ‘C’ type standards on vibration measurements are quite incomplete. The IMAMOTER institute of CNR, the DISAFA Department (University of Turin and the Occupational Medicine Department of the University of Catania started some tests to verify the vibration levels transmitted to an operator working with backed engine devices. Two machines have been examined: a blower and a spraying machine. Two operative conditions have been considered during all the tests: idling and full load. Three operators have been involved and each test has been repeated three times. The spraying machine has been tested both with the empty tank and with 10 litres of water, to simulate the load to be caused by the presence of liquid inside the tank. In this work the comfort condition of ISO 2631-1 standard was considered, using the frequency weighting Wc curve with the weighting factor 0.8 for X axis (back-ventral direction and the Wd curve for Y and Z axis (shoulder - shoulder and buttocks - head with weighting factors 0.5 and 0.4 (respectively for Y and Z axis. Data were examined using IBM SPSS Statistics 20 software package. The statistical analysis underlined that the running condition is the main factor to condition the vibration levels transmitted to the operator�

Applicability of Machine-Learning Enabled LIBS in Post Irradiation Nuclear Forensic Analysis of High Level Nuclear Waste

International Nuclear Information System (INIS)

Onkongi, J.; Maina, D.; Angeyo, H. K.

2017-01-01

Nuclear Forensics seeks Information to determine; Chemical Composition, Routes of transit, Origin (Provenance) and Intended use. Post Irradiation/Post detonation NF In a post-detonation event could you get clues/signatures from glass debris, minute sample sizes? Nuclear Forensic Technique Should be State-of -the art that is Rapid, Non-invasive, Remote ability and Non-destructive. Laser Induced Breakdown Spectroscopy (LIBS) unlike other Analytic Techniques that require tedious sample preparations such as Dissolution, digestion & matrix removal, which generate additional nuclear wastes that require proper Procedures for handling, storage & ultimate disposal, LIBS overcomes these limitations. Utility of Machine Learning Techniques employed include; Artificial Neural Networks, ANN (Regression/Modelling), Principal component Analysis, PCA (Classification) and Support Vector Machine SVM (Comparative study/Classification Machine Learning coupled with LIBS gives a state of the art analytic method. Utility of the technic in safeguards security and non-proliferation

Improving the reliability of stator insulation system in rotating machines

International Nuclear Information System (INIS)

Gupta, G.K.; Sedding, H.G.; Culbert, I.M.

1997-01-01

Reliable performance of rotating machines, especially generators and primary heat transport pump motors, is critical to the efficient operation on nuclear stations. A significant number of premature machine failures have been attributed to the stator insulation problems. Ontario Hydro has attempted to assure the long term reliability of the insulation system in critical rotating machines through proper specifications and quality assurance tests for new machines and periodic on-line and off-line diagnostic tests on machines in service. The experience gained over the last twenty years is presented in this paper. Functional specifications have been developed for the insulation system in critical rotating machines based on engineering considerations and our past experience. These specifications include insulation stress, insulation resistance and polarization index, partial discharge levels, dissipation factor and tip up, AC and DC hipot tests. Voltage endurance tests are specified for groundwall insulation system of full size production coils and bars. For machines with multi-turn coils, turn insulation strength for fast fronted surges in specified and verified through tests on all coils in the factory and on samples of finished coils in the laboratory. Periodic on-line and off-line diagnostic tests were performed to assess the condition of the stator insulation system in machines in service. Partial discharges are measured on-line using several techniques to detect any excessive degradation of the insulation system in critical machines. Novel sensors have been developed and installed in several machines to facilitate measurements of partial discharges on operating machines. Several off-line tests are performed either to confirm the problems indicated by the on-line test or to assess the insulation system in machines which cannot be easily tested on-line. Experience with these tests, including their capabilities and limitations, are presented. (author)

A reliability-based preventive maintenance methodology for the projection spot welding machine

Directory of Open Access Journals (Sweden)

Fayzimatov Ulugbek

2018-06-01

Full Text Available An effective operations of a projection spot welding (PSW machine is closely related to the effec-tiveness of the maintenance. Timely maintenance can prevent failures and improve reliability and maintainability of the machine. Therefore, establishing the maintenance frequency for the welding machine is one of the most important tasks for plant engineers. In this regard, reliability analysis of the welding machine can be used to establish preventive maintenance intervals (PMI and to identify the critical parts of the system. In this reliability and maintainability study, analysis of the PSW machine was carried out. The failure and repair data for analysis were obtained from automobile manufacturing company located in Uzbekistan. The machine was divided into three main sub-systems: electrical, pneumatic and hydraulic. Different distributions functions for all sub-systems was tested and their parameters tabulated. Based on estimated parameters of the analyzed distribu-tions, PMI for the PSW machines sub-systems at different reliability levels was calculated. Finally, preventive measures for enhancing the reliability of the PSW machine sub-systems are suggested.

Quantum Virtual Machine (QVM)

Energy Technology Data Exchange (ETDEWEB)

2016-11-18

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

Process capability improvement through DMAIC for aluminum alloy wheel machining

Science.gov (United States)

Sharma, G. V. S. S.; Rao, P. Srinivasa; Babu, B. Surendra

2017-07-01

This paper first enlists the generic problems of alloy wheel machining and subsequently details on the process improvement of the identified critical-to-quality machining characteristic of A356 aluminum alloy wheel machining process. The causal factors are traced using the Ishikawa diagram and prioritization of corrective actions is done through process failure modes and effects analysis. Process monitoring charts are employed for improving the process capability index of the process, at the industrial benchmark of four sigma level, which is equal to the value of 1.33. The procedure adopted for improving the process capability levels is the define-measure-analyze-improve-control (DMAIC) approach. By following the DMAIC approach, the C p, C pk and C pm showed signs of improvement from an initial value of 0.66, -0.24 and 0.27, to a final value of 4.19, 3.24 and 1.41, respectively.

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

Directory of Open Access Journals (Sweden)

Shyamala Loganathan

2015-01-01

Full Text Available Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

DEFF Research Database (Denmark)

Sousa, Tiago; Morais, Hugo; Vale, Zita

2015-01-01

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power...... at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power...... scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present...

Which Management Control System principles and aspects are relevant when deploying a learning machine?

OpenAIRE

Martin, Johansson; Mikael, Göthager

2017-01-01

How shall a business adapt its management control systems when learning machines enter the arena? Will the control system continue to focus on humans aspects and continue to consider a learning machine to be an automation tool as any other historically programmed computer? Learning machines introduces productivity capabilities that achieve very high levels of efficiency and quality. A learning machine can sort through large amounts of data and make conclusions difficult by a human mind. Howev...

VIRTUAL MACHINES IN EDUCATION – CNC MILLING MACHINE WITH SINUMERIK 840D CONTROL SYSTEM

Directory of Open Access Journals (Sweden)

Ireneusz Zagórski

2014-11-01

Full Text Available Machining process nowadays could not be conducted without its inseparable element: cutting edge and frequently numerically controlled milling machines. Milling and lathe machining centres comprise standard equipment in many companies of the machinery industry, e.g. automotive or aircraft. It is for that reason that tertiary education should account for this rising demand. This entails the introduction into the curricula the forms which enable visualisation of machining, milling process and virtual production as well as virtual machining centres simulation. Siemens Virtual Machine (Virtual Workshop sets an example of such software, whose high functionality offers a range of learning experience, such as: learning the design of machine tools, their configuration, basic operation functions as well as basics of CNC.

Interactive Whiteboards and Computer Games at Highschool Level: Digital Resources for Enhancing Reflection in Teaching and Learning

DEFF Research Database (Denmark)

Sorensen, Elsebeth Korsgaard; Poulsen, Mathias; Houmann, Rita

The general potential of computer games for teaching and learning is becoming widely recognized. In particular, within the application contexts of primary and lower secondary education, the relevance and value and computer games seem more accepted, and the possibility and willingness to incorporate...... computer games as a possible resource at the level of other educational resources seem more frequent. For some reason, however, to apply computer games in processes of teaching and learning at the high school level, seems an almost non-existent event. This paper reports on study of incorporating...... the learning game “Global Conflicts: Latin America” as a resource into the teaching and learning of a course involving the two subjects “English language learning” and “Social studies” at the final year in a Danish high school. The study adapts an explorative research design approach and investigates...

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

Science.gov (United States)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

Modernity Evaluation of the Machines Used During Production Process of Metal Products

OpenAIRE

Ingaldi, Manuela; Dziuba, Szymon T.

2015-01-01

Most manufacturing companies realize its technologies, implemented through concrete machinery parts. They differ in terms of importance, the relevance of their selection and the level of their modernity. Modernity and efficiency of the machine are also very important during production process of the metal products. They have an influence on the quality of these products. The purpose of this article is to analyse the chosen production machine (CNC machine AFE-3D8-T) used during pro...

CFCC: A Covert Flows Confinement Mechanism for Virtual Machine Coalitions

Science.gov (United States)

Cheng, Ge; Jin, Hai; Zou, Deqing; Shi, Lei; Ohoussou, Alex K.

Normally, virtualization technology is adopted to construct the infrastructure of cloud computing environment. Resources are managed and organized dynamically through virtual machine (VM) coalitions in accordance with the requirements of applications. Enforcing mandatory access control (MAC) on the VM coalitions will greatly improve the security of VM-based cloud computing. However, the existing MAC models lack the mechanism to confine the covert flows and are hard to eliminate the convert channels. In this paper, we propose a covert flows confinement mechanism for virtual machine coalitions (CFCC), which introduces dynamic conflicts of interest based on the activity history of VMs, each of which is attached with a label. The proposed mechanism can be used to confine the covert flows between VMs in different coalitions. We implement a prototype system, evaluate its performance, and show that our mechanism is practical.

Ultrasonic fluid quantity measurement in dynamic vehicular applications a support vector machine approach

CERN Document Server

Terzic, Jenny; Nagarajah, Romesh; Alamgir, Muhammad

2013-01-01

Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ν-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels...

The free-piston Vuilleumier machine: a new refrigerating sink from heat loss recovery?; La machine de Vuilleumier a pistons libres: une nouvelle source de froid par recuperation?

Energy Technology Data Exchange (ETDEWEB)

Rochelle, P. [Laboratoire de Mecanique Physique, UP6, 78 - Saint Cyr l' Ecole (France); Rochelle, P.; Grosu, L. [Laboratoire d' Energetique et d' Economie de l' Energie, UP10, 92 - Ville d' Avray (France)

2002-07-01

The Vuilleumier machine combines two Stirling cycles: a prime mover and a refrigerating cycle. lt could produce cold and heat at low temperature levels from heat loss recovered at the exhaust of heat generating processes (industrial transforming processes, thermal engines,...). Here, these regenerating dual cycle machines and their potential applications, particularly those concerning transportation vehicles, are examined. Towards this purpose, the Vuilleumier machine principles are briefly described along with a more in-depth look at the free-piston configuration type. In principle, these machines are simple to build, but specific starting and continuous running conditions must be met, and here they are established. Then, we discuss the applicability of these systems to vehicles, and the usable geometrical configurations are shortly examined with, as an application, the pre-design calculus of a 'pancake' machine. (authors)

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

CERN Document Server

Misic, Vojislav B

2014-01-01

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

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

Ultraprecision machining. Cho seimitsu kako

Energy Technology Data Exchange (ETDEWEB)

Suga, T [The Univ. of Tokyo, Tokyo (Japan). Research Center for Advanced Science and Technology

1992-10-05

It is said that the image of ultraprecision improved from 0.1[mu]m to 0.01[mu]m within recent years. Ultraprecision machining is a production technology which forms what is called nanotechnology with ultraprecision measuring and ultraprecision control. Accuracy means average machined sizes close to a required value, namely the deflection errors are small; precision means the scattered errors of machined sizes agree very closely. The errors of machining are related to both of the above errors and ultraprecision means the combined errors are very small. In the present ultraprecision machining, the relative precision to the size of a machined object is said to be in the order of 10[sup -6]. The flatness of silicon wafers is usually less than 0.5[mu]m. It is the fact that the appearance of atomic scale machining is awaited as the limit of ultraprecision machining. The machining of removing and adding atomic units using scanning probe microscopes are expected to reach the limit actually. 2 refs.

Using GPS to evaluate productivity and performance of forest machine systems

Science.gov (United States)

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

2001-01-01

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

EVALUATION OF THE MACHINE MODERNITY IN THE MOTOR INDUSTRY

OpenAIRE

Manuela Krystyna Ingaldi

2014-01-01

Most manufacturing companies realize its technologies, implemented through concrete machinery parts. They differ in terms of importance, the relevance of their selection and the level of their modernity. The purpose of this article is to analyse the chosen production machine in terms of its modernity. The ABC technology method was chosen do this research. All parts of the machine were divided into three groups: parts of main subassembly A, parts of supportive subassembly B, parts of collatera...

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...

User and Machine Authentication and Authorization Infrastructure for Distributed Wireless Sensor Network Testbeds

Directory of Open Access Journals (Sweden)

Gerald Wagenknecht

2013-03-01

Full Text Available The intention of an authentication and authorization infrastructure (AAI is to simplify and unify access to different web resources. With a single login, a user can access web applications at multiple organizations. The Shibboleth authentication and authorization infrastructure is a standards-based, open source software package for web single sign-on (SSO across or within organizational boundaries. It allows service providers to make fine-grained authorization decisions for individual access of protected online resources. The Shibboleth system is a widely used AAI, but only supports protection of browser-based web resources. We have implemented a Shibboleth AAI extension to protect web services using Simple Object Access Protocol (SOAP. Besides user authentication for browser-based web resources, this extension also provides user and machine authentication for web service-based resources. Although implemented for a Shibboleth AAI, the architecture can be easily adapted to other AAIs.

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.

"Sub-Surf Rocks"! An A-Level Resource Developed through an Industry-Education Collaboration

Science.gov (United States)

Mather, Hazel

2012-01-01

A free internet resource called "Sub-Surf Rocks"! was launched in 2010. Its aim is to use seismic data obtained by the oil industry for enhancing the teaching of structural and economic geology at A-level (ages 16-18) in the UK. Seismic data gives a unique insight into the sub-surface and the many high-quality images coupled with…

TECHNICAL EFFICIENCY OF AGRICULTURAL RESOURCES USE IN RUSSIA

Directory of Open Access Journals (Sweden)

V. M. Korotchenya

2016-01-01

Full Text Available Technical efficiency of agricultural resources use in Russia is assessed. As methodology for calculations the author used Data envelopment analysis (DEA which is the nonparametric method based on linear programming. The essence of the DEA method consists in an efficiency evaluation of homogeneous units of decision making proceeding from creation on the basis of real data (amounts of resources and amounts of types of output of general border of production capabilities. CCR-I model was offerd as a specific kind of the DEA model. It is the radial DEA model with continual returns to scale and orientation to resources. The group of 54 countries included in a research consisted of the states of the CIS, BRIC, the EU, OECD. The time frames of calculation were established: 1992-2007 and 2008-2012 (owing to lack of uniform data for all time interval. Аmount of agricultural products was used as output. Agricultural lands, an economically active population in agriculture, farm machines and the equipment, a livestock, fertilizers were used in the form of resources. The main source of statistical data is FAOSTAT. From 54 countries under consideration Belgium, Greece, Israel, Malta and the Netherlands became leaders in technical efficiency of agricultural industry in 1992-2007. Inefficient use of agricultural resources, especially lands was established as a result of the conducted research in Russia. On average efficiency of use of agricultural lands in our country can be increased by 8 times, work - by 2-2.5 times, machines - by 2-3 times, a livestock and fertilizers - by 1.5-2 times. Good tendencies to growth of efficiency of agricultural production are notice in 2008-2012.

Two Approaches for the Management of Virtual Machines on Grid Infrastructures

International Nuclear Information System (INIS)

Tapiador, D.; Rubio-Montero, A. J.; Juedo, E.; Montero, R. S.; Llorente, I. M.

2007-01-01

Virtual machines are a promising technology to overcome some of the problems found in current Grid infrastructures, like heterogeneity, performance partitioning or application isolation. This work shows a comparison between two strategies to manage virtual machines in Globus Grids. The first alternative is a straightforward deployment that does not require additional middle ware to be installed. It is only based on standard Grid services and is not bound to a given virtualization technology. Although this option is fully functional, it is only suitable for single process batch jobs. The second solution makes use of the Virtual Workspace Service which allows a remote client to securely negotiate and manage a virtual resource. This approach better exploits the potential benefits offered by the virtualization technology and provides a wider application range. (Author)

Tattoo machines, needles and utilities.

Science.gov (United States)

Rosenkilde, Frank

2015-01-01

Starting out as a professional tattooist back in 1977 in Copenhagen, Denmark, Frank Rosenkilde has personally experienced the remarkable development of tattoo machines, needles and utilities: all the way from home-made equipment to industrial products of substantially improved quality. Machines can be constructed like the traditional dual-coil and single-coil machines or can be e-coil, rotary and hybrid machines, with the more convenient and precise rotary machines being the recent trend. This development has resulted in disposable needles and utilities. Newer machines are more easily kept clean and protected with foil to prevent crosscontaminations and infections. The machines and the tattooists' knowledge and awareness about prevention of infection have developed hand-in-hand. For decades, Frank Rosenkilde has been collecting tattoo machines. Part of his collection is presented here, supplemented by his personal notes. © 2015 S. Karger AG, Basel.

Design of rotating electrical machines

CERN Document Server

Pyrhonen , Juha; Hrabovcova , Valeria

2013-01-01

In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

Learning Machine Learning: A Case Study

Science.gov (United States)

Lavesson, N.

2010-01-01

This correspondence reports on a case study conducted in the Master's-level Machine Learning (ML) course at Blekinge Institute of Technology, Sweden. The students participated in a self-assessment test and a diagnostic test of prerequisite subjects, and their results on these tests are correlated with their achievement of the course's learning…

Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

Science.gov (United States)

Pan, Ian; Nolan, Laura B; Brown, Rashida R; Khan, Romana; van der Boor, Paul; Harris, Daniel G; Ghani, Rayid

2017-06-01

To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based risk assessment. We compared different models and determined the strongest predictors of adverse birth outcomes using positive predictive value as the metric for selection. Machine learning algorithms performed similarly, outperforming the current paper-based risk assessment by up to 36%; a refined paper-based assessment outperformed the current assessment by up to 22%. We estimate that these improvements will allow 100 to 170 additional high-risk pregnant women screened for program eligibility each year to receive services that would have otherwise been unobtainable. Our analysis exhibits the potential for machine learning to move government agencies toward a more data-informed approach to evaluating risk and providing social services. Overall, such efforts will improve the efficiency of allocating resource-intensive interventions.

A review of machine learning in obesity.

Science.gov (United States)

DeGregory, K W; Kuiper, P; DeSilvio, T; Pleuss, J D; Miller, R; Roginski, J W; Fisher, C B; Harness, D; Viswanath, S; Heymsfield, S B; Dungan, I; Thomas, D M

2018-05-01

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning provides sophisticated and elegant tools to describe, classify and predict obesity-related risks and outcomes. Here, we review machine learning methods that predict and/or classify such as linear and logistic regression, artificial neural networks, deep learning and decision tree analysis. We also review methods that describe and characterize data such as cluster analysis, principal component analysis, network science and topological data analysis. We introduce each method with a high-level overview followed by examples of successful applications. The algorithms were then applied to National Health and Nutrition Examination Survey to demonstrate methodology, utility and outcomes. The strengths and limitations of each method were also evaluated. This summary of machine learning algorithms provides a unique overview of the state of data analysis applied specifically to obesity. © 2018 World Obesity Federation.

Hydraulic stud-tensioning machines in reactor technology

International Nuclear Information System (INIS)

Lachner, H.

1978-01-01

Hydraulic multiple stud tensioner (MST) for the simultaneous prestressing of all the stud bolts is make it possible to achieve highly accurate prestress levels in the highly stressed bolts holding down the top head of reactor pressure vessels. These machines can remove and replace the nuts and studs, and can rotate these components upwards and downwards, during the operation of opening and closing the reactor pressure vessel. In order to reduce the radiation exposure of the service personnel, and also to reduce the time required for this work which may lie in the critical path of the refuelling time schedule, it is desirable to achieve complete mechanisation of these machines, including remote control and remote monitoring. The devices and components required for this purpose are without precedent in machine construction with respect to their functions and to the load range involved. The reported operating experience therefore also covers some points of general interest while the data on maintenance reflect the known status of the technology. (orig.) [de

Cutting Zone Temperature Identification During Machining of Nickel Alloy Inconel 718

Science.gov (United States)

Czán, Andrej; Daniš, Igor; Holubják, Jozef; Zaušková, Lucia; Czánová, Tatiana; Mikloš, Matej; Martikáň, Pavol

2017-12-01

Quality of machined surface is affected by quality of cutting process. There are many parameters, which influence on the quality of the cutting process. The cutting temperature is one of most important parameters that influence the tool life and the quality of machined surfaces. Its identification and determination is key objective in specialized machining processes such as dry machining of hard-to-machine materials. It is well known that maximum temperature is obtained in the tool rake face at the vicinity of the cutting edge. A moderate level of cutting edge temperature and a low thermal shock reduce the tool wear phenomena, and a low temperature gradient in the machined sublayer reduces the risk of high tensile residual stresses. The thermocouple method was used to measure the temperature directly in the cutting zone. An original thermocouple was specially developed for measuring of temperature in the cutting zone, surface and subsurface layers of machined surface. This paper deals with identification of temperature and temperature gradient during dry peripheral milling of Inconel 718. The measurements were used to identification the temperature gradients and to reconstruct the thermal distribution in cutting zone with various cutting conditions.

VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

Directory of Open Access Journals (Sweden)

POPESCU Adrian

2015-11-01

Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

Findings From the National Machine Guarding Program–A Small Business Intervention

Science.gov (United States)

Parker, David L.; Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives: The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Methods: Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. Results: The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P < 0.0001) and a 33% point increase in LOTO program scores (P < 0.0001). Conclusions: Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:27466709

Research of influence of technological parameters on the noise characteristics of the machine for grinding meat

Directory of Open Access Journals (Sweden)

A. K. Pil’nenko

2016-01-01

Full Text Available Noise characteristics (NC machine is one of the main indicators of its quality and competitiveness on the world markets. Scientific and technical work to improve the noise characteristics are relevant and modern. Work focuses on the study of the emergence of the technological equipment of acoustic phenomena. Was selected method of determination and equipment, according to the international standards ISO “Acoustics” taking into account the acoustic properties of the surrounding space. Been established NC machines for grinding meat and fish under operating conditions the in various modes. The maximum value for the characteristic A sound power level (SPL machines produced at idling 79,7 dBA. When the machine comes with the product decline USM on the characteristics A 7.3 dB. It was found exceeding the maximum allowable sound power level at medium frequencies on 2 dB. Impact the components of machines on its NC depending on variables technological factors - the module of elasticity of the product and the effort on the pushrod. Increase modulus of elasticity SPL machines decreases and increase efforts on the pusher Machines USM increases. It was found negative impact construction machines part sat USM. Should be increased rigidity design of the machine.

Calculation of Airborne Radioactivity Hazard from Machining Volume-Activated Materials

International Nuclear Information System (INIS)

E.T. Marshall; S.O. Schwahn

1997-01-01

When evaluating a task involving the machining of volume-activated materials, accelerator health physicists must consider more than the surface contamination levels of the equipment and containment of loose shavings, dust or filings. Machining operations such as sawing, routing, welding, and grinding conducted on volume-activated material may pose a significant airborne radioactivity hazard to the worker. This paper presents a computer spreadsheet notebook that conservatively estimates the airborne radioactivity levels generated during machining operations performed on volume-activated materials. By knowing (1) the size and type of materials, (2) the dose rate at a given distances, and (3) limited process knowledge, the Derived Air Concentration (DAC) fraction can be estimated. This tool is flexible, taking into consideration that the process knowledge available for the different materials varies. It addresses the two most common geometries: thick plane and circular cylinder. Once the DAC fraction has been estimated, controls can be implemented to mitigate the hazard to the worker

Calculation of airborne radioactivity hazard from machining volume-activated materials

International Nuclear Information System (INIS)

Marshall, E.T.; Schwahn, S.O.

1996-10-01

When evaluating a task involving the machining of volume-activated materials, accelerator health physicists must consider more than the surface contamination levels of the equipment and containment of loose shavings, dust or filings. Machining operations such as sawing, routing, welding, and grinding conducted on volume-activated material may pose a significant airborne radioactivity hazard to the worker. This paper presents a computer spreadsheet notebook that conservatively estimates the airborne radioactivity levels generated during machining operations performed on volume-activated materials. By knowing (1) the size and type of materials, (2) the dose rate at a given distances, and (3) limited process knowledge, the Derived Air Concentration (DAC) fraction can be estimated. This tool is flexible, taking into consideration that the process knowledge available for the different materials varies. It addresses the two most common geometries: thick plane and circular cylinder. Once the DAC fraction has been estimated, controls can be implemented to mitigate the hazard to the worker

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

MAESTRO -- A Model and Expert System Tuning Resource for Operators

International Nuclear Information System (INIS)

Lager, D.L.; Brand, H.R.; Maurer, W.J.; Coffield, F.E.; Chambers, F.

1989-01-01

We have developed MAESTRO, a Model And Expert System Tuning Resource for Operators. It provides a unified software environment for optimizing the performance of large, complex machines, in particular the Advanced Test Accelerator and Experimental Test Accelerator at Lawrence Livermore National Laboratory. The system incorporates three approaches to tuning: a mouse-based manual interface to select and control magnets and to view displays of machine performance; an automation based on ''cloning the operator'' by implementing the strategies and reasoning used by the operator; an automation based on a simulator model which, when accurately matched to the machine, allows downloading of optimal sets of parameters and permits diagnosing errors in the beamline. The latter two approaches are based on the Artificial Intelligence technique known as Expert Systems. 4 refs., 4 figs

MAESTRO - a model and expert system tuning resource for operators

International Nuclear Information System (INIS)

Lager, D.L.; Brand, H.R.; Maurer, W.J.; Coffield, F.; Chambers, F.

1990-01-01

We have developed MAESTRO, a model and expert system tuning resource for operators. It provides a unified software environment for optimizing the performance of large, complex machines, in particular the Advanced Test Accelerator and Experimental Test Accelerator at Lawrence Livermore National Laboratory. The system incorporates three approaches to tuning: a mouse-based manual interface to select and control magnets and to view displays of machine performance; an automation based on 'cloning the operator' by implementing the strategies and reasoning used by the operator; and an automation based on a simulator model which, when accurately matched to the machine, allows downloading of optimal sets of parameters and permits diagnosing errors in the beam line. The latter two approaches are based on the artificial-intelligence technique known as Expert Systems. (orig.)

Coordinate measuring machines

DEFF Research Database (Denmark)

De Chiffre, Leonardo

This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...... and uncertainty during coordinate measurements, 3) Digitalisation and Reverse Engineering. This document contains a short description of each step in the exercise and schemes with room for taking notes of the results.......This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceability...

Rational use of cognitive resources: levels of analysis between the computational and the algorithmic.

Science.gov (United States)

Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D

2015-04-01

Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis." Copyright © 2015 Cognitive Science Society, Inc.

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.

Performance of quantum cloning and deleting machines over coherence

Science.gov (United States)

Karmakar, Sumana; Sen, Ajoy; Sarkar, Debasis

2017-10-01

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

Using Machine Learning for Risky Module Estimation of Safety-Critical Software

International Nuclear Information System (INIS)

Kim, Young Mi; Jeong, Choong Heui

2009-01-01

With the rapid development of digital computer and information processing technologies, nuclear I and C (Instrument and Control) system which needs safety critical function has adopted digital technologies. Software used in safety-critical system must have high dependability. Highly dependable software needs strict software testing and V and V activities. These days, regulatory demands for nuclear power plants are more and more increasing. But, human resources and time for regulation are limited. So, early software risky module prediction is very useful for software testing and regulation activities. Early estimation can be built from a collection of internal metrics during early development phase. Internal metrics are measures of a product derived from assessment of the product itself, and external metrics are measures of a product derived from assessment of the behavior of the systems. Internal metrics can be collected more easily and early than external metrics. In addition, internal metrics can be useful for estimating fault-prone software modules using machine learning. In this paper, we introduce current research status and techniques related to estimating risky software module using machine learning techniques. Section 2 describes the overview of the estimation model using machine learning and section 3 describes processes of the estimation model. Section 4 describes several estimation models using machine leanings. Section 5 concludes the paper

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

Tribology in machine design

CERN Document Server

Stolarski, Tadeusz

1999-01-01

""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

Directory of Open Access Journals (Sweden)

Woong-Kirl Choi

2018-01-01

Full Text Available Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks.

A Universal Reactive Machine

DEFF Research Database (Denmark)

Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

1997-01-01

Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...

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.

Virtual Machine in Automation Projects

OpenAIRE

Xing, Xiaoyuan

2010-01-01

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

New Balancing Equipment for Mass Production of Small and Medium-Sized Electrical Machines

DEFF Research Database (Denmark)

Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika

2010-01-01

The level of vibration and noise is an important feature. It is good practice to explain the significance of the indicators of the quality of electrical machines. The mass production of small and medium-sized electrical machines demands speed (short typical measurement time), reliability...

The reduction methods of operator's radiation dose for portable dental X-ray machines.

Science.gov (United States)

Cho, Jeong-Yeon; Han, Won-Jeong

2012-08-01

This study was aimed to investigate the methods to reduce operator's radiation dose when taking intraoral radiographs with portable dental X-ray machines. Two kinds of portable dental X-ray machines (DX3000, Dexcowin and Rextar, Posdion) were used. Operator's radiation dose was measured with an 1,800 cc ionization chamber (RadCal Corp.) at the hand level of X-ray tubehead and at the operator's chest and waist levels with and without the backscatter shield. The operator's radiation dose at the hand level was measured with and without lead gloves and with long and short cones. The backscatter shield reduced operator's radiation dose at the hand level of X-ray tubehead to 23 - 32%, the lead gloves to 26 - 31%, and long cone to 48 - 52%. And the backscatter shield reduced operator's radiation dose at the operator's chest and waist levels to 0.1 - 37%. When portable dental X-ray systems are used, it is recommended to select X-ray machine attached with a backscatter shield and a long cone and to wear the lead gloves.

The Buttonhole Machine. Module 13.

Science.gov (United States)

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

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

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

Science.gov (United States)

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Introduction to machine learning.

Science.gov (United States)

Baştanlar, Yalin; Ozuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

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.

A heuristic for the inventory management of smart vending machine systems

Directory of Open Access Journals (Sweden)

Yang-Byung Park

2012-12-01

Full Text Available Purpose: The purpose of this paper is to propose a heuristic for the inventory management of smart vending machine systems with product substitution under the replenishment point, order-up-to level policy and to evaluate its performance.Design/methodology/approach: The heuristic is developed on the basis of the decoupled approach. An integer linear mathematical model is built to determine the number of product storage compartments and replenishment threshold for each smart vending machine in the system and the Clarke and Wright’s savings algorithm is applied to route vehicles for inventory replenishments of smart vending machines that share the same delivery days. Computational experiments are conducted on several small-size test problems to compare the proposed heuristic with the integrated optimization mathematical model with respect to system profit. Furthermore, a sensitivity analysis is carried out on a medium-size test problem to evaluate the effect of the customer service level on system profit using a computer simulation.Findings: The results show that the proposed heuristic yielded pretty good solutions with 5.7% error rate on average compared to the optimal solutions. The proposed heuristic took about 3 CPU minutes on average in the test problems being consisted of 10 five-product smart vending machines. It was confirmed that the system profit is significantly affected by the customer service level.Originality/value: The inventory management of smart vending machine systems is newly treated. Product substitutions are explicitly considered in the model. The proposed heuristic is effective as well as efficient. It can be easily modified for application to various retail vending settings under a vendor-managed inventory scheme with POS system.

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.

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

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.

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.

ML Confidential : machine learning on encrypted data

NARCIS (Netherlands)

Graepel, T.; Lauter, K.; Naehrig, M.; Kwon, T.; Lee, M.-K.; Kwon, D.

2013-01-01

We demonstrate that, by using a recently proposed leveled homomorphic encryption scheme, it is possible to delegate the execution of a machine learning algorithm to a computing service while retaining con¿dentiality of the training and test data. Since the computational complexity of the homomorphic

Dictionary of machine terms

International Nuclear Information System (INIS)

1990-06-01

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

HTS machine laboratory prototype

DEFF Research Database (Denmark)

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

Architecture Without Explicit Locks for Logic Simulation on SIMD Machines

OpenAIRE

Cockshott, W. Paul; Chimeh, Mozhgan Kabiri

2016-01-01

The presentation describes an architecture for logic simulation that takes advantages of the features of multi-core SIMD architectures. It uses neither explicit locks nor queues, using instead oblivious simulation. Data structures are targeted to efficient SIMD and multi-core cache operation. We demonstrate high levels of parallelisation on Xeon Phi and AMD multi-core machines. Performance on a Xeon Phi is comparable to or better than on a 1000 core Blue Gene machine.

An analysis of switching and non-switching slot machine player behaviour.

Science.gov (United States)

Coates, Ewan; Blaszczynski, Alex

2013-12-01

Learning theory predicts that, given the repeated choice to bet between two concurrently available slot machines, gamblers will learn to bet more money on the machine with higher expected return (payback percentage) or higher win probability per spin (volatility). The purpose of this study was to investigate whether this occurs when the two machines vary orthogonally on payback percentage and volatility. The sample comprised 52 first year psychology students (mean age = 20.3 years, 20 females, 32 males) who had played a gaming machine at least once in the previous 12 months. Participants were administered a battery of questionnaires designed to assess level of knowledge on the characteristics and operation of poker machines, frequency of poker machine play in the past 12 months, personality traits of impulsivity and capacity for cognitive reflection, and gambling beliefs. For the experimental task, participants were instructed to play on two PC-simulated electronic gaming machines (EGMs or slot machines) that differed on payback percentage and volatility, with the option of freely switching between EGMs after a practice phase. Results indicated that participants were able to easily discriminate between machines and manifested a preference to play machines offering higher payback or volatility. These findings diverged from previous findings of no preference for play on higher payback/volatility machines, potentially due to of the current study's absence of the option to make multi-line and multi-credit bets. It was concluded that return rate parameters like payback percentage and volatility strongly influenced slot machine preference in the absence of betting options like multi-line bets, though more research is needed to determine the effects of such betting options on player distribution of money between multiple EGMs.

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

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

2011-01-01

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

A critical survey of live virtual machine migration techniques

Directory of Open Access Journals (Sweden)

Anita Choudhary

2017-11-01

Full Text Available Abstract Virtualization techniques effectively handle the growing demand for computing, storage, and communication resources in large-scale Cloud Data Centers (CDC. It helps to achieve different resource management objectives like load balancing, online system maintenance, proactive fault tolerance, power management, and resource sharing through Virtual Machine (VM migration. VM migration is a resource-intensive procedure as VM’s continuously demand appropriate CPU cycles, cache memory, memory capacity, and communication bandwidth. Therefore, this process degrades the performance of running applications and adversely affects efficiency of the data centers, particularly when Service Level Agreements (SLA and critical business objectives are to be met. Live VM migration is frequently used because it allows the availability of application service, while migration is performed. In this paper, we make an exhaustive survey of the literature on live VM migration and analyze the various proposed mechanisms. We first classify the types of Live VM migration (single, multiple and hybrid. Next, we categorize VM migration techniques based on duplication mechanisms (replication, de-duplication, redundancy, and compression and awareness of context (dependency, soft page, dirty page, and page fault and evaluate the various Live VM migration techniques. We discuss various performance metrics like application service downtime, total migration time and amount of data transferred. CPU, memory and storage data is transferred during the process of VM migration and we identify the category of data that needs to be transferred in each case. We present a brief discussion on security threats in live VM migration and categories them in three different classes (control plane, data plane, and migration module. We also explain the security requirements and existing solutions to mitigate possible attacks. Specific gaps are identified and the research challenges in improving

Frameworks to monitor and predict resource usage in the ATLAS High Level Trigger

CERN Document Server

Martin, Tim; The ATLAS collaboration

2016-01-01

The ATLAS High Level Trigger Farm consists of around 30,000 CPU cores which filter events at up to 100 kHz input rate. A costing framework is built into the high level trigger, this enables detailed monitoring of the system and allows for data-driven predictions to be made utilising specialist datasets. This talk will present an overview of how ATLAS collects in-situ monitoring data on both CPU usage and dataflow over the data-acquisition network during the trigger execution, and how these data are processed to yield both low level monitoring of individual selection-algorithms and high level data on the overall performance of the farm. For development and prediction purposes, ATLAS uses a special `Enhanced Bias' event selection. This mechanism will be explained along with how is used to profile expected resource usage and output event-rate of new physics selections, before they are executed on the actual high level trigger farm.

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

OpenAIRE

Parker, David L.; Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardize...

Machine vision systems using machine learning for industrial product inspection

Science.gov (United States)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Machine Directional Register System Modeling for Shaft-Less Drive Gravure Printing Machines

Directory of Open Access Journals (Sweden)

Shanhui Liu

2013-01-01

Full Text Available In the latest type of gravure printing machines referred to as the shaft-less drive system, each gravure printing roller is driven by an individual servo motor, and all motors are electrically synchronized. The register error is regulated by a speed difference between the adjacent printing rollers. In order to improve the control accuracy of register system, an accurate mathematical model of the register system should be investigated for the latest machines. Therefore, the mathematical model of the machine directional register (MDR system is studied for the multicolor gravure printing machines in this paper. According to the definition of the MDR error, the model is derived, and then it is validated by the numerical simulation and experiments carried out in the experimental setup of the four-color gravure printing machines. The results show that the established MDR system model is accurate and reliable.

Design and Construction of Wireless Control System for Drilling Machine

Directory of Open Access Journals (Sweden)

Nang Su Moan Hsam

2015-06-01

Full Text Available Abstract Drilling machine is used for boring holes in various materials and used in woodworking metalworking construction and do-it-yourself projects. When the machine operate for a long time the temperature increases and so we need to control the temperature of the machine and some lubrication system need to apply to reduce the temperature. Due to the improvement of technology the system can be controlled with wireless network. This control system use Window Communication Foundation WCF which is the latest service oriented technology to control all drilling machines in industries simultaneously. All drilling machines are start working when they received command from server. After the machine is running for a long time the temperature is gradually increased. This system used LM35 temperature sensor to measure the temperature. When the temperature is over the safely level that is programmed in host server the controller at the server will command to control the speed of motor and applying some lubrication system at the tip and edges of drill. The command from the server is received by the client and sends to PIC. In this control system PIC microcontroller is used as an interface between the client computer and the machine. The speed of motor is controlled with PWM and water pump system is used for lubrication. This control system is designed and simulated with 12V DC motor LM35 sensor LCD displayand relay which is to open the water container to spray water between drill and work piece. The host server choosing to control the drilling machine that are overheat by selecting the clients IP address that is connected with that machine.

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.

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

Directory of Open Access Journals (Sweden)

Xiwei Huang

2016-11-01

Full Text Available A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT. However, such a system has limited resolution, making it imperative to improve resolution from the system-level using super-resolution (SR processing. Yet, how to improve resolution towards better cell detection and recognition with low cost of processing resources and without degrading system throughput is still a challenge. In this article, two machine learning based single-frame SR processing types are proposed and compared for lensless blood cell counting, namely the Extreme Learning Machine based SR (ELMSR and Convolutional Neural Network based SR (CNNSR. Moreover, lensless blood cell counting prototypes using commercial CMOS image sensors and custom designed backside-illuminated CMOS image sensors are demonstrated with ELMSR and CNNSR. When one captured low-resolution lensless cell image is input, an improved high-resolution cell image will be output. The experimental results show that the cell resolution is improved by 4×, and CNNSR has 9.5% improvement over the ELMSR on resolution enhancing performance. The cell counting results also match well with a commercial flow cytometer. Such ELMSR and CNNSR therefore have the potential for efficient resolution improvement in lensless blood cell counting systems towards POCT applications.

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.

The Knife Machine. Module 15.

Science.gov (United States)

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

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

MACHINE-TRANSFORMER UNITS FOR WIND TURBINES

Directory of Open Access Journals (Sweden)

V.I. Panchenko

2016-03-01

Full Text Available Background. Electric generators of wind turbines must meet the following requirements: they must be multi-pole; to have a minimum size and weight; to be non-contact, but controlled; to ensure the maximum possible output voltage when working on the power supply system. Multipole and contactless are relatively simply realized in the synchronous generator with permanent magnet excitation and synchronous inductor generator with electromagnetic excitation; moreover the first one has a disadvantage that there is no possibility to control the output voltage, and the second one has a low magnetic leakage coefficient with the appropriate consequences. Purpose. To compare machine dimensions and weight of the transformer unit with induction generators and is an opportunity to prove their application for systems with low RMS-growth rotation. Methodology. A new design of the electric inductor machine called in technical literature as machine-transformer unit (MTU is presented. A ratio for estimated capacity determination of such units is obtained. Results. In a specific example it is shown that estimated power of MTU may exceed the same one for traditional synchronous machines at the same dimensions. The MTU design allows placement of stator coil at some distance from the rotating parts of the machine, namely, in a closed container filled with insulating liquid. This will increase capacity by means of more efficient cooling of coil, as well as to increase the output voltage of the MTU as a generator to a level of 35 kV or more. The recommendations on the certain parameters selection of the MTU stator winding are presented. The formulas for copper cost calculating on the MTU field winding and synchronous salient-pole generator are developed. In a specific example it is shown that such costs in synchronous generator exceed 2.5 times the similar ones in the MTU.

OAHG: an integrated resource for annotating human genes with multi-level ontologies.

Science.gov (United States)

Cheng, Liang; Sun, Jie; Xu, Wanying; Dong, Lixiang; Hu, Yang; Zhou, Meng

2016-10-05

OAHG, an integrated resource, aims to establish a comprehensive functional annotation resource for human protein-coding genes (PCGs), miRNAs, and lncRNAs by multi-level ontologies involving Gene Ontology (GO), Disease Ontology (DO), and Human Phenotype Ontology (HPO). Many previous studies have focused on inferring putative properties and biological functions of PCGs and non-coding RNA genes from different perspectives. During the past several decades, a few of databases have been designed to annotate the functions of PCGs, miRNAs, and lncRNAs, respectively. A part of functional descriptions in these databases were mapped to standardize terminologies, such as GO, which could be helpful to do further analysis. Despite these developments, there is no comprehensive resource recording the function of these three important types of genes. The current version of OAHG, release 1.0 (Jun 2016), integrates three ontologies involving GO, DO, and HPO, six gene functional databases and two interaction databases. Currently, OAHG contains 1,434,694 entries involving 16,929 PCGs, 637 miRNAs, 193 lncRNAs, and 24,894 terms of ontologies. During the performance evaluation, OAHG shows the consistencies with existing gene interactions and the structure of ontology. For example, terms with more similar structure could be associated with more associated genes (Pearson correlation γ 2  = 0.2428, p < 2.2e-16).

A Reference Model for Virtual Machine Launching Overhead

Energy Technology Data Exchange (ETDEWEB)

Wu, Hao; Ren, Shangping; Garzoglio, Gabriele; Timm, Steven; Bernabeu, Gerard; Chadwick, Keith; Noh, Seo-Young

2016-07-01

Cloud bursting is one of the key research topics in the cloud computing communities. A well designed cloud bursting module enables private clouds to automatically launch virtual machines (VMs) to public clouds when more resources are needed. One of the main challenges in developing a cloud bursting module is to decide when and where to launch a VM so that all resources are most effectively and efficiently utilized and the system performance is optimized. However, based on system operational data obtained from FermiCloud, a private cloud developed by the Fermi National Accelerator Laboratory for scientific workflows, the VM launching overhead is not a constant. It varies with physical resource utilization, such as CPU and I/O device utilizations, at the time when a VM is launched. Hence, to make judicious decisions as to when and where a VM should be launched, a VM launching overhead reference model is needed. In this paper, we first develop a VM launching overhead reference model based on operational data we have obtained on FermiCloud. Second, we apply the developed reference model on FermiCloud and compare calculated VM launching overhead values based on the model with measured overhead values on FermiCloud. Our empirical results on FermiCloud indicate that the developed reference model is accurate. We believe, with the guidance of the developed reference model, efficient resource allocation algorithms can be developed for cloud bursting process to minimize the operational cost and resource waste.

Closed Form Solution of Synchronous Machine Short Circuit Transients

Directory of Open Access Journals (Sweden)

Gibson H.M. Sianipar

2010-05-01

Full Text Available This paper presents the closed form solution of the synchronous machine transients undergoing short circuit. That analytic formulation has been derived based on linearity and balanced conditions of the fault. Even though restrictive, the proposed method will serve somehow or other as a new resource for EMTP productivity. Indisputably superior, the closed-form formulation has some features inimitable by discretization such as continuity, accuracy and absolute numerical stability. Moreover, it enables us to calculate states at one specific instant independent of previous states or a snapshot, which any discretization methods cannot do.

Foods Sold in School Vending Machines are Associated with Overall Student Dietary Intake

Science.gov (United States)

Rovner, Alisha J.; Nansel, Tonja R.; Wang, Jing; Iannotti, Ronald J.

2010-01-01

Purpose To examine the association between foods sold in school vending machines and students’ dietary behaviors. Methods The 2005-2006 US Health Behavior in School Aged Children (HBSC) survey was administered to 6th to 10th graders and school administrators. Students’ dietary intake was estimated with a brief food frequency measure. Administrators completed questions about foods sold in vending machines. For each food intake behavior, a multilevel regression analysis modeled students (level 1) nested within schools (level 2), with the corresponding food sold in vending machines as the main predictor. Control variables included gender, grade, family affluence and school poverty. Analyses were conducted separately for 6th to 8th and 9th to 10th grades. Results Eighty-three percent of schools (152 schools, 5,930 students) had vending machines which primarily sold foods of minimal nutritional values (soft drinks, chips and sweets). In younger grades, availability of fruits/vegetables and chocolate/sweets was positively related to the corresponding food intake, with vending machine content and school poverty explaining 70.6% of between-school variation in fruit/vegetable consumption, and 71.7% in sweets consumption. In older grades, there was no significant effect of foods available in vending machines on reported consumption of those foods. Conclusions Vending machines are widely available in US public schools. In younger grades, school vending machines were related to students’ diets positively or negatively, depending on what was sold in them. Schools are in a powerful position to influence children’s diets; therefore attention to foods sold in them is necessary in order to try to improve children’s diets. PMID:21185519

Micro-machined resonator oscillator

Science.gov (United States)

Koehler, Dale R.; Sniegowski, Jeffry J.; Bivens, Hugh M.; Wessendorf, Kurt O.

1994-01-01

A micro-miniature resonator-oscillator is disclosed. Due to the miniaturization of the resonator-oscillator, oscillation frequencies of one MHz and higher are utilized. A thickness-mode quartz resonator housed in a micro-machined silicon package and operated as a "telemetered sensor beacon" that is, a digital, self-powered, remote, parameter measuring-transmitter in the FM-band. The resonator design uses trapped energy principles and temperature dependence methodology through crystal orientation control, with operation in the 20-100 MHz range. High volume batch-processing manufacturing is utilized, with package and resonator assembly at the wafer level. Unique design features include squeeze-film damping for robust vibration and shock performance, capacitive coupling through micro-machined diaphragms allowing resonator excitation at the package exterior, circuit integration and extremely small (0.1 in. square) dimensioning. A family of micro-miniature sensor beacons is also disclosed with widespread applications as bio-medical sensors, vehicle status monitors and high-volume animal identification and health sensors. The sensor family allows measurement of temperatures, chemicals, acceleration and pressure. A microphone and clock realization is also available.

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

Directory of Open Access Journals (Sweden)

Cai Wingfield

2017-09-01

Full Text Available There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG, generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.

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.

Gear failure of a PHWR refuelling machine

International Nuclear Information System (INIS)

Iorio, A.F.; Crespi, J.C.

1986-01-01

After ten year service in Atucha Nuclear Station a gear belonging to a pressurized heavy water reactor refuelling machine, failed. The gear box was used to transmit motion to the inlet-outlet heavy-water valve of that machine. Visual examination of the gear device revealed an absence of lubricant and several gear teeth were broken off at the root. The gear motion was transmitted from a speed-reducing device with controlled adjustable times in order to produce a right fitness of the valve closure. The main cause of gear failure was due to misalignment produced during assembly or in-service operation. It is suggested to control periodically the level of oil lubricant. (orig./IHOE) [de

Mechanical design of machine components

CERN Document Server

Ugural, Ansel C

2015-01-01

Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

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...

Mankind, machines and people

Energy Technology Data Exchange (ETDEWEB)

Hugli, A

1984-01-01

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

Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning

International Nuclear Information System (INIS)

Veronesi, F; Grassi, S

2016-01-01

Wind resource assessment is a key aspect of wind farm planning since it allows to estimate the long term electricity production. Moreover, wind speed time-series at high resolution are helpful to estimate the temporal changes of the electricity generation and indispensable to design stand-alone systems, which are affected by the mismatch of supply and demand. In this work, we present a new generalized statistical methodology to generate the spatial distribution of wind speed time-series, using Switzerland as a case study. This research is based upon a machine learning model and demonstrates that statistical wind resource assessment can successfully be used for estimating wind speed time-series. In fact, this method is able to obtain reliable wind speed estimates and propagate all the sources of uncertainty (from the measurements to the mapping process) in an efficient way, i.e. minimizing computational time and load. This allows not only an accurate estimation, but the creation of precise confidence intervals to map the stochasticity of the wind resource for a particular site. The validation shows that machine learning can minimize the bias of the wind speed hourly estimates. Moreover, for each mapped location this method delivers not only the mean wind speed, but also its confidence interval, which are crucial data for planners. (paper)

Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning

Science.gov (United States)

Veronesi, F.; Grassi, S.

2016-09-01

Wind resource assessment is a key aspect of wind farm planning since it allows to estimate the long term electricity production. Moreover, wind speed time-series at high resolution are helpful to estimate the temporal changes of the electricity generation and indispensable to design stand-alone systems, which are affected by the mismatch of supply and demand. In this work, we present a new generalized statistical methodology to generate the spatial distribution of wind speed time-series, using Switzerland as a case study. This research is based upon a machine learning model and demonstrates that statistical wind resource assessment can successfully be used for estimating wind speed time-series. In fact, this method is able to obtain reliable wind speed estimates and propagate all the sources of uncertainty (from the measurements to the mapping process) in an efficient way, i.e. minimizing computational time and load. This allows not only an accurate estimation, but the creation of precise confidence intervals to map the stochasticity of the wind resource for a particular site. The validation shows that machine learning can minimize the bias of the wind speed hourly estimates. Moreover, for each mapped location this method delivers not only the mean wind speed, but also its confidence interval, which are crucial data for planners.

A Conjunction Method of Wavelet Transform-Particle Swarm Optimization-Support Vector Machine for Streamflow Forecasting

Directory of Open Access Journals (Sweden)

Fanping Zhang

2014-01-01

Full Text Available Streamflow forecasting has an important role in water resource management and reservoir operation. Support vector machine (SVM is an appropriate and suitable method for streamflow prediction due to its best versatility, robustness, and effectiveness. In this study, a wavelet transform particle swarm optimization support vector machine (WT-PSO-SVM model is proposed and applied for streamflow time series prediction. Firstly, the streamflow time series were decomposed into various details (Ds and an approximation (A3 at three resolution levels (21-22-23 using Daubechies (db3 discrete wavelet. Correlation coefficients between each D subtime series and original monthly streamflow time series are calculated. Ds components with high correlation coefficients (D3 are added to the approximation (A3 as the input values of the SVM model. Secondly, the PSO is employed to select the optimal parameters, C, ε, and σ, of the SVM model. Finally, the WT-PSO-SVM models are trained and tested by the monthly streamflow time series of Tangnaihai Station located in Yellow River upper stream from January 1956 to December 2008. The test results indicate that the WT-PSO-SVM approach provide a superior alternative to the single SVM model for forecasting monthly streamflow in situations without formulating models for internal structure of the watershed.

A Concrete Framework for Environment Machines

DEFF Research Database (Denmark)

Biernacka, Malgorzata; Danvy, Olivier

2007-01-01

calculus with explicit substitutions), we extend it minimally so that it can also express one-step reduction strategies, and we methodically derive a series of environment machines from the specification of two one-step reduction strategies for the lambda-calculus: normal order and applicative order....... The derivation extends Danvy and Nielsen’s refocusing-based construction of abstract machines with two new steps: one for coalescing two successive transitions into one, and the other for unfolding a closure into a term and an environment in the resulting abstract machine. The resulting environment machines...... include both the Krivine machine and the original version of Krivine’s machine, Felleisen et al.’s CEK machine, and Leroy’s Zinc abstract machine....

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